AI transcript
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0:00:23 Hi everyone, welcome to the A6NZ podcast, I’m Sonal.
0:00:28 So this week, to continue our 10-year anniversary series since the founding of A6NZ, we’re
0:00:33 actually resurfacing some of our previous episodes featuring founders Mark Andreessen
0:00:34 and Ben Horwitz.
0:00:38 If you haven’t heard our latest episode with Stuart Butterfield turning the tables as the
0:00:42 entrepreneur interviewing them, please do check that out and our other episodes in this
0:00:46 series on our website at a6nz.com/10.
0:00:52 But this episode was recorded at our Innovation Summit in 2018 and features economist Tyler
0:00:57 Cowan interviewing them about everything from their partnership and how it works to
0:01:01 talent, tech trends, and software eating culture.
0:01:02 Thank you all for coming.
0:01:06 I’d like to start with the two of you as a couple.
0:01:07 Oh yeah.
0:01:10 How was it you met at Netscape in 1995?
0:01:13 Well, Mark interviewed me way back then and he interviewed me.
0:01:18 I think I was interviewing for product management role and he was the founder of the company
0:01:24 and I had worked on a product called Lotus Notes and Mark had a fascination with Lotus
0:01:26 Notes for a couple of reasons.
0:01:31 One was it was kind of sort of the closest proprietary thing to the internet and then
0:01:35 they had email in it and Netscape was looking at doing email.
0:01:40 So he had all kinds of questions for me and I remember him just being absolutely shocked
0:01:46 and flabbergasted that like 50% of our code base and Lotus Notes was just making like
0:01:52 all the LAN protocols work together, IPX and Apple Talk and Net Buoy, Net Bios.
0:01:55 You guys don’t even know what any of that is anymore.
0:01:59 He was like literally just making the network talk to each other, which he thought was like
0:02:02 ridiculous given there was TCP/IP.
0:02:04 That was the very first conversation we had.
0:02:06 Mark, how did he do in the interview?
0:02:07 He did very good.
0:02:08 He did very good.
0:02:10 So he had a giant asset.
0:02:12 He was the first employee from Lotus.
0:02:15 So he looked great in comparison to all the ones we haven’t seen before.
0:02:18 No, he did great.
0:02:20 He was super knowledgeable and actually it was actually a really big deal at the time
0:02:25 because Lotus Notes was a big thing at the time and what Ben just alluded to in the architecture
0:02:28 like it just basically assumed that the internet was not going to work, which was the dominant
0:02:29 assumption at that time.
0:02:32 It’s kind of how the whole thing was built and then most of the people working on it
0:02:35 I think probably agreed with that.
0:02:37 There were many, many arguments that the internet couldn’t possibly do what a system like Lotus
0:02:38 Notes did.
0:02:41 So Ben was, I would say, young enough and smart enough and knowledgeable enough to figure
0:02:46 out very early among his cohort of kind of the professionals in the space that it actually
0:02:51 was going to happen a different way and so we were a little fly by night startup.
0:02:53 So we fast forward to 1999.
0:02:55 You two do loud cloud together.
0:02:56 Why?
0:02:57 How’d that happen?
0:03:01 Well, so the big thing basically that happened was so it turns out the internet worked, which
0:03:03 turned out to be a big deal, go figure.
0:03:06 And then basically what happened was basically people were unprepared for the internet to
0:03:10 work at some fundamental level and then we saw a very specific kind of version of people
0:03:14 being unprepared for that, which is we sold Netscape in 1998 to AOL and so Ben and I and
0:03:17 a bunch of us were working at AOL and then AOL had this thing at the time.
0:03:22 AOL was a little bit like the Google of the era or something where they had like a firehose
0:03:25 of traffic that they could basically steer wherever they wanted to steer it.
0:03:27 And so if you went on AOL and you typed in by clothes.
0:03:29 Half the traffic on the internet went through AOL.
0:03:30 I remember that.
0:03:31 It was a really big deal.
0:03:32 Not my half, by the way.
0:03:33 Yeah.
0:03:34 But that’s a lot, still.
0:03:35 Half.
0:03:36 That’s right.
0:03:37 And then by the way, almost all consumers, right?
0:03:38 Almost all consumers were on AOL at the time.
0:03:43 So you type in by clothes on AOL and then they would sell to like J Crew or Gap or whatever
0:03:44 that slot.
0:03:48 So basically what happened is that advertising business and then AOL would turn on that ad
0:03:52 and then basically the firehose of traffic would just blast the website to bits, right?
0:03:56 If it was J Crew, they just blasted the J Crew website to bits and then the J Crew people
0:03:58 would spend weeks trying to get the website to work to actually take advantage of all
0:03:59 this traffic.
0:04:03 And so it was sort of, you know, it just seemed kind of obvious that we, you know, we were
0:04:05 kind of in this business and so you go talk to the people running these things and they
0:04:09 just, they didn’t, they were just unprepared for this kind of sophistication.
0:04:13 And so we sort of incubated this idea that, boy, what if there was a cloud, right?
0:04:17 What if basically there was a system in which you could take your content and all your apps
0:04:19 and you could run them and it could handle the load and you could, you know, it could
0:04:23 load balance and it could spike up in response to demand and then all these companies, instead
0:04:25 of being in the business of running all your own stuff, like why can’t you just hand it
0:04:26 over to the pros?
0:04:29 And so, and then this is in the full flush of the dot com boom.
0:04:31 So it just seemed like an obvious opportunity.
0:04:36 And so 2009 comes along and why is it it seems to you both then that’s the right time for
0:04:38 a new venture capital firm?
0:04:39 What was the thought?
0:04:44 Well, you know, it was really one of those ideas that just came out of our experience.
0:04:49 You know, we were customers of venture capital and, you know, we had a couple of observations.
0:04:53 One was, you know, we had noticed over the years and Mark really made the observation
0:04:59 first that most of the really great companies, like forget about successful, but like great
0:05:02 companies, companies you admire and tech were all run by their founders for a very long
0:05:03 time.
0:05:10 Like Thomas Watson at IBM or Dave Packard, Bill Hewlett at Hewlett Packard or, you know,
0:05:16 Bill Gates or whoever it was, all the really giant successes were run by their founders.
0:05:20 And the conventional wisdom and venture capital was set up to replace the founder.
0:05:25 And then in our own experiences as technical founders, we knew why that was true because,
0:05:30 you know, well, if you just took, you know, loud like nobody would have ever been able
0:05:32 to fix loud cloud other than us.
0:05:36 Like there was no way you could bring in a professional to do that.
0:05:39 And so getting to that next product after you get the first product, getting to the
0:05:43 next product market fit required an innovator.
0:05:46 And so if you wanted subsequent product cycles, you needed the founder.
0:05:50 And so we just thought there ought to be a firm that is designed to do that.
0:05:53 And what is it that the two of you figured out?
0:05:56 What is it you two understood that other people didn’t?
0:05:57 And how would you articulate that?
0:06:01 You know, like we were just, there was a bunch of things.
0:06:02 One differentiation.
0:06:06 So like we came from a company, so we’re like, first we’re going to tell a very clear
0:06:09 sharp story about a real network that we’ve built out systematically.
0:06:13 We’ve got people who are going on your board who know exactly how to build companies.
0:06:17 So sometimes it feels to some people, there’s a lot of money running around, but talent
0:06:18 is quite scarce.
0:06:22 What is it that you two in the company as a whole have understood about talent search
0:06:23 that other people have not?
0:06:26 So we actually thought of it as a talent business.
0:06:30 And a lot of the reason for that is, you know, a friend of ours, Michael Ovitz, who founded
0:06:33 the talent agency, CAA, was a board member of ours at Opsware.
0:06:41 And you know, he always thought about talent in amazing detail and like, in incredibly
0:06:46 specific and one of his biggest concepts about it was, it was a network.
0:06:50 And you had to run the, and it seemed simple, oh, it’s a network, okay, great.
0:06:52 But like, how do you build that network?
0:06:53 How does it work?
0:06:56 How do you take a long view of the relationships with the talent?
0:07:03 So you know, we really thought out very early on, we’re going to invest heavily in building
0:07:09 this network and having the time, the luxury of time to build real relationships as opposed
0:07:13 to transactional relationships with every single person that we run into, be they an
0:07:18 engineer, an entrepreneur, a corporate partner, or whomever.
0:07:21 And that all kind of came out of this original CAA concept.
0:07:26 If you take a long view of relationships, you can build a network that’s so powerful
0:07:27 that nobody will ever be able to match it.
0:07:30 And that was kind of the original inspiration.
0:07:35 And we were fortunate enough to just hire a really astoundingly good team to help us
0:07:36 do that.
0:07:38 And Mark, how do you think about talent assessment?
0:07:41 So I think, you know, the other side of it is just the entrepreneur assessment, right?
0:07:44 And so it’s just one of those things where, you know, there is kind of this fundamental
0:07:47 question of kind of how extreme are you willing to get, right, with some of these people, right?
0:07:52 Because you know, the kinds of people who start these companies are not normal.
0:07:55 And we can say that speaking from experience, having done it ourselves.
0:07:58 And so, and I would actually go so far as to argue, like, it may be that the founders
0:08:02 are getting less normal as sort of society gets, let’s just say, more interesting in
0:08:03 recent years.
0:08:06 And so, you know, the ideas are getting bigger, the technologies are getting more disruptive,
0:08:09 the companies that win are getting much larger, technology is more central in everybody’s
0:08:10 lives.
0:08:11 By the way, there’s more competition than ever.
0:08:12 There are more tech startups than ever.
0:08:16 And so the kind of very special person who’s going to conceive of an original idea and
0:08:19 then be able to build a team and be able to prosecute the idea is going to be a very extreme
0:08:20 person.
0:08:24 And so a lot of it is sort of this, you know, the discovery and then partnering with these
0:08:25 really extreme people.
0:08:28 I’m going to throw out a few questions about particular technologies.
0:08:33 And either of you feel free to answer blockchain, what will be the breakthrough application
0:08:34 for blockchain?
0:08:35 I’ll take that.
0:08:38 So first of all, like asking what the killer app is, nobody ever gets it right.
0:08:42 Like I remember the internet killer app, it was never Facebook, that’s for sure.
0:08:48 But the way that we think about blockchain technology is that it’s a new computing platform.
0:08:54 And like other new computing platforms that preceded it, it’s worse in every way, but
0:08:56 really a very few ways.
0:09:00 So if you think about the smartphone, when it came out, it was much worse than the PC
0:09:02 at a tiny screen.
0:09:05 It was far less powerful, et cetera, et cetera.
0:09:08 People were like, how am I going to run my spreadsheet on that little ass screen?
0:09:11 Like there’s no way it’s going to work.
0:09:13 But I had a couple of properties that you didn’t have in the PC.
0:09:14 It had a GPS.
0:09:15 It had a camera.
0:09:17 And so you can now build things like Lyft.
0:09:21 You can now build things like Instagram that you could never build on a PC, and you still
0:09:22 can’t build on a PC.
0:09:26 And it created a whole new world of applications.
0:09:27 Blockchain is like that.
0:09:28 It’s slower.
0:09:29 It’s harder to use.
0:09:30 It’s harder to program.
0:09:34 But it has a new feature, and that feature is trust.
0:09:39 And trust is really, really an interesting feature because it means that you don’t have
0:09:45 to trust the government or a corporation or your lawyer.
0:09:50 You just have to trust the mathematical properties and the game theoretic properties of the system,
0:09:51 and then you can do things.
0:09:56 And it opens up applications such as you can program money.
0:09:59 You can program contracts.
0:10:03 You can create digital property, which is, you know, if you just think about the art
0:10:07 world, it’s an amazing kind of world, and it’s all virtual value.
0:10:13 You know, Bosque, it’s $150 million, but like the canvas is probably less than $5.
0:10:16 But because you know that it’s one of one, it’s got value, well, you can now do that
0:10:17 digitally with blockchain.
0:10:19 So there’s those kinds of things.
0:10:21 And then you don’t have to trust companies.
0:10:25 So if you’re a developer and you’re building an application, you know, you don’t have to
0:10:28 trust Facebook to not go, well, like, you know, we decided, like, we’re changing our privacy
0:10:29 policy.
0:10:30 You can’t run anymore.
0:10:33 Or if you’re a consumer, you don’t have to say, OK, like, I’ve got to trust you with
0:10:34 my data.
0:10:38 So that property of trust, we think, is very, very powerful, and there is a large set of
0:10:40 applications that will come off of that.
0:10:44 But you know, like, it takes a while for developers to get used to it, for the technology to
0:10:45 mature and so forth.
0:10:48 But it’s one of the things we’re most excited about.
0:10:52 Paint a picture for me 15 years from now.
0:10:53 Retail and wearables.
0:10:57 What will tech do for me in those areas that it’s not doing right now?
0:11:00 So I think retail will basically be gone by then.
0:11:01 I mean, so.
0:11:02 Gone?
0:11:03 I can’t go to the shopping mall anymore.
0:11:04 Who wants to go to the shopping mall?
0:11:05 I want to go to the shopping mall.
0:11:06 Oh, you can go.
0:11:07 OK.
0:11:09 They’ll have special preserved shopping malls.
0:11:10 OK.
0:11:11 For the people.
0:11:12 You’re in Washington, DC.
0:11:13 The Smithsonian.
0:11:14 You’re in DC.
0:11:16 The Smithsonian will have a shopping mall that you can visit.
0:11:22 In fact, you can drive there on a special road for your non-self-driving car.
0:11:27 So, and tie your horse up out back.
0:11:32 So, I mean, look, there will be, the term is experiential retail.
0:11:33 So like, experiences.
0:11:36 Like, if it’s, look, I mean, if it’s like a Gucci boutique, and it’s a whole experience
0:11:39 to go there, or it’s an Apple store, or it’s a, you know, it’s got something where it’s
0:11:42 like there’s like real magnetic appeal to the experience, then fair enough, right?
0:11:43 And there’s, there’s actually a bunch of companies we’re involved in that are doing
0:11:44 things like that.
0:11:48 But like, you know, the idea of we’re going to buy a bunch of stuff that other people
0:11:51 make, and we’re going to put it in a big box, and then we’re going to make everybody
0:11:52 drive to the big box.
0:11:53 Like, the problems with that are kind of twofold.
0:11:57 Number one is consumers don’t actually want, what you want is you want the Star Trek replicator,
0:11:58 right?
0:12:00 Like, what you want is like, you press the button and like, there’s my stuff, right?
0:12:01 Like, it worked great on Star Trek.
0:12:02 We don’t have that yet.
0:12:03 Like, we don’t quite have that.
0:12:06 We don’t actually have the materializer yet, but we do have the ability to press the button
0:12:07 and stuff gets dropped off.
0:12:11 So, and the logistics infrastructure to support delivery is getting built up, right?
0:12:12 Very rapidly now.
0:12:15 And so, I think the consumer behavior is cutting over quite quickly.
0:12:18 And then the other problem is just kind of traditional, let’s say, third-party retail
0:12:21 where you’re not selling your own product, you’re selling somebody else’s product is,
0:12:24 you just can’t, basically, you’re levered as a retailer, right?
0:12:27 You basically live on the basis of credit from the suppliers.
0:12:29 And the problem with that, so you’re kind of like an overlevered bank in a lot of ways.
0:12:33 And so, the problem with that is you loot, there’s basically no retailer of other people’s
0:12:36 products where they could lose 30% of their revenue and then they stay in business.
0:12:39 Which is why you see these retailers just going bankrupt like all the time, right?
0:12:43 It’s like, Toys R Us was the most recent big one, like, it detonated and then it detonated
0:12:45 so hard that it actually went into full liquidation, right?
0:12:48 Which everybody thought, obviously, it’s Toys R Us, like, people love toys.
0:12:53 Like, obviously, somebody was going to buy Toys R Us and there was just no way to make
0:12:54 the math work.
0:12:57 And so, I just think it’s an overlevered business and that part is going to go down.
0:13:00 Now, what it’s going to do is very interesting, it’s going to open up all the space, right?
0:13:04 And so, there’s a whole revitalization of physical environments that’s going to happen,
0:13:05 right?
0:13:07 Including, you know, you see that happening already in cities, but I think it’s going
0:13:10 to happen all over the place because a lot of this space is going to open up for, let’s
0:13:11 say, more interesting uses.
0:13:15 So instead of going shopping, I’m going to do something with my wearables.
0:13:16 And what will that be?
0:13:17 What’s the potential in wearables?
0:13:21 I think the really big one right now is I think audio, you know, audio is on the rise,
0:13:22 just generally.
0:13:24 And particularly Apple, you know, with the AirPods is just, I think, hit an absolute
0:13:25 home run.
0:13:28 It’s one of the most deceptive, you know, things is it’s just like this little product
0:13:31 and like how important could it be and I think it’s like tremendously important because
0:13:34 it’s basically just like a voice in your ear anytime you want.
0:13:36 And so, you have, well, I’ll just give you one random example.
0:13:39 There are now these YouTube, you know, there’s these kind of new kinds of YouTube celebrities
0:13:41 and everybody’s kind of wondering like, what, you know, where are people getting all this
0:13:44 spare time to like watch all these YouTube videos and listen to all these YouTube, you
0:13:47 know, people, you know, in the tens and tens of millions and the answer is like they’re
0:13:48 at work.
0:13:49 Right?
0:13:54 They’ve got like, they’ve got like a Bluetooth thing in their ear and they’ve got a hat,
0:13:55 right?
0:13:56 That’s 10 hours on the forklift, right?
0:13:57 10 hours of Joe Rogan, right?
0:13:59 And so, like, that’s a big deal.
0:14:03 It’s a voice in your ear all the time and then, of course, speech as a UI is rapidly
0:14:04 on the rise.
0:14:07 And so I think audio is going to be, you know, titanically important.
0:14:10 I would say the second thing I nominate for wearables is just generally the concept of
0:14:11 sensors on the body, right?
0:14:14 And so here the Apple Watch is clearly out in the lead with what they’re doing with
0:14:18 the heartbeat sensor, but I think we’ll have a full complement of medical grade sensors,
0:14:22 you know, on our bodies in a way that we have chosen to over the next five or 10 years.
0:14:24 And I think we’re, I think we’ll get to the point where we’re going to be able to do things
0:14:26 like predict heart attacks and strokes before they happen.
0:14:29 But I think it’s like, I mean, talk about, like, talk about a killer app.
0:14:33 Like, I’m going to have a, beep, I’m going to have a heart attack in four hours.
0:14:34 Maybe I should drive to the hospital.
0:14:37 The survival rate for heart attack in the hospital is like 99%.
0:14:39 The survival rate for heart attack at home is like 50%.
0:14:43 Like, there’s an opportunity for like a massive increase of quality of life with the sensor
0:14:45 platforms people are going to have.
0:14:47 And then I think, I think optics are coming, right?
0:14:49 And it’s going to be a long road, but I think AR and VR are both going to work.
0:14:53 And I think they’re, I think we’re going to have heads-up displays that are, that honestly
0:14:55 are going to remove the need to, you know, what we have now, which is kind of this little
0:14:58 pane of glass that we’re expected to kind of experience the whole world through, right?
0:15:00 The whole world’s going to open up around us.
0:15:03 What are we, what are we going to do with augmented reality and virtual reality?
0:15:05 So I’m big believers in both.
0:15:09 I think AR has, you know, tons of potential applications both working at home.
0:15:10 We can spend a lot of time on that.
0:15:13 I think VR is going to be like a thousand times bigger in the valley right now.
0:15:16 This is a very contrarian view because I’ll, the general kind of theme that you hear in
0:15:18 the valley is AR is going to be bigger than VR.
0:15:22 And it seems like obviously AR should be bigger than VR because obviously if you can do things
0:15:26 overlaid on the real world, that should be sort of inherently more interesting than having
0:15:28 to construct sort of a synthetic world.
0:15:31 I just think that that’s only true for people who live in a very interesting place in the
0:15:34 real world, which we all do.
0:15:38 But you know, only, you know, something between like point 1% and 1% of people on earth live
0:15:41 in a place where it’s like they wake up every morning and they’re like, wow, there are so
0:15:42 many interesting things to see, right?
0:15:45 Like most people don’t live in a place like that, right?
0:15:50 And so for everybody who doesn’t already live on a college campus or in Silicon Valley or
0:15:53 in a major city, the new environments we’re going to be able to create in VR are going
0:15:56 to be inherently much more interesting, right, than the physical environments.
0:15:58 And there’s going to be a lot more of them to choose from.
0:16:00 And so it’s going to be amazing.
0:16:03 Ben, there’s a tweet I’ve been dying to ask you about.
0:16:10 There’s two types of people in this world, fresh prince of Bel Air people and Martin people.
0:16:13 I’m a Martin person for what it’s worth.
0:16:14 Who’s Martin?
0:16:15 That’s funny.
0:16:17 I think Nate wrote that tweet and I replied to it.
0:16:23 So there were two kind of major African-American television shows on in the early nineties.
0:16:28 The Fresh Prince of Bel Air, which was based on a rapper known as the Fresh Prince and his
0:16:31 DJ, DJ Jazzy Jeff.
0:16:33 The Fresh Prince was actually Will Smith.
0:16:35 Him I know, but the Martin is what puzzled me.
0:16:42 Martin is Martin Lawrence, who is a comedian, a genius comedian who is also incredibly crazy.
0:16:44 So crazy that his special was called You So Crazy.
0:16:48 He’s just like a very, very crazy guy.
0:16:53 But Fresh Prince of Bel Air was kind of like the hood Beverly hillbillies.
0:16:57 It’s kind of like, you know, you get the black people from the inner city and you put them
0:17:02 in Beverly Hills and it’s kind of funny and it’s safe for, you know, everybody.
0:17:03 There’s nothing too itchy.
0:17:05 You know, they keep it kind of easy.
0:17:11 And whereas Martin was like just full out, like Martin was like actually the hood and
0:17:13 he was nuts and like the whole thing was great.
0:17:15 And so that was my show.
0:17:16 Now it makes sense.
0:17:22 Could you recommend a rapper for people who think they do not like rap music?
0:17:23 Will Smith.
0:17:24 Will Smith.
0:17:26 The Fresh Prince of Bel Air.
0:17:28 And does Mark like Will Smith?
0:17:29 I don’t know.
0:17:31 Fire of Spotify tonight.
0:17:38 Mark, if we think about television as presenting conceptual material to us and every now and
0:17:41 then you’ll watch TV shows.
0:17:45 What’s a TV show you’ve been watching lately that has a lesson in it about venture capital
0:17:47 and what’s that lesson?
0:17:48 Can I name three?
0:17:49 Three, yes.
0:17:50 I watched a lot of TV.
0:17:53 Halt and Catch Fire, which actually recently ended after four seasons.
0:17:56 Halt and Catch Fire, when it came out, it came out right after Mad Men and it came out
0:17:58 as kind of people were like, well, it’s kind of like Mad Men, but it’s like much more of
0:17:59 like a pot boiler.
0:18:02 It’s like super like dramatic and they’re like, it’s just all the emotionality of it.
0:18:06 Like, you know, it’s about this creation of basically it’s about the creation of a compact,
0:18:10 the PC company in the early 80s, it’s a thinly bailed kind of starts out kind of with that,
0:18:11 the birth of the PC.
0:18:14 And so all the critics were like, well, this is like too dramatic.
0:18:18 And like Ben and I watch it and we’re like, you know, no, that’s, it’s about right.
0:18:19 Exactly.
0:18:21 It was like literally going back in time.
0:18:22 It was like.
0:18:23 It’s exactly right.
0:18:25 And it really is like that dramatic and that stressful and that crazy.
0:18:28 And so especially the first season of that show, I think it’s the most accurate portrayal
0:18:31 of what a tech startup is actually like that’s ever been aired.
0:18:32 So that’s one.
0:18:36 Another one that I really like for founders to watch and they always think I’m crazy,
0:18:37 but I really, really believe this.
0:18:42 There was a, there was a great show on USA years ago called Burn Notice, which is a
0:18:43 very fun show.
0:18:47 It was about a spy who’d gotten burned, a CIA spy who’d gotten burned and had a whole
0:18:50 of Miami try to clear his name and he took on all these odd jobs.
0:18:51 So fairly normal setup.
0:18:54 The conceit of the show was though, he had every conceivable skill you could possibly
0:18:55 have.
0:18:56 Right.
0:18:57 And so he knew how to make like explosives out of bleach.
0:19:00 Like he knew how to like, you know, I don’t know, like disarm somebody with a mop handle.
0:19:04 Like whatever circumstance he was in, he had the, and then there was a voiceover or he
0:19:05 would explain to you.
0:19:06 And you haven’t hired him yet.
0:19:09 Well, we would love to hire him, but basically, I look at him and it’s like, that’s kind
0:19:10 of, that’s a good founder.
0:19:14 Like a good founder has to basically have every conceivable skill.
0:19:16 Like you basically have to be good at product development and at marketing and at sales
0:19:21 and at finance, legal and at HR and management and, you know, on and on and on and on.
0:19:24 And there really is no substitute for actually being good at all these things.
0:19:26 And so I like that one.
0:19:31 And then the third one is succession, which I just finished, which is one of the darker
0:19:33 and funniest things I’ve ever seen.
0:19:37 Let’s just say it’s a, it’s inspiring for founders because it, I think, pretty accurately
0:19:42 shows the dysfunction at, let’s say, certain kinds of larger companies.
0:19:46 It’s a show about a succession battle at a major media company and I can’t recommend
0:19:49 it highly enough if you’ve got the stomach for bad words.
0:19:54 So Ben, the company is starting something called a cultural leadership fund.
0:19:58 What are the strengths and weaknesses of applying the venture capital model to culture and
0:19:59 entertainment?
0:20:02 Well, I think we’re trying to apply culture to the venture capital model.
0:20:04 So it’s a little bit the opposite.
0:20:07 Like, you know, you know, back to your earlier question, you know, we really pride ourselves
0:20:13 on being able to understand talent and talent of all kinds.
0:20:18 And you know, one of the things we did very early is we built a lot of relationships with
0:20:23 geniuses at moving culture and we thought this was important because as tech was moving
0:20:29 into much more kind of consumer oriented field when we started the firm, that the people
0:20:35 who really knew how to change and create new consumer behaviors would be interesting.
0:20:40 So we, you know, had relationships with all these cultural geniuses like Quincy Smith and
0:20:46 Sean Puffy Combs and Nas and so forth, but we were doing it kind of fairly one-off and
0:20:51 we thought, you know, it would be really great, you know, and it was a great advantage for
0:20:52 us.
0:20:55 And Oprah had one of our entrepreneurs on her favorite things show, but we thought, you
0:20:59 know, it was a good thing to share with the rest of the industry.
0:21:04 And so we would have these cultural geniuses, but you know, geniuses, but who didn’t look
0:21:08 like the geniuses, our guys were used to like, you know, Mark Zuckerberg or Brian Chesky.
0:21:13 They kind of felt different, but our guys were interested in working with them.
0:21:14 So we put them together.
0:21:18 They get to know each other, which has got value on both sides.
0:21:24 And it also gives a lot of value to our CEOs because not only do they get to kind of learn
0:21:27 how to move culture, but they also get to learn about how a different kind of talent
0:21:33 looks like, which is very, very valuable when you’re kind of in the war for talent.
0:21:38 And then we invested back in kind of young African Americans who are wanting to come
0:21:39 into tech.
0:21:44 So we created talent pipeline with the fund and we have straight access to the pipeline.
0:21:49 So I would just say we get a lot of credit for being nice, but we’re really just winning.
0:21:50 So it’s gone great.
0:21:51 It works well.
0:21:56 And look, you know, the main thesis is, you know, if you’ve got like a very small group
0:22:01 of people that created every new musical art form in the last century from jazz to blues
0:22:05 to hip hop to rock and roll, you know, like that’s a real thing.
0:22:06 Like to be able to do that.
0:22:12 And that’s a real talent base that, you know, we need to figure out how to get to.
0:22:14 And we’re here in Los Angeles.
0:22:16 We’re very close to Hollywood.
0:22:21 What is it conceptually that Hollywood grasps about venture capital and talent identification
0:22:23 where Silicon Valley lags behind?
0:22:27 Well, I think that, you know, I just think of their different kinds of talent.
0:22:32 So and this is the thing that I think people make a mistake on when they think about, you
0:22:37 know, how diversity works or how inclusion works and so forth is there’s talent that
0:22:38 looks different.
0:22:41 And then if you don’t have that talent, you might not be able to see it.
0:22:46 And so, you know, in Hollywood, they see certain kinds of talent that they’re used to because
0:22:51 they know what that is, they know how it pops on screen, they know how like people emotionally
0:22:52 connect to it.
0:22:56 And then in Silicon Valley, we know another kind of talent, you know, a talent for like
0:23:00 systems thinking and engineering and this kind of thing.
0:23:04 But both are very valuable when you put them together in a company.
0:23:09 And so I think that, you know, in these endeavors, what we try to do is to see talent that we’re
0:23:10 not.
0:23:11 And it’s not an easy thing to do.
0:23:15 And there’s a story I tell that Margaret had in her profile.
0:23:18 One of the things she looked at in her employees was helpfulness.
0:23:23 And when I saw that, it shocked me because I had been managing for like nearly 30 years
0:23:27 at the time and I’d never interviewed anybody on that.
0:23:28 I couldn’t even see it.
0:23:33 Like, there’s a thing that’s an important talent, very important talent to a services
0:23:36 firm like ours that I couldn’t even see.
0:23:38 So how am I going to hire it if I can’t see it?
0:23:42 And so we spent a lot of time at the firm trying to see talent that’s not like us.
0:23:46 I’d also for a good, the LA effect we’re down here.
0:23:51 So I think it’s also very interesting time because, you know, for basically from when
0:23:55 I entered tech in the early 90s up through call it maybe 2012, 2013, it was just kind
0:23:59 of taken as a given that the Silicon Valley companies were never going to figure out culture
0:24:00 and never going to figure out content.
0:24:03 And it was also taken as a given that the media companies were never going to figure out tech.
0:24:05 And there were tons of attempts to kind of cross over, but they basically didn’t, none
0:24:06 of them worked.
0:24:09 And it really isn’t the last like three years it feels like.
0:24:13 It feels like a bunch of the Valley companies are really starting to decode culture, but
0:24:16 to the big, I mean, Netflix being Netflix sort of, you know, sort of setting a new model,
0:24:20 but now being, you know, replicated by other companies, Amazon being the most notable example,
0:24:24 you know, becoming big forces in the, in the formation of culture and entertainment and
0:24:25 media.
0:24:28 And then also by the way, the other is the flip side is that a bunch of the big media companies
0:24:30 now have gotten to the point where they now take tech incredibly seriously and have, you
0:24:34 know, really sharp people working for them, working on very interesting projects.
0:24:37 And then there’s a whole tech thing obviously now happening down here in LA that’s that’s
0:24:39 of a new level of magnitude than before.
0:24:43 And so it does feel like both of the kind of central hubs of California are developing
0:24:44 and crossing over, you know, quite nicely now.
0:24:50 A general question, 20 years from now, will location and being in the Bay area matter more
0:24:51 or less?
0:24:52 Yes.
0:24:53 Clearly both.
0:24:55 So on the one hand, it is absolutely true.
0:24:59 I mean, in 20 years, you know, basically like telepresence technologies, right?
0:25:01 So video conferencing and VR and all these things, like 20 years from now, there’s no
0:25:05 question it’s going to be like much easier to run large distributed organizations, large
0:25:07 distributed efforts than it is today, right?
0:25:10 We’re going to have such high fidelity video conferencing everywhere.
0:25:11 You can actually see this today.
0:25:15 If you see the super high end video conferencing systems, it really is like you are there.
0:25:17 And then we have these robots that we love in our office.
0:25:21 Some of you have seen the beams, which are a prototype of what I think, I think telepresence
0:25:24 robots are actually going to be a very big deal because they give you a sense of physical
0:25:26 presence of somebody in a room that’s even different than a screen.
0:25:30 And so like those technologies and then collaboration technologies like Slack and GitHub, right, are
0:25:31 becoming really good today.
0:25:35 And in 20 years, they’re going to be, you know, just spectacularly amazing.
0:25:38 And so it’s going to be easier to run all these companies and be able to run all these
0:25:41 efforts on a broad basis, and then it’s just going to make it much more straightforward
0:25:44 for people all over the world to participate.
0:25:46 So that’s on the one hand, but the other thing though is just like, okay, that’s going to
0:25:49 be a world that’s much more connected, right, much more networked, right?
0:25:53 It’s going to be, you know, past 5G, we’re going to be like 9 or 10 or 11G, right?
0:25:54 It’s going to be bandwidth everywhere.
0:25:56 It’s going to be, everybody’s going to be online all the time.
0:25:59 We’re going to have all these, you know, wearables, being online is going to be part
0:26:01 of everybody’s daily experience all the time.
0:26:04 You know, the economy is going to reform itself around software network effects.
0:26:07 And so the winning companies, you know, the winning entrepreneurial companies 20 years
0:26:10 from now that win are going to be staggeringly large.
0:26:13 Like they’re going to be like, I don’t know, 10 or 100 times the size of Google and Facebook.
0:26:18 And so the prize to have a startup that scales and wins is going to become so large that
0:26:22 you’re going to want to hyper-optimize every possible thing you could possibly do to have
0:26:25 that extra chance that you’re going to be the one that wins, right?
0:26:28 And that’s going to mean like people in the same room together, right?
0:26:32 And so I think the valley is actually going to become more central, not less central,
0:26:35 even though the technologies that we’re building are making it possible for the world to distribute.
0:26:37 Ben, I love your book on management.
0:26:40 It’s the only book on management I’ve ever given to my daughter.
0:26:41 No, I appreciate that.
0:26:42 I knew I had one chance.
0:26:44 I picked yours.
0:26:46 In your view, what is the best predictor?
0:26:47 Not of innovation.
0:26:50 We’ve talked about that, but of simple managerial intelligence.
0:26:53 How do you spot that and what does it consist of?
0:26:55 Well, you know, it’s interesting.
0:26:59 It’s two skills that don’t normally go together.
0:27:07 So it’s systems thinking, which is, you know, and I hadn’t even noticed Mark actually pointed
0:27:10 this out to me many years ago, which is most people are not systems thinkers, meaning they
0:27:16 cannot think about, OK, if I change this here, then it’s going to affect that over there.
0:27:21 And you know, you know, as an economist, people always make these dumb mistakes like, OK,
0:27:23 well, move the minimum wage and nothing else will happen.
0:27:25 It’s like, well, no, no, it’s a system.
0:27:26 You have to think of it in terms of the system.
0:27:30 And so that’s kind of part of it and a big part of it.
0:27:37 But the other part, which is, can you actually see the people in your organization?
0:27:42 Like, do you know who they are as opposed to you’re talking to them like they’re you?
0:27:46 And meaning, do you understand their motivation?
0:27:49 Do you understand what they would think about something if they were in the room and you’re
0:27:52 making a decision?
0:27:57 Can you interpret them well enough so that it’s as though they’re there?
0:28:01 And can you understand the implications through the eyes of the people who work for you?
0:28:05 And if you have those two things together, those are the people who are really great,
0:28:06 but it’s a rare thing.
0:28:09 And you can kind of see it because you’ll be talking to them and like you might not
0:28:12 be able to articulate something and they can articulate it for you the way you would have
0:28:14 done it better.
0:28:19 Like somebody who’s that perceptive on people plus a systems thinker is really the those
0:28:21 of the people who are gifted.
0:28:24 And Mark, did you really invent the TweetStorm?
0:28:26 And if so, what’s the general lesson about innovation?
0:28:27 We should learn from that.
0:28:31 What is a general lesson?
0:28:36 Inability to shut up, I think might have had a lot to do with it.
0:28:37 But you did invent it.
0:28:39 I think there might have been sequences of tweets, but literally I couldn’t shut up.
0:28:41 So like, I think it kind of catalyzed.
0:28:44 Well, look, I mean, the big lesson from it has been that the big lesson actually have
0:28:47 a lot of the Internet platforms, which is emergent behavior is incredibly important, right?
0:28:52 The really successful platforms let the user surface the behaviors, right, that the creators
0:28:54 of the platform could have never thought of and, you know, Twitter set all kinds of issues
0:28:57 over the years, but like it always has been amazing.
0:28:59 Most of the compelling ways in which people use Twitter have been invented by the users.
0:29:03 I mean, I think it’s true, retweets were invented by users, right, like very, very fundamental
0:29:04 features.
0:29:05 And that’s not just Twitter.
0:29:06 That’s also been true.
0:29:07 It was true of actually personal computers.
0:29:08 It was true of smartphones.
0:29:10 It’s been true of, you know, many of these platforms.
0:29:15 And so it’s a useful principle of product design, which is let the users innovate.
0:29:20 Ben, you’re famous actually for your barbecue cooking, viewed as a problem of management
0:29:22 and also innovation.
0:29:26 What makes for the difference between good and truly excellent barbecue?
0:29:27 Time.
0:29:28 Say more.
0:29:29 Time.
0:29:30 So, you know, it’s funny.
0:29:36 I had an interesting conversation years ago with my wife’s cousin, Atlee, in Kanye West,
0:29:41 which was just like a weird thing because Atlee’s from Baton Rouge, Louisiana.
0:29:45 And I have him to be in New Orleans and Kanye was there and we’re all out to dinner.
0:29:50 And Kanye asked Atlee, he says, “What’s the definition of luxury?”
0:29:53 Which is like, if you’re from Baton Rouge, you just don’t think of that word, like you
0:29:55 never hear the word luxury.
0:29:59 And so Atlee says, “I just like to cook.”
0:30:00 And Kanye says, “Well, how do you cook?”
0:30:03 He says, “Well, like I like to make red beans and rice.”
0:30:04 And he’s like, “Well, how do you do that?”
0:30:08 He’s like, “Well, I take my time, you know, I cut the onions very slowly, I boil it for
0:30:10 a long time, I make sure it simmers.”
0:30:15 And Kanye says, “Exactly, time is luxury.”
0:30:17 Like that’s why I make luxury records.
0:30:18 I take my time.
0:30:21 And I was like, yeah, that’s it.
0:30:22 So.
0:30:28 Mark, do you prefer to eat for-profit sushi or nonprofit sushi?
0:30:33 This is Tyler’s favorite question to suss out whether people are actually pro-government,
0:30:34 pro-increased government services.
0:30:40 The idea of nonprofit sushi makes me so nauseous that I think I want to throw up on stage.
0:30:47 General question, what’s the one thing that Wall Street does not understand about technology
0:30:49 that you would change if you could?
0:30:51 I think part of it is it’s a 3,000-mile-like thing.
0:30:55 I think a big part of its culture, there’s just a delay, and there always has been.
0:30:58 And so, you know, if I wanted to fix that, I would say, like, we need to spend a lot
0:30:59 more time.
0:31:02 And by the way, the tech industry does need to spend a lot more time trying to tell people
0:31:05 what we’re doing, but at the same time, people from outside the tech industry need to spend
0:31:08 more time in the valley and understand what’s happening here.
0:31:10 And a lot of that is happening as well.
0:31:13 That’s how I’m not sure I want to fix it.
0:31:15 The question assumes I want to fix it, like, I don’t think I want to fix it, because that’s
0:31:17 a big part of the opportunity.
0:31:21 What’s the one thing the U.S. government does not understand about tech that you would change
0:31:22 if you could?
0:31:25 So I think the first thing is something that Andy Grove said many years ago, which is it’s
0:31:27 inevitable.
0:31:31 And so, you know, somebody had asked him, you know, is the microprocessor good or bad?
0:31:34 He said, well, that’s like asking a steal, a good or bad, he’s like, we’ve got to deal
0:31:36 with it, like, it’s here.
0:31:41 And I think that, you know, the biggest mistakes the government makes are assuming it’s not.
0:31:46 So, you know, stem cells is a great one where the U.S. government went to really hold that
0:31:47 back.
0:31:49 They end hold back stem cell development or research at all.
0:31:53 They just made it very inconvenient for people in the United States, and a lot of people died
0:31:57 and, you know, missed out on cures and all kinds of things because of that.
0:32:00 And so I think that’s number one.
0:32:05 And then I think the other thing is that technology is always had and always will have good and
0:32:06 bad implications.
0:32:12 Going back to the cotton gin, the printing press, you know, certainly the internet has
0:32:13 had good and bad.
0:32:18 But if you look at it overall, it’s overwhelmingly positive.
0:32:26 And more than that, we have to go back to our population levels in like 1750 if you’re
0:32:30 going to take away technology and take away technological advancement because the way
0:32:35 the human population is growing, there’s no way we can, you know, live the way we want
0:32:37 to live and have the lives we want to live without technology.
0:32:42 So getting into these debates of whether we should hold it back is just, you know, if
0:32:45 there’s one thing I would change, it’s like, let’s not have that debate.
0:32:47 Let’s have the debate how to make it great.
0:32:52 Mark, what’s the last thing software will eat?
0:32:53 Other than sushi.
0:32:55 Other than sushi.
0:32:59 So I think it’s fundamentally, the term that you used actually called it, I think, project
0:33:00 selection.
0:33:05 And so basically it’s this question of like, okay, how do you organize a small number of
0:33:07 people to do something new, right?
0:33:09 And by the way, that could be a startup company.
0:33:11 That could be many other kinds of efforts where you need a small number of people to
0:33:12 do something new.
0:33:14 It could be a new political campaign, a new activist movement, whatever, but a small number
0:33:16 of people to do something new, right?
0:33:19 And then how do you pick, if you’re going to finance or donate or fund those things,
0:33:23 how do you pick ones to donate to, and then how are those things actually going to run,
0:33:24 right?
0:33:27 So the new part there is really important, like the little known fact, for example, about
0:33:31 venture capital is that there’s a term in venture capital and hedge funds called Cary,
0:33:34 which is basically called Cary’s interest, which is the sort of profit participation
0:33:36 that the VCs or hedge fund managers make.
0:33:42 The term Cary actually comes from whaling in the 1600s off like, you know, in the Atlantic
0:33:46 Ocean, like literally their term Cary was the people who would finance the captain and
0:33:49 the crew of the boat, but the boat actually would run as a startup.
0:33:52 There was actually like equity participation for all the people in the boat, and then they
0:33:56 would pick a captain, you’d raise money in town, you’d raise capital, and then the boat
0:33:59 would go off and try to take down a whale, right?
0:34:03 And about, you know, three quarters of the time the boat would come back, the other quarter
0:34:04 of the time.
0:34:05 The whale would win.
0:34:06 The whale would win.
0:34:08 Moby Dick was not a joke.
0:34:12 And so the boat comes back about 75% of the time, and then literally Cary was the portion
0:34:15 of the whale that the investors got, right?
0:34:18 And so if you think about it, like the process, if you’re like in, you know, I don’t know,
0:34:22 whatever, Boston or wherever, in like, you know, 1675, and you’re trying to say, okay,
0:34:28 this ship, this captain, this crew, this mission, into these waters, right, with these weather
0:34:31 patterns, like, and how are they going to behave under pressure, and what’s going to
0:34:33 happen when things go wrong, and it’s a crew going to mute me, and like, are we going to
0:34:34 make any money doing this?
0:34:39 Like, the whole thing is just such an intricate kind of puzzle, and it revolves around people.
0:34:45 And so, if you’re sitting out at the whaling expedition, you know, the Santa Maria is the
0:34:46 same kind of thing.
0:34:47 Tech startups are the same way.
0:34:50 By the way, you know, green lighting a movie or a TV show in Hollywood is the exact same
0:34:51 kind of process.
0:34:55 And it’s just, it’s so intangible, and it’s so much based on the interaction of a small
0:34:57 number of people who are going to be under extreme pressure.
0:35:01 Like, if we could figure out a way to automate that, like, we’d fund that company and then
0:35:03 retire, but at least we don’t know how to do that.
0:35:07 For each of you, what’s an interesting book you’ve read lately?
0:35:11 So one of the most interesting books I’ve read lately is a Genghis Khan and the Making
0:35:17 of the Modern World by Jack Weatherford, and it turns out to be very unexpectedly the most
0:35:22 interesting book on the topic of how you think about inclusion that I’ve ever read, and Genghis
0:35:27 Khan is not known for his thoughts on inclusion because he’s mostly known for, like, being
0:35:29 just ruthless.
0:35:35 But he really, you know, he was a guy who came from kind of the border of northern Mongolia
0:35:39 and Siberia, a very bad part of the world, he had a very, very hard life growing up.
0:35:45 He was from kind of the lower, they had white bones and black bone, kind of the higher and
0:35:50 lower caste, he was a lower caste person, and, you know, a lot of his experience growing
0:35:56 up led him to this idea that he should choose for kind of talent, not the caste system,
0:36:00 and not even the tribe that he was in, which was a huge breakthrough at the time, you know,
0:36:04 nobody had done that, and the way he thought about it and the techniques that he used for
0:36:11 doing it were breakthroughs today, you know, and so I just found it to be like a super
0:36:15 interesting book, definitely a great management book for anybody who’s interested in that
0:36:16 topic.
0:36:17 Mark.
0:36:20 So, the best book, the book’s had the biggest impact on me, it’s an incredibly well-written
0:36:24 book, it’s, of course, out of print, it’s by actually a guy, I think, Tyler, you know,
0:36:25 Timur Karan.
0:36:26 Sure.
0:36:29 You know quite well, who’s a economics and…
0:36:30 Economist at Duke.
0:36:31 At Duke.
0:36:36 So it’s a book about, 20 years ago, it’s called Private Truth’s Public Lives, and it basically
0:36:38 tells the story, the theory that he basically has, he calls preference falsification, and
0:36:43 it’s basically the idea, it’s a situation in which people believe something in their
0:36:46 own head, and then they feel for social reasons that they can’t say it out loud.
0:36:50 And so it starts kind of with that as kind of an idea, and then it kind of extrapolates
0:36:54 out kind of what happens as a society becomes the kind of society in which people feel like
0:36:58 they can’t speak the things that they believe, and it turns out to be quite an elaborate
0:37:01 process because basically, right, you can have these very interesting situations where
0:37:04 you can have a majority of people who believe something, but then they all believe they
0:37:08 can’t say it, but then as a consequence, they all come to believe that there are many fewer
0:37:12 people who believe it than there actually are, and so you can kind of suppress a point
0:37:16 of view artificially for quite a long time, but then he describes in the book how you
0:37:19 can then kind of just get the reverse process, kind of get the whole thing, kind of the spring
0:37:24 to expand, which is if a few brave people start to speak up, then a lot of other people who
0:37:27 have had that secret belief all of a sudden realize they’re not alone, and then you start
0:37:30 a cascade, right, in which a lot of people start to speak up, and he basically models
0:37:34 in the book like that’s where revolutions come from, and it’s basically like an explanation
0:37:39 for the fall of the Berlin Wall, it’s an explanation for political revolution.
0:37:42 It so happens to be, I think, highly relevant to what’s happening both on the left and the
0:37:44 right in the U.S., like right now.
0:37:47 Like, I think it’s, as you read the book, you’re just like, okay, that’s the cleanest
0:37:51 explanation of the Trump phenomenon I’ve ever seen, and furthermore, it’s also the cleanest
0:37:53 explanation of the Bernie phenomenon I’ve ever seen, like I think it actually describes
0:37:54 both quite accurately.
0:37:58 For the last question, I’d like to return to Mark and Ben as a couple.
0:38:03 Ben, what’s Mark’s biggest misconception about you, and Mark, what’s Ben’s biggest
0:38:05 misconception about you?
0:38:11 So this is the sad thing, is that he knows me so well that I wish he had misperceptions
0:38:18 about me, but like, he actually knows who I am, and so this is, and it manifests itself
0:38:22 the worst, like if something’s going wrong at the firm, it’s always some combination
0:38:27 of his and my fault, and he’ll know exactly the flaws that I have that have led us to
0:38:34 that situation, and like, it’s unbearable, and vice versa, but I’ll let him answer.
0:38:36 And Mark, you have the last word.
0:38:39 Ben’s biggest misconception to me is he thinks I’m gonna go to my room tonight and listen
0:38:43 to Will Smith.
0:38:45 I thank you both very much for this dialogue.
0:38:46 Thanks everybody.
0:38:50 (audience applauding)
0:39:00 [BLANK_AUDIO]
0:00:10 tax or investment advice or be used to evaluate any investment or security and is not directed
0:00:14 at any investors or potential investors in any A16Z fund.
0:00:18 For more details, please see a16z.com/disclosures.
0:00:23 Hi everyone, welcome to the A6NZ podcast, I’m Sonal.
0:00:28 So this week, to continue our 10-year anniversary series since the founding of A6NZ, we’re
0:00:33 actually resurfacing some of our previous episodes featuring founders Mark Andreessen
0:00:34 and Ben Horwitz.
0:00:38 If you haven’t heard our latest episode with Stuart Butterfield turning the tables as the
0:00:42 entrepreneur interviewing them, please do check that out and our other episodes in this
0:00:46 series on our website at a6nz.com/10.
0:00:52 But this episode was recorded at our Innovation Summit in 2018 and features economist Tyler
0:00:57 Cowan interviewing them about everything from their partnership and how it works to
0:01:01 talent, tech trends, and software eating culture.
0:01:02 Thank you all for coming.
0:01:06 I’d like to start with the two of you as a couple.
0:01:07 Oh yeah.
0:01:10 How was it you met at Netscape in 1995?
0:01:13 Well, Mark interviewed me way back then and he interviewed me.
0:01:18 I think I was interviewing for product management role and he was the founder of the company
0:01:24 and I had worked on a product called Lotus Notes and Mark had a fascination with Lotus
0:01:26 Notes for a couple of reasons.
0:01:31 One was it was kind of sort of the closest proprietary thing to the internet and then
0:01:35 they had email in it and Netscape was looking at doing email.
0:01:40 So he had all kinds of questions for me and I remember him just being absolutely shocked
0:01:46 and flabbergasted that like 50% of our code base and Lotus Notes was just making like
0:01:52 all the LAN protocols work together, IPX and Apple Talk and Net Buoy, Net Bios.
0:01:55 You guys don’t even know what any of that is anymore.
0:01:59 He was like literally just making the network talk to each other, which he thought was like
0:02:02 ridiculous given there was TCP/IP.
0:02:04 That was the very first conversation we had.
0:02:06 Mark, how did he do in the interview?
0:02:07 He did very good.
0:02:08 He did very good.
0:02:10 So he had a giant asset.
0:02:12 He was the first employee from Lotus.
0:02:15 So he looked great in comparison to all the ones we haven’t seen before.
0:02:18 No, he did great.
0:02:20 He was super knowledgeable and actually it was actually a really big deal at the time
0:02:25 because Lotus Notes was a big thing at the time and what Ben just alluded to in the architecture
0:02:28 like it just basically assumed that the internet was not going to work, which was the dominant
0:02:29 assumption at that time.
0:02:32 It’s kind of how the whole thing was built and then most of the people working on it
0:02:35 I think probably agreed with that.
0:02:37 There were many, many arguments that the internet couldn’t possibly do what a system like Lotus
0:02:38 Notes did.
0:02:41 So Ben was, I would say, young enough and smart enough and knowledgeable enough to figure
0:02:46 out very early among his cohort of kind of the professionals in the space that it actually
0:02:51 was going to happen a different way and so we were a little fly by night startup.
0:02:53 So we fast forward to 1999.
0:02:55 You two do loud cloud together.
0:02:56 Why?
0:02:57 How’d that happen?
0:03:01 Well, so the big thing basically that happened was so it turns out the internet worked, which
0:03:03 turned out to be a big deal, go figure.
0:03:06 And then basically what happened was basically people were unprepared for the internet to
0:03:10 work at some fundamental level and then we saw a very specific kind of version of people
0:03:14 being unprepared for that, which is we sold Netscape in 1998 to AOL and so Ben and I and
0:03:17 a bunch of us were working at AOL and then AOL had this thing at the time.
0:03:22 AOL was a little bit like the Google of the era or something where they had like a firehose
0:03:25 of traffic that they could basically steer wherever they wanted to steer it.
0:03:27 And so if you went on AOL and you typed in by clothes.
0:03:29 Half the traffic on the internet went through AOL.
0:03:30 I remember that.
0:03:31 It was a really big deal.
0:03:32 Not my half, by the way.
0:03:33 Yeah.
0:03:34 But that’s a lot, still.
0:03:35 Half.
0:03:36 That’s right.
0:03:37 And then by the way, almost all consumers, right?
0:03:38 Almost all consumers were on AOL at the time.
0:03:43 So you type in by clothes on AOL and then they would sell to like J Crew or Gap or whatever
0:03:44 that slot.
0:03:48 So basically what happened is that advertising business and then AOL would turn on that ad
0:03:52 and then basically the firehose of traffic would just blast the website to bits, right?
0:03:56 If it was J Crew, they just blasted the J Crew website to bits and then the J Crew people
0:03:58 would spend weeks trying to get the website to work to actually take advantage of all
0:03:59 this traffic.
0:04:03 And so it was sort of, you know, it just seemed kind of obvious that we, you know, we were
0:04:05 kind of in this business and so you go talk to the people running these things and they
0:04:09 just, they didn’t, they were just unprepared for this kind of sophistication.
0:04:13 And so we sort of incubated this idea that, boy, what if there was a cloud, right?
0:04:17 What if basically there was a system in which you could take your content and all your apps
0:04:19 and you could run them and it could handle the load and you could, you know, it could
0:04:23 load balance and it could spike up in response to demand and then all these companies, instead
0:04:25 of being in the business of running all your own stuff, like why can’t you just hand it
0:04:26 over to the pros?
0:04:29 And so, and then this is in the full flush of the dot com boom.
0:04:31 So it just seemed like an obvious opportunity.
0:04:36 And so 2009 comes along and why is it it seems to you both then that’s the right time for
0:04:38 a new venture capital firm?
0:04:39 What was the thought?
0:04:44 Well, you know, it was really one of those ideas that just came out of our experience.
0:04:49 You know, we were customers of venture capital and, you know, we had a couple of observations.
0:04:53 One was, you know, we had noticed over the years and Mark really made the observation
0:04:59 first that most of the really great companies, like forget about successful, but like great
0:05:02 companies, companies you admire and tech were all run by their founders for a very long
0:05:03 time.
0:05:10 Like Thomas Watson at IBM or Dave Packard, Bill Hewlett at Hewlett Packard or, you know,
0:05:16 Bill Gates or whoever it was, all the really giant successes were run by their founders.
0:05:20 And the conventional wisdom and venture capital was set up to replace the founder.
0:05:25 And then in our own experiences as technical founders, we knew why that was true because,
0:05:30 you know, well, if you just took, you know, loud like nobody would have ever been able
0:05:32 to fix loud cloud other than us.
0:05:36 Like there was no way you could bring in a professional to do that.
0:05:39 And so getting to that next product after you get the first product, getting to the
0:05:43 next product market fit required an innovator.
0:05:46 And so if you wanted subsequent product cycles, you needed the founder.
0:05:50 And so we just thought there ought to be a firm that is designed to do that.
0:05:53 And what is it that the two of you figured out?
0:05:56 What is it you two understood that other people didn’t?
0:05:57 And how would you articulate that?
0:06:01 You know, like we were just, there was a bunch of things.
0:06:02 One differentiation.
0:06:06 So like we came from a company, so we’re like, first we’re going to tell a very clear
0:06:09 sharp story about a real network that we’ve built out systematically.
0:06:13 We’ve got people who are going on your board who know exactly how to build companies.
0:06:17 So sometimes it feels to some people, there’s a lot of money running around, but talent
0:06:18 is quite scarce.
0:06:22 What is it that you two in the company as a whole have understood about talent search
0:06:23 that other people have not?
0:06:26 So we actually thought of it as a talent business.
0:06:30 And a lot of the reason for that is, you know, a friend of ours, Michael Ovitz, who founded
0:06:33 the talent agency, CAA, was a board member of ours at Opsware.
0:06:41 And you know, he always thought about talent in amazing detail and like, in incredibly
0:06:46 specific and one of his biggest concepts about it was, it was a network.
0:06:50 And you had to run the, and it seemed simple, oh, it’s a network, okay, great.
0:06:52 But like, how do you build that network?
0:06:53 How does it work?
0:06:56 How do you take a long view of the relationships with the talent?
0:07:03 So you know, we really thought out very early on, we’re going to invest heavily in building
0:07:09 this network and having the time, the luxury of time to build real relationships as opposed
0:07:13 to transactional relationships with every single person that we run into, be they an
0:07:18 engineer, an entrepreneur, a corporate partner, or whomever.
0:07:21 And that all kind of came out of this original CAA concept.
0:07:26 If you take a long view of relationships, you can build a network that’s so powerful
0:07:27 that nobody will ever be able to match it.
0:07:30 And that was kind of the original inspiration.
0:07:35 And we were fortunate enough to just hire a really astoundingly good team to help us
0:07:36 do that.
0:07:38 And Mark, how do you think about talent assessment?
0:07:41 So I think, you know, the other side of it is just the entrepreneur assessment, right?
0:07:44 And so it’s just one of those things where, you know, there is kind of this fundamental
0:07:47 question of kind of how extreme are you willing to get, right, with some of these people, right?
0:07:52 Because you know, the kinds of people who start these companies are not normal.
0:07:55 And we can say that speaking from experience, having done it ourselves.
0:07:58 And so, and I would actually go so far as to argue, like, it may be that the founders
0:08:02 are getting less normal as sort of society gets, let’s just say, more interesting in
0:08:03 recent years.
0:08:06 And so, you know, the ideas are getting bigger, the technologies are getting more disruptive,
0:08:09 the companies that win are getting much larger, technology is more central in everybody’s
0:08:10 lives.
0:08:11 By the way, there’s more competition than ever.
0:08:12 There are more tech startups than ever.
0:08:16 And so the kind of very special person who’s going to conceive of an original idea and
0:08:19 then be able to build a team and be able to prosecute the idea is going to be a very extreme
0:08:20 person.
0:08:24 And so a lot of it is sort of this, you know, the discovery and then partnering with these
0:08:25 really extreme people.
0:08:28 I’m going to throw out a few questions about particular technologies.
0:08:33 And either of you feel free to answer blockchain, what will be the breakthrough application
0:08:34 for blockchain?
0:08:35 I’ll take that.
0:08:38 So first of all, like asking what the killer app is, nobody ever gets it right.
0:08:42 Like I remember the internet killer app, it was never Facebook, that’s for sure.
0:08:48 But the way that we think about blockchain technology is that it’s a new computing platform.
0:08:54 And like other new computing platforms that preceded it, it’s worse in every way, but
0:08:56 really a very few ways.
0:09:00 So if you think about the smartphone, when it came out, it was much worse than the PC
0:09:02 at a tiny screen.
0:09:05 It was far less powerful, et cetera, et cetera.
0:09:08 People were like, how am I going to run my spreadsheet on that little ass screen?
0:09:11 Like there’s no way it’s going to work.
0:09:13 But I had a couple of properties that you didn’t have in the PC.
0:09:14 It had a GPS.
0:09:15 It had a camera.
0:09:17 And so you can now build things like Lyft.
0:09:21 You can now build things like Instagram that you could never build on a PC, and you still
0:09:22 can’t build on a PC.
0:09:26 And it created a whole new world of applications.
0:09:27 Blockchain is like that.
0:09:28 It’s slower.
0:09:29 It’s harder to use.
0:09:30 It’s harder to program.
0:09:34 But it has a new feature, and that feature is trust.
0:09:39 And trust is really, really an interesting feature because it means that you don’t have
0:09:45 to trust the government or a corporation or your lawyer.
0:09:50 You just have to trust the mathematical properties and the game theoretic properties of the system,
0:09:51 and then you can do things.
0:09:56 And it opens up applications such as you can program money.
0:09:59 You can program contracts.
0:10:03 You can create digital property, which is, you know, if you just think about the art
0:10:07 world, it’s an amazing kind of world, and it’s all virtual value.
0:10:13 You know, Bosque, it’s $150 million, but like the canvas is probably less than $5.
0:10:16 But because you know that it’s one of one, it’s got value, well, you can now do that
0:10:17 digitally with blockchain.
0:10:19 So there’s those kinds of things.
0:10:21 And then you don’t have to trust companies.
0:10:25 So if you’re a developer and you’re building an application, you know, you don’t have to
0:10:28 trust Facebook to not go, well, like, you know, we decided, like, we’re changing our privacy
0:10:29 policy.
0:10:30 You can’t run anymore.
0:10:33 Or if you’re a consumer, you don’t have to say, OK, like, I’ve got to trust you with
0:10:34 my data.
0:10:38 So that property of trust, we think, is very, very powerful, and there is a large set of
0:10:40 applications that will come off of that.
0:10:44 But you know, like, it takes a while for developers to get used to it, for the technology to
0:10:45 mature and so forth.
0:10:48 But it’s one of the things we’re most excited about.
0:10:52 Paint a picture for me 15 years from now.
0:10:53 Retail and wearables.
0:10:57 What will tech do for me in those areas that it’s not doing right now?
0:11:00 So I think retail will basically be gone by then.
0:11:01 I mean, so.
0:11:02 Gone?
0:11:03 I can’t go to the shopping mall anymore.
0:11:04 Who wants to go to the shopping mall?
0:11:05 I want to go to the shopping mall.
0:11:06 Oh, you can go.
0:11:07 OK.
0:11:09 They’ll have special preserved shopping malls.
0:11:10 OK.
0:11:11 For the people.
0:11:12 You’re in Washington, DC.
0:11:13 The Smithsonian.
0:11:14 You’re in DC.
0:11:16 The Smithsonian will have a shopping mall that you can visit.
0:11:22 In fact, you can drive there on a special road for your non-self-driving car.
0:11:27 So, and tie your horse up out back.
0:11:32 So, I mean, look, there will be, the term is experiential retail.
0:11:33 So like, experiences.
0:11:36 Like, if it’s, look, I mean, if it’s like a Gucci boutique, and it’s a whole experience
0:11:39 to go there, or it’s an Apple store, or it’s a, you know, it’s got something where it’s
0:11:42 like there’s like real magnetic appeal to the experience, then fair enough, right?
0:11:43 And there’s, there’s actually a bunch of companies we’re involved in that are doing
0:11:44 things like that.
0:11:48 But like, you know, the idea of we’re going to buy a bunch of stuff that other people
0:11:51 make, and we’re going to put it in a big box, and then we’re going to make everybody
0:11:52 drive to the big box.
0:11:53 Like, the problems with that are kind of twofold.
0:11:57 Number one is consumers don’t actually want, what you want is you want the Star Trek replicator,
0:11:58 right?
0:12:00 Like, what you want is like, you press the button and like, there’s my stuff, right?
0:12:01 Like, it worked great on Star Trek.
0:12:02 We don’t have that yet.
0:12:03 Like, we don’t quite have that.
0:12:06 We don’t actually have the materializer yet, but we do have the ability to press the button
0:12:07 and stuff gets dropped off.
0:12:11 So, and the logistics infrastructure to support delivery is getting built up, right?
0:12:12 Very rapidly now.
0:12:15 And so, I think the consumer behavior is cutting over quite quickly.
0:12:18 And then the other problem is just kind of traditional, let’s say, third-party retail
0:12:21 where you’re not selling your own product, you’re selling somebody else’s product is,
0:12:24 you just can’t, basically, you’re levered as a retailer, right?
0:12:27 You basically live on the basis of credit from the suppliers.
0:12:29 And the problem with that, so you’re kind of like an overlevered bank in a lot of ways.
0:12:33 And so, the problem with that is you loot, there’s basically no retailer of other people’s
0:12:36 products where they could lose 30% of their revenue and then they stay in business.
0:12:39 Which is why you see these retailers just going bankrupt like all the time, right?
0:12:43 It’s like, Toys R Us was the most recent big one, like, it detonated and then it detonated
0:12:45 so hard that it actually went into full liquidation, right?
0:12:48 Which everybody thought, obviously, it’s Toys R Us, like, people love toys.
0:12:53 Like, obviously, somebody was going to buy Toys R Us and there was just no way to make
0:12:54 the math work.
0:12:57 And so, I just think it’s an overlevered business and that part is going to go down.
0:13:00 Now, what it’s going to do is very interesting, it’s going to open up all the space, right?
0:13:04 And so, there’s a whole revitalization of physical environments that’s going to happen,
0:13:05 right?
0:13:07 Including, you know, you see that happening already in cities, but I think it’s going
0:13:10 to happen all over the place because a lot of this space is going to open up for, let’s
0:13:11 say, more interesting uses.
0:13:15 So instead of going shopping, I’m going to do something with my wearables.
0:13:16 And what will that be?
0:13:17 What’s the potential in wearables?
0:13:21 I think the really big one right now is I think audio, you know, audio is on the rise,
0:13:22 just generally.
0:13:24 And particularly Apple, you know, with the AirPods is just, I think, hit an absolute
0:13:25 home run.
0:13:28 It’s one of the most deceptive, you know, things is it’s just like this little product
0:13:31 and like how important could it be and I think it’s like tremendously important because
0:13:34 it’s basically just like a voice in your ear anytime you want.
0:13:36 And so, you have, well, I’ll just give you one random example.
0:13:39 There are now these YouTube, you know, there’s these kind of new kinds of YouTube celebrities
0:13:41 and everybody’s kind of wondering like, what, you know, where are people getting all this
0:13:44 spare time to like watch all these YouTube videos and listen to all these YouTube, you
0:13:47 know, people, you know, in the tens and tens of millions and the answer is like they’re
0:13:48 at work.
0:13:49 Right?
0:13:54 They’ve got like, they’ve got like a Bluetooth thing in their ear and they’ve got a hat,
0:13:55 right?
0:13:56 That’s 10 hours on the forklift, right?
0:13:57 10 hours of Joe Rogan, right?
0:13:59 And so, like, that’s a big deal.
0:14:03 It’s a voice in your ear all the time and then, of course, speech as a UI is rapidly
0:14:04 on the rise.
0:14:07 And so I think audio is going to be, you know, titanically important.
0:14:10 I would say the second thing I nominate for wearables is just generally the concept of
0:14:11 sensors on the body, right?
0:14:14 And so here the Apple Watch is clearly out in the lead with what they’re doing with
0:14:18 the heartbeat sensor, but I think we’ll have a full complement of medical grade sensors,
0:14:22 you know, on our bodies in a way that we have chosen to over the next five or 10 years.
0:14:24 And I think we’re, I think we’ll get to the point where we’re going to be able to do things
0:14:26 like predict heart attacks and strokes before they happen.
0:14:29 But I think it’s like, I mean, talk about, like, talk about a killer app.
0:14:33 Like, I’m going to have a, beep, I’m going to have a heart attack in four hours.
0:14:34 Maybe I should drive to the hospital.
0:14:37 The survival rate for heart attack in the hospital is like 99%.
0:14:39 The survival rate for heart attack at home is like 50%.
0:14:43 Like, there’s an opportunity for like a massive increase of quality of life with the sensor
0:14:45 platforms people are going to have.
0:14:47 And then I think, I think optics are coming, right?
0:14:49 And it’s going to be a long road, but I think AR and VR are both going to work.
0:14:53 And I think they’re, I think we’re going to have heads-up displays that are, that honestly
0:14:55 are going to remove the need to, you know, what we have now, which is kind of this little
0:14:58 pane of glass that we’re expected to kind of experience the whole world through, right?
0:15:00 The whole world’s going to open up around us.
0:15:03 What are we, what are we going to do with augmented reality and virtual reality?
0:15:05 So I’m big believers in both.
0:15:09 I think AR has, you know, tons of potential applications both working at home.
0:15:10 We can spend a lot of time on that.
0:15:13 I think VR is going to be like a thousand times bigger in the valley right now.
0:15:16 This is a very contrarian view because I’ll, the general kind of theme that you hear in
0:15:18 the valley is AR is going to be bigger than VR.
0:15:22 And it seems like obviously AR should be bigger than VR because obviously if you can do things
0:15:26 overlaid on the real world, that should be sort of inherently more interesting than having
0:15:28 to construct sort of a synthetic world.
0:15:31 I just think that that’s only true for people who live in a very interesting place in the
0:15:34 real world, which we all do.
0:15:38 But you know, only, you know, something between like point 1% and 1% of people on earth live
0:15:41 in a place where it’s like they wake up every morning and they’re like, wow, there are so
0:15:42 many interesting things to see, right?
0:15:45 Like most people don’t live in a place like that, right?
0:15:50 And so for everybody who doesn’t already live on a college campus or in Silicon Valley or
0:15:53 in a major city, the new environments we’re going to be able to create in VR are going
0:15:56 to be inherently much more interesting, right, than the physical environments.
0:15:58 And there’s going to be a lot more of them to choose from.
0:16:00 And so it’s going to be amazing.
0:16:03 Ben, there’s a tweet I’ve been dying to ask you about.
0:16:10 There’s two types of people in this world, fresh prince of Bel Air people and Martin people.
0:16:13 I’m a Martin person for what it’s worth.
0:16:14 Who’s Martin?
0:16:15 That’s funny.
0:16:17 I think Nate wrote that tweet and I replied to it.
0:16:23 So there were two kind of major African-American television shows on in the early nineties.
0:16:28 The Fresh Prince of Bel Air, which was based on a rapper known as the Fresh Prince and his
0:16:31 DJ, DJ Jazzy Jeff.
0:16:33 The Fresh Prince was actually Will Smith.
0:16:35 Him I know, but the Martin is what puzzled me.
0:16:42 Martin is Martin Lawrence, who is a comedian, a genius comedian who is also incredibly crazy.
0:16:44 So crazy that his special was called You So Crazy.
0:16:48 He’s just like a very, very crazy guy.
0:16:53 But Fresh Prince of Bel Air was kind of like the hood Beverly hillbillies.
0:16:57 It’s kind of like, you know, you get the black people from the inner city and you put them
0:17:02 in Beverly Hills and it’s kind of funny and it’s safe for, you know, everybody.
0:17:03 There’s nothing too itchy.
0:17:05 You know, they keep it kind of easy.
0:17:11 And whereas Martin was like just full out, like Martin was like actually the hood and
0:17:13 he was nuts and like the whole thing was great.
0:17:15 And so that was my show.
0:17:16 Now it makes sense.
0:17:22 Could you recommend a rapper for people who think they do not like rap music?
0:17:23 Will Smith.
0:17:24 Will Smith.
0:17:26 The Fresh Prince of Bel Air.
0:17:28 And does Mark like Will Smith?
0:17:29 I don’t know.
0:17:31 Fire of Spotify tonight.
0:17:38 Mark, if we think about television as presenting conceptual material to us and every now and
0:17:41 then you’ll watch TV shows.
0:17:45 What’s a TV show you’ve been watching lately that has a lesson in it about venture capital
0:17:47 and what’s that lesson?
0:17:48 Can I name three?
0:17:49 Three, yes.
0:17:50 I watched a lot of TV.
0:17:53 Halt and Catch Fire, which actually recently ended after four seasons.
0:17:56 Halt and Catch Fire, when it came out, it came out right after Mad Men and it came out
0:17:58 as kind of people were like, well, it’s kind of like Mad Men, but it’s like much more of
0:17:59 like a pot boiler.
0:18:02 It’s like super like dramatic and they’re like, it’s just all the emotionality of it.
0:18:06 Like, you know, it’s about this creation of basically it’s about the creation of a compact,
0:18:10 the PC company in the early 80s, it’s a thinly bailed kind of starts out kind of with that,
0:18:11 the birth of the PC.
0:18:14 And so all the critics were like, well, this is like too dramatic.
0:18:18 And like Ben and I watch it and we’re like, you know, no, that’s, it’s about right.
0:18:19 Exactly.
0:18:21 It was like literally going back in time.
0:18:22 It was like.
0:18:23 It’s exactly right.
0:18:25 And it really is like that dramatic and that stressful and that crazy.
0:18:28 And so especially the first season of that show, I think it’s the most accurate portrayal
0:18:31 of what a tech startup is actually like that’s ever been aired.
0:18:32 So that’s one.
0:18:36 Another one that I really like for founders to watch and they always think I’m crazy,
0:18:37 but I really, really believe this.
0:18:42 There was a, there was a great show on USA years ago called Burn Notice, which is a
0:18:43 very fun show.
0:18:47 It was about a spy who’d gotten burned, a CIA spy who’d gotten burned and had a whole
0:18:50 of Miami try to clear his name and he took on all these odd jobs.
0:18:51 So fairly normal setup.
0:18:54 The conceit of the show was though, he had every conceivable skill you could possibly
0:18:55 have.
0:18:56 Right.
0:18:57 And so he knew how to make like explosives out of bleach.
0:19:00 Like he knew how to like, you know, I don’t know, like disarm somebody with a mop handle.
0:19:04 Like whatever circumstance he was in, he had the, and then there was a voiceover or he
0:19:05 would explain to you.
0:19:06 And you haven’t hired him yet.
0:19:09 Well, we would love to hire him, but basically, I look at him and it’s like, that’s kind
0:19:10 of, that’s a good founder.
0:19:14 Like a good founder has to basically have every conceivable skill.
0:19:16 Like you basically have to be good at product development and at marketing and at sales
0:19:21 and at finance, legal and at HR and management and, you know, on and on and on and on.
0:19:24 And there really is no substitute for actually being good at all these things.
0:19:26 And so I like that one.
0:19:31 And then the third one is succession, which I just finished, which is one of the darker
0:19:33 and funniest things I’ve ever seen.
0:19:37 Let’s just say it’s a, it’s inspiring for founders because it, I think, pretty accurately
0:19:42 shows the dysfunction at, let’s say, certain kinds of larger companies.
0:19:46 It’s a show about a succession battle at a major media company and I can’t recommend
0:19:49 it highly enough if you’ve got the stomach for bad words.
0:19:54 So Ben, the company is starting something called a cultural leadership fund.
0:19:58 What are the strengths and weaknesses of applying the venture capital model to culture and
0:19:59 entertainment?
0:20:02 Well, I think we’re trying to apply culture to the venture capital model.
0:20:04 So it’s a little bit the opposite.
0:20:07 Like, you know, you know, back to your earlier question, you know, we really pride ourselves
0:20:13 on being able to understand talent and talent of all kinds.
0:20:18 And you know, one of the things we did very early is we built a lot of relationships with
0:20:23 geniuses at moving culture and we thought this was important because as tech was moving
0:20:29 into much more kind of consumer oriented field when we started the firm, that the people
0:20:35 who really knew how to change and create new consumer behaviors would be interesting.
0:20:40 So we, you know, had relationships with all these cultural geniuses like Quincy Smith and
0:20:46 Sean Puffy Combs and Nas and so forth, but we were doing it kind of fairly one-off and
0:20:51 we thought, you know, it would be really great, you know, and it was a great advantage for
0:20:52 us.
0:20:55 And Oprah had one of our entrepreneurs on her favorite things show, but we thought, you
0:20:59 know, it was a good thing to share with the rest of the industry.
0:21:04 And so we would have these cultural geniuses, but you know, geniuses, but who didn’t look
0:21:08 like the geniuses, our guys were used to like, you know, Mark Zuckerberg or Brian Chesky.
0:21:13 They kind of felt different, but our guys were interested in working with them.
0:21:14 So we put them together.
0:21:18 They get to know each other, which has got value on both sides.
0:21:24 And it also gives a lot of value to our CEOs because not only do they get to kind of learn
0:21:27 how to move culture, but they also get to learn about how a different kind of talent
0:21:33 looks like, which is very, very valuable when you’re kind of in the war for talent.
0:21:38 And then we invested back in kind of young African Americans who are wanting to come
0:21:39 into tech.
0:21:44 So we created talent pipeline with the fund and we have straight access to the pipeline.
0:21:49 So I would just say we get a lot of credit for being nice, but we’re really just winning.
0:21:50 So it’s gone great.
0:21:51 It works well.
0:21:56 And look, you know, the main thesis is, you know, if you’ve got like a very small group
0:22:01 of people that created every new musical art form in the last century from jazz to blues
0:22:05 to hip hop to rock and roll, you know, like that’s a real thing.
0:22:06 Like to be able to do that.
0:22:12 And that’s a real talent base that, you know, we need to figure out how to get to.
0:22:14 And we’re here in Los Angeles.
0:22:16 We’re very close to Hollywood.
0:22:21 What is it conceptually that Hollywood grasps about venture capital and talent identification
0:22:23 where Silicon Valley lags behind?
0:22:27 Well, I think that, you know, I just think of their different kinds of talent.
0:22:32 So and this is the thing that I think people make a mistake on when they think about, you
0:22:37 know, how diversity works or how inclusion works and so forth is there’s talent that
0:22:38 looks different.
0:22:41 And then if you don’t have that talent, you might not be able to see it.
0:22:46 And so, you know, in Hollywood, they see certain kinds of talent that they’re used to because
0:22:51 they know what that is, they know how it pops on screen, they know how like people emotionally
0:22:52 connect to it.
0:22:56 And then in Silicon Valley, we know another kind of talent, you know, a talent for like
0:23:00 systems thinking and engineering and this kind of thing.
0:23:04 But both are very valuable when you put them together in a company.
0:23:09 And so I think that, you know, in these endeavors, what we try to do is to see talent that we’re
0:23:10 not.
0:23:11 And it’s not an easy thing to do.
0:23:15 And there’s a story I tell that Margaret had in her profile.
0:23:18 One of the things she looked at in her employees was helpfulness.
0:23:23 And when I saw that, it shocked me because I had been managing for like nearly 30 years
0:23:27 at the time and I’d never interviewed anybody on that.
0:23:28 I couldn’t even see it.
0:23:33 Like, there’s a thing that’s an important talent, very important talent to a services
0:23:36 firm like ours that I couldn’t even see.
0:23:38 So how am I going to hire it if I can’t see it?
0:23:42 And so we spent a lot of time at the firm trying to see talent that’s not like us.
0:23:46 I’d also for a good, the LA effect we’re down here.
0:23:51 So I think it’s also very interesting time because, you know, for basically from when
0:23:55 I entered tech in the early 90s up through call it maybe 2012, 2013, it was just kind
0:23:59 of taken as a given that the Silicon Valley companies were never going to figure out culture
0:24:00 and never going to figure out content.
0:24:03 And it was also taken as a given that the media companies were never going to figure out tech.
0:24:05 And there were tons of attempts to kind of cross over, but they basically didn’t, none
0:24:06 of them worked.
0:24:09 And it really isn’t the last like three years it feels like.
0:24:13 It feels like a bunch of the Valley companies are really starting to decode culture, but
0:24:16 to the big, I mean, Netflix being Netflix sort of, you know, sort of setting a new model,
0:24:20 but now being, you know, replicated by other companies, Amazon being the most notable example,
0:24:24 you know, becoming big forces in the, in the formation of culture and entertainment and
0:24:25 media.
0:24:28 And then also by the way, the other is the flip side is that a bunch of the big media companies
0:24:30 now have gotten to the point where they now take tech incredibly seriously and have, you
0:24:34 know, really sharp people working for them, working on very interesting projects.
0:24:37 And then there’s a whole tech thing obviously now happening down here in LA that’s that’s
0:24:39 of a new level of magnitude than before.
0:24:43 And so it does feel like both of the kind of central hubs of California are developing
0:24:44 and crossing over, you know, quite nicely now.
0:24:50 A general question, 20 years from now, will location and being in the Bay area matter more
0:24:51 or less?
0:24:52 Yes.
0:24:53 Clearly both.
0:24:55 So on the one hand, it is absolutely true.
0:24:59 I mean, in 20 years, you know, basically like telepresence technologies, right?
0:25:01 So video conferencing and VR and all these things, like 20 years from now, there’s no
0:25:05 question it’s going to be like much easier to run large distributed organizations, large
0:25:07 distributed efforts than it is today, right?
0:25:10 We’re going to have such high fidelity video conferencing everywhere.
0:25:11 You can actually see this today.
0:25:15 If you see the super high end video conferencing systems, it really is like you are there.
0:25:17 And then we have these robots that we love in our office.
0:25:21 Some of you have seen the beams, which are a prototype of what I think, I think telepresence
0:25:24 robots are actually going to be a very big deal because they give you a sense of physical
0:25:26 presence of somebody in a room that’s even different than a screen.
0:25:30 And so like those technologies and then collaboration technologies like Slack and GitHub, right, are
0:25:31 becoming really good today.
0:25:35 And in 20 years, they’re going to be, you know, just spectacularly amazing.
0:25:38 And so it’s going to be easier to run all these companies and be able to run all these
0:25:41 efforts on a broad basis, and then it’s just going to make it much more straightforward
0:25:44 for people all over the world to participate.
0:25:46 So that’s on the one hand, but the other thing though is just like, okay, that’s going to
0:25:49 be a world that’s much more connected, right, much more networked, right?
0:25:53 It’s going to be, you know, past 5G, we’re going to be like 9 or 10 or 11G, right?
0:25:54 It’s going to be bandwidth everywhere.
0:25:56 It’s going to be, everybody’s going to be online all the time.
0:25:59 We’re going to have all these, you know, wearables, being online is going to be part
0:26:01 of everybody’s daily experience all the time.
0:26:04 You know, the economy is going to reform itself around software network effects.
0:26:07 And so the winning companies, you know, the winning entrepreneurial companies 20 years
0:26:10 from now that win are going to be staggeringly large.
0:26:13 Like they’re going to be like, I don’t know, 10 or 100 times the size of Google and Facebook.
0:26:18 And so the prize to have a startup that scales and wins is going to become so large that
0:26:22 you’re going to want to hyper-optimize every possible thing you could possibly do to have
0:26:25 that extra chance that you’re going to be the one that wins, right?
0:26:28 And that’s going to mean like people in the same room together, right?
0:26:32 And so I think the valley is actually going to become more central, not less central,
0:26:35 even though the technologies that we’re building are making it possible for the world to distribute.
0:26:37 Ben, I love your book on management.
0:26:40 It’s the only book on management I’ve ever given to my daughter.
0:26:41 No, I appreciate that.
0:26:42 I knew I had one chance.
0:26:44 I picked yours.
0:26:46 In your view, what is the best predictor?
0:26:47 Not of innovation.
0:26:50 We’ve talked about that, but of simple managerial intelligence.
0:26:53 How do you spot that and what does it consist of?
0:26:55 Well, you know, it’s interesting.
0:26:59 It’s two skills that don’t normally go together.
0:27:07 So it’s systems thinking, which is, you know, and I hadn’t even noticed Mark actually pointed
0:27:10 this out to me many years ago, which is most people are not systems thinkers, meaning they
0:27:16 cannot think about, OK, if I change this here, then it’s going to affect that over there.
0:27:21 And you know, you know, as an economist, people always make these dumb mistakes like, OK,
0:27:23 well, move the minimum wage and nothing else will happen.
0:27:25 It’s like, well, no, no, it’s a system.
0:27:26 You have to think of it in terms of the system.
0:27:30 And so that’s kind of part of it and a big part of it.
0:27:37 But the other part, which is, can you actually see the people in your organization?
0:27:42 Like, do you know who they are as opposed to you’re talking to them like they’re you?
0:27:46 And meaning, do you understand their motivation?
0:27:49 Do you understand what they would think about something if they were in the room and you’re
0:27:52 making a decision?
0:27:57 Can you interpret them well enough so that it’s as though they’re there?
0:28:01 And can you understand the implications through the eyes of the people who work for you?
0:28:05 And if you have those two things together, those are the people who are really great,
0:28:06 but it’s a rare thing.
0:28:09 And you can kind of see it because you’ll be talking to them and like you might not
0:28:12 be able to articulate something and they can articulate it for you the way you would have
0:28:14 done it better.
0:28:19 Like somebody who’s that perceptive on people plus a systems thinker is really the those
0:28:21 of the people who are gifted.
0:28:24 And Mark, did you really invent the TweetStorm?
0:28:26 And if so, what’s the general lesson about innovation?
0:28:27 We should learn from that.
0:28:31 What is a general lesson?
0:28:36 Inability to shut up, I think might have had a lot to do with it.
0:28:37 But you did invent it.
0:28:39 I think there might have been sequences of tweets, but literally I couldn’t shut up.
0:28:41 So like, I think it kind of catalyzed.
0:28:44 Well, look, I mean, the big lesson from it has been that the big lesson actually have
0:28:47 a lot of the Internet platforms, which is emergent behavior is incredibly important, right?
0:28:52 The really successful platforms let the user surface the behaviors, right, that the creators
0:28:54 of the platform could have never thought of and, you know, Twitter set all kinds of issues
0:28:57 over the years, but like it always has been amazing.
0:28:59 Most of the compelling ways in which people use Twitter have been invented by the users.
0:29:03 I mean, I think it’s true, retweets were invented by users, right, like very, very fundamental
0:29:04 features.
0:29:05 And that’s not just Twitter.
0:29:06 That’s also been true.
0:29:07 It was true of actually personal computers.
0:29:08 It was true of smartphones.
0:29:10 It’s been true of, you know, many of these platforms.
0:29:15 And so it’s a useful principle of product design, which is let the users innovate.
0:29:20 Ben, you’re famous actually for your barbecue cooking, viewed as a problem of management
0:29:22 and also innovation.
0:29:26 What makes for the difference between good and truly excellent barbecue?
0:29:27 Time.
0:29:28 Say more.
0:29:29 Time.
0:29:30 So, you know, it’s funny.
0:29:36 I had an interesting conversation years ago with my wife’s cousin, Atlee, in Kanye West,
0:29:41 which was just like a weird thing because Atlee’s from Baton Rouge, Louisiana.
0:29:45 And I have him to be in New Orleans and Kanye was there and we’re all out to dinner.
0:29:50 And Kanye asked Atlee, he says, “What’s the definition of luxury?”
0:29:53 Which is like, if you’re from Baton Rouge, you just don’t think of that word, like you
0:29:55 never hear the word luxury.
0:29:59 And so Atlee says, “I just like to cook.”
0:30:00 And Kanye says, “Well, how do you cook?”
0:30:03 He says, “Well, like I like to make red beans and rice.”
0:30:04 And he’s like, “Well, how do you do that?”
0:30:08 He’s like, “Well, I take my time, you know, I cut the onions very slowly, I boil it for
0:30:10 a long time, I make sure it simmers.”
0:30:15 And Kanye says, “Exactly, time is luxury.”
0:30:17 Like that’s why I make luxury records.
0:30:18 I take my time.
0:30:21 And I was like, yeah, that’s it.
0:30:22 So.
0:30:28 Mark, do you prefer to eat for-profit sushi or nonprofit sushi?
0:30:33 This is Tyler’s favorite question to suss out whether people are actually pro-government,
0:30:34 pro-increased government services.
0:30:40 The idea of nonprofit sushi makes me so nauseous that I think I want to throw up on stage.
0:30:47 General question, what’s the one thing that Wall Street does not understand about technology
0:30:49 that you would change if you could?
0:30:51 I think part of it is it’s a 3,000-mile-like thing.
0:30:55 I think a big part of its culture, there’s just a delay, and there always has been.
0:30:58 And so, you know, if I wanted to fix that, I would say, like, we need to spend a lot
0:30:59 more time.
0:31:02 And by the way, the tech industry does need to spend a lot more time trying to tell people
0:31:05 what we’re doing, but at the same time, people from outside the tech industry need to spend
0:31:08 more time in the valley and understand what’s happening here.
0:31:10 And a lot of that is happening as well.
0:31:13 That’s how I’m not sure I want to fix it.
0:31:15 The question assumes I want to fix it, like, I don’t think I want to fix it, because that’s
0:31:17 a big part of the opportunity.
0:31:21 What’s the one thing the U.S. government does not understand about tech that you would change
0:31:22 if you could?
0:31:25 So I think the first thing is something that Andy Grove said many years ago, which is it’s
0:31:27 inevitable.
0:31:31 And so, you know, somebody had asked him, you know, is the microprocessor good or bad?
0:31:34 He said, well, that’s like asking a steal, a good or bad, he’s like, we’ve got to deal
0:31:36 with it, like, it’s here.
0:31:41 And I think that, you know, the biggest mistakes the government makes are assuming it’s not.
0:31:46 So, you know, stem cells is a great one where the U.S. government went to really hold that
0:31:47 back.
0:31:49 They end hold back stem cell development or research at all.
0:31:53 They just made it very inconvenient for people in the United States, and a lot of people died
0:31:57 and, you know, missed out on cures and all kinds of things because of that.
0:32:00 And so I think that’s number one.
0:32:05 And then I think the other thing is that technology is always had and always will have good and
0:32:06 bad implications.
0:32:12 Going back to the cotton gin, the printing press, you know, certainly the internet has
0:32:13 had good and bad.
0:32:18 But if you look at it overall, it’s overwhelmingly positive.
0:32:26 And more than that, we have to go back to our population levels in like 1750 if you’re
0:32:30 going to take away technology and take away technological advancement because the way
0:32:35 the human population is growing, there’s no way we can, you know, live the way we want
0:32:37 to live and have the lives we want to live without technology.
0:32:42 So getting into these debates of whether we should hold it back is just, you know, if
0:32:45 there’s one thing I would change, it’s like, let’s not have that debate.
0:32:47 Let’s have the debate how to make it great.
0:32:52 Mark, what’s the last thing software will eat?
0:32:53 Other than sushi.
0:32:55 Other than sushi.
0:32:59 So I think it’s fundamentally, the term that you used actually called it, I think, project
0:33:00 selection.
0:33:05 And so basically it’s this question of like, okay, how do you organize a small number of
0:33:07 people to do something new, right?
0:33:09 And by the way, that could be a startup company.
0:33:11 That could be many other kinds of efforts where you need a small number of people to
0:33:12 do something new.
0:33:14 It could be a new political campaign, a new activist movement, whatever, but a small number
0:33:16 of people to do something new, right?
0:33:19 And then how do you pick, if you’re going to finance or donate or fund those things,
0:33:23 how do you pick ones to donate to, and then how are those things actually going to run,
0:33:24 right?
0:33:27 So the new part there is really important, like the little known fact, for example, about
0:33:31 venture capital is that there’s a term in venture capital and hedge funds called Cary,
0:33:34 which is basically called Cary’s interest, which is the sort of profit participation
0:33:36 that the VCs or hedge fund managers make.
0:33:42 The term Cary actually comes from whaling in the 1600s off like, you know, in the Atlantic
0:33:46 Ocean, like literally their term Cary was the people who would finance the captain and
0:33:49 the crew of the boat, but the boat actually would run as a startup.
0:33:52 There was actually like equity participation for all the people in the boat, and then they
0:33:56 would pick a captain, you’d raise money in town, you’d raise capital, and then the boat
0:33:59 would go off and try to take down a whale, right?
0:34:03 And about, you know, three quarters of the time the boat would come back, the other quarter
0:34:04 of the time.
0:34:05 The whale would win.
0:34:06 The whale would win.
0:34:08 Moby Dick was not a joke.
0:34:12 And so the boat comes back about 75% of the time, and then literally Cary was the portion
0:34:15 of the whale that the investors got, right?
0:34:18 And so if you think about it, like the process, if you’re like in, you know, I don’t know,
0:34:22 whatever, Boston or wherever, in like, you know, 1675, and you’re trying to say, okay,
0:34:28 this ship, this captain, this crew, this mission, into these waters, right, with these weather
0:34:31 patterns, like, and how are they going to behave under pressure, and what’s going to
0:34:33 happen when things go wrong, and it’s a crew going to mute me, and like, are we going to
0:34:34 make any money doing this?
0:34:39 Like, the whole thing is just such an intricate kind of puzzle, and it revolves around people.
0:34:45 And so, if you’re sitting out at the whaling expedition, you know, the Santa Maria is the
0:34:46 same kind of thing.
0:34:47 Tech startups are the same way.
0:34:50 By the way, you know, green lighting a movie or a TV show in Hollywood is the exact same
0:34:51 kind of process.
0:34:55 And it’s just, it’s so intangible, and it’s so much based on the interaction of a small
0:34:57 number of people who are going to be under extreme pressure.
0:35:01 Like, if we could figure out a way to automate that, like, we’d fund that company and then
0:35:03 retire, but at least we don’t know how to do that.
0:35:07 For each of you, what’s an interesting book you’ve read lately?
0:35:11 So one of the most interesting books I’ve read lately is a Genghis Khan and the Making
0:35:17 of the Modern World by Jack Weatherford, and it turns out to be very unexpectedly the most
0:35:22 interesting book on the topic of how you think about inclusion that I’ve ever read, and Genghis
0:35:27 Khan is not known for his thoughts on inclusion because he’s mostly known for, like, being
0:35:29 just ruthless.
0:35:35 But he really, you know, he was a guy who came from kind of the border of northern Mongolia
0:35:39 and Siberia, a very bad part of the world, he had a very, very hard life growing up.
0:35:45 He was from kind of the lower, they had white bones and black bone, kind of the higher and
0:35:50 lower caste, he was a lower caste person, and, you know, a lot of his experience growing
0:35:56 up led him to this idea that he should choose for kind of talent, not the caste system,
0:36:00 and not even the tribe that he was in, which was a huge breakthrough at the time, you know,
0:36:04 nobody had done that, and the way he thought about it and the techniques that he used for
0:36:11 doing it were breakthroughs today, you know, and so I just found it to be like a super
0:36:15 interesting book, definitely a great management book for anybody who’s interested in that
0:36:16 topic.
0:36:17 Mark.
0:36:20 So, the best book, the book’s had the biggest impact on me, it’s an incredibly well-written
0:36:24 book, it’s, of course, out of print, it’s by actually a guy, I think, Tyler, you know,
0:36:25 Timur Karan.
0:36:26 Sure.
0:36:29 You know quite well, who’s a economics and…
0:36:30 Economist at Duke.
0:36:31 At Duke.
0:36:36 So it’s a book about, 20 years ago, it’s called Private Truth’s Public Lives, and it basically
0:36:38 tells the story, the theory that he basically has, he calls preference falsification, and
0:36:43 it’s basically the idea, it’s a situation in which people believe something in their
0:36:46 own head, and then they feel for social reasons that they can’t say it out loud.
0:36:50 And so it starts kind of with that as kind of an idea, and then it kind of extrapolates
0:36:54 out kind of what happens as a society becomes the kind of society in which people feel like
0:36:58 they can’t speak the things that they believe, and it turns out to be quite an elaborate
0:37:01 process because basically, right, you can have these very interesting situations where
0:37:04 you can have a majority of people who believe something, but then they all believe they
0:37:08 can’t say it, but then as a consequence, they all come to believe that there are many fewer
0:37:12 people who believe it than there actually are, and so you can kind of suppress a point
0:37:16 of view artificially for quite a long time, but then he describes in the book how you
0:37:19 can then kind of just get the reverse process, kind of get the whole thing, kind of the spring
0:37:24 to expand, which is if a few brave people start to speak up, then a lot of other people who
0:37:27 have had that secret belief all of a sudden realize they’re not alone, and then you start
0:37:30 a cascade, right, in which a lot of people start to speak up, and he basically models
0:37:34 in the book like that’s where revolutions come from, and it’s basically like an explanation
0:37:39 for the fall of the Berlin Wall, it’s an explanation for political revolution.
0:37:42 It so happens to be, I think, highly relevant to what’s happening both on the left and the
0:37:44 right in the U.S., like right now.
0:37:47 Like, I think it’s, as you read the book, you’re just like, okay, that’s the cleanest
0:37:51 explanation of the Trump phenomenon I’ve ever seen, and furthermore, it’s also the cleanest
0:37:53 explanation of the Bernie phenomenon I’ve ever seen, like I think it actually describes
0:37:54 both quite accurately.
0:37:58 For the last question, I’d like to return to Mark and Ben as a couple.
0:38:03 Ben, what’s Mark’s biggest misconception about you, and Mark, what’s Ben’s biggest
0:38:05 misconception about you?
0:38:11 So this is the sad thing, is that he knows me so well that I wish he had misperceptions
0:38:18 about me, but like, he actually knows who I am, and so this is, and it manifests itself
0:38:22 the worst, like if something’s going wrong at the firm, it’s always some combination
0:38:27 of his and my fault, and he’ll know exactly the flaws that I have that have led us to
0:38:34 that situation, and like, it’s unbearable, and vice versa, but I’ll let him answer.
0:38:36 And Mark, you have the last word.
0:38:39 Ben’s biggest misconception to me is he thinks I’m gonna go to my room tonight and listen
0:38:43 to Will Smith.
0:38:45 I thank you both very much for this dialogue.
0:38:46 Thanks everybody.
0:38:50 (audience applauding)
0:39:00 [BLANK_AUDIO]
with Marc Andreessen (@pmarca), Ben Horowitz (@bhorowitz), and Tyler Cowen (@tylercowen)
Continuing our 10-year anniversary series since the founding of Andreessen Horowitz (aka ”a16z”), we’re resurfacing some of our previous episodes featuring Andreessen Horowitz founders Marc Andreessen and Ben Horowitz.
This episode was actually recorded in 2018 at our annual innovation Summit, and features economist Tyler Cowen interviewing Ben and Marc about everything from their partnership and how it works to talent, tech trends, and software eating culture.
You can find other episodes in this series at a16z.com/10.