Author: a16z Podcast

  • a16z Podcast: Fintech for Startups and Incumbents

    AI transcript
    0:00:02 – Hi, this is Frank Chen.
    0:00:04 Welcome to the A16Z podcast.
    0:00:07 Today’s episode is titled Three Ways Startups Are Coming
    0:00:11 for Established Fintech Companies and What to Do About It.
    0:00:13 It originated as a YouTube video.
    0:00:18 You can watch all of our videos at youtube.com/a16zvideos.
    0:00:19 Hope you enjoy.
    0:00:22 – Well, hi, welcome to the A16Z YouTube channel.
    0:00:24 I’m Frank Chen, and today I am here
    0:00:27 with one of our general partners, Alex Rampel.
    0:00:29 I’m super excited that Alex is here.
    0:00:32 So first fact, we both have sons named Cameron.
    0:00:33 – We do.
    0:00:34 – So affinity there.
    0:00:36 And then two, one of the things
    0:00:38 that I really appreciate about Alex,
    0:00:39 and you can sort of see this
    0:00:41 from his young chess playing days,
    0:00:46 is he understands fintech and incentives
    0:00:48 and pricing backwards and forwards.
    0:00:52 And so fintech has this hidden infrastructure
    0:00:54 on how do credit card transactions work?
    0:00:56 How do bonds get sold?
    0:00:58 How are insurance policies priced?
    0:01:02 And there’s deep economic theory behind all of these
    0:01:04 and Alex understands them all.
    0:01:05 So you’re gonna have a fun time
    0:01:08 as Alex takes you through his encyclopedia of knowledge
    0:01:10 of how these things are put together.
    0:01:12 And so excited to have you.
    0:01:13 – Yeah, it’s great to be here.
    0:01:15 – So what I wanted to talk to you about is
    0:01:19 I’m gonna pretend to be in the seat of a,
    0:01:21 let’s call it an incumbent fintech company, right?
    0:01:26 So I’m a product manager and visa or a Geico.
    0:01:30 And I am looking in my rear view mirror
    0:01:33 and there are startups in the rear view mirror.
    0:01:35 And I’m very nervous that the startup
    0:01:39 in the rear view mirror, exactly as the mirror says,
    0:01:41 objects in mirror maybe closer than they appear,
    0:01:44 is like, wow, they are catching up to me faster
    0:01:45 than I really want.
    0:01:49 And so I wanna understand like, what are startups doing?
    0:01:53 Like how would they mount an attack on me, the incumbent?
    0:01:56 And we’re gonna talk about sort of wedges they can use.
    0:01:58 And then that’s sort of the first half,
    0:02:00 like how are they coming after me?
    0:02:02 And then the second half, let’s talk about like,
    0:02:03 and what should I do about it?
    0:02:05 So that’s sort of the premise for our,
    0:02:09 so why don’t we start with the attacks?
    0:02:11 Like how would a startup come for me?
    0:02:14 And one way they come for me is they come
    0:02:16 after my best customers.
    0:02:19 – Well, so this is the interesting thing
    0:02:21 about financial services in general,
    0:02:25 because there’s a sharp television hanging on the wall.
    0:02:27 And Sharp knows that they make more money
    0:02:30 every time they sell an incremental television.
    0:02:33 So more customers equals more money, cause, effect.
    0:02:35 And the interesting thing is that for many kinds
    0:02:37 of financial services, that is not true.
    0:02:39 Because what you’re really trying to do
    0:02:41 is assemble a risk pool.
    0:02:43 And the best example of this is insurance.
    0:02:45 So what is car insurance?
    0:02:48 Car insurance has good drivers, okay drivers,
    0:02:50 and bad drivers.
    0:02:53 And effectively, your good drivers and your okay drivers
    0:02:56 are paying you every month to subsidize the bad drivers.
    0:02:57 So the same thing goes for health insurance.
    0:02:58 You have people that are always sick,
    0:03:00 you have people that are always healthy.
    0:03:02 And if you are an insurance company
    0:03:05 that only provided insurance for very, very sick people,
    0:03:07 or if you’re a car insurance company
    0:03:10 that only ensures people that get into accidents every day,
    0:03:13 there’s no economic model to sustain that.
    0:03:16 You actually have to accumulate the good customers
    0:03:18 and use them to pay for the bad customers.
    0:03:20 And the interesting thing about this is that
    0:03:22 from the perspective of the good customer,
    0:03:24 it’s not fair.
    0:03:26 And I’m not talking morally or philosophically,
    0:03:30 but just from a capitalist or economic viewpoint,
    0:03:32 it’s like, okay, I want life insurance
    0:03:35 and I eat five donuts a day.
    0:03:35 I just had a donut today.
    0:03:36 I don’t eat five a day.
    0:03:40 But I have one donut every Friday as you can testify.
    0:03:43 And then I have a friend who goes to the gym five times a day,
    0:03:45 never eats a donut.
    0:03:47 That guy’s probably gonna live longer than me.
    0:03:50 Hopefully not, but probabilistically,
    0:03:53 he’s probably going to have a better time than I am
    0:03:54 in terms of life expectancy.
    0:03:57 So why is it that we both pay the same rate?
    0:04:00 And that just seems unfair to him.
    0:04:03 It seems great to me because he’s subsidizing me.
    0:04:05 – Yep, Jim Guy, subsidizing donut guy.
    0:04:06 – Exactly, exactly.
    0:04:08 And that seems unfair.
    0:04:11 And then the startups can sometimes exploit
    0:04:13 that psychological unfairness,
    0:04:15 like that feeling of unfairness.
    0:04:16 So, and it kind of does two things
    0:04:19 because from the big company perspective,
    0:04:20 if you were to take away,
    0:04:22 think of it as a normal distribution.
    0:04:24 So most people are in the middle
    0:04:26 and they’re just gonna live whatever
    0:04:30 to the average of 79.6 years or whatever it is right now.
    0:04:31 Some people are gonna live forever.
    0:04:34 They’re the ones that have the olive oil go to the gym
    0:04:36 and do whatever it is that they do
    0:04:38 that makes them live a long time, great genes.
    0:04:40 And then some people are gonna die early.
    0:04:43 And from the perspective of the startup,
    0:04:44 if you can get all of the people
    0:04:47 that are going to live much, much longer,
    0:04:49 you’re going to be more profitable.
    0:04:50 The same thing for car insurance.
    0:04:52 If you can get all the people on the good end
    0:04:55 of that distribution curve, you’re going to make money.
    0:04:57 And then the nice thing is that
    0:04:59 if you’re starting a brand new company and saying,
    0:05:01 “Hey, I give you a loan if you can’t get a loan.
    0:05:02 “Who’s gonna sign up for that?
    0:05:04 “People who might be bad.”
    0:05:05 If I say, “I’m gonna give you insurance
    0:05:07 “if you can’t get insurance.
    0:05:08 “Who’s gonna sign up for that?
    0:05:10 “The people that are eating all the donuts.”
    0:05:11 And that might not be very good.
    0:05:15 So it actually has this nice kind of symbiosis
    0:05:17 between if you do it correctly,
    0:05:19 you get positive selection bias
    0:05:22 and that you establish a new criteria.
    0:05:24 Part of that new criteria is based on data,
    0:05:26 but part of it is based on psychology.
    0:05:28 The psychology is I’m treated unfairly.
    0:05:30 I want to be treated more fairly.
    0:05:32 That yields a lower price for people
    0:05:35 for a pretty demand elastic product.
    0:05:37 So I say, “I can get life insurance at half the rate
    0:05:38 “because I’m going to the gym.
    0:05:39 “That sounds great.
    0:05:40 “That sounds fair.”
    0:05:41 But to answer your question,
    0:05:44 what the incumbent might be left with
    0:05:47 is not half of the number of customers.
    0:05:48 Like that could be the case.
    0:05:50 It could be half the number of customers,
    0:05:51 but it could be half the customers
    0:05:54 and all of them are entirely unprofitable.
    0:05:55 – Right, they took all the profits.
    0:05:57 They didn’t have to take all your customers.
    0:05:58 They just had to take the good ones.
    0:06:00 – Right, so actually, if you just take,
    0:06:03 and the funny thing is that because it’s not like
    0:06:05 I want to get, “Oh, Geico has X million customers.
    0:06:07 “I want X plus one million customers.”
    0:06:08 You actually might want one tenth
    0:06:10 as many customers as Geico.
    0:06:12 Because if you can just get the good ones,
    0:06:15 I mean, what if you give people a 50% discount,
    0:06:17 not a 15% discount, like Geico always advertises about,
    0:06:20 but a 50% discount on their car insurance,
    0:06:23 and these are the absolute best drivers in the country,
    0:06:26 how many claims do you have to pay out on the best drivers?
    0:06:30 You might have to pay out nothing, literally nothing.
    0:06:31 And if you have to pay out nothing,
    0:06:33 and there are all these mandatory loss ratios
    0:06:34 for different insurance industries,
    0:06:35 so I don’t want to get into that.
    0:06:39 But imagine that unregulated, you can pay out nothing.
    0:06:42 Consumers feel like they’re treated very fairly.
    0:06:44 They’re rewarded for better behavior.
    0:06:48 This begets positive selection and not adverse selection,
    0:06:51 then you’re going to have the most profitable lending company
    0:06:53 or insurance company in the world,
    0:06:55 because it really is a unique industry
    0:06:57 where more customers is actually worse
    0:07:00 than less but more profitable customers
    0:07:03 because each incremental customer is like a coin flip
    0:07:04 of profit or loss.
    0:07:07 Might generate profit, might generate loss.
    0:07:09 And that’s not true for the vast majority of industries.
    0:07:11 Like Ford never sells a car saying,
    0:07:13 “Maybe we’ll lose money on this customer.”
    0:07:14 – Right, right.
    0:07:17 They just like, “I need everybody to buy a Ford F-150.”
    0:07:20 And if you don’t buy an F-150, I need you to buy.
    0:07:22 There’s other thing that said, the expedition or whatever.
    0:07:24 – They might lose money on the marginal customer
    0:07:26 until they hit their fixed costs.
    0:07:28 But they’re never going to have a coin flip
    0:07:29 of when they sell the car.
    0:07:31 Hmm, maybe we shouldn’t have sold that car,
    0:07:33 but that’s what every insurance company has
    0:07:34 when they underwrite a policy.
    0:07:37 And that’s what every bank has when they underwrite a loan.
    0:07:39 – Yeah, so auto insurance companies need to find people
    0:07:41 like me, I have this old Prius, right?
    0:07:45 First, it’s hugely reliable car.
    0:07:47 And then I drive like a grandma
    0:07:49 because I’m optimizing for fuel efficiency.
    0:07:52 So I rarely go above 65.
    0:07:54 And so really safe, I’ve never filed a claim.
    0:07:57 They need more customers like me.
    0:07:58 And that’s what drives the profits.
    0:07:59 – Yes.
    0:08:00 – ‘Cause there’s no payouts.
    0:08:01 – Well, not only does it drive the profits,
    0:08:05 it actually subsidizes the losses.
    0:08:08 Because there are a lot of people who are the inverse of you
    0:08:09 and you’re paying for those people
    0:08:11 and the transfer mechanism is through GEICO.
    0:08:12 – Yeah.
    0:08:16 I saw an ad in my Facebook feed recently
    0:08:17 for HealthIQ and I think they’re doing something
    0:08:18 like this too, right?
    0:08:20 So the, I think the proposition was,
    0:08:22 hey, can you run on my own in less than nine minutes?
    0:08:24 Can you bench press your own weight or something like that?
    0:08:27 There’s all these like, oh, healthy people.
    0:08:29 And is that the mechanism they’re exploiting?
    0:08:30 – It’s exactly that.
    0:08:32 I would say the first company to probably do this
    0:08:36 on a widespread basis in FinTech land was SoFi.
    0:08:38 And SoFi said, hey, you’re really smart.
    0:08:39 They actually coined this term.
    0:08:40 They called it the Henry.
    0:08:42 High earning, not rich yet.
    0:08:44 Because if you look at how student loans work,
    0:08:46 it’s like everybody gets the same price
    0:08:48 on their student loan, right?
    0:08:49 It doesn’t matter what your major is.
    0:08:54 It doesn’t matter what your employment prospects think.
    0:08:56 What your employment prospects are,
    0:08:57 everybody gets the same rate.
    0:09:00 You get this rate, you get this rate, you get this rate.
    0:09:01 Because a lot of it is effectively underwritten
    0:09:02 by the US government.
    0:09:04 And that’s not, so think about it again
    0:09:07 from the twin pillars of psychology.
    0:09:09 Where, I mean, psychology of the borrower.
    0:09:12 Like how come I’m paying the same rate
    0:09:14 as that person who’s going to default?
    0:09:15 That’s just not fair.
    0:09:17 I’m never going to default.
    0:09:20 In fact, I’m gonna pay back my student loans early.
    0:09:22 So that helped.
    0:09:24 And then again, positive selection
    0:09:26 versus adverse selection because,
    0:09:29 and actually refinance has this concept in general.
    0:09:30 Because I would say, if you’re planning
    0:09:33 on declaring bankruptcy, or if you’re saying,
    0:09:36 I’m going to, I’m gonna join Occupy Wall Street
    0:09:38 and never pay back my loans and I hate capitalism,
    0:09:40 why would you go refinance?
    0:09:41 It just doesn’t make sense.
    0:09:42 – Right.
    0:09:44 – Because you’re just gonna default.
    0:09:44 – Right.
    0:09:46 – So if you raise your hand, and actually it’s interesting,
    0:09:48 even on the other side, there are a lot of companies
    0:09:50 in what I would call the debt settlement space.
    0:09:52 And this is something that most people don’t know about.
    0:09:55 But if you listen to like some interesting talk radio,
    0:09:58 you’ll hear all these ads for debt settlement.
    0:09:59 And what is debt settlement?
    0:10:01 It’s saying, hey, do you have too much debt?
    0:10:05 If you call us, we will negotiate on your behalf
    0:10:08 and pay off your debts, and then you just owe us.
    0:10:10 And you kind of need this intermediary layer
    0:10:13 because imagine that you owe $10,000 to Capital One
    0:10:15 and you can’t pay it back.
    0:10:16 You call it Capital One.
    0:10:18 It says, press one for your balance.
    0:10:20 Press two to get a new card mail to you.
    0:10:22 Press three if you don’t want to pay us the full amount
    0:10:23 and want to pay us less.
    0:10:26 Everybody’s gonna push through, right?
    0:10:27 – This is why they don’t offer that option.
    0:10:29 – They don’t offer that option, nor will they ever.
    0:10:34 However, on talk radio, and this is very big in the Midwest,
    0:10:37 like you’ll hear, you know, Freedom Financial.
    0:10:39 Go call Freedom Financial and we will settle
    0:10:40 your debts for you.
    0:10:42 So they call Capital One and say, look,
    0:10:43 Alex can’t pay you back.
    0:10:45 We’ll pay you $2,000 right now,
    0:10:47 and then you’re gonna get rid of the loan.
    0:10:48 And you’re like, well, we’re not happy
    0:10:50 taking 20 cents on the dollar,
    0:10:52 but it’s better than zero cents on the dollar, fine.
    0:10:53 We’ll take it.
    0:10:57 And then you owe Freedom Financial the 20 cents.
    0:11:00 But why do they feel comfortable underwriting that?
    0:11:03 Because you rose your hand, you said,
    0:11:05 I want to get out of debt.
    0:11:08 And that’s positive selection bias right there.
    0:11:10 Because people who are just deadbeats,
    0:11:12 because behind every credit score,
    0:11:13 if you think about how that works,
    0:11:15 it’s willingness and ability to repay.
    0:11:18 And the psychological trait of the willingness
    0:11:20 is in many cases as important
    0:11:22 as the financial constraint of the ability.
    0:11:25 Because if I owe a million dollars to somebody,
    0:11:28 and I only make $100 a year,
    0:11:29 it doesn’t matter how honest I am,
    0:11:31 I can never pay that back.
    0:11:33 It doesn’t matter how long I’m gonna live 10,000 years
    0:11:34 and I guess I could pay it back.
    0:11:36 But otherwise I can’t pay that back.
    0:11:38 But the willingness to repay is interesting.
    0:11:40 And that’s very important.
    0:11:42 And that’s again, this kind of psychological trait
    0:11:45 that’s captured in this idea of positive selection.
    0:11:46 So what does SoFi do?
    0:11:48 They kind of again hit this twin pillar,
    0:11:52 which is I want to only get the good customers,
    0:11:55 I’m going to reprice them and steal them
    0:11:58 from the giant pool that again, normal distribution,
    0:12:00 these are the losers, these are the whatever’s,
    0:12:03 and these are the people that you have no risk on whatsoever.
    0:12:06 Let’s steal all of these people over here.
    0:12:07 And it makes them feel good.
    0:12:09 It’s a better marketing message.
    0:12:11 At least it’s differentiated.
    0:12:13 How do you compete with everybody?
    0:12:14 It’s like, hey, we’re just like Chase,
    0:12:17 but smaller and a startup and not profitable
    0:12:20 and you probably shouldn’t trust us, bad marketing message.
    0:12:22 Good marketing message is you’re getting ripped off.
    0:12:26 We’re going to price you fairly, come to us.
    0:12:29 So if I did this for lending.
    0:12:30 – And what a health IQ do?
    0:12:32 – So a health IQ did this for health,
    0:12:33 really for life insurance.
    0:12:35 So they started off with a health quiz
    0:12:38 because I mean, it seems almost self-evident
    0:12:40 that healthy people are health,
    0:12:42 I mean, it’s a tautology,
    0:12:44 like healthy people are healthier than not healthy people,
    0:12:47 but can you actually prove this
    0:12:48 from a life expectancy perspective?
    0:12:50 So they started off with just recording data
    0:12:53 and then building a mortality table.
    0:12:56 And it turned out that what I would assume
    0:12:59 is a prima facie case turned out to actually be correct,
    0:13:01 which is these healthier people do live longer
    0:13:03 than not healthy people.
    0:13:06 And then they turn that into both a positive selection
    0:13:07 advertising campaign,
    0:13:09 which differentiated them from a brand perspective,
    0:13:12 but also left them more profitable.
    0:13:13 So what they do is they say, yeah,
    0:13:16 can you run a nine or an eight minute mile?
    0:13:19 Can you do these things to prove
    0:13:21 that you’re better than everybody else?
    0:13:22 And why is that important?
    0:13:24 Well, from their own balance sheet
    0:13:25 or profitability perspective,
    0:13:27 they want to get these good customers
    0:13:30 versus a brand new life insurance company
    0:13:32 that said, hey, life insurance takes too long to get,
    0:13:34 it’s a big pain and it’s expensive,
    0:13:36 we’ll underwrite you on the spot in one minute,
    0:13:39 no blood test, that’s gonna be adverse selection.
    0:13:42 That’s like, ooh, I think I’m gonna die soon.
    0:13:44 I want to get, everybody rejected me for life insurance,
    0:13:45 I’m going to that company.
    0:13:48 As opposed to here, they’re only getting the customers
    0:13:50 that kind of hit,
    0:13:52 that think they’re gonna hit the underwriting standard,
    0:13:53 which is great.
    0:13:55 They think it’s fair.
    0:13:57 So it’s a differentiator from a brand perspective.
    0:14:00 And then it turns out that, again,
    0:14:02 each marginal customer in insurance
    0:14:03 is kind of a coin flip.
    0:14:05 They’re getting a weighted coin
    0:14:06 because they’re only getting people
    0:14:09 on the far right side of this normal distribution.
    0:14:14 – So wedge number one is exploit psychology, right?
    0:14:16 Positive selection rather than negative selection
    0:14:18 and what you’ll end up with
    0:14:20 because of this sort of unique dynamic
    0:14:21 of the FinTech industry
    0:14:24 is you’ll end up with the most profitable customers.
    0:14:25 What’s wedge number two?
    0:14:27 We’re gonna talk about sort of new data sources
    0:14:29 and what startups can do
    0:14:31 to sort of price their products smarter than incumbents.
    0:14:36 – Right, so imagine that you have a group of 100 people
    0:14:38 and of the 100 people,
    0:14:40 half of them are not going to pay you back.
    0:14:43 So think of this as the old combinatorics problem
    0:14:44 of bins and balls.
    0:14:46 So you’ve got this giant ball pit,
    0:14:48 you scoop up 100 balls in your bin
    0:14:50 and half of them are going to be bad,
    0:14:53 half of them are going to be good.
    0:14:56 So what’s a fair rate of interest if you’re a lender,
    0:14:59 that you have to charge this whole bin
    0:15:01 if half of them are going to default
    0:15:03 and you assume that you can’t lose money?
    0:15:05 The answer is going to be 100%.
    0:15:08 – Oh right, because half of them you have to make up
    0:15:09 for all the deadbeats.
    0:15:10 – So half of them, you lose all of your money,
    0:15:12 half of them you double your monies,
    0:15:13 you’re back to square one.
    0:15:14 – Now you’re even.
    0:15:15 – Now you’re even.
    0:15:18 So the problem is that that’s not good
    0:15:19 because well in the United States
    0:15:21 you can’t charge 100% interest.
    0:15:24 It’s called usury, there are other parts of the world,
    0:15:28 again, illegal, step one, Europe, so that’s a problem.
    0:15:32 But what if you can use different data sources to,
    0:15:36 again, it’s not positive versus adverse selection
    0:15:38 as in some of the insurance companies,
    0:15:41 but it’s saying can I collect more forms of data
    0:15:43 so that instead of saying the only way
    0:15:45 that I can make my operation work
    0:15:46 is to charge an interest rate
    0:15:49 which actually turns out to be illegal,
    0:15:51 can I come up with more data sources
    0:15:53 that effectively, even though discrimination
    0:15:55 sounds like a terrible word,
    0:15:57 and it’s normally used in that construct,
    0:15:59 if you discriminate against criminals that’s fine.
    0:16:01 I mean some of the people that try to take advantage
    0:16:04 of lenders are actual organized crime.
    0:16:05 You don’t want them in your bin,
    0:16:06 you want to throw them out.
    0:16:09 How do you take more data sources
    0:16:11 and actually start measuring this?
    0:16:12 And the interesting thing here,
    0:16:13 and it’s somewhat unfortunate,
    0:16:17 but you have a giant market failure happening
    0:16:18 in many different regions of the world
    0:16:19 because in the United States,
    0:16:21 like the top interest rate that you can charge,
    0:16:22 it’s regulated on a state by state basis,
    0:16:25 but Utah has a 36% usury cap,
    0:16:28 so a lot of people export that cap.
    0:16:30 That’s a lot less than 100% that I was mentioning.
    0:16:32 And there are lots of ways of kind of gaming that system
    0:16:34 and you charge late fees and you charge this fee,
    0:16:36 so it actually might end up looking more like 100
    0:16:39 or 200%, but so you can charge more than 36%.
    0:16:42 And then you actually can’t use certain types of data
    0:16:44 if they are prone to having an adverse impact.
    0:16:46 So if you think about how machine learning works,
    0:16:47 I always kind of describe it
    0:16:50 somewhat oversimplistically as linear algebra,
    0:16:53 where I have, here’s every user that I’ve ever seen,
    0:16:55 here’s every attribute that I’ve ever measured,
    0:16:57 and what I’m looking for is like strange correlations
    0:16:59 that I can’t even explain.
    0:17:01 So I’m gonna ask you,
    0:17:02 I’m not even gonna ask you a lot of these things,
    0:17:04 it’s like, how long did you fill out this field for
    0:17:06 on my loan application?
    0:17:08 Did you enter all caps or not all caps?
    0:17:09 Just all of these different things.
    0:17:11 – Did you take the slider on how much do you want
    0:17:12 and jam it all the way to the right?
    0:17:13 – Right, all of these things.
    0:17:16 – I can ask you, do you have a pet or not?
    0:17:16 That might be interesting.
    0:17:18 I don’t know if that’s a leading indicator
    0:17:20 of default or not, but I wanna collect
    0:17:21 all these different variables,
    0:17:22 and then at the end of the day,
    0:17:24 I’m going to see default or not default.
    0:17:26 That’s the output, and then I’m going to see
    0:17:27 what’s correlated with that.
    0:17:29 And it’s a little bit of this, it’s a little bit of that,
    0:17:31 I can’t explain it, but the computer can’t.
    0:17:33 Now the problem is that in the United States,
    0:17:35 you actually can’t do this,
    0:17:37 because it might have an adverse impact.
    0:17:39 And what does an adverse impact mean?
    0:17:42 There actually was outright and terrible discrimination
    0:17:44 in lending in the United States,
    0:17:46 where there’s unfortunately terrible discrimination
    0:17:47 in many things in the United States,
    0:17:50 but lending was one of several or one of many.
    0:17:54 So imagine that I said, are you married or not?
    0:17:57 Oh, you’re not married, I’m not gonna make you alone.
    0:17:59 Well, that’s illegal now.
    0:18:00 Are you this race?
    0:18:01 Oh, I’m not going to make you alone.
    0:18:02 Well, that’s illegal now.
    0:18:03 So what did people do to get around,
    0:18:06 the people that were actual racists,
    0:18:08 or actual, like maybe they weren’t racist
    0:18:09 or discriminatory at heart,
    0:18:11 but they were picking up on cues.
    0:18:13 They’d say, oh, what part of town do you live in?
    0:18:15 Well, you live on that part of town.
    0:18:19 Well, that’s like 100% correlated with this race,
    0:18:20 or this gender, or this, that.
    0:18:22 I’m not going to make you alone.
    0:18:23 So the law was strengthened,
    0:18:26 so there’s a law called Fair Lending in the United States.
    0:18:27 And then one of the components of it
    0:18:30 is this idea of called adverse impact.
    0:18:31 And it’s different than adverse selection.
    0:18:34 It’s saying, I don’t care what you said you did
    0:18:38 for why you rejected Frank for a loan.
    0:18:41 If it turns out that everybody in your reject pile
    0:18:45 has a disproportionate gender ratio, race ratio,
    0:18:46 something like that,
    0:18:49 I’m going to assume that you’re underwriting standards
    0:18:50 or having an adverse impact.
    0:18:53 So you as a bank couldn’t say,
    0:18:55 hey, look, I asked him if he had cats.
    0:18:58 And I’m using that to make the loan decision.
    0:18:59 If it turned out that having cats
    0:19:04 was correlated with being in particular race,
    0:19:09 they couldn’t use the cat’s answer to deny you a loan.
    0:19:10 – Correct, because that was,
    0:19:12 and in all fairness to the law,
    0:19:15 this is what people use with your geography.
    0:19:16 What zip code do you live in?
    0:19:18 Oh, you live in that zip code?
    0:19:21 100%, you were a member of this particular race,
    0:19:23 and the intent all along was to discriminate
    0:19:25 against people of that particular race.
    0:19:28 But now instead of using loan officers that use,
    0:19:30 God knows what to decide.
    0:19:31 Do I want to make you the loan or not?
    0:19:33 You’re using a computer, you can look at the code.
    0:19:35 So I think there is a lot of,
    0:19:38 there are some anachronistic laws
    0:19:39 that have to catch up here,
    0:19:42 but let’s take an area outside of the US
    0:19:44 to answer your question,
    0:19:47 where perhaps you don’t have interest rate caps,
    0:19:49 because the thing that a lot of people say,
    0:19:51 oh, 200% interest is terrible.
    0:19:55 500%, that sounds awful, you should go to jail for that.
    0:19:56 But what does APR mean?
    0:19:59 APR stands for annual percentage rate.
    0:20:01 And what if I’m giving you a four day loan?
    0:20:04 So I say, okay, I’m gonna loan you $9 right now.
    0:20:07 You don’t look very trustworthy.
    0:20:09 I want you to pay me back $10 on Monday.
    0:20:11 – Yeah, that doesn’t sound so bad.
    0:20:13 – Yeah, it’s like, you’re gonna pay me a dollar.
    0:20:16 But what is that on an APR basis?
    0:20:19 That’s like 9,000% made that up.
    0:20:20 But it’s probably about that, right?
    0:20:23 Because it’s 10% every four days, or every three days,
    0:20:25 10% every three days, and that cumulates.
    0:20:28 Like that’s a lot of money or a lot of interest
    0:20:31 on an APR basis, but it’s the wrong metric
    0:20:33 because effectively it’s like trying to figure out
    0:20:37 what your marathon time is based on your 100 meter dash.
    0:20:40 Like the winning marathon time would be an hour.
    0:20:41 And that’s not true.
    0:20:42 We know that nobody can run on that,
    0:20:44 two hour marathon right now.
    0:20:45 Yeah, so maybe Angela can.
    0:20:46 – Maybe Angela.
    0:20:50 – So there’s a company that we invested in called Branch.
    0:20:52 And what they’re doing is they just collect
    0:20:54 every form of data possible.
    0:20:57 And they look for these strange correlations.
    0:21:00 And the interest rates on an APR basis might be high,
    0:21:02 but they’re really charging like a dollar.
    0:21:04 – And these are small loans, right?
    0:21:05 – Very, very small loans.
    0:21:07 So I loan you, and actually the other interesting,
    0:21:09 like one of the nice data points
    0:21:11 that they’re accumulating over time
    0:21:15 that is a really interesting idea, I think.
    0:21:16 It’s not new.
    0:21:18 In fact, it’s almost back to the future old
    0:21:19 where they loan you a dollar.
    0:21:20 If you pay it back, they loan you $2.
    0:21:22 If you pay it back, they loan you $4.
    0:21:24 If you pay it back, they loan you $10.
    0:21:26 And they ladder up your credit
    0:21:29 and they keep that information proprietary to them.
    0:21:33 Because induction turns out to be a pretty good formula
    0:21:36 for figuring out not so much the ability to repay,
    0:21:37 but the willingness to repay.
    0:21:40 You’ve established a pattern of willingness to repay,
    0:21:43 but they also look at where were you today.
    0:21:46 And again, you provide all this information
    0:21:47 in order for them to crunch this,
    0:21:49 in order for them to give you a loan
    0:21:50 at ideally a lower rate.
    0:21:51 Because the more information,
    0:21:53 because it’s kind of twin pillars, right?
    0:21:55 The less information we have,
    0:21:57 the higher the rate that we have to charge.
    0:21:58 Not because we’re evil,
    0:22:00 but because otherwise you’re gonna have a market failure.
    0:22:01 Like you have in lots of-
    0:22:02 – You have the bin ball problem, right?
    0:22:03 – Exactly. – Because you have no idea
    0:22:04 how many deadbeats.
    0:22:05 – Exactly.
    0:22:07 And if I don’t have any idea,
    0:22:08 I either have to charge a high rate
    0:22:10 or not charge anything at all.
    0:22:11 And not charge anything at all
    0:22:13 doesn’t mean like everybody gets a 0% loan.
    0:22:14 It means I don’t make any loans.
    0:22:16 And like both of those are bad outcomes.
    0:22:19 The better outcome is you accumulate more data
    0:22:21 and you figure out here are the good people,
    0:22:23 let me not accept the bad people.
    0:22:25 Because again, the way that the good people
    0:22:27 end up paying more money
    0:22:29 is if the company starts accepting more bad people
    0:22:32 because it goes back to what I said at the beginning,
    0:22:35 which is more customers in this unique industry
    0:22:38 often is bad if you don’t understand
    0:22:40 how to select them correctly.
    0:22:42 And for many of these new fangled lending
    0:22:43 and insurance companies,
    0:22:46 the default customer is going to be adversely selected
    0:22:47 because if you’re a new lender
    0:22:49 and you have no underwriting standards,
    0:22:53 you’re basically advertising free money never pays back.
    0:22:54 And those are the people that will be attracted to you,
    0:22:57 both the criminals and the non criminals in droves.
    0:23:01 – Yeah, so this is sort of startup attack wedge number two,
    0:23:03 which is I’m going to generate a new data source
    0:23:06 that allows me to price my product in a way
    0:23:09 or reach a customer that a traditional company
    0:23:11 would never even try or they don’t have the data source
    0:23:13 or they have the bid and ball problem.
    0:23:16 So what are the types of data that branch went to go get
    0:23:17 to try to figure out,
    0:23:19 should I give you a loan of a dollar or two?
    0:23:21 – Well, the other type of data,
    0:23:23 so branch was somewhat unique
    0:23:27 in that they said we’re going to get data from your phone.
    0:23:29 And it seems odd.
    0:23:33 He’s like most lenders in the developed world
    0:23:35 or not developed versus undeveloped,
    0:23:37 it’s really like with developed credit infrastructure.
    0:23:39 – Yeah, if there’s a credit bureau.
    0:23:41 – They look up your credit report, if it’s good,
    0:23:43 they make you a loan, if it’s bad, they don’t make you a loan.
    0:23:45 It’s actually not that hard.
    0:23:47 And there are all sorts of nuances that you can layer on top,
    0:23:49 but this is how it’s been working for a long time
    0:23:51 in the United States as an example.
    0:23:55 Whereas there, it was like, okay, where did you work today?
    0:23:57 Did it look like you worked today?
    0:23:59 So it was stuff like that
    0:24:01 and even like how many apps do you have on your phone?
    0:24:04 Like weird stuff that you would never assume
    0:24:07 actually has any kind of indication
    0:24:09 of willingness or ability to repay,
    0:24:10 but in many cases it does.
    0:24:12 Like are you gambling?
    0:24:14 Well, if you have a gambling app on your phone,
    0:24:17 you’re probably gambling, maybe that’s good.
    0:24:18 Yeah, maybe it’s bad.
    0:24:20 It’s actually not making human judgments.
    0:24:21 And it’s also not looking at any one
    0:24:24 of these unique variables as a unique variable.
    0:24:26 It’s looking at them in concert
    0:24:29 and then correlating them with these outcomes
    0:24:31 or really observing the outcomes
    0:24:33 and then linking them back to all of these different inputs.
    0:24:35 – Yeah, I remember talking to the team
    0:24:38 when I was researching my last machine learning presentation
    0:24:41 and the fascinating things that I found were
    0:24:45 if you’ve got more texts than you sent,
    0:24:46 you were more credit worthy.
    0:24:47 If you had the gambling app,
    0:24:49 you were more credit worthy rather than less,
    0:24:52 which is not kind of what you would expect.
    0:24:54 If you burned through your battery,
    0:24:56 you were more likely to default, right?
    0:24:59 So like all of these things where human alone officers
    0:25:02 would never really guess,
    0:25:03 and they probably would guess the wrong way.
    0:25:05 – Right, because many of them are counterintuitive.
    0:25:08 And then many of them are not, they’re not unilateral.
    0:25:10 Like so it’s not just, I mean, I don’t know,
    0:25:12 but it’s not just the battery thing,
    0:25:14 it’s the battery thing with this, with that, with that.
    0:25:15 – It’s the combinations.
    0:25:17 – And it’s like humans can only really observe
    0:25:20 three dimensions plus time, so I guess four,
    0:25:23 and these are 9,000 dimensional problems.
    0:25:25 So it’s just, it’s much, much more challenging
    0:25:27 for humans to really grok.
    0:25:28 – Yeah, got it.
    0:25:31 So that’s the sort of the second category of attack,
    0:25:33 which is you generate a new data source
    0:25:36 and then that allows you to price or find customers
    0:25:38 in sort of a more cost effective way.
    0:25:40 Let’s talk about the third,
    0:25:45 which is around sort of fundamentally changing behavior.
    0:25:47 So why don’t you talk about,
    0:25:49 maybe Ernie is a good example of this?
    0:25:52 – Yeah, so if you assume that humans are static,
    0:25:55 so they’re born, both of our cameras were born,
    0:25:58 and their DNA is set upon birth.
    0:25:59 Maybe it changes a little bit with some mutations
    0:26:01 from some gamma rays here and there,
    0:26:03 but it’s set upon birth,
    0:26:05 and then human behavior never changes.
    0:26:06 And that’s one way of looking at things.
    0:26:08 And then you think about adverse selection
    0:26:09 versus positive selection.
    0:26:11 Good drivers are always good drivers.
    0:26:12 Bad drivers are always bad drivers.
    0:26:14 Let’s just get the good drivers.
    0:26:16 So the other category,
    0:26:17 and it’s not to say that these other two groups
    0:26:18 don’t do this,
    0:26:20 but if I look at a company like Ernie,
    0:26:24 most payday lenders are reviled
    0:26:25 because they charge high fees,
    0:26:29 they don’t educate their borrower very well.
    0:26:31 Now it actually provides a valuable service
    0:26:33 because if I’m getting paid next Friday,
    0:26:36 but my rent is due today and I don’t have money,
    0:26:37 do I want to get evicted?
    0:26:41 No, I want to get paid right now,
    0:26:43 and the only person that does this is the payday lender,
    0:26:46 but the payday lender is competing with other payday lenders
    0:26:49 for advertising in the local newspaper or something,
    0:26:51 and if they’re able to rip me off more,
    0:26:52 not because they’re evil,
    0:26:55 but because they have to afford the advertising spot,
    0:26:56 they’re now ascended to do so.
    0:26:59 So it’s just, it’s a vicious cycle.
    0:27:00 So let’s talk about Ernan.
    0:27:02 So what Ernan does is they say,
    0:27:05 okay, we know that you’ve worked this long.
    0:27:09 So again, new data source because the phone’s in your pocket
    0:27:12 and you work at Starbucks and you’re getting paid hourly
    0:27:13 and we’ve seen the phone in your pocket
    0:27:16 or in your locker in the Starbucks office
    0:27:19 and you’re by the barista counter for eight hours.
    0:27:21 So you worked, we saw your last paycheck,
    0:27:22 hit your bank account,
    0:27:24 we know that that’s where you work,
    0:27:25 we’re not taking your word for it,
    0:27:27 we have real-time streaming information about this,
    0:27:33 and now we will give you your money whenever you want.
    0:27:35 Not money that you haven’t earned yet,
    0:27:36 but money that you have earned,
    0:27:38 but you actually haven’t gotten paid for yet.
    0:27:41 And then you can tip us, there’s no cost.
    0:27:44 If you want, you can get us– – No interest, no fee, no–
    0:27:45 – If you want to pay us nothing, that’s fine.
    0:27:47 I mean, we would appreciate if you pay us something
    0:27:49 because obviously we’re providing valuable service for you.
    0:27:52 And then you can even give tips for your friends,
    0:27:54 there’s this community that’s really emerged
    0:27:55 of people on Ernan.
    0:27:57 And actually, if you look back at different business model,
    0:28:00 but this idea of microfinance in general,
    0:28:04 so if you think about Mohammed Yunus and what he did,
    0:28:07 this idea of can you encourage people
    0:28:11 to pay back loans using social pressure.
    0:28:13 So again, not adverse selection versus positive selection,
    0:28:16 but actually trying to force everybody
    0:28:18 down positive behavior.
    0:28:20 – Let’s get the community to encourage repayment.
    0:28:24 – Right, because then saying,
    0:28:27 or let’s get the community to encourage people
    0:28:29 actually driving safely.
    0:28:33 Because there’s underwriting at the time of admission,
    0:28:36 there’s underwriting based on ongoing behavior.
    0:28:38 So like many of the car insurance companies
    0:28:41 that are brand new are saying we will re-underwrite you.
    0:28:44 Like, yeah, if you drive like Frank when you signed up,
    0:28:48 great, but now you switched into like race car driver mode
    0:28:49 and you were trying to hack us,
    0:28:52 but we’re actually monitoring your speedometer at all times.
    0:28:53 So guess what?
    0:28:54 You got a higher rate now.
    0:28:57 So that might encourage you to drive safely.
    0:29:00 If I’m Frank and I drive safely in my Prius,
    0:29:03 but then I decide and then I got a really good rate
    0:29:05 on my car insurance as a result.
    0:29:07 And now I’m like, aha, I game the system.
    0:29:10 Now I’m going to drive like a maniac.
    0:29:12 Well, the nice thing is that you can make
    0:29:14 underwriting dynamic and you can say, all right,
    0:29:17 we’re actually going to re-underwrite you every day.
    0:29:18 So we had the positive selection
    0:29:20 to try to attract the Franks.
    0:29:24 We have the continuous evaluation to try to encourage
    0:29:27 the right behavior post Frank sign up
    0:29:30 and also to stop the gamification of it’s like,
    0:29:33 I’m gonna pretend to be safe and then be like a maniac.
    0:29:35 But then how do you actually get?
    0:29:38 What if Frank was a bad driver initially,
    0:29:42 doesn’t fall into my positive selection loop,
    0:29:47 but I still want to try to make Frank a better driver.
    0:29:48 – If I could turn him into a good driver,
    0:29:49 he’d be profitable.
    0:29:52 – Right, so because that’s the flaw
    0:29:55 with kind of wedge one and wedge two
    0:29:57 of like creaming the crop, really wedge one,
    0:29:58 which is we’re going to cream the crop.
    0:29:59 We’re going to do what SoFi did.
    0:30:00 We’re going to do with health IQ.
    0:30:03 I mean, it’s a great strategy,
    0:30:07 but the rest, again, if you assume that it’s all nature
    0:30:08 and there’s no nurture,
    0:30:10 then perhaps there’s nothing you can do.
    0:30:13 But if you can actually try to nurture better behavior,
    0:30:17 you actually see better, you do see better behavior
    0:30:19 and then the profitability goes up.
    0:30:21 So, and the interesting thing there
    0:30:24 is that you’re still finding mispriced customers,
    0:30:26 but you’re actually helping turn them
    0:30:28 into correctly priced customers.
    0:30:31 So somebody like a bank would turn away that customer
    0:30:33 and say, we don’t want them
    0:30:37 because they have a 500 FICO, which is really bad.
    0:30:39 And then you have to figure out,
    0:30:42 and as with all of the new startups
    0:30:43 that are saying we only want the best customers,
    0:30:46 we want to leave the banks with the bad customers,
    0:30:48 but it’s kind of the twin pillars of
    0:30:52 can you identify something that’s below that credit score
    0:30:54 or below that driving score or something,
    0:30:56 and then can you encourage positive change?
    0:30:58 And if you can, then you can start actually
    0:31:02 creaming the crop of the bottom half of the customers,
    0:31:02 right, not even the bottom half.
    0:31:04 It’s the customers that are just neglected
    0:31:06 because nobody wants to underwrite them.
    0:31:09 And then you do that, you take them on
    0:31:12 because you have a secret to change their behavior.
    0:31:14 – Right, you’re seeing a lot of companies
    0:31:18 that sort of are using behavioral economics research
    0:31:22 to figure out how do I nudge people into better behavior.
    0:31:23 And so this would be an example
    0:31:26 of how you’re trying to change behavior
    0:31:28 to get the profitable customer.
    0:31:31 – Right, so there is one company
    0:31:33 in the lending space a while ago called Vouch.
    0:31:35 I think ultimately it didn’t work,
    0:31:38 but when you apply for a loan,
    0:31:41 it actually kind of taps your social network
    0:31:44 and it requires that they do a reference for you.
    0:31:45 Either a reference in terms of like,
    0:31:49 yes, Frank is a good customer, you can trust him.
    0:31:52 And even kind of a co-commit.
    0:31:56 So I’m getting a loan for $1,000 and you say,
    0:31:59 yeah, Alex is okay, or I’m saying Frank is okay.
    0:32:01 And if he doesn’t pay you back,
    0:32:05 I will put $100 in, because that’s how confident I am.
    0:32:07 And it’s not all 1,000, but it’s 100.
    0:32:11 And then you’re my friend, I go bowling with you.
    0:32:13 We go take our cameras out together.
    0:32:16 And if you don’t pay back this $1,000
    0:32:19 to this kind of faceless, large, evil corporate entity,
    0:32:21 not really, but if you don’t pay that back,
    0:32:23 I’m on the hook for a hundred bucks.
    0:32:25 I’m not going bowling with you anymore.
    0:32:27 So there are other things that are really interesting
    0:32:30 to try to encourage the correct form of behavior.
    0:32:33 And actually, part of it is just making it personal.
    0:32:35 Like this was the whole Eunice theory,
    0:32:37 which is if you are kind of held accountable
    0:32:41 by your peers, that is so much more powerful
    0:32:44 than getting a collections call from Citibank.
    0:32:46 Like you’re like, ooh, that’s the collections never,
    0:32:48 iPhone block, done.
    0:32:50 But how am I going to block my friends out?
    0:32:53 If Alex calls me and says you really got to pay
    0:32:55 that loan back, otherwise I’m out a hundred bucks, right?
    0:32:56 That’s much more powerful.
    0:32:58 I mean, this has worked great for a lot of health
    0:32:59 in a different domain, right?
    0:33:03 Which is if you are trying to get a pre-diabetic patient,
    0:33:06 not to get diabetes, the most effective thing to do
    0:33:08 is lose something like six or 7% of your body mass.
    0:33:11 And the way they do it is they get you into a group.
    0:33:14 They mail everybody a scale.
    0:33:16 Everybody sees your weight in the morning, right?
    0:33:18 Like that’s a powerful motivator.
    0:33:20 – Yeah, I mean, this stuff, psychology is very powerful.
    0:33:24 So there are a lot of tricks that you can use here.
    0:33:27 And if you understand the impact of them,
    0:33:29 you actually have to reassess your entire branding
    0:33:31 and customer acquisition strategy, right?
    0:33:32 – Right, right.
    0:33:35 All right, so remember I opened up pretending
    0:33:38 to be the product manager at Visa.
    0:33:41 And now we’ve gone through all of these three categories
    0:33:42 of how the startups are coming for me.
    0:33:45 And like, I’m starting to sweat here, right?
    0:33:47 They can come get my best customers.
    0:33:48 They can generate new data sources
    0:33:50 that like I would have a hard time doing.
    0:33:53 They can actually even go after sort of worse customers,
    0:33:54 change their behavior,
    0:33:56 turn them into profitable customers.
    0:33:57 I’m scared now.
    0:33:59 Like what in the world should I do?
    0:34:02 Like you’re in my seat, you’re the head of innovation
    0:34:04 or head of strategy or head of digital
    0:34:06 at one of these big FinTech companies.
    0:34:10 What should I do with respect to startups?
    0:34:11 – Well, I think it’s actually very hard
    0:34:13 for a company that’s trying to be all things
    0:34:15 to all customers.
    0:34:16 Because if you look at what SoFi is,
    0:34:18 look at SoFi’s brand.
    0:34:20 Brand is, you know, we are the high,
    0:34:21 like if you’re great, you’re good enough for us.
    0:34:22 – If you’re Henry, right?
    0:34:24 – If you’re a Henry, you’re good enough for us.
    0:34:25 Health like you.
    0:34:27 If you’re healthy, you’re good enough for us.
    0:34:30 So on that sector of the curve,
    0:34:33 how does GEICO say, hey, if you’re a good driver,
    0:34:35 go to this special part of GEICO.
    0:34:37 If you’re a regular driver, you still save 15%.
    0:34:40 If you’re a bad driver and you had a DUI,
    0:34:41 well, we can cover you over here.
    0:34:46 It’s just, it’s lost in this kind of giant GEICO,
    0:34:48 you know, GEICO marketing message.
    0:34:52 So in many cases, it actually helps to have sub-brands
    0:34:55 and divide this up, which is somewhat anathema
    0:34:56 to a lot of companies that want to say,
    0:34:59 how do we get as much efficiency and synergy as possible?
    0:35:01 We’re gonna have one overarching brand.
    0:35:03 And, you know, one of my favorite examples
    0:35:04 of this kind of different industry,
    0:35:07 but the highest end of the highest end of jewelry
    0:35:08 is Tiffany and Co.
    0:35:10 Or one of the highest end of the highest end.
    0:35:13 And for a long time, it was owned by Avon.
    0:35:14 – No, really?
    0:35:15 – You know, the Avon lady, Avon.
    0:35:19 So, and if Avon bought Tiffany, which they did,
    0:35:20 and they said, okay,
    0:35:23 we’re gonna rebrand Tiffany and Co as Avon,
    0:35:25 like that doesn’t work.
    0:35:27 Like you’re not gonna get, you know,
    0:35:30 80% gross margins on whatever they sell at Tiffany and Co.
    0:35:33 – Prefisted Avon’s just doesn’t have quite the right ring.
    0:35:34 – It doesn’t work.
    0:35:36 And then for Avon to say, okay, you know,
    0:35:39 the door-to-door salesperson or sales lady
    0:35:41 with the pink Cadillac that’s going around,
    0:35:45 like we’re now going to have her push $2,000 bracelets
    0:35:48 as opposed to the normal $10 fare,
    0:35:49 like that’s not gonna work either.
    0:35:51 But it actually can make sense
    0:35:54 if you want to just appeal to more customers,
    0:35:55 you have different brands
    0:35:57 and you don’t wanna all suck them together.
    0:35:59 So you can imagine instead of having, you know,
    0:36:01 Geico could be your generic brand,
    0:36:03 but then you could have,
    0:36:04 I think I mentioned this to you once before,
    0:36:05 a friend of mine is Mormon,
    0:36:07 doesn’t drink alcohol,
    0:36:10 and says we should have Mormon insurance for cars
    0:36:11 because it’s just totally unfair.
    0:36:13 Again, going back to the psychology point,
    0:36:16 like why is it that I’m paying for the drunk idiot
    0:36:17 that goes through the stop sign,
    0:36:20 I don’t drink, I can prove that, I will never drink,
    0:36:21 I have a million friends just like me
    0:36:22 that will never drink,
    0:36:23 we should all get car insurance,
    0:36:25 we should all get a 40% lower rate.
    0:36:28 Do they think of Geico when they go there?
    0:36:29 Maybe they could,
    0:36:32 but it could be like Mormon car insurance,
    0:36:33 or something, I’m not good at branding,
    0:36:35 but you could have a separate brand
    0:36:37 for all of these separate subgroups
    0:36:40 and have the same underlying infrastructure
    0:36:41 behind all of them,
    0:36:44 but again, part of this is just how do you brand
    0:36:45 and how do you market effectively?
    0:36:48 Because if you look at the efficacy of health IQ ads,
    0:36:50 or the efficacy of SOFI ads,
    0:36:51 they’re so much higher,
    0:36:53 because again, you have this large group of people,
    0:36:56 or in many cases small but valuable groups of people,
    0:36:58 that feel like they’re being treated unfairly.
    0:37:01 So yeah, Geico is save 15% on auto insurance,
    0:37:03 click here.
    0:37:08 Mormon car insurance advertised to LDS members in Utah,
    0:37:11 shooting fish in a barrel,
    0:37:13 that’s gonna have a dramatically higher click rate,
    0:37:14 and then many of these products
    0:37:16 are also very demand elastic.
    0:37:19 So I’m not saying save 15% on car insurance,
    0:37:22 I’m saying save 80% on car insurance,
    0:37:24 it’s very easy to do, click here,
    0:37:26 positive selection bias,
    0:37:28 that’s gonna work better than like Geico,
    0:37:30 but we also have something for Mormons too.
    0:37:31 – Right, yeah.
    0:37:34 The goal is to find the LDSers and the hyper-myelors
    0:37:36 who are really safe, et cetera, et cetera, right?
    0:37:38 And so it’s very counterintuitive,
    0:37:39 because if you’re at a big company,
    0:37:40 you’re thinking scale,
    0:37:42 how do I get the next increment
    0:37:44 of revenue growth or profit,
    0:37:46 and you’re saying actually go the other way,
    0:37:48 don’t try to make your single brand bigger,
    0:37:50 try to think about a dozen sub-brands,
    0:37:54 each going after sort of the perfect market for them.
    0:37:57 How do you positively select into a sub-market?
    0:37:59 – Well the other side effect of this is that,
    0:38:02 part of the asymmetric warfare
    0:38:03 that some of the startups have,
    0:38:05 is that if you wanted to kill Geico,
    0:38:08 you wouldn’t steal 100% of their customers.
    0:38:10 I mean if you did that, that would almost be too obvious,
    0:38:12 you’d steal 20% of their customers,
    0:38:14 but only the good ones.
    0:38:17 So imagine that Geico could actually devolve or evolve,
    0:38:19 depending on your point of view, into 10 sub-brands.
    0:38:21 There’s no more Geico,
    0:38:24 but it’s just like the 10 sub-brands basically select
    0:38:25 for the right types of customers,
    0:38:29 or even help judge and improve behavior
    0:38:31 from other subsets of customers,
    0:38:35 and then expel the 30% that are just bad news.
    0:38:38 And if you can expel the 30% that are bad news,
    0:38:41 you might say okay, well all of this dis-sinergy
    0:38:43 of going from one brand into 10 sub-brands,
    0:38:45 well that was idiotic.
    0:38:46 Because now I have fewer customers,
    0:38:47 but actually no it isn’t.
    0:38:49 Because you might have fewer customers,
    0:38:50 but it’s not like selling widgets.
    0:38:52 You’re selling probabilistic widgets,
    0:38:55 where in many cases you have negative gross margin
    0:38:57 when you sell a widget.
    0:38:58 So it’s important to figure out,
    0:39:02 how do I get the good ones, keep the good ones,
    0:39:04 and then get rid of the bad ones.
    0:39:06 – Yeah, so that’s one strategy,
    0:39:10 which is sort of sub-brands and sort of customer segmentation.
    0:39:13 What if I’ve been told by main management team,
    0:39:16 go find a bunch of startups to work with, right?
    0:39:18 Sort of somehow figure out a marketing
    0:39:23 or co-selling relationship so that we can start experimenting
    0:39:24 with some of these new models,
    0:39:26 and we can keep an eye on the startup community
    0:39:29 so that maybe we can put ourselves in the best place
    0:39:31 to buy them if it turns out working.
    0:39:33 Is there a way to do that?
    0:39:34 – Well there are many ways to do that.
    0:39:37 Probably the easiest way that is often counterintuitive
    0:39:39 for a lot of big companies is I call this
    0:39:41 the turn down traffic strategy.
    0:39:44 So Chase turns down a lot of people for loans,
    0:39:47 either because, again, it’s the bin and ball problem
    0:39:50 where it’s like, well, you might be good, you might be bad.
    0:39:51 Sometimes it’s not even that.
    0:39:52 It’s like, we think you’re good,
    0:39:56 but we just can’t profitably underwrite a $400 loan.
    0:39:58 But Chase has all the traffic.
    0:39:59 So what is turn down traffic?
    0:40:02 It’s saying, okay, we rejected you.
    0:40:04 Hey, here’s a friend that you might like.
    0:40:05 So this is not cream of the crop.
    0:40:08 This is the bottom tier on the ingestion point
    0:40:12 for a big financial institution saying we don’t want you,
    0:40:14 which kind of is kind of a mean thing to say.
    0:40:17 A way to ameliorate that potentially is saying
    0:40:19 we don’t want you because we’re not smart enough to,
    0:40:22 hey, sorry, we’re working on it.
    0:40:23 All our systems are down.
    0:40:25 But here’s a great startup that does.
    0:40:27 Now why would you send customers to a startup?
    0:40:29 Well, the number one thing,
    0:40:32 that Geico spends $1.2 billion a year on advertising.
    0:40:34 It’s really hard to compete with that from a,
    0:40:37 so if I could not spend a dollar of advertising
    0:40:42 but give 90% of my net income to Geico as a startup,
    0:40:43 I still might make that trade.
    0:40:44 I mean, we don’t always like this
    0:40:45 because we wanna see do you have
    0:40:47 your own acquisition strategies,
    0:40:49 your own acquisition channels,
    0:40:51 you’re not dependent on the big company.
    0:40:52 But from the big company’s perspective,
    0:40:55 turn down traffic is often brilliant.
    0:40:57 Because it’s saying here’s somebody
    0:40:59 that knows how to underwrite better than we do
    0:41:01 or more profitably than we do,
    0:41:03 we’re going to send our customers,
    0:41:05 otherwise what happens?
    0:41:07 And this is what I think Amazon got right
    0:41:10 in an era where everybody else got this wrong.
    0:41:12 Amazon said, okay, you’re on Amazon’s website
    0:41:14 and you’re looking at the Harry Potter book.
    0:41:17 And then right next to our Harry Potter book
    0:41:20 is an ad for Barnes & Noble for the Harry Potter book.
    0:41:21 Barnes & Noble is like, this is amazing.
    0:41:23 We can buy ads on Amazon’s website.
    0:41:24 They’re so stupid.
    0:41:26 We’re buying ads and stealing their customers.
    0:41:29 But every time you click on that Barnes & Noble ad,
    0:41:31 Amazon made a dollar and it’s 100% gross margin.
    0:41:32 They share that with nobody.
    0:41:33 There’s no cogs on that.
    0:41:36 And then they can use that dollar of pure profit
    0:41:39 to lower their cost of their Harry Potter book.
    0:41:41 Which actually made more people wanna go to Harry Potter,
    0:41:43 we’ll go to Amazon to look for Harry Potter
    0:41:45 than go to Barnes & Noble that said,
    0:41:47 we’re locking you within our walls.
    0:41:49 It’s like a casino with no clocks.
    0:41:50 And we’re gonna pump oxygen in.
    0:41:53 So because what a lot of big companies don’t get
    0:41:54 is that Google is just one click away.
    0:41:57 Like why give all the excess profits to Google?
    0:42:00 When I go to Chase, I get turned down for a loan.
    0:42:01 And then I go back to Google and I say,
    0:42:03 where else can I get a loan?
    0:42:05 Well, Chase should be sending you there.
    0:42:06 And actually they’re starting to do this.
    0:42:08 So that’s one strategy that I think has a lot of legs.
    0:42:09 – Yeah, so turn down traffic.
    0:42:10 That’s super interesting.
    0:42:13 Look, you spent all the money to bring them to your site
    0:42:15 and otherwise you would have just lost them.
    0:42:17 That sort of sunk cost.
    0:42:19 So you get something out of it.
    0:42:20 That’s fantastic.
    0:42:22 Well, why don’t we finish this segment out?
    0:42:24 I wanna do a lightning round with you.
    0:42:26 Which is I want sort of instant advice
    0:42:27 for somebody in this seat.
    0:42:29 I’m an executive visa or a geico.
    0:42:31 And so I’m gonna name a category
    0:42:34 and you sort of just have how to deal with startups
    0:42:35 and you can react to it.
    0:42:38 All right, so category one is
    0:42:41 you should always invest super early
    0:42:43 as early as you can into a startup.
    0:42:45 – So again, remember adverse selection
    0:42:46 versus positive selection.
    0:42:48 So I would say the competence.
    0:42:50 So this is what you have to get right,
    0:42:53 which is if you take nine weeks to make a decision
    0:42:55 and like, you know, we’ll decide within a day
    0:42:56 or if Sequoia or Benchmark
    0:42:58 or some other great venture capital firm
    0:42:59 will decide within a day.
    0:43:01 Like you’re not going to get good deals
    0:43:02 if you take nine weeks.
    0:43:05 So it can be very, very important to invest early,
    0:43:07 but like the best things always seem overpriced.
    0:43:09 Like this is something that we’ve learned
    0:43:10 and it’s the same thing
    0:43:12 with underwriting your own customers,
    0:43:14 which is like if something’s too good to be true,
    0:43:15 it probably is.
    0:43:17 So some of the best things are actually very expensive.
    0:43:18 Yeah.
    0:43:19 All right.
    0:43:21 – Just given those dynamics,
    0:43:22 just wait for the later rounds.
    0:43:24 Let all the venture guys take all the risk
    0:43:26 and then like you plow in late.
    0:43:28 That should be my strategy.
    0:43:29 – I think in general,
    0:43:30 that’s probably a better strategy.
    0:43:31 But again, saying like,
    0:43:33 ooh, we’re getting a great deal on this one.
    0:43:34 That’s probably,
    0:43:37 then you know that you’re the adverse selection
    0:43:40 a source of capital as opposed to, okay,
    0:43:41 here’s something I can’t believe
    0:43:43 we’re paying this much money for it.
    0:43:44 We have to fight our way in.
    0:43:46 There are 10 other people that want it.
    0:43:48 You probably know you’re on to a good customer,
    0:43:50 if you will, or a good investment.
    0:43:54 – All right, partner with as many possible startups
    0:43:56 as you can, ’cause you don’t know who’s gonna win.
    0:43:58 So let’s open up a marketplace.
    0:44:01 Let’s 100 startups that I have either turned on
    0:44:03 traffic relationships or something.
    0:44:05 – I think that actually that does make sense.
    0:44:08 I mean, there should be some kind of gating item
    0:44:10 to make sure like maybe not a hundred.
    0:44:14 But how do we stay close to different models
    0:44:14 that are working well?
    0:44:17 Because the main advantage that the incumbents have,
    0:44:20 again, depends on like lending or insurance,
    0:44:23 but it’s typically something around cost of capital
    0:44:25 and something around distribution.
    0:44:27 So if you have both of those
    0:44:29 and you’re not using it to the fullest extent,
    0:44:30 like you turned down a lot of customers,
    0:44:33 like you should try to find an intelligent way
    0:44:36 of using this and using that’s your unique thing,
    0:44:38 like venture capital firms don’t have that.
    0:44:40 I can’t fund somebody and send them
    0:44:43 a million customers tomorrow, but Geico could.
    0:44:45 So, but you can’t do that a hundred times.
    0:44:48 You can probably do that some sub-segment of times
    0:44:51 according to how much additional traffic
    0:44:53 or whatever it is that the unique advantage
    0:44:55 that you want to bring to bear.
    0:44:58 All right, now on M&A strategy.
    0:45:02 M&A strategy one, buy super early
    0:45:05 before it’s proven to work
    0:45:07 because presumably the prices are lower.
    0:45:12 So M&A strategy early, focus on early stage companies.
    0:45:14 – I’m a big fan of what Facebook’s done with M&A
    0:45:15 and I encourage everybody
    0:45:16 and pretty much every other industry to do this.
    0:45:18 So Facebook has two formats for M&A.
    0:45:22 One is we buy the existential threat that could kill us
    0:45:24 and we price it probabilistically.
    0:45:28 So surrender 1% of our market cap to buy Instagram.
    0:45:29 That was way overpricable.
    0:45:31 – Everybody said that.
    0:45:32 – Wow, there you go.
    0:45:33 – There’s a one in a hundred chance
    0:45:35 that this is gonna be bigger than Facebook.
    0:45:38 We should probably surrender 1% of our market cap.
    0:45:41 WhatsApp, 7% chance or whatever it was.
    0:45:43 I think it was 7% of Facebook’s fully diluted market cap
    0:45:45 was spent on WhatsApp.
    0:45:47 These were brilliant acquisitions.
    0:45:48 Oculus, I mean Oculus hasn’t turned out
    0:45:50 the same way that WhatsApp has perhaps,
    0:45:51 but like same idea.
    0:45:52 This could be the new platform.
    0:45:54 If we don’t buy this and Apple does,
    0:45:57 we are subject to their random whims and fancies.
    0:45:58 So that’s category one.
    0:46:01 Category two, and this is super counterintuitive
    0:46:02 for a lot of companies,
    0:46:04 buy the guys that failed trying.
    0:46:09 Because they had the courage and the tenacity
    0:46:12 to try to go and build something new
    0:46:14 and that’s what you want in your company as well.
    0:46:17 And then this is the most counterintuitive part.
    0:46:18 Is like take the person that failed
    0:46:21 and put them in charge of the person that was successful.
    0:46:23 And that’s the part that, that’s breaking glass.
    0:46:26 – For a big company, that’s so hard.
    0:46:28 You reward your execs on success, not on failure.
    0:46:30 – Right, but in many cases it’s like you have a big company
    0:46:33 that’s been trying to build this thing for 10 years.
    0:46:35 And if they build it, they will get one billion customers.
    0:46:37 Because they have, or I’m making that up,
    0:46:38 they have the distribution.
    0:46:40 Then you have the startup that actually built the thing
    0:46:41 in like a week.
    0:46:43 And they built it for a million dollars.
    0:46:45 And that would take the big company like a billion dollars
    0:46:47 in 10 years to do.
    0:46:48 But like, oh, the company failed.
    0:46:50 Oh, that’s a bad company.
    0:46:51 These are bad managers.
    0:46:53 But actually you want to take them and put them in charge.
    0:46:55 And the joke that I would always make is like,
    0:46:59 if Amtrak buys Tesla, the worst thing that Amtrak could do,
    0:47:01 because Amtrak is probably more profitable
    0:47:02 than Tesla at this point.
    0:47:04 But if Amtrak were to buy Tesla,
    0:47:06 the worst thing they could do is say, okay,
    0:47:09 all of you Tesla bozos, you work for us.
    0:47:12 But the whole point of a lot of this other form of M&A
    0:47:14 is you’re really trying to buy products
    0:47:16 that you can push into your distribution.
    0:47:19 And you’re trying to buy talent that wrote the products,
    0:47:20 that built the products, that understand that.
    0:47:22 And the only thing that they needed,
    0:47:25 the only gap between them and actual huge success
    0:47:27 is distribution, which these big companies have in droves.
    0:47:30 – Yeah, so that makes perfect sense.
    0:47:32 Maybe just a piece of advice
    0:47:34 on how to actually make that happen.
    0:47:36 ‘Cause you have this dynamic where you’re a big company,
    0:47:39 you just bought a failing startup, right?
    0:47:41 You have all of the execs inside
    0:47:43 that have earned bonuses consistently over a year
    0:47:45 for awesome performance, right?
    0:47:46 You’ve rewarded success.
    0:47:47 And now you’re gonna say,
    0:47:50 I’m gonna take this guy that kind of failed.
    0:47:52 And like, you work for them.
    0:47:53 – Right.
    0:47:55 – Like, oh, that’s hard to do inside a big company.
    0:47:56 – It’s very hard.
    0:47:58 But I mean, in some cases, you just wanna do it early.
    0:48:00 I mean, I think it actually, where it works best
    0:48:02 is where you say, we need this product.
    0:48:03 – Yeah.
    0:48:03 – We need this product to exist.
    0:48:04 We don’t have it right now.
    0:48:06 We haven’t spent eight years trying.
    0:48:10 Rather than saying, let’s go assemble a team
    0:48:11 and I’m gonna rely on like something
    0:48:12 that’s just not in our core DNA,
    0:48:14 here’s how we’re gonna go shopping.
    0:48:16 We’re not gonna go shopping and value this.
    0:48:18 And again, we don’t, this is not a self-serving comment
    0:48:20 because if somebody buys one of our failing companies
    0:48:22 for $10 million and we have a billion dollar fund,
    0:48:23 it doesn’t matter, right?
    0:48:26 Like we want the companies that actually beat the incumbents.
    0:48:28 But the incumbents, the way that they can actually do great
    0:48:30 is to adopt more of this Facebook mentality.
    0:48:35 And like, the key thing is that many of these acquisitions,
    0:48:36 these kind of aqua hire,
    0:48:39 that’s the portmanteau of acquire and hire,
    0:48:41 these aqua hire acquisitions that Facebook made,
    0:48:45 these people now run big swaths of Facebook.
    0:48:47 So I agree, it’s hard to do
    0:48:49 if you already have a leader in place.
    0:48:50 In that case, it just requires
    0:48:52 a very strong-willed leadership team
    0:48:55 and an actual overt strategy that this is what we do.
    0:48:57 It becomes easier if it’s like, okay,
    0:48:58 we’re trying to do this new thing
    0:49:00 rather than assemble our own team
    0:49:01 and they don’t know what they’re doing
    0:49:02 but they’re well-intentioned.
    0:49:05 Let’s go buy a company, but let’s buy a company
    0:49:06 that hasn’t already done the thing,
    0:49:10 but a company that tried and failed to do the thing.
    0:49:12 But we’re pretty sure that these are the best triers
    0:49:14 and failures in the business.
    0:49:17 That’s the hard thing to really measure
    0:49:19 because most people are used to measuring outcomes
    0:49:20 and not process.
    0:49:23 And the key thing to make this strategy work
    0:49:26 is you actually want to over-allocate on process
    0:49:28 and you want to wait outcome to almost zero
    0:49:30 because you’re buying the outcomes that were in fact zero.
    0:49:34 – Yeah, the mark is about to interview
    0:49:37 Andy Duke, the thinking in bets, right?
    0:49:39 And this is sort of the essential thinking in bets motion,
    0:49:41 right, which is don’t confuse a bad outcome
    0:49:45 with sort of a bad bet, right, right, exactly, awesome.
    0:49:46 Well, thank you so much, Alex,
    0:49:48 for coming in and sharing your thoughts.
    0:49:50 For those of you in YouTube land,
    0:49:52 please like and subscribe.
    0:49:54 And for the comments thread on this,
    0:49:57 I’d love to get your input on what you thought
    0:50:01 of Alex’s idea that what you really should do
    0:50:03 is not go after more customers,
    0:50:07 but instead go after only the best customers.
    0:50:09 So what are examples that you’ve been trying
    0:50:11 in your own startup where you’re trying
    0:50:14 to implement that idea?
    0:50:16 So see you next time.
    0:50:18 Go ahead and subscribe to the channel if you like it
    0:50:20 and see you next episode.

    In this episode of the a16z Podcast — which originally aired as a video on YouTube — general partner Alex Rampell (and former fintech entrepreneur as the CEO and co-founder of TrialPay) talks with operating partner Frank Chen about the quickly changing fintech landscape and, even more importantly, why the landscape is changing now.

    Should the incumbents be nervous? About what, exactly? And most importantly, what should big companies do about all of this change? But the conversation from both sides of the table begins from the perspective of the hungry and fast fintech startup sharing lessons learned, and then moves to more concrete advice for the execs in the hot seat at established companies.


    The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates.

    This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investor or prospective investor, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.)

    Past performance is not indicative of future results. Any charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision.

    Please see https://a16z.com/disclosures for additional important information.

  • a16z Podcast: A Podcast About Podcasting

    AI transcript
    0:00:04 >> Hi, everyone. Welcome to the A6NZ Podcast. I’m Sonal.
    0:00:06 So I’m super-duper excited today,
    0:00:07 even way more than usual,
    0:00:10 because this episode is all about podcasting.
    0:00:12 For newer listeners, we actually did an episode
    0:00:15 called “A Podcast About Podcasts” about four years ago,
    0:00:18 which you can find on our website, A6NZ.com.
    0:00:21 But today, we’re focusing this podcast about podcasting,
    0:00:23 since the podcasting ecosystem has
    0:00:25 evolved and changed quite a bit since then.
    0:00:26 By the way, I had hoped that Roman Mars,
    0:00:27 who was on that episode,
    0:00:29 would join us again, but he lost his voice,
    0:00:30 so couldn’t.
    0:00:33 Our special guest today is Nick Kwa, who writes “Hot Pod,”
    0:00:35 a newsletter that I’ve been following since very early on
    0:00:37 and has grown to be a go-to source
    0:00:39 all about the podcasting industry,
    0:00:41 with analysis insights and more.
    0:00:45 He also publishes and contributes to Vulture on similar topics.
    0:00:46 Also joining us for this episode
    0:00:49 is A6NZ General Partner Connie Chan,
    0:00:51 who covers consumer, the future of media,
    0:00:54 and Gen Z social, as well as trends from China,
    0:00:56 and has observed the podcasting phenomenon there
    0:00:59 and shares ideas on what more platforms can do here,
    0:01:01 and the three of us do a hallway-style jam,
    0:01:04 taking a longer pulse check on where we are right now
    0:01:06 in the podcasting industry.
    0:01:08 Speaking of, since we do mention some companies,
    0:01:09 please note that the content here
    0:01:11 is for informational purposes only,
    0:01:14 should not be taken as legal business tax
    0:01:15 or investment advice,
    0:01:18 or be used to evaluate any investment or security,
    0:01:20 and is not directed at any investors
    0:01:23 or potential investors in any A6NZ fund.
    0:01:27 For more details, please also see a6nz.com/disclosures.
    0:01:29 So we begin with the latest stats on the industry,
    0:01:31 touching on structural factors and more
    0:01:33 for about the first 15 minutes.
    0:01:35 Then we do a bunch of lightning round style takes
    0:01:38 on how other content and entertainment models
    0:01:40 may or may not apply to podcasting
    0:01:41 for about the next 30 minutes.
    0:01:44 And finally, we go into monetization platforms,
    0:01:45 analytics, and more,
    0:01:47 which we also touch on throughout the episode,
    0:01:49 including impacts on creators.
    0:01:52 And we end on recent news and moves in the space,
    0:01:54 such as Spotify, Gimlet,
    0:01:56 how to think about terrestrial radio, and more.
    0:01:59 But we begin by defining a podcast,
    0:02:01 which seems obvious, but isn’t,
    0:02:03 and is a rather existential question.
    0:02:05 So guys, what is a podcast?
    0:02:07 – So, I mean, the real interesting thing here is,
    0:02:10 we’re in the midst of a really interesting moment of change,
    0:02:11 and there is internal conflict
    0:02:14 within the podcast community about that question.
    0:02:17 So historically, it’s been largely tethered
    0:02:18 to the notion of the RSS feed.
    0:02:23 It’s basically an audio file or a medium of distribution
    0:02:26 that largely happens through the technology
    0:02:28 that was carried over from blogging.
    0:02:31 And now with the entrance of Spotify
    0:02:33 and Pandora stepping up,
    0:02:36 and Google beginning to do whatever they’re going to do
    0:02:37 on the search engine side.
    0:02:39 – And Apple already is an entrenched player as well.
    0:02:41 – Yeah, absolutely, I heard media.
    0:02:46 And Luminary just announced their big 100 million fundraise
    0:02:49 and the fact that it gonna launch in July a couple days ago.
    0:02:50 – With a lot of exclusive content, right?
    0:02:53 So how does exclusive podcasts fit in
    0:02:54 with the old definition?
    0:02:56 – Especially with the Luminary announcement
    0:02:57 that was like a strong pushback
    0:03:00 from parts of the community that’s been around for a while
    0:03:04 and generally folks who really believe in the open ecosystem.
    0:03:06 And so we have a situation in which like,
    0:03:08 the technical definition is not
    0:03:10 the popular definition anymore.
    0:03:11 And if we go from the perspective
    0:03:15 of what the ordinary consumer thinks of a podcast,
    0:03:17 that is, it becomes a cultural question,
    0:03:18 not a technical question.
    0:03:20 – Which by the way, I wanna say parallels
    0:03:22 the history of the web,
    0:03:24 because this to me reminds me very much of early blogging.
    0:03:25 – Absolutely.
    0:03:27 – And debates about what is a blog,
    0:03:29 what is an article, what is a website.
    0:03:32 And there was this almost religious existential debate
    0:03:33 between the early kind of,
    0:03:35 in fact, some of the same people,
    0:03:36 because Dave Weiner,
    0:03:36 one of the people who invented–
    0:03:39 – Who also was important to the development podcast thing.
    0:03:40 – Right, he’s exactly.
    0:03:42 He’s, but I think he was technically the first person
    0:03:45 to do a podcast like in 2003 or something,
    0:03:47 or one of the early people.
    0:03:49 And he’s also been to specify the RSS feed,
    0:03:51 which drives the pipes
    0:03:53 and plumbing and ecosystem of podcasting.
    0:03:56 But today, users don’t even think of podcasts that way.
    0:03:59 It’s like, if it’s just recorded audio of people talking,
    0:04:01 oftentimes we’ll just call that a podcast.
    0:04:03 – Yeah, one of my favorite things
    0:04:05 when people always call our videos podcasts.
    0:04:06 – I mean, that’s a holdover, right?
    0:04:08 Like Joe Rogan still does that.
    0:04:11 There’s a lot of people who still do all video, audio,
    0:04:12 and still call it a podcast.
    0:04:14 I mean, the way I see it is that the tension
    0:04:17 has always been between people who see podcasting
    0:04:19 as the future of blogging
    0:04:22 and people who see the podcasting as the future of radio.
    0:04:25 And we’ve seen that tension cross many, many times.
    0:04:28 And I think we’re in a place where that no longer matters
    0:04:31 because ultimately the mass consumer will lead
    0:04:32 as where do you want to go?
    0:04:34 – Yes, and like the web, the analogy that I would draw
    0:04:38 is to the advent of the graphical user interface
    0:04:41 and how browsing, computing, et cetera.
    0:04:42 There’s always a phase in every technology
    0:04:44 where there’s a gooey phase
    0:04:45 where once you have an interface
    0:04:47 that’s user friendly and easy to navigate.
    0:04:50 And what’s interesting about this is that we’re in the phase
    0:04:53 where the listening has become easy to navigate.
    0:04:54 – And more accessible.
    0:04:55 – More accessible.
    0:04:57 – Through various kinds of hardware too.
    0:04:59 For example, listening to podcasts on their drive to work
    0:05:02 because the cars are enabled with podcasts.
    0:05:04 – Right, like the smartphone connected cars essentially.
    0:05:06 – Or AirPods making it so easy
    0:05:08 to listen to something while multitasking.
    0:05:10 – And in that sense, podcasts are different
    0:05:12 than audio books obviously just for the sake of definition.
    0:05:15 – But I would say like you can argue over time
    0:05:16 that even that definition may blur.
    0:05:18 – Of audio books and podcasts.
    0:05:20 – Right, like one day a podcast might just be thought of
    0:05:22 as like a self-published audio book.
    0:05:24 – I have long believed that audio books
    0:05:26 should be central to the conversation as well,
    0:05:27 especially a couple of years ago
    0:05:30 when Audible built sort of an original programming team
    0:05:33 that took after podcasts out programming.
    0:05:35 And in fact, the matter is that these are all distributors
    0:05:37 and platforms of the same kind of good.
    0:05:40 It’s just that we think of them and we class them differently
    0:05:41 and they also sort of are products
    0:05:43 of different economic systems.
    0:05:44 – I do want to add to this mix though
    0:05:46 that I would not confuse music into this.
    0:05:49 And the reason is first of all, from a creator perspective,
    0:05:53 every tool until now has been very music creator centric
    0:05:55 for podcast editing, creation, et cetera.
    0:05:59 And so there’s a really bad structural legacy effect
    0:06:00 of equating podcasting.
    0:06:01 I mean, we’re essentially bootstrapping tools
    0:06:03 tailored for music for podcasting.
    0:06:07 So the new wave of podcast native tools is really important.
    0:06:09 Full disclosure, we’re investors in Descript
    0:06:11 and it democratizes the editing of podcasting
    0:06:14 because you can essentially edit audio like a word doc.
    0:06:15 But the main point here is that
    0:06:18 I do think music should be treated very differently
    0:06:19 than podcasting. – I completely agree.
    0:06:21 I got to me like it’s audio with spoken word.
    0:06:23 – Yep, versus sunk.
    0:06:26 So I guess what we’re agreeing on
    0:06:28 just to recap the definition of podcasting.
    0:06:32 It is audio, it could potentially blur into including books
    0:06:35 if not in a content perspective, then to Nick’s point,
    0:06:40 then even in a distribution and business model perspective.
    0:06:42 But we agree that music should be treated differently.
    0:06:45 – And the common denominator here is spoken word.
    0:06:47 – That was actually the infinite dial study
    0:06:49 which is sort of an annual survey
    0:06:51 conducted by Edison Research.
    0:06:53 They just announced their latest results
    0:06:54 earlier this afternoon.
    0:06:56 The most interesting thing is that there were increases
    0:06:58 in both audiobooks and podcasting.
    0:07:02 So podcasting had a significantly like large leap this year,
    0:07:05 but on audiobooks, like after a couple of years
    0:07:09 of largely being flat, it’s been increased again.
    0:07:11 And I think that’s a sort of really interesting question
    0:07:13 because I can’t quite think of a structural reason
    0:07:14 why that would be the case,
    0:07:16 other than sort of like tethered effect.
    0:07:17 – In addition to that,
    0:07:19 you have all kinds of really easy to set up
    0:07:20 wireless speakers at home.
    0:07:24 They also make it more easy to consume this kind of content.
    0:07:26 – It reminds me of like what people say
    0:07:28 about the Kindle and romance novels.
    0:07:30 It helped sales increase
    0:07:33 because it made people like more willing to buy it
    0:07:35 and consume it because then nobody would judge them.
    0:07:37 – Oh, the judgment side, interesting.
    0:07:38 For me, it’s actually ease of access
    0:07:40 because I used to be really embarrassed
    0:07:42 and admit this publicly.
    0:07:46 I used to subscribe to the Harlequin Romance on Demand service
    0:07:48 where you’d get like the books a month
    0:07:51 and you’d pay like $11 or I can’t remember what it was.
    0:07:54 ‘Cause I’ve always been a huge reader of romance novels
    0:07:56 as a very nice lightweight thing to do.
    0:07:58 But what’s the analogy to podcasting?
    0:07:59 What’s the connection?
    0:08:00 – To me, I think it’s more ease of access
    0:08:02 around better hardware.
    0:08:03 – On demand, get it quickly.
    0:08:04 So speaking of the data and you mentioned
    0:08:07 that the Edison research study came out today
    0:08:08 and that’s sort of the definitive
    0:08:10 and longest running survey of digital media
    0:08:12 consumer behavior in America at least.
    0:08:15 But I hear a lot of mixed messages.
    0:08:16 I see like people cite this stat
    0:08:18 and that stat out of context.
    0:08:20 So why don’t we just do a quick pulse check
    0:08:21 on what are the key stats?
    0:08:22 And Nick, maybe you could recap for us
    0:08:25 what the key stats or big trends to know are here.
    0:08:27 – So I think there are a couple of big takeaways here.
    0:08:29 One is when it comes to the familiarity
    0:08:30 of the notion of podcasting
    0:08:33 and this doesn’t mean people who heard the word
    0:08:34 actually know what it is.
    0:08:38 It’s officially hit 70% of all Americans.
    0:08:40 And when it comes to the number of people
    0:08:42 who’ve actually tried out podcasting,
    0:08:43 maybe they didn’t stick around a bit
    0:08:44 but they just tried it at least.
    0:08:46 It’s gone over 50%.
    0:08:49 So about an estimate of 144 million Americans.
    0:08:51 Retention rates are sort of like really interesting.
    0:08:53 Like monthly podcast listening has also went up.
    0:08:56 It’s now 32% of all Americans up from 26 from last year.
    0:08:57 That’s a pretty big leap.
    0:08:58 – I mean, just that’s one third.
    0:08:59 That’s a lot.
    0:09:00 – Yeah.
    0:09:01 And there’s also a really interesting slide in here
    0:09:04 attributing some of the increase to Spotify.
    0:09:06 There is a stat here that shows
    0:09:09 amongst Spotify listeners between the ages of 12 to 24,
    0:09:12 monthly podcast listening went up to 53%.
    0:09:15 And so there’s a lot going on.
    0:09:17 I think currently it’s such a moment of flux.
    0:09:21 It’s a little unclear what the structural pillars are anymore.
    0:09:22 And I think there’s one of those things
    0:09:24 where we’re just gonna have to like look back
    0:09:25 at this moment and figure out where we turn.
    0:09:28 – So what’s a high level recap on that summary of the stats?
    0:09:30 – The high level is that this past year
    0:09:31 has seen an unprecedented growth.
    0:09:33 For the longest time podcast growth
    0:09:35 has been steadily and slow.
    0:09:37 And now it feels like it’s taken some sort of a leap.
    0:09:40 And so I feel like this past year has been the moment
    0:09:44 where it’s tipped into some form of mainstream.
    0:09:45 – That’s fantastic.
    0:09:47 So potentially a quote inflection point
    0:09:49 as people like to say in the business.
    0:09:51 – The usage of podcasts and the consumption of it
    0:09:55 has risen dramatically in the last year or two.
    0:09:57 But what always shocks me is that the revenue
    0:10:01 that podcasts generate is still such a small amount
    0:10:04 given how many hours people are spending
    0:10:05 consuming this kind of content.
    0:10:08 – So there is a study out there from the IAB
    0:10:11 that caveat being it was funded and financed
    0:10:13 by a constellation of podcast companies
    0:10:17 that puts the number at around 600 million plus plus
    0:10:18 this past last year.
    0:10:20 And it’s projected to keep growing of course.
    0:10:22 Monetization is a serious issue.
    0:10:24 And it largely has to do with the fact
    0:10:26 that podcasting is a technology
    0:10:29 hasn’t quite caught up to how the rest of the internet
    0:10:31 kind of works in terms of dynamic insertion.
    0:10:33 And it doesn’t allow like heavy increases
    0:10:36 in inventory and swap outs in inventory
    0:10:38 in a way that a lot of advertisers are now accustomed
    0:10:41 to getting from marketplaces like Facebook.
    0:10:44 – And then even that like from an advertiser standpoint
    0:10:46 you’re paying per download
    0:10:50 ’cause you aren’t getting like these per listen metrics back.
    0:10:52 So from the advertising standpoint
    0:10:55 it’s still really hard for them to measure the ROI
    0:10:57 from sponsoring a podcast.
    0:10:59 – Yeah, and that’s why historically we’ve seen
    0:11:01 a bunch of the activity among advertising
    0:11:03 from direct response advertisers
    0:11:06 because they have a secondary metric of conversions
    0:11:08 under promo codes and whatnot.
    0:11:10 And what they’re able to find is that
    0:11:12 the conversion rates are good.
    0:11:13 But when it comes to something like a brand advertiser
    0:11:16 or an advertiser that needs to lay an impression
    0:11:19 on a consumer over a five, 10 year period
    0:11:20 they need to know that they’re hitting
    0:11:22 the people that they’re hitting.
    0:11:23 There are a lot of movements right now
    0:11:26 towards standardizing what even a listen means.
    0:11:28 And this will become increasingly complicated
    0:11:30 as Spotify and Pandora.
    0:11:31 – Everywhere.
    0:11:32 I mean, right now you don’t know if it’s a,
    0:11:33 is it a download?
    0:11:34 Is it a click?
    0:11:35 Is it open?
    0:11:36 Is it a fee?
    0:11:37 I mean, who the fuck knows.
    0:11:38 – Or like how long did you listen to it, right?
    0:11:39 – Right, the engagement I care very,
    0:11:41 so that’s actually what I care most about as a creator.
    0:11:42 ‘Cause when I was at Wired,
    0:11:44 Chartbeat changed me as an editor
    0:11:47 and I need to know where people drop off.
    0:11:48 That is a number one thing.
    0:11:50 So I don’t know if you even know this, Nick.
    0:11:52 We were in the launch set for when Spotify launched
    0:11:55 their first move into podcasting in 2015.
    0:11:58 They selected us as part of one of their media outlets
    0:12:00 because our podcast was one of the very few
    0:12:02 that covered tech in a thoughtful way.
    0:12:05 And the reason I was so excited about Spotify,
    0:12:07 because Spotify didn’t really have much
    0:12:09 of a podcasting audience back then,
    0:12:12 was they showed me this really beautiful dashboard
    0:12:15 that showed you the potential and where people drop off.
    0:12:18 – But you don’t get that from all the other places
    0:12:19 our podcasts are distributed.
    0:12:21 – It’s still limited because not all of our listeners
    0:12:22 are listening on Spotify.
    0:12:23 They’re on SoundCloud, they’re on iTunes.
    0:12:24 They’re in a bunch of different apps.
    0:12:25 And iTunes, by the way, also announced this,
    0:12:27 I think, what last year, James Boggs,
    0:12:30 announced that you can actually have drop off.
    0:12:33 – Yeah, they rolled out a more granular
    0:12:34 in episode analytics.
    0:12:35 – Another thing I’d push back on though is like,
    0:12:38 I don’t actually think advertisements
    0:12:40 are the only way you can monetize podcasts.
    0:12:41 – Yes, I agree wholeheartedly.
    0:12:43 – I feel really, really strongly about that
    0:12:46 because even as someone who consumes podcasts,
    0:12:48 ads are extremely annoying to listen to.
    0:12:51 And this is where I look at other business models
    0:12:53 that are working in Asia for podcasts
    0:12:56 that I think could very much translate here.
    0:12:58 – Yeah, so a couple of points on that.
    0:13:01 It’s a situation in which there are behaviors
    0:13:05 in internet usage, in gaming, in media consumption,
    0:13:10 in China, Japan, Korea, Australia, Malaysia, Singapore,
    0:13:12 that doesn’t occur here,
    0:13:14 maybe through a path dependency reasons,
    0:13:17 maybe through sort of technical habituation reasons.
    0:13:20 And yes, we’ve already seen like a really healthy growth
    0:13:23 of the number of podcasts using Patreon as maybe not a primary,
    0:13:26 but a strong supplementary business model.
    0:13:28 Chatbot, ChatPos is an example of this.
    0:13:30 There are a bunch of podcast collectives
    0:13:32 that rely on Patreon for this.
    0:13:35 And there’s also like Slate Plus being sort of a central model
    0:13:38 to Slate as a digital media publisher
    0:13:40 that also heavily indexes on podcasting.
    0:13:43 But I think I’ve always found this lack of data conversation
    0:13:47 a little interesting because whether or not advertisers
    0:13:50 feel confident in the measurement
    0:13:52 and what the data is sort of trying to reflect
    0:13:55 in terms of reality, the world continues to spin
    0:13:59 and people do end up converting as a promo code.
    0:14:02 And so there is a strong sense that podcasting
    0:14:05 is a very powerful driver of consumers
    0:14:07 and it’s a powerful advertising driver,
    0:14:09 even though we’re not able to tell specifically
    0:14:11 how many people that gets hit
    0:14:13 in terms of just the analytics of it.
    0:14:16 And so there’s this fear among a lot of people
    0:14:19 that the analytics side will end up driving
    0:14:20 way too much of the conversation
    0:14:24 and ends up dictating the behavior of creators and publishers
    0:14:26 in a way that might end up being unhealthy
    0:14:29 or counterintuitive to the relationship
    0:14:31 between a listener and a creator.
    0:14:33 – The problem with that I think is like,
    0:14:36 yes, analytics may skew what kinds of content they put out
    0:14:37 and how they engage with their audience.
    0:14:41 But like really analytics is just a nicer way
    0:14:45 of saying revenue because at the end of the day
    0:14:46 your analytics are a reflection
    0:14:48 of how many listeners you’re getting, right?
    0:14:51 – I don’t agree actually completely.
    0:14:53 I agree with you from a business perspective,
    0:14:57 but as a creator the analytics tell me about community.
    0:14:59 And one of my favorite talks on the early days
    0:15:02 of resurgence of podcasting was Marco Arment gave a talk,
    0:15:04 I was at XOXO in 2013.
    0:15:08 And it was basically about the resurgence of podcasting,
    0:15:13 the early signaling of that and podcasts as a movement.
    0:15:14 Because what’s really unique for the first time
    0:15:16 when you think about the first wave of podcasting
    0:15:18 with all the indie bloggers,
    0:15:20 we now have brands podcasting.
    0:15:22 And sometimes they’re not actually looking
    0:15:23 for direct revenue through that.
    0:15:26 It’s a way to really connect intimately with your audience.
    0:15:28 I mean, it’s essentially a movement
    0:15:29 brought live in audio form.
    0:15:31 – So I mean, there are types of content
    0:15:34 where it’s not about monetization.
    0:15:35 But for a lot of creators,
    0:15:37 I do think revenue is one kind of proxy
    0:15:39 for how much value they’re providing their listeners.
    0:15:44 And I also think that we’re in such, such baby phases
    0:15:47 of how podcasters should be able to monetize.
    0:15:48 Like honestly, they shouldn’t be having
    0:15:51 to ask their listeners to go to other sites
    0:15:52 to pay them like a monthly fee.
    0:15:54 – You can’t do it in app.
    0:15:55 – I mean, this is where the platforms
    0:15:57 are gonna start rolling out subscriptions.
    0:16:00 I think some are gonna roll out like other ways
    0:16:02 of paying for packages or bundles of content.
    0:16:04 And I think that’s when you’re gonna see creators
    0:16:08 really unleash like much better content
    0:16:11 where they don’t have to focus on mainstream audiences,
    0:16:13 but they might focus on smaller audiences
    0:16:14 that are willing to pay for that.
    0:16:15 – So actually, I’m like really fascinating
    0:16:17 in terms of the concept of analytics
    0:16:20 is being the sort of like proxy for revenue here.
    0:16:22 It’s strange because I’ve always sort of viewed analytics
    0:16:26 as a certain kind of representation of reality.
    0:16:28 And it just so happens that advertisers
    0:16:31 at this point in time are really reliant
    0:16:34 on a certain expectation of a kind of analytics
    0:16:36 in order to discern whether a media product
    0:16:38 is effective in a way that they want it to be.
    0:16:40 And there’s this larger conversation
    0:16:43 about platforms in general, switching metrics
    0:16:47 or tweaking metrics or in some cases ballooning them
    0:16:49 in order to control and manage that narrative
    0:16:51 and relationship with the advertiser.
    0:16:52 – No, I completely agree.
    0:16:55 Analytics matters for an advertising model.
    0:16:57 But what I’m saying is like the advertising model
    0:17:01 is actually not a good model to monetize podcasts.
    0:17:03 – No, that we could be agree with.
    0:17:08 But it’s a situation in which like it is the revenue
    0:17:10 that a lot of people, a lot of publishers
    0:17:11 and creators feel most comfortable with
    0:17:14 because that’s all they know right now.
    0:17:16 – I think it’s actually also a legacy.
    0:17:17 This is where I think we need to think again,
    0:17:19 very native and a new medium.
    0:17:21 This is where we make, we do ourselves a huge disservice.
    0:17:24 Like the early days of the web
    0:17:27 when media outlets would put like a fricking,
    0:17:29 you know, homepage analog on the website.
    0:17:31 Right, exactly.
    0:17:34 Like we need to think very natively in this medium.
    0:17:36 And we have a huge opportunity for the first time
    0:17:39 because we have such an intimacy, a slipperiness,
    0:17:42 a connection with podcasting that’s visceral.
    0:17:43 That’s, I mean, personally,
    0:17:45 I think it’s unlike any other medium I’ve ever seen.
    0:17:47 I feel like I found my voice on this medium quite honestly.
    0:17:49 But so I do think that we have an opportunity here
    0:17:51 because we’re so stuck on the legacy.
    0:17:53 And in fact, this goes back to something we started with,
    0:17:54 which is what is the definition of a podcast?
    0:17:56 So I think the thing to revisit here
    0:17:59 is that the underlying pipes and infrastructure.
    0:18:00 And I know people don’t expect this
    0:18:02 when we’re talking about an episode about podcasts.
    0:18:03 But I think it’s really important
    0:18:04 because it informs this conversation.
    0:18:06 It is RSS feeds.
    0:18:07 It is literally an ecosystem
    0:18:09 of pipes that are connected by feeds,
    0:18:11 talking to feeds, talking to feeds.
    0:18:14 This is both a structural, huge limitation,
    0:18:17 causing major fragmentation in the industry,
    0:18:19 major limitations on what’s possible
    0:18:22 with what creators can do to even connect the dots.
    0:18:23 Because the unit of analysis is limit
    0:18:26 to what you can actually send in a feed.
    0:18:27 And that has certain trade-offs to it.
    0:18:29 And this actually reminds me of container ships,
    0:18:32 like physical, large shipping ships,
    0:18:34 like Merck, et cetera, that you see in the ocean.
    0:18:36 And one of the novel things about container ships
    0:18:39 is about what they did to creating trade across the world.
    0:18:41 And because they’re multimodal,
    0:18:45 they go from airplane to ship to truck to yard.
    0:18:47 They allowed so much collaboration
    0:18:49 and connection around the world.
    0:18:52 That’s what feeds are doing for the podcast ecosystem.
    0:18:55 What’s missing, however, is just like a container ship.
    0:18:57 Containers are rectangular boxes
    0:19:00 that are very limited in what you can actually fit into them.
    0:19:03 And people therefore need to fit the shape of their goods
    0:19:05 to fit in those boxes.
    0:19:07 And the entire ecosystem for physical container ships
    0:19:10 is architected around being able to lift things out and in.
    0:19:11 That is the same thing
    0:19:13 that’s happening in podcasting right now.
    0:19:15 The containers are connecting all of us
    0:19:16 in this feed ecosystem,
    0:19:19 but they’re also dictating what information
    0:19:21 travels where and in what form.
    0:19:22 And I just want to point this out,
    0:19:23 no matter how wonky it seems,
    0:19:25 because that structure both dictate so much
    0:19:28 of what the current batch of tools can and can’t do
    0:19:30 when it comes to analytics, to discovery,
    0:19:31 and more, all across the board.
    0:19:34 And it’s where platforms and tool builders
    0:19:36 have a huge opportunity to cleverly address
    0:19:39 or even bypass those containers
    0:19:40 once we get past this phase
    0:19:44 of where the podcasting industry is structurally right now.
    0:19:46 – Yeah, I just think like we are in such
    0:19:48 early, early, early innings of what podcasts can be.
    0:19:50 Because if you think about it,
    0:19:52 again, this is not using the technical definition
    0:19:54 of a podcast, but using this cultural definition
    0:19:57 of like audio recorded content, right?
    0:19:59 Most of the time you’re consuming that kind of content
    0:20:01 on an internet enabled device.
    0:20:04 It’s not like you’re downloading it onto your computer
    0:20:05 and then like using a USB stick
    0:20:07 to transfer it to your phone, right?
    0:20:11 And so therefore, like we are not monetizing this stuff
    0:20:12 or even creating features on top of it
    0:20:14 that are internet native.
    0:20:16 There’s just so much stuff we’re not even tapping into.
    0:20:19 And it’s such a shame because we’re consuming these things
    0:20:20 on internet enabled devices.
    0:20:22 And yet we’re using the same business model
    0:20:24 as televisions.
    0:20:25 – Where you can’t even do anything.
    0:20:28 – Which is not meant to be interactive.
    0:20:30 And there’s like right now very little interaction
    0:20:32 with the podcast, which I think is such a shame.
    0:20:35 – So I want to ask you guys kind of lightning round style
    0:20:37 on a couple of neat things that are artifacts
    0:20:39 of the existing world of content
    0:20:41 and how we think they’re going to play out with podcasting.
    0:20:42 So let’s just–
    0:20:43 – And I think you should give your take too
    0:20:45 ’cause you have more expertise on podcasts
    0:20:46 than anyone in the software.
    0:20:47 – Right, I forget to do that as a host sometimes.
    0:20:48 – Okay.
    0:20:50 – So I want to ask you guys about seasonality.
    0:20:52 Like what do you guys think of this trend
    0:20:54 of people dropping podcast seasons?
    0:20:56 – So I love seasonality.
    0:20:58 It gives, like it gives me a feeling of momentum
    0:21:00 and also we’re currently living in a moment
    0:21:02 where there’s all things happening all the time.
    0:21:04 So many things to consume.
    0:21:06 I would like things to have definite ends.
    0:21:09 And I’m a big fan of seasonality personally.
    0:21:11 – I think it also makes it easier for bundling
    0:21:13 and different pricing down the line.
    0:21:14 – Absolutely.
    0:21:15 – Oh, fascinating.
    0:21:16 So for me, seasonality is,
    0:21:19 so when I think of the long tail of content
    0:21:21 and Chris Anderson wrote the fundamental piece
    0:21:24 and book on this, it’s this idea of an infinite shelf space.
    0:21:26 And to me, things being in software and being digital,
    0:21:30 it’s unbounded to the point of being pointlessly infinite.
    0:21:33 And forcing a false scarcity is my favorite thing
    0:21:36 that like box in a month companies do,
    0:21:38 like stitch fix and makeup, whatever.
    0:21:42 It’s a way of curating and creating a scarcity
    0:21:43 in a world of abundance.
    0:21:45 And I think that’s a really interesting packaging thing
    0:21:47 for any kind of content across the board.
    0:21:49 And especially for podcasting because there is no,
    0:21:51 you’re essentially in an infinite scroll
    0:21:52 in the audible world.
    0:21:54 You don’t know where you are.
    0:21:55 You have no context.
    0:21:57 You’re not plugged into a specific thing
    0:22:00 ’cause you’re living in this weird ecosystem of voice
    0:22:02 and show or episode, depending on how you’re listening.
    0:22:04 So that’s my quick take on seasonality.
    0:22:05 – Love it.
    0:22:05 – Okay.
    0:22:08 So binge watching, this is related to seasonality.
    0:22:09 One of the most fascinating things
    0:22:14 about Netflix phenomenon in the space of visual content
    0:22:16 is they realize like, wait a minute,
    0:22:18 we don’t have to do weekly things.
    0:22:20 We can drop everything at once,
    0:22:22 not release it as a season that spreads out once a week
    0:22:24 or whatever the pace is.
    0:22:26 And allow binge watching.
    0:22:27 – I think binge watching is great
    0:22:30 and it’s natural human behavior for any kind of content.
    0:22:32 I suffer from it myself.
    0:22:33 Like I was the kind of person,
    0:22:34 I would watch the series 24.
    0:22:38 I would watch a season in like 30 hours.
    0:22:38 – I did that too.
    0:22:39 It’s stranger things and everything.
    0:22:40 – Yeah, yeah.
    0:22:42 And it’s just natural human behavior.
    0:22:43 And so I think it’s great.
    0:22:44 – That we wanna just be addicted
    0:22:46 and go deep all at once and we can’t stop ourselves.
    0:22:49 – And actually in terms of, for the creator,
    0:22:49 I think it’s a good thing
    0:22:52 because you don’t want that listener
    0:22:53 to kind of forget about it.
    0:22:54 – Yep.
    0:22:55 – I binge watch all the time.
    0:22:57 So I’m just gonna take “Devil’s Advocate”
    0:23:00 that I only like believe about 80% of.
    0:23:03 One is I actually think that binge watching
    0:23:05 or binge dropping has actually caused attention
    0:23:08 to a given show to deteriorate, right?
    0:23:11 It used to be the case where when a TV show drops weekly,
    0:23:13 there’s sort of a pulse of conversation
    0:23:14 that is drawn out over a longer period of time
    0:23:16 if that show has hit.
    0:23:17 I thought about–
    0:23:18 – You mean like the water cooler conversation?
    0:23:19 – Absolutely.
    0:23:21 Like true detective, game of thrones,
    0:23:23 same thing, basically everything that HBO,
    0:23:25 like that sort of structure of it,
    0:23:27 I really like that water cooler conversation
    0:23:29 and I like to be on the same sort of page
    0:23:31 as other people when I’m having that conversation
    0:23:34 and that’s something that I’ve never gotten with a binge show.
    0:23:36 I loved “Russian Doll”.
    0:23:38 I can’t find a single person to talk to about it
    0:23:39 who falls in love at the same time
    0:23:42 and I can guarantee in about a month
    0:23:43 I’m gonna forget about that show.
    0:23:45 To use a torture metaphor,
    0:23:48 the thing about binge TV that I enjoy really doing
    0:23:51 but I feel a little bit sick of doing afterwards,
    0:23:53 it reminds me of that thing when parents say
    0:23:54 that they do to certain kids
    0:23:56 where if they catch that kid smoking one cigarette,
    0:23:59 they make that kid smoke the entire pack of one cigarette.
    0:24:02 That’s kind of how I feel after when I binge a season.
    0:24:04 I feel like I don’t wanna watch TV for like a month.
    0:24:05 – But it’s like inevitable.
    0:24:08 I feel like this is a behavior you count.
    0:24:09 – Well, there is a lot of,
    0:24:10 so my whole thesis about this
    0:24:12 which is similar to screen time and kids
    0:24:13 ’cause people always have these stupid religious debates
    0:24:15 over it, it’s not so much the act of doing it
    0:24:17 or not doing it, it’s why you do it.
    0:24:18 So if you’re someone who’s binge watching
    0:24:20 ’cause you’re depressed, that’s not good.
    0:24:21 But if you’re someone who’s binge watching
    0:24:23 ’cause you just can’t stop watching the show, that’s great.
    0:24:24 I will say to push back on your point, Nick,
    0:24:26 ’cause I know you’re taking the devil’s advocate,
    0:24:28 but I think that what you’re describing this problem
    0:24:31 of the water cooler thing that Connie that you labeled,
    0:24:33 it’s actually an artifact of technology,
    0:24:36 not quite being there because there is a movement
    0:24:39 of second screen technologies that are allowing more,
    0:24:42 there’s forums online like Reddit that aggregate.
    0:24:43 To give you a perfect example of this,
    0:24:45 when I finished the Ubrati problem,
    0:24:47 the first thing I did was go trawl the web
    0:24:49 to find all the forums and all the people talking about it
    0:24:51 so I could find my people and talk about it
    0:24:53 and find other people who loved it.
    0:24:55 And so there are tools that are emerging
    0:24:58 that allow conversations to then to your point,
    0:25:02 the water cooler to be aggregated asynchronously.
    0:25:05 And there will be, I think, a second screen phenomenon
    0:25:09 happening with pod listening and binge listening
    0:25:11 as we start having the technology ecosystem grow.
    0:25:15 – I can see how you don’t want to spoil the ending.
    0:25:16 So you won’t actually go to that forum
    0:25:17 until you finish your book.
    0:25:18 – You’re absolutely right.
    0:25:20 And actually, I like that you can have a choice
    0:25:21 because in spoiler alert culture,
    0:25:23 which Nick is slightly hinting that he misses,
    0:25:24 at least on the devil advocate.
    0:25:25 – I do.
    0:25:27 – There is sort of like a thing
    0:25:29 where you can actually choose to check out of things.
    0:25:31 Luckily, so you’re not like stuck in a room
    0:25:33 with everyone talking and then you are screwed
    0:25:35 ’cause you missed like the closing season of Dallas
    0:25:36 or whatever show it was.
    0:25:38 The other point I want to make about binge listening
    0:25:41 in this context is with binge watching,
    0:25:43 new types of narratives are happening.
    0:25:45 I’m very curious about what will happen
    0:25:48 as we start seeing binge listening of podcast seasons
    0:25:50 or podcast episodes to narrative
    0:25:52 and how that’s gonna change that category of podcasts
    0:25:56 where a serial change the way it tells stories
    0:25:57 because people are binging it.
    0:25:58 – Well, then it becomes an audio book.
    0:25:59 – Oh, interesting.
    0:26:00 Then it becomes an audio book.
    0:26:01 Oh my God, I would have argued
    0:26:02 to almost the opposite item in the spectrum
    0:26:05 because it’s sort of going through a book very quickly.
    0:26:06 But the flip side of it is
    0:26:08 when I’m thinking the analog with binge watching
    0:26:10 is that you can watch an entire season
    0:26:13 and it changes the way you don’t have to have a cliffhanger
    0:26:14 at the end of every episode.
    0:26:15 Whereas even in a chapter,
    0:26:17 people still have a little bit of these things.
    0:26:18 – Right, narrative.
    0:26:20 – I will say, I think serial would have made a lot more money
    0:26:22 if it allowed people to pay.
    0:26:26 I think on the margin, binge listening helps creators
    0:26:28 because if you can make someone pay
    0:26:29 for like a whole season at once
    0:26:32 and maybe give them like one or two episodes for free,
    0:26:33 it’s better than hoping
    0:26:35 that they’re gonna come back every week, right?
    0:26:37 – The serial example is actually really, really interesting.
    0:26:40 Serial itself was an innovation of the form
    0:26:42 because it stuck to what podcasting
    0:26:44 was able to do at that time.
    0:26:45 Prior to the existence of serial,
    0:26:48 it was incredibly difficult to tell a serialized story
    0:26:50 over the radio in the form that they did it.
    0:26:52 And secondarily to that,
    0:26:55 they told that story in real, in semi-real time.
    0:26:56 And that’s something that they sort of looked
    0:26:59 at the structure of what the distribution format was
    0:27:00 and they go, we’re gonna try that out,
    0:27:01 we’ll see what happens.
    0:27:03 And so this is a little bit
    0:27:06 of like them playing perfectly to the form there.
    0:27:07 And I wanna sort of go back a little bit
    0:27:10 to the point about like the second screen experience
    0:27:13 and the sort of the death of the water cooler.
    0:27:14 So I love second screen experiences.
    0:27:17 I live for NBA Twitter, I live for Bachelor Twitter,
    0:27:21 but I gotta say, I do like that experience
    0:27:25 with physical people and that I miss hanging out
    0:27:26 and watching TV with my friends sometimes
    0:27:28 at the same pace, that’s all I got to say.
    0:27:30 – I just think like ever since DVR arrived,
    0:27:32 like we kind of lost it already.
    0:27:34 – I think you guys are both being very falsely nostalgic
    0:27:37 for a past that never was because I actually think,
    0:27:40 I mean, yes, there’s a reality to be physically present.
    0:27:43 But again, we’re in the early innings with all of this.
    0:27:45 We’re investors in a company called Big Screen
    0:27:48 where you can essentially share in this ambient intimacy,
    0:27:51 like hang out in VR, like when there is a digital overlay
    0:27:54 over the physical world, just like people connect on Twitter
    0:27:57 for ambient intimacy, the cocktail party of the web,
    0:27:59 there will be a physical like experience
    0:28:01 that you have similar level of satisfaction
    0:28:03 and hanging out in real time with your friends.
    0:28:04 And it’s just an artifact of technology
    0:28:05 that we’re not 100% there yet.
    0:28:06 That’s what I would argue at least.
    0:28:08 But back to the binge watching thing,
    0:28:11 I was gonna add that when a season drops all at once,
    0:28:12 I add it to my playlist, but I never watch it
    0:28:14 because what’s also missing in this space,
    0:28:16 and this is again why I love the idea of binge watching
    0:28:20 slash listening for podcasting, is the concept of virality.
    0:28:22 The viral hits don’t happen instantly
    0:28:23 unless you’re like a Joe Rogan experience
    0:28:25 and Elon Musk smoking pot on air.
    0:28:27 Like it’s sort of a cult of personality show,
    0:28:29 it’s slow burn type of virality.
    0:28:30 And so seeing what people are talking about
    0:28:34 and what resonates is hugely important for creators,
    0:28:35 not because you freaking want to crowdsource
    0:28:37 what you want to say, but you do want to know
    0:28:38 it doesn’t go in a black hole.
    0:28:40 – I would love a world where in the future
    0:28:42 you’ll know which parts of the podcast
    0:28:44 the audience like the most.
    0:28:45 – My proxy for that, by the way,
    0:28:47 is I do Twitter searches all the time for the commentary.
    0:28:49 So it’s a very skewed sample, but it’s helpful.
    0:28:52 And I push the editors to do this to close this loop,
    0:28:53 even if they’re not active on Twitter,
    0:28:56 because there was no other way to see what resonated.
    0:28:59 – But can’t you see like a platform just like saying,
    0:29:01 tap your screen if you like this part?
    0:29:01 – Oh, totally.
    0:29:02 Well, I don’t know if this is public.
    0:29:03 Do you know this, Nick?
    0:29:07 But is doing screen shot, audio shots of podcasting?
    0:29:09 – Yeah, I love this, yeah.
    0:29:10 – Is it public, do you know?
    0:29:12 Okay, but there will be sort of podcasts,
    0:29:14 sort of screen shotting and sort of audio clips.
    0:29:17 And I’m curious to see with or without
    0:29:18 the transcript, Connie, to your point
    0:29:19 about the importance of that,
    0:29:21 whether those will go viral.
    0:29:23 – It’s crazy to me that these things
    0:29:27 don’t have automatic transcription on the top hits.
    0:29:29 Like that’s such an easy technical thing to do.
    0:29:31 And for a listener, that would mean
    0:29:33 that I don’t have to just pause and say like,
    0:29:34 oh yes, remember, like go back
    0:29:37 to the one minute 30 mark later on and take notes.
    0:29:38 – Well, I actually love that too,
    0:29:40 because one of the biggest limitations of podcasting
    0:29:42 is the lack of a quote screenshot equivalent.
    0:29:44 – But that exists in China already.
    0:29:46 Not only can I see the transcript,
    0:29:48 I can then comment on it and I can make it
    0:29:50 so only my friends can see it
    0:29:51 or I can make it so the entire public can see it.
    0:29:52 And then there’s a discourse.
    0:29:53 – That’s amazing.
    0:29:54 Right now we have to manually upload transcripts.
    0:29:56 – And you basically have redded conversations
    0:29:58 around parts of your podcast.
    0:30:00 And so it’s okay if the listener doesn’t even get to the end
    0:30:01 ’cause you can have a highlight speed,
    0:30:05 all kinds of stuff right now that we just are not doing.
    0:30:07 And so I think this is like where the platforms
    0:30:09 can get much better at creating.
    0:30:12 Like even if they just chunked up the best clips, right?
    0:30:13 Or maybe you as the creator,
    0:30:15 you can like throw out which clips you think are the best.
    0:30:19 Make it easy for them to repost on other social mediums
    0:30:21 or make us like background music to whatever.
    0:30:23 – You can do that actually now on some of these tools,
    0:30:25 but to your point, it’s fragmented.
    0:30:26 It’s not central on a single user experience.
    0:30:28 – Fragmented and I think like the main platforms
    0:30:29 don’t allow that, right?
    0:30:33 – Currently no, Spotify and iTunes and others don’t.
    0:30:35 In fact, this is again where the ecosystem is so fragmented
    0:30:36 ’cause the side players are,
    0:30:38 there’s a whole budding ecosystem of tools
    0:30:39 that are doing this kind of thing.
    0:30:41 – So again, like it goes back to like,
    0:30:43 you know, like likes and comments and payments,
    0:30:46 like on tips like that’s just like a form
    0:30:48 of showing how much you like something.
    0:30:51 Creators don’t know which pieces of their podcasts
    0:30:52 were the best parts of the episode.
    0:30:53 They don’t know where that ends for it.
    0:30:54 – They don’t know any of it, it’s a black hole.
    0:30:57 But on the metrics, I do wanna say that one of my favorite
    0:30:59 analytics for podcast success,
    0:31:01 ’cause I do think that we need to think about
    0:31:03 what you’re measuring for, for the type of show you are.
    0:31:06 And in our case, what I care about as editor for the show
    0:31:09 is insights per minute.
    0:31:10 And this is the same thing as insights per inch
    0:31:14 in terms of like going down a verbal post.
    0:31:16 Because when you have a brand collective
    0:31:19 and not a cult of personality driven show,
    0:31:21 this is again where the metrics for the type of show
    0:31:23 need to vary as well in my view.
    0:31:24 For our kind of show,
    0:31:26 if you’re not like a famous personality,
    0:31:28 then the insights per minute matter a lot
    0:31:31 to get people to stick and stay.
    0:31:34 And then secondly, when you think of audience discovery,
    0:31:36 audience and movements of people and fans
    0:31:39 aggregating around a piece of content,
    0:31:44 then I care about if a show has say a drop off halfway,
    0:31:45 as a drop off point,
    0:31:48 if the first half are people who are mainstream interested
    0:31:50 in learning about quantum computing,
    0:31:52 and then they drop off 50%,
    0:31:54 I consider that a huge metric of success.
    0:31:56 And if the remaining 50% that stick around,
    0:31:59 a much smaller subset of people who are developers
    0:32:01 in quantum computing are interested in building
    0:32:03 quantum computing are physicists,
    0:32:05 then that’s a huge metric of success.
    0:32:07 So for me, again, this is again another granular way
    0:32:09 of thinking about the type of show,
    0:32:11 the type of content, et cetera.
    0:32:12 Now we can’t do any of this right now,
    0:32:13 but as we introduce new storytelling
    0:32:15 and forums and podcasting,
    0:32:16 I think we’ll be thinking a lot more differently
    0:32:18 than the obvious on those fronts too,
    0:32:20 and about podcast engagement.
    0:32:22 Which by the way, one quick factoid for you guys,
    0:32:24 the number one thing I hear from all of the publisher network,
    0:32:26 ’cause one of the things that I did when I came here
    0:32:28 was reach out to various people to beg them
    0:32:29 to put their authors on the podcast.
    0:32:31 So before authors became,
    0:32:33 like going on podcasts became the thing to do.
    0:32:36 And yeah, there’s nothing that moves books
    0:32:37 the way podcasts do.
    0:32:40 I’ve heard this over and over and over again
    0:32:42 from all of my publishing industry friends.
    0:32:43 – I heard the exact same thing.
    0:32:45 The way that the podcast experience
    0:32:48 is currently constructed, it drives sales.
    0:32:51 But the question is, is that when other platforms
    0:32:53 or when the experience changes
    0:32:57 due to technical innovations or new features added,
    0:32:59 would it fundamentally change that relationship?
    0:33:02 Will there be the same kind of sales push
    0:33:04 that we experience right now?
    0:33:05 I think it’s an open question.
    0:33:07 – I think it’s a totally work.
    0:33:09 I mean, like to me, it’s like the same way QVC
    0:33:10 is a great way to sell stuff.
    0:33:12 Like podcasts is a great way to sell content,
    0:33:14 written content that people don’t want to read.
    0:33:16 But I think this is a bigger problem
    0:33:18 with the book publishing industry.
    0:33:20 Meaning that they’re not selling books
    0:33:21 in an internet native way.
    0:33:24 There’s no great way to figure out the highlights of a book.
    0:33:26 There’s no way for me to read the first chapter for free.
    0:33:28 There’s no way for me to like get a sense of,
    0:33:31 do I want to pay for this entire book?
    0:33:33 – I do that all in a bookstore.
    0:33:34 We’re just skimming though.
    0:33:35 I mean like–
    0:33:37 – In a physical bookstore, yes.
    0:33:39 In a physical bookstore, you can do all these things,
    0:33:41 but on Amazon, you still can’t.
    0:33:42 – Right, this is another way where I think
    0:33:44 we’re not thinking of the native medium
    0:33:47 because it’s crazy to me that books,
    0:33:49 which are self-contained with no context,
    0:33:51 are still decoupled in audio book form.
    0:33:53 And it’s equally crazy to me that podcasting
    0:33:56 because of the structural limitation of the feed pipes
    0:33:59 don’t actually have context built into them
    0:34:00 where you can actually tie a podcast
    0:34:02 into the context of a broader show,
    0:34:04 more by this author, more on the topic,
    0:34:06 to your point about PDFs and show notes
    0:34:07 and related materials.
    0:34:09 It’s crazy to me that there isn’t a web link ecosystem
    0:34:10 for podcasting yet.
    0:34:12 – Because none of this stuff is being sold
    0:34:14 in an internet native way.
    0:34:16 I just think like right now, the way we sell books,
    0:34:18 it’s like if you had no movie trailer
    0:34:21 and you only had the movie poster, right?
    0:34:23 – It depends on the movie poster.
    0:34:25 You’re like buying the book based off the cover
    0:34:28 and maybe some quotes by people who’ve read it,
    0:34:31 but you don’t get to even see the trailer.
    0:34:34 And this totally actually skews the creator’s incentive
    0:34:35 for what kind of content to create.
    0:34:38 So like for a book, like are you gonna pay $20
    0:34:40 for like a 20 page book?
    0:34:42 Or will you feel better about paying $20
    0:34:44 for like a 170 page book?
    0:34:46 And then authors might have to write extra words
    0:34:48 for the sake of selling a, you know–
    0:34:50 – Well, that reminds me of the early days
    0:34:52 of Charles Dickens where he was paid by the word
    0:34:53 and that was like a funny artifact
    0:34:55 of the way the monetization was happening.
    0:34:57 But I would argue on the flip side of that,
    0:34:59 on the creator side, I think it’s more important
    0:35:01 to find your community because a beautiful thing about,
    0:35:03 again, podcasts are movements.
    0:35:05 Groups of people following either a show
    0:35:08 or an episode or a topic, serial fans, whatever it is.
    0:35:11 And so when you have thousand true fans
    0:35:13 in the Kevin Kelly phrase that are following
    0:35:16 a particular book author or a particular topic
    0:35:19 or a particular podcast, in our case,
    0:35:21 what we’re doing is we’re mobilizing the fan base,
    0:35:22 not because of that author,
    0:35:25 but because of the way that we do our take with that author.
    0:35:27 Like it’s sort of the A6 and Z take on it.
    0:35:29 So when we did Yuval Harari, it was me and Kyle
    0:35:31 talking to him about all kinds of random stuff
    0:35:33 that was probably not even related to his book.
    0:35:35 The point is that it’s a way to mobilize your movement,
    0:35:36 your fan base.
    0:35:37 And this goes to Nick’s earlier point about Patreon
    0:35:40 and fan bases or Mark Orman’s point
    0:35:41 about brand as intimate connection.
    0:35:44 – So my theory on this whole,
    0:35:46 this sort of notion of like what people will pay for it,
    0:35:48 people will pay as much for a thing
    0:35:51 based on how valuable they think the thing is.
    0:35:53 And so it’s equally plausible that a person looks
    0:35:56 at a 20-page book and thinks it’s worth $20
    0:35:58 as it is that a person looks at a 170-page book
    0:36:00 and thinks that they will pay $20 for that.
    0:36:02 It really depends on how that person
    0:36:05 or how it’s messaged to this consumer what value is, right?
    0:36:08 And so this ties back a little bit to the notion
    0:36:10 of advertisers and analytics.
    0:36:12 Analytics, as constructed by a technology company,
    0:36:14 by a platform, by a data team,
    0:36:16 is an effort to tell the advertiser
    0:36:19 this is how valuable you should think this is.
    0:36:20 And in the art world,
    0:36:23 value is constructed in a whole different amorphous way.
    0:36:26 And so I think it’s not a one-to-one objectivity
    0:36:27 of what is the right metric
    0:36:30 or how do we find the truth of the value of a certain thing.
    0:36:32 These are socially constructed things.
    0:36:35 And so I think that should be a consideration
    0:36:36 when it comes to when we think about it,
    0:36:37 even the book publishing industry.
    0:36:39 I should argue that celebrity books
    0:36:40 should be priced a lot higher than it is,
    0:36:42 but that’s just me.
    0:36:44 – Books is just one example, though.
    0:36:46 Like if you think about like a YouTube video,
    0:36:49 like the creator is incented to make it long enough
    0:36:50 so you don’t put just what pre-roll ad,
    0:36:52 but also put like another ad in the middle,
    0:36:54 which means the video has to be long enough
    0:36:57 to have enough gap time between the ads, right?
    0:36:59 – Really, because the most popular videos on YouTube
    0:37:01 that do really well are the short, quick takes,
    0:37:03 or tutorials, or like in those cases,
    0:37:05 it’s another example of,
    0:37:05 I mean, I think that’s the reason why
    0:37:07 tutorial culture is taken off
    0:37:08 because people are self-selected
    0:37:09 into like learning about X, Y, or Z.
    0:37:12 – But like some creators will lengthen their videos
    0:37:14 so they can put in a second ad.
    0:37:17 – Yeah, I think those to me are the more old-school creators
    0:37:19 that are doing that to monetize in that way.
    0:37:21 They’re not the ones who are the influencer creators
    0:37:23 because the influencer creators have their eye
    0:37:24 in a much bigger ballgame.
    0:37:27 They’re looking at moving their own freaking makeup lines.
    0:37:29 Or like, you know what I mean?
    0:37:30 Or like other things, but yes,
    0:37:33 that is sort of like the early phase of every platform
    0:37:36 and medium is that you have a quick way
    0:37:38 to kind of game it to get what you need.
    0:37:41 But I don’t know if that works for the long-lasting players.
    0:37:44 – YouTube in that situation is the arbiter of like
    0:37:47 how, of the data that tells advertisers what to value,
    0:37:49 but it’s also the arbiter of the data that tells creators
    0:37:52 how to value the way that they’re creating something.
    0:37:54 It also becomes a situation where YouTube
    0:37:57 is the thing that interprets human behavior
    0:38:00 and makes assumptions based on those interpretations
    0:38:01 as to what people are valuing.
    0:38:04 And so this is like YouTube sort of defining that reality
    0:38:06 and pulling levers in a bunch of different ways.
    0:38:10 And they may be correct, they may not be correct.
    0:38:12 In any case, it’s all a proxy of reality
    0:38:13 that may or may not be aligned.
    0:38:14 We don’t know necessarily.
    0:38:14 – I agree.
    0:38:16 I agree it’s socially constructed and value is created
    0:38:19 and a lot of it is limited by the tools people have
    0:38:21 for thinking about pricing and they have heuristics
    0:38:22 for doing that based on those directors.
    0:38:24 I would also say that there’s a really interesting
    0:38:25 opportunity, especially with podcasts,
    0:38:28 to flip the model where fans get paid.
    0:38:31 And in fact, Kevin Kelly made this really interesting
    0:38:33 argument in his book, Inevitable,
    0:38:34 about how when you swap your paradigm
    0:38:39 for thinking about attention in an abundant software world,
    0:38:40 which is what we’re talking about here,
    0:38:42 abundant digital world bits are infinite.
    0:38:44 There’s no limit on airwaves in this context.
    0:38:47 You can actually flip the model where fans
    0:38:48 can monetize their attention.
    0:38:50 So you actually reorient,
    0:38:52 and this is actually the premise of crypto, right?
    0:38:53 Or one of the premises of crypto,
    0:38:54 at least in the notion of crypto networks,
    0:38:58 where right now the locus of data controls the platforms.
    0:38:59 With crypto, you can actually invert that
    0:39:02 where you are the user is a container of the data.
    0:39:03 So if you think about this in the context
    0:39:06 of media creation and podcasting,
    0:39:08 how interesting to think about a fan monetizing
    0:39:09 their attention because if a fan is a sum
    0:39:11 of all the shows they watch,
    0:39:13 maybe an advertiser wants to buy that fan
    0:39:14 and the fan directly monetizes.
    0:39:15 That’s that attention.
    0:39:16 I know that sounds crazy,
    0:39:18 but I don’t think that’s impossible in a world like this.
    0:39:19 You guys are looking me like that.
    0:39:21 – I just think if platforms can do that,
    0:39:24 like there’s all the stuff they need to experiment with
    0:39:26 before they even can get to something like that.
    0:39:26 – Yeah, yeah.
    0:39:28 That is if you believe it has to go stepwise
    0:39:29 ’cause sometimes technologies can leap.
    0:39:30 I agree with you.
    0:39:31 I think it’ll be in the middle.
    0:39:33 – I’m like, if we can’t even get subscriptions or tips up.
    0:39:35 – We can’t even get downloads for fuck’s sake.
    0:39:36 – All right, I’m gonna do another quick,
    0:39:38 I wanna hear your quick lightning round take
    0:39:39 on interstitials and podcasting.
    0:39:40 Any thoughts on that?
    0:39:42 The idea of like, you know, title slides or breaks
    0:39:44 or segmentation, et cetera.
    0:39:46 – I’m pro interstitials.
    0:39:48 Like, you know, it’s really important
    0:39:51 to orient your audience to teach them
    0:39:52 how to listen to a thing.
    0:39:53 It’s an important creative tool.
    0:39:55 That’s a my view on it.
    0:39:57 – Connie, I feel like you have a lot of thoughts on this
    0:39:59 ’cause it feels so China native what people do and–
    0:40:00 – Describe more what you mean by interstitials.
    0:40:01 – I mean, more just like,
    0:40:03 it’s kind of to your point about there being granularity.
    0:40:06 Like you can actually break up a show into sub parts
    0:40:07 by having little breaks or–
    0:40:09 – I think interstitials is great because again,
    0:40:12 it allows me to show you which parts of your episode
    0:40:14 I value the most and which ones I’m willing to pay for.
    0:40:15 – Yeah, for me, I will say that’s,
    0:40:18 we tried some early experiments with segmentation
    0:40:20 because I got this funny feedback from people
    0:40:23 that they’re like, I listen to the podcast on the road
    0:40:24 and my commute’s 10 minutes.
    0:40:26 I wish they were 10 minutes long.
    0:40:27 And then someone else was like, my commute’s 20 minutes.
    0:40:28 I wish you were 20 minutes long.
    0:40:30 And then someone else was like, my commute’s 30 minutes
    0:40:32 or 40 minutes and they have this ideal time.
    0:40:35 For us, at least 30 minutes has been a sweet spot
    0:40:37 in terms of like the ideal podcast size.
    0:40:38 But I don’t think there’s a rule of thumb
    0:40:41 because some of our most popular episodes are an hour.
    0:40:43 And also 20 minutes so I don’t know.
    0:40:45 But I did because of that.
    0:40:47 I wanted kids on campuses like at Stanford or wherever
    0:40:49 to have a way of listening to an episode
    0:40:51 and kind of have like a nice natural stop-off point
    0:40:53 ’cause when you’re watching a show,
    0:40:54 the ability to kind of pause.
    0:40:56 So to me, interstitials are a way of creating
    0:40:58 a little bit of those moments and breaks.
    0:40:59 But then what I realized is that
    0:41:01 as an artifact of this industry,
    0:41:03 all the tools save your spot
    0:41:05 in where you were playing last in your player.
    0:41:07 Yeah, and so it kind of became a moot point.
    0:41:09 So that experiment didn’t really work.
    0:41:11 But the driver for it is this thesis
    0:41:15 that Dixon says the internet’s made for snacking.
    0:41:17 And podcasts can be beautifully long form,
    0:41:19 but I also think that there’s a consumption mode
    0:41:21 and very short micro-awaiting moments
    0:41:24 to use a term from a park paper on this concept
    0:41:25 that when you’re waiting in line,
    0:41:27 can you listen to a quick bite of content?
    0:41:29 Not just watch something on your thing,
    0:41:31 not just listen to it.
    0:41:32 Super interesting.
    0:41:35 Yeah, and I wonder if we can fill micro-awaiting moments.
    0:41:36 And so I wonder if interstitials
    0:41:37 would play an interesting role
    0:41:38 as a micro-awaiting moment.
    0:41:40 To do that, I feel like you need really good discovery.
    0:41:42 Oh yeah, because the likelihood of me
    0:41:44 finding something, like hitting something
    0:41:47 that I don’t like causes this fear in the listener.
    0:41:48 Of course, unless you are then,
    0:41:50 which currently is a model,
    0:41:52 following a show or a personality.
    0:41:54 You just have to have so much trust
    0:41:56 that it’s gonna spin up the right thing.
    0:41:57 Because right, ’cause in the cult of personality model,
    0:41:58 people are following the person,
    0:42:00 not necessarily the guests.
    0:42:02 I’ll just say that the notion of short form audio
    0:42:04 is one that’s constantly talked about.
    0:42:06 It’s also, this is another reminder,
    0:42:09 like what anchor essentially attempted to do
    0:42:10 at the very beginning of the journey
    0:42:12 and what audio tried to do.
    0:42:16 And it’s one of those things where it didn’t,
    0:42:17 both for those iterations, didn’t quite work.
    0:42:20 We don’t know if it has anything to do with what people want
    0:42:23 or if it’s the case that people were not ready for that yet.
    0:42:24 I would argue the last one,
    0:42:26 because we have seen over and over with technology,
    0:42:28 there’s like five Facebooks
    0:42:29 before there’s a Facebook that works.
    0:42:31 I subscribe to the view of the world
    0:42:33 in which human beings are generally plastic.
    0:42:35 And so you could force a human being
    0:42:36 to accept just about anything.
    0:42:39 And so it’s a question of whether they are,
    0:42:42 whether the right startup or the right platform
    0:42:43 executes the right experiment
    0:42:45 at the right time with the right group of people.
    0:42:45 That’s just kind of how these things work.
    0:42:48 – Yeah, human beings are creators of emergent behaviors
    0:42:49 because this is where you can never predict
    0:42:51 the second order effects of new mediums, right?
    0:42:53 Like Twitter spawned all kinds of interesting
    0:42:55 emergent behaviors and that is the fundamental truth
    0:42:57 of the evolution of all kinds of technologies.
    0:42:58 – But it’s all technically,
    0:43:01 I mean, this is not like cutting edge science
    0:43:03 or technology that doesn’t exist yet.
    0:43:06 It’s just a platform hasn’t put all of these things in place.
    0:43:10 But the fact of the matter is that stuff like social audio,
    0:43:14 stuff like Anchor’s initial bit to be the Twitter of audio,
    0:43:17 the stuff like audio, which is what Twitter was
    0:43:18 before Twitter became Twitter,
    0:43:20 which is essentially for audio,
    0:43:25 is that we need proof that the consumer side
    0:43:28 will lead the way that it will stick with them.
    0:43:29 – But I think that’s the problem, right?
    0:43:31 If we’re waiting to have like survey data
    0:43:32 to see if this works,
    0:43:34 then no platform is gonna experiment on it.
    0:43:38 And this is why like new startups and new platforms
    0:43:40 need to experiment with how to engage with podcasts.
    0:43:43 I think it’s like a given that everyone would prefer
    0:43:45 to have no ads in their podcasts.
    0:43:48 And that’s why it’s up to all the platforms
    0:43:50 to figure out how to create the tools
    0:43:52 so creators can still make money
    0:43:54 and make better money than I think what they’re making now.
    0:43:57 I actually think creators are vastly underpaid in podcasts
    0:43:59 and it’s up to the platforms to figure out
    0:44:00 how to help them monetize
    0:44:03 so we can get ads out of the podcast itself.
    0:44:05 – I don’t think we’re disagreeing.
    0:44:06 I think we’re sort of like coming at it
    0:44:07 from opposite directions here
    0:44:08 because my number one principle
    0:44:09 when I’m thinking through these things
    0:44:11 is that no matter what happens
    0:44:13 in terms of feature development,
    0:44:14 and no matter what happens to those
    0:44:16 of whether certain platforms or tools
    0:44:18 ends up innovating on these fronts
    0:44:20 is whether creators themselves end up controlling
    0:44:21 their destinies in this situation
    0:44:24 and whether they control the means of distribution.
    0:44:26 Like the entire wave,
    0:44:28 the entire learnings of what happened of YouTube
    0:44:30 and YouTube creators really haunts a lot of the people
    0:44:33 that I speak to when I report week in week out.
    0:44:36 That is the nature of the platform being capricious
    0:44:38 and altering the way that they expect
    0:44:40 their certain revenue projections over time.
    0:44:44 And so I’m personally all for the ability
    0:44:46 to create better tipping structures
    0:44:50 to streamline Patreon and direct revenue sort of pathways
    0:44:52 straight into the listening point.
    0:44:55 But the fact of the matter is that all these pieces
    0:44:58 connecting the listener to the creator
    0:45:00 are all gonna be controlled by other people.
    0:45:02 And I think this is the nature of things
    0:45:06 that brings the most anxiety to the creator class right now.
    0:45:07 Of course, the creator class would change over time
    0:45:10 with changing expectations of how these things should work.
    0:45:11 – Connie, I’m hearing you say
    0:45:12 that there’s huge experimentation
    0:45:14 that’s already happening in China
    0:45:16 that we’re not even remotely seeing here.
    0:45:18 That is also a case, however, where we have platforms
    0:45:21 because to the point of tipping as an example,
    0:45:23 Nick also mentioned Patreon is a good thing,
    0:45:26 but clearly one of the big structural limitations in the US
    0:45:28 is that people don’t obviously always
    0:45:30 have their credit cards linked
    0:45:31 and the way that you have in WeChat
    0:45:33 or like that we’ve talked a lot about on the podcast.
    0:45:34 – But like Apple Pay, right?
    0:45:36 Or like in app payments.
    0:45:37 – Right.
    0:45:39 – Like people oftentimes will say like,
    0:45:40 oh, our payment infrastructure
    0:45:41 is why none of this stuff would work in the US.
    0:45:42 – But you’re saying that’s not true.
    0:45:43 – And I don’t agree with that.
    0:45:44 – You’re saying that’s a cop out.
    0:45:45 Okay, that’s fair.
    0:45:47 So then maybe tipping needs to be done
    0:45:47 at a more micro level.
    0:45:49 – It’s not even just the money.
    0:45:54 It’s also helping creators see who their real fans are.
    0:45:56 – You want the 1,000 true fans.
    0:45:58 – And right now it’s like a one-way conversation.
    0:45:59 Like why can’t the platforms
    0:46:01 that allow you to listen to podcasts
    0:46:04 also allow me to record a quick message back to you.
    0:46:06 And then also like use algorithms
    0:46:08 to figure out which comments are valuable or not.
    0:46:10 – Yeah, I think we agree in that sense.
    0:46:11 Like platforms should basically do more
    0:46:12 for their users and experiment.
    0:46:14 I also agree with Nick though
    0:46:16 on the point that he’s raising.
    0:46:18 I don’t like the assumption going right to platforms
    0:46:20 as the default owners of this
    0:46:22 and the default aggregators of this.
    0:46:24 And this kind of goes to Ben Thompson
    0:46:26 who writes about aggregation theory a lot,
    0:46:28 which is just a fancy name for network effects
    0:46:29 in a lot of ways.
    0:46:30 I mean, he’s very much more nuanced,
    0:46:31 but it is at the end of the day,
    0:46:33 the tension between centralization,
    0:46:35 between bundling and unbundling,
    0:46:37 and these cycles that constantly go back and forth
    0:46:38 and waves.
    0:46:40 – Yeah, especially with the YouTube platform.
    0:46:42 Like you look at how the influencers
    0:46:44 who started YouTube channels 10 years ago,
    0:46:46 they have massive followings now.
    0:46:48 – Yeah, and they’re dependent on YouTube,
    0:46:48 which is Nick’s point.
    0:46:50 – Yes, but also it makes it really hard
    0:46:53 for a newcomer to come in and create a YouTube channel
    0:46:55 and get to that one million subscriber count, right?
    0:46:57 And in the similar way, like even now,
    0:46:59 I hear about so many friends even starting podcasts.
    0:47:02 – Oh yeah, it’s very competitive.
    0:47:04 Like there are people who barely get
    0:47:07 to 10,000 listens per episode and that’s insane.
    0:47:09 – And it can get more competitive, right?
    0:47:10 – Yes, very crowded.
    0:47:12 – And so that’s why I think all these new platforms
    0:47:14 are kind of interesting because as they try
    0:47:16 and pick off creators to have them exclusive
    0:47:19 to their platform, this dynamic may change.
    0:47:20 But it’s really interesting ’cause like for video,
    0:47:22 it was like winner-take-all.
    0:47:23 – Which is not true in podcasting.
    0:47:25 So I’m curious then for your guys’ take,
    0:47:27 because back to the point of centralization
    0:47:29 is to give people a better user experience
    0:47:33 and choice and variety and ease of use.
    0:47:36 What do we think about the moves of Spotify
    0:47:39 and Apple in this space, especially given Spotify’s news
    0:47:41 a few weeks ago of acquiring Gimlet?
    0:47:43 – So I think the necessary background here
    0:47:45 is that for the longest time,
    0:47:47 Apple has been a primary distributor of podcasting.
    0:47:51 It used to be somewhere upwards of like 80%.
    0:47:55 We believe it’s now somewhere between like 60 to 75 maybe.
    0:47:58 But with today’s infinite dial, so studies,
    0:48:01 it suggests that Spotify has grown their particular share,
    0:48:04 but we’re nowhere seeing like 50/50 parity or something.
    0:48:06 We’re just not seeing that just yet.
    0:48:09 And so Spotify, the business case for Spotify
    0:48:12 going to podcasting or spoken audio at large
    0:48:13 is pulling their business model away
    0:48:16 for being completely tethered to the dynamics
    0:48:18 of the music industry.
    0:48:20 Which is to say a music industry that’s very,
    0:48:22 that’s been very costly for them to play in
    0:48:25 and it’s been very costly for a lot of music platforms
    0:48:29 to try to come in and take over essentially distribution power
    0:48:30 from the music labels.
    0:48:33 And so Spotify looked in the situation and go,
    0:48:36 we see a category of content here
    0:48:39 that is significantly cheaper, that is still unwieldy
    0:48:40 and it’s still untamed.
    0:48:42 And we can try to figure out our place in that world
    0:48:45 and sort of push us off the narrative
    0:48:46 of just being a music company
    0:48:48 and giving ourselves other avenues of growth.
    0:48:50 – And that impacts like the company’s branding
    0:48:51 and positioning, right?
    0:48:53 It’s no longer seen as just a music company
    0:48:56 but like an audio destination for all kinds of audio.
    0:48:57 – Absolutely.
    0:49:00 – And in that same way that Spotify was also known
    0:49:02 for helping you discover stuff you like.
    0:49:04 I think this is also a reflection they’re realizing
    0:49:06 like podcasting has gotten so large
    0:49:08 in terms of how many new creators are jumping in.
    0:49:12 – Can you guys address the exclusive shows angle?
    0:49:14 – I actually see both models working really well.
    0:49:16 I think if you have a platform
    0:49:18 where anyone can submit a podcast, that can be great.
    0:49:19 You can have long tail creators.
    0:49:21 But I also think a podcast that says,
    0:49:24 “Hey, I’m going to curate the top two, 300 podcasts,”
    0:49:25 can also work really well too.
    0:49:27 Both have great monetization potential
    0:49:30 if they want to be niche or just long tail.
    0:49:31 – Yeah.
    0:49:34 And so, I mean, we have a couple of situations
    0:49:36 that’s probably, that’s pretty interesting right now.
    0:49:39 So there’s been a paid podcasting attempt
    0:49:41 for quite some time called Stitcher Premium.
    0:49:42 It’s a sort of exclusive layer
    0:49:46 on top of a fairly popular third party podcast
    0:49:48 I have called Stitcher, which is part of Mintroll.
    0:49:49 And earlier this week,
    0:49:51 I saw the formal announcement of a company called Luminary
    0:49:53 that’s attempting to be,
    0:49:57 they literally use the tagline sort of Netflix for podcasts,
    0:49:58 which is going to be difficult
    0:50:00 because the primary challenge there
    0:50:03 is that they’re trying to build a catalog of things
    0:50:06 that you could argue has free alternatives
    0:50:07 almost everywhere else.
    0:50:11 But I have made this argument a couple of times before
    0:50:13 and I don’t think it’s stuck yet,
    0:50:15 but I think we should be looking at Headspace
    0:50:17 as a really interesting comp here.
    0:50:18 – What do you mean by that?
    0:50:21 – So Headspace essentially is an on-demand audio app
    0:50:23 that performs a very specific function
    0:50:25 that provides a very specific genre
    0:50:27 of on-demand audio content.
    0:50:30 It fits into one’s life in a very, very specific way.
    0:50:32 You know exactly what you’re paying for it
    0:50:35 and you can’t find quality alternatives elsewhere
    0:50:37 of that platform generally speaking.
    0:50:40 And so we’re in a situation where we,
    0:50:45 there is some lane here to build a paid podcasting platform.
    0:50:46 The question is like,
    0:50:48 will there be a really, really big one
    0:50:50 or will it be a series of smaller ones
    0:50:52 that ends up being bundled over the long run?
    0:50:53 And I think we are at the very beginning
    0:50:55 of beginning to answer that question.
    0:50:56 – Yeah, I agree.
    0:50:59 I would also say it does work for people in the know
    0:51:00 in terms of the history of podcasting
    0:51:02 in the recent past five years.
    0:51:05 I think I’ve seen versions of Netflix for podcasts
    0:51:06 and one of them I remember,
    0:51:09 I don’t even know if you remember this, Nick, is 60DB.
    0:51:11 – I do, acquired by Google.
    0:51:12 – Right, they got acquired by Google
    0:51:14 and I don’t know what Google’s doing inside.
    0:51:16 But the problem is like, it’s still a subscription, right?
    0:51:17 – Why is that a problem?
    0:51:18 I would love a subscription service.
    0:51:21 – But I think I would rather pay for a specific podcast.
    0:51:23 – Oh my God, yes!
    0:51:25 So my number one complaint.
    0:51:27 So everyone at A6 has either heard my whole thesis
    0:51:29 on this a million times, which is first of all,
    0:51:32 podcasting is such a homogenous word.
    0:51:35 We’ve defined it technically and in user experience,
    0:51:38 but when I think of the content side of podcasting,
    0:51:41 I like to split it into a simple taxonomy
    0:51:42 of three types of shows.
    0:51:43 There are personality based,
    0:51:46 what I call cultur personality based shows.
    0:51:48 You know, like the Azure Klein show, the Tim Ferriss show,
    0:51:49 and my God, by the way,
    0:51:51 most of them are named after male names.
    0:51:53 Let’s just go off on that one.
    0:51:56 Then the next category besides cultur personality shows
    0:51:58 is what I call like more collectives
    0:52:00 or like brands or voices of groups of people,
    0:52:02 which is what I would consider the A6 and Z podcast.
    0:52:05 And then the third show is a much more produced serialized
    0:52:07 like serial or narrative type of podcasting show.
    0:52:09 That’s a very loose broad taxonomy.
    0:52:11 But if you think of these three categories,
    0:52:13 discovery for each of them,
    0:52:15 it is so frustrating to me,
    0:52:17 again, going back to this containerization model,
    0:52:20 that discovery is limited at a show level.
    0:52:22 Again, structurally, it’s terrible.
    0:52:23 I keep bringing up structure
    0:52:25 because while everyone is so caught up
    0:52:27 in talking about discovery and monetization,
    0:52:29 they’re missing the big opportunity here,
    0:52:29 the bigger thing,
    0:52:32 which is defining a new unit of analysis
    0:52:34 of episodes versus shows
    0:52:36 and possibly even more granular units within that.
    0:52:37 I hate that we’re still stuck
    0:52:39 in the legacy ways of thinking about this.
    0:52:41 When we can bypass things with software,
    0:52:43 we don’t have to have the CD stage first
    0:52:45 to get to the individual song stage.
    0:52:47 And I also talk to analytics people all the time
    0:52:49 about how feeds limit what tools
    0:52:51 outside the big platforms can do,
    0:52:53 like not being able to tag podcasts by topic.
    0:52:55 Because I believe we all need the ability
    0:52:58 to find episodes, not entire shows.
    0:52:59 I like Berks and Birdwatching.
    0:53:01 I should be able to find any episodes on those topics
    0:53:02 regardless of show.
    0:53:05 Connie, you like real estate and crafts.
    0:53:07 You should be able to fucking find those topics
    0:53:09 and discover every single episode on those.
    0:53:11 But see, this is where a transcription and tagging
    0:53:14 and just a much smarter internet native way
    0:53:19 of displaying podcasts makes all of that automatic.
    0:53:21 There is no technical reason
    0:53:24 why we cannot automatically transcribe all the top podcasts.
    0:53:27 And again, I think subscription for an entire platform
    0:53:29 doesn’t necessarily make sense for podcasts.
    0:53:31 Like maybe it’s a good starting point.
    0:53:31 – It makes sense.
    0:53:33 – It’s a decent starting point.
    0:53:35 But hey, maybe you’re a podcaster
    0:53:37 and you’re only gonna create a couple episodes,
    0:53:39 but it’s really, really good content.
    0:53:41 Like why can’t you let people pay for that?
    0:53:42 And again, I think it’s not just about
    0:53:44 the money that’s getting transferred.
    0:53:46 The problem right now is like,
    0:53:48 there’s certain podcasts that I would happily pay for
    0:53:50 and a bunch that I would not pay for.
    0:53:51 – Yeah, exactly.
    0:53:53 – And right now these platforms don’t give you that option
    0:53:56 to say, hey, these are the ones that I ascribe more value to,
    0:53:58 much less even to say I like this one or a comment
    0:53:59 or anything.
    0:54:01 – I mean, right, well, you’re also looting at the,
    0:54:02 when you talk about the transcription of shows though,
    0:54:05 is like, and this is obviously another key point of discovery
    0:54:07 is it goes again parallel to the web.
    0:54:08 There was a curated links phase
    0:54:10 that preceded the portal phase
    0:54:11 that preceded the search phase.
    0:54:12 – Give it a couple of months
    0:54:13 ’cause Google is working on that
    0:54:16 and they are beginning to beta test all of that
    0:54:17 in terms of transcriptions,
    0:54:19 in terms of whether a podcast shows that
    0:54:22 or audio at large shows up in the search engines.
    0:54:25 – But they’re not even gonna have all the podcasts, right?
    0:54:26 The exclusive podcast on Luminary,
    0:54:28 Google’s not gonna have.
    0:54:29 – Well, then that’s Luminary’s problem
    0:54:31 at the end of the day.
    0:54:34 Like, I think Google’s situation is
    0:54:36 that they’re gonna pull in the RSS feeds
    0:54:39 or they’re gonna pull in podcasts
    0:54:42 that exist on the open sort of ecosystem
    0:54:43 and they’re gonna transcribe it
    0:54:45 and they’re gonna index it within the search engine.
    0:54:45 – I guess what I’m saying, like,
    0:54:49 rather than rely on Google as the search engine to do it,
    0:54:52 at least very basic transcription and search,
    0:54:55 all the platforms should be able to do it themselves.
    0:54:57 And like, imagine all the other stuff
    0:54:57 you’d like to talk on to it.
    0:54:59 Like, hey, maybe in addition to the podcast
    0:55:02 on podcast today, you have like five links
    0:55:04 that the listener can go in and click on.
    0:55:05 – Click while you’re playing.
    0:55:08 I would love the ability to embed a link natively
    0:55:10 instead of in the show notes.
    0:55:12 – Or a PDF that you can then charge more money for, right?
    0:55:13 Like, hey, to read more.
    0:55:16 Or maybe like all the like parts that you cut out.
    0:55:18 Like those special clips.
    0:55:22 Maybe someone pays like a dollar to untap it, right?
    0:55:25 – I agree, I would love to pay for stuff
    0:55:27 that I want, but it’s a situation.
    0:55:29 I mean, look, I’m just a normal person
    0:55:31 that has like normal finances.
    0:55:32 I don’t think I’m going to spend
    0:55:35 more than X amount of money per month on entertainment goods.
    0:55:37 – I agree that people aren’t going to spend
    0:55:40 like tons and tons of money on podcasts.
    0:55:43 But I think the better creators would get more rewarded
    0:55:45 for their content, which means new creators
    0:55:49 that don’t have, you know, crazy followings to begin with
    0:55:50 can still get paid.
    0:55:51 – No, I agree.
    0:55:54 But the question is like, I’ve heard the line of argument
    0:55:57 that it’s really hard to become a Patreon supporter
    0:56:00 or find a way to give you money to a creator
    0:56:01 that you really support.
    0:56:04 And I do wonder the nature of that assumption.
    0:56:06 There’s only so much frictionless,
    0:56:08 so much attacking off the friction
    0:56:10 that we can introduce to that layer
    0:56:13 that we find what the maximum most efficient point of,
    0:56:16 you know, listener supporting creators ends up becoming.
    0:56:19 – Okay, but that is assuming that I want to support
    0:56:21 that specific creator.
    0:56:24 Maybe I only want a tip for that specific episode.
    0:56:26 Maybe I don’t actually want to give the tip to Sonal,
    0:56:29 but I want to give it to Connie and Nick, right?
    0:56:30 – That’s fucked up, but okay.
    0:56:31 – I mean, like, no, seriously,
    0:56:35 like the way that we are thinking about paying,
    0:56:37 it’s not necessarily the same person
    0:56:40 who’s speaking even on every podcast.
    0:56:44 And the fact that we aren’t able to more directly indicate
    0:56:46 and tie our money to the products
    0:56:48 that we truly, truly value,
    0:56:50 I just think that’s really lost opportunity.
    0:56:52 – Well, so let me push back on that a little bit, right?
    0:56:57 So the assumption here is that the show is made up of,
    0:57:00 that this show is made up of you, me,
    0:57:03 and, you know, and let’s say a producer,
    0:57:06 and let’s say, you know, a couple of people behind the scenes.
    0:57:10 But I think the reality is that most of the production
    0:57:13 structures constitutes a lot more people
    0:57:15 than the listener can ordinarily see.
    0:57:18 So what a listener, who a listener is moved to tip,
    0:57:19 doesn’t necessarily translate
    0:57:21 to who’s actually creating the content,
    0:57:23 because that’s a, there’s an entire,
    0:57:24 there’s an entire sort of conversation over here
    0:57:27 in terms of like, how listeners value the creators,
    0:57:29 how they sort of make assumptions
    0:57:30 about what they want to support,
    0:57:32 how they want to support, why they want to support.
    0:57:34 There’s a, there’s a huge, there’s a sort of,
    0:57:36 there’s a, there are a lot of gaps in information there
    0:57:39 to give all that power to listeners, I think.
    0:57:42 There still should be some middle point there
    0:57:43 in terms of how support works.
    0:57:45 – I’m not saying it can’t go to a show,
    0:57:48 but a show is, even then supporting a show
    0:57:50 is different than supporting a person.
    0:57:51 – I’m hearing both of you guys.
    0:57:53 I also hear that there is a lot more granularity you can do
    0:57:55 because we have an infinite web.
    0:57:57 And the fact that we define things as containers
    0:58:01 of a feed or a podcast or a show or an episode,
    0:58:03 these are all things we can redefine in this new era.
    0:58:05 And I agree it’s very early innings.
    0:58:07 I also agree so wholeheartedly
    0:58:10 that a thriving content ecosystem
    0:58:12 has to support its creators.
    0:58:13 And I know you’re arguing for that too,
    0:58:14 ’cause you’re arguing in this framework
    0:58:16 that people have more comments,
    0:58:18 they have more ability to interact with their top fans.
    0:58:20 You’re saying the same thing from a different angle,
    0:58:23 but from a pure business perspective
    0:58:25 in terms of being able to run a business
    0:58:26 that is based on podcasting,
    0:58:28 there does need to be a middle layer
    0:58:31 where creators can get the value they need.
    0:58:33 And for me, the open question, quite honestly,
    0:58:35 is whether the assumption or thesis
    0:58:36 that happened with blogging,
    0:58:39 and this is actually the initial premise of Anchor as well,
    0:58:41 which Spotify also acquired,
    0:58:43 is whether there will be now a new wave
    0:58:47 of mobile podcast creators who don’t have tools.
    0:58:48 And again, with tools like Descript,
    0:58:49 which democratize editing,
    0:58:52 with tools like just being able to record a podcast
    0:58:54 in your phone without having to have like a fancy
    0:58:56 Zoom recorder or mics.
    0:58:58 Like that is an open question to me.
    0:58:59 And I don’t know if people are really gonna listen to that
    0:59:02 because we have this discovery problem in the ecosystem.
    0:59:04 And yet there are a few centralized choke points
    0:59:05 that are coming up now,
    0:59:08 particularly iTunes, Spotify, Pandora, et cetera.
    0:59:11 By the way, on this notion of growing the podcast ecosystem
    0:59:13 and the total addressable market size,
    0:59:15 what do you guys make of radio here?
    0:59:17 ‘Cause that has its own set of structural and policy
    0:59:19 and regulatory considerations.
    0:59:21 I’m curious for your guys’ take on that aspect of it.
    0:59:24 – Well, I think the market size for podcasts
    0:59:27 is multiples larger than what it is today.
    0:59:30 And I do think it’s tapping into radio,
    0:59:32 but it’s also tapping into other things
    0:59:34 that do really well in the audio format.
    0:59:36 So like audio books that are self-published,
    0:59:39 for example, things that are related
    0:59:41 to the knowledge sharing market for adult learning,
    0:59:44 I think really, really work well for audio formats.
    0:59:46 There’s a lot of stuff where I don’t need to watch someone
    0:59:49 talking on YouTube with like a whiteboard,
    0:59:50 ’cause usually they don’t even really need
    0:59:52 a whiteboard, honestly.
    0:59:54 – Although there is a funny argument to be made,
    0:59:56 which is that people also listen to audio on YouTube.
    0:59:58 And in fact, Chris Anderson was telling me his son
    1:00:01 watches entire movies on YouTube in audio mode only,
    1:00:03 which I think is freaking fascinating.
    1:00:06 – I also just listen to movies on YouTube all the time.
    1:00:08 – I mean, yes, YouTube also works for audio.
    1:00:11 But I mean, just imagine topics around business,
    1:00:14 topics around finance, topics around parenting,
    1:00:19 even like meditation and how to like improve your life.
    1:00:21 All of that stuff works really well in the audio format
    1:00:24 and doesn’t necessarily always require video.
    1:00:26 So anyways, those kinds of podcasts,
    1:00:28 at least today, are not the mainstream podcast, right?
    1:00:31 ‘Cause today, mainstream podcasts are again around shows
    1:00:33 versus individual pieces.
    1:00:35 Instead of being like a TV show,
    1:00:38 why can’t you be like a movie?
    1:00:40 And it’s like this one-time thing that goes really deep,
    1:00:42 which is really valuable content.
    1:00:43 And I think if you take that kind of definition
    1:00:46 for a podcast, it is so massive.
    1:00:48 – So let’s begin the whole notion of treasure radio, right?
    1:00:53 Like we, it is an industry completely utterly defined
    1:00:55 by the nature of the distribution point.
    1:00:57 It is antennas going out, it hits you in the car,
    1:00:59 it hits you in the radio,
    1:01:01 and it commands billions and billions of dollars.
    1:01:03 My interpretation of that industry
    1:01:06 and its sort of strange persistence
    1:01:08 has a lot to do with advertising relationships.
    1:01:13 It is still the medium that has the most easy reach
    1:01:16 for, and that hits the most Americans,
    1:01:19 and has the most like history behind it.
    1:01:21 And so if you’re an advertiser,
    1:01:23 you feel significantly more comfortable
    1:01:26 because that is your default industry to fight into.
    1:01:29 And I feel like that feeling of safety and confidence
    1:01:31 is something that should not be understated.
    1:01:34 And it’s something that all digital media sort of sectors,
    1:01:36 including podcasting and beyond it,
    1:01:37 should sort of be cognizant of like,
    1:01:41 that’s one of the primary things driving that situation.
    1:01:44 – And I think another reason why ads work so well on radio,
    1:01:46 and it works well on podcasts too.
    1:01:49 Sometimes it comes in the voice of the creator
    1:01:51 versus the voice of the brand
    1:01:53 or like some other random voice.
    1:01:54 – 100%, yep.
    1:01:56 The sort of buzzword that podcast industry executives
    1:01:58 use all the time is intimacy, right?
    1:02:02 And that’s why we sort of hear the host rat ad being
    1:02:05 the pinnacle of the podcast advertising experience.
    1:02:10 And it’s also its most valuable ad slot, ad type.
    1:02:14 And so, that’s why like a lot of the genres
    1:02:16 that you pointed out when you sought to build
    1:02:18 the taxonomy of a podcast is very personality driven.
    1:02:20 It’s very people driven.
    1:02:22 That’s why there’s a little bit of trickiness
    1:02:24 when we talk about something like fiction podcasts
    1:02:26 or non-narrated podcasts and how you monetize that,
    1:02:27 how you build that relationship.
    1:02:29 – Yep, I agree.
    1:02:31 It’s very much native to the content of the storytelling
    1:02:32 and the medium in that context.
    1:02:33 – Absolutely.
    1:02:35 And at some point we will see innovations in business models,
    1:02:37 innovation in distribution in the structure,
    1:02:41 in the sort of like container of it
    1:02:45 that will alter the advertising assumptions here
    1:02:47 or the monetization assumptions here.
    1:02:48 But I just want to go back to,
    1:02:50 to tie it back to the very first thing we talked about.
    1:02:52 The definition of it, what we think about it,
    1:02:53 how we think about it,
    1:02:55 our assumptions of it being personality driven
    1:02:57 or show driven or episode driven,
    1:02:59 it needs to fragment at some point.
    1:03:00 It kind of needs to break up
    1:03:04 because it needs to be a universe that can hold
    1:03:06 a bunch of different kinds of experiences
    1:03:08 in the same way that when we think about television,
    1:03:10 we’re not just talking about breaking bad.
    1:03:12 We’re talking about real fortune.
    1:03:15 We’re talking about like so many different kinds of styles.
    1:03:17 – We’re talking about like American Idol,
    1:03:19 which is such an important movement around the world
    1:03:21 when you think of the future of content.
    1:03:24 And TikTok and challenge-based things, right?
    1:03:26 But the point is that there is a whole,
    1:03:28 that was a huge fun reality TV, like–
    1:03:30 – Or things around holidays.
    1:03:31 – Right. – Like the Super Bowl.
    1:03:33 Once a year type events, right?
    1:03:35 Like this is again, like we have to break away
    1:03:36 from the show concept.
    1:03:37 – Exactly, I agree.
    1:03:39 And to your point, just on a terminology thing, Nick,
    1:03:41 I would say the word fragmented,
    1:03:44 we’ve used that in the context of industry fragmentation.
    1:03:46 To me, it’s more how to make a homogenous term
    1:03:49 more heterogeneous and have more diversity
    1:03:50 embodied within it.
    1:03:53 – Yeah, and so I think the question here is sort of like,
    1:03:56 do we think about the spread as on the one hand,
    1:03:58 you have prestige TV, and on the other hand,
    1:03:59 you have reality TV?
    1:04:01 Or do we think about the spread more like,
    1:04:02 on the one hand, you have Netflix,
    1:04:04 on the other hand, you have Twitch?
    1:04:06 Like, is that the way we’re gonna think
    1:04:08 about the ecosystem at large?
    1:04:09 Or are we gonna be a bit more specific
    1:04:11 when we use the term, when we do our coverage?
    1:04:13 I think that’s also, you know,
    1:04:15 what we talk about is this important
    1:04:16 about how we talk about it, so.
    1:04:17 – Do you wanna say one more thing?
    1:04:19 – No, I wanna ask you questions,
    1:04:20 ’cause there’s so many of my friends today
    1:04:22 who want to create podcasts.
    1:04:25 And you created the A16Z podcast from scratch
    1:04:25 to what it is today.
    1:04:28 – To full credit, it was actually created before I joined,
    1:04:30 and I took over at three months in the production
    1:04:31 and then I’m hosting it a year later.
    1:04:33 – Okay, but I know like the user base massively,
    1:04:36 the listenership massively grew under your care.
    1:04:37 So I think you should talk about, you know,
    1:04:39 what are your tips for someone
    1:04:40 who just wants to get started on podcasts?
    1:04:42 – Oh my God, that could be its own episode,
    1:04:43 and I’d love to do that someday.
    1:04:45 So I guess maybe on the spirit of creation,
    1:04:46 which is a theme of this episode,
    1:04:48 I’ll just say some very quick, high-level takeaways,
    1:04:50 which is one, and I do this when I give a lot of talks
    1:04:52 and talk to founders about how to start their own things
    1:04:53 for their company.
    1:04:54 – Yes.
    1:04:55 – I think the fundamental thing people need to ask
    1:04:58 is where they are in the taxonomy of shows that I outlined,
    1:04:59 because that is sort of a flow chart
    1:05:00 for what your next step is,
    1:05:01 for either how to hire, build,
    1:05:03 or just what tools to use.
    1:05:05 If you’re a cult of personality show,
    1:05:07 the things you can do are very different
    1:05:08 than if you’re doing a brand show,
    1:05:10 than if you’re doing a serialized narrative show.
    1:05:11 So the first thing I always ask people is,
    1:05:13 what is your goal and what kind of show you want?
    1:05:14 ‘Cause it’s a very crowded environment.
    1:05:17 So then the next thing is, attention is scarce.
    1:05:18 With podcasting, maybe less so
    1:05:19 because you have a bit of a captive audience
    1:05:23 in a phone or commute or workout or a, you know,
    1:05:26 a situation where they are on a hike or a walk
    1:05:27 where they’re only gonna listen,
    1:05:29 but even then you are competing with other shows.
    1:05:31 So the number one thing is how you differentiate your show.
    1:05:34 And one of the number one ways to get a lot of listeners
    1:05:37 is to have a lot of episodes, a variety of episodes.
    1:05:39 And so the other way to do it then is to enforce seasonality
    1:05:40 where you drop a season of episodes
    1:05:42 and then just like drop them in like, you know,
    1:05:43 record 10 and drop them.
    1:05:43 – So basically if you wanna do it,
    1:05:45 it’s like a long-term commitment?
    1:05:47 – I don’t think it has to be
    1:05:48 because as you’ve also talked about,
    1:05:53 there’s a lot more tools emerging and startups emerging
    1:05:55 that will allow like experimentation and sharing.
    1:05:57 – But for now, it has to be a long-term commitment.
    1:05:59 – I think Ben Thompson said this.
    1:06:00 Headcount is the biggest predictor
    1:06:01 of how much people invest in something.
    1:06:05 And I think if a company has people dedicated to podcasting,
    1:06:06 then you know they’re serious about podcasting,
    1:06:07 I would say it’s as simple as that.
    1:06:09 So you do have to invest in it to make it happen.
    1:06:10 – Yeah, but on the simple mechanics,
    1:06:11 one of the most beautiful things is the thing
    1:06:12 that I complained about,
    1:06:14 which is the very thing that also is the best thing
    1:06:16 about podcasting is the feed ecosystem
    1:06:20 makes it so easy to simply record an episode,
    1:06:21 distribute wherever you want.
    1:06:23 And then it’s about using the feed ecosystem
    1:06:25 to then freely put your feed out all into the world
    1:06:26 because it’s as simple.
    1:06:28 All iTunes is doing is taking a bunch of feeds.
    1:06:30 All we had to do when we got on Spotify
    1:06:31 was like feed them our feet.
    1:06:34 And people can self-select the feeds into different apps.
    1:06:35 So you can use that to your advantage.
    1:06:37 And there’s a ton more about the content side,
    1:06:39 but the one thing I do wanna say is that
    1:06:42 the editing process is now becoming democratized
    1:06:43 because there’s a huge gap.
    1:06:45 I would often put it as the analogy
    1:06:46 between design and manufacturing
    1:06:48 where there is a design phase and a manufacturing phase
    1:06:50 and you need to close and tighten that feedback loop
    1:06:52 to get the best content out.
    1:06:54 And what’s happening with tools like Descript,
    1:06:55 you tighten this feedback loop
    1:06:56 between design and manufacturing
    1:06:59 where you no longer have to separate creators and writers
    1:07:02 from the technical skills of actually editing a podcast.
    1:07:03 So that’s really important
    1:07:05 because there’s a whole bunch of tools now
    1:07:07 that are on the analytic side that will,
    1:07:08 and there are a new bunch of distribution tools
    1:07:10 that are now connecting all these pieces
    1:07:11 and supporting creators.
    1:07:12 So it’s a very quick answer.
    1:07:14 There’s so much more you could say on this.
    1:07:15 – I think we need to do another podcast
    1:07:17 on how to create podcasts.
    1:07:18 – Well, that would be fun.
    1:07:20 Thank you for joining the ASICS NC Podcast.
    1:07:21 – Thank you so much for having me.
    1:07:22 I really enjoyed this talk.
    1:07:23 – Thank you.

    with Nick Quah (@nwquah), Connie Chan (@conniechan), and Sonal Chokshi (@smc90)

    It’s a podcast about podcasting! About the state of the industry, that is. Because a lot has changed since we recorded ”a podcast about podcasts” about four years ago: podcasts, and interest in podcasting — listening, making, building — is growing. But by how much, exactly? (since various stats are constantly floating around and often out of context); and what do we even know (given that no one really knows what a download is)?And in fact, how do we define ”podcasts”: Should the definition include audio books… why not music, too, then? So much of the podcasting ecosystem — from editing tools to the notion of a ”CD phase” to music companies like Spotify doing more audio deals — stems from the legacy of the music industry. But other analogies — like that of the web and of blogging! — may be more useful for understanding the podcasting ecosystem, too. Heck, we even throw in an analogy of container ships (yes, the ocean kind!) to help out there.If we really think medium-native — and borrow from other mediums and entertainment models, like TV and streaming and even terrestrial radio — what may or may not apply to podcasting as experiments evolve? In this hallway-style jam of an episode, Nick Quah (writer and publisher of Hot Pod) joins a16z general partner Connie Chan (who covers consumer startups among other things) in conversation with Sonal Chokshi (who is also showrunner of the a16z Podcast) to talk about all this and more. We also discuss the obvious and the not-so-obvious aspects of monetization, discovery, search, platforms… and where are we in the cycles of industry fragmentation vs. consolidation, bundling vs. unbundling, more? And where might opportunities for entrepreneurs, toolmakers, and creators lie?


    The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates.This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investor or prospective investor, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.)Past performance is not indicative of future results. Any charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Please see https://a16z.com/disclosures for additional important information.

  • a16z Podcast: How Many Taps in the Apple (Plus) Tree?

    AI transcript
    0:00:06 Hi, and welcome to the A16Z podcast. In this episode, another of our hallway conversations,
    0:00:11 Benedict Evans and Steven Sinovsky go over the recent Apple event, Apple Event Plus,
    0:00:15 and consider what it all means in terms of big company strategy and the evolution of
    0:00:20 Apple moving to services. Please note that the content here is for informational purposes only,
    0:00:25 should not be taken as legal business tax or investment advice, or be used to evaluate any
    0:00:31 investment or security and is not directed at any investors or potential investors in any A16Z fund.
    0:00:35 For more details, please visit a16z.com/disclosures.
    0:00:40 Welcome to an episode of the A16Z podcast. I’m Steven Sinovsky.
    0:00:41 I’m Benedict Evans.
    0:00:47 And today we’re going to talk a little bit about the announcements at Apple’s sort of new look
    0:00:48 event. The Apple Plus event.
    0:00:55 The Apple Plus event, the Event Plus. But I want to start off because I haven’t paid
    0:01:00 that much attention afterwards, but certainly during the event there was just
    0:01:04 so much build up as usual, which is good because they’re a huge company and people pay attention.
    0:01:11 But then so much sort of, oh, it was weird, it was different, and it wasn’t what we were
    0:01:16 expecting and all this kind of stuff. And I want to take a step back because I’m completely
    0:01:22 fascinated by Apple moving to services, which is obviously a huge deal.
    0:01:26 And I want to talk about it at the strategic sense, not necessarily the financial.
    0:01:30 This isn’t really about the finances or the business side as much as the strategy.
    0:01:32 And so one thing that’s super interesting, just to add to the gate,
    0:01:36 is Apple has 360 million or so subscribers worldwide.
    0:01:42 That’s a sort of a vanity number because it includes subscriptions to apps in the App Store.
    0:01:46 But because Apple gets a cut, at least for year one, it’s a relevant number.
    0:01:49 So I try to find other subscriptions that were big.
    0:01:53 The only one I came close was China Mobile, which is like a billion.
    0:01:58 And then after that, Benedict’s old friends in Europe, Vota and Telefonica.
    0:02:02 Yeah, the global mobile operators have got hundreds of millions.
    0:02:04 Nobody else is as big on a global scale.
    0:02:09 But even Vota and Telefonica, at least the current numbers are under that 360 number,
    0:02:10 but it’s very close.
    0:02:17 Yeah, it’s interesting if you sort of sit and make a list of how many different places
    0:02:22 is Apple kind of putting a tap onto the tree and taking some sap out.
    0:02:26 So how many different places do you have an opportunity to pay Apple $10 a month?
    0:02:29 It’s a little bit like the joke about cable TV.
    0:02:33 Like you cancel your cable for $100 a month and then you sign up to this for $10 and this
    0:02:36 for $10 and this for $10 and you end up spending $100.
    0:02:42 You could probably, pretty soon you’ll be able to pay Apple $100 a month in subscriptions.
    0:02:47 Right, and the interesting thing, and of course it is a good joke about cable TV and unbundling.
    0:02:52 Now, one of the things that I think that’s super interesting about that is it is replacing
    0:02:58 a place where you have no choice effectively, especially in the U.S. market for television,
    0:03:01 but not the case for news necessarily.
    0:03:06 But it’s replacing it with a feeling of self-determination and control,
    0:03:07 which I think is really important.
    0:03:11 And I want to come back to something that just resonated for me throughout
    0:03:14 each of the main new plusy things.
    0:03:18 And that was the sort of this positioning underlying everything they said.
    0:03:24 And it’s sort of the number of times in this consistency across each new subscription $10
    0:03:29 a month thing that they talked about it being private and having no tracking between it being
    0:03:30 curated and using humans.
    0:03:36 So I heard this, somebody on Twitter said that they were a publisher and they had a
    0:03:42 big advertising deal for their content on Apple News.
    0:03:44 They had a big third-party advertiser.
    0:03:48 The Apple News team blocked the advertiser because it wanted tracking that they weren’t
    0:03:48 willing to give it.
    0:03:50 Guess who the Apple advertiser was?
    0:03:51 Apple.
    0:03:51 Oops.
    0:03:57 Apple’s advertising team was demanding tracking that Apple’s news team was not
    0:03:58 going to allow a publisher to do.
    0:04:03 Well, I’ve been in the situation of the right hand, left hand on tracking in particular,
    0:04:05 and I know how tricky that one can be.
    0:04:10 But going back, so it was private, no tracking, curated with humans was very important.
    0:04:12 And that’s obviously a statement they’re making.
    0:04:15 Also, no ads and family.
    0:04:19 And that’s, of course, when you subscribe to a magazine or cable, it’s for your family too.
    0:04:21 So it’s not like some giant leap.
    0:04:25 But particularly on games, which today aren’t quite shared.
    0:04:27 Obviously, Netflix does a great job on family.
    0:04:34 And so there’s a big kind of sense of kind of the brand, the fuzzy brand feeling here,
    0:04:36 which is not about the technology and the product.
    0:04:38 It’s about privacy and curation.
    0:04:42 The sort of, there was sort of gossip coming out of Hollywood that
    0:04:44 Apple kept pushing back on the TV show.
    0:04:46 He’s saying it wasn’t family-friendly enough.
    0:04:50 They were just going, “Tim Cook apparently was writing this as being too mean.
    0:04:51 Can you be less mean?”
    0:04:56 And, you know, that’s a very different to where the kind of the direction of travel
    0:04:59 of TV has been in the last five and 10 years with other subscription services,
    0:05:02 which is being less family-friendly and more edgy and more alternative and pushing the boundaries.
    0:05:04 Interesting challenge for Apple.
    0:05:05 Of course, they end with April Winfrey.
    0:05:07 Start with Steven Spielberg and end with April Winfrey.
    0:05:11 They didn’t show lots of action movies in the interim.
    0:05:13 And you’re talking about services.
    0:05:17 I mean, there’s something that sort of intrigues me here that for a long time,
    0:05:20 you would look at the App Store and the 30%.
    0:05:22 And people would say, “Apple is doing X and Y and Z.
    0:05:25 I don’t like on the App Store and they’re doing it for the money.”
    0:05:29 And you would say, “No, because actually if you think about what 30% of the App Store is,
    0:05:32 it’s tiny in proportion to the overall Apple business.
    0:05:37 And the purpose of the App Store is to sell iPhones and to make the iPhone a great experience.”
    0:05:40 And yes, they’re making a little bit of money from it kind of on the side,
    0:05:43 but actually it’s there to sell iPhones.
    0:05:48 And I think that’s still sort of true, except there’s now 800 million iPhones
    0:05:50 and over a billion iOS devices.
    0:05:53 And I think Apple said 500 million people open the App Store every week.
    0:05:58 And so 30% of those purchases has become a real number.
    0:05:59 Yeah, yeah.
    0:06:01 And so there’s a kind of an interesting thing across
    0:06:03 many of these tech companies actually,
    0:06:06 that something that was kind of non-core or non-strategic,
    0:06:07 all sort of not there for the money.
    0:06:11 The money that you weren’t really there for has now become a really big number.
    0:06:15 Well, and that’s one of the things about the scale that makes this all very interesting.
    0:06:17 Because I think that this move to services,
    0:06:21 people are just having trouble getting their heads wrapped around it.
    0:06:28 And it’s a very natural progression for any company when it starts to reach a mature level,
    0:06:35 which is, okay, are we now effectively selling things to our “installed base” enough?
    0:06:41 And in the world of enterprise software, every company is in the transition to cloud space.
    0:06:43 They’re taking their existing customers,
    0:06:46 and they’re reselling in their old software about on a cloud thing.
    0:06:48 And in the enterprise space, that’s like heroic,
    0:06:51 and it’s viewed as this brilliant strategy.
    0:06:53 And here’s Apple doing the same thing.
    0:06:55 And it’s like, oh, this is a recognition that they’re doomed,
    0:06:57 and it’s the end of the line for them.
    0:07:02 And it’s a very weird thing to sort of see because it’s both natural.
    0:07:05 And unlike all the other enterprise businesses,
    0:07:11 Apple is saturating the population, not some artificial number,
    0:07:13 like number of computers and marketing people.
    0:07:15 There’s five and a half billion adults on Earth,
    0:07:17 and four billion or so people have a smartphone,
    0:07:20 and 800 and 900 million of those now are iPhones.
    0:07:22 I mean, we should probably just kind of,
    0:07:24 if you’re people who haven’t been obsessed with this stuff
    0:07:24 and haven’t seen the event,
    0:07:27 we should probably talk specifically about this before they’re announced.
    0:07:28 So they did four announcements.
    0:07:31 So the first is that they’ve extended the existing news product,
    0:07:33 which has been, so they have the Apple news product,
    0:07:34 has been kind of a sleeper hit.
    0:07:36 It draws a lot of traffic for publishers.
    0:07:38 It’s, again, manually curated,
    0:07:40 so they don’t let any, theoretically,
    0:07:42 they don’t have kind of random junk in there.
    0:07:46 Apple News now gets this company they bought last year called Texture,
    0:07:52 which is sort of PDF magazines plus reformatted magazines,
    0:07:55 $10 a month, and there’s, I think, 300 magazines on the title,
    0:07:56 and there’s some notable exceptions,
    0:07:58 but basically everything is in there.
    0:08:00 Like the New York Times isn’t in there,
    0:08:03 but National Geographic and all sorts of other stuff is in there.
    0:08:04 Loads and loads of magazines.
    0:08:05 And you pay your $10 a month,
    0:08:08 then that sits within the news curated experience,
    0:08:10 so it will suggest stuff from titles
    0:08:11 that you wouldn’t necessarily have looked at.
    0:08:13 It will say stuff will flow up.
    0:08:17 And the picture magazine, of course, here is found money,
    0:08:18 because these people wouldn’t have bought your magazine.
    0:08:20 They won’t read all of it, but they’ll read five stories,
    0:08:22 and you’ll get some money from that.
    0:08:24 People in magazine business are saying,
    0:08:26 A, you’re giving up customer ownership,
    0:08:28 and B, you’re giving Apple 50%.
    0:08:30 An awful lot of people don’t get customer ownership.
    0:08:33 Well, this is me, like yoga magazines.
    0:08:36 Like the only time I really buy yoga magazines is at the airport.
    0:08:37 So this is the thing, they say this,
    0:08:40 you’ve got people at kind of top right corner
    0:08:42 of the quadrant titles saying,
    0:08:45 you’re insane, you shouldn’t give up customer ownership.
    0:08:46 You look at these titles.
    0:08:48 Most of those titles don’t have customer ownership,
    0:08:50 and will never get it.
    0:08:52 And so there’s a sort of a found money conversation in there.
    0:08:53 So there’s the news product.
    0:08:54 That’s kind of interesting.
    0:08:55 There’s some execution questions.
    0:08:56 You could go and do the micro thing,
    0:08:59 which we weren’t on what’s going on there.
    0:09:01 There’s news plus, then they have a credit card.
    0:09:03 Well, let’s slow down for a second.
    0:09:04 One more thing on news.
    0:09:04 Well, shall I go?
    0:09:05 I’ll do the four bullets.
    0:09:08 So there’s news, they’ve extended Apple pay
    0:09:09 and Apple cash with a credit card.
    0:09:13 They have got a new version of their TV app
    0:09:15 that aggregates content from other TV apps
    0:09:18 on your phone, on your device,
    0:09:19 and from stuff that you might have access to
    0:09:20 through your cable subscription.
    0:09:22 So it should all just show up in one UI.
    0:09:24 And then they have, they are paying people
    0:09:26 in Hollywood to make TV shows for them.
    0:09:27 So those are those four things.
    0:09:28 So that’s news.
    0:09:28 Right.
    0:09:30 So the interesting thing for me about news, again,
    0:09:34 it comes back to, so Apple has like core values.
    0:09:38 It has a set of core attributes Tim Cook has done,
    0:09:40 but there’s three sets of Apple values
    0:09:41 that sort of float around.
    0:09:43 The Steve Jobs one, the early Tim Cook ones,
    0:09:45 and then the most current ones that you can see on the website.
    0:09:48 But the middle ones, one of the things
    0:09:50 that they really talk about a lot is
    0:09:53 they like to make complex things simple.
    0:09:54 Yeah.
    0:09:57 And to me, the thread through all of the announcements today
    0:10:01 was like making complex things simple.
    0:10:04 And for most people, a lot of these things
    0:10:06 are actually pretty complex.
    0:10:08 Like the idea of subscribing to six magazines,
    0:10:10 it’s not just that it’s expensive.
    0:10:12 It’s kind of a complex thing.
    0:10:13 You got to find them.
    0:10:15 Should make a note here that the US print
    0:10:17 magazine market is a subscription market.
    0:10:17 Right.
    0:10:19 It’s not true in other places.
    0:10:21 So in the UK, no one subscribes to magazines.
    0:10:23 There’s a shop selling 300 magazines,
    0:10:25 every 100 yards on every shopping street,
    0:10:26 you want a magazine, you go in and you buy it.
    0:10:27 No one subscribes.
    0:10:29 In America, like living in San Francisco,
    0:10:30 supposedly in an urban center,
    0:10:32 if I want to get a magazine, I actually can’t.
    0:10:33 Like unless I go to the airport.
    0:10:35 Yeah, all of those stores, there used to be many of them.
    0:10:36 They’re all.
    0:10:38 But the only way I could get a copy
    0:10:41 of National Geographic today is to find some way
    0:10:43 of getting them to mail it to me.
    0:10:43 Right.
    0:10:46 And so in that context, moving to the Apple news product
    0:10:48 does actually solve a consumer problem.
    0:10:48 Right.
    0:10:51 And also, just like again with all of these,
    0:10:54 there was a lot of like hemming and hawing over,
    0:10:58 oh, is this part of it going to be available in Germany?
    0:11:01 And is Lichtenstein going to have special TV shows for them?
    0:11:04 And the thing is, when you’re looking at your
    0:11:06 installed base as the potential customers,
    0:11:10 you have a lot of data over who’s buying what and where.
    0:11:13 And so it becomes very natural to sort of tilt things
    0:11:16 towards where the money is already being spent
    0:11:19 because the easiest dollar to make is a dollar more
    0:11:21 from somebody who’s already paying you.
    0:11:25 And in Apple’s case, like tilting it towards the U.S.
    0:11:26 and the early versions of these products
    0:11:29 makes it a ton of obvious sense.
    0:11:31 Now, they’ll have and expand it,
    0:11:34 but they will follow the economics much more
    0:11:36 than you might for hardware.
    0:11:39 It’ll look a lot more like when they open their Apple stores.
    0:11:39 Yeah.
    0:11:41 And going back to the old world of print,
    0:11:43 U.S. magazines is a bigger market,
    0:11:45 and then the U.K. is a bigger magazine market
    0:11:46 than France or Germany.
    0:11:48 And you would expect that to be reflected
    0:11:50 in what happens on this platform.
    0:11:50 Yeah.
    0:11:53 And so, but it’s part of what made the event weird
    0:11:54 for people is sometimes it was like,
    0:11:56 well, this isn’t what we’re really used to.
    0:11:59 We’re used to a new device that’ll be available
    0:12:02 in 160 countries on Thursday.
    0:12:02 Yeah.
    0:12:04 And all of a sudden, it’s like, well,
    0:12:05 it’s complicated to roll out all these things.
    0:12:07 Like, even just the magazines,
    0:12:10 you’ve got to get everybody to be in sync on an issue.
    0:12:12 Like, they can’t just show up.
    0:12:14 And TV production, it’s even more uncertain.
    0:12:18 So, I personally thought that Apple News
    0:12:20 was particularly interesting.
    0:12:21 I have some beefs with it.
    0:12:23 So, I think, yeah, I’m just listening to you talk.
    0:12:25 I feel like there’s these four events,
    0:12:27 and you could put them in very different places.
    0:12:28 Because Apple News is, I would say,
    0:12:31 this is a good solid incremental upgrade
    0:12:32 to an interesting, useful product.
    0:12:34 It’s not changing the world.
    0:12:34 It’s a good product.
    0:12:36 This is a good upgrade.
    0:12:38 The same thing with their refresh of the TV app.
    0:12:38 Yeah.
    0:12:40 This is a good upgrade of an existing product
    0:12:42 that solves a bunch of problems.
    0:12:43 There’s also a two-hour argument
    0:12:44 about how well it does that,
    0:12:46 and what else will happen, and so on.
    0:12:46 Right.
    0:12:48 But there, basically, it’s an incremental upgrade
    0:12:50 to an existing, well-understood product.
    0:12:52 Then you have these kind of two sort of meteorites.
    0:12:54 Let’s finish TV, and let me get to that one.
    0:12:56 Because the thing on the TV that I think,
    0:13:00 this is one where I would say it’s the,
    0:13:02 if only Apple got into the business of X,
    0:13:04 they would fix it.
    0:13:06 And there’s just this hope
    0:13:08 that Apple could show up and erase
    0:13:11 the existing business infrastructure of television.
    0:13:14 And all the reasons why it’s like that would stop mattering,
    0:13:15 and it would just go away.
    0:13:18 It reminds me of anything that we all dislike,
    0:13:21 and we all wonder if only Apple would make that,
    0:13:22 the world would be a better place.
    0:13:25 And we forget they didn’t do that to telco.
    0:13:29 You still pay your telco X amount of money,
    0:13:32 and the service is still the works of pretty much
    0:13:33 the way it was trained 15 years ago.
    0:13:35 In fairness to them, they, you know,
    0:13:37 especially with the soft sim and things like that,
    0:13:38 they’ve made–
    0:13:39 But pretty incrementally.
    0:13:42 It’s incremental, but it reduced complexity
    0:13:43 in some significant way.
    0:13:44 And so I think that–
    0:13:45 But they didn’t buy a record label.
    0:13:46 Right.
    0:13:47 They didn’t buy telco.
    0:13:47 Exactly.
    0:13:49 They didn’t, until they didn’t buy a bank.
    0:13:50 Or a book publisher.
    0:13:51 Yeah, exactly.
    0:13:52 To fix books and stuff.
    0:13:53 And so I think that there’s,
    0:13:57 the problem is when people are unhappy with
    0:13:58 any company doing something,
    0:14:01 it’s often because, you know, the company messed up.
    0:14:03 But it’s equally often that there’s just a mismatch
    0:14:06 between expectations and what was really done.
    0:14:07 And I think in the case of TV,
    0:14:10 everybody just wants so much more.
    0:14:13 And really, nobody is cracked it.
    0:14:15 In fact, what’s interesting is so much of the negatives
    0:14:17 about what’s going on with TV,
    0:14:20 we forget how many people thought Netflix would never work.
    0:14:23 And how many people, like, that were in TV
    0:14:24 said Netflix wouldn’t work.
    0:14:26 Like, there were a bunch of people at Disney
    0:14:27 who were clearly convinced
    0:14:29 that it wasn’t going to get any traction.
    0:14:31 Which is why they let them buy their shows.
    0:14:31 Right.
    0:14:35 There’s just no escaping this reality of TV
    0:14:38 that the people who make things like
    0:14:40 there to be a large number of customers
    0:14:42 and divide up the market in different ways,
    0:14:44 by streaming and not streaming and DVD,
    0:14:47 or pay-per-view or theater, plus by country.
    0:14:49 And that’s not, they make it.
    0:14:51 So it’s not going to change.
    0:14:52 Yeah, exactly.
    0:14:54 I mean, it is as though Apple had to do a telco
    0:14:56 and then you were complained that somehow
    0:14:58 the existing telco market structure hadn’t changed.
    0:15:02 Well, yeah, you’re only going to do this slowly
    0:15:03 and piecemeal in a careful bit
    0:15:05 because there’s very, very strong incentives there
    0:15:06 that aren’t going to go away.
    0:15:07 Right.
    0:15:10 But if they can make, you know, like, I’m a TiVo user
    0:15:12 and Roku was much the same way.
    0:15:14 And both of those are products
    0:15:17 that take a very complex world of many different apps
    0:15:20 with many different feeds of potential content
    0:15:22 and make it simple.
    0:15:25 And there’s so much room for Apple to make that even simpler.
    0:15:28 And the fact that they have a TiV device is very interesting.
    0:15:31 The fact that they will incrementally expand where that,
    0:15:35 you know, in Visio TV or LG TV or Samsung TV is all goodness.
    0:15:40 And I think it fits the description of like progress.
    0:15:41 And that’s good to see.
    0:15:43 It didn’t erase the TV industry, but it’s progress.
    0:15:46 Yeah, we’ve got news and the TiV app.
    0:15:49 These are interesting, useful products to sell problems for people.
    0:15:51 They are not the Jesus phone.
    0:15:51 No.
    0:15:55 But this is just good incremental work by a bunch of people there
    0:15:56 making it a bit better.
    0:15:56 Apple card.
    0:15:58 I’m not, I’m not a card person,
    0:16:00 which is actually also interesting in the context of TV.
    0:16:03 Are you like, so you’re like anti-tracking and everything?
    0:16:05 So you only use money or is that a British thing?
    0:16:07 No, no, what I mean is I can’t sit there
    0:16:09 and analyze exactly what this position is
    0:16:11 and what it looks like relative to other positions,
    0:16:12 which is similar to TV.
    0:16:15 A lot of the TV questions are actually TV industry questions,
    0:16:16 not Apple or tech questions.
    0:16:17 Right, right.
    0:16:20 I think another way you can think about all of these services
    0:16:23 are they all bind you into the phone.
    0:16:24 Right, and so there is a, you know,
    0:16:27 just as everything Amazon adds to prime
    0:16:29 keeps you from canceling your prime account
    0:16:32 and that drives all of your purchases through Amazon,
    0:16:35 all of these things are sort of ways of making
    0:16:38 your next phone purchase be another iPhone.
    0:16:42 And if your credit card is a particularly sticky thing,
    0:16:43 if you’re getting your TV through it,
    0:16:45 if you’re getting your magazines through it,
    0:16:49 if you’re getting any other transit, XYZ service,
    0:16:52 anything that you can do that makes,
    0:16:54 both makes the product better,
    0:16:56 but also is something that’s going to be kind of a pain
    0:16:59 in the backside to switch out and replace with something else,
    0:17:00 all of that becomes valuable.
    0:17:02 Right, which is of course exactly what
    0:17:04 everybody enterprise software does
    0:17:06 and why SaaS is so interesting to them.
    0:17:09 So it’s no surprise that Apple is doing all of these things.
    0:17:12 And it’s this, it is just this weird view of like Apple
    0:17:15 as a boom bust company dependent on hit gadgets,
    0:17:18 which isn’t true all that much either.
    0:17:20 But the thing to me about the card,
    0:17:23 I found the card actually particularly innovative.
    0:17:25 And then a lot of people were like, oh, you know,
    0:17:28 you go to nerd wallet and you see all of these cards
    0:17:30 that do better points or better this and better that.
    0:17:32 You think it’s like the people who said,
    0:17:33 oh, Dropbox isn’t very innovative.
    0:17:37 You just go into your GitHub and you can download 15 scripts
    0:17:38 and tie them together and you get the same thing.
    0:17:41 Like even people who said that the way Apple did,
    0:17:43 Wi-Fi hotspots wasn’t innovative.
    0:17:47 And like underneath every, they’re probably, you know,
    0:17:49 a very, very small number of people
    0:17:53 at a very, very smaller number of companies
    0:17:55 that understand all the complexity
    0:17:57 that could go into delivering Apple card.
    0:18:00 That complexity, Apple is erasing.
    0:18:02 Like some very simple thing, like you mentioned,
    0:18:04 well, if Apple can make the phone sticky
    0:18:06 when you get a new phone, right,
    0:18:08 this is exactly the kind of thing that they can do.
    0:18:10 Make it really easy to get a new phone,
    0:18:11 even if all your credit card and money
    0:18:14 are sitting on your Apple device.
    0:18:17 And that upgrade is hugely valuable.
    0:18:18 But on top of that,
    0:18:21 there’s all this innovation that happened in the space.
    0:18:22 And yes, you can go to Nerd Wallet
    0:18:25 and you could find some card that does, you know,
    0:18:28 3% cashback on everything, not just store purchases,
    0:18:30 or you can find one that gives you better miles.
    0:18:32 But anyone who knows any of these things
    0:18:34 knows that once you’re on that game,
    0:18:37 you’re almost like the person who’s determined
    0:18:40 to find everything you want to watch on off-air free TV.
    0:18:44 Like people are only willing to spend so much effort
    0:18:46 for some of those…
    0:18:47 You’re like the coupon queen.
    0:18:50 Well, coupons are very good for certain people
    0:18:52 at certain economics.
    0:18:53 But like at some point,
    0:18:56 like you’re making a trade-off over time versus effort.
    0:18:58 And if you’re an Apple customer,
    0:18:59 you’ve already made that trade-off
    0:19:01 because your phone is a luxury good.
    0:19:04 Like you didn’t buy the $99 phone,
    0:19:05 you bought the expensive one.
    0:19:07 So you’re looking for other things.
    0:19:11 And this is where another part of where people view these services,
    0:19:12 they sort of get a little confused,
    0:19:15 which is first, Apple off the top
    0:19:18 is not aiming for all five billion humans
    0:19:19 that will have a smartphone.
    0:19:21 They’ve already said we’re going to only go,
    0:19:22 we’re not making super cheap phones,
    0:19:23 it’s not that big.
    0:19:24 We’re aiming for a billion.
    0:19:25 Right.
    0:19:28 And on top of that, they can do their services
    0:19:29 as a subset of those people.
    0:19:31 Like they already have everybody in the app store
    0:19:34 and then they have some very large percentage of people
    0:19:36 that will buy iCloud for backup.
    0:19:38 And then after that,
    0:19:41 they don’t have to get 900 million people for every service.
    0:19:44 And they can aspire to that and they can measure that.
    0:19:48 But there’s some point where it becomes a very good business
    0:19:50 and a very great value proposition,
    0:19:51 even for people who don’t have them
    0:19:53 to know that they can get them.
    0:19:55 I think that kind of takes us onto the TV product
    0:19:57 where we sort of slightly hesitant about,
    0:20:00 I suppose the best way of putting it is to say,
    0:20:04 we’re sort of reserving judgment on any kind of specifics
    0:20:05 because we don’t have the specifics.
    0:20:07 We know Apple has officially said,
    0:20:09 we’re doing a TV service.
    0:20:11 We’re going to get a bunch of really great people
    0:20:13 to make some fantastic TV.
    0:20:14 We’ll tell you more later.
    0:20:15 Yeah, yeah.
    0:20:16 So that’s TV plus you’re talking about.
    0:20:17 Yes, this is TV plus.
    0:20:18 Apple will pay people in Hollywood
    0:20:20 to make the TV shows for them
    0:20:22 and they will tell us more in the autumn.
    0:20:26 You can guess that it will be $10, $15 a month.
    0:20:30 They’ve said it will be global or 100 countries
    0:20:31 because they own the rights.
    0:20:35 The big unanswered question is how much,
    0:20:37 what actual volume of content,
    0:20:39 because Netflix is spending something over $10 billion,
    0:20:42 it’s here, how much are they going to make in there?
    0:20:43 For how big will the proposition be?
    0:20:45 How many of those great shows will there be?
    0:20:47 That’s kind of the big thing everyone wants to know
    0:20:48 and we don’t know.
    0:20:50 And we don’t know and we’ll find out.
    0:20:51 And the thing is people are like,
    0:20:52 ooh, this is weird and stuff.
    0:20:53 And look, this is what,
    0:20:55 this is the power of being Apple
    0:20:58 is that you basically can convene all of these people.
    0:20:59 They’re willing to experiment.
    0:21:01 But the strategic level that one sees there
    0:21:03 is here again, Apple is saying,
    0:21:05 here is something good that you might like
    0:21:07 and you can pay a bit more money
    0:21:08 and get it on your Apple devices.
    0:21:10 And that sits next to news.
    0:21:12 It sits next to the card.
    0:21:14 Is Apple bringing something unique to credit cards?
    0:21:16 No, they’re just changing the experience.
    0:21:19 Well, and there’s a bunch of integration.
    0:21:21 I think the credit card is more innovative
    0:21:22 than people are willing to say
    0:21:24 because they focused on sort of the nerd wallet checklist
    0:21:26 as opposed to the security and the privacy
    0:21:26 and the money management.
    0:21:28 There’s a bunch of Apple engineering stuff
    0:21:29 going on in the card.
    0:21:32 There’s not apparent that there’s a bunch of Apple engineering
    0:21:34 stuff going on in the TV,
    0:21:36 but there’s a bunch of Apple decision
    0:21:37 about what should you see
    0:21:39 and how does this make your overall
    0:21:41 being an Apple customer experience better.
    0:21:43 Right, and if they can reduce the friction
    0:21:46 of acquiring it, of browsing it,
    0:21:48 of suggesting what to watch and when,
    0:21:50 I mean, there’s a whole lot of places
    0:21:52 where this is literally,
    0:21:54 you know, like the Jim Barksdale famously said,
    0:21:57 like there are two ways to make money in business.
    0:21:59 You can either bundle things or unbundle them.
    0:22:02 And so what we’re seeing is a gradual creation
    0:22:05 of a series of bundles from Apple.
    0:22:07 And yeah, sure, there might be Apple Prime
    0:22:09 or something down the road
    0:22:11 that bundles all of these into something,
    0:22:13 but for the time being, they don’t need to.
    0:22:14 And in fact, it’s, I would argue,
    0:22:16 one of the things that people were jumping to
    0:22:18 was to have like this all in one.
    0:22:19 But the fact that Apple is allowing them
    0:22:21 or keeping them separate
    0:22:23 is also a way to find product market fit
    0:22:24 for each of those.
    0:22:26 Because you don’t prematurely bundle things
    0:22:28 because then you really don’t know
    0:22:29 if you’re successful or not.
    0:22:31 And this is what all the credit card companies
    0:22:33 sort of count on, which is basically,
    0:22:35 they’re going to make a giant basket of stuff
    0:22:37 and move it around all the time.
    0:22:39 And most people only care about like one thing
    0:22:40 that they’re getting.
    0:22:42 – Yeah, I mean, see what the Apple could say,
    0:22:45 it is 200 bucks a month and you get a free iPhone
    0:22:47 and a free iPad every two years
    0:22:49 and you get all of this stuff.
    0:22:50 – Yeah.
    0:22:51 – And yeah, that would,
    0:22:54 I don’t think that would actually be a good proposition
    0:22:55 for most customers
    0:22:57 because you wouldn’t get to pick and choose which bits
    0:22:59 and it would also be kind of a huge sticker price.
    0:23:00 And it’s much better to say,
    0:23:02 well, there’s a phone and there’s how you pay for a phone.
    0:23:03 And then there are these bits that come
    0:23:05 that you can have on top of it.
    0:23:07 – And also the people who would jump at buying that
    0:23:10 probably would be spending $400 anyway.
    0:23:12 And so that’s like one of the weird things
    0:23:15 when you do these mega bundles is you’re also trading off.
    0:23:17 – Yeah, those are the people who’d buy a new foot
    0:23:19 atop of the line iPhone XS.
    0:23:20 – Every year.
    0:23:21 – Every year anyway.
    0:23:22 – Every year and they would buy AirPods
    0:23:24 and a whole bunch of other stuff.
    0:23:30 And so, for me, there was just a lot of overthinking
    0:23:31 of this whole thing.
    0:23:34 And that’s the constant challenge with Apple is you over,
    0:23:36 in fact, last night I tweeted that like
    0:23:38 when before the iPad came out,
    0:23:40 we were all sitting around trying to figure out
    0:23:41 what they were going to do.
    0:23:43 And we for sure thought they were going to go build
    0:23:45 a Mac tablet with a pen,
    0:23:48 which was just sort of our weird
    0:23:49 strategizing about what they were going to do.
    0:23:50 Not this very-
    0:23:51 – I think there’s a kind of,
    0:23:52 there’s a sort of a high level point here,
    0:23:54 which I think you said a couple of years ago that,
    0:23:56 you know, Microsoft would do some big event
    0:23:58 and then you look in the tech press
    0:24:01 and you discover what your brilliant Dr. Evil strategy was
    0:24:02 and you read it and you think,
    0:24:03 “Oh, that would be a good idea.
    0:24:04 “Maybe we should do that.”
    0:24:06 And the people sort of, you know,
    0:24:09 I said earlier there’s like,
    0:24:11 there’s two sets of Apple strategy here.
    0:24:13 There’s news in the TV app,
    0:24:14 which are incremental improvement.
    0:24:16 And then there’s a credit card in the TV content,
    0:24:18 which are rather big around ambitions.
    0:24:19 And you can kind of generalize that over
    0:24:22 any kind of big company that you’ve got stuff to doing,
    0:24:24 which is just VPs doing VP stuff
    0:24:25 and product teams doing product stuff.
    0:24:26 And they’ll just carry on doing it.
    0:24:27 Every now and then, like you’ve got
    0:24:28 the huge mega strategy.
    0:24:30 But very often you’re just kind of carrying on
    0:24:31 doing what you’re doing.
    0:24:34 And I think a lot of what we saw was sort of Apple
    0:24:35 just kind of carrying on doing what they’re doing.
    0:24:36 Some of it’s good.
    0:24:37 Some of it you can argue about.
    0:24:39 Some of it is a big mega future strategy.
    0:24:40 Some of it isn’t.
    0:24:42 And you can kind of, and over analyze,
    0:24:44 you can kind of over rotate on that we’ve got to work on.
    0:24:45 – And it is one of the things
    0:24:47 that Apple does particularly well,
    0:24:50 is progressively reveal the strategy.
    0:24:52 Like take something like the Apple card
    0:24:55 and the Apple cash that’s in it.
    0:24:56 Like Apple cash came out
    0:24:58 and everybody’s like, why would I ever use this?
    0:24:58 What am I going to do?
    0:25:00 And then last week, they just, or earlier in the week,
    0:25:04 they made the change that now you can pay off your bills
    0:25:06 using Apple, which now it’s all starting to come together.
    0:25:07 And it’s this whole thing like,
    0:25:08 I always think about Keychain
    0:25:11 and how for years they were doing Keychain.
    0:25:13 And then one day they have the fingerprint reader.
    0:25:13 – Yes.
    0:25:14 – And it all comes together.
    0:25:15 – And suddenly your fingerprint,
    0:25:17 your password is automatic.
    0:25:18 Yeah, I mean, you can run your scenario back.
    0:25:20 So they start with a fingerprint reader
    0:25:22 before the year before they do Apple Pay.
    0:25:23 It’s really obviously going to do Apple Pay.
    0:25:24 But they do the fingerprint reader first.
    0:25:26 And there’s a reason that it’s there.
    0:25:28 Then they had Apple Pay.
    0:25:29 Then they had the cash.
    0:25:30 Then they had the card.
    0:25:32 Now you take the Apple card,
    0:25:34 you get your 2% cash back on everything you spend
    0:25:35 and where does that money go?
    0:25:38 Well, it goes into P2P payments using cash
    0:25:40 or it goes into the app store or you spend it.
    0:25:42 – And I, you know, like just,
    0:25:45 and taking their family friendly view of things.
    0:25:47 Well, now you have like a credit card
    0:25:50 where the, your son or daughter doesn’t need the card,
    0:25:52 can use it at a set of number of places.
    0:25:53 They have spending graphs.
    0:25:54 They’ll earn this, man.
    0:25:56 You can give them cash allowance directly.
    0:25:58 All of a sudden it’s like the family friendly way
    0:26:00 to run finances.
    0:26:02 And it’s super interesting.
    0:26:05 So sort of for me, like there was just a lot more there.
    0:26:08 And I think it just didn’t have this big bang,
    0:26:10 you know, big companies too that you set a date
    0:26:12 and you have to do an event.
    0:26:13 Like you can’t not do it.
    0:26:16 And then you’re, you run around and like,
    0:26:18 sure, when you’re launching hardware, you know,
    0:26:19 – We forgot to mention the game thing.
    0:26:20 – Oh, the game, right.
    0:26:22 – The game thing is also the family friendly piece,
    0:26:24 which is you pay the subscription,
    0:26:27 you get these nice, fun, interesting indie games
    0:26:30 that are not about blowing people up and are-
    0:26:31 – Curated and private.
    0:26:34 – And private and are not about kind of manipulating you
    0:26:37 to get you to spend more money on loot boxes.
    0:26:39 And also about kind of trying to help
    0:26:41 the indie development, develop a base a bit more,
    0:26:44 which is obviously sort of a challenge
    0:26:45 that they have to address.
    0:26:47 And make money and make money.
    0:26:49 – In this case, iMac 2 or Mac 2.
    0:26:51 – And pull people, you know, another way
    0:26:53 in which there are better games on iOS
    0:26:54 than there are on Android.
    0:26:55 And it’s another $10 thing.
    0:26:57 And it’s another piece of your brand experience
    0:26:59 and a reason why as a parent
    0:27:01 or something you might prefer to be on iOS
    0:27:03 because you’ve got this great thing.
    0:27:04 And again, you wouldn’t want to say,
    0:27:06 well, you have to have this,
    0:27:08 but it’s an interesting experiment
    0:27:10 for a way of shifting what that gaming experience
    0:27:12 might look like that kind of fits into the Apple
    0:27:14 kind of branding and experience.
    0:27:16 – Right. And it also, it shows that their view
    0:27:18 of how these bundles work,
    0:27:20 which is they’re confident enough
    0:27:23 in the value proposition of the phone itself
    0:27:25 that they’re not bringing all of these things in
    0:27:27 for free on the phone.
    0:27:29 Like it’s very easy to see another company
    0:27:32 with a similar set of assets and other strategy
    0:27:35 constantly worried about making the phone upgrade cycle work
    0:27:38 and drawing every bit of software that they make
    0:27:41 into the sort of the default phone experience.
    0:27:42 And then a bunch of groups within the,
    0:27:44 all the VPs, as you said, within the groups,
    0:27:47 like competing over which percentage of the phone upgrades
    0:27:48 did their free thing cause.
    0:27:49 – Yeah. And then it would be like,
    0:27:52 you can only get the game subscription on the new iPhone.
    0:27:52 – Right.
    0:27:54 – You have to buy the new, you have to buy this product
    0:27:55 in order to get that subscription.
    0:27:57 – And again, this was something Apple pioneered
    0:27:59 very early when they made upgrades
    0:28:01 to the Mac operating system free.
    0:28:04 They realized that that turns out to be a better business
    0:28:06 if you just make owning,
    0:28:07 being part of the ecosystem great.
    0:28:11 So for me, I felt that there was just a lot of,
    0:28:15 of strategizing and hand wringing
    0:28:17 and trying to find like the big thing
    0:28:19 when in fact this is a big company executing
    0:28:22 reasonably well on a bunch of stuff.
    0:28:24 And some of it is going to play out and some of it won’t,
    0:28:26 but the strategy is really clear
    0:28:28 and the evidence is clear.
    0:28:29 And then what I would call like the framework
    0:28:32 or the meta strategy of being family friendly and private,
    0:28:35 it resonated across all the things that they did.
    0:28:39 I left thinking it was a pretty positive view for them
    0:28:41 in the sense of putting together a strategy
    0:28:43 and communicating it.
    0:28:44 – Yep. It came. Thank you.
    0:28:48 Thank you. I’m Stephen, and this is A16Z Podcast.

    with Benedict Evans (@benedictevans) and Steven Sinofsky (@stevesi)

    What does Apple’s recent event — in which a range of new services was announced, from Apple News Plus to Apple TV Plus to the Apple card — mean for the company’s overall strategy and tactics? In this another of a16z’s ‘hallway conversations’, Benedict Evens and Steven Sinofsky discuss the build up, announcements, and postmortem of the recent Apple event, and consider what it all means in terms of a big company’s evolution into services. How many different places is Apple now putting a tap into the tree, with new subscriptions available? What’s the positioning underlying all those different services, from a new credit card to new magazines and content, all bundled up together?

    The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates.This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investor or prospective investor, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.)Past performance is not indicative of future results. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Please see https://a16z.com/disclosures for additional important information.

  • a16z Podcast: Incenting Innovation Inside, Loonshots to Moonshots

    AI transcript
    0:00:03 Hi, everyone. Welcome to the A6NZ Podcast. I’m Sonal.
    0:00:07 Today, we have one of our book launch episodes with Safi Bakal, author of “Loone Shots.”
    0:00:14 The subtitle is, “Had a Nurture the Crazy Ideas that Win Wars, Cure Diseases, and Transform Industries.”
    0:00:20 So joining me to co-host this episode is A6NZ General Partner for Bio, V.J. Punday,
    0:00:23 who also happened to be a Miller Fellow with the author back in their grad school days.
    0:00:27 Speaking of, Safi has an academic background in theoretical physics,
    0:00:33 co-founded a biotech startup developing new drugs for cancer, and then led its IPO and served as its
    0:00:37 CEO for over a decade. So he has a really interesting vantage point that unites perspectives from
    0:00:43 academia, startups, and big company innovation. By the way, you can find other episodes touching
    0:00:47 on some of these themes from different angles, including with former Stanford president John
    0:00:52 Hennessey on the transition of ideas from academia to startups, and with CEO of Novartis,
    0:00:58 Vashrini Vasan, on R&D and innovation inside Big Pharma, as well as an episode on what disruption
    0:01:03 theory is and isn’t by searching for those on our website. But in this interview, we cover
    0:01:09 what is a loonshot versus a moonshot, and how do or don’t those connect to the concept of disruption.
    0:01:13 And given that those are some buzzy buzzwords, after briefly defining them and considering
    0:01:18 how companies can innovate regardless of what we call it, we then go into some deep scientific
    0:01:24 concepts and analogies to share a very different framework than in typical management literature
    0:01:30 with practical advice for teams and companies of all sizes to nurture new ideas and initiatives.
    0:01:36 And we even dismantle some common dogma around culture, product, and market along the way.
    0:01:42 But first, Safi begins briefly with an analogy to historical empires and why new ideas didn’t take
    0:01:50 off there. For thousands and thousands of years, truth was established by the divine ruler or the
    0:01:58 tribal leader. And in the 17th century, plus or minus a few years in Western Europe, this kind of
    0:02:06 new idea spread. But instead of asking what was true and false, there was a universal truth that
    0:02:13 anybody could figure out through measurement and experiment. And that idea, now called the
    0:02:18 scientific method, changed the world more than any other idea. It essentially democratized truth.
    0:02:22 If you got rid of all the previous books, you destroyed them, they should all be able to come
    0:02:29 back to the extent that they were right. And in some sense, you asked me what a loonshot is,
    0:02:34 this idea that there are natural laws in the universe and we can access them through
    0:02:39 measurement and experiment. We take that for granted today.
    0:02:40 It was really controversial at the time.
    0:02:48 Not only was it controversial, it was subversive, it was threatening. It didn’t just suddenly appear,
    0:02:53 it was a 2000 year story of it, that same idea appearing and being quashed and appearing and
    0:02:59 being quashed and appearing, you know, for hundreds if not thousands of years. So why did that idea
    0:03:05 appear there? And in fact, so much of the stuff that we take for granted and fed into that
    0:03:11 revolution came from China, Islam and India, the astronomy, the medicine, the mathematics,
    0:03:16 which came from algebra and India. Many of the technologies, paper and printing had been
    0:03:23 used in China and developed in China and not for 50 years or 100 years, but for a thousand years.
    0:03:28 China did a paper printing compass, currencies, scholar elites,
    0:03:34 agricultural mining that was unheard of, that was not seen in Europe until many centuries later.
    0:03:40 So why Western Europe? What was, and I just kept getting stuck on this question, especially
    0:03:46 when you grow up in, you know, a Western culture, you’re told, well, basically there was the Greeks
    0:03:50 and nothing. Oh, no, you’re so right. I had the same upbringing. I completely relate to that.
    0:03:54 That was like how I’d grown up. It was basically 30 second history of science,
    0:03:58 Greeks, nothing new and done. History started and were modern. And maybe Einstein.
    0:04:04 But the more I started to think about it and the more I realized like there’s something in the
    0:04:11 question of why did these big empires did so well for so long, but why do they have trouble
    0:04:17 innovating? And I realized there was a close parallel to my industry. So I was in the drug
    0:04:23 discovery industry. So the parallel, China, India and the Islamic empires were a lot like
    0:04:28 the Merck, Pfizer, Novartis of today. Fascinating. They were global, everywhere, dominant,
    0:04:33 they’re phenomenal at franchises. So in India, you’ve had the Taj Mahal. You know, in China,
    0:04:38 they built the Great Wall and just incredible, the grand canals. They had a series, sequels.
    0:04:44 But the little tiny ideas got quashed. And where did the incredibly innovative revolutionary new
    0:04:49 drugs come from? From them teaming market of hundreds and hundreds of small biotechs like the
    0:04:53 one that I was at. Essentially, what you’re pointing to is that if you think about how we
    0:04:57 parallel that now, biotechs are just great examples of startups in general, you know,
    0:05:00 and that startups are maybe the ultimate loon shot, right? Especially the reason why often you
    0:05:05 have to do in a startup is that if you try to do it in the big established empire, you know,
    0:05:09 that you’d be either going against what the empire does, or it’d be heretical, it’d be crazy.
    0:05:15 Right. So a moon shot is a big, exciting goal, like you’re in cancer, eliminating poverty. But
    0:05:22 it’s a destination. To go to the moon. Yeah. Like in 1961, when President Kennedy said, let’s put a
    0:05:29 man on the moon, that was the original moon shot. But if you rewind the tape, 40 years earlier,
    0:05:35 there was a guy named Robert Goddard who explained how he might get there with jet propulsion and
    0:05:41 liquid fuel rockets. Kennedy, when he announced his moon shot, was widely applauded. Goddard,
    0:05:46 when he explained that crazy idea, might get there was ridiculed. In fact, there was an editorial
    0:05:51 in the Times when he was talking about his idea that said, well, obviously this guy who, you know,
    0:05:55 has this quote unquote chair in physics at Clark University or wherever, you know, he doesn’t
    0:06:01 understand the basic principles of physics that we teach in high school every day. About 49 years
    0:06:08 after the Times printed that, the day after the successful Apollo 11 launch to the moon,
    0:06:14 the Times printed a retraction and said, apparently rocket flight does not violate the laws of physics
    0:06:18 and quote, the Times regrets the error. Such a victory lap. But that doesn’t happen all the time.
    0:06:22 The fundamental question for anyone listening to this episode who kind of has a lot of
    0:06:28 understanding of the history of innovations is how do you go from being a Goddard to a Kennedy?
    0:06:32 There’s a fine balance somewhere in between them. You don’t want to be the person completely
    0:06:36 ridiculed. You don’t also want to get there so late that it’s already an accepted idea to succeed.
    0:06:41 So when do you know a moon shot becomes a moon shot? Kennedy’s was a moon shot because it worked
    0:06:46 too, right? I mean, if NASA was not able to get to the moon, it would have been a moon shot,
    0:06:50 presumably, right? On this idea of moon shots, I do want to talk briefly about Google X,
    0:06:54 which is in some ways given both a good name and a bad rap to the concept of moon shots in
    0:06:58 multiple levels. One, because they talk about what they do as moon shots. Two, because they
    0:07:04 actually have a project called loon, which has been mixedly received. And so that’s another context.
    0:07:08 But three, I think what is really interesting here is when you think about a moon shot as
    0:07:13 this destination, as you’ve described it, a desire to go somewhere. I think a lot of people
    0:07:19 have a hard time in organizations in terms of teasing apart. What is a shot that’s worth further
    0:07:23 nurturing, regardless of the destination, whether it fails or not? Because I agree,
    0:07:27 there’s no shortage of ideas. But it’s precisely because there’s no shortage of ideas that I want
    0:07:33 to know when can we pick which ones to invest in, because there’s still limited resources.
    0:07:37 Yeah, you’re right. A moon shot is a destination, and we get there by nurturing loon shots,
    0:07:40 which are these crazy ideas. And your question is, how do you prioritize?
    0:07:43 Exactly. How do you winnow those ideas as well?
    0:07:49 I think you want to find the ones that challenge your belief system, because those are the ones
    0:07:57 that are most dangerous to you and your business. So the reason you nurture loon shots is when
    0:08:03 there’s some new crazy idea that appears that’s going to kill one of your business lines, or take
    0:08:08 away your customers, or even open a completely new business line, where would you rather find
    0:08:13 out about it? By reading about it in the press release from one of your large customers who’s
    0:08:18 going to move all their business away, or would you rather find out about it from one of your
    0:08:23 people who presents you one morning with this crazy idea that you were sure was not true.
    0:08:29 And all of a sudden, he or she shows you this great proof of concept that there’s some traction
    0:08:33 to it. I love that you said proof of concept and traction, actually. I’m so glad you said that,
    0:08:38 because when Astro Teller, who heads up GoogleX, wrote an op-ed for me at Wired, he made the argument
    0:08:43 that it’s identifying a big problem, articulating a solution that can actually solve the problem
    0:08:47 if it existed, even if it does not already exist, which is to your point that it is dangerous and
    0:08:52 not out there, but more precisely, when you mention the proof of concept, that there is an
    0:08:56 indicator right now that this thing can become a reality. And that, I think, is like the key.
    0:09:01 So I spent a while talking about this with Astro, who actually I knew well before GoogleX. And one
    0:09:06 of the things that Astro pointed out, which we both agree on, is that using the word moonshot,
    0:09:11 unless you really know what you’re doing, and they obviously really know what they’re doing at X,
    0:09:18 can be very misleading. And it comes back to why there are a few phrases in the English language
    0:09:23 that give me more gas pain than the phrase disruptive innovation. Here’s the problem.
    0:09:29 When people talk about disruption, they’re talking about a market. And if you look across history,
    0:09:35 if you look across the ideas that change a field of science or a field of business,
    0:09:42 or even world history, none of the champions knew anything about where their idea would end up.
    0:09:48 I’ll give you an example, the transistor. It was developed at Bell Labs, although it was based on
    0:09:52 a lot of federal research, but it was developed at Bell Labs, why they were looking for better
    0:09:58 switches. By every definition, it was an incremental innovation, not a quote disruptive.
    0:10:02 Once they figured it out, they didn’t know what they could do. It wasn’t usable in the phone
    0:10:07 system initially, because it was too expensive and too unreliable. So after a bunch of years of
    0:10:10 trying to figure out what they could do with this damn thing, they came up with hearing aids.
    0:10:17 So do you think the scientists working on semiconductor junctions in 1946 and 1947
    0:10:23 told their bosses, we’re working on disrupting the hearing aid market? The word disruptive
    0:10:28 innovation makes sense in hindsight, if you’re a history professor. Right. But not for predicting
    0:10:32 and knowing the future. Right. So the reason using the word disruptive innovation or moonshot,
    0:10:36 unless you know what you’re doing, can be very misleading, is that it causes you to overlook
    0:10:42 the small things that end up having a tremendous difference, because they challenge accepted
    0:10:46 belief, but you thought maybe it’ll just be for hearing aids. In fact, it’s not so much an accident,
    0:10:53 but it’s this emergent kind of building block that’s created that has so much like second,
    0:10:58 third order effects. We had Brian Arthur on this podcast, and he’s like the father of complexity
    0:11:02 theory and economics. And one of it’s, he’s the one who’s sort of studied when network effects tip,
    0:11:07 when these systems sort of, it’s a very sudden, and they’re always like small, tiny tips. There’s
    0:11:13 never some big specific iPhone moment that is a, you know, discrete thing. It’s actually this
    0:11:17 continuum of things. What you want to do is you want to fund a portfolio of moonshots,
    0:11:23 irrespective of market. Nothing kills a great idea faster, and has been more of a disaster to
    0:11:29 innovation, certainly in my industry and drug discovery, than the idea of market projections.
    0:11:34 Forget the market protections. Does it challenge accepted beliefs? If so, let’s go try it.
    0:11:38 That’s what it’s all about. Well, then let me push some more then, because
    0:11:42 then I want to really understand then what distinguishes a good moonshot from a really
    0:11:47 bad one. Because when you are a company, you have limited resources. When you’re an entrepreneur,
    0:11:52 you have limited time and energy to devote into what product you’re going to build.
    0:11:54 And you want to nurture them, but which ones do you nurture?
    0:11:57 Exactly. How do you think about that here? I mean, this is your job.
    0:12:00 Yeah. So first off, you know, it’s interesting from the point of view of venture capital that
    0:12:04 we’re looking for things that have that huge disruptive potential. That’s very much our business.
    0:12:10 And it’s usually the things that Ben has, I think it’s been, or Chris Dixon, talk about how often
    0:12:13 really great companies look like bad companies. Yeah, they both talk about it and they’re actually
    0:12:19 quoting Peter Thiel. Okay. So for example, like, you know, going on the web and meeting strangers
    0:12:23 to ride in cars with you, these things at one time seem like crazy. And now it’s a good idea only,
    0:12:29 because in part what made it seem like a bad idea was also what opened the door for a team to come
    0:12:34 in and have that opportunity. So, you know, for what we’re looking for, especially on the biocide,
    0:12:38 I’m looking for things where they’re right at that cusp between where the science has largely
    0:12:43 been done, where we’re not investing in science projects, and that it’s about to scale into engineering.
    0:12:47 And the small crazy ideas that changed the course of science, business, or history,
    0:12:54 they always stumble. I had this story about Jim Black, Mr. James Black, who was a Nobel laureate,
    0:12:59 very famous, actually chemist, pharmacologist, originally was advising us. I was saying, God,
    0:13:04 he asked me why I was looking kind of down. You know, we were working on this really promising
    0:13:07 drug program in the lab, and it just didn’t, you know, we just had these bad results. And he’s
    0:13:12 like leaned over, you know, padded me on the knee, and this is like 10 o’clock, a couple whiskies in,
    0:13:19 and he’s like, Oh, Sophie, I can’t do a Scottish. Oh, Sophie, it’s not a good drug unless it’s
    0:13:23 been killed three times. That’s fabulous. And so I’ve always thought of that as the three deaths
    0:13:28 of the luncheon. And that’s actually a little different than some of the philosophy here,
    0:13:34 especially in Silicon Valley of, you know, fail fast and pivot. Because in many cases,
    0:13:39 the really good ideas that completely transform industries, they fail the first few times.
    0:13:43 And it’s a false fail. And it’s a false fail. What do you mean by a false fail? I mean,
    0:13:47 I think about in the context of false positives, false negatives. False fail is it’s a failure
    0:13:53 that’s due to a flaw in the experiment, rather than a fundamental flaw of the idea. I mean,
    0:13:57 just as a simple example, Peter Thiel and Ken Howrie, who I remember Ken Howrie was telling
    0:14:02 me this story, you know, a couple years ago, that when they were first looking at Facebook,
    0:14:08 everybody was passing on social networks because it was like the 15th or 16th or whatever social
    0:14:13 network. And right around that time, Friendster was just sort of going down the toilet. And I
    0:14:17 remember what Ken and Peter did was they got access to the, they were like, really, is it
    0:14:24 the case? Maybe that’s the case. But why don’t we just probe and get a little more background.
    0:14:29 And they asked where they knew the CTO and the team behind that they knew that the website was
    0:14:33 having a lot of problems. So they got the user retention data. And they looked at it and they
    0:14:38 were like, holy shit, you know, people are staying on this freaking website, even though
    0:14:42 it’s crashing, they’re staying on it for hours. And they’re like, wait a minute,
    0:14:46 maybe it’s not a bad business model. Maybe actually, it’s a really good business model
    0:14:49 and people are leaving because the website sucks. That’s a false fail.
    0:14:54 And when the lesson is to false fail within an org, if the false fail takes down your org,
    0:14:58 then the other startups that come after you get to benefit from your failure.
    0:15:02 But if you can sort of understand the false field internally, that’s your best bet to
    0:15:06 keep on moving, right? And I think that these false failures, there really wasn’t a failure.
    0:15:09 It was if failures of execution is not a failure at the loonshot.
    0:15:11 And I’m curious to get your take on this, Hafi, because you’ve lived this,
    0:15:15 is that for a lot of drug design projects, when they get canceled,
    0:15:19 Pharma never has the time or the interest. Sometimes it seems to go back and understand why.
    0:15:24 I remember the head of R&D of a very large, one of the top few Pharma one time, we were having
    0:15:30 dinner, we were discussing doing a large partnership together. And we were talking about
    0:15:34 killing projects and your people say, oh, you got to have balls to kill a project. And he said,
    0:15:38 killing a project is the easiest thing in the world. It never comes back.
    0:15:43 And that’s one of the reasons it’s so difficult to innovate inside, let’s say in my field,
    0:15:46 in our field, inside a large drug discovery or research organization,
    0:15:50 is because it’s so hard to keep a project going.
    0:15:52 That’s fascinating, because I would have argued, I would have thought it’s actually
    0:15:57 much harder to kill something than to actually keep something going that shouldn’t be killed.
    0:15:59 Now, it’s the easiest thing in the world to kill a project.
    0:16:04 It’s much harder when, because of the three deaths of the luncheon, because really good ideas
    0:16:08 often seem really stupid in the beginning, as soon as they hit that first stumble,
    0:16:12 it’s much harder to justify to your colleagues.
    0:16:14 That’s true in a big company. Do you think it’s true in a small company? In a small company,
    0:16:19 if this is your thing, killing something is actually the dreaded pivot, right?
    0:16:22 And so maybe in a small company, is it less likely that people want to kill it?
    0:16:27 Well, this comes down to the incentives. The underlying theme of this book is let’s look at
    0:16:34 structure rather than culture. I became a first-time CEO. I think I was 32 or three.
    0:16:37 And probably like a lot of first-time CEOs and entrepreneurs,
    0:16:42 I read everything I could find about management, how to be a better leader,
    0:16:47 how to build a great company, how to empower my employees and get great returns from my
    0:16:52 stakeholders and achieve our big mission. And almost everything I read about was about
    0:16:59 building a great culture. And as a physicist, that felt kind of squishy to me. And there’s also
    0:17:04 that sort of after the fact, let’s say somebody wins a lottery and you say, “Well, that’s
    0:17:09 fantastic. What color socks was he wearing? Let’s all go wear.” I did want to see if there was a
    0:17:16 little more of a scientific underpinning. Let’s do the behavioral economics, but of groups.
    0:17:19 And as soon as you arrange people into groups, what are these sort of hidden incentives? That’s
    0:17:24 the kind of thing that I didn’t think about for 10 years and kind of none of the traditional
    0:17:28 management literature has really looked at. So it’s interesting you bring up behavioral
    0:17:33 economics because prospect theory itself was a very dangerous idea to the establishment at the
    0:17:38 time. And yes, there’s a lot of debates right now in the literature about how robust those findings
    0:17:43 are so many years later. But that aside, it was a very important contribution. I’m curious for
    0:17:49 how that connects into your worldview. Sure. In fact, that’s kind of one of the most fun things
    0:17:54 for me because what Kahneman and Firsky did was they found a new Venn diagram intersection of
    0:18:00 psychology and economics. And this is a new Venn diagram intersection of physics and economics.
    0:18:06 Oh, interesting. I love that. So you simply look at the incentives for individuals whenever you
    0:18:12 organize into a group. It’s only relevant inside a group. And then you borrow an idea from physics,
    0:18:17 which is a phase transition. How does this phase transition idea come into play? I mean,
    0:18:21 you’re a physicist by training. So I get that there’s a physics aspect to this. But how does
    0:18:26 this play in the innovation organizational context? Every phase transition in nature is a result of
    0:18:32 two competing forces, a tug of war. And the phase transition is as you adjust the balance,
    0:18:39 you change certain parameters of design or the environment, you adjust the balance between
    0:18:44 those two forces and boom, at some point, they cross and the system snaps. I’ll give you an
    0:18:48 example with water. There’s a glass of water right here, which your audience can’t quite see.
    0:18:52 I’ll take a photo. But you can imagine. When I stick my finger in the glass of water,
    0:18:59 I can swish it around, right? Except as I gradually lower the temperature, all of a sudden,
    0:19:04 at a critical temperature, boom, the behavior completely changes.
    0:19:12 So when it freezes. Exactly. Why? How did those molecules know to go from sloshing around and
    0:19:17 being fluid to being completely rigid? It’s the same molecules. And it’s the exact same molecules.
    0:19:23 There’s no CEO molecule with a bullhorn. And that’s sort of the other counterintuitive thing
    0:19:28 about this is it doesn’t matter what the CEO does. Okay, it’s not about the culture. Yeah,
    0:19:34 it’s about understanding those two forces and what are the balance. So here’s the two forces
    0:19:40 in a glass of water. There’s one force, entropy, which wants to makes water molecules run around
    0:19:46 and be free. Right. The creative force, one could argue. If one wants to do that, entropy is actually
    0:19:53 a hard physical quantity. And it is the case that molecules have two competing forces, one of which
    0:19:58 is entropy, which wants to make them run around and be free. And the other is binding energy.
    0:20:04 It wants to lock every molecule of water, exactly 2.8 angstroms from its neighbor.
    0:20:10 When the temperature is high, entropy wins. Now, as you gradually lower the temperature,
    0:20:16 the entropy force gets weaker and weaker and weaker. And the binding energy gets more and more
    0:20:22 important. And then what happens? Boom. At 32 Fahrenheit, those two things cross. Below 32,
    0:20:28 it becomes totally rigid. So it has nothing to do with the CEO molecule yelling, be rigid, be fluid.
    0:20:32 Let’s adopt a fluid culture and all slush around. The CEO can set the temperature.
    0:20:37 That’s exactly right. Control parameter is the equivalent of temperature. It controls the
    0:20:42 behavior of the system. It turns out when you work out the mathematics of this, of the incentives,
    0:20:47 the two forces, there are four control parameters inside organizations, elements of organizational
    0:20:53 design. And not the CEO, the executive team, the board has control over, just like you have control
    0:20:58 over a glass of water. In classic innovation parlance, it is sort of disruptive versus non-disruptive
    0:21:03 core versus non-core, these two forces. However you describe them, the point is that organizations
    0:21:08 clearly have these two competing forces. So back to not being, you know, the cultural stuff that
    0:21:14 management literature gives us, what structurally needs to happen to make organizations know how
    0:21:21 to navigate these two forces? Okay. So when you bring a group of people together and you organize
    0:21:27 them and you set a mission and you tie a reward system, incentives tied to that mission, all of
    0:21:35 a sudden you create two forces. And here’s what they are. The first one is stake in outcome.
    0:21:43 Think of that as equity. So let’s say to stick with our industry, you have a small biotech company
    0:21:46 and you’re developing a new cancer drug. Your stake in outcome is your stake in that drug
    0:21:52 success. Does it work or not? Now when you’re a small, your stake in outcome is enormous. If the
    0:21:58 drug works, everybody’s a hero and a millionaire. If the drug fails, everybody’s unemployed.
    0:22:02 Right. What’s the second force? It’s perks of rank.
    0:22:08 Interesting. So you can think of this almost as equity in cash or equity in base salary.
    0:22:14 When you’re a tiny small company, stakes in outcome are so much bigger than perks of rank.
    0:22:21 Now let’s flip it. Let’s say you, Sonal, are a manager at Pfizer. So now let’s look at your
    0:22:26 incentives. What’s the stake in outcome? Well, if you make a good drug, let’s say it sells
    0:22:31 500 million a year, that’s a pretty good drug. Plus you’re going to be fighting for the next seven
    0:22:35 or 10 years. Everybody wants your budget and there’s going to be the three deaths with the
    0:22:38 loon shot. You’re going to have to try to defend it. So your stake in outcome is pretty tiny.
    0:22:44 What’s the perks of rank? Well, if there’s a committee meeting and you sit around the table
    0:22:48 and keep, you know, trashing these loon shots and doing it in a very thoughtful wise, and maybe
    0:22:54 you’re very funny and kind of witty, and they’re like, well, this young person, she’s got a great
    0:22:59 head. She’s aligned with our vision. Right. What might you get? Promoted. Exactly. And then what
    0:23:04 happens when you’re promoted? 30% bump in salary. And not much change in stake in equity, actually.
    0:23:11 Exactly. So we just went from small, a small company, stake in outcome was much bigger.
    0:23:17 Perks of ranks were irrelevant. To large, where stakes in outcome is very small and perks of
    0:23:21 rank. So that’s very much equivalent to the water. These are the dynamic two forces that you’re
    0:23:26 describing. Right. And instead of temperature, it’s size. So somewhere between small and large,
    0:23:31 as you grow and you grow and you grow, all of a sudden the balance of incentives suddenly shift.
    0:23:38 And the same person, the same sonal, would go from pounding the table. This is the most awesome idea
    0:23:42 to kind of making fun of it at committee meetings. You know, I think this makes a ton of sense. And
    0:23:46 we see it in big companies. And I think the challenge then is, you know, as your company is
    0:23:51 growing, what can you do about it? So let me ask you a question. When it snows overnight,
    0:23:56 what do you sprinkle on your sidewalk? Salt. Why? Because it blocks the snow from
    0:23:59 hardening and freezing over. Exactly. And the reason it does that is because adding salt to
    0:24:05 water lowers the freezing temperature. This is a control parameter. It is another. So
    0:24:09 the really interesting thing about complex systems, which is what we’re talking about,
    0:24:13 whether it’s a glass of water or humans understanding incentives when you bring people
    0:24:18 together in a group, is that they have more than one control parameter. There are four other control
    0:24:24 parameters. And to what Vijay was saying earlier, that’s what a manager or a leader or an executive
    0:24:29 team or a board can control. You may not control size. You may need 100 people. You may need 500
    0:24:34 people. You may need 10,000 people. And that, you can’t control, but you can add a little salt.
    0:24:37 It’s interesting to think about how far the analogy goes and where it breaks down. So I think one of
    0:24:42 the most powerful things about it is the fact that you can take the same person from one face to the
    0:24:46 other. I agree. Just like with the molecule. Yeah. So that part is really interesting. And also,
    0:24:51 just what you’re talking about, you can imagine doping and putting in certain types into given
    0:24:55 phases to change their behavior. And I think we’ve seen that in various groups, right? You can put a
    0:24:59 certain type of person to a team. And so some people will change with phases. Some people are
    0:25:04 just intrinsically different. I thought where you were going with this was doping in semiconductors,
    0:25:07 which actually gave us the transistor. Well, you know, but that doping either one,
    0:25:10 you’re talking about alloys or semiconductors is the same concept, right? Actually, it’s exactly
    0:25:15 right. If you take an insulator like silicon and you dope it a little bit and then you get a metal
    0:25:20 and it’s a phase transition. That’s what Phil Anderson won his Nobel Prize for, is the localization
    0:25:26 transition, the metal insulator transition. But to get to your question, yes, this is a phase
    0:25:32 transition. That’s kind of the theme of the book. CEOs at the end of the day, they’re sort of lamenting,
    0:25:36 oh, no one cares. Well, that’s because they don’t own half the equity of the company like you do.
    0:25:41 But when you were a small startup, of course, everybody, their incentives were aligned.
    0:25:45 And of course they rushed out because they were going to be unemployed if the loonshot failed.
    0:25:49 I find it’s a very hopeful idea, quite honestly, because you’re saying that you can,
    0:25:53 you essentially can be a big company that can figure out how to innovate. You can be a small
    0:25:57 company that doesn’t innovate, that actually sometimes goes into the frozen zone without
    0:26:02 figuring out how to keep the entropy moving and the creativity and the excitement moving,
    0:26:08 and that you can more precisely be both at the same time. And you can file up or down various
    0:26:13 parameters to make that happen. So I find that’s a very hopeful message. A question I have, and
    0:26:18 when you think about the history of innovation, kind of going back full circle to what makes
    0:26:23 something a loonshot versus a moonshot. And yes, I heard you, a moonshot’s a destination,
    0:26:30 a loonshot could be a false fail along the way. I still want to understand how you know when a
    0:26:37 field, an area becomes more ready to be optimized a certain way.
    0:26:42 This reminds me a lot of just the general topic of how a biology right now is shifting from
    0:26:47 science to engineering. And there’s lots of different trends and reasons why. We talk about
    0:26:51 these two different groups, the sort of creative types, the inventors, the artists versus the
    0:26:56 the soldiers, the people who get things done. We’re seeing that shift in biology as one can
    0:27:01 finally engineer biology in many ways. So in that field then, when you move from say artistry to
    0:27:06 soldierry, for lack of a better phrase, the way I’ve heard you describe this is like the bespoke
    0:27:11 to the machine automator. How do you in this particular example know? Yeah, I mean, that’s the
    0:27:16 billion dollar or trillion dollar question, right? Yeah, literally. And so, you know, what it comes
    0:27:21 down to when, at least for me, what I’m looking for is both in Safi’s language that there is a
    0:27:27 destination that we see where you would land, and that at each step of the way that there is a way
    0:27:31 to do it through engineering like execution, there’s all these different places where bio plays
    0:27:38 a role, either with consumer or with healthcare or other industries. And in each one, it’s just not
    0:27:42 enough that there’s a technology in our product that there really is probably market fit. And
    0:27:46 that’s always unavoidable. And probably market fit is one of the hardest things for anyone to
    0:27:52 sort of just theorize, you know, because you can very easily be wrong, or you can be wrong,
    0:27:56 could be three years too early. It’s not wrong, it’s when. It’s when. And so, some of that also,
    0:28:01 you have to have the intuition that it’s now, you can have theses for why it’s now. In the end,
    0:28:06 the market will tell you whether you’re right. Like the classic example, Xerox was a great example
    0:28:10 of a disruptor in earlier days with just the copying machine. People are like, “Well, I don’t
    0:28:14 need copies. What do I want copies for?” You know, it just wasn’t part of the workflow. You wouldn’t
    0:28:18 think to use a machine that doesn’t exist. And that only after people start to understand, “Oh,
    0:28:24 actually, it was really useful to have this,” did you create a market. And so, in a sense that
    0:28:30 device had product market fit before the market was there. And so, I think, I agree with Sophie in
    0:28:34 the sense that just because the market isn’t there now, isn’t a reason to kill it. But obviously,
    0:28:38 there has to become a market. Otherwise, there’s no one to buy it.
    0:28:42 I would then argue just to reconcile these different views. It basically is how you,
    0:28:46 the word market, just might be over-indexed. Because what we’re really talking about is a
    0:28:51 pull, a draw, a need. But some might even say a want. Because sometimes you don’t need something.
    0:28:55 You might just want something but not know that you want it in the classic Jobsian sense.
    0:29:01 Right. In the sense of some, I mean, I can bring it to very nuts and bolts. Someone’s got to pay
    0:29:04 for it. And this is one of the mistakes I see over and over again with startup founders is that
    0:29:10 when they’re small, it feels like they’re all artists. They do a great job of building an org.
    0:29:14 And then suddenly, the org is not what they’re comfortable with or familiar with because they
    0:29:18 have built an army. And they actually never want to join the army. Right. They don’t want to be navy,
    0:29:22 actually, in that context, right? So, when you think of artists versus soldiers, this idea that
    0:29:26 there’s the creatives and the builders and the people have to fight the war on the ground,
    0:29:30 another way to think about it is Jobs’ famous quote about pirates versus navy. I mean,
    0:29:33 there’s so many different variations of this over time in innovation history.
    0:29:37 I think our companies have both too. But hopefully, there’s something for the soldiers to start
    0:29:41 working on, you know, to go to war on, even though, you know, you constantly have to continue to
    0:29:46 innovate. So you need both. But so when I think about how I’m going to find them, I want to find
    0:29:50 things that are just at that transition. If it’s only artists, it’s not going to work. But once
    0:29:54 they’re there, we have to think about which ones have the opportunity to become the moonshots
    0:29:58 eventually. And which ones also, frankly, that can continue to innovate. And so one of the things
    0:30:02 I thought was interesting about the book was that phase transition interplay between the two and
    0:30:07 how it’s not a bad thing to have that phase transition. And that was maybe one of the more
    0:30:10 surprising things. There are two things that I find very hopeful. I know a lot of people have
    0:30:17 found very helpful. One is, and they’re both a little bit against the grain of what you often hear.
    0:30:20 I love things that are against the grain. More against the grain, the better.
    0:30:25 Especially what I hear from my tech friends in Silicon Valley. So one is don’t hire people from
    0:30:31 big companies or big people from big companies are a terrible fit. And I thought that as well.
    0:30:34 We’re doing the great stuff because we’re the risk takers. We’re the innovators and all those big
    0:30:40 corporate guys, they’re risk averse and that’s why you shouldn’t hire. And then as you grow up,
    0:30:43 you start doing these partnerships with large farmers. So you’re spending a lot of time with
    0:30:48 these people and you get to know them well. And then these people are just like us. If they’re
    0:30:53 advisor and they have no stake in outcome and a ton of stake in getting promoted, what do you think
    0:30:57 they’re going to do? They’re going to work on being promoted. And if they’re at a 50-person
    0:31:03 startup and being promoted or titled is totally irrelevant, but whether the project works or not,
    0:31:06 means whether they’re unemployed or not, what are they going to do? They’re going to pound
    0:31:11 the table and save the thing if it stumbles. So it’s about the subtle influence of incentives.
    0:31:16 And when you really peel back the layers on that, you tease out all these things that you can do
    0:31:21 to balance the incentives better for what you’re trying to achieve. So that’s one hopeful thing.
    0:31:25 It’s not really about there, these two kinds of people. You should never hire a big corporation.
    0:31:28 It’s the same person in different environments. Exactly. It’s the molecule that lands on the
    0:31:34 block of ice versus the molecule that drops in a glass of water. So okay, now you say these
    0:31:40 organizations have these phase transitions when they grow, they go from being totally fluid and
    0:31:46 embracing wild new ideas to being quite rigid. So what do we do if we are a 500,
    0:31:52 a thousand, or 10,000-person company? And so the point is that innovating well is a phase of
    0:31:58 organization, just like being solid or liquid is a phase of matter. It’s a property of the whole
    0:32:02 that doesn’t depend so much on the details of the parts. That’s what it means in
    0:32:06 science or physics of an emergent behavior. And actually, it’s just sort of straightforward
    0:32:12 mathematics. And the book that innovating well and a focus on politics or not is a phase of human
    0:32:15 organization. I love that you actually have an equation that you outlined in the appendix,
    0:32:20 which is awesome. We’ve never seen that in a management book. That took a lot of convincing
    0:32:25 with the publisher. That’s another story. It got relegated. To the appendix. We’re way back there.
    0:32:33 But anyways, if it’s a phase of organization, there are operationally excellent, high execution,
    0:32:39 or you are innovating well. Larger companies today or startups that have grown need to do both.
    0:32:43 Yeah. Mark talks about how startups are on the sort of five-year cycle theory. And I think of
    0:32:48 this a little bit like growing versus sustaining organizations that even startups, by definition,
    0:32:53 after a certain amount of time, have this inevitable gravity that begins to hit because
    0:32:56 there are other startups coming out there sort of doing things faster.
    0:33:01 Part of it is that also these environments keep on changing as we were talking about. And so
    0:33:05 as the environment changes, the question is how we can sort of push back on the environment. And
    0:33:09 maybe to abuse the analogy in physics with phase transitions, you can have hysteresis.
    0:33:15 Which is… You can push the environment past where something… So there’s a really fun thing
    0:33:20 to do. And so kids, you could do this at home. For the beer, put in the freezer. You take it out.
    0:33:25 And it looks like water. But it’s already below the freezing temperature. And you just knock it.
    0:33:29 And it’ll suddenly, it’ll freeze right in front of you. I’ve never done that. I’ve never got kids out of it.
    0:33:34 The knocking kind of catalyzes this. And so this is a historic effect that it really should have been
    0:33:39 a solid. But that it was lingering in the old phase for a little bit. What’s the point of that?
    0:33:43 So the point is, you may think you have innovation in your org. And you may think that you have the
    0:33:49 environment. But it is just a message of the past. And in an instant, you can lose it.
    0:33:54 Just like the beer can shift. And so you need to really understand what your environment is.
    0:33:59 And as a CEO, as a leader of something, you have to understand your org. You have to look to see,
    0:34:04 do you have this phase segregation? Do you have two healthy phases there? The pirates in the navy,
    0:34:08 the artists and the soldiers. And then what do you need to do to sort of affect the balance?
    0:34:12 And it can be the hysteretic argument is that it can be misleading sometimes, too.
    0:34:18 I love that beer example. So it is absolutely true that matter can’t be in two phases at the same time.
    0:34:25 You can’t be solid and liquid at the same time. So if complex systems can never be in two phases
    0:34:32 at the same time, you can’t be solid and liquid. You can’t be water and ice. How can you do both?
    0:34:36 There’s one exception to the rule that you can’t be in two phases at the same time.
    0:34:44 And that’s right on the edge of a phase transition. Life at 32 Fahrenheit. What happens is,
    0:34:51 matter separates. You get blocks of ice and pools of liquid. So you get phase separation
    0:34:56 and they coexist at the same time. The second thing that happens is you get something called
    0:35:00 dynamic equilibrium, which the molecules go back and forth and back and forth. Little molecules
    0:35:05 swimming in the pool of liquid hits on the block of ice and freezes. A molecule on the surface of
    0:35:10 the ice starts shaking loose and then goes into the pool. And it’s back. It’s a continuous cycle.
    0:35:14 I mean, if you think about the word dynamic equilibrium itself as a seeming contradiction,
    0:35:17 but it’s not in this context because it’s dynamic and in equilibrium at the same time.
    0:35:24 Exactly. It’s a balance cycle of exchanging back and forth with neither side dominating the other.
    0:35:30 And that’s what happened during World War II. Vannevar Bush came in, told FDR, he said,
    0:35:35 “We’re going to lose this war.” At a 10 minute meeting in the summer of 1940, he said, “We are
    0:35:40 far behind the technologies that are going to be crucial to winning this war.”
    0:35:46 The culture of the military, not only is it resistant to new technologies like any
    0:35:50 military culture, but it should be. It is the right culture for their job.
    0:35:53 In this case, they’re literally soldiers.
    0:35:58 They’re literally soldiers. And he said, “I want you to give me a group of people,
    0:36:03 give me the authority to mobilize the nation’s scientists for war and we’ll develop the radical
    0:36:08 new technologies and I’ll report just to you.” So he created phase separation within the federal
    0:36:13 government. And to this day, that really is the origin of the national research infrastructure
    0:36:20 of the United States. The National Science Foundation, the NIH, DARPA, came out of Vannevar
    0:36:27 Bush’s idea during the Second World War. But he made sure where most, where this fails so often,
    0:36:32 so many years, so many times across companies. I mean, Xerox Park is a great example of that
    0:36:37 because it was overly siloed. They missed the second part, which is the dynamic equilibrium.
    0:36:39 Constantly moving back and forth.
    0:36:44 So here’s the message for entrepreneurs or leaders or managers, which is also a little
    0:36:51 different than what you get typically in Silicon Valley and is different than the model of a great
    0:36:57 manager, a great leader. And that is, there is this myth that the great manager, the great
    0:37:03 leader of a technology company is this product, product, product person and they build their…
    0:37:07 Oh, you’re really fighting some major dogma right now. This is going to be blasphemous.
    0:37:08 I want to hear it.
    0:37:13 They build the company, this great company on the back of their inventions.
    0:37:21 So the companies across history that have done that have failed spectacularly. They may survive
    0:37:27 for a while when there’s a Moses on the mountain with a staff anointing the next Holy Loonshot.
    0:37:32 They may survive for a while, that’s the hysteresis effect,
    0:37:36 but eventually they’ll turn. That’s exactly what happened with Polaroid when Edwin Land,
    0:37:42 who certainly deserved Nobel Prizes for some of his breakthroughs, stood on top of that mountain
    0:37:46 and anointed the next Holy Loonshot and that was the end of Polaroid.
    0:37:51 So the difference, the ones who have really succeeded, let’s say Vannevar Bush,
    0:37:55 a theater veil at AT&T, the ones who really succeeded didn’t have that mindset.
    0:38:01 Vannevar Bush was a brilliant inventor. He invented the first analog computer. He anticipated
    0:38:04 much of the personal computer industry and certainly the internet and…
    0:38:06 He wrote that memex memo, right? I remember reading it.
    0:38:11 The famous essay published in the Atlantic, which inspired Doug Engelbart and a lot of
    0:38:16 that traces back to Vannevar Bush, but as he likes to say, “I made no original contribution
    0:38:21 to the war. None of my inventions ever amounted to anything.” What he did, rather than lead as a
    0:38:28 Moses, he led as a gardener and he saw his job as maintaining life at 32 Fahrenheit.
    0:38:32 Setting up the structure, the scaffolding that allowed that dynamic equilibrium,
    0:38:38 that living at the edge. He maintained the balance between his group and the military.
    0:38:44 And so if there’s a lesson there, it’s not about your ideas. Your job is to maintain life at 32
    0:38:51 Fahrenheit. Your job is to maintain the exchange of… Because where innovation fails is not in the
    0:38:56 supply of new idea. It’s in the transfer of those new ideas to the field. It’s actually like Xerox,
    0:39:01 exact same thing. They were giving these computers to people selling typewriters and what were they
    0:39:04 being commissioned on? Typewriters. Exactly. It was a very sales-driven organization.
    0:39:10 It was a subtle influence of incentives. Bush recognized that the dynamic equilibrium,
    0:39:16 it’s not just transfer one way from the scientist or the artist or the creative engineers to the
    0:39:21 salespeople or the soldiers in the field, but the other way. Because most ideas suck when they first
    0:39:27 come out of the lab. There’s a huge jump from a technology to a product, like a really beautiful
    0:39:30 product. And then even if you have a really beautiful product, you still have to create a
    0:39:35 market and sell to sell it. I was outside of my Stanford office after I’ve been at ACSNZ for a
    0:39:40 while. And a founder at Stanford came by and he’s like, “You present this whole new tech.” And he’s
    0:39:44 like, “Oh my god.” And I was like, “Well, this is really interesting, but I’m not sure you could
    0:39:48 build a company.” And he’s like, “You know, the physics was so hard, building a company will
    0:39:54 be easy.” But actually, the tech is not enough. And this goes back to Steve Jobs’ story is learn
    0:39:59 to love your artists and soldiers equally. So when Steve Jobs started his first time at Apple,
    0:40:06 he was exactly like that. I only love the artist. And people who know the history know this quite
    0:40:12 well. It was a disaster. So the Lisa that he tried to run was a flop, the Apple 3 that when it was
    0:40:16 a flop. And when he developed the Macintosh, although it was a phenomenal ad that goes down in the
    0:40:22 history of advertising, it was a disaster as a product. The sales completely plummeted. He
    0:40:28 loved his artist and he ridiculed the soldiers. And it caused enormous dysfunction and it almost
    0:40:34 made Apple go bankrupt. And then he did this same thing at Next. When his next computer company,
    0:40:38 it was product, product, product, it’s all about the product, da, da, da, da, da. And that was,
    0:40:42 that product flopped. And then he bought this little company, this Lucas Film Group, because
    0:40:46 they had a computer. And he thought this is an even bigger, faster computer, the Pixar Image
    0:40:52 Computer called PIC. And that product flopped. But eventually over 10 years, when he came back
    0:40:58 to Apple the second time, he had Johnny Eve, that was his artist, and he had Tim Cook. Tim Cook was
    0:41:02 known as the Attila the Hun of Inventory before. And the myth around him, oh, is all his ideas,
    0:41:07 and he championed the product. That’s not really what happened. In fact, when he did that, it was
    0:41:13 a disaster. And only by evolving and learning to love his artists and shoulders equally,
    0:41:19 that’s when things really took off. And that’s why Vannevar Bush succeeded. And so many scientists
    0:41:24 before him failed, because soldiers love soldiers. Artists love artists. He not only worked well
    0:41:29 with the military, he loved them and respected them. And that’s why he was able to bridge the
    0:41:33 two. Yeah. I would argue just to Vijay’s point too, though, that this is why there’s such a
    0:41:39 resurgence in modern tech management literature and startups in particular, around the important
    0:41:43 role of product managers and product management. Because traditionally, there was so much discussion
    0:41:49 around engineering and sales and design, all being sort of separated and siloed. But now,
    0:41:52 through this, and it’s not a new role, it’s been around for ages. But in a sense, that product
    0:41:58 manager role is to connect the engineers to set the temperature. Exactly. There’s sort of like
    0:42:02 this person who maintains a dynamic equilibrium between orgs, they move and travel. I actually
    0:42:07 think it’s actually one of the most important schools of thought for the future of the firm
    0:42:11 in the startup to company environment, which is the evolving role of product management in this.
    0:42:16 Because that is the concrete instantiation of exactly what you’re describing, Safi.
    0:42:20 There’s all these different threads going on here. Bush and his famous memo right after World War
    0:42:26 II define what basic research is. And in Safi’s concept of dynamic equilibrium,
    0:42:32 by, I think, inadvertently talking about the separation between science and engineering,
    0:42:35 he kind of pulled engineering away from scientists. Oh, that’s fascinating.
    0:42:40 Yeah. And that now there was these two different disciplines and science is done by scientists
    0:42:45 and engineering is done by engineers. And that actually took a little bit about that
    0:42:50 equilibrium that was there our way. And so what we’re seeing now is something different where
    0:42:54 scientists are doing translational work, which is another name for engineering.
    0:42:59 And in biology in particular, the shift from science to engineering is becoming very powerful.
    0:43:03 And one of the things I think is always a topic very germane, I think, to our listeners and to me
    0:43:09 is one of the more things that we can do that to practically learn from this. Because I think the
    0:43:14 analysis is very compelling. But if you’re a CEO right now, what can you do? I mean, what are the
    0:43:19 knobs? And so in the book, you talk about one of the classic things being the magic number.
    0:43:24 Basically, a number of people at which beyond that, it’s hard to, you have to start to create
    0:43:29 an org and a hierarchical structure too often. And the magic number is canonically 150, but
    0:43:35 often I see the magic number being 30 when it’s not built right. And so how can you push it
    0:43:38 such that you can try to maintain what we loved about the start from the beginning?
    0:43:43 Right. So this idea of a magic number, like the Dunbar number comes from the idea that the number
    0:43:48 of neurons in your brain is fixed. So sometimes, as you know, in science or in physics, you might
    0:43:53 have a good observation, but the wrong theory. So if you just look at the hidden influence of
    0:43:59 incentives out pops a size, but it’s not a fixed number. I have a little fun with it because I
    0:44:05 show how if you plug in certain things, it can be 150, but it can be as low as 30 or as high as
    0:44:11 5000, because it depends on these four parameters. So when you adjust these four parameters,
    0:44:14 you make those numbers bigger. What are the four parameters again? I don’t actually think we listed
    0:44:21 them. There’s equity fraction. For example, to what extent is a person being incentivized by
    0:44:26 base salary, in which case there’ll be a ton more focus on politics versus to what extent are they
    0:44:32 being rewarded on their project? Right. Another parameter is you might call it return on politics.
    0:44:41 To what extent is the system’s design so that individuals can lobby their managers for promotion
    0:44:46 and that has an impact? Obviously, the more impact lobbying has, the more political and the more
    0:44:52 careers matter, but some companies, actually Google does this, McKinsey does this and others,
    0:44:56 they take the promotion decisions completely away from the manager. So that’s
    0:45:02 another example. Right. And then the third? The third one is project skill fit. So if you’re very
    0:45:07 if you’re very good and working more on your project, moves the project, if you’re a coffee
    0:45:12 machine designer, you’re good at coffee machine design, then you’re likely to spend more time on
    0:45:16 your coffee machine. I love that idea. It’s like founder market fit. It’s like writer topic fit.
    0:45:19 It’s this idea that you really match the skills and passion of the person
    0:45:23 so well with the thing they’re working on. This is project skill fit. Now, if somebody puts you
    0:45:28 on coffee machine design and you’re like me, not a very good designer with very little aesthetic
    0:45:33 sense, then it doesn’t matter if you spend an extra hour or 10 hours or 100 hours on your project,
    0:45:37 it’s going to be still the same lousy coffee machine. You might as well spend your time on
    0:45:43 politics and lobbying. So project skill fit is another parameter. And the fourth parameter?
    0:45:49 Management span. So there’s a lot of literature on management span, but they kind of miss the
    0:45:55 point. There isn’t a right management span. There’s the right span for your goal. So for example,
    0:46:00 if you are building planes, you don’t want to assemble 10 planes and see which eight fall
    0:46:06 out of the sky. You don’t want a very innovative risk taking. Right. You don’t want to be doing
    0:46:09 that with like autonomous cars, for instance. Right. So there you actually want to narrow
    0:46:14 a span because that encourages quality control and redundancy checking because you don’t want
    0:46:19 those eight planes. On the other hand, if you want to do a ton of experiments and have groups
    0:46:24 work together well, you actually want a very wide span. So there’s no right answer for a company.
    0:46:28 And that’s what like all these things that average across the company make no sense at all. Right.
    0:46:33 If the group that’s assembling planes, you want one kind of system, one kind of metric,
    0:46:38 you want narrow spans, you want high quality controls, the group that’s creating crazy new
    0:46:42 technologies for those planes, you want those spans as wide as possible with very different
    0:46:50 metrics. So there’s a handful of these parameters and those are what you adjust to tune for the
    0:46:55 goals that you want to achieve. Yeah. So many of the world’s problems that can be addressed through
    0:46:59 bioengineering, healthcare comes off naturally into many different sub parts about healthcare,
    0:47:02 but just the world around us is created by biology, whether we’re talking about
    0:47:08 the food we eat, the air we breathe, just about everything. And so that is a huge opportunity
    0:47:12 for companies to come in and become huge companies because of the potential of the problems they
    0:47:17 can address. And it’s just fascinating to think about how the dynamics of human nature comes into
    0:47:22 play here and that there really are these knobs that a CEO can turn. And now I think the question is,
    0:47:26 can you really read your organization right and understand what the temperature is?
    0:47:30 Finding the thermometer or the equivalent starts to become, I think, really critical.
    0:47:33 And if you can find that and know where these knobs are, I think you could
    0:47:37 have a huge impact on your work. Yeah, that’s great. Thank you for joining the A6NC podcast.
    0:47:40 Thank you so much. Thanks. It was a lot of fun to be here.

    with Safi Bahcall (@safibahcall), Vijay Pande (@vijaypande), and Sonal Chokshi (@smc90)

    A ”moonshot” is a destination (like going to the moon, quite literally) — but nurturing ”loonshots” (which often involves a number of stumbles along the way) is how we get there. This goes beyond the trite mantra of failing fast! It is about not having ”false fails” or not killing the seemingly small ideas that could lead to outsized yet unexpected outcomes, observes Safi Bahcall (physicist, ex-startup founder, and CEO of a public biotech company), author of the new book, Loonshots: How to Nurture the Crazy Ideas That Win Wars, Cure Diseases, and Transform Industries.So in this episode of the a16z Podcast — in conversation with a16z bio general partner Vijay Pande and Sonal Chokshi — Bahcall shares why concepts like ”disruptive innovation” cause him gas; why doing market projections can sometimes be crap; and why most management books that focus on culture are b.s.Because CEOs and culture, argues Bahcall, do not control organizational behavior… but hidden incentives, ”phase transitions”, and specific control parameters do. So how can organizations — of any size, big or small — be in two states at the same time: both fluid and stable, soft and solid, with high entropy yet bound energy, and both artists and soldiers? The answer may be in a more scientific, less ”squishy” framework for management at the intersection of physics and economics. Big empires always miss the small but important new ideas… can this be why?

  • a16z Podcast: For the Billions of Creatives Out There

    AI transcript
    0:00:06 Hi everyone, welcome to the A6NZ Podcast. I’m Sonal. Today we have a unique sort of
    0:00:11 crossover episode with writer/director/producer Brian Koppelman, who, with his partner David
    0:00:16 Levine, also wrote some of the most popular and still-discuss movies like Ocean’s 13
    0:00:21 and Rounders, which we’ll also touch on in this episode. But currently, Brian is a co-showrunner
    0:00:26 with David on Billions, which airs on Showtime and the newest season actually drops this weekend.
    0:00:30 The reason I’m calling this a sort of crossover episode is that Brian also interviewed Mark
    0:00:36 Andreessen for his podcast, The Moment, which you can listen to on iTunes and elsewhere
    0:00:38 if you want to hear more of their thoughts on the difference between hallucination and
    0:00:44 vision, putting your art or products and yourself out into the world, and more. We also put
    0:00:49 the written Q&A version of that conversation up if you want to read it on A6NZ.com. But
    0:00:52 there are two separate conversations, so you don’t have to have listened to either to
    0:00:57 follow both. Today’s discussion begins with Mark interviewing Brian, and I jump in in
    0:01:01 between here and there as well, starting with the business of creativity and the creativity
    0:01:07 of business, then going into how to speak to power, speak to one’s team, speak to co-partners,
    0:01:11 as well as managing the emotions and ego around all that. And finally, ending on some specific
    0:01:16 moments about Billions The Show in the last 10 minutes, where I’ll signal a light spoiler
    0:01:21 alert warning beforehand. We’re here to talk about the business and making of film and
    0:01:27 TV, and startups, and tech, and the parallels, and whatnot. Take it from the top, Mark.
    0:01:31 Fantastic. So, Brian, thank you for doing this. So, I’ve always been fascinated. I’m deeply
    0:01:37 fascinated by the process of creative expression and success, for sure, in technology. And
    0:01:40 we think of what we do up here as fundamentally trying to find the most creative entrepreneurs
    0:01:44 and trying to help them build enormous, both creative and professional and business success
    0:01:49 around what they do. And it strikes me for a long time that there are a lot of similarities
    0:01:54 between how the valley works and tech works and how entertainment works, film, television,
    0:01:56 other forms of entertainment works. There’s some big similarities. There’s also some
    0:02:00 big differences, which hopefully we’ll talk about. You know, Gallagher’s obviously been
    0:02:04 super successful across both film and television for a long time, and even before that in music.
    0:02:08 But I’m going to focus on film and television. Let’s start with this. What was the first
    0:02:12 project that you, and I think it was you and your partner, David, first project that you
    0:02:17 view that you and David were responsible for creating, selling, and making?
    0:02:22 It was Rounders, for which we wrote the screenplay. And today, there are people online arguing
    0:02:28 about that movie, which is incredibly satisfying, because as you know, when you make these bets,
    0:02:34 it takes a long time to know if you were right very often. And Rounders was rejected. It was
    0:02:39 incredibly difficult. The movie wasn’t a big box office hit. But 21 years later, people
    0:02:44 are in ferocious online arguments about the most microscopic moments in the film, which
    0:02:48 I, back then, of course, I would have said two things. I would have said we were trying
    0:02:52 to make a movie like, and write a movie that would have the effect on people that movies
    0:02:56 like Diner had on us, which is that we would watch them over and over again and quote them.
    0:03:01 And so the fact that that happened is really rewarding, and it was kind of in our minds.
    0:03:06 But when we set out to do that, we knew that there was only a needle in a haystack chance
    0:03:11 of success. The doing it, we knew right from the beginning, and I think this is something
    0:03:15 that has been really important to our ability to continue to do this work, David and me
    0:03:22 for this long is from the beginning, it was only about us getting in a room or going separately
    0:03:29 in our individual rooms before we would come back together and doing the work itself, trusting
    0:03:34 that if we found a way to do the work itself well enough, some rewards would come. Some
    0:03:40 have been really delayed rewards and some have been much quicker. We never seem to
    0:03:42 know which it’s going to be.
    0:03:45 So let’s start with for people who haven’t seen rounders, maybe thumbnail description
    0:03:51 of rounders. Rounders is a movie set in the poker underground of New York and Matt Damon
    0:03:54 and Edward Norton, John Malkovich are the stars of the movie, and John Turturro. And
    0:04:00 it’s about a character who’s faced with a life decision, which is, is he going to pursue
    0:04:05 his passion, this thing that he believes he’s great at, even though he’s had setbacks. And
    0:04:09 in fact, these setbacks have threatened his stable life. And so he’s at a point where he
    0:04:15 has to choose the stable, traditional road or the road that his heart is telling him
    0:04:19 to pursue. And that’s the central question. And the movie has a lot of sort of heightened
    0:04:24 dramatic, you know, you want to choose a heightened dramatic construct in which to hide the theme.
    0:04:26 Because the last thing you want to do, if you want to talk about the themes, you know,
    0:04:32 be, as you had Kowski and just write essays, if you were going to tell it in a fictional
    0:04:36 construct, make that construct compelling. So only later people wonder and feel what
    0:04:37 the themes are.
    0:04:42 So when you say the, do the work, like what was, what was the do the work part of rounders
    0:04:43 for you and David?
    0:04:50 First, it was about researching. So I walked into a poker club one night, heard the way
    0:04:55 the people spoke, saw what it looked like, and immediately recognized, nobody’s made
    0:05:01 a movie about this. I can’t believe this exists. This should be a movie. I called Dave. He
    0:05:04 said, that’s great. Who are the people in the world that we’re going to write about?
    0:05:07 Who are the characters? Who are we going to care about?
    0:05:13 So we started going to this poker club most every night, taking notes surreptitiously.
    0:05:17 And then at a certain point when we felt we had enough of those notes, we started really
    0:05:22 figuring out what the character’s question would be, who the character would be, what
    0:05:27 the important relationships would be in his life. And then we had to, so then we started
    0:05:31 outlining it, and then we had to just decide, okay, starting tomorrow, we’re going to meet
    0:05:35 every morning. One mistake I see people make when they decide they have to do some kind
    0:05:39 of artistic work is they think it means they have to grab that identity so hard that it’s
    0:05:45 to shut out the rest of their identity. But what I found was you don’t have to do that.
    0:05:48 I didn’t want to put all the pressure on myself of quitting my job and saying, I need a beret
    0:05:49 and an easel, and I’m an artist.
    0:05:51 So what was your job at the time?
    0:05:55 I was working as an executive in the music business. David was bartending. And so what
    0:05:58 we did was when he would come off bartending, he would sleep a couple hours, and I would
    0:06:03 get up extra early, and we would meet in a storage locker underneath my apartment that
    0:06:07 had a slop sink in it because it was an institutional little room, had barely room for both of us
    0:06:13 to sit. I sat on the floor a lot of the time. And we met every day for two hours in the
    0:06:14 morning to write the script.
    0:06:16 And this was purely on spec?
    0:06:21 Completely on spec. In fact, this is I think a piece of this puzzle that I never told before,
    0:06:28 which is that when we had the idea, David met a young producer and told them the idea
    0:06:33 and the producer offered us $5,000 and said, for five grand, I’ll be your partner. I’ll
    0:06:36 give you five grand, but then we’re going to share and if we sell it, we’re going to
    0:06:40 share in the writer’s fee and I’m going to be your partner on the thing. And we were
    0:06:45 tempted because it represented, hey, wait, someone’s paying me to write. We’re professionals
    0:06:49 then, right? But we asked some advice of a woman named Rachel Horowitz who was at Fine
    0:06:53 Line. She happens to be the sister of Adam Horowitz, the Beastie Boys.
    0:06:54 That’s awesome.
    0:06:57 Rachel was a great executive and I knew somebody who knew her and we met and met with her and
    0:07:01 we said, what should we do? Someone’s willing to pay us $5,000 and she said, I don’t need
    0:07:05 to hear the idea, but if someone’s willing to pay you guys who have no credits, $5,000
    0:07:09 now, write the thing and you’ll have a much better chance of success. And we’ve taken
    0:07:15 that lesson to heart still to this day to write unencumbered. We like to go in a room
    0:07:25 and let our idea come to fruition fully. Let ourselves, let us work out all of the complicated
    0:07:28 parts of it without outside interference.
    0:07:31 So let me ask you a lot of professional, one of the adages I think professional writers
    0:07:34 is never write for free. If you write for free, you’re a sucker.
    0:07:36 Well, that was like Samuel Johnson said that, right?
    0:07:38 Okay. Yeah. You’re a sucker. You’re being taken advantage of, right? Never, never, you
    0:07:41 know, a doctor wouldn’t, doctor wouldn’t do surgery for free. A pilot wouldn’t fly
    0:07:44 a plane for free. Writers shouldn’t write for free. But, and I know you’re not writing
    0:07:48 for free per se, but like, there is an element to this of like how, like, it feels like a
    0:07:51 lot of your peers need the deal before they’ll write.
    0:07:56 Well, it depends where you, where you put EV, right? Okay. Expect, you know, right, right?
    0:08:03 Where do you put the EV? By the way, I look at the way I view the need for personal expression.
    0:08:06 I don’t, I actually completely disagree with that quote. I don’t understand what the quote
    0:08:09 is talking about. Don’t be taken advantage of. And it’s also kind of making fun of the
    0:08:11 artistic impulse. It’s saying, are you a professional or not?
    0:08:16 Yeah. But I would assert you can be a professional. You can treat, you can act like a professional
    0:08:20 before you’re paid as a professional. It depends how you’re going to approach it. It depends
    0:08:24 what your expectations are. But our expected value, even though it might have been foolhardy
    0:08:29 to think so, was that there would be something on the other side of it. And I’ll say this,
    0:08:34 the expected value of not doing the work is zero. Like, there’s no, there’s no question
    0:08:37 about the EV of just thinking I’d like to write and not write it.
    0:08:41 Well, if you had shown up in, if you, if you guys had just gone and tried to pitch, try
    0:08:45 to get an agent at stage of your careers, would you have been able to do the project?
    0:08:49 No, probably not other than we got someone who would have paid us five grand, but, but,
    0:08:53 but then later we did make the mistake of pitching at various times. And I mean, occasionally
    0:08:59 a pitch becomes, has become a movie for us. But for whatever reason, we’ve found that
    0:09:04 our strongest work is done in private. And then we take it out and show the world. And
    0:09:10 that’s the, for us, the, for us, we find that when you, when you pitch an idea, as you know,
    0:09:16 when someone comes to pitch you, you’re entering into dialogue about this endeavor. And inevitably
    0:09:19 what we found is a smart person would say something in the room, cause let’s assume
    0:09:24 for a moment that the people across the desk are an idiots. Someone says something smart.
    0:09:27 You can’t help but have them in your head when you’re then going to do the work. And
    0:09:30 that might be a smart thing, but it really might not be the right thing. Because maybe
    0:09:36 I’ve only explained this, this feeling that, that, that I have about what this thing could
    0:09:42 be. Maybe I’ve explained it in a way the best I could at that moment, but left to my own,
    0:09:45 it would take all sorts of different terms. But, but I have that, that phrase that the
    0:09:50 person uttered to me. And I have to keep returning to that for some reason, because I’ve already
    0:09:52 let them inside this process.
    0:09:56 I have a question about this though, because, you know, when we go back to this idea of
    0:10:00 you had the confidence to do this in private and then put it out into the world. And even
    0:10:04 with the rounders, there was sort of a long staying power that came about with that. It
    0:10:06 wasn’t like an instant box office hit in one.
    0:10:07 That’s right.
    0:10:12 How do you, what’s a timeframe that you sort of a gauge the success and B how do you sort
    0:10:18 of balance this sort of impetus from executives and other people in your life who care, who
    0:10:24 are producing and paying for these products with sort of keeping the creative process intact
    0:10:26 without over rotating on the data.
    0:10:31 So let me back up to answer that question. I have to tell you where I was before we wrote
    0:10:37 the first thing. And where I was was in a pretty decent state of misery. Because although
    0:10:43 I had a job that was well-paying and on the surface scene creative, and although I had,
    0:10:49 I was lucky enough, even having Amy, and then our first child did not, was not a salve for
    0:10:53 the way I was feeling, which was like, I wasn’t doing this thing that I knew I had to pursue.
    0:10:59 I wasn’t doing the work. I was blocked. And I have this notion that when you’re a blocked
    0:11:05 person, when you allow this creative impulse to be kept down, it dies. And like any other
    0:11:10 kind of death, there’s toxicity that’s attached to that. And as in the toxicity I knew would
    0:11:16 leech out and would actually make, you know, leech onto the people that I loved because
    0:11:20 I would become a bitter person. And I wanted to be the kind of person who would come home
    0:11:25 and tell my kids that they should chase their dreams with rigor. You know, people often
    0:11:30 just think of it as a relic of the 60s. And it’s like, Hey, pursue your dreams, do your
    0:11:34 thing. But it’s like, well, wait, if you have a dream, if you have a dream, work with incredible
    0:11:38 rigor and discipline to pursue it. And so I finally got to the place where I knew, and
    0:11:42 it wasn’t about, can I have a movie in the movie theaters? What it was about was, can
    0:11:46 I find a way to have the courage to do the work that I’m worried I’ll fail at the work
    0:11:50 that I think is going to be meaningful. And so I decided to follow my curiosity and my
    0:11:56 obsessions. And it’s not merely pay following your passion. What it is, is figuring out
    0:12:00 if I’m obsessed, I’m incredibly curious if I can get to the root of that. And I can
    0:12:05 somehow create something out of it that is worthy. First of all, in the doing, I will
    0:12:11 change and become better. To answer your question about success, the moment that I was in there
    0:12:17 for two hours a day, I was charged the rest of the day. So the job that it seemed mundane
    0:12:21 and bitter and sort of annoying to me was much easier to get through because I’d spent
    0:12:27 two hours already firing on all cylinders. And so that in the beginning, and of course
    0:12:31 along a career, you can hold onto those things and you can let them go because we’re all
    0:12:38 human, which means that we’re all pray to, we can all fall, fall prey to being judged
    0:12:42 by a standard that isn’t our own. And we have to find a way to remind ourselves that
    0:12:46 our own standard is the standard that matters. So of course, I’m not going to say that the
    0:12:49 whole time I’ve been doing this, I only cared about what I felt like when I was doing the
    0:12:53 work. I will say that each time I have reframed and refocused to remember that what matters
    0:12:57 is what I feel like when I’m doing the work. It immediately makes me feel better. And then
    0:13:01 I immediately don’t care about the rest of that stuff. Easier to say, of course, you
    0:13:05 might think easier to say because we’ve had this success, but I know I can point to a
    0:13:09 movie like “Solitary Man,” which was a commercial failure. I mean, it made its money back, but
    0:13:13 it was not a big commercial success. But I know it’s the best movie we ever made. It
    0:13:18 got these incredible reviews. So I wasn’t crazy. That’s how I know this question. I’m
    0:13:22 really interested in this delusion versus genius or delusion versus capability. But
    0:13:25 I wouldn’t change anything of the four-year struggle to write that movie, and then we
    0:13:30 directed the movie because as an artist, if you get to express the thing you want to
    0:13:37 express, and then you get to make it, you’ve kind of won. The odds against are so great.
    0:13:41 Even the odds against completing something, right? Even the odds against actually showing
    0:13:44 up, “I want to be a writer is way different than I am a writer. I want to be an artist
    0:13:48 is way different than I am an artist.” And we decide when you get to give yourself those
    0:13:55 designations. But I was so sad, so miserable, that it immediately changed upon doing the
    0:13:59 work. And so I have had to force myself to have that be the standard.
    0:14:03 To go back to the state. So do you ever suffer from writer’s block?
    0:14:04 No, because I have rituals.
    0:14:05 Like morning pages?
    0:14:06 Can you describe that?
    0:14:11 Yeah, I meditate every morning, and I do morning pages every morning. So morning pages, like
    0:14:16 out of Julie Cameron’s book, “The Artist’s Way,” I do three longhand pages, a real brain
    0:14:23 dump, where I just let the pen move for three pages no matter what. And it has this incredible
    0:14:27 effect on me. It’s self-hypnosis. It’s a brain dump so that you’re putting all the
    0:14:32 dross just gets out there on the page. Also, it has the effect of, “I can’t be blocked.
    0:14:37 I’ve already written three pages.” So you’re in a state of flow. You’re in a state of movement.
    0:14:42 That is the tool I used to become unblocked when I was 30. And when I was that unhappy
    0:14:46 and I said I had to try to write something, I had given Dave, “Awake and the Giant,”
    0:14:50 within, and Dave gave me “The Artist’s Way.” And the combination of those things made me
    0:14:56 realize I had to figure out what it was that I really wanted to do and be. And then “The
    0:15:00 Artist’s Way” gave me this tool to try to actualize it. And as soon as I started doing
    0:15:03 those pages, I was like, “Oh, I can do this. I can write. I can actually make good on it.”
    0:15:05 And I’ve done it for 23 years.
    0:15:06 Do you keep the pages?
    0:15:10 No, you burn. My kids have instructions to burn upon my day.
    0:15:11 Upon your day.
    0:15:14 So I was going to say, you know, decades or centuries later, these get published as
    0:15:15 the notebooks.
    0:15:19 Yeah, they can’t. I’ve read Camus’ notebooks and Somerset Mom’s notebooks. And I’m happy
    0:15:22 that they exist, but that probably wasn’t their intention.
    0:15:25 So when you guys sold “Rounders” or got the gun, whatever you want to say, the trigger
    0:15:30 got pulled. So what did you guys have when you walked into the room to do that at that
    0:15:31 point?
    0:15:35 Well, so we finished the screenplay. It was first rejected. It was my favorite story.
    0:15:40 But I tell in detail on my blog, which is not a very active blog, at BrianCobbleman.com.
    0:15:45 But we were rejected by every single agency in Hollywood. One said it was overwritten,
    0:15:48 another said it was underwritten. I still don’t know what either of those terms mean.
    0:15:52 And I wrote down everything they all said. And this was an incredible Hollywood lesson
    0:15:56 because, you know, in the beginning, every rejection feels so personal. Every rejection
    0:15:59 also feels so final, right, in the beginning.
    0:16:05 I wrote down what everyone said and then we sold the thing. And that Monday, so we sold
    0:16:13 the thing over a weekend on a Monday and by Tuesday, every single agency that had passed
    0:16:18 called us to try to sign us. And I read them all their comments. I had it on a yellow legal
    0:16:22 pad and I just read them. I said, “Well, but you said that the thing was overwritten.”
    0:16:23 I did. I read it to them all.
    0:16:25 And it wasn’t that the movie had gotten made and they liked it. It wasn’t that the movie
    0:16:27 was a commercial success. It was simply that you sold it.
    0:16:32 The thing had intrinsically changed in the work itself. And they all, nobody owned it.
    0:16:36 Not one of them said, “You know what? I guess I’m…” They all said, “I didn’t read it.
    0:16:40 It was my reader. It was my assistant. I meant to read it. I read the wrong script that was
    0:16:45 about poker and I thought it was your script.” It was incredible. But it immediately framed
    0:16:49 the question for me, for the rest of my career about who knows what.
    0:16:55 So then it’s bought by Miramax, which is something I guess they used to say with pride. And David
    0:16:58 and I were just the writers. We weren’t the producers on the movie. We weren’t the directors
    0:17:03 of the movie. And this has to do with continuing to work with Rigger. There was a moment where
    0:17:07 they were going to hire a director who we thought would fire us off the movie and we
    0:17:12 thought would do a bad job. We met him. We didn’t like him. And so even though it wasn’t
    0:17:19 in our billet, we decided we’d better find a director who they would hire but who would
    0:17:24 be someone we felt we could work with. And it was really overstepping our position.
    0:17:32 And I think part of it is, and this gets into us, part of it was that each of us were raised
    0:17:37 in environments where we saw people take these kinds of risks. And my dad was an entrepreneur
    0:17:42 and I saw a lot of the time the way that he would just overstep his position to achieve
    0:17:49 a result. And so we found out through some sources who directors were that the movie company,
    0:17:52 who they were interested in making movies with, we triangulated that with people we
    0:17:57 could get to. And we found out that our agency represented John Dahl, who was really high
    0:18:02 on our list. And we said to our agents at the time, “Listen, we’re going to stay in
    0:18:06 California until you can get us a meeting with John Dahl.” And they were like, “Well,
    0:18:09 how are we going to do that?” We said, “Well, send him this script, the letter that we
    0:18:13 write, and we’ll just wait around.” And they had all just competed to sign us, right?
    0:18:20 So this was the very beginning of this relationship with the agent. And in a way, he had to prove
    0:18:24 himself to us. We were able to leverage the newness of the situation, even though often
    0:18:29 people in that situation think that they work for the agents. The agents do a really good
    0:18:34 job of making people feel lucky to have them. But we were aware of the actual leverage in
    0:18:39 the situation. He got the script to John. John read it. Luckily for us, he really liked
    0:18:42 it. He came over and met us at our hotel. We all shook hands on it. We knew he was an
    0:18:48 honorable person. We then got to have this incredibly, incredible moment, which now when
    0:18:52 I think back in it, I can’t even believe happened, which is we then called the producers and
    0:18:55 the studio and we said, “John Dahl’s going to direct ‘Rounders’.” And they all went,
    0:18:58 “Well, that makes no sense. He’s supposed to direct this other movie for us. How could
    0:19:00 you do that? You overstepped.” And we all said, “Well, do you want John Dahl to direct
    0:19:04 the movie?” And they all went, “Yeah.” And what was really great about that is then
    0:19:08 that allowed us to be on set every day. Because when you’re the one who brought the director
    0:19:14 in and you have this relationship, plus John has no ego and he knew we understood the world
    0:19:20 of poker. Also, this incredibly lucky thing was we were the same age as Matt and Edward.
    0:19:24 And so there was a relationship that developed right away, which was we were going to take
    0:19:28 these guys and show them the world of underground poker. We were going to be experts about this.
    0:19:31 John Dahl gave us our limits. He was like, “You have to really think carefully about
    0:19:35 your set of actors. You can’t contradict me. We’re going to work together, but there’s
    0:19:39 a chain of command.” And with that, he gave us complete freedom. Within that, he was like,
    0:19:43 “Now, help me make the movie.” But none of it would have happened if we would have
    0:19:47 pitched a movie. We would have been powerless. We had ownership because we’d written the
    0:19:49 whole thing and we’d proven we were experts.
    0:19:51 Can I ask you a quick question on this notion of ownership?
    0:19:52 Yeah.
    0:19:56 David Levine and you guys are both the showrunners for Billions. I’m dying to know how, because
    0:20:05 when a studio buys your show, someone is producing billions, it is your show as showrunner.
    0:20:08 What if there’s a conflict and you guys have a huge falling out and I’m thinking of the
    0:20:13 case of the Sherman Paladinos and Gilmore Girls and they had to exit before the last
    0:20:17 season and it totally changed the last season of the show and then they came back to remake
    0:20:21 the thing? Is there this thing where you’re owning this thing that other people are now
    0:20:24 sharing in and then you have to give up your baby? How does the ownership thing work?
    0:20:32 I’ll tell you, it’s so analogous to the way a founder and will work with the investors,
    0:20:38 the VC, the board. It’s up to you to manage that relationship. It’s up to you to set
    0:20:47 the terms. This does get into questions of privilege. As two white men growing up with
    0:20:53 David’s grandfather and my father were pretty successful, we learned at a young age how
    0:20:57 to talk to powerful people. Most people don’t get in education and talk to powerful people.
    0:20:58 You’re so right about that.
    0:21:02 When people ask about advantages, yes, getting college paid for was a huge advantage, meaning
    0:21:07 that I knew I could take certain risks that other people couldn’t because I didn’t have
    0:21:12 a massive debt. But much more important or certainly equally important was from a young
    0:21:16 age, my dad would like put me in situations where I would have to deal with powerful people
    0:21:21 and I would have to find a way to get the result I wanted. He would let me be in a recording
    0:21:26 studio when he was making records and sometimes ask my opinion in a room full of incredibly
    0:21:30 scary powerful people. He would let me be in meetings and he would leave and I would
    0:21:31 conduct stuff.
    0:21:32 You really set you up for that.
    0:21:39 From a young age, how to interact? How do you talk to power actually? Give us the advice
    0:21:40 for our listeners.
    0:21:44 The main thing is don’t treat them as the most of the time. Don’t treat them with a
    0:21:49 sense of awe and that their station makes them better than you. But also don’t try to condescend
    0:21:53 to them as though you’re the smartest person in the world. And you know the biggest thing?
    0:21:55 Make them laugh once in a while.
    0:21:56 That’s actually great.
    0:21:59 I mean, right? Walk into a room, make them laugh, make them feel like you have the answers
    0:22:03 to their problems and that you’re comfortable in your own skin. I mean so much of what I’m
    0:22:09 talking about is an ingrained sense of comfort in your own skin is being able to just continue
    0:22:13 to grow. You must always continue to grow, continue to better yourself, but find a way
    0:22:19 to sit there in the room relaxed and understand that you’re not sitting there with the all-knowing,
    0:22:25 all-powerful Oracle or Oz, which is to say to answer your question. It’s our job to make
    0:22:32 the show, to make the actors comfortable, to make the crew feel empowered, to make
    0:22:36 sure the show is written, edited and shot, right? It’s also our job to make the show
    0:22:42 on budget, to communicate with the show time if there’s going to be, “Hey, guess what?
    0:22:44 This next week it’s going to look like we’re over, but here’s how we’re going to solve
    0:22:49 that the week after.” Also to make them feel heard when they’re talking about the show.
    0:22:50 You’re so right.
    0:22:54 If they’re giving notes, make them feel heard, make them know that you actually are listening.
    0:22:57 Again, it’s really important that we only take the notes that’ll make the show better
    0:23:01 and that we do that in a way that makes them feel good about the process.
    0:23:04 That’s fantastic advice. That’s so great. I feel like that can apply to any business.
    0:23:05 It does. I think that applies across the board.
    0:23:07 You know how I coach people how to do that?
    0:23:08 How do you?
    0:23:09 Yeah.
    0:23:10 From Larry Sanders.
    0:23:11 From Artie.
    0:23:12 So tell us.
    0:23:13 I don’t know where you’re from.
    0:23:16 We both love Larry Sanders, like my third favorite show of all time.
    0:23:22 So people haven’t seen it. You must watch it immediately. So Artie, the producer, played
    0:23:26 by the legendary Riptorn, Artie, the producer.
    0:23:30 So typically we see this with young people out in here, which is like, you give somebody,
    0:23:33 in your world, it’s called a note. In our world, it’s like feedback or here’s an idea.
    0:23:37 You give somebody an idea and they immediately get their backup. Well, they do one of two
    0:23:40 things. They either take it way too seriously and they try to do everything you tell them
    0:23:44 or they get their backup and they get offended, “How dare you question my vision?” kind of
    0:23:47 stuff and then that sets up a weird dynamic where you feel like you can’t talk to them.
    0:23:52 Both of those are bad. One way you basically hijack their creative vision, usually a bad
    0:23:55 effect. The other way is you end up with a bad, a hostile relationship.
    0:23:59 And so, Artie’s whole approach to dealing with the network executives in Larry Sanders
    0:24:03 is a show inside a show, basically. It’s a show about a show. His way of dealing with
    0:24:07 the suits from the network was basically that they’d say, “Well, I don’t know. I think
    0:24:10 the curtain that the talk show has read, we really think it should be purple.” And Artie
    0:24:13 would literally say, “That is a really interesting idea. I am really going to think hard about
    0:24:17 that one.” And he would read it on his legal panel. He goes, “Okay, okay. What else do
    0:24:21 you have?” And then, of course, the show, the suit leaves the room, he rips up the
    0:24:22 baby. And the suits are on their way out, and they’re like, “That was the best meeting
    0:24:23 ever.” Yeah.
    0:24:25 Is this a feeling of feeling that you’ve been hurt?
    0:24:30 And so, that’s like, what I’m telling people is like, “That’s the baseline.” If you can
    0:24:34 just do that, you’re better than most. And then to your point, if on top of that, you
    0:24:36 can actually consider and actually absorb some of the feedback.
    0:24:40 And sometimes, listen, nobody’s perfect. So, there are times I’m working 17 hours a day,
    0:24:45 and somebody gives me a note I really disagree with, and I might say, you know, as you might,
    0:24:50 I might, once in a while, say, “Listen, I tend to say kind of like, ‘Fuck off. That’s
    0:24:51 a stupid idea ever heard.’”
    0:24:54 I sometimes say that’s a stupid idea, but here’s the thing. If you have the right kind
    0:24:58 of relationship with the people with whom you work, you can say that, because they know
    0:25:03 that’s not your default position, and they understand, because you’re in dialogue with
    0:25:07 them, but not operating from a place, no one’s operating from a place of fear, hurt, or misunderstanding.
    0:25:11 And by the way, if you say that’s the stupidest fucking note I ever heard, call them the next
    0:25:14 day and say, “Let me tell you what was going on yesterday. Here’s the way I’m going to
    0:25:19 think about addressing it, or read this and tell me if you still think so.” It’s a constant,
    0:25:24 you constantly have to remember, if you’re in our position, that you’re grateful to be
    0:25:29 in this situation, but that you’re not an indentured, you’re not so grateful that you’re
    0:25:32 going to prostrate yourself and ruin the thing in the process.
    0:25:33 Of course.
    0:25:34 And if you remember that, you’re in okay shape.
    0:25:37 The part that I always struggle with here, and I wonder if a lot of people struggle with
    0:25:41 this, is that I always had this belief that competency is a thing that will always get
    0:25:45 you ahead. The result will speak for itself. How do you sort of play back the results to
    0:25:50 tell the story that you want? Because oftentimes, the rounder’s example, this is the conversation
    0:25:54 that’s happening around the movie, because people have ways of defining those things.
    0:25:58 I think that’s a really big challenge. How do you sort of define it so that you can make
    0:26:04 sure that the narrative you untold your way is that part of the point? I mean, in terms
    0:26:05 of how people perceive your way?
    0:26:11 Well, when you’re a showrunner of a going concern, you’re going to get to prove it out
    0:26:16 or not prove it out, because you’re making the show. And I will say, certainly in the
    0:26:22 relationship we have with Showtime, all their notes are suggestions. And so, Dave and I
    0:26:25 are getting to prove it out every episode. I will say we did, so okay, there are a few
    0:26:30 other things. It’s not bad thing to learn the mistakes people have made ahead of you.
    0:26:35 It’s not bad to do research and know, well, what is the third round in this situation,
    0:26:39 right? So if the third round in the situation is don’t go more than 3% over budget on a
    0:26:46 given episode without having conversations, that that is the third round, then don’t be
    0:26:50 a jerk. You’re in an incredibly lucky situation to find a way to do what you have to do. But
    0:26:57 there are many other non-budgetary examples. So here’s how a pilot works. When I lay this
    0:27:02 example out, there will be parallels to your world. So a pilot gets green lit. They give
    0:27:08 you this amount of money to go make the pilot. And they’ve already approved the script.
    0:27:13 You cast the show together. So that’s another one of these things where you’re trying to
    0:27:18 find a way to express your opinions. Make sure you have the cast you want. While understanding
    0:27:21 we’re in the real world, you’re not going to cast a complete unknown to play the lead
    0:27:25 unless you have a bunch of other ways to say, well, that’s okay because in these three spots
    0:27:32 we have people who aren’t. But then once that stuff’s done, guys go off, make your show,
    0:27:36 right? Because once it starts going and before it’s edited, there is no feedback they can
    0:27:41 really give you. You’re making the show. You’re making the show. You go in the editing room
    0:27:46 after you have all this material. You know the show is going to fit in an hour long slot.
    0:27:52 But most people, when they cut their pilot because they don’t actually have the real
    0:27:59 limitation of an hour, will turn in a 67 minute pilot because they’re, every idea they had,
    0:28:03 everything they want to be there. Now, David and I, because by the time billions have come
    0:28:07 around, we’ve been doing this for a long time. And what happens when you give the 67 minute
    0:28:13 thing is you’re inviting a bunch of people to tell you how to get the thing to 57 or
    0:28:19 58 minutes. And suddenly they’re giving you their opinion on it. Also, by you not having
    0:28:26 to have rigorously with discipline make those decisions, you’ve inevitably left in a bunch
    0:28:32 of stuff that you shouldn’t have. So David and I decided and no matter what, we’re turning
    0:28:37 something in that’s 57 or 58 minutes, maybe 56 if we could do it. We’re going to take
    0:28:43 all of those questions off the table before showing it to the people who put up the money.
    0:28:49 And I’ll tell you, we gave them this cut and we’re realistic people. So we knew all the
    0:28:52 flaws and the things we would want to reshoot before it would go in the air. But you know,
    0:28:55 they’re going to make it as some of the audience doesn’t know. When you shoot a pilot, there’s
    0:28:58 no guarantee you’re going to have a series. They’ve invested a bunch of money, showtimes
    0:29:01 known for if they make a drama pilot. It’s very likely they’re going to put it on the
    0:29:07 air, but you don’t know. And so we turn over this pilot. And the first thing they said
    0:29:12 to us when they called us was, you guys have already done all the stuff that normally takes
    0:29:16 a month for us to work through with showrunners, which is you’ve gotten the thing into show
    0:29:24 shape. And so that’s because we looked ahead at how best practice practices. And by the
    0:29:28 way, it’s hard, right? It’s actually when you’re in the, then you’re in the situation.
    0:29:32 You understand why everybody turns in at 67 minutes because you don’t have to, it’s much
    0:29:38 easier to not have to make those decisions. Right? It’s much easier to hand the confidence
    0:29:42 actually quite frankly, it’s easier to offload those decisions to the X, to someone else,
    0:29:44 the people who are paying for it. Instead we said, you know, we’re going to make these
    0:29:49 choices and we’re going to show them that this is the vision we have for the show. And
    0:29:53 our structure, I think I’ve put the pilot script online at my, I think I put it online
    0:29:57 at the blog. And if you go look at it, I put rounders up there too, which people have really
    0:30:01 been reading a lot lately. But if you look at it structurally, it’s quite different than
    0:30:05 the pilot that got on the air. Different scene starts it. And because when we got in the
    0:30:10 editing room, we decided, well, now we have the opportunity to make the show be the best
    0:30:15 version of itself. We were able to gain objectivity, even though it was all of our hearts in there.
    0:30:17 It’s only in the edit that you get that arc totally.
    0:30:19 And then there’s one message you’re delivering is like, here’s an incredible product. The
    0:30:22 meta message I think you’re delivering is you guys are professionals.
    0:30:26 And they said that to us. They specifically explicitly said, we know your showrunners who
    0:30:31 can make the show. That was what gave. So this goes to your question of the relationship.
    0:30:36 How do you establish a relationship with them that makes them your professional? We can
    0:30:43 trust. And by the way, as you know, all you want is a founder show, a founder CEO who can
    0:30:47 not make it your job to run the company and just take the best of your ideas. And you
    0:30:50 want them to discard the worst of your ideas. Go knock it out of the park. Right. Go do
    0:30:55 your thing. By the way, that’s hard. Those are hard one lessons over a career. Yeah. You
    0:30:59 know what I mean? Those aren’t. We were 20 years in by the time. I think we sold rounders
    0:31:06 in 1997 and we made the pilot of this in 2015. So that’s a long period of time over which
    0:31:10 we figured this stuff out. So for people who aren’t aware, there’s a very interesting kind
    0:31:14 of split and how movies are made and how TV shows are made at least these days, which
    0:31:18 is movies are made. Generally, the writer writes the script, turns it over and then
    0:31:21 other people run with it and other people being the presumably the producers and then
    0:31:24 particularly the director, the director, the director ends up actually running the project
    0:31:28 in a lot of ways, right? Maybe with a line producer or something. For TV shows, especially,
    0:31:32 it seems like in the last couple of decades, you have this concept of showrunner and the
    0:31:38 writers are often or usually at this point, the showrunners. And I’m just, I’m picturing
    0:31:42 I don’t know, Louis B. Mayer or, you know, Jack Warner or somebody, you know, being
    0:31:46 told that the writers should run the project and probably screaming and being very upset
    0:31:49 like that would be impossible. And so two-part question, what was the left turn in the industry
    0:31:53 that caused the writers to get in a position where they could be the showrunners? And then,
    0:31:57 and then what did you guys do as writers to make sure that you specifically were able
    0:31:58 to do that?
    0:32:04 So there’s this, there’s this great book called Difficult Men by Brett Martin that’s about
    0:32:12 five showrunners, David Simon, David Chase, Vince Gilligan, Sean Ryan and one other that
    0:32:13 I’m not remembering right now.
    0:32:19 And this is Breaking Bad, The Shields, The Wires, The Prannos and The Wire and, but he
    0:32:22 goes into the history of it and Hill Street Blues is when this first, because they were
    0:32:27 making this kind of serialized show and Stephen Boczko started having meetings with the directors.
    0:32:30 When the director would come in, he would start having meetings saying, let me give,
    0:32:35 set the tone. He was executive, nobody named him showrunner, but he decided that he was
    0:32:42 going to, had to because of the nature of that show, exert upon the situation a kind
    0:32:47 of tone, a control of the voice and, and tone because most shows have been more like law
    0:32:51 and order was like the apotheosis of the other way around, which is each, each episode is
    0:32:52 independent.
    0:32:53 Yes.
    0:32:54 Right.
    0:32:59 But before Hill Street Blues, Hill Street Blues was one of the first shows that sort of combined
    0:33:03 these elements for a cop show, I think, for sure. But, but the answer to your question
    0:33:09 is about David and me and about anyone who wants to be a showrunner, which I’m happy
    0:33:12 that showrunners officially in the dictionary now, like two years ago, it became.
    0:33:13 I’m so glad.
    0:33:14 I love that word.
    0:33:19 It’s a real job title. Now, like, what do you do for a living showrunner? It’s learning
    0:33:23 to be a producer. We have 150 people who work with us, but we’re who we’re in charge of.
    0:33:28 And so it is quite different. But, but, but, you know, as you know, David and I directed
    0:33:32 movies and we produced movies. So for us, it was a quite a natural thing because we’d
    0:33:37 already, you know, at Rounders was as good an experience as you could have as a writer.
    0:33:42 And there were still areas in which we didn’t have enough control over the voice. And what
    0:33:47 we also knew was we’re probably never going to get that exact situation again. So we’d
    0:33:50 better learn how to do these other parts of it. We’d better learn how to gain control
    0:33:55 of the, you know, mechanisms of production means production means production.
    0:34:01 That’s exactly right. And so we realized that we had to do that. But again, that goes goes
    0:34:09 back to this question of a lot often a writer is takes solace while they’re whining about
    0:34:14 not having control. They take solace and not having control because if you don’t have control,
    0:34:17 you don’t take the blame somebody else as well. So if you’re comfortable, if you can
    0:34:21 find a way to be comfortable with failure, which is a writer you have to or comfortable
    0:34:25 in your mistakes, then you can be comfortable in wanting to be the final voice on what the
    0:34:32 product is going to be. And we very early on decided, I’ll say this, when we work with
    0:34:38 Steven Soderbergh, we are so glad to have his voice. If he’s directing them, man, what
    0:34:43 a thrill to work with a genius, right? And what a thrill to have Soderbergh make us
    0:34:44 better to this day.
    0:34:45 This is OSHA 13.
    0:34:48 Yeah, but also the girlfriend experience. And then he produced Solterman. I mean, if
    0:34:53 Steven called tomorrow and said that he wanted us to just be screenwriters on a movie, he
    0:34:57 was directing, we would jump at it because he’s going to make our stuff better. So but
    0:35:02 if you’re comfortable in, if you’re comfortable taking the blame, if you’re comfortable in
    0:35:08 a position of control, it makes you incredibly comfortable to then seed that control or to
    0:35:14 share with somebody else. And so you can pick your spots then and decide. And also because
    0:35:21 we’re able to make our own stuff, it’s the being in a situation where we are not the
    0:35:26 final voice doesn’t make us chafe against it. I have plenty of that over here. So I don’t
    0:35:28 have to chafe against it over here.
    0:35:30 I’m happy to play this role in this situation.
    0:35:31 Fantastic. I love it.
    0:35:34 This is why we’re good producing other people’s movies. When it’s someone else’s vision, we’re
    0:35:38 great at just helping them achieve their vision. Like Neil Berger, who’s an incredibly, incredibly
    0:35:42 successful director, director of the pilot of Billions. We produced his first three movies.
    0:35:47 And it’s like, Hey, Neil, we’re here to advise counsel, help. It’s your movie. Go run with
    0:35:52 it. We’re comfortable in any of those different modes creatively. But I think the reason for
    0:35:57 that is that we got comfortable early on with just doing the work and failing.
    0:36:00 That’s right. We’ve been talking a lot about kind of managing ups, hierarchically, so
    0:36:04 to speak. Now, turning it the other direction, like managing down in the writer’s room, you’ve
    0:36:08 got like a lot of writers working with you. So how do you now navigate debates with all
    0:36:12 those writers in the writer’s room? Like essentially you’re the show runners. And how do you make
    0:36:14 it collaborative yet not a democracy at the same time?
    0:36:17 Well, it isn’t a democracy.
    0:36:21 So different show runners approach the question of the writer’s room differently. And some
    0:36:27 who’ve come up through a writer’s room, rely on it in a very deep way, describe a writer’s
    0:36:28 room.
    0:36:33 A writer’s room is you get, let’s say six people in the room plus a show runner. There’s
    0:36:37 a white board on the, and you start at the beginning of the season and it’s like, where
    0:36:41 are we and how do we fill that in? And then each, but then it’s really hard to describe
    0:36:45 a writer’s room mark because writer’s rooms become extensions of the way the show runners
    0:36:48 see the world and the way they see the world of their shows.
    0:36:52 So in theory, it’s a team of people writing the show together in some form.
    0:36:57 In some form, meaning maybe everybody will write an episode. Almost all shows, the show
    0:37:01 runner does the final pass on all the episodes, no matter whose name is going on.
    0:37:01 Yeah, like the top edit.
    0:37:08 On our show, though, David and I end up writing most of the show. And we have a great room
    0:37:14 of men and women who help us really break the story arc of the season. And that is an
    0:37:21 invaluable process. Tons of stuff comes out of the room about how the big arc of the season
    0:37:25 should occur, about the twists and turns, about where characters, and that’s a months-long
    0:37:31 process of talking. We haven’t yet found, and then when it comes to writing the scripts,
    0:37:38 David and I, and then we have a writer named Adam Perlman, who’s now a co-executive producer.
    0:37:43 He’s a number two person. And Adam writes a good amount of the show, too. But the truth
    0:37:48 is, it is mostly us writing it. And I’m not saying that’s the way it should be on every
    0:37:51 show. The voice of our show, the way that our show is, whether you like our show or
    0:37:56 not, our show is canted in a certain way. It has a very clear voice that somehow the
    0:37:57 two of us can do.
    0:38:03 Instead, if someone on the team starts a script, their name goes on, and ours does
    0:38:04 not.
    0:38:07 So you’ve got a young hotshot writer, and they have an opportunity to write on a show.
    0:38:10 This may be not as, let’s say, critical respect or whatever, but maybe it’s like they know
    0:38:15 that they’ll actually get to write scripts. And what’s your pitch to them of why they
    0:38:17 should come work for you, given that it’s a more constrained environment?
    0:38:21 I’m not sure. Well, Adam was somebody who had a lot of job offers when he came on our
    0:38:25 show in the second season. He started on the second season. He came into the room as just
    0:38:31 a producer level, which is kind of a low-level position in terms of the hierarchy. He wasn’t
    0:38:36 helping to be a showrunner, but he came in the room. He had incredibly good ideas. He
    0:38:42 then wrote his first script that he wrote was very strong, strong enough that when someone’s
    0:38:46 script came in that was not that strong, and David and I had to work on three other things.
    0:38:49 We called him in and we said, “Hey, take a shot at rewriting this. Here are the things
    0:38:50 that matter.”
    0:38:55 We made extensive notes. Adam, go try to rewrite it. He rewrote that script. We then sat with
    0:38:58 him and talked about how we were going to now rewrite it, but he did a really good job.
    0:39:03 We kept being able to go to him, and by the next season, season three, he was running
    0:39:07 the room when we weren’t there. We bumped him up to co-executive producer really quickly
    0:39:14 and said, “Look, you’re our creative partner now. Help us do this.” If you’re really great,
    0:39:18 if you’re great in the way that our show requires, someone may kill it on another show and just
    0:39:23 not kill it on ours, the other thing is they get to be on set, watch how a show is made,
    0:39:24 and be a part of it.
    0:39:27 I’ll say one thing though to answer, another thing to ask your question, which is some
    0:39:30 people have come into the writer’s room, talented, and I’ve found out they came into the writer’s
    0:39:35 room because they like my podcast, but I’ve had to say to them, I’m this incredibly nurturing
    0:39:39 and encouraging voice on the podcast, and I want you to know I am that for you and your
    0:39:44 life, and I’ll help you get your next job, but you’re going to turn in a script and you’re
    0:39:46 not going to get the voice on the podcast.
    0:39:47 Oh my God, totally relate to this.
    0:39:52 You’re going to get somebody saying to you, “Here’s what doesn’t work.” You have to know
    0:39:55 that this is now you’re entering, this is, we’re in the major leagues here, we have
    0:39:58 no choice because we’re playing the Red Sox tomorrow.
    0:40:04 So we have to be ready to get in there and play the Red Sox.
    0:40:06 So that’s, that has happened twice.
    0:40:10 So one more question about Rounders, which goes to the kind of current state of the industry.
    0:40:15 So Rounders was made in 1997, so that was the heyday of kind of the high status independent
    0:40:19 movie, like medium budget, but like super high status.
    0:40:20 Yeah, 14-5 we made that for, yeah.
    0:40:23 Okay, yeah. And then, and then as you said, like it, you know, it had the thing, it wasn’t
    0:40:27 a huge commercially hit out, but then it had this long, long life, you know, kind of plays
    0:40:30 out through now and probably long into the future.
    0:40:33 If that movie had not gotten made, and if a movie like that had not got made, just if
    0:40:37 nobody had made kind of the definitive book or movie, and you and David entered the industry
    0:40:43 today at age 25 or 30, whatever it is, and decided to make that movie, that project today,
    0:40:44 what would be different about the process?
    0:40:47 People constantly ask me how to break in to the business.
    0:40:51 And my answer is, I have no idea, I did it 23 years ago.
    0:40:52 I can’t help you.
    0:40:55 I wish I could help tell you how to break in.
    0:40:57 The conditions on the ground are entirely different.
    0:41:01 The last thing I want to be is some general back in thing, ignoring what the sergeant says.
    0:41:03 Like I have no idea.
    0:41:07 I do know that what I know is that, well, I think it would resemble a movie that I love
    0:41:10 and that launched many careers, which is Margin Call.
    0:41:15 But whereas Rounders was a 14-5, I think Margin Call was made for a million too, and scraped
    0:41:18 together by a commercial director, and they had limited sets.
    0:41:20 Now, because Margin Call has a lot of similarities to Rounders.
    0:41:24 It’s set in an insular world with a language of its own.
    0:41:26 It doesn’t spell anything out for you.
    0:41:27 You have to be willing to–
    0:41:28 You have to be willing to roll with it.
    0:41:29 We should describe it.
    0:41:33 It’s kind of the definitive movie of the September 2008 financial meltdown.
    0:41:36 It kind of takes place overnight, effectively in Lehman Brothers.
    0:41:37 Yes.
    0:41:38 A fictionalized version of Lehman Brothers.
    0:41:41 And it’s actually a very chilling– people in finance look at it and say–
    0:41:42 Goldman.
    0:41:43 Well, it’s Goldman, right?
    0:41:44 Because they survive.
    0:41:50 Because it’s set at Goldman, and it’s about the willingness of gold– and they never
    0:41:51 say it’s Goldman.
    0:41:55 It’s about the willingness of– it’s about a decision that Goldman Sachs made to get
    0:41:57 rid of their toxic assets.
    0:42:02 But I think that movie is really analogous to Rounders because it is doing a bunch of
    0:42:05 the stuff that we did.
    0:42:10 You have to just catch on to the lingo, and you have to understand what the stakes are.
    0:42:15 But he had to– look, they made that movie for a 10th of what we made Rounders for.
    0:42:16 They had Kevin Spacey.
    0:42:17 They had Jeremy Irons.
    0:42:18 Jack Herquinto was in it.
    0:42:19 And he was starting to become famous.
    0:42:20 That’s right.
    0:42:21 So they had Top End.
    0:42:22 They put the Top End people.
    0:42:23 But it was still– they had to make it for like a million and a half bucks.
    0:42:24 A million and two, maybe.
    0:42:25 OK.
    0:42:30 It’s much harder to make those mid– those sort of mid-budget 14 to 25 or $30 million
    0:42:31 movies.
    0:42:32 The Netflix does it, right?
    0:42:33 Right.
    0:42:38 You can do it at Netflix now, which is probably where it would happen.
    0:42:40 But– or you would try to tell the story in a novelistic way on television.
    0:42:41 Well, that was a great question.
    0:42:46 So would you pitch today– young David and young Brian show up– would you pitch Rounders
    0:42:48 for television or for a film?
    0:42:49 No.
    0:42:51 You would pitch the world in the underground card rooms for television.
    0:42:52 OK.
    0:42:53 Because I think a lot of that– that’s where this stuff lives.
    0:42:57 And that would have been, I think, a fascinating thing to see also.
    0:42:59 David and I grew up watching movies.
    0:43:05 We loved television, but our shared language, our lingua franca, was movies.
    0:43:08 We were quoting movies at each other from when we were little kids.
    0:43:10 We would watch movies 20 times.
    0:43:16 We watched Stripes Together at least 20 times and Diner and many more movies where they
    0:43:20 became the way we communicated.
    0:43:23 And so it made sense to us to go make movies.
    0:43:30 Since then, things like The Sopranos, West Wing, Larry Sanders, Mad Men showed up and
    0:43:31 showed us the way.
    0:43:35 They lit the way for us to think about television.
    0:43:36 That’s actually huge.
    0:43:37 We always talk about this.
    0:43:39 Mark and I television is so much better than movies.
    0:43:40 It’s unbelievable.
    0:43:42 Well, I think it’s actually– it’s the best shows there are novels.
    0:43:43 What?
    0:43:44 I think we all think about it.
    0:43:45 Or a series of novels.
    0:43:46 I call it visual literature.
    0:43:47 A movie is still more like a play.
    0:43:48 It’s visual literature.
    0:43:49 These shows are like thousand-page novels.
    0:43:50 We definitely think about it.
    0:43:52 We definitely think about it that way.
    0:43:56 We’re trying to tell novelistic stories, deepening characters in challenging situations.
    0:43:57 I call it visual literature.
    0:43:58 It’s exactly what it is.
    0:43:59 I love that term.
    0:44:03 When you came up in the music industry, I watched– I was involved in the internet.
    0:44:07 I wasn’t involved in Napster, but I knew the guys really well.
    0:44:11 We both watched from various professional perches, kind of the music industry confront
    0:44:14 digital distribution and basically just like implode.
    0:44:15 Yeah, get run over.
    0:44:16 I didn’t confront it.
    0:44:18 Unfortunately, they didn’t confront it.
    0:44:22 They just stood there and got– they were like, they just got run over.
    0:44:23 Kablooey, right?
    0:44:24 I mean, like France.
    0:44:25 Like France.
    0:44:26 In the deuce, man.
    0:44:31 You know, they were like, should we pick up our guns and their rifles?
    0:44:32 No.
    0:44:33 Let’s just lay down.
    0:44:36 That’s a comment brought to you entirely.
    0:44:37 No, Mark.
    0:44:38 You signed up.
    0:44:39 You laughed.
    0:44:42 You completely laughed.
    0:44:45 So I fully– I’ll just confess, I fully expected the same thing was going to happen to TV.
    0:44:49 Like, you know, Napster for music, BitTorrent for TV, it’s just like it’s just obvious.
    0:44:50 Same thing’s going to happen to TV.
    0:44:51 It’s just going to get run over.
    0:44:54 And then the most like amazing thing in the world happened, which is the exact opposite
    0:44:55 thing happened.
    0:44:58 The exact opposite happened, which is like this– like the creative explosion of all
    0:44:59 time.
    0:45:00 Yes.
    0:45:03 Like the– and you’ve probably seen, you know, John Landgraf, who runs FX, has always
    0:45:04 talked about it.
    0:45:05 He’s a brilliant man.
    0:45:06 Brilliant man.
    0:45:08 You’re a great programmer, but, you know, he talks about the content bubble, the TV
    0:45:09 bubble.
    0:45:12 And it’s like, I don’t know, every year now, it’s like 500 original scripted dramas are
    0:45:13 getting made.
    0:45:15 I think it’s 560 or something insane.
    0:45:16 Yeah.
    0:45:18 And so, and he’s been calling this a bubble the whole time, but like it keeps expanding.
    0:45:21 And I mean, then we all get to, you know, you get to make it, but like we get to watch
    0:45:22 it.
    0:45:24 You know, I really like routinely see shows now where I’m just like, you know, 20 years
    0:45:26 ago, this would have been the best show in the entire history of town.
    0:45:30 The fact that “Mindhunter and the Crown” came out like in the same year on Netflix is amazing
    0:45:31 to me.
    0:45:32 Those would have been the best show of an era.
    0:45:33 Ever.
    0:45:34 Ever.
    0:45:35 Ever.
    0:45:36 Like the crown is as good as you can make something.
    0:45:37 And like–
    0:45:38 I keep trying to make Mark watch it.
    0:45:39 He hasn’t–
    0:45:40 I can give you the language by which to watch it.
    0:45:41 So I’m totally not interested in monarchy.
    0:45:42 I hate it.
    0:45:43 And nothing about that is interesting to me.
    0:45:45 The show is just the most beautifully written and shot.
    0:45:46 I agree with you.
    0:45:47 And acted show that there is.
    0:45:48 He doesn’t believe me.
    0:45:49 So here’s my question.
    0:45:51 Let’s assume it is the medium of our time.
    0:45:53 And let’s assume it kind of keeps expanding so that this all makes sense.
    0:45:57 But the amazing thing is, it seems like the more shows get made, it seems like the average
    0:45:59 quality level is rising.
    0:46:01 And you would expect, I think, the opposite.
    0:46:03 You’d expect the average quality level to fall because you’d expect to run out of talent
    0:46:04 at some point.
    0:46:05 I agree.
    0:46:07 And so where is all this talent coming from?
    0:46:08 I have no idea.
    0:46:09 Okay.
    0:46:12 So were there just all these geniuses out there who just never had the opportunity to
    0:46:13 do it and now they do?
    0:46:16 Or is there something happening in the industry where people are being trained in a different
    0:46:17 way?
    0:46:18 It’s just the love of television.
    0:46:19 So it perpetuates itself.
    0:46:23 And we might be in a golden age where artists are apprenticing in some way for other artists
    0:46:26 and learning and figuring it out.
    0:46:30 You know, I have the luxury not to think about the 560 shows or to appreciate what Landgraf
    0:46:34 says and know he’s a brilliant guy without having to be cowed by that or feel anyway
    0:46:37 about it because I just want to, I still go back to the same thing.
    0:46:40 I just want to get in the room and get the feeling I get when I’m making the thing.
    0:46:44 I want to be walking on the set and see Damien and Paul and Maggie in Asia and be able to
    0:46:45 work with them.
    0:46:53 And we’ve just found a way to make decisions still based on our curiosity and our obsession.
    0:46:57 So if we’re interested in the US Open in 1991 and Jimmy Connors, we’ll go make a documentary
    0:47:01 about it because we’ll really enjoy the process of making it and we have faith that there
    0:47:02 will be people who will want to see it.
    0:47:05 I was thinking my answer to Mark’s question, I’m trying to make him watch this movie Gully
    0:47:06 Boy.
    0:47:07 I haven’t seen it.
    0:47:11 It’s a Bollywood movie that’s produced by Nas, but to me the point is that technology
    0:47:14 has democratized the access to watching all this visual literature.
    0:47:15 I don’t understand.
    0:47:20 Ben is not able to make him watch something produced by Nas that makes no sense to me.
    0:47:23 Ben and I have the kind of partnership where we’re able to compliment.
    0:47:26 Actually, I wanted to ask you, that was the other question I wanted to ask you.
    0:47:29 So you have been partners now with David for how long?
    0:47:30 Over 20 years.
    0:47:31 It’s an equal partnership.
    0:47:32 It has always been from the beginning.
    0:47:33 Okay, equal partnership.
    0:47:34 Fully 50/50.
    0:47:35 Beautiful.
    0:47:38 So how do you, if somebody comes to you and says like, I want to have a partnership
    0:47:39 like that.
    0:47:40 I want to have a career where I have a partner like that.
    0:47:41 How do you do that?
    0:47:43 Well, do you remember when the four of us first, do you remember when the four of us
    0:47:44 first met?
    0:47:47 How funny it seemed to the bus when we, you, Ben and David, we were sitting there and
    0:47:54 it was just like, this is a rare thing to have two sets of people who just, in the same
    0:47:58 way it makes sense when someone sees you and Ben and talks to you for five minutes.
    0:48:02 When someone sees David and me and they talk to us for five minutes, the whole thing just
    0:48:03 kind of makes sense.
    0:48:08 In the ways that we can finish each other’s sentences, but also are different in some significant
    0:48:09 ways.
    0:48:14 When someone else heard us talking, we’re maybe very similar, but the two of us understand
    0:48:16 the ways in which we’re complementary to each other.
    0:48:22 The key is to really regard the other person as incredibly smart, to really always know
    0:48:26 that their motive is to make the work better.
    0:48:32 So much of the stuff sounds like platitudes, but like trying your hardest to get your emotions
    0:48:34 out of these decisions and being rational.
    0:48:38 I think the key to having a good partnership is not about looking for the partner, it’s
    0:48:42 about how can you make yourself be the best version of yourself in a way that complements
    0:48:48 this other person that who you respect and whose work you admire.
    0:48:50 And so that’s all hard work in life, right?
    0:48:57 It’s the same thing in a marriage or any kind of a kind of a partnership, but it’s about
    0:49:02 all of us, even the most rational, smartest among us, have emotional reactions sometimes.
    0:49:06 And the question is, okay, it’s not to not have an emotional reaction, but it’s to not
    0:49:09 let the emotional reaction dictate your response.
    0:49:17 So if that means you know that you’re the worst of you, instantly reacts with anger,
    0:49:22 then find a way to say, hey, I don’t want to react with anger, I’m going to go take
    0:49:24 a run and then I’m going to come back.
    0:49:27 And this is stuff you figure out over a long period of time.
    0:49:31 But the more you know that the success or failure of a partnership is based entirely
    0:49:35 on how you comport yourself, the better off that you’ll be.
    0:49:36 It’s not the other guy’s fault.
    0:49:37 It’s not the other guy’s fault.
    0:49:38 Don’t you think of it that way?
    0:49:40 I am curious what Mark’s take on this.
    0:49:42 What is your take on that?
    0:49:46 No, so the way I describe it, by the way, this comes up a lot in our business, Ben and
    0:49:50 I have this kind of partnership, lucky for me, but also there’s a lot of founder and
    0:49:51 then CEO.
    0:49:54 Like sometimes we have founder CEOs, which is like your showrunner model, but sometimes
    0:49:57 we have a founder and then there’s a CEO who’s brought in or promoted inside the company
    0:50:00 and then they have to be part, you know, if you want the magic of the founder and the
    0:50:02 company will well run, they need to have that kind of partnership.
    0:50:05 And so when I always tell them, I kind of try to put a point on it and it’s kind of
    0:50:10 say it has to be more important to each of you that it has to be more important than
    0:50:16 each of you that the other one has to be more important that the other one gets to make
    0:50:19 the decision than that you get to prove yourself right.
    0:50:21 And you have to both have that attitude.
    0:50:24 Like if one of you has that attitude, then you just, that person’s just going to run
    0:50:25 over the other ones.
    0:50:27 If you both have the attitude where your reflexive view is, you know what?
    0:50:28 This is a debate.
    0:50:29 It’s an argument.
    0:50:30 It’s 50/50.
    0:50:31 It’s a toss up, which a lot of these things are.
    0:50:33 We’re going to do it your way.
    0:50:36 If both people have that as their default point of view, then you can navigate through
    0:50:37 these things.
    0:50:40 And then you get in the positive version of the deadlock, which is like, no, let’s do
    0:50:41 it your way.
    0:50:42 Okay.
    0:50:43 Now we have a healthy conversation.
    0:50:48 Sometimes there’ll be emails back and forth about a thing in an editing where one of us
    0:50:52 will have an idea and the other one will say, my instinct was to go the other way with
    0:50:53 it.
    0:50:54 But you know what?
    0:50:55 Let’s, let’s, let’s do it that way.
    0:50:57 And it’s not even a, it has to not be a move.
    0:51:01 I think you have to actually be like, there was a thing yesterday.
    0:51:06 I, where I, I saw something and I had a, um, a notion about it and David sent me back.
    0:51:08 Um, well, there are a few different things that are good.
    0:51:13 So normally when we’re doing edits on, when we’re comment, making notes on a cut in order
    0:51:17 to do edits, our two assistants, we share two assists.
    0:51:18 Not like one’s his assistant and one’s mine.
    0:51:23 We have two assistants who help the two of us normally there on the conversation so that
    0:51:27 they can then collate the notes and give them to the editor before we go talk to the editor.
    0:51:31 But if there’s something that suddenly is going to, we see really differently, we just
    0:51:33 immediately take it to a private communication, right?
    0:51:37 We take the, we take the audience out of it.
    0:51:38 We never talked about this, but we just do it.
    0:51:41 We take the audience out of it because let’s not perform, not performing and we’re also
    0:51:43 not worried about being judged.
    0:51:46 But so yesterday was one of those things where we just saw one little tiny moment slightly
    0:51:47 differently.
    0:51:48 I wrote this thing like, I think we should do this.
    0:51:51 And then Dave wrote me separately and said, you know, I don’t, I don’t see the scene that
    0:51:52 way.
    0:51:53 Here’s what I think is going on.
    0:51:56 And I still saw the scene the way that I saw it, but I just immediately went, no, he’s
    0:51:57 right.
    0:51:58 Yeah.
    0:51:59 Let’s just do that.
    0:52:00 It makes total sense.
    0:52:03 Like let’s go through the next bunch of iterations of the, of the cut with it in like that.
    0:52:06 And the, in the hope that I’m just going to come around to seeing it that way.
    0:52:09 Or let’s show it to some, some other people this way and let’s see what, what comes out
    0:52:10 of it.
    0:52:12 It would have been very easy.
    0:52:14 And I see a lot of people fall into the trap of trying to argue.
    0:52:17 Well, I look for as many, by the way I think about it is I look for as many chances as
    0:52:19 I can to let him make the decision, right?
    0:52:21 And then, and then to your point, like if I real feel as a consequence of that, I build
    0:52:22 up so much trust.
    0:52:23 That’s right.
    0:52:28 If I still strong about something, that’s a really great point.
    0:52:32 This is important to attach to that, which is because all the time Dave is willing to
    0:52:34 say to me, let’s do that.
    0:52:37 When he wrote me and said like, Hey, I think this is different than you think it is.
    0:52:41 It was just so easy to go, well, yeah, of course, dude, go, let’s do that thing.
    0:52:44 Because we’re always looking to let it be the way I want it.
    0:52:45 As I am.
    0:52:50 So I would say I’m certain none of that is a tactic or a strategy with Dave and me.
    0:52:54 It just so happens to be the way that the two of us interact.
    0:52:57 A quick question on this, though, just from like an advice point of view, because you
    0:53:03 talk about this, how do you manage your own personal psychology around anger and creative
    0:53:08 impulse and ego kind of in the, in this process, even beyond the partnership?
    0:53:09 Well meditation helps.
    0:53:14 It’s so, I mean, I know, as I said before, some of this stuff sounds so reductive and
    0:53:18 so much like platitudes, but you know, I love that Tim Ferriss has said out of the whatever
    0:53:23 a thousand people that he’s interviewed, who he views as highly successful creatives, like
    0:53:27 92% of them meditate.
    0:53:28 And I don’t think that’s just buy-in.
    0:53:30 I don’t think it’s just that everyone’s decided to buy-in.
    0:53:31 So I’m in the 8%.
    0:53:32 Yeah, I know.
    0:53:33 I’m like, Mr. Anti-Meditation.
    0:53:34 I’m not into anti-meditation.
    0:53:35 Anti-meditation.
    0:53:37 Well, I’ve never, I’ve never, I’m not philosophically anti-meditation.
    0:53:38 I’m personally anti-meditation.
    0:53:43 I cannot imagine sitting still with my own thoughts for longer than about 30 seconds.
    0:53:44 I couldn’t either.
    0:53:45 Right.
    0:53:46 So this is my question.
    0:53:50 Talk to me as a practical person who’s interested in performance and not particularly interested
    0:53:51 in introspection.
    0:53:52 Like, how would I?
    0:53:53 Well, I do the simplest kind.
    0:53:55 I do Transcendental Meditation.
    0:53:58 So it’s the easiest one because it’s just quietly saying a mantra to yourself for 20
    0:53:59 minutes, right?
    0:54:00 Yeah, define Transcendental Meditation.
    0:54:01 Well, that’s what it is.
    0:54:07 Transcendental Meditation is you, because I had ADHD person, I can’t sit still.
    0:54:12 I have to check all that stuff, except I really do this twice a day, 20 minutes.
    0:54:15 And what I found, and it’s just personal.
    0:54:20 But what I found was it like reduced the physical manifestations of anxiety by a lot.
    0:54:24 And when you get, for me, when I get anxiety out of the equation, I just think more clearly
    0:54:25 and more creatively.
    0:54:29 So it’s, and it’s not, I’ll say the other thing is people build it up too much, right?
    0:54:31 It’s not some magic pill.
    0:54:37 It doesn’t like immediately make you, you’re not suddenly becombed, but it just kind of
    0:54:43 takes like a little bit of the tumult out.
    0:54:48 And a lot of forms of meditation require you to force out the thoughts as you said, or
    0:54:52 require you to be introspective, or require you to focus on your breathing.
    0:54:56 Transcendental Meditation, all you’re doing is sort of allowing this mantra to be said
    0:54:57 over and over.
    0:54:58 And if thoughts come in, that’s fine.
    0:55:02 You just kind of let the thoughts come in, and then you kind of return to this mantra.
    0:55:04 And I’ll say the results for me.
    0:55:09 So I was hugely skeptical, but I was at a point where I was feeling like I needed something.
    0:55:13 I had too much agitation.
    0:55:17 And so in reading about, I read David Lynch’s book, Catching the Big Fish, and a couple
    0:55:18 of other books.
    0:55:19 And it made me interested enough.
    0:55:22 And I went and sat down with Bob Roth, who runs the Lynch Foundation, and I said, look,
    0:55:24 I think you’re probably a cult.
    0:55:28 I think that I’m an atheist.
    0:55:32 You know, I know these are like Sanskrit words that have some holiness to them.
    0:55:34 So none of that stuff works for me.
    0:55:37 So talk to me about why I should even be sitting here.
    0:55:40 And you know, Bob was like, well, why don’t you read this book and why don’t you read
    0:55:42 this study and why don’t you look at these EEGs?
    0:55:47 And let’s talk about what this tool does in terms of affecting the loops in your brain
    0:55:48 and your brainwaves.
    0:55:54 And in through that conversation, I was like, well, okay, let me, you know, I’ll learn.
    0:56:02 And within, I’ll say like within two months, I noticed in my family noticed that I was
    0:56:04 just in a much better place.
    0:56:09 And again, it doesn’t mean I’m never a dick.
    0:56:10 Like we’re all a dick sometimes.
    0:56:14 It doesn’t mean I’m never short with anyone or that I’m never worried.
    0:56:15 Of course I am.
    0:56:16 I’m a human being.
    0:56:19 But it means that I can manage it in a much better way.
    0:56:25 And if the only thing I got out of it was I was sitting and meditating and when you’re
    0:56:33 not trying to think of ideas, but like I’ve solved many tricky story problems.
    0:56:37 I’ve come out of a meditation and just kind of had the answer show up.
    0:56:41 Now that that could just be a function of like, I turned everything off and I, I consciously
    0:56:43 wasn’t thinking about it.
    0:56:45 And so I allowed this.
    0:56:46 That’s great.
    0:56:47 Perfect.
    0:56:54 How, whatever it is, it’s not surprising to me that so many of us who are high achievers
    0:57:01 aggressive in going after what we want, willing to take risks, that finding some tool that
    0:57:05 gives you some enforced break from that.
    0:57:09 It’s not surprising to me that that then when you then come out of that, you’re kind of
    0:57:10 firing again.
    0:57:14 That’s what makes sense to me.
    0:57:15 Sir, who’s Bob?
    0:57:16 Sir, who’s Bob?
    0:57:17 Bob Roth runs David Lynch Foundation.
    0:57:20 David Lynch Foundation is like at the center of transcendental meditation.
    0:57:21 Lynch had the side.
    0:57:22 David, the real David Lynch.
    0:57:23 The director, David Lynch.
    0:57:24 David Lynch is the biggest.
    0:57:28 David Lynch is the reason transcendental meditation is popular in America.
    0:57:32 Lynch credits TM with making him the artist that he is.
    0:57:35 David Lynch just for Twin Peaks, Blue Velvet.
    0:57:36 Oh yeah, all that stuff.
    0:57:39 He started doing like 40 years ago or 50 years ago and he wanted to start a thing that would
    0:57:42 give it to kids and post-traumatic stress people.
    0:57:47 So he started this foundation and the guy who runs it and who’s like sort of the kind
    0:57:49 of the head of TM in America is this guy Bob Roth.
    0:57:53 The best part of that story, by the way, though, is that you were literally arguing, to Mark’s
    0:57:56 point about this tent, because Mark essentially set it up as a tension between performance
    0:58:00 and introspection and you’re essentially arguing that introspection leads to better performance.
    0:58:03 Well, I know I would argue that it’s not introspection.
    0:58:06 My journaling is definitely, a certain kind of introspection serves me, but meditation
    0:58:13 is like the calming of the thoughts or the stilling of it, or it’s just a respite in
    0:58:14 a way.
    0:58:19 It’s a respite from the perpetual thinking machine thing.
    0:58:23 I think the idea is that you have these thoughts, these pattern thoughts, and there are some
    0:58:26 thoughts that you know you have, but then there are these like patterns of thoughts
    0:58:32 that you have that are probably a little bit disruptive, but they’re loop.
    0:58:36 And when you start to say this mantra, you’re interrupting, right, suddenly that’s what
    0:58:40 the sound is and the other thing just dissipates and you get calm.
    0:58:45 I’m not trying to think about my life when I’m meditating, I’m just trying to take a
    0:58:46 break.
    0:58:47 Yeah.
    0:58:48 Okay.
    0:58:50 Let’s spend the last few minutes just talking about billions specifically.
    0:58:54 As friends, we’re about to go into some light spoiler alerts, particularly from the last
    0:58:55 and early seasons.
    0:58:58 So if you haven’t seen them already, you’ve been warned.
    0:59:02 I have to ask this question because you know that scene from as good as it gets where there’s
    0:59:05 a female character that goes to Jack Nicholson and you just say, “How?”
    0:59:08 I just, I sacrifice take away honor and what’s the exact line.
    0:59:10 Well, actually I was thinking of another thing.
    0:59:11 I have not seen this movie.
    0:59:12 Oh, you haven’t.
    0:59:13 You guys have to describe.
    0:59:14 You guys have to describe.
    0:59:16 I thought you were going to say the one where I think of a man and then I take away reason
    0:59:17 and…
    0:59:18 Yes.
    0:59:19 Well, that was his response to her.
    0:59:21 What I have is, “How do you write women so fucking well?”
    0:59:22 Well, that’s his answer.
    0:59:23 Yes.
    0:59:27 I disagree wildly disagree with his answer, which is good to hear.
    0:59:34 But the best characters on billions are quite honestly the female and transgender characters
    0:59:40 of Maggie Sif, who plays Wendy Rhodes and Asia Kate Dillon, who plays Taylor.
    0:59:43 I mean, I want to ask you, how do you do this incredible character development for these
    0:59:44 female characters?
    0:59:48 You know, the hardest questions to answer are the, “How do you do the thing?”
    0:59:53 Because that is, that’s the part that’s not…
    0:59:55 There is no intellectual answer to that question.
    1:00:01 That’s the part of it that either makes you someone who does this or doesn’t do it.
    1:00:05 The most fun part for me is when I’m sitting on my couch, actually writing the scenes,
    1:00:06 right?
    1:00:14 I have music blasting, able to put the computer, the laptop actually on my lap, and I’m able
    1:00:16 to sort of fly.
    1:00:19 And that’s the part that isn’t intellectual at all.
    1:00:22 It’s the result of all the intellectual work you’ve ever done.
    1:00:23 It’s the result of your curiosity.
    1:00:27 It’s the result of everything you’ve read, of everything that you’ve watched, of everything
    1:00:29 that you’ve been a part of.
    1:00:34 And then you want to just allow it to happen.
    1:00:38 And so we honor these characters.
    1:00:44 And Wendy Rhodes, when we invented that character and then wrote it, we certainly know who
    1:00:49 that person is very well, but you have to make these fictional characters feel incredibly
    1:00:54 real to you and you want to write them smarter than you are.
    1:00:57 And that’s the only thing I can say is we want every character in Billions to be smarter
    1:00:58 than we are.
    1:01:03 So a quick question about Taylor as a character because Billions, the next season is now dropping.
    1:01:11 You ended the last season with a tension between the head of Axe Capital and his protege, Taylor,
    1:01:13 including their own firm.
    1:01:18 And I so relate to Taylor’s character, like you won’t believe, there’s a sense of like
    1:01:19 unbounded ambition.
    1:01:20 Are you trying to tell Mark something right now?
    1:01:22 No, no, no, no, not in that sense.
    1:01:23 This happened before.
    1:01:28 There’s this unbounded ambition with Taylor and Axe initially nurtures it and then essentially
    1:01:29 squashes it.
    1:01:34 I’m dying to know, like, Taylor’s a really interesting archetype actually, both that
    1:01:39 Taylor’s transgender and that you have this essential universal archetype in every organization.
    1:01:41 Tell me how you think about Taylor as a character.
    1:01:47 Well, Taylor’s just the most highly competent person and is a brilliant person.
    1:01:54 And if this is a long novelistic piece, we’re still sort of at the middle, the beginning
    1:01:56 of the middle of the story.
    1:01:59 And so that kind of person has to be tempted, right?
    1:02:00 Has to be tested.
    1:02:06 If you don’t test the morality of those kind of characters, how do you know whether they’re
    1:02:07 really moral or not?
    1:02:09 They don’t get lost for a little while.
    1:02:10 How do they become found?
    1:02:13 And so that’s where we find Taylor in this season.
    1:02:14 I don’t want to spoil anything.
    1:02:15 Okay.
    1:02:16 I have another quick one.
    1:02:17 I’m just dying to ask.
    1:02:18 And we’ll lightly round these and then we’ll wrap up.
    1:02:21 I want to ask you about some of the music choices you make and one specific one.
    1:02:27 Last season, one of the most compelling raw music choices you made is in a scene for those
    1:02:28 who haven’t caught up all the way.
    1:02:33 I’ll just give a little teaser where Axe essentially is let out of a situation where
    1:02:36 he was in trouble and he’s coming back to his pad and it’s literally, you guys portray
    1:02:40 it visually as a completely raw bachelor pad.
    1:02:42 And the song was “Street Punk.”
    1:02:43 Vince Staples, yeah.
    1:02:44 Oh my God.
    1:02:46 I fucking love that moment.
    1:02:50 It so stripped him bare down to just, he’s a street punk.
    1:02:52 Tell me about that decision and that choice.
    1:02:57 I mean, David and I choose all the music for the show together and we’re both music fanatics
    1:03:03 and trade music all the time and so, and we put music in the scripts.
    1:03:07 So when we’re writing that script, we’re going back and forth about what it should be.
    1:03:08 Is it hip hop?
    1:03:10 If it is, who is it and why?
    1:03:13 We had Vince Staples on the list since the end of the first season, I think, when his
    1:03:15 first record came out.
    1:03:18 “North, North” is what I thought we would use from the beginning.
    1:03:24 But that moment, you know, that moment people really understand what happens when Axe gets
    1:03:25 in that hot tub.
    1:03:27 And again, that was in the script.
    1:03:30 That was what our goal was and then we had to work incredibly hard with our brilliant
    1:03:40 editor who figured out how to make that sequence work the way we’d had it in our heads.
    1:03:45 Marnie Mayer, who edited that episode, really worked incredibly hard to build that sequence
    1:03:49 so that it matched and then exceeded what we had written.
    1:03:51 And Marnie’s been with the show from the very beginning.
    1:03:54 She and an editor named Naomi Garrity have been with the show from the start and are
    1:03:58 really and truly our creative partners there, the guardians of the tone of the show with
    1:03:59 us.
    1:04:00 That’s great.
    1:04:01 That was the last one.
    1:04:02 And then we can wrap up.
    1:04:04 So in season one, does this count as a spoiler alert?
    1:04:05 Because it’s so early in the season.
    1:04:06 I’ll just give it a high level.
    1:04:07 We’ll decide.
    1:04:08 Okay.
    1:04:12 There’s a scene where you essentially set up Axe.
    1:04:15 The entire audience thinks that he’s going to cheat on his wife.
    1:04:19 And I spent that entire episode on the edge of my seat worried that he was going to cheat
    1:04:20 on his wife.
    1:04:21 This is an acceptable spoiler.
    1:04:22 This is a spoiler.
    1:04:23 This is totally a spoiler.
    1:04:24 But it’s an acceptable one.
    1:04:25 100%.
    1:04:26 I don’t know how you can conceivably think of this.
    1:04:27 It’s season one.
    1:04:28 Okay, fine, guys.
    1:04:29 But just a quick thing on that.
    1:04:30 That was obviously deliberate.
    1:04:32 Tell me about the decision making behind that.
    1:04:37 So what I was saying, the thing about sitting on the couch writing and how that is this
    1:04:41 incredibly free process, then you have to rewrite.
    1:04:43 And then you have to think about how it fits into the whole.
    1:04:48 So the whole gag is to write with total freedom and then rewrite with total clarity.
    1:04:54 And so when we’re thinking about whether a character will behave in way A or way B,
    1:04:55 we’re thinking about what they would do in the moment.
    1:04:57 And then we’re thinking about the ramifications of that.
    1:05:03 So if the character did decision A, well, what does that then say about that character
    1:05:05 as we go through the rest of the series?
    1:05:09 Which will leave us in a place where there’s more optionality.
    1:05:13 And it’s clear in that case, which one would leave us with more optionality.
    1:05:14 That’s great.
    1:05:15 Okay.
    1:05:16 Oh, can I say one thing though?
    1:05:18 One of the great things about something like this is that someone like Mark can do the work
    1:05:21 he does and then I can do the work that I do.
    1:05:26 And if there’s some sort of a mutual sort of fascination with the work, you get to connect
    1:05:27 with people on that.
    1:05:31 And that is one of the sort of unintended joys of the work that I get to do.
    1:05:36 And so that’s why I was happy to fly out here and do this podcast because we’ve gotten to
    1:05:39 know each other over the last few years and it’s been a real pleasure.
    1:05:40 Thanks for having me here.
    1:05:41 Thank you, Brian.
    1:05:43 Thank you so much for joining the A6NZ podcast, Brian, and for coming out here.
    1:05:44 We really appreciate it.
    1:05:46 And Billions in the next season is now out.
    1:05:47 March 17th.
    1:05:48 Thanks, Brian.
    1:05:49 So happy to be here.
    1:05:50 Thanks, guys.
    1:05:51 Thank you.
    1:05:53 And by the way, people may not know, I actually play on the show.
    1:05:57 I actually play wigs under a rubber mask.
    1:05:59 And so that’s why you never see me in a cameo.
    1:06:00 I thought we weren’t supposed to have sex.
    1:06:01 I’m sorry, everybody.
    1:06:02 Speaking of spoilers.
    1:06:03 Oh, my God.
    1:06:04 This is one of my favorite characters.
    1:06:04 Well, thank you.
    1:06:12 [BLANK_AUDIO]

    with Brian Koppelman (@briankoppelman), Marc Andreessen (@pmarca), and Sonal Chokshi (@smc90)

    The writer-showrunner is a relatively new phenomenon in TV, as opposed to film, which is still a director-driven enterprise. But what does it mean, as both a creative and a leader, to “showrun” something, whether a TV show… or a startup? Turns out, there are a lot of parallels with the rise of the showrunner and the rise of founder-CEOs, all working (or partnering) within legacy systems. But in the day to day details, really “owning” and showunning something — while also having others participate in it and help bring it to life — involves doing the work, both inside and out.

    This special, almost-crossover episode of the a16z Podcast features Billions co-showrunner Brian Koppelman — who also co-wrote movies such as Rounders and Ocean’s 13 with his longtime creative partner David Levien — in conversation with Marc Andreessen (and Sonal Chokshi). The discussion covers everything from managing up — when it comes to executives or investors sharing their “notes” aka “feedback” on your work — to managing down, with one’s team; to managing one’s partners (or co-founders)… and especially managing yourself. How to tame those irrational emotions, that ego?

    Ultimately, though, it’s all about unlocking creativity, whether in writing, coding, or other art forms. Because something surprising happened: Instead of TV going the way of music à la Napster with the advent of the internet, we’re seeing the exact opposite — a new era of “visual literature”, a “Golden Age” of television and art. Are artists apprenticing from other artists virtually, learning and figuring out the craft (with some help from the internet, mobile, TV)? And if we really are seeing “the creative explosion of all time”, what does it take to explode our own creativity in our work, to better run the shows of our lives? All this and more in this episode of the a16z Podcast… as well as some Billions behind-the-scenes (and light spoilers, alerted within!) towards the end.

  • a16z Podcast: Lessons Learned from Chinese Education Startups

    AI transcript
    0:00:02 >> Hi, this is Frank Chen.
    0:00:04 Welcome to the A16Z podcast.
    0:00:08 This episode is part two of a series called
    0:00:10 “What’s Next for Education Startups?”
    0:00:12 It originally aired as a YouTube video,
    0:00:19 and you can watch all of our YouTube videos at youtube.com/a16zvideos.
    0:00:21 >> Hi, this is Frank Chen.
    0:00:23 Welcome to the A16Z network.
    0:00:26 I’m very excited today to share a conversation I had with
    0:00:29 Connie Chan, one of our general partners.
    0:00:33 Connie is one of the world’s experts on trends,
    0:00:36 especially consumer trends in China and tech.
    0:00:40 Today, we’re going to talk about the future of lifelong learning,
    0:00:46 and she’s going to share a few examples of very awesome startups in China.
    0:00:50 She’s super interested in what’s happening with Gen Z consumers.
    0:00:56 She’s very interested in real estate and how people are finding homes,
    0:01:01 preparing their homes to be listed on Airbnb, renting homes, so on and so forth.
    0:01:06 She’s also very inspired by things that entrepreneurs are doing in China
    0:01:09 that might have applicability here in the United States.
    0:01:15 She helped us find our investments in line and Pinterest,
    0:01:20 and I think you’ll really enjoy this conversation that I had with Connie.
    0:01:23 I have to tell you a funny story before we get started,
    0:01:26 so we did not synchronize our sweaters.
    0:01:31 We’ve known each other so long that we just knew to come in the same color family.
    0:01:34 So Connie was my first hire at Andreessen Horowitz.
    0:01:37 The Adam Rifkin introduced us to Adam at one time,
    0:01:40 and may still be the most connected person on LinkedIn,
    0:01:43 and his whole heart and mission is to connect people,
    0:01:45 and so when I told Adam,
    0:01:48 I was looking for the best ideal partner ever.
    0:01:49 He went and found Connie,
    0:01:53 and I’m so thrilled that you’ve been here for so long,
    0:01:57 and now are a general partner looking to make investments, so welcome.
    0:01:58 Thank you.
    0:02:04 So today, we’re going to continue our series in education
    0:02:06 and talk a little bit about ongoing education,
    0:02:10 and we’re so excited about the things that we can do as adults
    0:02:12 to continue to learn new things,
    0:02:13 and for those of you that know me,
    0:02:16 like learning a new thing is my favorite thing in life,
    0:02:18 so I’m so excited about this episode.
    0:02:20 So Connie, why don’t you set the context,
    0:02:23 and let’s talk a little bit about the things that are working,
    0:02:25 especially in China,
    0:02:29 and I thought maybe it’d be good to just anchor on how much money
    0:02:32 and how many users people spend on ongoing adult education,
    0:02:34 because this is very surprising.
    0:02:37 Yeah, I think about education and learning
    0:02:40 in a way that goes well beyond K through 12.
    0:02:44 So I’m actually hyper-focused on education for adults, people.
    0:02:46 Once they’ve graduated college,
    0:02:51 how can they use online education for self-improvement, for example?
    0:02:53 And if you look at the dollars abroad,
    0:02:57 I do a lot of studying what’s working in China and working in Asia
    0:03:00 to give me inspiration for ideas here in the States.
    0:03:02 It’s a massive market in Asia.
    0:03:03 It’s massive in China,
    0:03:06 and I think it’s because China has developed
    0:03:08 all these online education platforms
    0:03:10 that are specifically made for mobile
    0:03:13 that unlock all these other new features and benefits.
    0:03:16 And in terms of how big it is,
    0:03:18 iResearch says that right now,
    0:03:23 online education in China is 150 million users
    0:03:28 and expected to grow to nearly 300 million by year 2020.
    0:03:31 It’s a $40 billion industry,
    0:03:33 expected to grow to $70 billion.
    0:03:36 Of course, this is a very broad categorization
    0:03:37 of what counts as education,
    0:03:40 but what’s interesting is the way
    0:03:42 that these research reports break it up.
    0:03:44 The largest group is not K through 12.
    0:03:47 It’s not even college students.
    0:03:49 The largest groups of students
    0:03:52 who want to do self-improvement in online education,
    0:03:54 they are 26 to 35.
    0:03:56 – Yeah, that’s super interesting.
    0:03:58 So you would expect sort of the Asian cultures
    0:04:01 that the parents sending their students
    0:04:03 to after school enrichment programs,
    0:04:05 and so you think that’s where all the money is going,
    0:04:07 but you’re saying, look, it’s after they graduate college.
    0:04:08 – Right, right.
    0:04:11 And I think that’s because if you take the word education
    0:04:15 and you expand it just to self-improvement, self-learning,
    0:04:17 then it greatly increases the demographic
    0:04:18 that you can address.
    0:04:21 And yes, a lot of people just say China education,
    0:04:25 it’s huge because parents spend so much money on tutoring
    0:04:29 and so forth because of the way the college system works.
    0:04:32 But most of that money is actually going through
    0:04:34 post-college graduates.
    0:04:37 – It’s really interesting ’cause in China,
    0:04:39 what’s already happening is what we sort of expect
    0:04:42 to happen here, which is today we have this system
    0:04:44 where sort of you go through K through 12
    0:04:45 and then a subset of these people go to college
    0:04:49 and then basically at age 22, you’re done.
    0:04:50 There’s no more formal education
    0:04:54 and now it’s basically the workplace’s job to train you.
    0:04:55 They’ll send you to classes and so on.
    0:04:57 And we know that’s gonna change.
    0:05:00 We know that the world is so dynamic now
    0:05:02 that you can’t learn everything that you need
    0:05:05 to be a productive worker or a citizen by age 22
    0:05:07 and you’re gonna have to learn ongoing.
    0:05:10 This is sort of a big part of our investment thesis
    0:05:11 behind Udacity.
    0:05:14 – And there’s a bunch of courses that a college curriculum
    0:05:16 would likely never include.
    0:05:18 How to conduct yourself at a meeting,
    0:05:23 how to speak publicly, how to sleep train your kid.
    0:05:24 That counts as education.
    0:05:26 Parenting courses, that counts as education.
    0:05:29 You would never cover that stuff in college.
    0:05:31 – And in addition to sort of the evergreen stuff
    0:05:33 that you mentioned, everybody needs to be
    0:05:34 a good public speaker.
    0:05:36 Everybody needs to know how to do it.
    0:05:39 There’s also sort of topical things that emerge
    0:05:41 as marketplaces emerge.
    0:05:43 So I’m thinking about the Taobao sellers, right?
    0:05:45 So Taobao was like eBay here.
    0:05:49 And what happened in Taobao was there were sellers
    0:05:51 who were experimenting with the system
    0:05:54 and they kind of figured out what was working for them
    0:05:57 and they would share online and in videos
    0:05:59 and Taobao saw this happening and they’re like,
    0:06:01 oh, let’s actually get behind this and push, right?
    0:06:03 Let’s set up Taobao University
    0:06:05 where we can take our very best sellers
    0:06:08 and actually have them make money from their content,
    0:06:10 not just their markets.
    0:06:11 – Yeah, completely.
    0:06:13 – Yeah, so awesome.
    0:06:16 So why do you think this is happening already in Asia?
    0:06:17 Why are they ahead?
    0:06:22 – I think Asia is in general much more mobile first
    0:06:26 and mobile only of an environment than the States.
    0:06:29 Meaning that if I asked you to go buy a pair of shoes,
    0:06:32 you might naturally flock to your computer
    0:06:34 to get the best user experience.
    0:06:36 But in Asia, you’d pull up your phone
    0:06:39 and you’d open the T-Mall or the Taobao app.
    0:06:41 And the idea that your PC and phone
    0:06:44 are completely interchangeable
    0:06:46 and you can completely rely on your phone
    0:06:50 to give you everything you need is more prevalent in Asia.
    0:06:52 There’s also more mobile payments
    0:06:54 and the idea of paying on your phone
    0:06:56 is very natural and common to people,
    0:06:59 not just interior one cities, but across the country.
    0:07:03 But I think there’s three core breakthroughs and insights
    0:07:04 that Asia has really figured out
    0:07:06 that has propelled its education market
    0:07:08 so much more forward.
    0:07:12 The first one is that they rely on artificial intelligence
    0:07:17 and machine learning in a much more interesting way.
    0:07:21 So that allows them to unlock products and features
    0:07:24 and just ideas that I don’t see here in the States.
    0:07:27 So for example, there’s this company called Lingo Champ
    0:07:29 and it teaches you English.
    0:07:32 And typically when you look at a language learning app
    0:07:35 here in the States, it’s very flashcard driven
    0:07:39 or it’ll give you a sentence and you can read it.
    0:07:42 But in Asia, they realize that people want to learn English
    0:07:44 not just to be able to read and write,
    0:07:46 but more importantly to have conversations
    0:07:48 to be able to visit the world,
    0:07:51 to interact with other people.
    0:07:54 And so they use the mobile phone and the microphone
    0:07:57 to allow you to speak directly into the app
    0:08:01 and read out sentences and actually carry on conversations
    0:08:04 with a computer that will speak back to you.
    0:08:07 And that kind of scoring using machine learning
    0:08:09 and artificial intelligence allows people
    0:08:14 to learn pronunciation with a standalone mobile app.
    0:08:16 And I think that’s a fantastic example
    0:08:18 of like leaning into artificial intelligence
    0:08:21 and machine learning to dramatically reduce the cost.
    0:08:24 This company, Lingo Champ, their gross margins
    0:08:28 are over 70% because they don’t have the teacher cost.
    0:08:30 – Right, so nobody has to sort of say,
    0:08:32 “Oh, that’s a terrible accent.”
    0:08:34 My funny story on this is when I was learning
    0:08:38 Chinese Mandarin, my Mandarin teacher asked me one day,
    0:08:39 “Are you from Hong Kong?”
    0:08:41 Which, for those of you that don’t realize it,
    0:08:43 is probably the most grievous insult
    0:08:45 that you could hurl at somebody trying to learn Mandarin
    0:08:46 ’cause it’s so bad.
    0:08:50 So you’re saying, look, they didn’t have to have a teacher
    0:08:51 listening to you and then getting guns.
    0:08:53 They’re using the machine learning to say,
    0:08:55 “You don’t sound like a native and here’s where.”
    0:08:58 – Right, and because their gross margins are so high,
    0:09:00 their price point is so much lower
    0:09:01 than having a real-life tutor
    0:09:05 or even an online course instructor tutor.
    0:09:07 Their price point is so affordable
    0:09:11 that people all around the country can access it.
    0:09:15 And that same concept of leaning into machine learning
    0:09:19 is also true in music as another category.
    0:09:24 There’s this company in China called BIP, Peilian.
    0:09:28 And Peilian in Chinese translates to
    0:09:31 they will practice piano
    0:09:34 or practice an instrument alongside you.
    0:09:37 And what it is is a mobile app, which is a piano teacher.
    0:09:40 And this app, you put it on the stand
    0:09:42 and you attach it to your piano.
    0:09:47 And this teacher can help your kid age five through 16
    0:09:48 learn an instrument.
    0:09:49 They do piano, violin,
    0:09:52 a bunch of classical Chinese instruments.
    0:09:55 But again, it’s that price point that they’re able to unlock
    0:09:58 because for a lot of these music instructors,
    0:10:01 so much of that cost is in their travel time
    0:10:03 or because you’re living in a city
    0:10:06 where the cost of living is just so high.
    0:10:11 But now in China, my teacher doesn’t have to live in Beijing.
    0:10:13 They don’t have to live in Shanghai.
    0:10:15 They can live anywhere in the country.
    0:10:18 They don’t even have to live in China, right?
    0:10:19 And then not only is that the case,
    0:10:21 they use the machine learning aspect
    0:10:24 to help the teachers with scoring the kids
    0:10:26 and scoring the performance.
    0:10:29 Because with music, just like with language,
    0:10:31 there is an actual pitch.
    0:10:34 There is an actual tempo and actual rhythm
    0:10:36 that you’re supposed to play, right?
    0:10:39 So they can take the composition score
    0:10:41 and then hear your actual performance
    0:10:42 and give you a grade,
    0:10:44 which then allows one teacher
    0:10:48 to teach two or three students at the same time,
    0:10:50 which then unlocks even more cost savings,
    0:10:54 allowing more parents to give their kids these music lessons
    0:10:56 that they would typically not be able to afford.
    0:11:00 – I’m flashing back to my piano learning days
    0:11:03 and I’m hearing that too fast, too fast, right?
    0:11:06 So now we can do that with machine learning.
    0:11:06 – Right, right.
    0:11:10 And imagine being able to do that during practice sessions,
    0:11:13 right, and having that information feedback to the teacher.
    0:11:15 There’s just a lot more we can do with machine learning,
    0:11:18 especially when it comes to language and music
    0:11:21 that is still, I think, very untapped here in the West.
    0:11:26 – So let’s talk a little bit about sort of the efforts
    0:11:27 that we’ve sort of seen here
    0:11:31 and sort of how you think we get from here where we are.
    0:11:33 So we have learning platforms like Masterclass,
    0:11:34 we have learning platforms like Udemy,
    0:11:36 we have learning companies like Udacity,
    0:11:38 one of our portfolio companies.
    0:11:41 What’s sort of missing from those
    0:11:44 that sort of the next generation of ed tech startups
    0:11:46 you’re looking for, you think we’ll have?
    0:11:51 – Yeah, I think the answer is one word, it’s mobile.
    0:11:56 And the reason is because mobile only is in a society
    0:11:59 that I think is inevitably in our future.
    0:12:00 And when you have mobile,
    0:12:03 that allows for all kinds of different things.
    0:12:07 It allows, again, for microphone input as an example.
    0:12:09 Everyone has a camera, a front-facing
    0:12:11 and a back-facing camera on their phones,
    0:12:13 which allows for different kinds of input
    0:12:15 and interaction with the platform.
    0:12:18 Mobile allows you to have these bite-sized snacks
    0:12:21 rather than opening your Instagram news feed.
    0:12:23 Maybe you can take a three-minute class,
    0:12:27 a five-minute class whenever you have downtime.
    0:12:31 And also mobile allows people to not feel like
    0:12:33 you have to be confined to a video format.
    0:12:36 And I think this is really critical
    0:12:39 because a lot of long-tail expertise
    0:12:42 doesn’t always naturally suit video.
    0:12:44 For example, you can be a math teacher
    0:12:47 and, yes, you’re writing formulas on the board
    0:12:49 or you can be a philosophy teacher, right?
    0:12:51 And you can be sitting there giving a lecture,
    0:12:53 just sitting there.
    0:12:56 Or that same kind of content
    0:12:58 can be also conveyed through a podcast,
    0:13:00 through an audio format.
    0:13:02 And once you’re focused on mobile,
    0:13:05 you’re not thinking like it has to be video,
    0:13:07 it has to be full-screen immersive.
    0:13:10 It now can also be a podcast that you listen to
    0:13:13 when you’re driving to work, when you’re walking to work.
    0:13:18 And again, I think that that expansion of formats
    0:13:21 is really obvious once you make something
    0:13:23 that is mobile-centric.
    0:13:26 – So we haven’t seen the class of mobile-first edtech
    0:13:27 that you were expecting to see,
    0:13:29 which is pretty surprising, right?
    0:13:32 It is sort of an obvious insight
    0:13:34 once you say it out loud like you did.
    0:13:40 – And I think the reason is because so much of edtech
    0:13:43 has been either you pay this one-time
    0:13:44 very expensive tuition,
    0:13:48 or honestly it’s ad-based, right?
    0:13:52 Like YouTube is the biggest university in the world.
    0:13:55 And most of the creators are monetizing
    0:14:00 through advertisements, but because it’s ad-based,
    0:14:02 a lot of the content on YouTube
    0:14:04 can’t go to the depth of absurdities
    0:14:06 that you need to really make a big impact
    0:14:08 on your life or your career.
    0:14:11 Because the creators, they have these incentives
    0:14:14 to have to create content that gets lots of clicks.
    0:14:17 And the reality is a lot of self-improvement
    0:14:21 lifelong learning content is not all clickbait content.
    0:14:25 And to go into that depth of what you need to know,
    0:14:29 an ad format is not the best way to compensate
    0:14:30 these creators.
    0:14:31 So for example, if you’re buying a house
    0:14:34 for the first time, you need to understand
    0:14:36 how to think through that transaction.
    0:14:38 But it doesn’t make sense for someone
    0:14:40 to create these ad-based videos
    0:14:42 because one, they’re not gonna get all the clicks
    0:14:45 they need to justify their time and expertise.
    0:14:48 But I mean, imagine a platform where someone
    0:14:50 could package that in 20, 30 courses.
    0:14:53 It could be a mixture of audio, a PDF,
    0:14:58 video, a live stream Q&A, a paid one-on-one consultation
    0:15:00 and put that all in one format
    0:15:03 where that creator now can make much more money
    0:15:06 and have the right incentives to create deeper,
    0:15:07 better content.
    0:15:09 – Yeah, so that makes perfect sense, right?
    0:15:12 Which is it takes a lot of work to create this content.
    0:15:14 And if you’re monetizing with advertising,
    0:15:17 that means only the top 1% are gonna even break even
    0:15:20 or barely break even on all of that effort, right?
    0:15:22 ‘Cause you need to attract tens of millions of people.
    0:15:26 – And ads reward production value, right?
    0:15:28 So you need the great videographer there.
    0:15:31 You need to spend an hour on your YouTube thumbnail.
    0:15:33 And that’s nuts, right?
    0:15:35 Because honestly, a lot of these great experts,
    0:15:37 a lot of these professors, these doctors,
    0:15:42 these nutritionists, they are not media experts.
    0:15:44 And the fact that they have to go hire videographers
    0:15:47 buy very expensive equipment, cameras, lighting,
    0:15:50 what have you, learn how to edit videos themselves
    0:15:54 for the first time, that’s not long-term,
    0:15:55 I think, going to work.
    0:15:57 Because these creators are being underpaid
    0:15:58 for their knowledge.
    0:16:03 So, as I think about my own sort of ongoing education
    0:16:06 habits, YouTube has definitely become one of them.
    0:16:08 Which is to say, I’m watching TED Talks,
    0:16:09 I did something over the holidays,
    0:16:13 which I’m very proud of, which is I replaced a doorknob.
    0:16:15 And I’m proud of this because I’m the least handy person
    0:16:17 I know, and so I watched a YouTube video
    0:16:20 and went to Home Depot, and in Law’s house,
    0:16:21 I replaced the little doorknob mechanism.
    0:16:24 I was like, yes, I did it.
    0:16:27 And so you were saying, look, I know,
    0:16:28 I shouldn’t be that proud of myself.
    0:16:30 But I was like, giddily proud of myself,
    0:16:31 because I’m a software person,
    0:16:33 and that was definitely hardware.
    0:16:37 So anyway, thank you for indulging my burst
    0:16:39 of enthusiasm for myself there.
    0:16:41 So you’re saying, look, that type of content,
    0:16:43 that’s fine for YouTube, because that’s super easy, right?
    0:16:45 It’s a fine video. – And it’s visual.
    0:16:48 It’s visual, you need to see which part to change out,
    0:16:49 which nail to take out.
    0:16:51 – So ads, for that makes sense,
    0:16:53 but it doesn’t make sense for this sort of
    0:16:56 highly produced package where I’m teaching you something
    0:16:57 that’s a more serious life skill.
    0:17:01 – Right, I mean, TED Talks are fantastic intro courses.
    0:17:03 It’s a first great lecture,
    0:17:05 but there should be 10 lectures
    0:17:07 beyond that for every topic, right?
    0:17:11 And a lot of things that are skill-based, in particular,
    0:17:15 I think deserve having 10 courses,
    0:17:17 20 courses, 30 courses, so on.
    0:17:18 And there’s a lot of things
    0:17:20 that I would be willing to pay for.
    0:17:22 I would love to pay to figure out
    0:17:23 how can I improve my voice.
    0:17:25 I would love to pay to see
    0:17:27 how can I improve parenting and so forth.
    0:17:30 And there aren’t great platforms right now
    0:17:34 that make it as easy as creating like a Shopify website
    0:17:37 for these creators to monetize their knowledge.
    0:17:39 And these creators, typically,
    0:17:41 one, they’re not media experts,
    0:17:43 two, they’re not technologists,
    0:17:46 so they don’t have time to build their own blogs
    0:17:48 or their own websites and integrate PayPal
    0:17:50 or credit card payments into them.
    0:17:54 And the biggest problem is they’re truly underpaid right now
    0:17:57 for the knowledge that they’re freely sharing on YouTube.
    0:17:58 – Yeah.
    0:18:00 If you think about sort of an example
    0:18:02 that is in this ecosystem,
    0:18:03 you think about masterclass, right?
    0:18:06 Where the entrepreneur’s doing a great job
    0:18:09 of sort of hoovering up all of the top experts
    0:18:11 in their fields.
    0:18:13 And I think part of the reason he went top down
    0:18:15 is sort of the same reason that Elon Musk
    0:18:19 went to the Roadster first and then the X
    0:18:21 and then the, or the S and then the X and then the three,
    0:18:23 right, sort of he’s working his way down.
    0:18:26 And I think part of that is because
    0:18:29 I wonder if there’s enough cultural support
    0:18:34 in the West for paying for education of this kind, right?
    0:18:35 So it sounds like in China,
    0:18:36 you already have that cultural support.
    0:18:39 So like what is education amongst household expenses?
    0:18:41 Is it like number three or number four
    0:18:43 after housing and medical, right?
    0:18:48 So you have this inbred sort of support, cultural support.
    0:18:50 Like of course I’m paying for education, right?
    0:18:54 And so once mobile sort of content sources sprung up,
    0:18:56 the money just went, right?
    0:18:58 And so what do you think is gonna happen here?
    0:18:59 Do we need more cultural support?
    0:19:01 How does that interaction happen?
    0:19:05 – I think the way that we Silicon Valley
    0:19:08 and platforms can help encourage this shift
    0:19:10 for more lifelong learning and self-improvement
    0:19:14 is really breaking away from just the ad-based model
    0:19:16 and finding the right incentives for creators
    0:19:18 to be able to monetize.
    0:19:20 Because I think a lot of creators,
    0:19:23 when they have an ability to make a significant amount
    0:19:26 of income from sharing their expertise,
    0:19:28 they will create better content.
    0:19:30 And as there’s better content out there,
    0:19:33 users will say, hey, this is a fantastic way
    0:19:38 to put a small investment into myself, right?
    0:19:40 And right now the platforms, I think,
    0:19:44 are not doing enough to help these creators monetize.
    0:19:46 And for a platform that doesn’t just mean
    0:19:48 changing their business model,
    0:19:51 it also means monetizing their own brand
    0:19:55 and becoming a mainstream app, a mainstream website.
    0:19:58 And that’s really important because for a lot
    0:20:02 of these platforms, they shouldn’t have just one teacher
    0:20:03 teaching you how to sing.
    0:20:05 There should be 20, 30 teachers.
    0:20:07 And then there should be rankings based off
    0:20:09 of student reviews or based off people
    0:20:13 who actually completed the course, right?
    0:20:14 And repeat students and so forth.
    0:20:18 And all those things should help bubble up the best teacher.
    0:20:21 And these platforms need to do a lot to invest
    0:20:23 in building out their own brands
    0:20:24 to become mainstream in order to do that.
    0:20:28 And I love the master class content.
    0:20:32 I think once they expand, they’re gonna have to include
    0:20:33 more teachers for the same categories.
    0:20:34 – They sort of go down in market.
    0:20:36 It doesn’t have to be Steve Martin teaching you
    0:20:37 how to do comedy.
    0:20:39 It’ll be your local comedy genius.
    0:20:41 – Or it could be all of them together, right?
    0:20:44 And they could be priced at different price points.
    0:20:47 And then when you go the level beyond Steve Martin,
    0:20:50 you can have them ranked differently, right?
    0:20:52 And I’d love to be able to figure out
    0:20:55 what are the rankings of the classes that people finished?
    0:20:56 What are the rankings where people gave
    0:20:58 the highest reviews, right?
    0:21:00 What are the rankings based off price?
    0:21:02 What have you, right?
    0:21:08 And all of that kind of data is totally presentable right now.
    0:21:12 It’s just not being surfaced by the platforms.
    0:21:15 – Another sort of age old challenge in sort of building
    0:21:18 these pervasive education marketplaces in the past
    0:21:20 has been you sort of have very broad categories
    0:21:21 of education.
    0:21:23 There’s sort of, let’s call it hobby entertainment, right?
    0:21:24 I’m learning the piano.
    0:21:26 I want to sing better, right?
    0:21:28 And then there’s sort of business self-improvement.
    0:21:31 Like I want to learn how to use Excel better
    0:21:33 or I want to be a better offer up seller
    0:21:34 or something like that.
    0:21:37 So do you think that there’s gonna be one platform
    0:21:39 that sort of wins both?
    0:21:41 Do you think there will be more specialty things
    0:21:42 that sort of cater to each of these
    0:21:44 ’cause it feels like they have different dynamics?
    0:21:46 – I think it’s possible.
    0:21:50 But it’s unclear how the future will shake out.
    0:21:51 I mean, for example, I think there’s a lot
    0:21:54 of great workout apps today already.
    0:21:56 That put a bunch of fitness instructors
    0:21:57 or nutritionists up against each other
    0:22:00 and you can choose which instructor you want.
    0:22:02 And they have that category down pretty well.
    0:22:05 But I also think it’s very possible
    0:22:07 if there was a platform that created the right tools.
    0:22:11 I know that’s like Shopify in a box where I can say,
    0:22:14 here are my podcasts, here are my blog posts.
    0:22:18 These are the times where I’m gonna do a live stream Q&A.
    0:22:22 This is the PDF of the book I’m willing to sell, right?
    0:22:24 If it gave creators these options
    0:22:27 to just turn on these modules
    0:22:31 and create their own knowledge store,
    0:22:32 I think it’s possible also
    0:22:36 to have one major platform as well.
    0:22:39 It serves both sort of the hobbyist entertainment market
    0:22:42 as well as the serious self-improvement market.
    0:22:44 – And it’s possible that it’s not a new startup.
    0:22:47 It could eventually be something that YouTube goes into
    0:22:48 or something that Twitter goes into.
    0:22:50 Twitter has a ton of influencers too
    0:22:52 and lots of long-tail experts.
    0:22:56 But I think the opportunity is still there
    0:22:59 and still so early enough that a new startup could take it.
    0:23:02 – Great.
    0:23:06 If you were to give, if you had one or two pieces of advice
    0:23:08 that you have for entrepreneurs in this space,
    0:23:09 what would it be?
    0:23:15 – This is probably a contrarian view
    0:23:18 even in Silicon Valley, but I would build for mobile first.
    0:23:21 And I would build your app before you build your website
    0:23:24 because it will drastically unlock different ways of thinking.
    0:23:28 You’ll be able to use your GPS, your microphone,
    0:23:30 you’ll be able to use the camera.
    0:23:33 And if those new additions of features
    0:23:34 don’t help you brainstorm new things,
    0:23:37 then that’s a problem actually.
    0:23:40 You’ll be able to use in-app payments, right?
    0:23:42 You might be able to use Apple Pay and so forth.
    0:23:45 So I think one big thing I would say is
    0:23:47 if you’re building for the future,
    0:23:50 consider building this platform first on mobile
    0:23:52 even before you go to the PC.
    0:23:55 And now I know that’s a very contrarian view
    0:23:58 ’cause a lot of investors will also say
    0:24:00 go to the PC first, get your brand
    0:24:02 and then go to the app.
    0:24:05 But I think when you start at least brainstorming
    0:24:07 at the very least on a mobile platform first,
    0:24:09 it unlocks this idea,
    0:24:11 how can I use a microphone differently?
    0:24:15 And then now that I have microphone and audio input,
    0:24:18 how can I use machine learning differently, right?
    0:24:21 And that allows you to unlock ideas
    0:24:23 like the lingo champ for English learning
    0:24:25 or like Paylian for piano teaching
    0:24:28 that honestly someone building for a PC
    0:24:30 would never get to that insight.
    0:24:31 Right, right.
    0:24:33 And then presumably your next piece of advice
    0:24:36 would be experiment on the business model, right?
    0:24:38 So we’ve got mobile, we’ve got machine learning
    0:24:40 and now it’s like let’s do something other than ads.
    0:24:43 Yeah, for sure, for sure.
    0:24:48 I am not a fan of strictly ad-based models
    0:24:52 mostly because the ones that do succeed,
    0:24:53 say like a Facebook or Google,
    0:24:55 I mean the reason their ads succeed
    0:24:57 is not because of the massive page views
    0:25:00 it’s also because of all the information
    0:25:01 they have on that user.
    0:25:04 So the ads are highly targeted, right?
    0:25:06 And if you’re a platform where you don’t have
    0:25:10 such detailed information on your end users,
    0:25:11 your ads are not as valuable
    0:25:14 and they’re not gonna convert as well.
    0:25:17 So focusing on just building up page views
    0:25:18 and hoping they’ll monetize with ads
    0:25:21 to me is a scary strategy in general
    0:25:24 for any consumer app.
    0:25:27 Yeah, but I think business model experimentation
    0:25:29 in the education space is huge
    0:25:31 because I mean a lot of these categories
    0:25:33 like your skills for doorknob, right?
    0:25:37 Maybe it could sell you a similar doorknob.
    0:25:38 They should have sold me the doorknob.
    0:25:40 They should have sold you other doorknob.
    0:25:42 They should have sold you other home projects
    0:25:43 that hey, if you take this course
    0:25:46 buy the components for it at a discount
    0:25:49 and that can be a partnership with your local Home Depot
    0:25:52 ’cause geographically they know the local Home Depot
    0:25:54 is only two, three miles away from where you are.
    0:25:55 Right.
    0:25:57 And those ideas are very possible
    0:25:59 and not being implemented today.
    0:26:02 Kind of thinking if this person learned this course
    0:26:06 what else can I sell them beyond just another course?
    0:26:09 What physical things can I sell them?
    0:26:11 What other services can I sell?
    0:26:12 Yeah.
    0:26:15 It seems inevitable that as we continue into a world
    0:26:18 that rapidly changes, therefore needs new skills
    0:26:22 all of the time that the spending pattern here
    0:26:24 on education will flatten, right?
    0:26:25 Which is the way I think about education spending
    0:26:28 over a lifetime today is kind of like
    0:26:30 there’s an elephant inside a python, right?
    0:26:31 Which is you spend a lot of money
    0:26:34 and then you get to college, right?
    0:26:36 Where you have the 529 plan, right?
    0:26:38 To help subsidize, right?
    0:26:40 Tax deferred dollars to go to university
    0:26:42 and then basically it drops to zero, right?
    0:26:45 It’s sort of like a very small proportion
    0:26:47 of the population spends money on ongoing training
    0:26:49 and if you spend it, it’s mostly like,
    0:26:52 oh, work had me do it and then I expensed it, right?
    0:26:54 But it’s nowhere approaching college tuition.
    0:26:56 So it’s sort of this big sort of college expense
    0:27:00 in the middle, it feels like as we move into a new world
    0:27:01 like we want to flatten that out, right?
    0:27:05 We want to give access to piano teaching for kids,
    0:27:06 smooth it out earlier in life
    0:27:08 and then we sort of smooth it out later in life too.
    0:27:12 And that’s gonna require this business model experimentation.
    0:27:14 Business model experimentation
    0:27:17 and just making that information more accessible.
    0:27:21 Like if I told you you could spend $15
    0:27:23 and get 10 courses on how to improve your voice,
    0:27:24 would you consider it?
    0:27:28 I am looking for voice instructors right now, right?
    0:27:29 – You would do it, right, right, right.
    0:27:31 – I’d pay far more than that.
    0:27:32 – Right.
    0:27:35 – But I feel like so many of these ideas
    0:27:38 or these instructors, people oftentimes just forget
    0:27:42 that they exist because it’s not so in their face.
    0:27:45 And it’s not also done in bite-sized stacks
    0:27:48 on their own schedule, on their own timeframe, right?
    0:27:50 And when you’re on a mobile platform,
    0:27:52 when you’re doing these bite-sized lessons,
    0:27:55 you can do it every morning.
    0:27:56 – Yeah.
    0:27:58 Well, I personally can’t wait for a lot of this stuff.
    0:28:00 As I mentioned, I love learning new things
    0:28:03 and I can’t wait to have very compelling products
    0:28:05 that are teaching me new things
    0:28:08 a little more sophisticated than how to replace a doorknob.
    0:28:10 Maybe a little less sophisticated than how to do it.
    0:28:12 – A platform should have also sold you services
    0:28:14 of a handyman nearby in case you failed.
    0:28:16 – That’s true, right?
    0:28:17 – Luckily.
    0:28:19 – There’s just so many ways you can monetize
    0:28:21 a simple video like replacing a doorknob
    0:28:22 that’s not being done today.
    0:28:24 – Yeah, yeah, totally true.
    0:28:27 – Like all these how-to home fixes,
    0:28:30 a good chunk of people who attempt them can’t do it, right?
    0:28:32 And they’re willing to pay for the local
    0:28:34 handyman to do it. – Surrounded by an explosion
    0:28:35 of tools, right?
    0:28:36 Oh, I give up.
    0:28:37 – Right, or I may be missing this part,
    0:28:39 maybe I’m missing this wrench or hey,
    0:28:41 the power tool, right?
    0:28:42 You could have done this in half the time
    0:28:44 if you had this power tool.
    0:28:47 These ideas aren’t being thought of right now
    0:28:51 because it’s a business model innovation, right?
    0:28:54 Think about not just selling them the next course
    0:28:56 and stuffing more ads into your course
    0:28:58 and then therefore making your video much longer
    0:29:00 than it needs to be, which is the game
    0:29:02 that a lot of these influencers have to play.
    0:29:05 They’re being forced to play that game right now.
    0:29:07 Give them better ways to monetize what they’re selling.
    0:29:10 – Yeah, and that business model would be good for,
    0:29:12 ’cause another age old problem with these education markets
    0:29:14 places that try to get broad, right?
    0:29:16 I want to have all of this content
    0:29:19 is that the repeat usage is never as good
    0:29:20 as the entrepreneur hopes, right?
    0:29:24 So you kind of hope that I sell you the piano playing class
    0:29:26 and then you’ll come to me for filmmaking
    0:29:27 or whatever it is.
    0:29:29 And it turns out in a lot of these
    0:29:33 that you’re almost capturing that customer again
    0:29:36 for the first time, even though they bought a class from you,
    0:29:37 right? – Yeah.
    0:29:39 And to this point is actually,
    0:29:42 I wouldn’t say I’m never a fan of subscription models,
    0:29:45 but for this category,
    0:29:48 I don’t think subscription is necessarily the best model.
    0:29:51 Because for me to sign up for a subscription,
    0:29:54 I have to think I’m gonna take more than one class, right?
    0:29:57 I mean, why not instead let me pay per course?
    0:30:00 And for other courses, if you want to push discovery,
    0:30:04 allow me to sample the first 10 minutes of a class for free,
    0:30:07 right, or do some other kind of incentive
    0:30:09 to get me to see the value.
    0:30:11 And then maybe after two, three courses,
    0:30:13 then sell me something like a subscription.
    0:30:14 Or I’m like, yes, for sure,
    0:30:17 I’m gonna use this multiple times over.
    0:30:20 But the idea of jumping from day one
    0:30:21 to push you a subscription, I think,
    0:30:24 is a hard business model for this category.
    0:30:25 – Yeah, it’s hard.
    0:30:26 You have to capture the people
    0:30:28 who would pay upfront for health clubs, right?
    0:30:30 Which is the sort of, it’s the aspirational me
    0:30:33 that will go to the gym all the time, right?
    0:30:34 – Right.
    0:30:35 – Well, thanks for joining us.
    0:30:39 We’re so excited for the future of EdTech
    0:30:41 that is mobile first and AI enabled
    0:30:43 and isn’t just advertising,
    0:30:44 ’cause I wanna learn new stuff,
    0:30:45 I wanna learn it all the time.
    0:30:47 The next thing I think in our house
    0:30:48 will be clearing clutter.
    0:30:51 And so it’s funny, Marie Kondo
    0:30:52 has that series on Netflix now.
    0:30:56 And so maybe I should watch it
    0:30:58 and maybe there will be a tailor-made startup
    0:31:00 for that type of stuff.
    0:31:02 They can offer me help when I get stuck
    0:31:04 clearing my own crap.
    0:31:06 So, all right, thanks, YouTube.
    0:31:08 We’ll see you next episode.
    0:31:09 If you liked what you saw,
    0:31:13 go ahead and comment and subscribe on the bottom.
    0:31:14 And we’ll see you next episode.
    0:31:15 – Bye.

    When people talk about trends in education technology, they often focus on how to disrupt higher education in the U.S., whether it’s about breaking free of the ”signaling” factor of elite educations or how to shift education out of its ”cottage industry” mindset to achieve greater scale. However, in China, the transformation of education is already well underway, with a fast-growing ecosystem built around lifelong learning. In fact, one of the largest demographic groups paying for education in China is actually not college students — it’s college graduates, aged 26 through 35.In this episode — which originally aired as a video on our YouTube channel — a16z general partner Connie Chan talks with operating partner Frank Chen about the lifelong learning ecosystem in China; what it means for startups there; and lessons for entrepreneurs everywhere… or will these techniques even work outside of China?

  • a16z Podcast: What’s in the Water at the George Church Lab?

    AI transcript
    0:00:03 Hi, and welcome to the A16Z podcast. I’m Hannah.
    0:00:07 Today’s episode features a special conversation with renowned scientist George Church,
    0:00:11 known for his groundbreaking work and methods used for the first genome sequence
    0:00:14 and for his work in genome editing, writing, and recoding.
    0:00:17 Church’s innovations have become an essential building block
    0:00:21 for most of the DNA sequencing methods and companies we see today.
    0:00:25 He has joined in this conversation with A16Z bio-general partner Jorge Conde,
    0:00:29 who, among other things, founded a company with Church out of the church lab.
    0:00:32 The two take us on a wild journey into the scientist’s mind and work,
    0:00:37 starting with what the leading pioneer in this space makes of where we are today with CRISPR,
    0:00:39 especially given recent news about CRISPR babies in China,
    0:00:43 then moving on to the broader implications of all that on a cultural level
    0:00:48 to finally what it takes to go from science fiction to lab to reality.
    0:00:49 So, let’s start at the beginning.
    0:00:55 If we were to bet 10 years ago whether we’d have a CRISPR baby, a mammoth baby,
    0:01:00 or a Neanderthal baby, which would you have bet would have come first?
    0:01:05 Oh, and questionably, a CRISPR baby, you know, I mean, it was not a huge technical leap.
    0:01:10 They all involved societal and ethical questions,
    0:01:14 but that one probably had the clearest path, you know,
    0:01:19 because there was such divergence of opinion, somebody was going to do it.
    0:01:24 And would you have expected that it would have been essentially a rogue effort
    0:01:28 versus a solo effort, as it seems to have been the case in the China CRISPR baby news?
    0:01:30 I wouldn’t characterize it as a solo effort.
    0:01:32 I’ve seen the author list, it’s quite long.
    0:01:38 And I also find it unlikely that a government as technically astute
    0:01:44 and as engaged in observation would be unaware of such an important thing.
    0:01:48 If I were a technically astute government,
    0:01:51 there are very limited number of topics I would be paying attention to.
    0:01:58 And these would be things like, you know, nuclear, biological, encryption, and CRISPR.
    0:02:01 It’s a short list, so I don’t think it’s solo.
    0:02:05 So let’s talk a little bit about the way it’s been sort of positioned, at least publicly.
    0:02:11 Can you describe a little bit what the experiment actually was?
    0:02:15 What did the scientists or scientists do in this particular case for the CRISPR baby?
    0:02:19 I’ve actually seen a lot of the data and the preprints.
    0:02:25 And this was a simple, in a certain sense, application of CRISPR
    0:02:31 to alleviate a potential for HIV infection.
    0:02:37 You know, 900,000 people die every year of HIV, and this was an approach to it.
    0:02:44 And they did it by knocking out the gene that encodes the HIV receptor on the surface of T cells.
    0:02:45 This is CCR5.
    0:02:52 This is CCR5, which has already been approved for FDA clinical trials for Sangamo
    0:02:56 and for editing in adults that have AIDS.
    0:03:00 That’s a different scenario, but vets many of the issues that come up
    0:03:04 as to whether this is a reasonable editing strategy.
    0:03:08 So first of all, people have described it as knocking out the gene.
    0:03:11 Other people have described it as editing the CCR5 gene.
    0:03:15 Having seen the data, what exactly was done to CCR5?
    0:03:21 Right, so what CRISPR does well is often described as editing, it really is damaging.
    0:03:24 It’s not really that good at precision editing.
    0:03:28 Hopefully there will be a good way in the future.
    0:03:30 And so what it does is it knocks out genes.
    0:03:34 And in this case, that’s exactly what you want, is you want to knock out the CCR5 gene.
    0:03:35 And there’s precedent for it.
    0:03:40 About up to 10% of certain parts of Europe have a double null.
    0:03:43 To double null in this case, basically, two non-functional CCR5s.
    0:03:48 And you need really both non-functional in order to be resistant to the virus.
    0:03:50 And it doesn’t make you resistant to all viruses.
    0:03:55 It doesn’t even make you resistant to all HIV viruses, but that’s not the point.
    0:03:58 It’s like a vaccine, it makes you resistant to whatever you’re vaccinated against.
    0:04:03 And analogies were made in the consenting for this between this and vaccination.
    0:04:08 There is no good vaccine, there’s no cure for HIV/AIDS.
    0:04:14 And right now, if you get it, and there are 37 million people who have been affected,
    0:04:19 if you get it, you’re doomed to a lifetime of combined antiretroviral therapy,
    0:04:24 which is not the thing that you would wish to have if you had any choice.
    0:04:24 Sure.
    0:04:28 Well, vaccines, if there did exist one, would be quite a good choice.
    0:04:32 And so this is as close as you can get to a vaccine.
    0:04:37 So I read that the double nulls for CCR5 have increased predisposition to West Nile.
    0:04:38 That is correct.
    0:04:42 So there’s a risk for almost every preventative antiretroviral therapy.
    0:04:43 And this is the risk in this case.
    0:04:47 In most populations, that’s considered a smaller medical risk.
    0:04:51 It’s obviously a case by case for populations and individuals.
    0:04:54 And there are undoubtedly other advantages and disadvantages.
    0:04:58 And I may be taking you a little bit out of context here, but I’ve heard you describe
    0:05:02 CRISPR as genetic vandalism.
    0:05:06 So do you think that that’s a good application for germline editing?
    0:05:10 Well, it’s vandalism in the sense that it can add or delete a small number of base
    0:05:16 pairs, typically, in the range of 1 to hundreds.
    0:05:22 It’s not going to do something really wacky, except it may be some incredibly low frequency.
    0:05:24 Again, no drug is without its side effects.
    0:05:28 And that’s why there’s all the fine print that accompanies all the approved drugs.
    0:05:31 So I think in this case, it is what you want.
    0:05:32 It’s exactly what you want.
    0:05:36 You want to destroy the CCR5 gene without destroying any adjacent genes.
    0:05:41 And that’s every allele that I’ve seen in the literature for CCR5, whether it’s done
    0:05:46 in adults or done in tissue culture, is what you would want.
    0:05:50 So I’ve read in this case in the Chinese CRISPR baby publication that there is some
    0:05:55 mosaicism that he might not have functionally knocked out all of the CCR5.
    0:06:00 So is there any worry that after the post-experiment that this particular child might still be
    0:06:02 at risk for HIV infection?
    0:06:08 So first of all, in the approved clinical trials on adults that have HIV/AIDS, there
    0:06:11 is a lot of mosaicism.
    0:06:13 It’s considered part of the clinical trial.
    0:06:20 And maybe as little as 20% are properly edited, meaning double nulls.
    0:06:24 That’s enough, though, because all the rest are wiped up by the virus, and then the ones
    0:06:28 that are edited dominate the T-cell population.
    0:06:29 So it’s one way of thinking about it.
    0:06:34 So it’s basically selection for the edited T-cells so you don’t develop immunosuppression.
    0:06:35 Right.
    0:06:37 So as long as there’s a fair number of properly edited ones.
    0:06:43 Now on the other hand, looking at the data, I don’t see that much evidence for mosaicism.
    0:06:49 It’s quite possible that what you see in the pre-implantation embryo when you select a
    0:06:57 few cells out of that blastocyst is not representative of the final, and the final is less mosaic,
    0:06:59 or maybe even non-mosaic.
    0:07:04 So when they talk about a baby having mosaicism in the case of the CRISPR baby, essentially
    0:07:08 what they’re referring to is that there are some cells that will have edits, and some
    0:07:10 cells that won’t.
    0:07:16 And so essentially that child may grow up to be a mosaic of two different or multiple
    0:07:17 different cell types.
    0:07:18 Correct.
    0:07:22 And the same thing I should note is true for adult gene therapies is that whether they’re
    0:07:27 done ex vivo or in vivo, it usually results in a high level of mosaicism because the delivery
    0:07:29 is inefficient.
    0:07:33 And it may even be the case that the germline has lower mosaicism.
    0:07:34 We need more data.
    0:07:35 Great.
    0:07:42 So the amount of off-target and mosaicism so far for these two babies seems to be low,
    0:07:43 but time will tell.
    0:07:49 You know, it could be that we’re just lucky the same way that the first in vitro fertilization,
    0:07:51 Louise Brown, turned out just fine.
    0:07:55 And so that greatly influenced, it shouldn’t have, I mean, it’s an N of one.
    0:07:59 We shouldn’t have all said, “Oh, IVF is perfect because we have one perfect baby.”
    0:08:03 To your referencing the test tube hysteria around the first IVF.
    0:08:11 1978, which subsided, it grew too much and it subsided too quickly based on N of one.
    0:08:15 And I think here we have an N of two, maybe an N of three, and there’s going to be a lot
    0:08:20 of attention paid to the actual outcomes rather than how we got there, hopefully.
    0:08:25 If you had been in charge of the project, would you have done CCR five or is there another
    0:08:28 different obvious application that you’d have gone after first?
    0:08:29 Very preclinical.
    0:08:33 In other words, I create technologies that’s been used by companies that I found, and they
    0:08:34 do the clinical trial.
    0:08:39 So I probably would not be doing a clinical trial at all, just to put it in context.
    0:08:44 But in terms of choice of target, I have said publicly already that targets that have been
    0:08:49 championed by the critics to the extent they champion anything, or the ones that they present
    0:08:56 as possibilities or as higher priority, although with great reservations, even for those, are
    0:09:03 things that are typical Mendelian diseases, that is to say diseases that are very severe
    0:09:11 and are predictably heritable, which are things like hemoglobinopathy, salicylium, sickle
    0:09:18 cell, cystic fibrosis, and so forth, ignoring the fact that if you’re in an IVF-PGD clinic
    0:09:25 anyway, to do your CRISPR editing of your Mendelian disease, you could just do selection
    0:09:26 for most of these things.
    0:09:33 So I think it’s kind of like they’re rationalizing their choice, which in the same sense that
    0:09:37 they might feel is rationalizing to pick a more prominent disease.
    0:09:40 But also, I think in all the examples you just cited, you would actually need to edit the
    0:09:45 gene to create function as opposed to knocking out, as was the case with CCR five.
    0:09:49 And in some sense, the critics might think that that’s attractive, that CRISPR is inappropriate
    0:09:53 at this moment because it gives us more time to think about it.
    0:09:58 But in any case, yeah, I think that we want an example of a disease that is very common,
    0:10:04 and most of the gene therapies are rare, whether editing or not, and we want something that’s
    0:10:09 very serious, and certainly HIV falls in that category.
    0:10:15 So it struck me as a plausibly justifiable choice, possibly more justifiable and something
    0:10:21 that you can avoid with genetic counseling or with PGD IVF or both.
    0:10:27 So IVF-PGD stands for In vitro fertilization with prenatal genetic diagnosis.
    0:10:32 So the diagnosis can essentially be done before you implant the embryo from an in vitro fertilization
    0:10:33 into the mother.
    0:10:39 And so by some people’s definition, that’s still kind of a lab resource rather than a
    0:10:40 baby.
    0:10:45 And those are typically used for Mendelian diseases, meaning that you can see in the
    0:10:49 parents, for example, both parents could be unaffected carriers.
    0:10:55 You can predict that 25% of their children will or their embryos in vitro fertilization
    0:10:58 could be affected with a very serious disease.
    0:11:03 So now that the gene is out of the bottle, we have the first CRISPR babies born.
    0:11:09 First of all, what was the role of ethicists in the first project in the CCR-5 Chinese
    0:11:11 CRISPR baby project?
    0:11:14 And what do you see as the role of ethicists going forward?
    0:11:19 Well so the National Academy of Sciences in the US and with participation from China and
    0:11:24 other countries in February 2017 came out with a report where they listed 10 items that
    0:11:31 would be recommendations for prerequisites for doing germline editing in children.
    0:11:38 I mean obviously you can do germline editing in animals or you can do it in cells in culture
    0:11:42 or even embryos in culture but actually in planting and having children.
    0:11:44 And a lot of these had ethical components.
    0:11:50 Many of them were very similar to what you would expect the FDA or the CFDA or the EMA
    0:11:56 to be, these are all regulatory agencies around the world, would recommend for any therapeutic
    0:11:57 clinical trial.
    0:12:03 We should all be focused on safety and efficacy and ethics and that’s what these 10 items
    0:12:06 look like for germline as well.
    0:12:10 Do you suspect or do you expect, I should say, that we’re going to see more and more
    0:12:15 of these experiments going forward or do you think that after this first one, going back
    0:12:18 to the IVF example, do you think there will be a pause?
    0:12:23 Well there probably will be something that looks like a pause but it will probably be
    0:12:25 an acceleration.
    0:12:29 So the same thing happened with the prominent DNA, there was supposedly a moratorium but
    0:12:34 during that time, I mean I was a first-hand observer, my research went faster because
    0:12:39 people were building incredible facilities for containment and they had just state-of-the-art
    0:12:42 equipment that helped everything go faster in my opinion.
    0:12:47 And I think the same thing has gone with almost every major ethical debate is it attracts
    0:12:54 attention, attracts money, whatever is ethical at the time is accelerated and then so whenever
    0:13:00 we become comfortable with it, all that acceleration clicks into place and it’s as if there’s been
    0:13:02 a steady growth.
    0:13:07 That doesn’t mean we should be incautious, on the contrary, I’m very much pro-regulation.
    0:13:14 I think that regulation is what saves us from phalidomide and Vioxx and hormone replacement
    0:13:17 therapy and so forth, long-term.
    0:13:21 So I think we need to support our regulatory agencies around the world.
    0:13:25 They are not agents of slowing things down, they’re actually agents of smoothing things
    0:13:26 out.
    0:13:28 Yeah, and I think it’s pretty clear we’re seeing that today in the regulatory environment,
    0:13:29 certainly here in the US.
    0:13:34 I mean, we’ve got the first cell therapies, the first gene therapies, the first digital
    0:13:35 therapies.
    0:13:38 It’s a pretty remarkable moment from a regulatory standpoint for a new therapy.
    0:13:41 To some extent, I think they like new technologies more than like the old ones.
    0:13:47 The old ones tend to fail because they’re so incremental that they’re no longer compared
    0:13:50 to the placebo, they’re compared to whatever they’re an increment over or whatever therapy
    0:13:57 already works and they often fail, but brand new category, monoclonal antibodies or cell
    0:14:04 therapies or gene therapies, those just like blow past and create all sorts of new improvements,
    0:14:06 traumatic improvements in safety and efficacy.
    0:14:11 So the FDA is, that’s their mandate, is to cure people, not to stop people from practicing
    0:14:12 medicine.
    0:14:18 So just to take that vein, if we look forward, what do you see as sort of the next non-incremental
    0:14:23 sort of step function change in the way we treat disease or manage disease or even diagnose
    0:14:24 disease?
    0:14:28 Well, first of all, if we started diagnosing, that would be a really big thing.
    0:14:33 It’s really, we’re as a population, even worldwide, we’re under-diagnosed.
    0:14:38 There’s a lot of very cost-effective diagnoses that partly because they’re cost-effective,
    0:14:45 they’re undervalued and the care providers are not compensated as much as some less effective
    0:14:47 but expensive medicine.
    0:14:51 So that’s one thing, diagnosis would be terrific and that’s part of preventative medicine.
    0:14:56 So we talk a lot about precision medicine, but the preventative part gets kind of swept
    0:14:57 under the rug a bit.
    0:15:01 If you look at the pie charts for a number of government agencies, including the NCI,
    0:15:09 NIH in general, is preventative is sort of in the 1 to 5% of the pie chart, but its payback
    0:15:10 is enormous.
    0:15:14 And so basically you’re saying misaligned incentives and human behavior has sort of
    0:15:17 mitigated how much prevention we actually do.
    0:15:21 That’s right, but that would be a huge breakthrough so we could do more diagnosis and more prevention.
    0:15:26 Now the ultimate diagnosis for genetics is whole genome sequencing and environmental
    0:15:30 monitoring with sequencing as well for pathogens, allergens and so forth.
    0:15:39 The therapeutic cognate of that is preventing serious Mendelian diseases that are very predictive
    0:15:44 and very often single gene or have enough of a single gene component that they’re ready
    0:15:47 for medical practice, thousands of them.
    0:15:48 And those can be prevented.
    0:15:52 We often talk about gene therapy, actually that’s a million dollar drug.
    0:15:57 It is once and done so you don’t have a lifetime of dosing, but it is expensive, we need to
    0:15:58 acknowledge that.
    0:16:00 Partly because a lot of them are rare.
    0:16:06 If you get a common gene therapy, like let’s say aging reversal or some major infectious
    0:16:11 agent that everybody wants to be vaccinated against, it’s like most infectious ages have
    0:16:16 potentially billions of customers, then that will bring the price down radically.
    0:16:22 But in addition to gene therapy, either in adults, children, fetuses or germ line, there
    0:16:28 is the option of doing IVFPGD that we already mentioned and even earlier in matchmaking.
    0:16:36 So if you never meet or fall in love with someone who is predisposed to create heavily
    0:16:43 disease, genetically diseased children, that’s very both cost effective and humane.
    0:16:45 So you’re describing 23andMe meets 10andMe.
    0:16:47 No, I am not actually.
    0:16:52 I’m describing a whole genome sequencing, which is not, there are a very small number
    0:16:56 of companies that provide whole genome sequencing because everything else, anything less than
    0:17:00 whole genome sequencing is not medically powerful enough.
    0:17:04 Anything less than that misses because you false assurance.
    0:17:09 That combined with some sort of dating that is an odd combination and possibly further
    0:17:14 combined with whoever is paying for the Mendelian costs right now, which are about a million
    0:17:18 dollars per person, doesn’t have to be gene therapy, which happens to be a million.
    0:17:21 It can be just caregiving.
    0:17:27 It adds up and somebody is paying for that, typically insurers and employment benefits
    0:17:34 and they could be saving this money if they could encourage their clients, patients to
    0:17:38 avoid falling in love, marrying and having children when they have incompatibility.
    0:17:39 Their carriers of something.
    0:17:40 And this actually works.
    0:17:48 So Dorya Sharim has eliminated significant menial disease like Tasex by practicing a
    0:17:53 version of this that probably isn’t perfectly generalizable, but there are versions that
    0:17:59 could keep a great deal of privacy and allow people to just never know whether they’re
    0:18:02 affected or not, or whether they’re carriers or not, never know if anybody else is affected,
    0:18:05 but still avoid meeting.
    0:18:09 I mean, the analog version of this was back in the day in certain communities, Jewish
    0:18:12 communities where there was disease, the rabbi would essentially replace function.
    0:18:13 That’s what Dorya Sharim was.
    0:18:14 Exactly.
    0:18:20 It was started by an individual who had five children in a row that were affected by Tasex,
    0:18:25 which is a terrible burden on the child and the family that typically died before they’re
    0:18:27 four years old and very painful.
    0:18:34 And so he correctly determined that you could do this very inexpensively and mainly.
    0:18:35 Via matchmaking.
    0:18:36 Via matchmaking.
    0:18:37 Right.
    0:18:39 So let’s take another blast back to the past.
    0:18:44 So about 10 years ago, you and I started a company in whole genome sequencing.
    0:18:45 Called Nome.
    0:18:46 Thank you.
    0:18:47 Called Nome.
    0:18:48 Not Nome.
    0:18:49 Called Nome.
    0:18:52 We used to have this constant back and forth that you thought it should be called Nome.
    0:18:53 I would call it Nome.
    0:18:54 Yeah.
    0:18:55 I thought it should be called Nome.
    0:18:56 Yeah.
    0:18:57 And this was the market test.
    0:18:59 It was the youth into me, which is incredibly frustrating.
    0:19:00 Yeah.
    0:19:01 And now I listen to you.
    0:19:02 Thank you.
    0:19:03 Like I said, no.
    0:19:04 Okay.
    0:19:08 My rejoiner on that always was, if you want to call it know me, then I want to call you
    0:19:12 Jorge Iglesias and you are never a big fan of that one.
    0:19:13 Okay.
    0:19:14 I don’t have no problem with that name.
    0:19:15 I think it’s a better name.
    0:19:16 It’s a nice name.
    0:19:17 It’s going to increase the brand.
    0:19:20 It just has more syllables, that’s all.
    0:19:22 But it just, it rolls off the tongue.
    0:19:23 Does.
    0:19:24 Yes.
    0:19:28 It basically made the bet that whole genome sequencing was important.
    0:19:32 That interpretation of that data would be relevant, that it would be meaningful.
    0:19:36 Ten years hence, there still are not many people walking around that have had their
    0:19:41 whole genomes sequenced despite the fact that the cost has now fallen arguably below $1,000
    0:19:44 or at least we’re at that $1,000 threshold.
    0:19:46 So I had two questions for you.
    0:19:52 Number one is, is the $1,000 threshold for this to be useful for everyone to get sequenced
    0:19:53 too high a dollar number?
    0:19:57 In other words, does it need to be $100 or $10?
    0:20:02 And number two, to the extent that this hasn’t happened yet, why hasn’t it happened yet if
    0:20:03 it’s not cost?
    0:20:06 I would say there’s three reasons why it hasn’t happened yet.
    0:20:10 And I’ve been living this reality for most of my career.
    0:20:15 I’m convinced that it would be valuable for the world, it costs effective medicine, preventative.
    0:20:18 And I think the three reasons are one is cost.
    0:20:20 The cost should probably be $0.
    0:20:22 And secondly, it’s privacy.
    0:20:27 We should have a convincing mechanism of people getting benefit from their genome without
    0:20:29 necessarily knowing their genome or anybody else knowing their genome.
    0:20:34 You can have something where it’s only an encrypted form, not available to anybody, including
    0:20:36 insurance and government.
    0:20:37 That’s second.
    0:20:41 And the third is most people don’t understand the value proposition.
    0:20:44 It’s either misrepresented, but by both extremes.
    0:20:48 So some people say, oh, it’s so valuable that you’re going to whip out your cell phone and
    0:20:50 look at your genome twice a day.
    0:20:54 And at the other extreme, they say, I can’t imagine ever using it.
    0:20:58 And the reality is somewhere in between, and I think the analogy is seatbelts.
    0:21:00 So seatbelts were essentially free.
    0:21:01 They were standard equipment.
    0:21:04 They were required by law that you buckle.
    0:21:09 And there were a lot of ad campaigns to get you to do so, kind of like smoking.
    0:21:15 And none of those were effective because people did, you know, the kind of ordinary math,
    0:21:19 which is, hey, I’ve got a less than 1% chance of ever using a seatbelt, ever needing one.
    0:21:21 So I’m not going to bother.
    0:21:26 And then the thing that made the difference was technology to sense the buckling and turning
    0:21:28 off an annoying sound.
    0:21:29 So that’s what made the difference.
    0:21:30 And we need an equivalent thing.
    0:21:32 It’s a public health issue.
    0:21:35 It’s not an individual health issue.
    0:21:37 So I don’t benefit from being sequenced, the collective.
    0:21:43 These people, 95, 96% will get a blank sheet.
    0:21:50 They should get a blank sheet in terms of really actionable, very serious Mendelian diseases.
    0:21:51 And that should be the expectation.
    0:21:56 Not the two extremes that you’ll use it every day, or that everybody will use it every day,
    0:21:57 or the other extreme, which is totally useless.
    0:22:04 It’s this strange thing where 1% to 4% of the population will have a very big impact
    0:22:05 on their life.
    0:22:12 And the bottom line for their care providers, millions of dollars, huge impact on the whole
    0:22:17 family, if you’re one of the unlucky 4%.
    0:22:19 And we need to get that message out there.
    0:22:24 And I think that bringing the price down to $0 and showing that it’s protectable, encrypted
    0:22:29 and so that nobody can get access to it except for things that benefit you or your family
    0:22:33 or society, that will get their attention.
    0:22:36 But it’s going to take a little bit more than that’s going to take some anecdotes.
    0:22:40 You would think that data would be better than anecdotes, but you need both.
    0:22:43 And I think it’s going to happen very soon now, because we finally have the $0 genome
    0:22:50 and the encryption, and we’re starting to get communication of this rare advantage where
    0:22:54 you’re not exempt, even though the odds are that you’re exempt, you don’t know that you’re
    0:22:57 exempt until you get your genome sequenced.
    0:22:59 So two questions for you on the three ones you’ve laid out.
    0:23:04 The first one is, in the early days of Nome, I remember when we would think about this
    0:23:10 question of security, you correctly pointed out that if you really wanted my genome,
    0:23:13 you would just wait for me to leave the room and collect it from all of the genome.
    0:23:14 Exactly.
    0:23:15 That is even more true than it was back in 2007.
    0:23:16 Right.
    0:23:18 So you collect all of this chair off this table, and you’ve got me.
    0:23:19 Got it.
    0:23:24 So why is security and privacy, is it even a meaningful thing to think about if it’s
    0:23:25 an impossible thing to achieve?
    0:23:30 Well, the point is, if it’s preventing people from getting their own genome sequenced, if
    0:23:36 they think that them seeing their own genome puts them at risk for somebody like hacking
    0:23:41 or requesting it or subpoenaing it, then yes, it’s a problem, because there is a difference
    0:23:46 between me woefully getting my genome and looking at it and somebody surreptitiously
    0:23:47 taking it.
    0:23:48 Okay?
    0:23:51 So we can pass laws that punish people for surreptitiously taking my DNA.
    0:23:56 We do have the Genetic Information Non-Discrimination Act of 2008 that is along those lines.
    0:24:00 It’s not perfect, but it shows the intention of the public.
    0:24:05 So that can kind of handle the abandoned DNA problem, and we could keep shoring that
    0:24:07 up and building up those laws.
    0:24:11 But then there’s the question, if I look at my genome, if I have my genome available
    0:24:16 in text format, unprotected, then anybody can come along and demand it, right?
    0:24:20 Insurance companies say, “I know you know it, so I want to see it.”
    0:24:24 And they can say, “I want to see it, so I can convict your brother.”
    0:24:29 And if it’s encrypted so that even you can’t hack it, then you can just say, “Sorry, it’s
    0:24:30 out of my hands.
    0:24:31 I don’t have my genome.
    0:24:33 If you want my genome, you’re going to have to steal it from me.”
    0:24:34 Right?
    0:24:35 Got it.
    0:24:36 And I think that’s where we are today, finally.
    0:24:39 By the way, you may not remember this, but we were laying out the risk factors and all
    0:24:46 of the other things for the consent form on all the things that a potential recipient
    0:24:48 of their genome data would have to think about.
    0:24:53 By far and away, my favorite one that you contributed was the potential risk that someone
    0:24:55 could plant your DNA at a crime scene.
    0:24:56 Right.
    0:24:57 Yep.
    0:24:58 High risk or low risk?
    0:25:03 So that was also in a personal genome project consent form, which started around that same
    0:25:04 time as Noam did.
    0:25:06 Is it high risk or low risk?
    0:25:14 I’d say that we’re getting more and more sophisticated at sequencing and methylation analysis.
    0:25:17 You’d have to have the whole genome now rather than back then, it might be just the CODIS
    0:25:18 parts.
    0:25:26 CODIS is just a few handful of simple sequence repeats that are used in criminal investigations
    0:25:27 like —
    0:25:28 Take forensics.
    0:25:31 Yeah, forensics and CSI type stuff.
    0:25:35 Now you’d need the whole genome because if somebody felt it was being hacked, they’d
    0:25:37 say, “Well, let’s check the whole genome.”
    0:25:39 A defense attorney could ask for the whole genome.
    0:25:42 Further, you could ask for methylation to show that it’s the right age.
    0:25:47 For example, I can have my DNA from 20 years ago, and you’d have to show — or you could
    0:25:48 check the immune status.
    0:25:53 So you could say, “Oh, does the immune status coincide with what the –” which that should
    0:25:59 be an argument for you to be constantly sequencing your immune, your blood DNA, so you can date
    0:26:01 whatever samples you’re taking.
    0:26:03 For every hack, there is a counter hack.
    0:26:08 So I think I’m glad that we’re not at that stage right at the moment, even though we
    0:26:11 predicted it back in 2005.
    0:26:16 So going back to 2005, can you describe briefly what the Personal Genome Project was?
    0:26:19 Because it was the first effort to really start to think through these issues.
    0:26:25 The Personal Genome Project was one of the first recognitions about how identifiable
    0:26:31 both your genome is and also even parts of it and your medical records.
    0:26:37 And people were starting to want to share genomic data and medical records, ideally integrated,
    0:26:43 so that you could see what an individual, what we would now call precision medicine,
    0:26:46 record would look like, right, back in 2005.
    0:26:51 And I wrote an editorial saying that this was a risk, that the data could leak out,
    0:26:55 and once it leaked out, the people could be re-identified, and all of their diseases could
    0:26:59 be determined from either the medical record or the genome or both.
    0:27:00 And this is played out.
    0:27:05 I mean, there’s many examples of millions of people being their medical records and/or
    0:27:08 their genome leaking out in various ways.
    0:27:12 And of course, now, since then, WikiLeaks has occurred, which is just an example of
    0:27:17 how they can be officially stored publicly after leaking.
    0:27:20 So I think that was what we were concerned about, and we started the Personal Genome
    0:27:25 Project so that we could get people properly consented so they knew these risks, they accepted
    0:27:26 them.
    0:27:27 And you had to take a quiz, right?
    0:27:28 Exactly.
    0:27:34 Up to that point, many of the consent forms were long, written in legalese, a lot of
    0:27:39 language protected the institution rather than the person, and you would sign them often
    0:27:43 under course of circumstances where you were afraid you weren’t going to get the best medical
    0:27:45 care if you didn’t sign it.
    0:27:50 So we added to that a simple multi-choice exam where you kind of simultaneously got
    0:27:55 educated if you didn’t get a perfect score until you got a perfect score.
    0:28:00 So it wasn’t like we wanted 90% comprehension, we wanted 100% that you knew all of the risks
    0:28:03 and all the benefits, and we had a record of that.
    0:28:06 So those were some of the key points of the Personal Genome Project, but the other key
    0:28:08 point is we really wanted to share it.
    0:28:13 Not just what a lot of people call sharing, even to this day, 13 years later, they call
    0:28:19 sharing medical data for research is really a silo that’s hard to get into.
    0:28:22 Now, unfortunately, it’s not impossible to get into, it’s not really encrypted the way
    0:28:27 you would want it to be, and so there’s a lot of potential for leakage, but it’s hard
    0:28:33 enough for regular scientists of good intention to get access to it legitimately.
    0:28:37 So we wanted something that was more like Wikipedia where you didn’t have to agree to
    0:28:42 be a co-author on a paper, you didn’t have to pay a lot of money, you literally could
    0:28:47 use it for whatever you wanted to use it for, commercial, private, teaching, whatever, just
    0:28:53 by clicking on it, and that project still exists today in many countries now with high-level
    0:28:56 enthusiasm among the participants.
    0:29:01 So you were obviously participant one, 001 of the Personal Genome Project.
    0:29:02 You’re an open book.
    0:29:06 If you go to your lab website, you have everything you’re working on, everything you’ve ever
    0:29:11 worked on, you’ve described your phenotype in detail, which I think is fascinating.
    0:29:15 Did you learn anything from having access to your own genome that you found particularly
    0:29:17 interesting or enlightening?
    0:29:21 So I didn’t expect to because I felt that I was likely to be in the 96% that would get
    0:29:23 a blank report.
    0:29:27 As it turned out, it did learn a couple of things.
    0:29:31 So one of them my family was very concerned about because I had a family history of cognitive
    0:29:36 decline was that I had no risk factors for Alzheimer’s.
    0:29:38 To this ApoE4 status.
    0:29:39 APP.
    0:29:40 Precinalin 1 and 2.
    0:29:41 Every known factor.
    0:29:46 So that was reassuring, although I try to tell people not to be reassured that there’s always
    0:29:48 something new to learn.
    0:29:54 Secondly, I’m an alpha 1 antitrypsin compound heterozygote, which just means I have two
    0:29:59 different risk factors that result in a risk for lung disease.
    0:30:02 So I should probably avoid pollution, which is probably not a bad thing for everybody
    0:30:04 to avoid and smoking.
    0:30:08 And those were the two main things that I learned.
    0:30:13 So it’s not that different from getting a blank sheet, quite frankly, but probably more
    0:30:18 importantly was having my medical records publicly available meant the hematologist
    0:30:22 gave me personal advice on my incorrect use of statin.
    0:30:26 So it turned out that I was not being properly diagnosed.
    0:30:31 Going back to where we’re under diagnosed, and I was having poor reactions of statin
    0:30:32 as well as low efficacy.
    0:30:34 It wasn’t doing its job.
    0:30:38 And so we tried a little bit of nudging them around and finally gave up when I showed and
    0:30:43 determined that a vegan diet, strict vegan diet, was enough to bring me down from almost
    0:30:46 300 to almost 200.
    0:30:52 So it’s not generic advice, it’s something that’s very personal and precision and empirical.
    0:30:55 So that was another advantage of having people look on.
    0:30:59 And then there was an advantage to the project of me being guinea pig number one.
    0:31:04 The IRB, Harvard Medical School IRB, asked me to be an institution review board.
    0:31:10 There’s sort of an ethics and protocol reviews of human subjects research.
    0:31:16 They wanted me to participate as initially the only subject, or at least part of the
    0:31:18 first 10.
    0:31:24 And that was beneficial in that when we were developing the skin biopsy for induced pleuripotent
    0:31:29 stem cells, the skin biopsy, first one we tried out in me, was ridiculously painful.
    0:31:30 I remember that.
    0:31:32 And in retrospect, it was crazy.
    0:31:39 It was like a six millimeter punch, 12 stitches, no anesthetic, or at least not in the right
    0:31:40 place.
    0:31:45 And then we switched over to a cream anesthetic, which is instead of 12 injections in the wrong
    0:31:48 place, it was cream in the right place.
    0:31:51 And then a simple bandage rather than stitches, and a one millimeter punch.
    0:31:57 So that was an example for me being eyewitness or guinea pig.
    0:32:01 I said, no, that’s not an acceptable protocol immediately.
    0:32:06 And I might not have said that if I were detached and I just said to one of the staff physicians,
    0:32:08 oh, just go do it.
    0:32:14 So that’s a summary of why sometimes it’s important for the top researcher to also
    0:32:16 be a guinea pig in the study.
    0:32:21 And I don’t think it supplies all studies, but it certainly applied to the Personal Genome
    0:32:22 Project.
    0:32:24 So switching gears to the church lab.
    0:32:28 So if you go on your website, you have a list of sort of the active projects that you’re
    0:32:29 working on.
    0:32:32 And I mean, it almost reads like screenwriters for like coming up with the next, you know,
    0:32:34 great movie.
    0:32:35 Talk to me about the church lab.
    0:32:37 How do you think about what you work on?
    0:32:41 And even one step before that, how does one get into the church lab?
    0:32:44 Because from an external standpoint, I mean, this is like Willy Wonka’s chocolate factory
    0:32:45 for science.
    0:32:49 So what do you look for in incoming students for the church lab?
    0:32:50 And then let’s go from there.
    0:32:51 Yeah.
    0:32:55 So a lot of it looks like science fiction and most people would run away from that, not
    0:32:56 run towards it.
    0:33:01 And they did when I was starting out, but now we have a track record, same level of creativity
    0:33:03 and risk taking.
    0:33:08 But actually many of the things we do are they look hard from the outside, but from
    0:33:12 the inside, they look like they’re low hanging fruit and they happen way ahead of schedule.
    0:33:18 So for example, things that did look like science fiction were fluorescent next generation
    0:33:20 sequencing and Nanopore sequencing.
    0:33:24 Both of those were wacky when I started them in the 1980s.
    0:33:27 And the whole idea that you could bring down the price of the genome from three billion
    0:33:33 down to now sub thousand dollars also seemed science fiction.
    0:33:36 But now that we’ve done it, now it becomes a beacon for people to say, Oh, whoever did
    0:33:38 that, we should go there.
    0:33:43 And if, oh, if at the same lab also helped bring in multiple ways of doing genome editing,
    0:33:48 including CRISPR, if you just do one, you could be lucky, but if you do several different
    0:33:52 ways of doing next-gen sequencing, several different ways of doing editing, then that’s
    0:33:55 an attractant to get in.
    0:33:56 Self selection is another major filter.
    0:34:00 We do such quirky stuff that people don’t even bother to apply unless they’re kind of
    0:34:02 already on our wavelength.
    0:34:06 So then the biggest filter for me, and I tell us in the first interview, the first conversation
    0:34:09 I have is we’re looking for people that are nice.
    0:34:11 We’re not necessarily looking for geniuses.
    0:34:13 We got plenty of geniuses.
    0:34:15 We’re looking for people that are nice.
    0:34:16 And how does one demonstrate niceness?
    0:34:19 Well, you know, I think, to some extent, just having that conversation, if they want to
    0:34:21 be cutthroat, they’re not going to come back.
    0:34:26 If they’re kind of sitting on the fence, then they’re going to rise to the occasion.
    0:34:31 They’re going to be influenced by that conversation and by all the people that have already passed
    0:34:33 through that filter that are in the lab.
    0:34:39 And you create a culture where you try not to compete with other labs if you can avoid
    0:34:40 it.
    0:34:44 Sometimes it’s unavoidable, but you can avoid it by inviting them to work with them, leaving
    0:34:49 alone fields where there’s plenty of momentum and a lack of interest in collaboration, making
    0:34:53 sure there’s a diverse enough set of ideas going on the lab so that everybody gets to
    0:34:59 leave with a subset of those ideas as a parting gift or continue to collaborate if they want
    0:35:01 to as long as they want to.
    0:35:06 So I think you build up this momentum of knocking off things that look like science fiction,
    0:35:12 turning them into science fact and create a culture of ability to fail and to jump back
    0:35:15 and to be nice to your colleagues within and outside the lab.
    0:35:19 So if I go through the list of things that you’re working on, it’s a pretty broad array
    0:35:20 of things.
    0:35:25 So you are crispering dogs to keep them young, you are crispering pig organs or had been
    0:35:30 working on editing pig organs to make them useful for transplantation.
    0:35:34 And then you run the other end of the spectrum, you’re re-engineering biology to create a
    0:35:39 mirror universe of things that would be essentially immune to all known viruses or microbes.
    0:35:41 How do you pick the projects?
    0:35:44 What is it about what’s in the water in the, well, in the Iglesias lab, formerly known
    0:35:45 as the church lab?
    0:35:52 Like, what’s in the water that gets this lab to produce so many startups and spinouts?
    0:35:56 What is that entrepreneurial energy that’s sort of been fostered and created here?
    0:35:57 Right.
    0:36:02 It may look like an averse set of projects, but they’re actually have common thread that
    0:36:08 is surprisingly focused, meaning most people wouldn’t fit in this lab because we’re sort
    0:36:12 of into radical transformative technologies, not incremental.
    0:36:17 A lot of labs don’t even want to touch technology until it’s working in a company.
    0:36:23 We work years before that company and we create the company and then the company has another
    0:36:29 few years before it’s sufficiently worked out that it can be adopted by a technology
    0:36:32 adoption lab, which is before most biologists.
    0:36:37 So anyway, that’s one thing that we’re a little bit on the edge and it’s an acquired taste
    0:36:39 or maybe even a rare taste.
    0:36:41 What’s an idea that was pitched to you that you said, “Wow, that’s too crazy?”
    0:36:43 Well, I’m usually the one pitching the crazy ideas.
    0:36:47 I mean, not to say that we don’t have a lot of creativity in the lab.
    0:36:48 That’s pretty rare.
    0:36:51 In fact, we’ve sort of banned the word impossible.
    0:36:55 We certainly try to behave ethically, but I think that many things, there’s a technological
    0:36:59 solution to some of the ethical components, not all of them.
    0:37:03 And we try to explore creative solutions to ethical problems.
    0:37:06 Personal Genome Project was one of those creative solutions.
    0:37:10 Surveillance for synthetic biology is another one that I suggested in 2004.
    0:37:16 Biocontainment using recoding is a way that we can make any organism resistant to all
    0:37:19 viruses and horizontal transfer.
    0:37:20 Most of these things now work.
    0:37:21 And many of these things are now companies.
    0:37:22 That’s correct.
    0:37:27 And their foundation was some sort of safety ethics component to the company.
    0:37:30 And part of the secret sauce is hidden in plain view.
    0:37:31 Like you say, we’re quite transparent.
    0:37:35 We can keep other people’s secrets, but our own, we try to get people to adopt them.
    0:37:39 Part of the thing that we do that is, instead of saying failure is not an option, which
    0:37:42 was one of the Apollo slogans, we say, “Fail fast.
    0:37:44 Just pick yourself up quickly.
    0:37:46 Have a bunch of things going in parallel.
    0:37:50 Find the low-hanging fruit empirically as well as theoretically.”
    0:37:54 And just a lot of things people reject too easily.
    0:37:57 They either don’t think of it at all, or they think about and reject it.
    0:38:02 And so if we see something that looks a little hard, we’ll put it up on the shelf or in plain
    0:38:06 view so we can keep reminding ourselves whenever a new technology makes that possible, we pull
    0:38:08 it back off the shelf and we do it.
    0:38:12 And so we have that culture of constantly reevaluating things that are on the edge of
    0:38:14 science fiction.
    0:38:18 Do you recruit entrepreneurs that happen to be scientists, or are you turning scientists
    0:38:19 into entrepreneurs?
    0:38:26 I mainly recruit people who are multilingual, multidisciplinary, because I found it’s hard
    0:38:31 to build a multidisciplinary team from disciplinarians.
    0:38:36 You have to have a lot of people who already have done two things, and even if you get two
    0:38:39 people who have done two things each, they don’t have to overlap, but they’ve done enough
    0:38:42 translation that they can start talking to each other.
    0:38:46 And if you have enough of those multidisciplinary individuals, then you can sprinkle in a few
    0:38:49 disciplinarians and you have an amazing team.
    0:38:53 So the church lab, you were pioneers in sequencing, so reading DNA.
    0:38:58 You were pioneers in CRISPR, so writing DNA.
    0:38:59 What comes next?
    0:39:02 Well, so there’s three-dimensional structure of living organisms, so we’d really like
    0:39:08 to know every voxel, every volume, element of every pixel in the body of an embryo or
    0:39:09 a larger section of tissue.
    0:39:13 We’d like to know every molecule here, and we now have tools for doing DNA, RNA, and
    0:39:17 protein in 3D at super resolution, finally.
    0:39:18 So that’s one thing.
    0:39:22 We would like to be able to do higher levels of multiplexing in the terms of editing synthesis
    0:39:23 of genomes.
    0:39:27 So some people call it, we call this GP Right, or Genome Project Right, but it could just
    0:39:28 be heavy editing.
    0:39:34 So we’ve set the record of 62 edits in the pigs, and we now have, we have 10,000 edits
    0:39:35 in a single cell.
    0:39:36 That’s unbelievable.
    0:39:38 So it goes from two to 62 to 10,000.
    0:39:39 And we want uses for each of these things.
    0:39:45 So each of these projects, we have a driving societal benefit for each, and we have a driving
    0:39:50 technology where we say, we don’t just want a factor of 1.5, we want a factor of a million
    0:39:51 or 10 million.
    0:39:58 And so that’s what pushes each of these projects is that triple criteria, which is cool, basic
    0:40:04 science, philosophically interesting, technological factors of a million, and societal benefit.
    0:40:08 Last question, 10 years from now, or just looking forward into the future.
    0:40:11 Do we get the Neanderthal baby, or do we get the mammoth calf first?
    0:40:16 Well, we never really said that we were going to a Neanderthal baby.
    0:40:20 I mean, there’s a response to a journalist, whether it was technically possible, but nobody
    0:40:21 has articulated a reason to do it.
    0:40:26 But for the mammoth, there are lots of reasons, both for the environment and for enriching
    0:40:29 the diversity of a living endangered species.
    0:40:34 So this is not about de-extinction, this is about making hybrids, and many of the species
    0:40:40 are already hybrids of multiple species, but now we can have the benefit of synthetic genes
    0:40:41 and ancient genes.
    0:40:42 Great.
    0:40:43 Well, thank you, George.
    0:40:44 Thank you for making time.
    0:40:45 It was a real pleasure.

    with George Church (@geochurch) and Jorge Conde (@JorgeCondeBio)

    Renowned scientist George Church is known for his groundbreaking work and methods used for the first genome sequence, and for his work in genome editing, writing & recoding — in fact, Church’s innovations have become an essential building block for most of the DNA sequencing methods and companies we see today. In this conversation, a16z bio general partner Jorge Conde — who also founded a company with Church out of the George Church Lab — take us on a wild journey into the scientist’s mind and work, starting with what the leading pioneer in the space makes of where we are today with CRISPR (especially given recent news about CRISPR babies in China), to the broader implications of all of this on a cultural level, and finally to what it really takes to go from science fiction, to lab, to reality.

  • a16z Podcast: Capitalizing on an Autonomous Vehicle Future

    AI transcript
    0:00:06 Hi everyone, welcome to the A6NZ Podcast. I’m Sonal. Today we’re continuing our series
    0:00:12 on consumer tech trends with an episode that pulse checks the state of autonomy in 2019.
    0:00:17 Where are we with autonomous vehicles right now? We also share some clarity on what levels
    0:00:22 of autonomy means there, including touching on regulatory aspects, and also discuss quite
    0:00:27 frankly capitalism, what cars mean nationalistically, and what it will take to bridge the worlds
    0:00:33 of Silicon Valley and Detroit, which is why our special guests are Kazer Yunus, former
    0:00:39 COO at Y Combinator and co-founder and CEO of Applied Intuition, and Peter Ludwig, CTO
    0:00:44 at Applied Intuition, which builds software for the autonomous vehicle industry. Throughout
    0:00:49 the discussion, we thread the analogy of mobile to autonomous vehicles, where it applies and
    0:00:55 where it breaks down. Speaking of, be sure to also check out a6nz.com/autonomy for posts,
    0:01:01 decks, and videos from Benedict Evans, Frank Chen, and others. But this conversation begins
    0:01:07 by cutting through the hype on whether autonomous vehicles are coming soon or not.
    0:01:12 It’s interesting. You can kind of read publications and within a three-month period you’ll hear.
    0:01:17 We’re in the early days, the hype site we’re in, the trough of despair, disillusionment,
    0:01:20 I think it’s called, right, the Gardner hype cycle.
    0:01:22 Yeah, you have pessimism. It’s kind of all over the board.
    0:01:24 And then you have people saying it’s here tomorrow.
    0:01:29 Yeah, exactly. And I think probably a good analogy to think about where we are specifically
    0:01:35 is that I like to use is where mobile was in kind of roughly 2005. What we consider
    0:01:38 to be the modern smartphone isn’t really there because you’re like, oh, look at this
    0:01:42 Motorola Razer. It’s not that powerful. And I can kind of extrapolate that maybe this
    0:01:47 Blackberry will be cheaper, but it’s very hard to really extrapolate. And so being even
    0:01:53 more specific, if you look at kind of 2010, 2011, 2012, mobile engineers highly coveted
    0:01:58 in Silicon Valley. I had a mobile company. My last startup was a messaging company,
    0:02:02 and that was kind of the bleeding heart of Silicon Valley, and that was the next wave.
    0:02:05 You kind of have a lot of that right now in autonomy where autonomous vehicle engineers,
    0:02:09 roboticists are highly valued, highly coveted.
    0:02:14 I mean, didn’t Uber or Waymo suck up the entire CMU robotics department at one point?
    0:02:18 Yeah, exactly. And that’s happened multiple times. These companies like May Mobility who
    0:02:24 basically are the U of M lab. You have a voyage who came out of Udacity. And so, yeah, that’s
    0:02:28 happening left and right. If you take that mobile analogy though, and then you think,
    0:02:34 well, 2010, there’s 11, there’s excitement. Just a few years later, 2015, 2016, nobody’s
    0:02:40 writing Objective C. These waves go really, really fast. And I think a good kind of adage,
    0:02:44 I think it was Bill Gates who said this, “In two years, nothing looks different, but every
    0:02:48 10 years, things are dramatically different.” So if we look back at 2017, autonomy doesn’t
    0:02:53 look that much different. The players are generally the same. But I think 10 years from
    0:02:57 now, autonomy would be very, very different. Insofar as it might even be a commodity.
    0:02:59 Interesting. That’s kind of controversial.
    0:03:03 I think there will be a lot of parallels as well on the hardware front as well as the
    0:03:08 software front, looking back at mobile. A modern mobile phone has GPS and an inertial
    0:03:12 measurement unit has all these advanced sensors that, prior to mobile becoming big, were very
    0:03:16 expensive electronics that were only present in potentially military systems.
    0:03:22 Right. Chris Anderson calls these components the peace dividends of the smartphone wars.
    0:03:26 This idea that essentially all the supply chains and all that competition and the commodification
    0:03:30 actually created this rich and thriving ecosystem of all these commoditized parts that can now
    0:03:32 be recombined and deployed in many ways.
    0:03:35 Exactly. And today, we’re just at the beginning of that for automotive sensors and autonomy.
    0:03:39 Yeah. The real miracle of, I don’t want to get too philosophical with capitalism, frankly,
    0:03:46 philosophy, go for it. This is the, not the engineer in me, this is the MBA in me speaking.
    0:03:52 The real miracle of capitalism is, I mean, there are all of these things that are made
    0:03:58 much, much better, much, much cheaper, that almost are the rails in which these industries
    0:04:04 lie on. And I think, even if you’re sitting in 2012, I don’t think anybody had the, “Aha,
    0:04:09 I can’t believe it. The mobile era has arrived,” exclamation mark. And people, when we talk
    0:04:15 about autonomy, they almost want a declarative event, a Eureka moment, where autonomy is
    0:04:19 suddenly unloaded into the masses. And then you look at mobile, that didn’t ever happen.
    0:04:23 You just remember, one day you decided, “I’m going to find and get that iPhone.” In 2007,
    0:04:28 I was at Harvard at the time, and I remember one of my buddies getting a phone, and I said,
    0:04:31 “Oh, what do you, what do you think of this iPhone thing?” And he goes, “Ah, it’s kind
    0:04:34 of like a toy.” Well, you know, Chris Dixon says this at ACC a lot.
    0:04:37 The next big thing we’ll start out as a toy, which he’s modeling that off-crate Christians
    0:04:41 and disruption theory. Yeah, who’s an HBS professor, bringing a full circle, right?
    0:04:45 Exactly, which is essentially that the innovations happen at the lower end, or the underserved
    0:04:49 end of the market, before they hit the mainstream, and the kind of tips enabled by some kind
    0:04:57 of enabling technology underneath it. Yeah. And so this type of incremental kind of revolution
    0:05:02 or incremental changes that one day bring to you a product, you know, even if you take
    0:05:07 the iPhone, the iPhone rests on hundreds of companies and thousands and thousands of
    0:05:12 innovations, and they’re not just in, you know, the screen. No, it’s an entire ecosystem.
    0:05:17 It’s the store, the payment processing, all the way down to, you know, the analytics for
    0:05:20 apps. The broadband and the connectivity. I mean, that’s actually the missing piece
    0:05:23 for a lot of continuing installation in the mobile phase.
    0:05:29 There’s so much, exactly. I think there are these statements made that, you know, the
    0:05:36 path to autonomy is far, far away. It is better to start autonomy company today in 2019 than
    0:05:37 ever before.
    0:05:40 So I want to ask a few questions on this. So the first thing is the kind of theme of
    0:05:46 what you’re saying, and I buy this, is that, you know, innovations, they seem incremental
    0:05:51 at the time, and then they kind of tip to where they accelerate very fast. And there’s
    0:05:57 some kind of combo of the two, where the iPhone was like 20, 30 years in the making. But then
    0:06:02 I would also argue that there is, well, there may not be a discrete specific single event.
    0:06:07 It is an accumulation. There is still a quote, iPhone moment in every industry where that
    0:06:13 industry sort of mainstreams, and you really then begin to see and experience the potential
    0:06:18 even if it does start off as a toy. So my first question is for autonomy, how far away
    0:06:22 do you think we are? Not just in terms of time, but steps towards that quote, iPhone
    0:06:23 moment.
    0:06:28 So let’s define the iPhone moment first. You know, I think it was Steve Jobs who said,
    0:06:32 you know, the ’60s really happened in the ’70s, and the iPhone moment really happened
    0:06:40 in like 2012, 2013. Right? The iPhone moment in my mind is when you have, you know, frankly,
    0:06:47 the 12 or 24-month period where Instagram, Snapchat, Uber, and WhatsApp are all created,
    0:06:51 and they all are created in a roughly pretty tight time bound. That’s the iPhone moment
    0:06:52 in my mind.
    0:06:56 So you’re really saying the app layer where people are really using things.
    0:07:01 I think that’s what generally the public thinks about it. Now, I think probably the more specific
    0:07:06 moment is the announcement of the iPhone. But if you look back, the announcement of
    0:07:09 the iPhone is met with skepticism.
    0:07:10 We forget that now in hindsight.
    0:07:14 There’s that famous video, I think, of Steve Ballmer talking about how great Windows Mobile
    0:07:17 is in comparison to iPhone because it has so many more features.
    0:07:18 Oh, I forgot that.
    0:07:23 Blackberry was like, well, no way, this is going to be actually a real thing. Again,
    0:07:28 the gimmick, the toy. So if you take the iPhone moment as a 2007, we’ve already had that.
    0:07:32 That’s the Waymo shuttles. People are like, wow, these things can only go during the day.
    0:07:36 That’s not very useful. I don’t live in Arizona. So what the general public, though, will consider
    0:07:41 the autonomy moment is when you meet somebody who doesn’t live in Silicon Valley, doesn’t
    0:07:46 work in technology, and they’ve had an autonomous ride. Maybe it’s on college campuses. Maybe
    0:07:50 it’s an airport shuttle. Maybe some goods appear at their house with an autonomous robot.
    0:07:54 That’s when you’re seeing the penetration of the market into areas which are far beyond
    0:07:56 the early adopters or something like that.
    0:07:59 I mean, one could argue that that, to your point, in terms of defining what the iPhone
    0:08:06 moment is, is not the moment. It’s actually the experience of the iPhone. It’s the applications,
    0:08:11 the iPhone phenomenon even. So that’s really what we’re talking about here. So then on
    0:08:16 that front, where do you guys think we are? How far are we from there?
    0:08:23 So we have shuttles already. This is another, I think, mischaracterization or classification
    0:08:28 of autonomy. It’s almost always, excuse me, thought as robo-taxis. And autonomy is actually
    0:08:34 much more the adage that anything that moves will one day be autonomous. We blew that very
    0:08:40 deeply. And so the point being is they’ll come in these little waves. And each of those
    0:08:46 are different. The robo-taxi wave is kind of a bit orthogonal to the shuttles wave,
    0:08:52 which is a real thing, which is campus shuttles, retirement communities. So those are different,
    0:08:56 which is orthogonal to the self-driving truck wave, which is orthogonal to the, I would
    0:08:59 say, the warehouse robots.
    0:09:01 Why do you think all of these are orthogonal to each other? One would argue that they’re
    0:09:07 the same underlying kind of roboticization, automation. So why are they orthogonal in your
    0:09:08 taxonomy and worldview?
    0:09:12 There are many similar technologies that are shared across the different verticals, but
    0:09:16 there is a lot of domain-specific work that’s still done to make the system actually production
    0:09:23 worthy. For example, John Deere has had a production semi-autonomous tractor/trailer system for harvesting
    0:09:27 crops for more than a decade. As these systems become more and more sophisticated and more
    0:09:31 autonomous to the point where there’s no human in the loop, there is a lot of engineering
    0:09:34 effort that sort of goes in that last 10% to get to that production quality.
    0:09:38 Yeah, that’s what people always talk about is that sort of last 10%, that last mile, that
    0:09:43 you get the 80%, the 99%, but then you have this percentage left, which is quote all the
    0:09:47 edge cases and all the things that people are trying to tackle. There are levels out
    0:09:51 there for how people describe these things. And so Elon Musk will make a claim about Teslas
    0:09:55 and people will say, “Well, they can’t handle all these edge cases,” etc. So in this state
    0:10:01 of autonomy 2019, where are we on the levels of autonomy? Can you quickly break down that
    0:10:02 taxonomy for our listeners?
    0:10:06 Sure, so going through the levels just one by one. So level zero is where most production
    0:10:11 vehicles are today. And so this would be a car that perhaps has anti-lock brakes and
    0:10:16 traction control, some version of electronic stability control. But the systems are all
    0:10:22 fairly done in a sense that they’re not necessarily seeing the world in any way. Level one system
    0:10:27 will mean that there’s some level of automation. So adaptive cruise control is an example of
    0:10:31 a level one system where typically there’s a radar that’s seeing the vehicles in front
    0:10:35 of you on the road and then the vehicle is able to accelerate and apply the brakes automatically.
    0:10:39 Level two is where things get pretty interesting. That’s where you typically have a combination
    0:10:44 of a lane-keep system with an adaptive cruise system. So for example, the Tesla autopilot
    0:10:49 system is a level two system. It’s able to maintain its own lane safely on the highway.
    0:10:54 And right now the trend in production systems is automakers are trying to go to what they’re
    0:10:59 calling level two plus, which is taking these level two sort of lane-keep plus adaptive
    0:11:05 cruise systems, and they’re adding on functionality for automatically taking freeway interchanges.
    0:11:09 And so if you can automatically take an exit and then perhaps automatically merge into freeway,
    0:11:12 while the human is still behind the wheel and paying attention, that’s called a level
    0:11:18 two plus system. That’s a level two plus. Exactly. And so major vendors, for example,
    0:11:23 Mobileye, they are now marketing their level two plus systems to OEMs. Level three is sort
    0:11:30 of a bit of a dubious classification where it’s essentially saying that the user should
    0:11:36 be able to not pay attention, and the system should be able to alert them when they need
    0:11:39 to take over. So it’s kind of like a passive driver, a passive human in the loop, not an
    0:11:44 active human in the loop. Exactly. The problem with that classification though is it sort
    0:11:49 of breaks down at the technical detail level. There are lots of situations where dangerous
    0:11:53 things can occur where the system wouldn’t necessarily be able to warn the driver ahead
    0:11:58 of time. Within the industry, there’s been hesitation to use that actual classification
    0:12:02 of level three. And that’s where really the level two plus classification comes from.
    0:12:06 Right. It’s a funny little distinction, but I get it. It’s almost like it’s like one,
    0:12:11 two, three, four, five, and then you have like three in the middle of this weird blurry pivot
    0:12:16 to quote true autonomy. Exactly. And I think I’ve seen some demos of systems that were
    0:12:22 purported to be level three, but actually then in the demos, there were events that
    0:12:25 required the driver to take over immediately. So that’s not really a level three. That’s
    0:12:29 really a level two system. And then when you get to level four, that’s really where we’re
    0:12:35 talking about these fully autonomous robotaxies that have some geographic fence. So for example,
    0:12:39 the Waymo pilot in Arizona, that’s a level four system where there’s fully autonomous
    0:12:43 vehicles, but only within a certain geographic region. So the geofencing is just like the
    0:12:48 physical location of how far it can operate in. So generally, there’s what’s called an
    0:12:54 ODD and operational design domain. And that’s the set of capabilities that the car has.
    0:13:02 And so as long as the car is within the region of the world where it knows based on the engineers
    0:13:05 who worked on the system, where they have good confidence that it’s able to handle all the
    0:13:09 situations that can occur, that’s considered within the ODD. And oftentimes that also has
    0:13:14 to do with the mapping system that’s on the vehicle. And the weather and time of day.
    0:13:18 Is this by the way also where like a lot of these cart robots and delivery robots sit
    0:13:22 because they’re only delivering on campuses and constrained spaces? Does that count as
    0:13:23 level four?
    0:13:28 That’s absolutely a level four system. Because for those, there’s no human operator typically.
    0:13:31 And so it is a level four system within the ODD of the robot.
    0:13:34 And so level four is fully autonomous in that there is no human in the loop. Or at least
    0:13:39 is a human offsite, like not in the car, but maybe monitoring feeds.
    0:13:46 So technically, you can have a human in a loop, but the system needs to be able to safely
    0:13:50 handle any situation that it can be in for it to be considered level four. And so that
    0:13:54 might entail the vehicle pulling off to the side of the road, waiting for a human to do
    0:13:57 something. But typically, most of the systems that are considered level four operate the
    0:14:02 vast majority of the time fully autonomously. And then the very last level is level five,
    0:14:08 which is more of an idea than a reality. It’s the notion that there could be a vehicle that
    0:14:12 is able to drive autonomously in all conditions where a human would be able to operate that
    0:14:18 vehicle. And the truth is in the industry, no one is even close to that particular goal.
    0:14:19 So that’s further off.
    0:14:20 That’s quite a bit further off.
    0:14:21 Yeah.
    0:14:23 Okay. So what we’re talking about here when we’re talking about autonomy in this context
    0:14:27 of this podcast, you guys are actually focusing more on level four.
    0:14:31 We fundamentally believe that the tools that you’re using to develop your level two systems
    0:14:35 should be actually the same tools that you use for three and four. And if you look at
    0:14:40 kind of the tooling used to develop these systems, historically the tooling for level
    0:14:46 two system, what Peter mentioned earlier, LCC and ACC lane keep and adaptive cruise control,
    0:14:51 those were more hardware focused tools. And so they would, the quote unquote simulators
    0:14:56 were trying to spoof the hardware that is actually controlling the system. So the radar
    0:15:03 or the camera system, they’re literally tools where you actually point the camera that would
    0:15:08 be sitting in a car in front of like a monitor. That’s the quote unquote simulation. Now the
    0:15:13 fundamental differences you go up the levels is there’s a proliferation of scenarios. There’s
    0:15:16 a finite number of scenarios when you’re just going down the highway trying to keep a lane
    0:15:21 and a certain distance when you’re in an intersection with, you know, four lane intersection with
    0:15:25 multiple agents, all those agents can behave in many, many different ways. And the vehicle
    0:15:31 needs to be able to understand and then navigate in that environment. And so we build tools
    0:15:35 that not only start with a level two but then take, you know, take development all the way
    0:15:41 to level four. Interesting. So you drew the analogy earlier about the mobile analogy,
    0:15:43 but where does that apply? And where does that fall apart? Because the one, a couple
    0:15:48 of differences, all right, I would argue here are one that with mobile, we knew there would
    0:15:52 be some application, but there’s been a lot of second and third order, you know, applications
    0:15:56 that no one could have predicted or maybe would not have known that selfies would be
    0:16:00 such a big deal or social would be so, you know, powerful. They might have thought it
    0:16:06 might, transactions, commerce, I think people predicted. So that’s one thing. So with autonomy,
    0:16:09 it feels like it’s the other way around where actually I think people do know what a lot
    0:16:12 of these things could be. Of course, there’ll be second and third order effects. One of
    0:16:16 our partners Frank Chen did a whole series on the, you know, second order effects of
    0:16:17 autonomy.
    0:16:18 Real estate. Yeah, exactly.
    0:16:22 Insurance. How does it change? You know, infrastructure. I didn’t op-ed when I was at Wired on folks
    0:16:25 from Autodesk that we’re thinking about the future of infrastructure because you have
    0:16:26 cars out there today.
    0:16:28 Exactly. So we have an analog.
    0:16:32 You have an analog, which mobile, you had computers, but they’re kind of fundamentally
    0:16:33 different.
    0:16:35 People didn’t even believe that they could even handle the constraints in this way because
    0:16:39 that completely changes the design. And here we are talking about cars still look like
    0:16:44 cars for the most part. And yeah, Google’s cars could be a little Kauai-like and cutesy
    0:16:47 and Waymo’s and all the other ones have different looks and feels, but overall, they look like
    0:16:48 cars.
    0:16:50 I think that’s where we’re getting to the edge. The interesting stuff happens beyond
    0:16:58 that we can draw the Instagram analogy now because we’re in 2019 and not 2005. In 2029
    0:17:02 or 2039, we’ll be able to say, well, it was actually in hindsight, it was so obvious that
    0:17:07 there’d be people who are living maybe in autonomy or some more unique and crazy things or implications
    0:17:11 that we just don’t have right now. I think sci-fi, I’m a big fan of sci-fi. And I think
    0:17:17 our imagination only goes so far and there will without a doubt be autonomy applications,
    0:17:18 which we’re just not thinking of.
    0:17:19 I agree.
    0:17:22 I think it was in the sci-fi world, I think it was William Gibson, I can’t remember who
    0:17:25 said that quote about, you know, don’t predict the car of the future, predict the traffic
    0:17:27 jam of the future or whatever that is.
    0:17:32 Or the iRobots scene, right, where I think Will Smith jumps in and he says, I want to
    0:17:35 drive this manually. So are you crazy? Are you going to drive this manually? Like that
    0:17:44 will become a norm. We always get caught up of will that be 2025, 2029, 2035, 2045? I’m
    0:17:48 less concerned about the preciseness of when that date will come, but that will happen.
    0:17:49 Yeah. You’re just saying it’s inevitable.
    0:17:54 It’s inevitable because of the kind of the three prongs of, you know, of new products,
    0:17:58 which is cost convenience and safety. And guess what autonomy gives you all three of
    0:18:02 those things. It’s cheaper, it’s safer, and it’s more convenient.
    0:18:06 And safer in the sense of accidents overall, right now, focus on the outlier incidents,
    0:18:09 which are real and we have to worry about them, but we’re not there yet.
    0:18:14 Exactly. I mean, again, the mobile analogy is relevant here. In 2005, you’d see those
    0:18:18 bumper stickers, you know, get off your phone. And now if you get in the car and somebody
    0:18:22 is in your phone, there’s like, what are you crazy? How are you? It’s like the opposite
    0:18:26 because it’s mapping and all these other things that you wouldn’t have thought of when you
    0:18:27 had the Motorola Razer.
    0:18:30 Well, since we’re talking about right now, and I agree that we don’t know what we don’t
    0:18:35 know, who are the players in the ecosystem right now? Like I can guess some of the obvious
    0:18:41 ones like the manufacturers of cars, the mapping companies, the mobilize that, you know, supply
    0:18:45 components and sensors, like how would you break down the taxonomy of the players?
    0:18:50 I think the automotive industry is a good analog to some degree of what I think the
    0:18:55 autonomy industry will be. You’ll have end consumer facing companies who will have brands
    0:19:00 that interface with the consumer. Now, whether those are ride sharing companies, AV providers
    0:19:05 or the continue to be the BMW or the Tesla’s, I think that’s up for debate. Then you’ll
    0:19:10 have folks who are supplying services. Right now in the automotive business services
    0:19:15 quote unquote are the dealer services. But in the autonomy world, we always talk about
    0:19:19 and is the emergence of the software car. And so in the software car, those services
    0:19:24 are much more, they look like kind of your phone. I think that seems fairly obvious because
    0:19:29 you see some of those already. CarPlay and Android Auto are early indications of that.
    0:19:33 And then you have the thing that you can call the infrastructure companies. Just like you
    0:19:38 have in phones and in the web, there’s this, you know, every time you go to San Jose, you
    0:19:43 see these office parks of companies you’ve never heard of. And you wonder, why do they
    0:19:48 have 10 glass buildings? Yeah, totally. And they’ll be those companies and they’ll exist
    0:19:53 in automotive as they exist right now. They’re, I mean, people, you know, Forci and Magna,
    0:19:57 these are becoming more known in the valley. When I worked at Bosch before, Bosch was unknown
    0:20:02 just a few years ago. And it’s finally now because of autonomy, Bosch is like a relevant
    0:20:07 name. And so I think the ecosystem will be like that. Each of the things that you have
    0:20:12 in mobile and web or more accurately automotive will continue to exist just in different shapes
    0:20:16 and shapes and forms because the change is pretty significant.
    0:20:19 What we’re talking about autonomy, the human driver becoming a software product, but you
    0:20:23 also have the internal combustion engine becoming an electric drivetrain.
    0:20:27 And so an electric drivetrain, for example, that doesn’t just impact the propulsion system,
    0:20:31 but it actually impacts every other component in the vehicle. For example, the cooling system,
    0:20:35 an air conditioner, that’s on a typical gas car is going to be different from an air conditioner
    0:20:37 system that’s on, it’s on an electric car.
    0:20:43 Yeah. I mean, I have a Prius, which is nowhere near autonomous, but it is electronic partially.
    0:20:47 And I have to say, it was like a huge like mindset chef for me to even realize like,
    0:20:51 oh, all those tips about how to check your coolant and open your hood in case of an emergency
    0:20:56 before triple A comes like, they don’t apply anymore. The mere fact of pushing a button
    0:20:59 to turn it on instead of using a key, like, I mean, those are really mundane examples,
    0:21:03 but it’s an example of what you’re talking about, which is like a changes everything.
    0:21:04 Things you don’t even think about.
    0:21:06 All these great revolutions are very mundane.
    0:21:09 Yes. I like that concept, actually, because I think about that even in terms of self-improvement
    0:21:13 in your life. Like it’s always like at the mundane level that the real shit happens.
    0:21:18 Yeah. Day to day, nothing looks different, but when you reflect, you know, five, 10 years,
    0:21:20 it’s pretty significant.
    0:21:26 I think in front of the old and new and zooming into just autonomy, you have this rich universe
    0:21:31 of companies now that are either form forming or are quite mature, that are doing individual
    0:21:35 components. So you have sensor companies that Peter mentioned earlier, you have mapping
    0:21:39 companies, you have companies like us, infrastructure companies.
    0:21:42 Do you guys would categorize yourself as infrastructure?
    0:21:46 Yeah. I think that’s probably the most accurate term. What’s different about simulation in
    0:21:51 the past versus simulation today, is simulation in the past was usually used to build hardware
    0:21:55 products and we’re using simulation to build a software product.
    0:21:57 That’s actually really interesting. Let’s pause on that for a moment. I love talking
    0:22:00 about simulation on this podcast, actually, in general, because to me, to your earlier
    0:22:06 point about virtual worlds, it reminds me of one of my old edities concepts of mirror
    0:22:10 worlds, David Galerinter. And this idea that you can essentially turn everything into something
    0:22:15 that can be in a virtual system. And that is, I think, what you mean by virtual world
    0:22:19 as opposed to quote, you know, VR virtual world like only immersive. And so this idea
    0:22:25 that you can essentially softwareify everything, that’s pretty significant. So that swap that
    0:22:28 you’re talking about that before we would use simulation to build hardware, now we’re
    0:22:32 using simulation to build software. Let’s talk a little bit more about that.
    0:22:37 Yeah. Simulation is not new to automotive or aerospace. These methodologies that existed
    0:22:44 for decades and even longer than that, you would develop a product, let’s say a turbine,
    0:22:49 and then you would manufacture, you develop a bridge, and then you would build it. Using
    0:22:53 software simulation is different because you have these products that are out there in
    0:22:57 the real world and they’re going to continue to inform the thing that you’re developing
    0:23:01 in the simulator world. And so this connection of, it’s almost like reality in the loop.
    0:23:04 It’s a little feedback loop, but you’re right. Reality in the loop is a more significant
    0:23:10 wave. It’s less linear. X creates Y, Y creates Z, Z goes and influences X and it’s a nonlinear
    0:23:16 circle. And because of that, we’re more infrastructure than purely simulation because, like for instance,
    0:23:19 if you’re managing large amounts of data, is that really simulation? Technically, it’s
    0:23:25 not. But you need to do that in order to make your simulations useful. Connecting to the
    0:23:29 car, or is that part of simulation? No. So that’s why I think where the larger umbrella
    0:23:35 is infrastructure. You could say HD mapping is really an infrastructure play. Those are
    0:23:40 the rails of which the train rides. It’s also infrastructure in the sense that it’s used
    0:23:45 continuously on an ongoing basis, whereas the traditional forms of simulation were typically
    0:23:51 used sort of for this big, big moment, which is the creation of this final hardware specification
    0:23:55 which is then going to be made. It’s shipped. It is delivered. It is done. This is never
    0:23:58 done. You guys, I mean, it’s a terrible analogy, but it’s a little bit like a Kanye album.
    0:24:03 It’s continuing to evolve in the wild. And after it’s dropped, it’s going to keep getting
    0:24:10 modified. It’s a real life goal I had of comparing my simulation company to… Well, we’re all
    0:24:15 fans of music. So using your analogy of trains, because you mentioned the train tracks. So
    0:24:19 this is interesting because what we’re really describing here is laying down the tracks while
    0:24:22 also inventing the train itself. And the two things are kind of like moving targets against
    0:24:27 each other, et cetera. So what does that mean for the evolution of the ecosystem? I think
    0:24:31 overall, there is a co-evolution of sorts that happens between each of the different
    0:24:36 components involved. And so, for example, sensor companies and mapping companies, ensuring
    0:24:40 that the latest advancements that they have in their own products are then accurately
    0:24:44 represented inside of simulation. It’s like the phone supply chain we’re talking about
    0:24:50 earlier. So all these little revolutions and miracles happening. And the untold story that
    0:24:57 hasn’t been discussed is if you’re building autonomy yourself, what’s the right path?
    0:25:01 Is the path to go vertical and build everything yourself? Or is the path to buy things off
    0:25:08 the shelf? Where in this ecosystem, where do you draw that line of what is critical for
    0:25:17 autonomy, quote-unquote, and what is not? And so my rough view, and I would say largely,
    0:25:22 what is not differentiated between the companies, the mapping companies included, you should
    0:25:27 basically buy off the shelf. That’s commoditized. And you should be differentiating elsewhere.
    0:25:30 Because mapping companies are sensor companies, which are all kind of have the same role in
    0:25:37 different ways. We’re spreading our R&D costs across 10, 20, 30, 50 players. And therefore,
    0:25:42 each individual player gets a more advanced product for a cheaper cost. And that’s capitalism,
    0:25:47 right? You’re driving market efficiency. When people talk about a new industry, we’ll drive
    0:25:51 market efficiencies like tactically. How does it happen? It happens where you have individual
    0:25:57 players who are now unbundling the cost onto a bunch of people, a bunch of different companies,
    0:26:02 and then those people who are participating almost in that consortium are getting the benefit
    0:26:05 of it. Now, that doesn’t mean you can go ahead and you can definitely go and do that
    0:26:08 at a vertical company. There will always be an apple in every ecosystem.
    0:26:15 Yeah, exactly. But you better be Steve Jobs. Right, exactly. And what I love about what
    0:26:18 you’re describing, and this is capitalism, it’s funny because we might as well say cloud
    0:26:24 is capitalism at this point to make that syllogism. But it is the AWS moment in this ecosystem.
    0:26:29 And it’s talking about the fact that you can actually then free a whole new wave of companies
    0:26:34 to do things. I do find that very fascinating because until now, I would have thought that
    0:26:38 autonomy is only for like the big, the big, big five car companies.
    0:26:42 So the AWS example is exactly right. You can roll your own server. Some people have pride
    0:26:47 in running their website off their local, but guess what? Your consumers actually don’t
    0:26:53 care if you’re running on-prem, AWS, GCP, Azure or whatever.
    0:26:57 They just want the service. They just want the service. And so by the way, this happened
    0:27:01 in automotive. Automotive started, you know, Alfred P. Sloan.
    0:27:03 Wait, who’s Alfred P. Sloan? I don’t even know who that is.
    0:27:05 Oh, okay. So they are early automotive pioneers.
    0:27:07 Oh, I would have thought it was Henry Ford.
    0:27:12 Sloan was, so he’s not technically the founder of General Motors, but Sloan and Kettering
    0:27:17 were essentially the leaders of General Motors. GM was founded by a person named William Durant,
    0:27:21 who had started another car company. The amazing thing about the AV industry today is it’s
    0:27:25 almost copy and paste of the automotive industry a hundred years ago because you have these
    0:27:30 individual personalities who are shaping companies in their own way. Some get fired, they start
    0:27:34 competing companies. There’s all this drama between the existing players who are coming
    0:27:38 in. There’s a lot of M&A activity happening.
    0:27:42 Oh, this is one of my favorite things when we talk about how software and tech evolution
    0:27:46 is taking you back to an earlier era. That’s one of my favorite themes ever.
    0:27:52 The Sloans of the world and the Henry Fords of the world, they wrote and they tried to
    0:27:58 build vertical companies. I mean, Ford used to do everything. They used to get rubber
    0:28:04 from plants. They would forge steel. I think they even owned the farms where things were
    0:28:09 grown. So guess what? We don’t do that. Why? Because it’s actually more efficient to have
    0:28:12 a supplier ecosystem. Well, that’s like capitalism to the T. I mean,
    0:28:17 that’s like the classic, you don’t want to, someone did an experiment where they tried
    0:28:21 making their own sandwich from scratch. If they grew the vegetables, I think they had
    0:28:26 to outsource the cheat. They take the cows and the cheese and I think they estimated it
    0:28:31 to be like over almost $2,000 and capitalism makes that sandwich $7.
    0:28:37 So try doing that for like a computer, something that’s more manageable. You can go on YouTube
    0:28:40 and watch videos about people trying to build their own phones. They end up just going to
    0:28:43 China and buying for a bunch of suppliers because that’s actually the faster way to
    0:28:49 do it. And the ecosystem conversation that’s happening every single day in these autonomy
    0:28:55 teams is, oh, wow, we don’t have that many engineers. Oh, wow, there’s another huge pilot
    0:29:01 that somebody has announced and how can we move faster? One of the easy rules of thumbs
    0:29:07 of you can see how sophisticated and AV leadership is just asking them, where’s that line? And
    0:29:12 that line, that circle of competence should be as small as possible. That small circle
    0:29:16 in autonomy is algorithms. That’s the coveted golden nugget.
    0:29:19 Takes confidence to focus, narrow laser focus like that.
    0:29:24 So you can go to like a completely different industry, go to consumer CPG or you can go
    0:29:30 to consulting. If McKinsey or a, you know, Unilever or whoever it is will very clearly
    0:29:35 say, hey, you know what, this is the thing, this is the hill we die on. This hill, we
    0:29:38 have to be better than everybody else. The only way we win this hill is we abandon every
    0:29:39 other hill.
    0:29:43 Right. Well, this begs the question and Benedict often asked a similar question in his post
    0:29:48 on autonomy a lot, which is, you know, will Tesla become more like Detroit? Is Detroit
    0:29:53 more likely to acquire the Silicon Valley mindset faster or is Silicon Valley going
    0:29:56 to move faster in sort of learning the skills of Detroit?
    0:30:00 I think there’s no path to autonomy that doesn’t go through Silicon Valley and Detroit.
    0:30:01 So it’s an and not a word.
    0:30:04 And when you say Detroit, we mean roughly the automotive centers. Jit guard included.
    0:30:08 I mean, the Japan and Korea and China included in that.
    0:30:12 Right. You don’t mean Detroit geographically, you mean the entire category of automotive.
    0:30:13 Detroit is the concept of automotive.
    0:30:14 Right.
    0:30:20 Yeah. As a second hand for the automotive industry because Detroit has the delivery mechanisms,
    0:30:27 which are the brands and the factories which build these vehicles and the channel for lack
    0:30:28 of better words.
    0:30:33 This is not an internet product. The channel is not a website. The channel is the traditional
    0:30:40 OEM business. But the thing that you’re distributing through this channel is almost ideally built
    0:30:43 in Silicon Valley. Again, we’re talking about that circle of competence and how small you
    0:30:44 can make it.
    0:30:50 So we’re Silicon Valley, I think strays is when we start doing things, which frankly
    0:30:56 speaking, are outside this very small circle of software. And I get a little nervous when
    0:31:01 companies are doing a lot of hardware because there are other hardware centers in the world
    0:31:06 which are arguably better or when even broadly like on podcast, people start talking about
    0:31:08 like these other things.
    0:31:13 And it’s like, if we went to some group of factory owners who I don’t know are specialists
    0:31:20 and they don’t get on podcasts and then start advocating about things outside of their little
    0:31:26 circle of competence, they talk about a leather price and how are you getting cheaper electricity?
    0:31:30 I hear you. It’s both. It’s both arrogant and charming at the same time.
    0:31:31 Exactly.
    0:31:37 But it’s good because it pushes you to go into trying new things, agree. And so the magic
    0:31:42 happens where you’re pushing trying new things in your area of competence. I can go and try
    0:31:47 to be an NBA basketball player, but guess what? It’s probably not going to work no matter
    0:31:52 how much effort and, you know, I try, I put into, but so I think there’s a similar, you
    0:31:58 know, relationship between Detroit and Silicon Valley. There is a real merger. And my background,
    0:32:01 you know, both Peter and I, we grew up in a group in Detroit area.
    0:32:02 I had no idea. You guys grew up in Detroit?
    0:32:06 Yeah. Of all the random coincidence, not only we grew up in the same town, we grew up in
    0:32:11 the same subdivision. We’re literally at the same crossroads for people who are in Detroit
    0:32:16 as 22 and Shayner and Shelby Township. I went to GMI or now Kettering University, which
    0:32:18 is the General Motors Institute. Peter went to U of M.
    0:32:22 So I actually started my career at a small engineering tool company in Michigan, but
    0:32:23 really my entire family works on a motive.
    0:32:25 So you guys are like Detroit, born and bred?
    0:32:29 Yeah. I worked five years at General Motors, two years at Bosch. And then we’re in the
    0:32:33 same team on Google Maps. This is five, eight years, seven years ago, a long time ago. And
    0:32:39 we saw chauffeur, which was, which became Waymo. And I remember saying to Peter, man,
    0:32:42 this is going to hit Detroit like a ton of bricks.
    0:32:46 Kettering is located in Flint, Flint, Michigan. So I spent five years at Flint. And when you
    0:32:52 look at places like Flint, you really start thinking long and hard about like, well, where
    0:32:56 do people get in these new jobs? That was the theme in the 90s and the early 2000s when
    0:33:00 I was growing up was, oh, there’s going to be this revolution and all these people in
    0:33:03 Michigan are so suddenly going to have these great new jobs. And guess what? My family
    0:33:09 included those jobs didn’t come. My dad never became a software engineer in his late 50s.
    0:33:13 That doesn’t happen. And then also I think any business in the human experience is emotional
    0:33:18 to some degree. I mean, we very much like practice that belief that there is this connection
    0:33:19 between these two.
    0:33:23 You guys are really, we’re really long on the Detroit Silicon Valley and not the ore.
    0:33:28 So what do you think then that the winning company, maybe it’s not a winning company,
    0:33:32 there’s plenty of room for many, but where is it going to sit? And how is it going to
    0:33:33 look?
    0:33:39 Well, it’s like, you know, where does the winning automotive player today sit? I think
    0:33:40 it’s very hard to answer that question.
    0:33:43 There’s at least a few in every major geography.
    0:33:48 And the supply chain, which is really what the auto business is, is everywhere. These
    0:33:53 are such massive industries. They have epicenters. So I think the autonomy software stack will
    0:33:59 probably for a long time be in Silicon Valley, but even you can look at like TRIAD, the Toyota
    0:34:05 Research Institute’s Autonomous Division based in Tokyo. You have other companies, BMW,
    0:34:10 even TRIAD actually has presence here in the valleys as well in the Detroit area.
    0:34:15 So I think this concept of like, there’s a company that wins it for a town, I think
    0:34:19 that’s different. I think we sometimes get that analog because of the internet where
    0:34:22 you have Google, which is basically home home, home team, which is Mountain View.
    0:34:23 Yeah.
    0:34:27 A lot of the companies are like Silicon Valley and Seattle and there’s like a few centers
    0:34:28 that are very focused.
    0:34:33 I think these large industries that are very intertwined with each other, it’s a lot less
    0:34:39 concentrated like that. I think the real fundamental issue we have, and this is getting more philosophical
    0:34:44 again is what the internet has done and what software has done is it’s concentrated wealth.
    0:34:48 We talk about wealth concentration as like somehow blaming sometimes, you know, a certain
    0:34:53 political viewpoint, but really they’re so efficient software companies that does bring
    0:35:00 a disproportionate amount of money to where the epicenter is. And so how can we make sure
    0:35:09 that concentration, you know, that the next wave, which is autonomy, doesn’t keep just
    0:35:12 kind of underlying that. One of the other things that is not talked a lot about autonomy
    0:35:18 but should be talked about autonomy is that these are national questions. The German government
    0:35:24 won’t just let Waymo come take over Germany and let Daimler and BMW go under business.
    0:35:29 And the same thing is true for Hyundai in Korea, Hyundai and Toyota in Japan and the Chinese
    0:35:32 companies because there’s a recognition that if all of these cash flows end up going to
    0:35:36 these little neighborhoods in the suburbs of San Francisco, maybe that’s not good for
    0:35:43 our national interest. In the internet, because it was a new market, it wasn’t very visceral.
    0:35:48 Daimler is a visceral, Bosch is a German thing. Peugeot is a French thing.
    0:35:53 It’s like the classic discussions around manufacturing, like, you know, this idea that like it’s a
    0:35:58 physical product that is made in India, made in China, made in Japan, made in Italy, made
    0:36:04 in Italy. You know, it’s very specific and you’re right, there is a very national sentiment.
    0:36:07 But what I love about what you’re describing too, though, is it is true capitalism because
    0:36:12 I think capitalism gets a bad rap for the inequality, which is a fair complaint and
    0:36:17 a fair criticism. But to me, true capitalism is something that raises the all boats in
    0:36:18 the ocean.
    0:36:23 Yeah. It’s on Pakistani, by birth on Pakistan. My family were from a small farming village
    0:36:27 for the first, you know, seven, rough seven years of my life. I was in this, you know,
    0:36:31 in this remote farming village in the, roughly in this valley. And you know what’s a real
    0:36:35 luxury? Hot showers. Yeah. And so, you know, when I, when I had that hot shower in the
    0:36:37 morning and I drank that cold water.
    0:36:38 You don’t take it for granted.
    0:36:39 Capitalism.
    0:36:43 I know. I go the same way about electricity. I mean, my dad, I was born and raised here,
    0:36:47 but my dad’s from India, small village, and he grew up without electricity. And then he
    0:36:51 later got electricity and I was just marveling just very recently in our families at the
    0:36:58 valley that we had electric BIAS. That’s insane. Like before electricity was not even available
    0:37:03 to people. And now you have mass produced little tiny LED lights and like little bases
    0:37:04 as candles.
    0:37:05 That’s fricking amazing.
    0:37:06 Exactly.
    0:37:07 No, I agree.
    0:37:08 So on that front.
    0:37:13 I think where autonomy is different is I think it has the potential. And I think whether
    0:37:17 we like it or not, there is a regulatory aspect to this entire conversation.
    0:37:20 So I have a question about this because you brought up the point about there being a national
    0:37:25 interest. There’s also a local city and state level of interest. Mark wrote an op-ed a few
    0:37:30 years ago in Politico, arguing that you can use it for a regulatory arbitrage where like
    0:37:34 say, Detroit could actually loosen some of the barriers. Just like, you know, I think
    0:37:38 Governor Ducey is doing in Arizona where you have different cities offering different
    0:37:42 incentives and doing more experiments so that they can ensure the ecosystem kind of grows
    0:37:47 up locally. How is that really happening? Given your thesis, it sounds like you’re saying
    0:37:52 that everything can happen everywhere and there’s room for all kinds of players and
    0:37:57 B, what do you see as sort of the regulatory and policy issues in the autonomy ecosystem?
    0:38:00 Yeah, I think everything can happen everywhere is more of this concept of there are so many
    0:38:04 components and these components will come from everywhere. One of my friends who’s Indian
    0:38:09 who was wished that states themselves in India would have more of a control over their own
    0:38:14 laws because he believes that within the US, the states creating their own regulatory, many
    0:38:20 regulatory environments is almost like a mini form of capitalism. It’s a grand laboratory
    0:38:25 of capitalism actually. States are laboratories of innovation. There’s cities are to that
    0:38:31 sort of federalist style. I think it was an enabling condition for success, not a bug.
    0:38:36 And it’s a great feature because the state like Indiana says, Hey, listen, maybe this
    0:38:40 is in our best interest because we’re a state that trucks go through and want to make sure
    0:38:44 we make that toll, toll income. But if you’re a state like Arizona, and maybe you don’t
    0:38:49 have that and you have this great testing ground, historically Arizona belong before
    0:38:54 autonomy has been approving grounds for the auto business, that, Hey, we see that, you
    0:38:58 know, the Arizona approving grounds for General Motors brought all of this, you know, business
    0:38:59 over the last 20 years.
    0:39:02 Right. Why can’t we do the same for this? It takes a lot of courage, by the way, because
    0:39:06 they did have, I think, the first instance of a fatality through autonomy. So when we
    0:39:11 do talk about these states sort of taking the leap, there is sort of a cost you pay.
    0:39:15 Because in the case of Arizona, I think they were the first to have the first fatality
    0:39:19 related to autonomy. And of course that’s going to happen. I’m not trying to minimize
    0:39:24 it. That’s a really big deal. But that is, I think one of the trade offs is that cost.
    0:39:29 I think the states that are making those decisions are opening some of them and their citizens
    0:39:34 to that risk. And so the citizens then elect those, you know, those representatives who
    0:39:39 then say, Hey, this is or is not the trade off that I want to have.
    0:39:44 That matches their needs. And I think, I think though, probably what again doesn’t get covered
    0:39:49 is I think that night, there were also 10 other pedestrian accidents in America where
    0:39:50 people died.
    0:39:54 You’re right. There is a statistical thing, which is hard to think about when you’re
    0:39:56 talking at a personal level.
    0:40:01 It is tough because that’s a real family. And if you’re that person, you don’t care.
    0:40:06 There’s 10 other 11 other people that died that night. Also, these are the guardrails
    0:40:13 we roughly think are ones that can be employed. You don’t want to have complete laissez-faire
    0:40:16 open. Everybody does whatever and
    0:40:21 Pure permissionless innovation. We’re talking about moving, killing robots.
    0:40:25 This is like a human being. Like they’re like one of the things we don’t think about in
    0:40:30 Silicon Valley. A lot of the, a lot of times engineers in the auto business over the last
    0:40:32 years have gone to prison.
    0:40:33 I had no idea.
    0:40:39 Just a Volkswagen diesel scandal that put employees of Volkswagen in prison. And so there is real
    0:40:45 consequences when you’re dealing with a product, which an automotive product, which can harm
    0:40:46 the public.
    0:40:51 The other end though, is if you put in regulations and, and they’re onerous and they’re significant,
    0:40:52 guess what?
    0:40:53 Squelch is innovation.
    0:40:59 100%. And we are, we’re talking this, this, this conversation has been very US centric.
    0:41:03 In 1980 capitalism was a very, you know, regional thing. The real revolution that’s happened
    0:41:07 in the, in the last, you know, 30, 40 years is a capitalist revolution. It’s just the
    0:41:10 shade of capitalism. And so when you think about China, which is a different shade of
    0:41:13 capitalism, you think about Europe, which is a different shade of capitalism, generally
    0:41:18 different approaches. But, you know, some, some, some regulatory environments are very
    0:41:24 open and we have to be aware of that for not only the Silicon Valley and Detroit companies,
    0:41:29 but just in general as Americans of being in an economy which is healthy and productive
    0:41:34 and at the cutting edge. But at the same time, you as citizens, you don’t want to be a laboratory
    0:41:42 for private entities to make a profit. And so there is a very nuanced approach there.
    0:41:47 At the end of the day, we’re really advocates of best practices for safe development. And
    0:41:53 so that means really taking the steps necessary to ensure that the systems, the software are
    0:41:58 safe before they actually go to the public. Yeah. You’re talking about simulation here.
    0:42:03 We’ve talked about simulation earlier in terms of the industry evolution, but simulation
    0:42:06 itself got a bad rap for a while. You know, there’s a lot of companies that sort of felt
    0:42:10 like, oh my God, simulation, it had a bad rap for a while. It’s like a, you know, I think
    0:42:16 trying to do VR and AR to some degree in the 1980s. And so I think simulation, which has
    0:42:21 been different than AR VR is there are no complex systems that are being developed without
    0:42:28 simulation aircraft, military systems, automotive, internal combustion engines, microprocessors,
    0:42:36 simulation is everywhere. And so I think that’s because the underlying kind of software industry
    0:42:43 has become so much more advanced. It’s computationally more efficient. You can apply, you have things
    0:42:48 like the cloud revolution, the ability to point lots and lots of resources at the problems.
    0:42:52 What to say is shifted from constrained to abundant. And that essentially creates abundant
    0:42:58 sensors, abundant data. You can waste bits. You can essentially simulate complex things
    0:43:03 unbounded in a way that humans can’t even remotely conceive of. That does answer the
    0:43:08 why now question. What are the limits of simulation? I mean, we are talking about complex systems
    0:43:13 on a ton of edge cases here. Yeah. I mean, at the more technical level,
    0:43:18 simulations are never perfect. There’s always going to be some difference between a simulation
    0:43:22 and a real physical system. We like to get our simulations to the point where they are
    0:43:26 plenty good enough for useful development. Good enough for development. Good enough for
    0:43:30 development. Good enough for pushing things forward and to give a very high confidence
    0:43:35 that the behaviors and simulation are representative of the real behaviors. But with that said,
    0:43:40 there will always be situations and scenarios where there are differences in behavior between
    0:43:43 the simulation environment and the real environment. Of course. Right. Okay. So what’s also interesting
    0:43:47 about this is that it essentially lets you get the three C’s that you described earlier,
    0:43:51 cost, convenience and safety in one system. And to the regulatory point that you brought
    0:43:56 up, Casar, it is unless you kind of strike that just right balance in there. But the
    0:44:00 big thing now, because you’ve been talking in this podcast about this importance of differentiation,
    0:44:05 if this is a tool that everyone has, it sounds like they would differentiate on data. So
    0:44:08 how do you in this ecosystem where you’re making this argument that there’s this horizontal
    0:44:12 versus vertical layer, are all these players willing to share in the ecosystem, the mapping
    0:44:17 companies, the sensor companies, the big vehicle companies? How do you navigate the data side?
    0:44:22 Data means a lot of different things. It’s not like scenarios and, you know, the data
    0:44:28 that you have for autonomy, but it is the autonomy engineer who themselves are understanding
    0:44:34 how are the methodologies to best develop an autonomy system. There is some, what we
    0:44:38 call light network effects there between companies. Well, I mean, if you go to Stanford, they
    0:44:43 teach classes that help you learn ANSYS’s simulation tools. So there’s literally this
    0:44:49 public company called ANSYS that does simulation tools and you can learn how to use it by taking
    0:44:53 classes at Stanford. And that’s the same thing with AutoCAD. If you look back, if you look
    0:44:58 there, there are many tools that kind of fall into the, into this group. I mean, when you
    0:45:01 learn how to program, you’re actually just learning tools. Now, what’s happened with
    0:45:06 software development is those tools, it becomes a really just a commodity and there, and there’s
    0:45:11 many different ways. And so we’re still in a quite a nascent niche field with autonomy.
    0:45:15 So the tools are not a commodity. These tools are so hard to build. These two simulations,
    0:45:17 it’s not a trivial thing to build.
    0:45:22 At the end of the day, the lowest cost solution will win, but of course it has to be a real
    0:45:23 solution.
    0:45:24 Yeah, it has to solve something.
    0:45:25 And that’s what the industry is still working on.
    0:45:29 Right. It’s actually kind of funny because the conundrum here is that software is bits
    0:45:34 and it’s abundant and therefore it’s accessible to everybody. But the specialties and the algorithms
    0:45:39 I’m clearly hearing and like the nuance of the art, and we used to call it know-how when
    0:45:44 I used to be at park. It’s kind of the idea of the know-how and the differentiation. But
    0:45:48 the point is, it’s basically going the way of mobile and you’ve been drawing the analogy
    0:45:51 and we’ve talked a little bit about where the analogy breaks down and where it applies.
    0:45:55 How do you think this plays out given that you are a horizontal player? There aren’t
    0:46:01 really big horizontal huge like apples and Googles. There are vertical companies.
    0:46:07 Well, they are, but actually, you know, each of the sub components, the phone manufacturers
    0:46:12 themselves, companies that do analytics for mobile, companies that do ads for mobile,
    0:46:19 a lot of horizontal players, anything that exists both on Android and iOS is in some
    0:46:25 way a cross-platform horizontal play. And so I think where the commoditization has happened,
    0:46:30 quote unquote, is in the apps themselves. I’m reading this book, The Five Ages of the
    0:46:32 Universe, which is The Physics of Eternity. Fascinating.
    0:46:40 So what happens at the end of the universe, right? All the stars have now died.
    0:46:45 Oh my God, I really need to read this book. This is totally my jam. I’m like really obsessed
    0:46:48 with space and evolution right now. Yeah, it can be dry. I find it very interesting.
    0:46:55 But the point is, once you get into these outer edges, the strange things start happening.
    0:47:02 And so we’re now in that mobile age where there are applications that are gaining users
    0:47:07 very, very, very quickly and still not being valuable or some applications that might not
    0:47:11 have as many users but can become super, super valuable because they’re catered towards
    0:47:18 a very specific audience that needs that thing. And so I think with autonomy, I think the
    0:47:23 arc here, you’ll see all these individual modules will be run by individual players
    0:47:27 because there is this natural arc in capitalism, which says the independent providers can do
    0:47:32 cheaper, better and faster than anybody doing it vertically. But the question is, will the
    0:47:36 algorithms themselves ultimately commoditize? And I think that’s when you get into this
    0:47:40 far edge of the universe. It’s like, could we be in a situation in 10 or 15 years that
    0:47:46 like today, starting a mobile app is very easy. That starting an autonomy company is very
    0:47:47 trivial. It’s just that easy.
    0:47:52 I think it would be very hard in 2005 to think that Kim Kardashian or whoever would have
    0:47:56 their own app and it would make millions and tens of millions of dollars. But that’s the
    0:48:01 reality today because that’s so niche. It’s not just, hey, it’s a phone app. It’s a phone
    0:48:05 app on a specific platform for a specific celebrity and just their fans because everybody
    0:48:10 else can just consume Instagram or something else. And so that real edge, I think that
    0:48:15 far off the world of autonomy, 10 or 15 years from now, imagine if you could build an autonomous
    0:48:20 vehicle very quickly and very easily. If that could happen, how does that, what does that
    0:48:21 make the industry?
    0:48:24 Yeah, no, it’s like a theme we talk about actually is that the edge is where it’s at.
    0:48:28 I mean, in computing and innovation, I mean, it’s basically the democratization of autonomy.
    0:48:31 Well, you guys, thank you for joining the A6NZ podcast.
    0:48:32 Thanks for having us.

    with Peter Ludwig, Qasar Younis (@qasar), and Sonal Chokshi (@smc90)

    When people talk about autonomous vehicles, we hear everything from ”we’re much closer than you think” to ”we’re much further than you think”. So where are we, really, in the widespread reality of autonomous vehicles today? It depends, of course, on how you define autonomy — which is where a handy recap and update of the SAE (Society of Automotive Engineers) levels of autonomy comes in. But still, given everything out there from self-driving shuttles to Teslas, it’s really hard to tell just where we are and where the nuances of, say, Level 2-plus vs. Level 3 might come in.

    This episode of the a16z Podcast takes a quick pulse on where we are in the state of autonomy in 2019 when it comes to autonomous cars, shuttles, robots — basically any ”autonomous” and/or ”self-driving” vehicle out there — as well as the analogy of mobile for understanding the space: where it works, where it breaks down. But did even the mobile industry itself really have a clear iPhone ”moment”? When did mobile devices that seemed so limited — or seemed like just ”toys” — suddenly (or not so suddenly) go to an apps layer that we use every single day? How do we build ”the rails” and ”the trains” at the same time in this case?

    And perhaps most importantly, where will the spoils of this new wave of innovation go — to Silicon Valley or Detroit? Or outside the U.S.? Who are the players? How do regulatory — and quite frankly, nationalistic — concerns come into play here? And finally, how does one balance the desire to embrace innovation in an open and fast, yet still very thoughtful and safe way?

    The answers, according to Applied Intuition co-founder and CEO Qasar Younis and CTO Peter Ludwig (in conversation with Sonal Chokshi), have to do with commodities and capitalism, with science and science fiction, with simulation and software as infrastructure, and more… And really, how we define autonomy now, and in the future.

  • a16z Podcast: Gaming Goes Mainstream

    AI transcript
    0:00:04 Hi everyone, welcome to the A6NC podcast.
    0:00:07 Today’s episode features Mark Andreessen interviewing Bobby Kotick,
    0:00:12 CEO of Fortune 500 company Activision Blizzard, the largest game network in the world,
    0:00:17 responsible for popular entertainment franchises such as Call of Duty, Candy Crush and World of
    0:00:23 Warcraft. The discussion originally took place at our most recent annual innovation summit
    0:00:28 and covers everything from the evolution of games in the 80s to the mergers and acquisitions that
    0:00:33 created the company he runs today to trends in gaming, including touching on esports.
    0:00:40 You can also find other podcasts and videos from this event at asixnz.com/summit.
    0:00:45 Please note that the content here is for informational purposes only, should not be taken as legal
    0:00:51 business tax or investment advice, or be used to evaluate any investment or security.
    0:00:55 For more details, please also see asixnz.com/disclosures.
    0:00:59 So, Bobby, it is really fun as a long-time video game aficionado. Really fun to have the chance
    0:01:05 to talk to you today. I would love to start with your origin story, as they say in the superhero
    0:01:09 business. So, part of your origin story, if I recall correctly, is that you started writing
    0:01:14 software for the Apple II while you were still in college. So, my college roommate and I started
    0:01:19 a company. He worked at Apple Computer in France. He was French and his summer internship,
    0:01:25 he was working for a guy called Jean-Louis Gasset, and they had a prototype of the Lisa,
    0:01:30 and the Lisa was the Mac before the Mac. It was the $10,000 version of the Mac.
    0:01:38 So, he saw this prototype of the Lisa and thought for $10,000 this would be too expensive to turn
    0:01:44 into a consumer product. So, he came back from his internship and said, “We should make Lisa-like
    0:01:50 software and a mouse for the Apple II.” And we were in another sort of technology-related
    0:01:54 business in our dorm room at the time, but we thought we were making hardware. I thought this
    0:01:59 would be a better business, is make software. And we really thought if Steve Jobs is going to
    0:02:04 appropriate all the great technology from Xerox Palo Alto Research Center, we should do the same,
    0:02:11 but do it on a broader scale. So, we designed this mouse and a word processor and a spreadsheet
    0:02:17 and a database all for the Apple II with a graphical user interface about a year before
    0:02:21 the Macintosh was released. You also, I believe, credit, if I’m correct, Steve Jobs with convincing
    0:02:25 you to drop out of college? I don’t know if it’s credit, but Steve Jobs heard about us.
    0:02:29 Because when you started, you were in college. I was in college. I was making Apple II software,
    0:02:36 and he heard about the software, and he called me and said, you know, the lady said, “Steve Jobs
    0:02:40 calling.” I was like, “Okay, it’s one of the kids I grew up with from Rosalind Long Island, and this
    0:02:46 is not even that good a joke.” Steve is like super famous, like Cover Time magazine. Yeah, this is
    0:02:54 like 1983, late 1983. ’83, ’83, ’83. Right. Super famous. Yeah, and I’m like, “Yeah, right, whatever.”
    0:02:59 So, I pick up the phone, he’s like, “Hi.” I said, “Hi.” He said, “This is Steve Jobs.” I said,
    0:03:03 “Yeah.” Sure. And all I’m thinking is like, I wanted to say like, “I’m Oscar Robertson.” I was
    0:03:09 a big Knicks fan. I thought like, so he starts like telling me, “You need to come to Cupertino,
    0:03:14 and I really want to talk to you about this Jane thing that you made.” And so I go, and he shows
    0:03:20 his prototype of the Macintosh, and like, I’ll never forget this moment. He unzips this little blue
    0:03:24 bag from off of his table, and he takes it out, and he turns it on, and you see the hell out come
    0:03:28 up on the screen, and I thought, “Wow, this is unbelievable. This is going to change computing.”
    0:03:33 And I like, I still get the goosebumps of just thinking about it. And then he said, “Okay, now
    0:03:40 show me yours.” And so like, I’ve had lugged this Apple II with like the 64K floppy drive,
    0:03:44 and this mouse that we designed, and we put it on, and I show him the mouse, and he looks at it,
    0:03:51 he’s like, “This is a piece of shit.” And he throws it on the floor, and he says, “You’re going to use
    0:03:54 our mouse, and don’t ever think of using a two-button mouse. You’re going to use a one-button
    0:03:59 mouse.” And then I show it to him, and the first thing he says is, “Wait a second. You select the
    0:04:03 text, and then you select boldface?” I’m like, “Yeah.” He’s like, “No. We’re going to think about
    0:04:08 verb noun versus noun verb in the way you actually boldface type.” And for 45 minutes, we had this
    0:04:13 huge debate about how you boldface type. And at the end of it, he’s like, “You’re going to make
    0:04:17 this for a new computer that we’re going to build called the Apple II GS, and we’re going to tell
    0:04:21 you all about it, but you’re going to make this software for the Apple II. And we’re going to
    0:04:27 give you a contract.” He goes, “This is a contract.” And then he comes to visit us in Ann Arbor,
    0:04:35 Michigan, in our office above a Burger King. And the first thing he says is, “How the hell do you
    0:04:43 work here? The smell of burgers comes up the elevator.” He’s like, “It was cheap rent. Nobody
    0:04:49 else wanted to rent on top of a Burger King.” So at the end of the meeting, he says, “Do you have
    0:04:56 any vegetarian restaurants here that we could go to for dinner?” And I said, “Yeah, I’m sure we do,
    0:05:01 but I can’t go to dinner. I have a class.” He’s, “What do you mean?” I said, “I have a class.” He
    0:05:06 said, “In what?” I said, “It’s a history of art makeup class.” He said, “What are you making up for?”
    0:05:11 I said, “Well, I didn’t go to the class.” He’s like, “Well, why do you need to go to this?” I said,
    0:05:17 “Well, I’m in college.” And he looks at me. He’s like, “What are you talking about? You have a
    0:05:21 contract with Apple Computer, and we have a deadline for the Apple II GS. You can’t be in
    0:05:25 college. You have employees. You have to work full-time.” He’s like, “Get out of college.”
    0:05:30 And I said, “I can. I promise my parents I would finish college.” He said,
    0:05:36 “No, you’re not finishing college. I will rip,” and I can’t say the word,
    0:05:41 “I will rip this f-ing contract up right now if you don’t quit college.” So I quit the next day.
    0:05:47 Did your parents believe the story? I didn’t tell them for about eight months. I felt like,
    0:05:51 all right, I needed to get more progress in the business before my father would say,
    0:05:56 “You’re an idiot. Now, you took money from this gambling guy and you quit college. You’re just a
    0:06:04 loser.” So then fast forward a few years. So 1990, you bought 25% stake in Activision,
    0:06:09 became CEO in 1991. So Activision, people may not know, Activision was a storied brand in video
    0:06:13 games. Activision, I believe this is correct, was the first third-party developer of video games
    0:06:19 in 1980. So it was a spin-off from Atari. It was for the top people at Atari. They got in
    0:06:22 conflict with management. And this is a very big deal, number one, just because, you know, to quit
    0:06:25 starting a company is a big deal. But also it’s just a big deal because like literally there had
    0:06:29 not been a business of making video games for somebody else’s platform. Atari made all the
    0:06:33 games for Atari. And now at this company, Activision, they had a run of hits, I guess in the 80s,
    0:06:37 early 80s, you know, they made a bunch of the top games for Atari systems. And then they went
    0:06:41 bankrupt or they were about to go bankrupt. They had a decade of pathetic performance and then
    0:06:46 finally went bankrupt. Okay, got it. So as long as a whimper, not a bang. And so how did you get
    0:06:53 from building mice in your above the Burger King to buying Activision? So in 1987, there were no
    0:06:59 real video game hardware companies. And I played a lot of video games as a kid and I loved Activision
    0:07:05 games. So they made the original Atari 2600 games that made the company so successful. Games like
    0:07:12 Pitfall and River 8 and Kaboom. And these are just great games. And so in 1987, I thought there’s a
    0:07:18 great opportunity to make video game hardware. And nobody is making video game hardware games are
    0:07:24 just played on personal computers. Nintendo was just coming to the US. So there was no
    0:07:31 dedicated video game hardware. My best friend from growing up had just started a hedge fund
    0:07:36 with this guy from Texas named Richard Rainwater. And they were looking for investments.
    0:07:42 And I went to him and I said, I have this idea. And in 1987, in October, the market had crashed.
    0:07:46 It was like a 500 point market crash was Black Monday. Black Monday was one of the
    0:07:53 biggest crashes in the market history since the Great Depression. And I had been working
    0:07:58 making software for, among other companies, Apple and Commodore. And Commodore was this
    0:08:06 $900 million revenues company at the time with $150 million market value. And so I went to
    0:08:10 my best friend and I said, we should buy Commodore. They have this computer called the Amiga.
    0:08:14 And it has a keyboard and a disk drive, but we should pull the keyboard and the disk drive out of
    0:08:20 it. And it would be the first 16 bit video game system. And it was designed by Exitari engineers
    0:08:25 and was made basically as a video game. It was a big leap forward graphics performance at the time.
    0:08:31 68,000 microprocessor and dedicated graphics processors. And it was like a really innovative
    0:08:39 idea. And my best friend at the time said, yeah, let’s try and do this. And so we tried. And
    0:08:45 ultimately couldn’t persuade the chairman of Commodore to do the deal. But I just became then
    0:08:53 fixated with being in the video game business. And my best friend at the time was Eddie Lampert,
    0:08:57 who then went on instead of buying Commodore to buy Sears and Kmart. And he was a customer for a
    0:09:04 little while. We stopped extending credit to him. I think four years ago, though. So I thought, okay,
    0:09:10 we have to be in the video game business. And I had a little side business that was a licensing
    0:09:18 company. We licensed characters. So one of our licensing partners was Nintendo. And we were
    0:09:25 licensing Nintendo characters for bedsheets and lunchboxes. And I knew the Nintendo people. And
    0:09:30 one day I was having a Nintendo meeting. And they said, have you ever thought about
    0:09:35 Activision? And I said, yeah, I know the company well, I played all the games. And they said,
    0:09:39 they’re not in really good shape. And they’re about to lose a patent infringement judgment that
    0:09:47 will probably make them bankrupt. So you should consider buying Activision. So I bought a 25%
    0:09:53 stake in Activision for $440,000. And I became the largest shareholder.
    0:10:00 And it was insolvent. But I tried to get the CEO on the phone to tell him I was his new largest
    0:10:04 shareholder. It’s a public company. It’s a public company with a market cap of $1.6 million. Yeah,
    0:10:12 $1.6 million. And a patent infringement judgment that made it insolvent. And so I couldn’t… Here’s
    0:10:17 this company that’s doing horribly, has all these great franchises. And the CEO wouldn’t return my
    0:10:22 phone call. And so I kept calling, kept calling. And finally I just thought, I’ll just go to the lobby
    0:10:29 of the building and tell him I’m there and see if he’ll see me. So I go and I’m waiting in the lobby.
    0:10:34 And finally after three hours, he says, okay, I’ll come talk to you. And I talked to him and I
    0:10:37 said, you know, we’re your largest shareholder. I have some really great ideas for you. I have
    0:10:42 some game ideas I’d like to make. And, you know, I love some of the old properties. Maybe we can
    0:10:47 figure out how to really get some of those properties back to being games. And he’s like,
    0:10:52 well, thank you very much for visiting and nice to meet you. And I said, no, no, I’m like, when is
    0:10:58 the next meeting? And he said, there’s not a next meeting, but we’re very happy to have you as
    0:11:05 shareholders. And so I thought, well, how does that work? I own 25% of the company. I’m the
    0:11:10 largest shareholder. We’re really a quarter of the furniture in the lobby. And he didn’t return my
    0:11:14 phone calls for a little while. And then he agreed to have breakfast with me at this consumer
    0:11:19 electronic show in Las Vegas. Obviously, Activision was then, you know, tremendously successful.
    0:11:23 You then did one other really, really big deal that was transformative for the company, which was
    0:11:27 and I don’t quite know how to describe it, but I think it’s a merger with Vivendi games
    0:11:31 that resulted in Activision Blizzard, because Vivendi owned Blizzard, Blizzard, obviously,
    0:11:35 World of Warcraft and all these other amazing properties. And then ultimately that partnership
    0:11:38 on one, maybe you could tell us like that was a very, very big deal for you at the time.
    0:11:44 How did that deal come about? So it was the spring of 2008. And I had a lot of anxiety about the
    0:11:50 public markets and financial crisis is brewing. Yeah. And you could see there was a lot of
    0:11:55 volatility instability. We were nervous, but we thought, you know, if we could buy something,
    0:11:59 we had a big market value at the time. And I thought if we could buy something great,
    0:12:04 that we really love, this would be a good time to do it. And you guys weren’t yet doing the massive
    0:12:08 multiplayer. You guys weren’t yet doing like there was this big World of Warcraft had been a big hit
    0:12:14 at that point. Huge hit. And we had explored doing a massively multiplayer persistent game.
    0:12:19 There were a couple of other games before World of Warcraft that were massively multiplayer games,
    0:12:25 but nothing that had had the success of WoW. And we looked and said, if we even could figure out
    0:12:31 how to do it, it would take us five, six, seven years and a billion dollars. And the likelihood is
    0:12:36 we wouldn’t do a good job of it. But it was a, and I knew the Blizzard team because we had worked
    0:12:42 with them on, they were a contract development company in the early 1990s. And I knew the team
    0:12:48 very well and really liked them. And I tried to recruit them out of the company. And I knew that
    0:12:52 they had so much of a love and a passion for the company that no matter who owned it, they probably
    0:12:57 wouldn’t leave. And I called the guys at Blizzard a bunch of times and said, we should truly try and
    0:13:03 work this out. And they were stuck as a division of Vivendi Games, which was owned by Vivendi.
    0:13:10 And you might describe what Vivendi was at this point. It was a big mess. And it was a former,
    0:13:15 if I think it’s correct, it was a former public utility. Well, it was the water company of France
    0:13:20 that this very, and by water and other things that flow through pipes. Yeah, water, other things that
    0:13:26 flow through pipes. It was a collection of more industrial businesses that the, a man had taken
    0:13:32 it over and decided he was going to become the media mogul of earth and bought universal studios.
    0:13:38 And anything he could actually buy, he just bought. And then it got disassembled because
    0:13:44 it was insolvent. And they ended up with a couple of businesses. The best one for them at the time
    0:13:51 was probably Universal Music, which I think Lucine is here somewhere. So they had Universal Music.
    0:13:58 They owned Morocco Telecom, Upstake. They owned SFR, which is a French mobile company.
    0:14:04 They own Kennel Police. And somehow they managed as a part of a bunch of things to own
    0:14:10 this games business, which included Blizzard. And I asked them to sell us Blizzard. And we didn’t
    0:14:14 have any interest in the rest of their games business, but we wanted Blizzard. And they said,
    0:14:20 no, repeatedly. And we offered them $4 billion and then $5 billion and then $6 billion and then $7
    0:14:25 billion. They kept saying, no, they like video games. So we came up with this idea and we said,
    0:14:31 how about this? We’ll stay a public company. You sell us Blizzard or give us Blizzard and $2
    0:14:38 billion of cash, and we’ll give you 51% of the company. And my view was in 2008, even the biggest
    0:14:45 institutional investors no longer were really long-term holders. And all the big institutional
    0:14:49 investors were trading in and out of the stocks like they were hedge funds. So if we could get
    0:14:56 Vivendi to own 51% of our company, we got Blizzard as a partner, we would have a great business and
    0:15:01 a stable shareholder who would never sell our stock and would be enthusiastic about investing,
    0:15:07 at least what they told us, investing with us for the future. So we went back and forth for a
    0:15:13 long time, finally negotiated a deal where they would do that deal. And I almost blew the deal
    0:15:19 in the worst way too. They had this beautiful headquarters in France, like the nicest building
    0:15:23 in France. And the guy who had put the original Vivendi together, there were lots of these
    0:15:29 beautiful French offices that had gardens on the top of their roof. He built a park
    0:15:36 and like mature trees on the top of the Vivendi building. It was like a park with trees that
    0:15:41 were all over the place. And one room was like a wine cellar and one room was this magnificent
    0:15:46 dining room. And so we’re standing on the top of this roof overlooking the Arc de Triomphe
    0:15:54 and the Eiffel Tower. And the chairman of the Vivendi says to me, “Bobby, this building,
    0:15:59 it will be your home. This will be your place. You can do your business in France and you should
    0:16:03 treat this building like your home. You can do anything you want with this building, but it will
    0:16:08 be your place for Paris. You can make a business here. And it’s the most beautiful building in
    0:16:13 Paris. It’s the most beautiful view in Paris and it’s for you. You can do anything you want with
    0:16:19 it.” And I said, “Anything? You can do anything.” And I said, “Can I build 20 stories of condominiums?”
    0:16:26 And he turned white and I could see the like, “Oh my God, who are we getting in business with love?”
    0:16:31 I was going to say, “He hadn’t been briefed.” And I said, “No, no, Jean-Marie, I’m just kidding.
    0:16:37 We would only build 10 stories.” But he still went through with the deal. And so we had five
    0:16:45 wonderful years with them as our 51% shareholder until they were forced to sell our stake. But it
    0:16:49 was the thing that actually allowed us to acquire a business. So it’s a big deal. I mean, it’s really
    0:16:53 uncharacteristic for a company like this with a founder really of the modern business and then a
    0:16:57 CEO like you to be willing to sign over control. So that story to me makes a lot of sense if you’d
    0:17:05 said 49%. What was it about that deal that made you willing to literally sign up? Because it
    0:17:09 worked out well with that. Was it a pretty big risk at the time or not? I didn’t really think I
    0:17:16 was selling control. I think I was selling 51%, but I thought they really know nothing about video
    0:17:22 games. What are they going to do? And I don’t think they’re going to interfere all that much. I was
    0:17:26 actually wrong. They didn’t really have, you know, it’s like a corporate holding company. So they
    0:17:32 were always trying to justify their value as a corporate holding company. And you know, we had
    0:17:38 like, I remember the, and Lucien who’s here will attest to this is exactly what happened. But
    0:17:43 they said we’re having a synergy meeting and all the business unit heads need to come together
    0:17:50 for the synergy meeting. Now they own a stake in Morocco telecom. We didn’t do business in Morocco.
    0:17:56 They own SFR, the French telephone company and mobile games wasn’t really a thing at that time.
    0:18:01 They own Canal Plus. So a French TV network didn’t really have any applicability and
    0:18:06 universal music where we did license some music for Guitar Hero, but other than that we had no
    0:18:11 relationship and a broadband company in Brazil. So we all get together and have this big synergy
    0:18:15 meeting. And then we had to go around the room and say the synergies that we identified between
    0:18:23 each other. And they got to me and I said that Morocco telecom, we went to their cafeteria
    0:18:30 and they have tagine. And we got the tagine recipe for our cafeteria,
    0:18:42 which I thought was a great synergy because I like tagine, but there wasn’t really that much
    0:18:48 synergy. So then they had to sell us back their stake. And then it was completely unwinding,
    0:18:53 ultimately. And I guess they completely unwound in their own way. And everybody did well.
    0:18:57 So it turned out. So give us a kind of a state of the video games industry today,
    0:19:03 gigantic global phenomenon, lots and lots of change and flux, lots of potential controversy.
    0:19:09 So I would say of the 28 years I’ve been doing Activision, 30-some-odd years I’ve been doing
    0:19:16 software, I’ve never seen more opportunities than exist today. Markets that are opening. And you
    0:19:22 think just 10 years ago, if you wanted to play video games, you either needed $1,000 PC or $300
    0:19:27 or $400 video game console. And there really weren’t any other ways to play video games. But
    0:19:34 phones have ushered in this whole new opportunity. And like for years, for most of the tenure that
    0:19:41 I’ve had as CEO, we sold in developed countries to middle-class consumers on expensive devices.
    0:19:47 Today, we sell in 196 countries around the world. We have 400 million customers.
    0:19:56 And anyone in any socioeconomic strat can actually play games. I think that was the biggest shift
    0:20:01 that took place is now you truly have a global market. The second thing that then happened is
    0:20:08 when you started to see the games become more social experiences. I can use a headset. I can
    0:20:12 talk to the person I’m playing with. I can play with somebody from anywhere around the world.
    0:20:19 The introduction of the social experience was the true transformation to me of the opportunity.
    0:20:24 And so where you look out in the world today, you have a global audience. You have this ability
    0:20:31 to create this true social experience. And I remember years ago hearing this, and I’ll paraphrase,
    0:20:36 but Mandela had this definition of sport, that it was the great equalizer. And it was this thing
    0:20:42 that allowed you to actually break racial barriers and religious barriers and economic barriers in
    0:20:48 order to foster competition and that the great competitors in sport could come from anywhere.
    0:20:53 And everybody felt this ability to have a sense of belonging and purpose and meaning. And that
    0:21:00 is what video games has become for so many people. And it’s hard to illustrate this for some people,
    0:21:05 but I was at a panel not long ago with Alex Rodriguez, who actually owns one of our Overwatch
    0:21:13 team franchises, and Roger Goodell, who is the NFL commissioner. And the moderator said, “Are eSports
    0:21:20 sports?” And I said, “The same characteristics that Mandela described, what makes sport great
    0:21:26 is what makes eSports so compelling and engaging.” And I said, “To Alex, stand up.”
    0:21:34 And Alex stood up and I said, “Look at you. How many people in the world can play professional
    0:21:38 baseball?” And he said, “Well, there are roughly 1,200 professional baseball players in the
    0:21:45 Major League Baseball and about 3,000 capable of playing Major League Baseball.” And I said,
    0:21:52 “Look at this guy. Like this is like the most fit athletic specimen of a human on the earth.
    0:21:58 And there are only 3,000 of those people who can do what he does. Video games is the only
    0:22:03 competitive medium that is going to give me that experience and that purpose and that sense of
    0:22:07 belonging and that camaraderie that you get from sport.” And so, of course, it’s going to be
    0:22:13 as popular as sport, if not more popular than sport. And that, I think, more than anything, is now
    0:22:19 what we see as driving consumption and engagement and interest and passion. And we’re just scratching
    0:22:24 the surface of opportunity. So I think people have obviously had a lot of great experiences
    0:22:27 and a great faith in the video game industry for many years, based on the idea that everybody
    0:22:32 can participate. This idea that people are going to voluntarily watch other people playing video
    0:22:37 games is a new idea. And obviously it’s becoming a twitch and one of our companies and so forth.
    0:22:42 Like this is going to be a very big phenomenon. It’s a key part of eSports is the ability to
    0:22:45 fill an arena with people watching other people play video games. Like a few years ago,
    0:22:50 that just sounded wildly implausible. What was the point? Like, when did you figure that out?
    0:22:55 Well, I think probably when we launched. I didn’t own Blizzard at the time, but when Starcraft
    0:23:00 launched, this was a game that in Korea, I think at the height of its popularity. Rob’s here,
    0:23:05 so he’ll know the exact number. But I think, you know, this is more than a decade ago, but the
    0:23:11 height of its popularity in Korea, Starcraft had 5 million registered players. Now this is a country
    0:23:18 of 60 million people. The game is primarily a male game experience. And so you think about 20% of
    0:23:24 the population actually of the male population played, or was a registered player of Starcraft.
    0:23:30 And we saw arenas getting filled with spectators. There were three dedicated cable channels in
    0:23:34 South Korea that just broadcast Starcraft competition. There were sponsors. There were
    0:23:40 professional players making $100,000 or more. So this is an amazing phenomena that took place that
    0:23:45 we looked at as purely marketing. You know, the people are enthusiastic. We saw the box. There was
    0:23:51 nothing more to it than that. And we managed to do every single thing wrong in commercializing the
    0:23:58 eSport of Starcraft. But it was the first time where I really thought, you know, there’s something
    0:24:04 that could even be bigger than the games themselves that would relate to the spectator experience.
    0:24:10 Now, even with games like Overwatch, which is probably our most successful eSport initiative,
    0:24:16 it’s more like golf. So if you’re a spectator of Overwatch, it’s likely you’re a player of
    0:24:24 Overwatch. Fortnite, I think, was the first game where people would spectate and it would actually
    0:24:30 be a catalyst for them to play. And so I think what’s happened is it’s more of a social experience
    0:24:35 in a lot of respects than it is just a game. But I think that what you’re now starting to see is
    0:24:41 that games have so infiltrated the popular culture of the world that it’s exciting for people to watch
    0:24:45 their heroes who compete against each other in the same way as sport.
    0:24:50 Right. So many of the most successful games that people watch or that are now actually
    0:24:53 formerly eSports, correct me if I’m wrong, they were not originally designed for this
    0:24:56 period. They were designed to be games that people just played and they’ve been kind of repurposed
    0:25:00 into this kind of broader public phenomenon. Maybe that’s to play untrue, but I guess my question
    0:25:06 is kind of how will video games be designed going forward for eSports and for people watching it in
    0:25:10 addition to playing that is different than how video games have been designed up to this point?
    0:25:14 Yeah, that’s a great question. So a lot of the games today were not specifically designed for
    0:25:21 spectating, which is why you end up with that phenomenon of the players are the spectators.
    0:25:29 In order to have a more broad appeal spectator experience, the games need to be designed in a
    0:25:33 way that you actually want to watch them, whether you do or don’t play them. And I would say that
    0:25:40 the Overwatch team spent a lot of time early on trying to construct a game from the ground up
    0:25:45 that would be a fun spectator experience. But I think what you will see is that people are now
    0:25:51 paying more attention to in game design, the idea that the games may be spectated by people who
    0:25:56 aren’t players. I don’t think anytime soon that’s going to be the primary consideration. We’ll still
    0:26:05 be principally focused on gameplay, but things like camera angles and commentating and making sure
    0:26:10 like when we organized the Overwatch League, one of the organizing principles was the reason why
    0:26:17 sports are so successful is tribalism and that having a local affiliation was so crucial to the
    0:26:22 success of sport, whether it’s a country affiliation or city affiliation. So we created a structure
    0:26:29 that allowed for 28 independent cities to field teams. And I think that as you start to take those
    0:26:34 considerations into play when you’re thinking about the design of the games or the leagues or the
    0:26:39 competitive experience, that they will have more of the characteristics of traditional sport.
    0:26:42 Right. Would you venture a guess as to when video games will be in the Olympics?
    0:26:46 Which is a logical implication of what we’re discussing, right?
    0:26:51 I don’t think so. I actually don’t think like the Olympics has never been about
    0:26:57 a commercial enterprise. And so if you think of the analog, right, there’s not like if you had to
    0:27:04 pick a game, you’re now endorsing someone’s commercial enterprise. You know, there’s not any,
    0:27:11 there’s they don’t have that analog today. And so I don’t know that you could see the logical
    0:27:16 jump to the Olympics. Okay. The video game industry seems to have a particularly cute version of a
    0:27:21 dynamic that you see with, you know, let’s just say consumer properties that inspire an avid fandom.
    0:27:24 So it’s the enthusiastic early adopters, right? And so you see this with movies,
    0:27:28 you see this with TV shows, you see this with basically things that really occupy the popular
    0:27:33 imagination. You know, for sure see it with video games. So you’ve got this kind of leading edge,
    0:27:38 you might say early adopters slash super enthusiastic user base, and they start to develop
    0:27:42 opinions and they start to develop opinions that maybe the people who make the games are quite
    0:27:46 doing what they want. And then when things, you know, really go sideways, there can be, you know,
    0:27:50 protestant boycoss and all kinds of like, you can end up with the inmates running the asylum or at
    0:27:54 least looking like they’re certainly trying to, how do you throw the needle as somebody who make
    0:27:58 an overseas letters? How do you how do you throw the needle for the early adopter base as opposed to
    0:28:02 the mainstream? And how much is the early adopter base an asset? How much is the early adopter base
    0:28:08 a challenge, a problem? So I think that the difference between film or television, you know,
    0:28:14 a great film, you’re going to spend two hours of your life watching. You know, great TV shows,
    0:28:20 it’s going to be 13 episodes or 22 episodes a season. You know, it’s going to be 13 or 22 hours.
    0:28:28 Video game, our average duration of gameplay that includes games like Candy Crush is an hour per
    0:28:36 person per day. Games like Call of Duty or World of Warcraft are hours a day. So the interest in
    0:28:41 the engagement and the commitment that you’re making to that form of media is so different
    0:28:50 than film and television. In my view, you have the right to have a strong opinion and voice your
    0:28:56 opinion in exchange for making that hour plus commitment a day, which becomes more of a lifestyle.
    0:29:02 And so instead, you know, I think some companies run and hide and don’t really engage their user
    0:29:08 base. But I think we have users and players who will and audience members who will tell you
    0:29:14 and give you really good insight into how you can modify and adapt your game. So you listen to
    0:29:20 them and they’re not always right. But oftentimes they’re pretty and especially when you hear the
    0:29:27 sort of the mass view, they’re pretty right. The beauty of our business though is that if you
    0:29:31 can get out in front of it early, let people actually have an experience with the game,
    0:29:36 get the feedback and you’re willing to take that feedback and enhance and improve and modify the
    0:29:40 games. It’s a great roadmap for innovation. So I’d like to ask you about two games that I think
    0:29:44 are arguably transformative from a conceptual standpoint for gaming. And you tell me what
    0:29:48 you think or maybe describe what you think are the structural significance of each of these.
    0:29:52 And so the first is Fortnite. And you alluded to one of the dramatic changes. So maybe describe
    0:29:57 like what is the significance of Fortnite to the industry? So for starters, there’s this perception
    0:30:02 that Fortnite is an overnight success. It’s not epic. The company that made it has been in the
    0:30:07 video game. Tim has been in the game business almost as long as I have been. And they are excellent
    0:30:15 at making games. And what they did was to really spend the time in a very focused, determined way
    0:30:20 taking the Unreal Engine and turning it to something that was going to be a broad appeal,
    0:30:25 very compelling social experience. And I think the aspiration was build the social network that’s
    0:30:32 anchored in a game conceit. And they made it cross-platform in its playability. They made it
    0:30:39 very accessible. They changed the way that they deliver content to season. So moved from the
    0:30:45 feature film model to the serialized television model. And it’s really fun. And they managed to
    0:30:52 do what you probably can’t do intentionally, but capture the popular cultural zeitgeist.
    0:30:58 And the other thing is that it doesn’t require you to make a two hour a day investment. You know,
    0:31:04 you can have a 20 minute experience that is really satisfying. But this is not accidental. You know,
    0:31:08 these guys have been doing this for a very long time. And I think what it has started to do is
    0:31:14 broaden the appeal of games to people who might never have played games before.
    0:31:17 And then what is the significance of Pokemon Go? And by the way, for people who don’t actually
    0:31:21 just saw this yesterday, Pokemon Go, third party report. But the report was revenue last month was
    0:31:26 still in the order of $75 million. So it’s still something like a billion dollar a year revenue
    0:31:30 business today. And this is where the game is now what, two years old or something like that.
    0:31:31 Almost three years.
    0:31:34 At least rumor has it that they have new stuff coming. But it’s been a giant hit.
    0:31:38 Again, it’s like, where’s the innovation there? But it’s like, you know,
    0:31:44 Nintendo is really great at innovations that are very physical in their nature. So the Wii,
    0:31:50 that moment I was describing to you about the Macintosh, when I first saw the prototype of the
    0:31:57 Wii, it was like that equivalent goose bump moment. I was in Kyoto and I went into his room
    0:32:04 and there was a TV and it wasn’t like an LED. It was an actual tube TV. And there was a pond that
    0:32:10 was on the screen, like a little cartoon pond with little bubbles popping up from every once in a
    0:32:15 while. And the head of Nintendo at the time was a guy named Iwata-san. And he gave me the controller.
    0:32:19 And I held the controller and I just started going like this. And all of a sudden you could feel
    0:32:26 the tension of the controller and the motion control of the controller. And I started to like
    0:32:31 fish around and I grabbed the fish and I pulled the fish out. And I thought that video games
    0:32:38 will be completely transformed. Nothing had really taken the physical experience in video games to
    0:32:45 that level. And I think that what Pokemon Go did is something very similar. But it created this
    0:32:52 physical experience that I think it was the first time AR had been executed on a broad scale.
    0:32:59 And so I haven’t seen anything in gaming that I would tell you has really captured the imagination
    0:33:06 of people on a broad scale using AR besides Pokemon Go. But I would say when you look at
    0:33:09 where some of the next big innovations in gaming, including what we’re working on,
    0:33:15 AR is going to have more near-term impact than VR. Amazing. Okay, good. And then final closing
    0:33:19 question. What’s the one Activision game that has come out this year that people really have to
    0:33:24 play? And then I know it may pain you, but I’m going to ask you, what’s the best non-activision game
    0:33:29 that has come out this year that people really have to play? So I would say Call of Duty Blackhouse
    0:33:35 4, which we just released, the blackout mode of Call of Duty Blackhouse 4 is so incredibly fun to
    0:33:40 play. And what is that? What is that mode? It’s like a PUBG mode. It’s like a battle royale mode.
    0:33:47 And it’s super fun to play. And you can do it in like small 25 minute increments, but very accessible,
    0:33:53 very fun to play. I haven’t played Red Dead Redemption yet, but I want to. And I would say of the things
    0:33:59 that have come out this year, I think it looks like Westerns are very hard to do because they’re
    0:34:04 very American in their field. But the game looks fantastic. And everybody they know has played
    0:34:08 it. Is that a lot of fun playing it? Yeah, fantastic. And I think we have party favorites. We brought
    0:34:11 Call of Duty for everybody. Call of Duty. So I believe everybody’s going to have a copy of Call of
    0:34:18 Duty. Bobby, thank you so much. Mark, thank you very much.

    Bobby Kotick is the CEO of Activision Blizzard (a merger he engineered); it’s one of only two video gaming companies in the Fortune 500, and the largest game network in the world. The company is responsible for some of the most iconic entertainment franchises, including Call of Duty, Candy Crush, Overwatch, and World of Warcraft — as well as its own professional esports league.

    So in this episode of the a16z Podcast, Marc Andreessen interviews Kotick on everything from the evolution of video games in the 1980s to gaming trends more broadly. What changes as gaming goes from ”just for nerds” to ”just for kids” and spreads more broadly into entertainment and cultural phenomena (esports, Fortnite, Pokemon Go, etc.)… both online and offline?

    The conversation originally took place at our annual innovation a16z Summit in November 2018 — which features a16z speakers and invited experts from various organizations discussing innovation at companies small and large. You can also see other podcasts and videos from this event here: https://a16z.com/tag/summit-2018/

  • a16z Podcast: Who’s Down with CPG, DTC? (And Micro-Brands Too?)

    AI transcript
    0:00:06 Hi everyone, welcome to the A6NZ Podcast. I’m Sonal. Today is part of our ongoing series
    0:00:12 on consumer tech trends. We’re talking all about the category of consumer packaged goods
    0:00:18 or CPG and where this fits with what’s going on in online and offline commerce trends overall,
    0:00:23 including when it comes to the grocery business. We also talk about the trends of DTC or direct
    0:00:29 to consumer and the concept of micro or emerging brands as well. Joining us to have this conversation,
    0:00:34 we have A6NZ General Partner Jeff Jordan, who’s written a lot about competing with Amazon and
    0:00:38 the future of e-commerce and marketplaces and has been on the front lines of this area both as
    0:00:43 an operator and investor, witnessing firsthand from many angles a lot of changes in the industry.
    0:00:48 And then we also have Ryan Kahlbeck of Circle Lab, an investment platform powered by data and
    0:00:53 technology. He also talks a lot about innovation in the CPG space and more, which is why we
    0:00:58 invited him to join this discussion. Please note that the content here is for informational purposes
    0:01:03 only should not be taken as legal business tax or investment advice or be used to evaluate
    0:01:09 any investment or security. It’s not directed at any investors or potential investors in any fund.
    0:01:15 For more details, please also see A6NZ.com/disclosures. The broader question that we covered throughout
    0:01:21 this episode is how does technology and especially the internet change and in some ways not change
    0:01:26 the way we do things. Why do some of the traditional businesses in these industries, though full of
    0:01:32 some of the smartest people, have trouble innovating and can tech really help? In fact, that’s where
    0:01:37 we begin the conversation with the assertion that it’s been hard to bring tech to CPG, even though
    0:01:45 there seem to be a lot of products trying out there. As a user, I have a hard time perceiving this
    0:01:50 because I am constantly bombarded with consumer products that are techie, whether it’s like
    0:01:54 a thousand beauty product lines, there’s a thousand even generics lines that I’m getting hit with.
    0:01:58 So I have a hard time grokking that this is a reality. Tell me what’s happening there.
    0:02:05 It’s a great point. So I think, first, one of the reasons that you see that is the D2C movement,
    0:02:11 which is direct to consumers. A handful of tech VC firms, they’re putting a fair amount of money
    0:02:17 into consumer product companies that sell just direct to consumer or predominantly direct to
    0:02:23 consumer. That money is usually not used for innovation, for product innovation. It’s usually
    0:02:28 used for marketing. I agree with Ryan that they’re largely marketing companies. It’s actually
    0:02:32 derivative of Amazon, unfortunately. If you want to play any e-commerce in a post-Amazon
    0:02:37 era, you cannot sell what Amazon sells successfully. I mean, early on, we tried a number of concepts
    0:02:43 that some are around anymore that said, okay, I can kind of sell the same thing as Amazon with
    0:02:47 a different distribution twist with something like this, but you can’t. So then the next wave
    0:02:52 of companies was, okay, if I can’t sell, I can’t compete with Amazon directly skew by skew,
    0:02:58 let me get proprietary skews. And so they’re formulating different products with different
    0:03:05 branding, and they typically aren’t on Amazon or on other retail. But that is where a lot of the
    0:03:11 direct to consumer stuff is happening. And frankly, some success, not a ton of success
    0:03:14 in doing it. Why is that, by the way? At some point, you’re still competing with
    0:03:21 legacy players. And what’s worse is they’re also competing with each other. So there are a half
    0:03:29 dozen, a dozen brands all trying to find you. Early on, they find you at $20 acquisition cost
    0:03:34 when 10 of them go at each other. They’re competing for you, 10 companies trying to grow,
    0:03:39 competing for you. And then that also caps their ability to price. So one of the big
    0:03:44 secrets in e-commerce is virtually no companies get big and make money in the United States on
    0:03:51 e-commerce. I can name five e-commerce companies in the US after two decades of investing and
    0:03:56 God knows how many tens of billions of dollars who are a billion dollars in sales and profitable.
    0:04:01 Yeah, I mean, you’re making the point, particularly around the rise in CAC. We see a lot of
    0:04:07 DTC companies raise money with a CAC, let’s call it $10, $30. And then over the course of
    0:04:13 subsequent two years, it raises literally sometimes by an order of magnitude. And that is just killing
    0:04:17 their profitability. And by that, just to quickly summarize, you mean CAC is on customer acquisition
    0:04:20 costs and they’re using all that marketing dollars to acquire their customers.
    0:04:26 Exactly. I think when DTC directed consumer businesses, I think a lot of folks look at it
    0:04:31 from the outside and say, okay, we’re stripping out the middleman, the retailer, the offline
    0:04:36 retailer. And because of that, we can put that margin that the retailer gets into our business.
    0:04:40 And this is going to be a wonderful business. The problem is that you need to attract people to
    0:04:47 your site, right? To get people to come to your startup, to come to your URL and buy something
    0:04:51 is a really difficult thing. And so that’s what’s driving these customer acquisition costs up.
    0:04:55 Now, there are some DTC companies, Native Deodorant was bought. They only raised
    0:04:59 two or three million bucks in total, sold for $100 million to Unilever.
    0:05:03 Why did Unilever want to buy that company? Why wouldn’t they just make their own in-house brand,
    0:05:09 another brand? The CPG companies, large ones, have lost the ability to innovate. They innovate
    0:05:13 through acquisition now and they buy early. So Unilever bought Dollar Shave Club. Unilever
    0:05:18 doesn’t have a shaving business. I don’t know Unilever Deodorant offerings, but I’m guessing
    0:05:24 they saw something in there. So it and Biotech are kind of the same. The big pharma companies are
    0:05:28 buying their innovation. The big CPG companies are buying their innovation. Historically,
    0:05:34 large CPG has been able to rely on their brands. Brands that have existed literally in some cases
    0:05:40 for 50 or 100 years. Meg, Scott Cook, and Brian, Sweetie, and Steve Ballmer, we’re all at P&G
    0:05:45 together. Right after I graduated from college, Meg was the brand manager, I believe, on Crest.
    0:05:52 Wow. That’s awesome. But can you think of that cadre of talent in all analysts in Cincinnati?
    0:05:56 CPG seems like, because I have a lot of friends that go through their career starting at Clorox.
    0:05:59 And it seems like sort of a training, there’s always like a mafia and a training ground that
    0:06:02 people get some fundamental skills in these companies. So what are they actually getting
    0:06:06 out of these companies? There’s a quote in one of the Apple movies, if you can sell sugar water,
    0:06:12 you can certainly sell. That was Steve John’s quote, like he tried recruiting John Scully.
    0:06:16 I think there’s probably something to that, right? To be able to sell literally the same product
    0:06:19 for 30 years in a row. Think about trying to do that in the technology space. That’d be
    0:06:26 impossible. There’s a fun book by a Harvard dean called Different. And it basically says,
    0:06:31 almost all consumer goods are these small incremental improvements that everyone copies
    0:06:38 because that’s the improvement that wider mouths on the Crest toothpaste because that you go through
    0:06:44 it faster. Oh, so Colgate will do wider mouths and Spearman and whitening and versus brands that
    0:06:50 kind of just throw it out and just do it differently. She uses Harley. She uses Apple. She uses Red Bull.
    0:06:56 And they just came to market with completely, we are going to be different. And it’s so interesting.
    0:07:02 I love the book because 99% is exactly the same. And then the 1% is different.
    0:07:05 That gets back to the point of like why these large brands are losing market share.
    0:07:11 The large brands have not had to innovate. They’ve been able to rely on their brands on,
    0:07:16 whether it’s Coke or Pepsi or whatever it is, the same product, just their brand name for decades.
    0:07:22 Now these smaller upstart brands, these emerging brands are able to develop the innovation in
    0:07:27 house and deliver that to the consumer. The consumer, on the other hand, for the first time
    0:07:32 in history is saying, I demand products that meet my unique needs. Maybe the three of us used to
    0:07:37 eat the same breakfast cereal. Now the three of us are eating different things. We’re demanding
    0:07:43 products that meet our unique needs. That customer consumer demand is pulling forward the innovation
    0:07:46 and giving it a market. That’s why though, I just want to push a little bit more on this DTC topic
    0:07:51 though, because when I think of the theory of the internet, which, you know, it disintermediates this
    0:07:56 intermediary, you can go direct to people, you create movements on the internet. I mean,
    0:08:00 talk about meme culture. Like if a meme can monetize, why the hell can’t a product?
    0:08:03 So I’m still having a hard time buying why DTC is so hard.
    0:08:07 The internet enables a long tail. So all of a sudden everything’s discoverable,
    0:08:11 where it used to be, there were three television networks and 10 magazines that mattered.
    0:08:18 The world is different. It used to have, you know, very narrow portals to work, which was great for
    0:08:25 big companies that have stable product lines. So you couldn’t do TV on a $5 million revenue line.
    0:08:29 You can do internet on a $5 million revenue line. Right. But that’s exactly my point,
    0:08:33 is we have a world where we do have a long tail discoverability. You have the ability to access,
    0:08:38 find your niche audience. You also have a world where you can still make hits on that long tail.
    0:08:42 So you just describe why there’s a proliferation of CPG companies.
    0:08:45 But why does DTC not work? That’s a part I don’t get.
    0:08:49 When we say it doesn’t work, I think it is an incredible channel for iterating on a product.
    0:08:54 I think it drives innovation. I can find my consumer base and I can test a new product.
    0:08:57 Next month, I can test a different product. That’s very different than the offline world,
    0:09:00 where if I’m selling into Safeway or Whole Foods or Costco down the street,
    0:09:05 it’s hard for me to switch the product out if it’s not working, to tweak a package, whatever it is.
    0:09:09 People in the technology space take that kind of A/B testing for granted. In CPG, it’s much,
    0:09:12 much harder because you literally… Because it’s physical product and offline space.
    0:09:14 Yeah, you have atoms, you need to move, not just bits.
    0:09:18 And so if you run a chain of stores, actually a couple of my… All the companies that are
    0:09:23 getting challenged growing, continuing to grow DTC sales are turning to offline retail in different
    0:09:27 forms. Every company I’ve worked with is trying to do that because incremental sales…
    0:09:29 That’s actually rather counterintuitive.
    0:09:33 It is. But the way store management work, I used to be CFO of the Disney store, is
    0:09:40 you try products. Typically, you do two or four sets a year and you try products in a
    0:09:44 significant subset of your stores because if it’s a bomb, you don’t want to buy
    0:09:48 deep in it. So you’ll put it in five stores a test for the first six months.
    0:09:52 And then they say, “That worked well. Let’s go to 50 stores for the next six months.”
    0:09:56 And then by the time you get chain-wide, it literally is a couple of years later.
    0:10:00 And so it’s really hard to grow your business.
    0:10:03 And that’s for Disney stores where you have your own product in the store.
    0:10:09 So if you think of the CPG products, they’re selling through a third party, the retailer.
    0:10:14 Now, they have to make a much bigger bet. They can’t usually just start in five safe ways.
    0:10:18 So they have to start in 200. Now when you start in 200, flipping that and changing that product,
    0:10:21 if it didn’t work, it can kill the company.
    0:10:26 When I was at Xerox PARC, one of the companies we partnered with was a large CPG company.
    0:10:30 And their number one challenge was trying to figure out what happens after the consumer
    0:10:33 buys the product. They had zero insights.
    0:10:35 Oh, actually, it’s even worse. They have zero insight.
    0:10:40 They know what they sell into the retail chains. They don’t know what’s sold where to who.
    0:10:41 Right. Seriously?
    0:10:41 No. It’s incredible.
    0:10:42 It’s absolutely incredible.
    0:10:44 That’s great. That’s crazy. How is that not possible?
    0:10:47 So people who are listening to this will respond, “Well, what about credit card data?”
    0:10:50 The problem with credit card data is it can tell you what the retailer is selling,
    0:10:51 not what was bought at the retailer.
    0:10:54 So I can see what Nordstrom.com sales for last month.
    0:10:56 I can’t see what pairs of jeans were bought there.
    0:10:58 Why not? Doesn’t it say?
    0:10:58 They don’t sell.
    0:11:00 Isn’t that the whole point of a skew?
    0:11:03 No. Well, yeah, but these credit card companies don’t sell it.
    0:11:08 And more importantly, back to Jeff’s point, they don’t tie those products to individual people.
    0:11:16 Some retailers have loyalty card data, but there’s privacy issues with them selling that.
    0:11:22 $84.51, a division of Kroger sells part of it, but not in the way that we’re talking about here.
    0:11:26 They can say, “This person who I can, by the way, I can match Sonals,
    0:11:29 what her purchasing power to your Instagram account, that is not done anywhere.”
    0:11:33 Typically, CPG marketing is you buy a circular in the Sunday paper.
    0:11:35 You buy an end cap, and you have no idea–
    0:11:37 An end cap being the little display at the end of the grocery store.
    0:11:38 At the end of the aisle in the grocery store.
    0:11:42 And billions of dollars goes into those, and who knows if it works.
    0:11:48 And they certainly don’t have any data beyond, “Oh, our total sales went up a little bit there.”
    0:11:53 One of the key things that was compelling about Instacart to us is that they have a revenue
    0:11:56 stream from the consumer, a revenue stream from the grocery retail partner,
    0:12:00 and a revenue stream from CPG companies who are interested in accessing the consumer.
    0:12:04 Why the CPG companies were so interested in that is,
    0:12:06 it’s the first performance marketing they’ve ever seen.
    0:12:09 On something like Instacart, they know everything I’ve ever bought.
    0:12:15 And if they know I love Heineken beer and the product manager of Stella wants to try to convert me,
    0:12:19 they can give me a Stella coupon, a Stella samples, a Stella, everything else.
    0:12:21 And then see, did I change my behavior over time?
    0:12:23 That’s the holy grail of marketing.
    0:12:24 The holy grail for marketing.
    0:12:26 I mean, performance marketing, like that type of data,
    0:12:29 like closing that feedback loop is a big F-deal.
    0:12:34 They also over time have the ability to kind of literally move the product on the page, right?
    0:12:36 Which if you think about offline retail, you can’t do.
    0:12:38 What do you mean by on the page?
    0:12:43 Meaning when you’re looking at Instacart, what product you’re looking for can be moved physically.
    0:12:47 Oh, like kind of personalized rearrange to your needs.
    0:12:47 Exactly.
    0:12:48 Which you cannot do in a physical way.
    0:12:50 And it’s completely obvious in tech.
    0:12:52 But for people that are in CPG, it’s a game changer.
    0:12:57 So I was in a Safeway half a mile from here on Sand Hill six months ago,
    0:12:59 and was buying some steak.
    0:13:01 Steak was in the refrigerator.
    0:13:04 Next to the steak in the refrigerator were wood chips.
    0:13:06 The wood chips have no need to be refrigerated.
    0:13:08 They’re literally just wood chips to put in a barbecue.
    0:13:11 They’re in the refrigerator because they’re on sale.
    0:13:13 And they want to put them next to the steak.
    0:13:14 That’s it.
    0:13:16 And so you’re refrigerating literally wood.
    0:13:17 That’s crazy.
    0:13:19 Because back to Jeff’s point, if I bought an end cap,
    0:13:21 the end cap would have been 30 feet away.
    0:13:23 Then you would have lost the consumers.
    0:13:24 And they need to have that proximity.
    0:13:26 That’s a crazy awesome example.
    0:13:27 I love that.
    0:13:30 Let’s talk about grocery for a little bit as an interesting category.
    0:13:35 So first of all, is grocery going to go the way of malls and other retail?
    0:13:37 So I’ve got a not very popular opinion on this.
    0:13:38 Let’s hear it.
    0:13:39 The more popular, the better.
    0:13:43 I think grocery stores are here for the very, very long term.
    0:13:46 Very long term, meaning next 20 years at least.
    0:13:50 So taking a step back, D2C and e-commerce has been around for 20 plus years.
    0:13:52 This is not a recent phenomenon.
    0:13:55 Food is still, Jeff, you could tell me, I think 5% of sales.
    0:13:56 Of digital?
    0:13:56 Yeah.
    0:13:57 Way under.
    0:13:58 Yeah.
    0:14:02 I don’t foresee a world in which everyone is just going to go online, A.
    0:14:07 And B, when that happens or when it gets to be a much higher proportion of where you buy
    0:14:13 your groceries, I still think that that grocery is going to be delivered locally.
    0:14:18 But the core point is grocery today, 2%, 3% net margin business.
    0:14:21 That’s hard to strip out a lot of costs from that.
    0:14:21 There’s not a lot of room left to go.
    0:14:23 You can’t do any cost cutting at all.
    0:14:23 That’s right.
    0:14:29 So you think about where technology has been particularly successful at killing other industries.
    0:14:32 They tend to be industries where there’s a fair amount of profit, right?
    0:14:35 It’s also like Bommel’s cost disease, too, if you think about it, eventually penetrating
    0:14:39 health care and education, like things that are way more expensive than they need to be.
    0:14:41 And technology is a vector to just cut right through that.
    0:14:42 Absolutely.
    0:14:46 But the safety down the street has a 1.5% net margin.
    0:14:48 So what are we going to do to rip the cost of that?
    0:14:52 Because that thing is already delivering a pretty good product to the people that live within a
    0:14:53 mile and a half of here.
    0:14:57 I mean, there was a set of companies that was trying to help physical retail compete
    0:14:58 with the digital commerce.
    0:14:59 And it was so interesting.
    0:15:04 We didn’t invest in many of them at all because our internal reference was we’re shorting the
    0:15:05 future.
    0:15:08 You know, just so it’s not a long-term winning proposition and their margins are going to
    0:15:10 get squeezed, so they’re going to squeed their vendors.
    0:15:13 Then we made the Instacart investment in the belief that the grocery stores are there.
    0:15:15 It’s distributed.
    0:15:17 They have distributed little warehouses.
    0:15:18 They provide service.
    0:15:19 And it was interesting.
    0:15:22 Fred Smith, the founder of FedEx, when the internet first came up said,
    0:15:26 “I think a whole lot of goods are going to be delivered by FedEx.
    0:15:27 Groceries ain’t going to be one of them.”
    0:15:32 Because the concept that you’re going to load a truck in the morning and having
    0:15:36 bouncing down the streets and this and that and deliver at 8.
    0:15:40 It’s something at 8 p.m. that was put in the truck at 4.30 a.m.
    0:15:42 And he just said, “I don’t think it works.”
    0:15:47 Building up the shopper network is so hard to replicate for someone else going forward.
    0:15:50 It’s not as simple as, “Let’s just hire FedEx to go do this thing.”
    0:15:54 Oh, and the operational intensities observe.
    0:15:58 We think in grocery, we think effectively there are a couple different dimensions
    0:15:59 that grocery chains need to compete on.
    0:16:01 We think it’s assortment.
    0:16:03 We think it is convenience.
    0:16:05 We think it is pricing and experience.
    0:16:07 Pricing is a really, really hard place to compete on.
    0:16:10 You’re competing with Amazon to a point that Jeff made earlier.
    0:16:12 You’re competing with Walmart.
    0:16:14 I think that’s just a really, really hard place to win.
    0:16:15 Yeah, you can’t win on price.
    0:16:18 Especially when you already have this 1% to 2% margin.
    0:16:20 Exactly. The margins are already so low.
    0:16:22 So let’s put pricing aside for a second.
    0:16:28 I also think that grocery is, in some ways, an experience for some people.
    0:16:33 An experience for the consumer to go in, perhaps with the family,
    0:16:36 perhaps just buy a couple of things here and there.
    0:16:38 They want the immediacy of that.
    0:16:41 We don’t see that going away anytime soon.
    0:16:43 I think it’s going to be hard to win, again,
    0:16:47 because how do you invest into an experience if you have such low margins?
    0:16:49 I will say one quick sidebar on experience,
    0:16:50 such as if Connie were in this room,
    0:16:52 she talks a lot about what happens in China.
    0:16:55 And she talks about this incredibly fascinating phenomenon
    0:16:59 where grocery stores in China have become destinations themselves
    0:17:01 because there’s literally restaurants inside.
    0:17:04 They’re doing all kinds of neat food chef things, etc.
    0:17:06 Cooking on site, doing all these interesting things.
    0:17:07 I mean, what should you take on that?
    0:17:10 I was with the CEO of a large grocery chain about a month ago
    0:17:12 who made that same point.
    0:17:14 They are starting to experiment by putting restaurants,
    0:17:18 effectively restaurants, inside their grocery chain.
    0:17:22 The local Asian supermarkets almost all have restaurants forever.
    0:17:23 Indian ones, too.
    0:17:25 They have like samosas for $2.
    0:17:25 Yeah.
    0:17:30 I would say I think it is nice to have not a requirement to be successful.
    0:17:33 I’m not convinced that that’s going to be the core differentiator going forward.
    0:17:35 So what do you think is going to be the core differentiator?
    0:17:35 You had one more dimension.
    0:17:38 Well, convenience and assortment, those are the last two.
    0:17:40 So convenience, to me, is delivery.
    0:17:41 Delivery or in-store pickup.
    0:17:45 I think that that will end up being table stakes, not a nice to have.
    0:17:47 Meaning you need to have convenience.
    0:17:50 Well, my question on this is why bother even having a grocery store
    0:17:51 if you only need to deliver?
    0:17:53 Why not keep warehouses then?
    0:17:54 If experience isn’t going to win the thing.
    0:17:56 Like why not just have a bunch of warehouses
    0:17:57 that deliver food if delivery is the thing?
    0:17:58 Yeah.
    0:18:01 So to be frank, that could be the 50-year vision.
    0:18:02 That really could.
    0:18:04 In the UK, which for whatever cultural reason
    0:18:06 has been doing grocery delivery for a long time
    0:18:09 and it’s a much deeper state of penetration,
    0:18:11 they’re starting to have what’s called dark stores,
    0:18:14 where you basically, they look a lot like supermarkets.
    0:18:16 They’re locally distributed.
    0:18:17 They have inventory assortment,
    0:18:19 but they’re not in high traffic parts of town,
    0:18:22 which means the rents are much, much lower.
    0:18:26 And so, as a result, you don’t have to make it pretty.
    0:18:28 You don’t have to have the lights, lots of lights.
    0:18:29 You don’t have to have high labor.
    0:18:30 All you have to do is pick in them.
    0:18:33 And so that is how grocery has been developing
    0:18:36 in one of the most advanced digital grocery markets.
    0:18:39 So it’ll be interesting if whether that happens in the US,
    0:18:43 every argument that I can make on why grocery stores won’t
    0:18:46 just be warehouses where it gets delivered from,
    0:18:49 every argument that I can make is a short-term argument.
    0:18:51 I can’t make a 50-year argument for that.
    0:18:53 So I think that that could happen.
    0:18:55 Over the next 10 years, I don’t think customer adoption
    0:18:56 will be big enough to get rid of these stores.
    0:18:59 These stores, these aren’t little mom and pops.
    0:19:02 They’re Fortune 500 companies that would not go down
    0:19:03 without a really big fight.
    0:19:04 No, and I think there are destinations.
    0:19:06 I mean, I see like families on the weekends all the time.
    0:19:08 It’s like, it’s an outing to go to the grocery store,
    0:19:10 which if they had like a daycare,
    0:19:12 I think that would be a huge win, frankly.
    0:19:14 That alone would be a big differentiator.
    0:19:15 I would love that.
    0:19:16 I know, I think everybody would take that.
    0:19:18 I exclusively shop through Instagram.
    0:19:20 I do our family’s grocery because I can’t bring the kids
    0:19:23 to the grocery store because it’s too much of a disaster.
    0:19:26 So I believe that convenience will be table stakes.
    0:19:29 So then it comes down to what is the way grocery wins?
    0:19:30 What are the way grocery store competes?
    0:19:32 To me, it is just about assortment.
    0:19:33 That’s your fourth dimension.
    0:19:33 This is the fourth dimension.
    0:19:36 After price, experience, convenience, and now assortment.
    0:19:37 That’s right.
    0:19:40 Assortment is what are the products that are on the shelf?
    0:19:43 So if you think the last 80 years,
    0:19:46 it has been, well, what’s Pepsi gonna give us this month?
    0:19:49 Coke, General Mills, Unilever, Procter & Gamble, et cetera.
    0:19:50 Today, as we’ve talked about,
    0:19:53 consumers want brands and products to meet their unique needs.
    0:19:57 The problem with that is that the buyer at the retailer,
    0:20:00 meaning the person that selects, let’s say, the chocolate company,
    0:20:03 the buyer at the retailer is still the same buyer
    0:20:06 that lived there 20 years ago in some cases.
    0:20:08 They don’t use a lot of data.
    0:20:10 They’re literally trying chocolate bars
    0:20:11 to decide what goes on the shelf.
    0:20:13 That’s a really hard place to be in a market
    0:20:16 that is trillions of dollars
    0:20:19 to decide which of these emerging brands they want to work with.
    0:20:23 So the default is, gosh, maybe I just rely on the big brands
    0:20:24 to tell me who to work with.
    0:20:25 That’s a real example.
    0:20:27 Sometimes the big brands literally say,
    0:20:29 work with these emerging brands.
    0:20:30 Maybe I work with the distributor,
    0:20:33 who, by the way, has paid more than by the larger brands.
    0:20:35 But there isn’t really a good solution
    0:20:38 for a lot of these Fortune 500 retailers
    0:20:41 on how to optimize their assortment.
    0:20:45 The data that exists for these grocery chains is pretty poor.
    0:20:48 You’ve got a couple retail-level sales providers
    0:20:51 that on average track 20,000, 30,000 products,
    0:20:53 or companies, rather, each.
    0:20:56 There’s about a million and a half out there.
    0:20:58 A million and a half, and they cover less than 5% of them.
    0:21:00 And even the grocery and food shows, aren’t they?
    0:21:03 Sort of like, I’m thinking of the equivalent in fashion
    0:21:03 and boutiques.
    0:21:05 You essentially have a fashion show
    0:21:07 to curate all the brands, the emerging brands,
    0:21:09 the existing brands, new product lines.
    0:21:11 Why isn’t there an anthropology of grocery stores?
    0:21:13 Because when I think of anthropology as a retailer,
    0:21:16 they have assortment because they go around the world
    0:21:17 to find a variety of designs.
    0:21:20 So it works very well for a certain demographic of women,
    0:21:22 like in their 20s, 30s, et cetera.
    0:21:25 Then you have to say, which of these will my consumers
    0:21:27 respond to at the rate price?
    0:21:29 So you get exposed to the million,
    0:21:33 but then I can only carry X,000 in my store.
    0:21:34 How do I figure that out?
    0:21:36 Online might actually help,
    0:21:38 because you can put infinite selection online
    0:21:39 and see what’s selling.
    0:21:42 So if you’re a grocer, I’d be looking at my online sales
    0:21:44 just to inform my offline sales.
    0:21:46 Like, oh, wow, that’s a breakout hit online.
    0:21:48 Why wouldn’t it be a breakout hit offline?
    0:21:51 Interestingly, then, you might come back to a customer
    0:21:53 acquisition challenge for the CPG companies,
    0:21:56 which is if we have a ton of products online,
    0:21:57 how do we then stand out?
    0:21:59 That comes back into advertising.
    0:22:00 This kind of vicious circle.
    0:22:01 Or virtuous.
    0:22:02 Or virtuous.
    0:22:03 It’s a skewed sample, too.
    0:22:05 Like what happens online and offline sometimes.
    0:22:05 It’s definitely skewed.
    0:22:08 But if you’re in a complete information vacuum,
    0:22:09 which essentially these guys are, at least you have something.
    0:22:11 Even, by the way, loyalty cards are a really skewed sample.
    0:22:14 That’s a very self-selected, self-interested group.
    0:22:16 You’re not really getting the huge untapped space
    0:22:16 of what people want.
    0:22:19 You’re not, but you’re actually finally getting data
    0:22:21 on a per person basis to kind of understand what’s there.
    0:22:22 Exactly.
    0:22:26 It’s hard to understate how blind most buyers
    0:22:29 at most physical retailers are right now.
    0:22:31 Yeah, they’re just kind of, it’s instinct.
    0:22:33 It’s, you optimize the current assortment.
    0:22:36 But then how do you layer in new things is,
    0:22:38 and there’s a plethora of new things.
    0:22:39 Or just everything that you don’t know
    0:22:41 people have the taste for.
    0:22:41 Exactly.
    0:22:42 So you think about that you’ve got a buyer
    0:22:44 for the chocolate category, right?
    0:22:47 And that could be an older, candidly white male
    0:22:49 who’s making a decision on the entire category.
    0:22:50 For a very diverse audience.
    0:22:53 By the way, not diverse racially by age,
    0:22:57 a certain gender, demographic, location.
    0:22:59 So should we be selling the same thing in LA
    0:23:00 that we do in Vermont?
    0:23:02 So how are people going to get this data?
    0:23:03 Because right now Jeff is describing
    0:23:04 that they’re desperate for data.
    0:23:06 So they have to rely on these,
    0:23:07 they have to get data somewhere.
    0:23:09 But that’s still adverse selection type data.
    0:23:11 It’s not like the true opportunity space of data.
    0:23:12 So where does the data come?
    0:23:15 Broadly speaking, in consumer,
    0:23:16 there’s a really beautiful thing
    0:23:17 that a lot of people that don’t live and breathe
    0:23:19 this space, they don’t recognize,
    0:23:21 which is there is a tremendous amount of data
    0:23:22 that’s out there in the world.
    0:23:26 Meaning I can already see where a product is sold,
    0:23:28 how many SKUs a company has,
    0:23:30 meaning how many products that company sells,
    0:23:32 what the price points of the products are,
    0:23:33 what the end users think of the product.
    0:23:34 And if I’m tracking it,
    0:23:37 I can see how all those things change every single month
    0:23:39 and how they compare to every other company in the category.
    0:23:43 Those factors have been shown to be predictive of success.
    0:23:46 People can aggregate those.
    0:23:47 Now the challenge,
    0:23:48 and this is where it gets really tricky.
    0:23:51 The challenge is that you’re consolidating information
    0:23:53 across literally hundreds of unstructured data sources.
    0:23:55 It’s extremely intensive,
    0:23:57 extremely intense and very difficult.
    0:23:59 Sounds like a deal for an AI solution.
    0:23:59 Yeah, it is.
    0:24:00 It is.
    0:24:01 But the data is out there is my point.
    0:24:05 We think that that data is going to start getting consolidated
    0:24:08 by data providers, technology companies,
    0:24:11 that then sell it to the CBG companies,
    0:24:13 or in this case, the grocery chains.
    0:24:15 So the data opportunity, do you believe that?
    0:24:15 Yeah, no.
    0:24:17 We actually have seen a ton of companies trying to do it.
    0:24:23 The interesting part is how hard they have to work to get the data.
    0:24:24 There have been a whole bunch of them
    0:24:28 that are trying to incent consumers to take pictures of their receipts
    0:24:29 and submit the pictures.
    0:24:32 And they do Optical Character Direct Edition on the picture
    0:24:34 to try to reverse engineer.
    0:24:36 What did Jeff buy?
    0:24:37 We’ve seen multiple companies trying to do that.
    0:24:39 There are other approaches too.
    0:24:42 There was an on-demand,
    0:24:45 they’d send armies of people with smartphones
    0:24:46 to take pictures of shelves
    0:24:48 so that they know the competitive pricing.
    0:24:53 Oh, look, Crest is $2.29 and Colgate is $3.15.
    0:24:54 What happened to sales?
    0:24:57 But they don’t know what Colgate and Crest is,
    0:24:58 and so they don’t know.
    0:25:03 All they know is my philosophy in the southern region slowed down.
    0:25:04 Or it’s sped up and you don’t know why,
    0:25:05 which is equally problematic actually.
    0:25:07 In the case of the receipts companies,
    0:25:08 we’ve seen a lot of those too.
    0:25:10 The challenge has been many of them tap out
    0:25:13 at five, 10 million consumers, at least here in the US.
    0:25:16 The problem with that level is that then,
    0:25:18 that’s such a small portion of the overall population
    0:25:21 that you’re not capturing the long tail of companies.
    0:25:25 The chances that the $5 million popcorn company
    0:25:29 is bought in a population that small is relatively low.
    0:25:30 They’re going to be buying
    0:25:31 the Procter & Gamble’s General Mills of the world,
    0:25:33 but then you’re just getting more data
    0:25:34 on the larger companies.
    0:25:35 They need it on the smaller ones.
    0:25:37 Exactly, they need data on the long tail.
    0:25:40 Okay, so in this world, this long tail world,
    0:25:42 this world of offline and online distribution,
    0:25:44 and those are the two distribution broadly
    0:25:45 that we’re talking about.
    0:25:47 We are seeing a lot of microbrands,
    0:25:48 and we didn’t talk about that
    0:25:50 when we were talking about direct-to-consumer.
    0:25:51 I mean, there’s a whole lot of media pieces
    0:25:53 dissecting this phenomenon.
    0:25:54 First of all, what is a microbrand
    0:25:57 and why does it matter, or is it just a hypey thing?
    0:25:59 Yeah, so let me just clarify.
    0:26:02 By microbrand, you mean an emerging consumer product company
    0:26:05 typically called less than $10 or $15 million in revenue.
    0:26:08 So yes, but I think you’re the one who argues
    0:26:10 that it denotes size, not channel,
    0:26:12 because the way I’ve read it in the media,
    0:26:13 it does talk about it as well.
    0:26:15 Yeah, so the recent Economist article
    0:26:16 kind of confused the two.
    0:26:17 They started talking about microbrands,
    0:26:19 and then they said, basically implied
    0:26:21 that microbrands means D to C.
    0:26:24 Micro to me, unless I’m missing something,
    0:26:26 denotes size, not channel.
    0:26:28 So I don’t really love that term to be candid with you.
    0:26:29 Why didn’t you like it?
    0:26:30 Well, for the same reason,
    0:26:32 I would imagine that the entrepreneurs around here
    0:26:35 wouldn’t like it if we called them micro technology companies.
    0:26:36 They’re starting companies
    0:26:37 because they want to build something big.
    0:26:41 And I think that sometimes that comes across
    0:26:43 as a little bit high and mighty, perhaps,
    0:26:46 but especially if it’s just an ice cream company.
    0:26:47 But look, I’ll be frank with you.
    0:26:51 The ice cream company that’s able to strip out
    0:26:53 fat and calories from the ice cream
    0:26:54 and still deliver great products,
    0:26:56 to me, is having a bigger impact on the world.
    0:26:57 This is like Halo, right?
    0:26:59 Halo Top, yeah, it’s exactly right.
    0:27:03 So when we talk about them as emerging brands,
    0:27:07 so emerging brands can be sold certainly offline or online.
    0:27:09 But what’s happening,
    0:27:12 these brands are growing very, very quickly right now.
    0:27:14 In every single category in consumer,
    0:27:17 large brands are losing share to emerging brands.
    0:27:19 And the large brands are just terrified by this.
    0:27:20 So why is it happening?
    0:27:22 We think three primary reasons.
    0:27:25 First is what we talked about
    0:27:27 before the personalization of the consumer.
    0:27:29 Consumers are demanding products that meet their unique needs.
    0:27:31 Two other reasons that are pretty relevant
    0:27:32 to this conversation.
    0:27:36 One is decline in distribution costs.
    0:27:39 Really, instead of just saying it’s a decline,
    0:27:41 it’s really a shift from fixed costs
    0:27:43 to variable costs.
    0:27:44 And that’s because of the internet,
    0:27:46 like the entry point to be able to buy,
    0:27:47 get up a business up and running.
    0:27:50 The internet is part of the driver,
    0:27:52 but I don’t want to imply that that is the key driver.
    0:27:55 In my view, it’s more that the offline retailers
    0:27:58 are hungry to work with the small brands.
    0:27:59 They’re struggling to figure out how to do it.
    0:28:01 And so what we’re seeing is many of the offline retailers
    0:28:04 are eliminating or lowering slotting fees.
    0:28:07 Slotting fees are the cost to get your product on the shelf.
    0:28:08 So if I want to launch a new chocolate bar
    0:28:09 to get on the shelf of Safeway,
    0:28:12 it is literally $50 to $100,000 just to get it on the shelf.
    0:28:13 Think about that for a second.
    0:28:15 If it’s the Apple App Store to launch an app,
    0:28:18 it’s $100,000, it’d be a huge buried entry.
    0:28:21 That fixed cost is declining rapidly
    0:28:22 over the last five or 10 years.
    0:28:23 Because these big brands are eager for–
    0:28:25 The grocery stores are eager for these smaller brands.
    0:28:27 More assortment, actually.
    0:28:27 That’s right.
    0:28:29 The third driver for why these emerging brands
    0:28:32 have been so successful over the last five or 10 years
    0:28:33 is marketing costs.
    0:28:36 And that does get back to your point about the internet.
    0:28:39 So marketing costs have also flipped from fixed to variable.
    0:28:41 Fixed, meaning it used to be, let’s buy an ad in us weekly.
    0:28:42 It cost me $100,000.
    0:28:43 Or Jeff’s circular example.
    0:28:44 Circular example is a great one.
    0:28:47 Today, it is, let’s say, it’s the dollar-shaped flood YouTube ad.
    0:28:50 And that’s an extreme example.
    0:28:52 But you’re able to at least get your product out there
    0:28:54 on a variable cost basis.
    0:28:57 Because the flick fixed to variable transition,
    0:29:00 these smaller brands, these emerging brands,
    0:29:02 are able to grow much more effectively
    0:29:03 than they could have 10 years ago.
    0:29:05 So it literally is a variable cost.
    0:29:07 When I was managing eBay, we were doing TV
    0:29:09 and it was $1 million to produce an ad.
    0:29:13 And then $10 million to distribute it with a frequency
    0:29:15 that the brand people thought was efficient.
    0:29:20 So $11 million was the ante to go on television for eBay at the time.
    0:29:24 And so now you can go buy a $10,000 of Facebook ads
    0:29:26 and try to reach your core audience.
    0:29:28 So when you think about where this goes
    0:29:30 in terms of innovation in the consumer space,
    0:29:33 we think that over the next 10, 15, 20 years,
    0:29:36 the brands that win, there will be more of them,
    0:29:39 but they will get to a smaller level.
    0:29:41 So what I mean is in the last 10 or 15 years,
    0:29:44 the brands that won, Chabani, et cetera,
    0:29:47 you can build multi-billion-dollar businesses.
    0:29:51 I’m skeptical if that’s true in CPG going forward.
    0:29:52 I mean, it’s almost math
    0:29:56 because the total grocery market’s growing one or 2% a year.
    0:29:58 If the number of brands proliferate,
    0:30:00 the average revenue per brand should come down.
    0:30:01 That’s exactly right.
    0:30:04 But there’s no possibility for a player
    0:30:08 like with Coke or Pepsi or white vitamin water or LaCroix.
    0:30:10 So there’s certainly some very, very smart people
    0:30:12 that disagree with me on this point.
    0:30:17 I don’t see a world in which consumers want less options
    0:30:19 where they’re saying, “Look, I want to go to the grocery store.
    0:30:20 I want to go on Instacart.
    0:30:22 And I only want to see one chocolate bar.
    0:30:25 I don’t want to see something that’s different
    0:30:27 for Sonal versus Ryan versus Jeff.
    0:30:28 We don’t foresee that happening.”
    0:30:31 Yeah, my view on that whole debate always comes down
    0:30:34 to when people talk about more choice versus less choice.
    0:30:36 Always comes down to actually what is the right choice for me.
    0:30:38 And that does go to your point about personalization.
    0:30:41 But the nuance I would say and data
    0:30:42 is that it doesn’t necessarily have to do
    0:30:43 with how many choices you have,
    0:30:45 but that the right choices are presented to you.
    0:30:45 Absolutely.
    0:30:47 And that’s going to be a huge challenge.
    0:30:49 Whoever the grocery chain or in this case,
    0:30:50 or in the case of Instacart,
    0:30:53 is to be able to present the right choices to you.
    0:30:55 But we don’t think that the answer is going to be,
    0:30:57 “Let’s strip out the choices altogether.”
    0:30:57 Right.
    0:31:01 And in 20 years ago, the choice was Coke or Pepsi.
    0:31:03 But if now you go into the beverage aisle
    0:31:06 and there’s things that I don’t even recognize where I am.
    0:31:06 Right.
    0:31:07 You know, just saying you’re just like–
    0:31:08 I really don’t even understand
    0:31:09 still why people love LaCroix so much.
    0:31:12 It’s just like water with like a little hint of a taste.
    0:31:12 I still don’t get it.
    0:31:13 It is passion fruit.
    0:31:16 I’m so confused over this.
    0:31:17 Well, let’s talk about data then.
    0:31:19 So we’ve been scooting around this topic of data for a while.
    0:31:20 The biggest thing I’ve heard so far
    0:31:23 as we talk about online to offline
    0:31:25 is that in the offline world,
    0:31:27 it has been nearly impossible to get the data we want.
    0:31:29 On one hand, I’ve heard you say, Ryan,
    0:31:31 that there are many data sources out there
    0:31:32 that are really good proxies
    0:31:34 and that we can do a lot.
    0:31:36 But Jeff, you’ve also said that people are starved for data,
    0:31:38 that things are missing.
    0:31:40 So tell me what the status is in the world of CPG and data.
    0:31:43 Like where are we right now really on where–
    0:31:46 how far data– what data can do in this world?
    0:31:47 Well, so I think both are true.
    0:31:49 Both that there is a lot of data
    0:31:51 and that people are starved for data.
    0:31:54 And the bridge there is that while there is an outrageous amount
    0:31:56 of data in this industry,
    0:31:58 the data is very hard to pull together.
    0:32:01 And in some cases, impossible.
    0:32:04 It’s just impossible to actually go get it.
    0:32:08 So the data that’s out there around distribution,
    0:32:09 around product uniqueness,
    0:32:11 how unique a product is relative to its competitive set,
    0:32:14 on what the user thinks of the product,
    0:32:17 on the competitive set of that product, et cetera,
    0:32:19 all that data is out there in the world.
    0:32:20 And if you begin to kind of think about
    0:32:22 where would I get that data?
    0:32:24 Well, most brands are not trying to hide.
    0:32:26 There’s no concept of living in stealth in consumers.
    0:32:29 Yeah, you can’t really, like, hide your toothpaste.
    0:32:32 That’s right. When I launch in my chocolate bar in the Whole Foods,
    0:32:34 Whole Foods wants you to know that you can buy the Whole Foods,
    0:32:36 and I want you to know you can buy the Whole Foods.
    0:32:39 Similarly, I want you to know what’s in the product.
    0:32:40 How you have an ingredient deck and nutritional panel
    0:32:43 that’s mandated by the FDA, but it’s out there.
    0:32:46 Then consumers talk about my chocolate bar.
    0:32:47 That’s also key.
    0:32:50 So people can begin to understand what people think of it.
    0:32:53 They get the sentiment analysis of the data of the chocolate bar.
    0:32:55 So if you think about, you know,
    0:32:58 rewind to the first year slack was in existence, right?
    0:33:00 So if you could see every customer that used slack,
    0:33:03 what they paid for it, what the end users thought of the product,
    0:33:05 and how all of those things changed every single month,
    0:33:08 that’d be pretty valuable data for a lot of people to have.
    0:33:12 You have that data on every single CPG company in existence.
    0:33:13 It’s out there.
    0:33:13 Who has it?
    0:33:15 Well, that’s the challenge, right?
    0:33:19 So the challenge is basically it’s out there living somewhere on Google.
    0:33:22 Meaning if you Google the smallest brand you can find,
    0:33:24 you can see everything that I just said.
    0:33:29 The challenge, though, is how do you pull all that unstructured data together
    0:33:30 and then normalize it?
    0:33:32 So I see a brand on Amazon.
    0:33:36 I see the same brand being sold and Whole Foods being talked about on Instagram, etc.
    0:33:39 So a process that we call entity resolution.
    0:33:42 I remember this from NLP where you have to essentially find the same entity
    0:33:43 with different variations or names on it,
    0:33:46 but be able to resolve that it is the same entity.
    0:33:47 It’s an incredibly hard problem.
    0:33:49 Right. It’s a lot harder than people think.
    0:33:50 Yeah. And then on top of that,
    0:33:55 you also have the problem of how do you know that that product is a chocolate bar
    0:33:56 and not a pair of shoes?
    0:33:57 That sounds like an easy problem.
    0:34:00 I have eaten chocolate bars that taste like a bar of shoes.
    0:34:03 You’re right. Chocolate bars do taste like shoes.
    0:34:04 Not that I’ve actually eaten shoes.
    0:34:06 I mean, have you eaten shoes?
    0:34:07 You’re a basketball player.
    0:34:08 I always put my foot in my mouth.
    0:34:11 So that’s another challenge.
    0:34:13 Is that now you think about the people that want to consume this data.
    0:34:20 Grocery chains, large CPG companies, they’re not equipped to pull all that data
    0:34:24 and structure data in, normalize it, make sense of it, match it together.
    0:34:25 That’s not a core competency for them.
    0:34:29 That’s why I strongly believe it’ll be a technology company that does that
    0:34:31 and then sells that data to others.
    0:34:34 Right. So that’s where you believe that CPG companies can compete
    0:34:38 and where technology has a place to play by providing that data.
    0:34:43 There is a ton of data, and yet people are running blind.
    0:34:47 It’s not the data they need.
    0:34:52 There’s data around. It’s not helping to make the important decisions
    0:34:53 that are moving the needle.
    0:34:56 In some cases, it’s not the data that they need.
    0:34:58 In other cases, they’re not equipped to digest the data.
    0:35:03 And you think of, okay, so at the grocery store, the chocolate buyer,
    0:35:07 going back to that example, that’s trying to pick what chocolate bars are on their shelves,
    0:35:11 they are used to, for their entire career,
    0:35:14 basing it off of either A, their own taste, literally.
    0:35:17 That’s how they try product or that’s how they decide products.
    0:35:20 Or B, a small amount of retail-level sales,
    0:35:23 bought from a very structured data source over and over again.
    0:35:25 And that’s not competitive, right?
    0:35:26 Because every company has access to that same data.
    0:35:28 Every grocery store has access to that same data.
    0:35:31 Everyone’s got this commoditized data.
    0:35:32 Everyone’s using the exact same thing.
    0:35:34 So now when you go to them and you say,
    0:35:37 well, actually there’s this whole universe of data out there,
    0:35:42 covers 30 to 50 times as many companies as your existing data source does.
    0:35:42 Do you want to use it?
    0:35:44 The answer is yes, but.
    0:35:47 And the but is, well, how do I digest that?
    0:35:51 I’m stuck in Excel, Windows 95.
    0:35:53 That’s what I’m stuck using here.
    0:35:55 How do I digest all of this data?
    0:35:56 Who’s going to pull this together for me?
    0:35:58 Because by the way, I’ve got literally one engineer
    0:36:02 that works at the entire company, entire division that I’m in right now.
    0:36:03 How am I going to do this?
    0:36:05 That’s why we think it’s an outsource provider.
    0:36:08 We think grocery stores and CBG companies
    0:36:10 are either going to be buying it from a technology company
    0:36:12 or they’ll have to buy that technology company,
    0:36:13 bring it in-house.
    0:36:16 It makes me think a little bit of automotive and traditional
    0:36:19 Detroit car companies trying to become autonomous car companies.
    0:36:22 And I think it’s fascinating because they could potentially
    0:36:23 win on that front if the right competency is.
    0:36:25 There are some really smart people in the grocery business.
    0:36:26 Yeah, exactly.
    0:36:27 Walmart’s diving in.
    0:36:31 They’re also in top line sales right now in stores.
    0:36:33 That said, it’s hard.
    0:36:36 A lot of the best engineers might want to work for a grocery store
    0:36:38 and might not want to live in Bentonville, Arkansas.
    0:36:41 And then they’re incredibly low margin businesses.
    0:36:44 So how do you hire a ton of really expensive engineers?
    0:36:46 I give Walmart credit for making the bet.
    0:36:47 They bought jet.
    0:36:49 They bought a number of small–
    0:36:50 They also have their own labs.
    0:36:52 Like Walmart is known to be a little bit more innovative
    0:36:54 with internal R&D than some of the other CBG players
    0:36:55 that we’re talking about here.
    0:36:58 But it’s not that the grocers aren’t capable
    0:37:00 and don’t understand it.
    0:37:02 They’re a bit of a prisoner’s dilemma.
    0:37:05 There are extremely, extremely smart people working at both
    0:37:08 large CBG companies and large grocery stores
    0:37:10 that are in a really difficult position.
    0:37:13 You think about what would you do if you were in their position?
    0:37:14 Well, they’re out of business.
    0:37:18 That’s, in the case of grocery, 2% net margin business.
    0:37:20 How do they then say to their boss,
    0:37:23 let’s go hire 150 engineers to go build this thing?
    0:37:26 By the way, it’s not going to pay back for two or three years.
    0:37:28 That’s a really, really hard proposition to make.
    0:37:31 So I think incredibly talented smart people that work there,
    0:37:33 it’s a hard position to be in.
    0:37:35 One of the smartest people I’ve ever met in business
    0:37:39 was the CEO of one of the largest consumer package companies.
    0:37:42 And she came to Silicon Valley and wanted to sit down.
    0:37:43 And I’m like, why are you here?
    0:37:45 We believe software’s eating the world.
    0:37:47 How is software eating snacks?
    0:37:50 She came up with this very lucid argument of two things.
    0:37:53 One is all of a sudden, there’s promotional transparency.
    0:37:57 I used to move, gain share by going on special on knob,
    0:38:00 Hills food one day and then special at Safeway.
    0:38:02 Now the consumer knows exactly where I’m on special.
    0:38:04 So I’ve lost the share moving thing,
    0:38:08 all I’m doing is discounting and then nutritional transparency.
    0:38:11 And so she says, I have to retool my company
    0:38:15 because the two bedrocks that it was built on, software eight.
    0:38:17 The challenge with that, and I, by the way,
    0:38:19 I totally agree with that diagnosis.
    0:38:22 The challenge then is that I don’t think that the CEOs
    0:38:24 of these large CPG companies or large grocery chains
    0:38:26 are given enough runway to go do that.
    0:38:28 So there’s this, what we call 3G effect,
    0:38:30 large financial institution down in South America
    0:38:35 that has been investing into or buying public CPG companies,
    0:38:36 basically stripping costs out.
    0:38:39 And delivering shareholder value.
    0:38:42 Problem with that is when you’re stripping the costs out,
    0:38:44 one of the first things to go is R&D.
    0:38:46 So you already had a problem for these large CPG companies.
    0:38:48 What’s the percentage of R&D that they have?
    0:38:51 So today, large CPG spends about 2% of sales in R&D.
    0:38:52 Are you kidding?
    0:38:55 Tech spends about 14% of sales in R&D.
    0:38:57 CPG spends nothing on R&D.
    0:39:01 And so- You have low margins, like 1.5 to 2% R&D.
    0:39:01 That’s right.
    0:39:03 So when you strip out costs,
    0:39:06 I can deliver shareholder value and hit quarterly numbers
    0:39:08 for the next, let’s say, year or two years.
    0:39:10 But you look five, seven years out.
    0:39:11 It’s not going to last long-term.
    0:39:12 How far can you cut?
    0:39:13 It’s like the activist investor problem, right?
    0:39:14 That’s exactly right.
    0:39:18 And so what we’re seeing is that many of these companies,
    0:39:20 regardless of whether they’re doing that cost cutting or not,
    0:39:23 they’re saying, look, we were already spending almost nothing on R&D.
    0:39:24 How do we get the innovation?
    0:39:26 And this goes back to a point Jeff made earlier.
    0:39:27 That’s why CPG is beginning to look a lot
    0:39:29 like Big Pharma has for the past 20 years.
    0:39:31 So one last question then,
    0:39:34 just to think about more on the data and innovation side.
    0:39:36 All of us in this room are in the world of investing.
    0:39:38 How does this change the investing game?
    0:39:42 So in terms of how I think the investing landscape will change,
    0:39:49 we have a pretty strong thesis that in CPG specifically,
    0:39:52 there will be quantitative VC firms.
    0:39:54 So what I mean by that is if you think of the public markets,
    0:39:58 there are systematic quant funds that have historically,
    0:40:00 over the last 20 years or so, in some cases 30 years,
    0:40:05 invested into public companies basically just using technology.
    0:40:07 It’s very different than a discretionary hedge fund
    0:40:09 where you’ve got a team of really smart people
    0:40:12 that research a stock for six months and make a decision.
    0:40:14 In the case of a systematic quant fund,
    0:40:17 they’ve got a lot of really, really smart engineers and data scientists
    0:40:18 who are building algorithms to evaluate the company
    0:40:20 and then make an investment decision.
    0:40:23 We think that that is possible in some industries in the private markets.
    0:40:26 We don’t think it’s possible in tech.
    0:40:27 Why do you think that’s possible in CPG?
    0:40:30 So there’s two main reasons that CPG is beautiful.
    0:40:33 First, the business models are basically the same.
    0:40:36 So what I mean is if I’m selling shampoo, dog food, or water,
    0:40:37 the margins are different,
    0:40:39 but I’m making a product and I’m selling the product.
    0:40:40 It’s very different than tech.
    0:40:42 In tech, I might give away the product for five years.
    0:40:43 You might do a freemium, right?
    0:40:44 I might do a SaaS business, et cetera.
    0:40:45 Very different business models.
    0:40:47 Because it’s the same business model,
    0:40:49 it’s the same game of chess over and over again.
    0:40:50 Interesting.
    0:40:54 The second reason that there’s just an outrageous amount of data in this space,
    0:40:59 but many of the dimensions that are predictive of success of a consumer company
    0:41:01 are not data that you can get externally.
    0:41:04 It’s hard to get information from afar.
    0:41:05 In consumer, you can get it from afar
    0:41:07 without ever talking to the company.
    0:41:09 We have gone private financials on thousands of companies.
    0:41:11 That acts as our training data.
    0:41:13 The training data is private financials on thousands of companies.
    0:41:15 And is that kind of providing the ground truth
    0:41:16 in order to sort of compare the decisions again?
    0:41:17 That’s exactly right.
    0:41:18 Yeah, so it’s the ground truth.
    0:41:23 So I need to know what success and failure looks like in order to predict it.
    0:41:25 If you look at a SaaS company, a consumer company,
    0:41:28 and an infrastructure company in tech, you can’t compare them.
    0:41:31 Whereas if you’ve got two beverage companies,
    0:41:38 and one is selling 20 units per Whole Foods per week at a 60% margin,
    0:41:42 another selling 10 units per Whole Food per week at a 30% margin,
    0:41:44 it’s pretty obvious which is the better company.
    0:41:48 But also in CPG, I can find that company
    0:41:50 just by using publicly available information.
    0:41:52 So I can see that one of the two companies
    0:41:55 started in one Whole Foods six months ago,
    0:41:58 and now is in 400 Whole Foods and added 300 targets.
    0:42:01 There isn’t really an equivalent in, let’s say, the SaaS world.
    0:42:04 Going back to the SaaS world, while there might be structured metrics to look at,
    0:42:06 and those metrics might be predictive of success,
    0:42:08 almost all of them, not all, but almost all of them,
    0:42:10 are only available once you start talking to the company
    0:42:11 and you already know who to focus on.
    0:42:14 I do wonder because when I watch a show like Billions,
    0:42:16 you know, they have, they use data like empty parking lots
    0:42:19 and aerial shots of an empty parking lot for retail
    0:42:22 to be able to make a decision on whether to pull a trigger on a company or not.
    0:42:24 The equivalent in SaaS might be developer heat,
    0:42:28 like viral developer activity or the adoption rate among developers.
    0:42:30 There’s various heat maps and sources.
    0:42:32 The part that I have to ask on the big question
    0:42:35 of quant investing in general, and especially in this case,
    0:42:37 and even in our world, Jeff, which is more tech than CPG,
    0:42:41 doesn’t it miss the outlier, the outsize winners?
    0:42:42 It’s a great point.
    0:42:43 It’s a great point.
    0:42:43 Yeah.
    0:42:46 So we, that’s another reason we struggle to believe
    0:42:47 that it is possible in tech.
    0:42:50 You think about many of the massive home runs in tech.
    0:42:51 Exactly.
    0:42:55 There weren’t prior examples that did something very similar.
    0:42:56 No, they’re all, they’re all a priori.
    0:42:57 Right. Yeah.
    0:42:59 And so, so that’s why I really struggled to believe
    0:43:00 that that’s possible in tech.
    0:43:02 When you look at the winners and consumer,
    0:43:04 the previous winners looked really similar.
    0:43:06 That might have been a different,
    0:43:07 might have been a different magnitude,
    0:43:08 but they grew in really, really similar ways.
    0:43:11 So this might be the one case where that phrase pattern recognition
    0:43:13 that people throw around so wildly in the valley actually applies.
    0:43:17 But who the winner was, wasn’t that still an irrational
    0:43:20 behavioral thing versus something programmable?
    0:43:24 So we’ve been able to show that there are some common themes
    0:43:29 between both in A, why something wins and how it wins.
    0:43:29 So here’s what I mean.
    0:43:31 So you’re nuanceifying the two, which is really important.
    0:43:31 That’s right.
    0:43:36 So why typically the winners have, and look, to be clear,
    0:43:37 this is not perfect.
    0:43:39 There are holes, there are inaccuracies.
    0:43:42 Typically the winners have brand intensity with the consumer.
    0:43:44 So think of vitamin water 15 years ago,
    0:43:49 kind bar 10 years ago, the brand really resonates with the consumer.
    0:43:51 The second thing that is common amongst the winners in CPG
    0:43:55 is the product has uniqueness that matters.
    0:43:55 Interesting.
    0:43:58 So kind bar is actually a pretty good example here.
    0:43:59 When it first came out, everyone said,
    0:44:00 “This is a really crowded category.”
    0:44:03 By the way, everyone always says every CPG category is crowded.
    0:44:06 Because they are, because they are, but they’re also massive.
    0:44:08 Right, crowded but massive.
    0:44:09 I like that distinction.
    0:44:12 So kind bar, at the time though, what people missed was,
    0:44:15 there’s Nature’s Valley, there’s Cliff Bar, a number of others.
    0:44:18 When you look at those products, they didn’t look like real food.
    0:44:21 Kind bar had an insight, which was,
    0:44:23 “Let’s make a product that actually just looks like real food.”
    0:44:24 That’s actually why I’m drawn to them.
    0:44:26 I don’t feel like I’m eating a crappy processed bar.
    0:44:28 Yep, and they actually show the food.
    0:44:30 The biggest innovation for Guy Bar from my perspective is,
    0:44:33 it’s see-through and you can see that there’s real food.
    0:44:33 So you can see a whole lot to that.
    0:44:35 And it’s not symmetrical.
    0:44:35 Yeah, that’s exactly right.
    0:44:36 Like it’s not this perfect rectangle.
    0:44:38 It’s got like jagged edges where you can see it’s real.
    0:44:39 It’s not processed.
    0:44:41 Exactly, exactly, exactly.
    0:44:45 So in that case, you know, you can build an algorithm
    0:44:47 which evaluates the picture of the package.
    0:44:49 And literally just says, “Is this different?”
    0:44:51 So we’ve done that in the case of snack bars.
    0:44:52 We track about 3,000 snack bars.
    0:44:54 So you answer that question of, “Is it different?”
    0:44:54 “Is it different?”
    0:44:57 And then, now I could put fish in my snack bar
    0:44:57 and it’d be different then,
    0:44:59 but it may not resonate with the consumer.
    0:44:59 Right, that would be great.
    0:45:01 So those are two kind of orthogonal dimensions.
    0:45:03 One is does it resonate with the consumer
    0:45:05 and is the product unique?
    0:45:08 The ones that have one tended to be high in both.
    0:45:11 Then there’s the question of how it wins, right?
    0:45:13 So why it wins and then how it wins.
    0:45:16 The how it wins is typically distribution gains.
    0:45:17 Distribution gains.
    0:45:18 Meaning–
    0:45:20 It’s because it’s not the one of Alex’s famous lines.
    0:45:22 Like it’s always about distribution.
    0:45:24 Yeah, yeah, it’s, and that is very true in CBG.
    0:45:26 So there aren’t a lot of big winners
    0:45:28 that have only been sold in five stores.
    0:45:30 That’s not a thing.
    0:45:31 So then if you think about,
    0:45:34 okay, if it’s number of, it’s breadth and quality of doors,
    0:45:35 meaning TG Max not as valuable
    0:45:37 as let’s say Whole Foods or Costco.
    0:45:40 So how do you measure breadth and quality?
    0:45:41 That data is out there.
    0:45:44 Where the product is being sold is out there in the world.
    0:45:45 Whole Foods wants you to know it.
    0:45:46 The brand wants you to know it.
    0:45:48 Now it’s just aggregating that information
    0:45:49 and making sense of it.
    0:45:50 But that’s the how it wins.
    0:45:52 And you can also get into price points.
    0:45:53 You can get into skew count,
    0:45:54 number of other things.
    0:45:56 But marrying those two things together is the foundation.
    0:45:58 But it’s basically one business model.
    0:46:00 A couple of the differences in tech.
    0:46:02 We’ve been trying to figure out,
    0:46:04 how do you leverage data in the decision-making process?
    0:46:05 Is this a holy grail?
    0:46:09 Yes, we can probably define a dozen, two dozen,
    0:46:12 three dozen different worlds of,
    0:46:15 you know, universes of tech companies that are unique.
    0:46:18 You have SaaS and open source and consumer.
    0:46:20 And then within consumer, you have social and e-commerce.
    0:46:23 So, you know, just by definition, comparison’s hard.
    0:46:26 And then the other part you have is what you said,
    0:46:28 most of the huge winners are lightning strikes.
    0:46:30 Facebook was the second or third social network.
    0:46:32 But, you know, no one was thinking social networks
    0:46:35 when they talk about a trillion-dollar company.
    0:46:40 eBay was collectibles online, weird, Facebook hot or not.
    0:46:44 You know, these things, I mean, the Airbnb sleep on someone’s couch.
    0:46:47 You know, these things don’t present as monster companies.
    0:46:51 They start, hit a chord and are expanded
    0:46:53 by their community of users.
    0:46:54 And the thing I would add to that, by the way,
    0:46:56 is that there’s a complexity math to this,
    0:46:57 which is a little bit like the Brian Arthur,
    0:46:59 we had Brian Arthur on the podcast.
    0:47:00 And he’s the father of network effects
    0:47:02 and network effects theory.
    0:47:05 And the point of when that tipping point hits,
    0:47:07 you don’t know when it tips.
    0:47:07 That’s the hard one.
    0:47:08 Yeah, yeah.
    0:47:10 Like the when it seems like the really tough question.
    0:47:11 Will it.
    0:47:12 Then when, yeah, so it’s good.
    0:47:14 And if you think of Jeff’s point,
    0:47:15 like when Facebook hit,
    0:47:17 there was two other social networks and maybe three.
    0:47:17 Yeah.
    0:47:19 There weren’t 300 or 3000.
    0:47:20 Right.
    0:47:21 There were very few examples.
    0:47:24 You don’t have 40 or 400 examples
    0:47:26 to begin to look at pattern recognition.
    0:47:26 Right.
    0:47:28 The n equals three or the CPG.
    0:47:30 You’ve got massive data set.
    0:47:33 So now I can compare certainly one ice cream company
    0:47:34 to the many others that have hit.
    0:47:36 But the difference between ice cream companies
    0:47:37 and snack bars is not great enough
    0:47:40 that you can’t compare the two and begin to see patterns.
    0:47:42 Well, that was a fascinating discussion.
    0:47:45 Ryan, Jeff, thank you for joining the ice cream company.
    0:47:46 It’s a pleasure.
    0:47:46 Thank you.
    0:47:47 Thank you.
    0:47:57 [BLANK_AUDIO]

    with Ryan Caldbeck (@ryan_caldbeck), Jeff Jordan (@jeff_jordan), and Sonal Chokshi (@smc90)

    It’s clear that all kinds of commerce companies and consumer products have been disrupted — or enabled — by tech. Yet for certain categories, like consumer packaged goods (CPG), it seems like tech hasn’t changed things very much. How is the rise of so-called ”micro-brands” (or emerging brands) playing out here?

    And, how is it possible that ”real” — different — innovation isn’t really happening in the CPG industry, despite the tremendous legacy of brand, talent, and more in the space? How are CPG companies tackling grocery, which represents the perfect end-capsule and case study of challenges — and opportunities — in going from offline to online, from online to offline, and more? As for grocery itself, stores themselves (in the U.S. at least) haven’t changed very much due to tech, either… is it a last-mile delivery thing; could we also possibly move to distribution-only centers in the future?

    Finally, while the holy grail of performance marketing and personalization remains elusive for the industry — let’s face it, most brands are still guessing in the dark (and forget trying to customize offerings!) — even going direct-to-consumer (DTC) hasn’t been shining as much of a light here as one might expect. Or so argue the guests in this episode of the a16z Podcast, featuring Ryan Caldbeck of CircleUp, along with a16z general general partner Jeff Jordan, in conversation with Sonal Chokshi. Cuz this episode is all about CPG, DTC; micro-brands, yah you know, all kinds of commerce.