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0:00:06 Like anyone who’s out to get ahead,
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0:00:52 – Welcome to the Prop 2 Pod’s office hours.
0:00:55 Today, we’re kicking off a special three-part series,
0:00:57 Lunodos Therese series.
0:00:58 That’s right.
0:01:00 Featuring some of our favorite office hours moments,
0:01:02 best of business, best of career,
0:01:04 and best of parenting.
0:01:06 Not good business or good career or good parenting,
0:01:07 but the best of.
0:01:10 In today’s episode, we start with best of business,
0:01:13 where we’ll answer your questions surrounding the brand era,
0:01:15 big tech companies, and their ethical responsibility,
0:01:17 and when a founder CEO should step down.
0:01:20 So with that, first question.
0:01:21 – Hi, Scott.
0:01:23 Matt here and a big fan of your podcast.
0:01:25 I followed you for a while and one of your enduring takes
0:01:27 has been that advertising and building brand
0:01:30 through paid media is a dying business strategy.
0:01:32 Outside of some companies seeing hyper growth
0:01:34 without big media budgets, mainly in the tech sector,
0:01:36 most major firms continue to increase budgets,
0:01:38 and those tech companies are now some of the biggest
0:01:39 advertisers in the world.
0:01:42 Even Tesla, famously a versed advertising,
0:01:44 is now paying for media to try to differentiate
0:01:46 versus the growing EV market.
0:01:48 As someone who also falls as closely,
0:01:51 there’s been a golden age of advertising effectiveness
0:01:53 research from professors like Byron Sharpe,
0:01:54 showing the value of paid media.
0:01:57 I’d be curious how much of your successful
0:02:00 prof media business, profging media business,
0:02:02 is supported by advertising.
0:02:05 I work in the space, so I’m obviously biased,
0:02:08 but curious if you’ve amended any of your opinions here.
0:02:10 Thank you for all you do, and go Connors.
0:02:12 – Go Connors, I love that.
0:02:14 Look, I make these provocative statements
0:02:17 that if you’re advertising, it means your product sucks.
0:02:20 And I’ve also said, and this is, I think, more true,
0:02:23 if you constantly are having dinner with strangers,
0:02:25 it means you’re selling an undifferentiated product.
0:02:26 So if you’re in the services business,
0:02:29 and your job is to have these full relationships with people,
0:02:31 it means you’re all selling the same damn widget,
0:02:33 and you’re dependent upon relationships.
0:02:34 One of the things I loved about,
0:02:36 I started a brand strategy firm.
0:02:38 And basically, we were good at what we did,
0:02:40 but there were a lot of good firms out there
0:02:42 in a brand doing brand strategy.
0:02:44 And the way we got business is I would develop
0:02:46 sort of these proxy father son relationships
0:02:47 with the CMO or the CEO.
0:02:49 And I found it just fucking exhausting.
0:02:52 They were really interesting, wonderful men,
0:02:53 and they were all men.
0:02:55 This was in the 90s, but I’m an introvert,
0:02:58 and I just found a different, I vacationed with clients.
0:03:01 I mean, it was just so much, but anyways,
0:03:05 I do think advertising is sort of a tell for a company
0:03:07 that doesn’t have a truly differentiated product.
0:03:10 And I would push back that the tech companies,
0:03:11 yeah, they advertise a lot,
0:03:14 but as a percentage of their top line budget, they don’t.
0:03:18 And Netflix uses, I met with Ted Serrano,
0:03:19 the CEO of Netflix, and I said,
0:03:21 “Why wouldn’t you start a TikTok competitor?”
0:03:22 I still, by the way, I think they should partner
0:03:26 with an AI firm and buy a hopefully divested TikTok.
0:03:29 But he said, “No, we use TikTok as free advertising.
0:03:31 It’s amazing, we give them a certain number of clips,
0:03:33 and it’s fantastic marketing for us.”
0:03:34 And they don’t spend a lot of money,
0:03:35 I don’t think on marketing.
0:03:38 And I think the companies that,
0:03:40 the companies that have added the most shareholder value
0:03:43 over the last 10, 20 years have a few things in common.
0:03:45 When they’re typically asset light,
0:03:48 why build a factory when you can just design the chip
0:03:50 and video, why invest in expensive real estate
0:03:52 when you can just create a platform and take fees,
0:03:54 Airbnb, why buy and maintain cars
0:03:56 when you can just create software,
0:03:59 a thick layer of software on top of them, that’s Uber.
0:04:01 They tend to have recurring revenue streams
0:04:06 that are more predictable, like a software company,
0:04:09 but also I have found they tend to be less reliant
0:04:11 on advertising.
0:04:12 And the thing about advertising,
0:04:14 one of the reasons Google killed,
0:04:16 largely killed the traditional ad business,
0:04:17 and I think it has.
0:04:21 Google loses or gains the value of IPG, WPP,
0:04:25 Puberty, and Omnicon every day.
0:04:27 Those guys used to be the big swing index,
0:04:30 and now they basically work and they beg for the crumbs
0:04:33 off of the Google and Meta cookie, if you will,
0:04:36 is that those companies have difficult times
0:04:37 finding attribution or building it.
0:04:41 Basically, all the research that Condonast or IPG does,
0:04:42 all leads to one place.
0:04:45 You should spend more money on our advertising, right?
0:04:47 And it’s kind of bullshit,
0:04:49 and it’s kind of a model where the lack of attribution
0:04:51 was both the sin and the opportunity
0:04:53 in the sense that brand building is difficult
0:04:55 to reverse engineer to specific sales.
0:04:57 So there’s been a dearth of it,
0:04:59 which probably means it’s gonna offer higher ROI,
0:05:01 and direct response advertising,
0:05:04 specifically Meta and Alphabet,
0:05:06 with their unbelievable targeting.
0:05:10 I mean, boy, you only have 70% of your budget
0:05:12 in digital marketing, it should probably be more.
0:05:14 I mean, every year, these companies just take more
0:05:16 and more share of an industry.
0:05:17 Advertising is a weird industry.
0:05:19 It’s always like one and a half percent of GDP.
0:05:22 It doesn’t go below that, it doesn’t go above it.
0:05:24 So this is not a growth industry,
0:05:26 but you have some companies that are going 20
0:05:30 and 25% a year, everyone from Meta and Alphabet to TikTok,
0:05:32 which means they are sucking the oxygen out of the room
0:05:33 for the other folks.
0:05:35 Does that mean traditional based advertising
0:05:36 and brand building is gonna go away?
0:05:39 No, but it’s gonna be a shitty place to work or invest.
0:05:41 If you’re absolutely in love with it,
0:05:44 or you’re scaling and have senior level sponsorship
0:05:47 or you’re rounding third, then by all means, stay there.
0:05:49 But if you’re younger, don’t love it,
0:05:53 I just think it’s gonna get more and more difficult
0:05:57 for the traditional advertisers/brand building complex.
0:05:58 And this is from someone
0:06:00 who made a really good living preaching about brand.
0:06:02 I think things have genuinely changed.
0:06:04 I think we’ve moved from a brand era,
0:06:05 and I don’t wanna call it an innovation era,
0:06:06 to a supply chain era.
0:06:09 Most of the big, big advances in shareholder value,
0:06:12 in addition to being asset-like, recurring revenue,
0:06:14 lack of advertising and been supply chain.
0:06:16 So, you know, my brother, I just,
0:06:18 and I’m a professor of brand strategy.
0:06:23 I think the era of brand, the sun has passed midday,
0:06:27 and Don Trapper has been drawn and quartered.
0:06:28 Thanks for the question.
0:06:30 Question number two.
0:06:33 – Hey, Scott, this is Sean from Seattle.
0:06:34 Love the podcast.
0:06:36 Thank you so much for taking my question.
0:06:39 I recently fielded offers from Amazon and Meta,
0:06:40 and got into a debate with friends
0:06:43 around which was less ethically problematic.
0:06:45 Given the contentious business practices
0:06:48 and societal implications associated with both companies,
0:06:50 do you truly believe there is a distinction
0:06:52 in choosing one over the other for ethical reasons?
0:06:54 Can someone really sleep better at night
0:06:57 choosing to work at one big tech company over another?
0:06:59 We’d love to hear your insight.
0:07:01 – Sean, this is the mother of all good problems.
0:07:03 And so let me be clear.
0:07:07 Both firms from an employee perspective are great firms.
0:07:10 I would say probably a third of my kids,
0:07:14 and when I say my kids, my students would go to work
0:07:17 for big tech, and at 1.20%, we’re going to Amazon.
0:07:19 And the people I know that went to Amazon
0:07:23 described it as intense, unforgiving, and very rewarding.
0:07:25 Meta has a fantastic reputation
0:07:26 in terms of how they treat their employees.
0:07:28 They pay them really well.
0:07:32 A lot of investments in human capital around the ethics.
0:07:36 I think your first priority is to develop
0:07:39 economic security for you and your family.
0:07:41 And I think big tech is good for the world.
0:07:43 I think if we had a button we could press
0:07:47 and make big tech vanish, we would not push that button.
0:07:49 That we are net gainers from big tech.
0:07:51 The problem is with the word net,
0:07:52 and that is we’re net gainers from pesticides,
0:07:55 we’re net gainers from fossil fuels, I still believe,
0:07:58 but we choose to have emission standards in an EPA.
0:08:00 I would argue at this point,
0:08:03 at this point, meta is probably a net negative.
0:08:06 Whether it’s teen suicide, self-harm,
0:08:10 self-cutting among girls, election misinformation.
0:08:13 I mean, these guys really are a mendacious fox.
0:08:15 And Amazon might be a mendacious fox,
0:08:18 but the implications of that are monopoly abuse
0:08:19 and small retailers go out of business,
0:08:21 and bigger retailers or great employers
0:08:23 might have gone out of business faster
0:08:24 than they otherwise would have.
0:08:29 But they’re not spreading conspiracy theory.
0:08:31 They’re not spreading anti-vax information.
0:08:33 And some of it might not be that they’re,
0:08:36 the people are any less or more ethical.
0:08:38 It’s that they’re just in different businesses.
0:08:40 So if you really got to the point
0:08:44 where it came down to who was less bad or more ethical,
0:08:46 I would say you’d probably choose Amazon
0:08:49 just by virtue of the fact that they’re in the business
0:08:53 of e-commerce and cloud versus media.
0:08:55 Having said that, I think most likely
0:08:57 you should probably make the decision
0:08:59 based on what’s best for you personally.
0:09:01 Do you wanna live in Seattle?
0:09:03 Do you wanna live in the Bay Area?
0:09:05 Where do you think you’ll have senior level sponsorship?
0:09:09 Where do you have a better rapport or relationship?
0:09:11 Do you believe currently or the children develop
0:09:13 with who you’ll be reporting into?
0:09:16 What does the career path look like at each organization?
0:09:18 I find with decisions like this,
0:09:20 you don’t wanna listen to a podcast or that is yours truly.
0:09:23 You wanna build a kitchen cabinet of people
0:09:26 and say, okay, these are the offers.
0:09:27 This is the opportunity.
0:09:31 This is the division, what do you think?
0:09:32 And then at the end of the day,
0:09:35 you’ll probably ignore all those decisions
0:09:38 and just go with your gut and make your original decision.
0:09:40 So these are personal decisions.
0:09:42 I would say the quote unquote ethical stuff, if you will,
0:09:45 is a tiebreaker unless it’s something
0:09:46 that really weighs on you.
0:09:49 Corporate America, these are platforms for making profits
0:09:52 and folks in the media and people such as myself,
0:09:55 I think play a role in holding them accountable
0:09:58 and trying to urge our elected officials
0:10:00 to put in place the regulations
0:10:03 such that there’s guardrails around these companies.
0:10:04 But at the end of the day,
0:10:06 they are going to do whatever increases their profits,
0:10:08 full stop, that’s just what they do.
0:10:11 But anyways, like I said, let me end where I began.
0:10:12 This is a great problem.
0:10:17 Congratulations to you, offers from Amazon and Metta.
0:10:21 Jesus, Jesus man, good luck to you, that’s fantastic.
0:10:24 We have one quick break before our final questions.
0:10:25 Stay with us.
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0:10:50 Diverse of high, IRA, 401K, liquidity.
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0:10:53 But if he’s such an expert,
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0:11:47 When I told my parents I was declaring a major in philosophy,
0:11:50 my dad was a little worried about my financial prospects.
0:11:53 See, he’s got an MBA and he loves to corner us
0:11:56 at the dinner table with all kinds of business talk.
0:12:01 Diverse of high, IRA, 401K, liquidity.
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0:12:16 Anyone can be an expert,
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0:12:19 Wait, how much?
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0:12:27 Get unlimited premium wireless for $15 a month
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0:12:52 (air horn)
0:12:55 – Welcome back, question number three.
0:12:56 – Hi, Scott.
0:12:59 My name is Melissa in Chapel Hill, North Carolina.
0:13:02 I’m a four time CMO in B2B SAS
0:13:05 with 30 years of experience and many startups.
0:13:08 I saw your recent post about the probability
0:13:12 a startup will be successful by the number of attempts.
0:13:15 I’ve been part of startups that have been very successful
0:13:18 and some that have been total flops.
0:13:21 One thing I’ve noticed that is critical to success
0:13:24 is the founder CEO.
0:13:28 Many founder CEOs are not always strong business operators.
0:13:31 They can be great ideators and innovators,
0:13:34 but many don’t seem self aware of their shortcomings
0:13:36 as operators.
0:13:38 What are your thoughts about when a founder CEO
0:13:42 needs to step aside to bring in an experienced team
0:13:44 of business operators to drive the company’s
0:13:46 next level of growth?
0:13:48 Thank you for considering my question.
0:13:50 Love you and love the show.
0:13:53 – Well, Melissa from North Carolina, I love you.
0:13:55 That’s some really nice thing to say.
0:13:58 This is a tough one because you’re exactly right.
0:14:00 Entrepreneurs have role models as they should
0:14:03 and they look at Steve Jobs and Bill Gates
0:14:04 who are unicorns.
0:14:06 They’re a rare species and that is,
0:14:09 if you think of a company as an idea, is letter A.
0:14:12 And then the startup, getting the initial seed funding,
0:14:14 hiring and firing a group of people,
0:14:17 like hand to hand combat for the first 20, 30 people.
0:14:19 And that’s what you have to do with the first 20 or 30 people
0:14:22 and working around the clock and sharing a vision
0:14:24 and being just sort of irrationally passionate
0:14:26 and a little bit crazy, if you will.
0:14:27 That’s kind of A to D or E.
0:14:31 And then the company leans in or discovers something
0:14:33 that is differentiated and is a real product
0:14:36 that’s generating more gross income
0:14:39 or has positive gross margins.
0:14:40 You don’t need to be profitable,
0:14:42 but when you sell a widget for a buck,
0:14:44 it should be at least on a marginal basis
0:14:47 and that is the cost to deliver that incremental
0:14:51 consulting engagement or that incremental piece of software
0:14:52 or that incremental whatever it is,
0:14:55 widget that you have positive gross margin.
0:14:56 You say, okay, if I hire enough people here,
0:14:59 I can start to scale and I can build an enterprise
0:15:01 and maintain some culture and show
0:15:03 that this is more than just a practice.
0:15:07 So the ones that succeed oftentimes never get to scale
0:15:08 and that is their practice.
0:15:11 Typically, a small group of people in the services industry
0:15:13 are great at PR or great investment banking
0:15:16 or great at a specific product or service.
0:15:18 And the people who started the company are selfish
0:15:20 and think that they’re the real innovators
0:15:22 and they don’t want to share in the upside
0:15:24 of people to scale the company.
0:15:26 And so whenever I meet with people
0:15:28 that have a great company, 20, 30, 50 people
0:15:29 and they’re wondering why they can’t scale my kids,
0:15:32 usually because you are too fucking selfish
0:15:34 and don’t realize that people want to have a nice life
0:15:36 like you and you need to give away large chunks.
0:15:38 So the company, if you want people to act like owners,
0:15:40 which is the key early in a company,
0:15:42 you have to make them owners.
0:15:43 Anyways, back to your question.
0:15:46 Most CEOs think they’re Steve Jobs or Bill Gates
0:15:48 and they can go A to Z.
0:15:51 And key part of self-actualization and also success
0:15:55 is recognizing, as I did fairly early, quite frankly,
0:15:58 as a CEO, that about the time we get a CFO,
0:16:00 about the time we have someone in HR,
0:16:02 it is time for me to step down as CEO
0:16:04 and become kind of the thought leader,
0:16:08 the person that is responsible for driving new business.
0:16:11 I really enjoy that, play a big role in strategy,
0:16:14 but somebody needs to be Mr. or Mrs. inside
0:16:16 and basically run the company.
0:16:19 And I was always a fan of giving them the CEO title.
0:16:20 Why as a founder?
0:16:22 My objective was always to build shareholder value
0:16:24 and get economic security for me and my family,
0:16:26 which is Latin, forget rich.
0:16:27 And titles are inexpensive.
0:16:30 So I was always up for giving away the CEO title.
0:16:32 I’ve never been the CEO of a company when I’ve left.
0:16:35 Typically within three to five years,
0:16:37 I find someone that is outstanding,
0:16:40 that I want to retain and I give them five, seven, 10,
0:16:43 15% of the company and say congratulations,
0:16:44 you’re now the CEO.
0:16:46 And this is kind of what I’m responsible for
0:16:48 and this is what you’re responsible for.
0:16:52 A lot of founders never come to that conclusion.
0:16:53 Now the question is,
0:16:55 how do you nudge them to that realization?
0:16:57 That’s a tough one, a board.
0:17:01 I don’t know how you tell someone
0:17:02 to be more self-actualized
0:17:03 and that they have limits on their capabilities
0:17:06 and we’d all be better off if you brought in someone
0:17:08 to run this organization that isn’t you.
0:17:09 It’s a difficult one.
0:17:13 Typically that’s the kind of conversation
0:17:15 a board should have with the founder CEO
0:17:18 that used to be very common in the 90s.
0:17:21 Essentially we thought there are absolutely no founders
0:17:22 that are good enough to be CEOs.
0:17:24 So what happened was a guy like Steve Jobs
0:17:25 was immediately assumed to be crazy
0:17:28 and we need to bring in the gray hair old guy from Pepsi,
0:17:30 John Scully and let him or her run it.
0:17:32 Things have changed so dramatically.
0:17:35 The pendulum has swung so far to the other side
0:17:37 because of the return of Steve Jobs
0:17:40 and people like Mark Benioff and Bill Gates
0:17:41 that are able to build a company
0:17:43 from A to Z and be outstanding CEOs.
0:17:47 You should assume if you’re the CEO, you are not Bill Gates.
0:17:49 You should assume you are not Steve Jobs.
0:17:51 I apologize, I don’t have a direct answer
0:17:54 for how to convince possibly your CEO to step down
0:17:56 but the fact you’re thinking that way
0:17:58 means you’re gonna be or you’re probably successful
0:18:02 and can kind of gauge whether or not this company
0:18:04 has the right stuff to get to the next level.
0:18:08 Against CEOs out there, you know, search your feelings.
0:18:11 Are you really the person to get to the letter M?
0:18:14 Cash in, cash in, recognize how awesome you are
0:18:16 and if you have the ability to bring in somebody
0:18:17 who will be outstanding and compliment your skills
0:18:19 by all means, hit that bit.
0:18:20 Thanks for the question.
0:18:23 That’s all for this episode.
0:18:25 If you’d like to submit a question,
0:18:26 please email a voice recording
0:18:28 to officehours@proptingmedia.com again.
0:18:31 That’s officehours@proptingmedia.com.
0:18:34 (waves crashing)
0:18:44 Support for this special series comes from Mint Mobile.
0:18:46 Thanks to Scott for inviting us.
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0:19:38 you

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0:00:24 to make customers happier.
0:00:27 All built into a single platform you can use right now.
0:00:29 That’s why the world works with ServiceNow.
0:00:33 Visit servicenow.com/aiforpeople to learn more.
0:00:38 – We interrupt your podcast to bring you breaking news.
0:00:40 Tim’s classic breakfast sandwiches are just $3
0:00:42 when you buy any size coffee.
0:00:43 You heard that right, $3.
0:00:45 Your mornings will never be the same,
0:00:47 plus tax Canada only, limited time only,
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0:00:53 ♪ It’s time for Tim’s ♪
0:00:57 – I’m Scott Galloway and this is No Mercy, No Malice.
0:01:01 – The Olympics used to be a slab of television content.
0:01:05 The internet is grounded into social media moments.
0:01:08 – Smaller, as read by George Hahn.
0:01:13 Things change.
0:01:15 When I was a kid, the summer Olympics
0:01:17 were an iconic quadrennial opportunity
0:01:20 to rewatch the moon landing.
0:01:22 Another chance to beat the Russians,
0:01:25 this time in the medal count.
0:01:28 But despite still commanding huge audiences,
0:01:31 the five rings feel like a shadow of their former selves.
0:01:36 The Olympics have lost much of what made them
0:01:38 the Paramounts sporting event.
0:01:41 The key to an aspirational luxury brand
0:01:44 is the illusion of scarcity.
0:01:48 And the Olympics feel less scarce.
0:01:50 You no longer have to wait four years
0:01:52 now that the summer and winter games
0:01:55 alternate every two years.
0:01:58 In 21 months, Comcast will begin marketing
0:02:03 the winter games in Cortina D’Ampezzo, awesome name.
0:02:08 A brand based on scarcity has effectively doubled its supply.
0:02:12 Also, while likely unavoidable,
0:02:15 the presence of professionals in almost every sport
0:02:18 has diluted the brand and the authenticity
0:02:20 amateur athletes brought.
0:02:23 The youth-focused events added in recent years,
0:02:26 including skateboarding and BMX freestyle,
0:02:28 cool as they are, don’t have the mystique
0:02:33 of classic Olympic sports such as track and field.
0:02:36 It feels as if the Olympics, like the rest of us,
0:02:39 are desperately trying to look younger.
0:02:41 To be fair, the games have a history of adding
0:02:44 and dropping new and or weird sports
0:02:48 going back to the first modern event in 1896.
0:02:50 Firefighting, ballooning, and lifesaving
0:02:53 were events in the early days.
0:02:57 Finally, the good guys versus bad guys rush,
0:02:59 inspired by the Cold War, has faded,
0:03:02 and not just for us Americans.
0:03:04 Athletes and fans are still proud
0:03:06 to represent their countries, of course,
0:03:10 but the nationalism seems less ferocious.
0:03:14 The whole thing feels smaller.
0:03:16 Just before the start of the games,
0:03:18 the International Olympic Committee
0:03:20 said it was on track to hit its target
0:03:25 of $1.2 billion in corporate sponsorships.
0:03:29 The IOC says about 30% of its revenue
0:03:30 comes from sponsorships.
0:03:33 The rest comes from TV rights and licensing.
0:03:38 LVMH paid about $163 million
0:03:42 to be what the company calls a creative partner.
0:03:46 Watching the opening ceremony, two things struck me.
0:03:49 First, Paris isn’t a city.
0:03:54 It’s the premier backdrop for any person, place, event,
0:03:56 trying to create a sense of elegance,
0:03:59 sophistication, and exclusivity.
0:04:03 The Olympics is the gangster travel ad for the host city,
0:04:08 and no tourist destination is an easier sell than Paris.
0:04:13 The second thing, I’m a Celine Dion fan.
0:04:15 I’d always dismissed her out of hand,
0:04:19 but she gave what may be the performance of 2024.
0:04:30 I just read that last sentence and realized
0:04:33 I have officially become a senior citizen.
0:04:37 Anyway, it was impossible to see her performing solo
0:04:40 under the Eiffel Tower, despite the neurological problems
0:04:42 that have derailed her career
0:04:45 without thinking of another Olympics moment.
0:04:47 A Parkinson’s-wracked Muhammad Ali
0:04:51 lighting the cauldron at the 1996 Atlanta Games.
0:04:56 The Olympics are, and always have been,
0:05:00 about big emotional moments.
0:05:03 What’s changing is how we watch them.
0:05:06 The TV audience has been shrinking for years.
0:05:08 The opening ceremony this year
0:05:13 brought a U.S. audience of 28.6 million viewers to NBC
0:05:16 and its Peacock streaming service.
0:05:20 That was significantly more than the 17.9 million
0:05:24 who watched the COVID-hobbled 2020 Tokyo opening ceremony,
0:05:29 but a steep drop from the peak 40.7 million
0:05:32 who watched the London opening in 2012.
0:05:38 NBC paid $7.65 billion in 2014 for broadcast rights
0:05:44 through 2032, and looking at the TV viewership numbers,
0:05:47 the IOC is on the better end of the deal.
0:05:52 NBC, however, claims it booked $1.2 billion
0:05:54 in Olympic ad revenue before the Games
0:05:59 and says it believes Paris will set a new ad revenue record.
0:06:03 A big engine of that ad revenue is streaming
0:06:06 and other online distribution.
0:06:08 While the overall viewership numbers are down,
0:06:11 the digital share of Olympic viewership is up.
0:06:15 NBC is using the games to jumpstart Peacock
0:06:17 and also ran in the streaming wars,
0:06:22 33 million subscribers versus Netflix’s 277 million.
0:06:25 For the first time, Peacock plans to stream
0:06:30 all 329 metal events, 5,000 hours worth of content, live.
0:06:37 Streaming coverage of previous games was clunky.
0:06:40 NBC also wants to lock in a piece of the action
0:06:42 on other digital platforms,
0:06:45 specifically social media it doesn’t own.
0:06:50 For the Paris Games, NBC has done digital partnership deals
0:06:55 with Meta, Overtime, Roblox, Snapchat, YouTube, and TikTok,
0:07:00 with which it is producing a daily one-hour TikTok live show,
0:07:02 Spotlight on Paris.
0:07:05 On its own, the network itself
0:07:07 doesn’t seem to add much value.
0:07:12 Watching the games on linear broadcast TV is frustrating.
0:07:15 Somebody else is deciding what you’re going to watch.
0:07:18 A producer decides you’re going to see race walking
0:07:20 instead of surfing.
0:07:23 On Peacock, you can be your own producer.
0:07:27 This year, the technology caught up with the content.
0:07:29 The shift towards streaming has cultivated
0:07:32 more engaged audiences.
0:07:35 Viewers actively choosing what and when to watch
0:07:37 has led to greater engagement
0:07:41 and more targeted advertising opportunities.
0:07:44 I’d rather sit on the couch, let someone else decide,
0:07:46 complain about it, and be pelted by ads
0:07:49 about my restless legs or opioid-induced constipation,
0:07:51 but I digress.
0:07:56 Linear TV used to be the entire story.
0:07:59 Now it’s just one of three ways to watch.
0:08:01 Broadcast, streaming, and social media.
0:08:06 Increasingly, it’s becoming less of a distribution channel
0:08:09 and more of a content generator that feeds video
0:08:12 to the insatiable streaming and social media platforms.
0:08:16 Every sports organization on the planet
0:08:19 from Formula One to the National Football League
0:08:23 has turned its attention to digital distribution.
0:08:26 The Olympics, though, may be better suited
0:08:29 to the internet than any other sporting event.
0:08:32 Unlike the Super Bowl or the World Cup final,
0:08:34 the Olympics is not an event people will watch
0:08:36 from beginning to end.
0:08:40 It is, instead, a huge collection of little stories,
0:08:41 human moments.
0:08:46 We’ve watched best friends, Sarah Bacon and Cassidy Cook,
0:08:49 win a medal in synchronized diving,
0:08:52 and Simone Biles take flight.
0:08:53 We’ve watched the emotional TikTok
0:08:56 of Filipino weightlifter, Hidelin Diaz,
0:08:59 winning her country’s first ever gold medal.
0:09:01 Actually, this is from the 2020 games,
0:09:03 but never mind, go watch it.
0:09:09 Other Paris moments, Ukrainian fencer Olga Carlon
0:09:10 dedicating her bronze medal
0:09:13 to her country’s servicemen and women.
0:09:16 French swimmer, Leon Marchand,
0:09:19 crushing the competition in front of a huge crowd,
0:09:22 Brazilian surfer Gabriel Medina,
0:09:27 seeming to walk on air after an epic wave off Tahiti.
0:09:29 The good-natured trash talk between members
0:09:31 of the U.S. table tennis team
0:09:33 and basketball star, Anthony Edwards,
0:09:36 Edwards refused to believe he wouldn’t win a single point,
0:09:41 has been shared nearly 16 million times on X.
0:09:48 I was, no joke, the worst D1 athlete in UCLA’s history.
0:09:53 Crew, however, several friends went to the Olympics.
0:09:55 These athletes put their life on hold
0:09:57 to represent their country at the games
0:10:00 and, outside the romance sports,
0:10:03 made huge sacrifices economically
0:10:07 to be the best in the world at something, at that moment.
0:10:10 Greatness is in the agency of others,
0:10:12 and at the Olympics,
0:10:15 athletes are competing for something bigger.
0:10:16 National pride.
0:10:22 The Olympics do feel smaller than in the 1980s.
0:10:24 It may be because we are consuming them now
0:10:27 in smaller bites.
0:10:30 Some of what made them feel important in the past,
0:10:34 particularly the intense us versus them nationalism
0:10:36 of the Reagan era, is gone.
0:10:42 What is still there is the primal drive to compete
0:10:44 and the hunger to feel something.
0:10:48 In a world increasingly run by old people,
0:10:51 it’s inspiring to watch young people pursue excellence
0:10:55 for the sake of something bigger than themselves.
0:10:58 One another and their countries.
0:11:03 I like Celine Dion and the Olympics.
0:11:08 Life is so rich.
0:11:10 (gentle music)
0:11:13 (gentle music)
0:11:15 (gentle music)
0:11:18 (gentle music)

0:00:03 I’m Anusa Bramunyan from Vox Media.
0:00:04 While I see them all around the city,
0:00:07 I’ve never ridden in an autonomous vehicle myself.
0:00:09 I do have some questions about the tech.
0:00:10 You may as well.
0:00:13 – Hello, from Waymo.
0:00:15 This experience may feel futuristic.
0:00:16 – This is so cool.
0:00:20 – Vox and Waymo teamed up for an in-depth study
0:00:21 about AV perception.
0:00:22 And what they found was that,
0:00:24 as people learned more about Waymo,
0:00:26 their interest in choosing one
0:00:29 over a human-driven vehicle almost doubled.
0:00:30 – Person approaching.
0:00:34 Waymo can see 360 degrees and up to 300 meters away,
0:00:36 which helps it obey traffic laws
0:00:38 and get you where you’re going safely.
0:00:41 Swiss Re found that compared to human drivers,
0:00:44 Waymo reported 100% fewer injury claims
0:00:47 and 76% fewer property damage claims.
0:00:49 And speaking of safety,
0:00:52 folks identifying as LGBTQIA and non-binary
0:00:54 showed the highest interest in AVs
0:00:56 and women showed the greatest increase in interest
0:00:57 after learning more.
0:01:02 – Arriving shortly at your destination.
0:01:05 – So that actually felt totally normal.
0:01:06 AVs are here, and the more you know,
0:01:09 the more exciting this tech becomes.
0:01:11 You can learn more about Waymo,
0:01:13 the world’s most experienced driver,
0:01:14 by heading to Waymo.com.
0:01:20 – Support for the show comes from Into the Mix,
0:01:22 a Ben and Jerry’s podcast about joy and justice
0:01:24 produced with Vox Creative.
0:01:28 Ainez Bordeaux is a self-described hellraiser,
0:01:29 and she became an activist
0:01:32 after being caught up in the criminal legal system
0:01:34 when she couldn’t afford her bond.
0:01:36 And without a trial,
0:01:38 Ainez was sent to a St. Louis detention facility
0:01:41 known as the Workhouse,
0:01:43 notorious for its poor living conditions.
0:01:45 Here how she and other advocates
0:01:48 fought to shut it down and won
0:01:50 on the first episode of this special three-part series
0:01:51 out now.
0:01:54 Subscribe to Into the Mix, a Ben and Jerry’s podcast.
0:01:59 Today’s numbers, 180,000 and 200,000.
0:02:00 That’s how many people attended
0:02:03 the White Dudes for Harris fundraising event,
0:02:05 and white women answered the call,
0:02:08 which was the largest Zoom meeting in history.
0:02:10 Let’s turn this back to me.
0:02:12 I asked a hero of mine, no joke,
0:02:14 on the Zoom to say the following.
0:02:15 – I’m Luke Skywalker,
0:02:18 and I’m here to rescue you, Mr. Galloway.
0:02:20 (upbeat music)
0:02:24 (singing in foreign language)
0:02:31 – Welcome to Prop G Markets.
0:02:33 Today, we’re discussing Microsoft
0:02:37 and Meta earnings, Bill Ackman’s failed IPO, Ed.
0:02:39 That’s right, the farm boy from Tatooine,
0:02:42 who went on to be one of the most powerful Jedi Knights,
0:02:44 battling the Sith.
0:02:47 That’s right, he gave a shout out to me, Ed.
0:02:47 Jealous?
0:02:48 Jealous?
0:02:49 Do you even know what Star Wars is?
0:02:52 – I just watched like Ariana Grande or Bridgerton.
0:02:53 – No, what is Star Wars?
0:02:55 (laughs)
0:02:57 – My first sort of date, I was 13,
0:03:02 and I took Paula Cumnock to the Star Wars premiere
0:03:04 at the Abco Cinema in Westwood.
0:03:07 If that was back when, I’m not exaggerating,
0:03:09 I used to see movie, I used to see two movies a week,
0:03:12 and I would see some movies five or seven times
0:03:13 in the theater.
0:03:15 – Wow, that’s awesome.
0:03:16 – Well, I’m glad you’ve enjoyed
0:03:17 this walk down memory lane, Ed.
0:03:20 (laughs)
0:03:23 – I can see the enthusiasm in your voice.
0:03:25 – Yeah, yeah, it’s brimming, right?
0:03:29 This white dude’s Vaharis thing that you joined.
0:03:31 Have you been getting much shit from Fox people?
0:03:32 ‘Cause I’ve been seeing,
0:03:33 all I’ve been seeing on Fox News,
0:03:35 you know that’s my favorite news program.
0:03:37 All I’ve been seeing is people shitting
0:03:38 on white dudes Vaharis.
0:03:40 – No, I actually, I get more shit.
0:03:43 Fox in the far right is giving up on me.
0:03:45 I get shit from either the far lift
0:03:48 or I’m convinced it’s bots from people who hate me
0:03:51 or see me in the diametrically opposed to their economics.
0:03:53 – By the way, that’s one of my favorite biases of yours.
0:03:55 Is there any time that there’s a negative comment
0:03:58 about prof G, you have a theory that it’s a Russian bot
0:03:59 invasion?
0:04:01 – See, I believe what you just said was inspired
0:04:04 by some sort of the GRU or the CCP.
0:04:06 I don’t really think you feel that way about the dog.
0:04:07 – Yeah, the CCP has put me up here.
0:04:09 – It’s you, it’s you’re clearly been weaponized
0:04:11 by foreign adversaries.
0:04:13 Hey, just ’cause I’m paranoid doesn’t mean I’m wrong.
0:04:14 And by the way, when you get to my age,
0:04:15 you’re allowed to be a little bit paranoid.
0:04:16 – I agree, I like it.
0:04:19 – Fox is saying essentially that it was very identity,
0:04:22 it was the same identity politics that we always fall into
0:04:25 and that if Trump tried to do it, he’d get criticized.
0:04:26 – They did not like the name.
0:04:27 – Yeah, he would get criticized,
0:04:30 but he would basically say this is a thinly veiled
0:04:33 KKK meaning to inspire the crazies.
0:04:37 And when we did it, it was meant to sort of,
0:04:38 and it was a nice vibe kind of poke fun
0:04:43 at the identity politics that the left is guilty of sometimes.
0:04:46 But we weren’t there to represent white guys interests.
0:04:48 No one, I listened to all the speeches,
0:04:50 no one was talking about the power of white dudes
0:04:52 or why we’re not represented.
0:04:53 It wasn’t anything like that.
0:04:56 It was really, I was really, I don’t know
0:04:58 if you, how much time you spent up,
0:04:59 but it was a really nice vibe.
0:05:01 And we raised more than four million bucks.
0:05:04 I shouldn’t say we, it was this really talented guy.
0:05:06 He pulled off something so impressive so fast.
0:05:09 And if you think about every presidential election
0:05:11 usually has a technology at the core of it
0:05:16 or media, FDR was radio, JFK was TV, Trump was Twitter.
0:05:20 People say it was with Obama, it was Google.
0:05:21 And I used to think that this one
0:05:22 would be short form video.
0:05:25 This would be kind of the TikTok election.
0:05:27 But now I’m wondering if it’s gonna be the Zoom election.
0:05:29 All of these Zoom, have you been,
0:05:31 I assume almost everyone’s been invited
0:05:33 to a Zoom call something for Harris or something.
0:05:35 My bank account isn’t big enough for that.
0:05:39 No, like young men looking for love, Zoom for Harris.
0:05:41 Luckiest podcaster in the world,
0:05:44 drafting off the heels of someone much more talented
0:05:49 for Harris Zoom, do you haven’t got that call yet?
0:05:50 You haven’t got that call yet?
0:05:51 But we can keep going.
0:05:53 We should keep going with these ideas anymore.
0:05:55 Yeah, yeah.
0:05:56 You’re getting fed up.
0:05:56 You used to laugh at my jokes.
0:05:59 Now you realize, now you feel some power.
0:06:01 Now you’re like, oh.
0:06:02 Oh, come on.
0:06:04 So the big news, everyone comes up to me.
0:06:06 I had someone come up to me and asked me yesterday
0:06:08 and say, oh, we love your content.
0:06:13 Ed has a girlfriend, so this news has traveled
0:06:16 all the way to Picken County, Ed.
0:06:19 This is very exciting, very exciting.
0:06:20 So exciting.
0:06:22 Yeah, clearly you’re looking to move on.
0:06:25 Okay, let’s start with our monthly review of market vitals.
0:06:28 (upbeat music)
0:06:34 The S&P 500 had its worst July in a decade,
0:06:36 advancing about 1%.
0:06:39 The dollar fell, Bitcoin rose marginally,
0:06:41 and the yield on tenure treasuries declined,
0:06:43 shifting to the headlines.
0:06:45 The Federal Reserve held interest rates steady,
0:06:47 but acknowledged recent progress on inflation
0:06:49 could allow them to cut rates soon.
0:06:52 Second quarter revenue at Starbucks missed expectations
0:06:55 as total same-store sales declined 3%.
0:06:57 That metric was especially painful in China,
0:06:59 the company’s second largest market,
0:07:02 where same-store sales fell 14%.
0:07:05 And finally, Delta’s CEO revealed
0:07:07 that the CrowdStrike technology outage
0:07:09 cost the company half a billion dollars.
0:07:12 It took Delta longer than many other airlines
0:07:13 to recover from the outage,
0:07:16 and they ultimately had to cancel 5,000 flights
0:07:17 over several days.
0:07:20 The airline notified both CrowdStrike and Microsoft
0:07:22 to prepare for litigation.
0:07:26 Scott, your thoughts starting with the Fed meeting.
0:07:28 All right, so look, this continues to be
0:07:30 the kind of Goldilocks economy.
0:07:33 There’s 195 nations in the world, 194.
0:07:34 I wish they were the same nation,
0:07:37 and that is the US, at least economically.
0:07:39 Even though the current Fed funds rate
0:07:42 is at a 5.3% or two-decade high,
0:07:44 that historically is not that high.
0:07:48 US GDP rose at almost, I think it was about 2.8% annualized
0:07:49 in the second quarter,
0:07:53 which is higher than economists had forecasted.
0:07:55 And the unemployment rate’s about 4%,
0:07:57 which is still like historically low.
0:07:59 That’s basically full employment.
0:08:01 And the S&P and NASDAQ both had their best days
0:08:03 since February, following the announcement.
0:08:06 S&P up 1.6% of the NASDAQ up 2.6,
0:08:09 although I think it’s down today.
0:08:11 I just can’t get over how bad the Democrats are messaging.
0:08:15 The American public feels like Bidenomics didn’t work.
0:08:19 The economy here is, there is no nation in the world
0:08:21 that has an economy like ours right now.
0:08:23 And it just amazes me that we’ve done,
0:08:27 when I say we Democrats have done such a shitty job
0:08:30 communicating that I’m curious,
0:08:32 do you have any thoughts on why
0:08:34 Americans feel so bad about the economy?
0:08:36 – Well, we’ve talked a little bit about this
0:08:38 and we talked about it with Kyla Scanlon,
0:08:39 this idea of the vibe session.
0:08:43 But the data that we’ve seen is that,
0:08:45 generally speaking, consumer sentiment
0:08:48 doesn’t have anything to do with the economy.
0:08:50 All it has to do with is politics.
0:08:54 I mean, if you look at consumer sentiment by party,
0:08:57 Republicans were feeling good about the economy
0:08:58 until Biden took over.
0:09:02 And the same is true, or vice versa, for Democrats.
0:09:06 So I think the takeaway from this Fed meeting,
0:09:09 you know, this is probably the most decisive statement
0:09:11 we’ve heard from Jerome Powell
0:09:13 since we’ve started talking about this.
0:09:15 He was still a little bit cryptic,
0:09:16 but he did give us a timeline
0:09:19 and he was pretty confident and clear
0:09:20 about the direction of inflation.
0:09:24 And most importantly, he mentioned the word September.
0:09:27 He said, quote, a reduction in the policy rate
0:09:28 could be on the table as soon as September.
0:09:31 So I think we can be pretty confident at this point.
0:09:34 Rates will be cut at the next Fed meeting.
0:09:37 The cutting cycle is about to begin,
0:09:38 which will be good for the stock market.
0:09:40 It’ll also be really good for us
0:09:45 because for the first time in my career as a podcaster,
0:09:47 maybe I’ll get to stop talking
0:09:48 about Fed meetings every month.
0:09:50 – Yeah, or maybe buying a house at some point.
0:09:51 – Yeah, that too.
0:09:53 – So really interesting story,
0:09:56 Starbucks specifically, Elliot is gonna take a mistake.
0:09:58 You could go through the S&P 500 and say,
0:10:01 who has made the biggest bet is the most exposed to China.
0:10:02 And those stocks are probably
0:10:05 some of the worst reforming stocks in the S&P.
0:10:06 And that is China,
0:10:09 just as everyone uses the term AI and every earnings call,
0:10:11 if you go back seven, eight years,
0:10:13 it was the same except everyone just repeated
0:10:15 the word China over and over.
0:10:18 And Starbucks kind of went all in on China.
0:10:20 In the last five years, it’s nearly doubled.
0:10:21 Think about this.
0:10:23 It doubled its stores in the region,
0:10:27 but sales over that same timeframe are down 0.4%.
0:10:28 About one in five of their stores
0:10:30 are now located in China.
0:10:33 In addition to the lackluster spending,
0:10:36 Starbucks faces competition from Chinese coffee chain.
0:10:38 I think it’s called Lucan,
0:10:41 whose beverages get this ad cost a third of Starbucks.
0:10:44 And Elliot shows up, it’s an amazing brand.
0:10:47 Its stock price, I think is,
0:10:49 I don’t know if it’s down or flat over the last five years,
0:10:52 but it’s been a pretty significant underperformer.
0:10:53 I think they’re gonna take a page
0:10:58 out of the playbook from their activist intervention
0:10:59 at Salesforce.
0:11:01 And I think they’re gonna say,
0:11:03 stop the hallucination around growth and spending.
0:11:04 You need to cut costs here.
0:11:07 And so for example,
0:11:09 Starbucks is saying they plan to open an average
0:11:12 of eight new stores every day through 2030.
0:11:14 I think they’re gonna ask them to revise that.
0:11:15 I mean, these stores used to have
0:11:17 like an incredibly short payback period.
0:11:19 And so you just keep opening more stores.
0:11:22 And I think the juice has been squeezed from that lemon.
0:11:23 We’ve seen same store sales decline
0:11:24 for two straight quarters.
0:11:27 So there might be over stored in some regions.
0:11:29 They’ll probably urge them to invest more
0:11:31 in their expanding higher margin pickup delivery
0:11:32 and drive through businesses
0:11:36 while shutting down struggling brick and mortar locations.
0:11:39 But this feels like a classic sort of Elliot come in,
0:11:40 hi, we’re here to help,
0:11:44 meaning you need to cut costs or do the following things.
0:11:46 And we’ll go away quietly if the stock pops,
0:11:47 which I might hear.
0:11:50 And if it doesn’t, we’ll go gangstron you.
0:11:52 But Elliot typically likes to go after the ones
0:11:54 I’ve seen, big brands, big companies
0:11:58 where they have liquidity such that they can deploy AUM.
0:12:00 I also wonder if it’s sort of the last,
0:12:03 we’ll call it the last battle of Howard Schultz.
0:12:04 But Howard sort of left and come back.
0:12:06 He’s kind of the thing that wouldn’t leave in the sense
0:12:11 he’s always announcing his retirement and then coming back.
0:12:14 And so I’ll be curious if they get along here
0:12:18 like the kind of Benioff, Elliot love affair.
0:12:20 Again, this is all gonna come down to the male ego,
0:12:23 but starting or finishing where I started,
0:12:27 China has become the anchor around everyone’s neck.
0:12:28 If you’re exposed to China,
0:12:30 you’re just kind of hating life right now.
0:12:33 – Going back to Howard Schultz.
0:12:37 So this is the former CEO of the company.
0:12:38 He took up the job in 1986.
0:12:40 He sort of turned Starbucks
0:12:42 into the global iconic brand today.
0:12:46 He’s no longer the CEO, he’s no longer on the board,
0:12:49 but he has been publicly criticizing Starbucks
0:12:52 and its management for the poor performance
0:12:53 in the past few weeks.
0:12:54 – That’s helpful.
0:12:55 – Right?
0:12:57 – Thanks, thanks for that.
0:12:58 – This was a quote he said,
0:13:02 “The company has not executed the way I think it should have.
0:13:04 Senior leaders need to spend more time
0:13:06 with those who wear the green apron.”
0:13:08 He went and said this on LinkedIn.
0:13:11 He also went on a podcast and started talking about it.
0:13:13 And this is the guy, as you mentioned,
0:13:15 who’s been the CEO three times.
0:13:18 He came back to Starbucks in 2022.
0:13:20 And his job when he came back as the interim
0:13:24 was to facilitate a clean transition to the current CEO.
0:13:25 And now he’s going out to media outlets
0:13:29 and he’s shitposting the CEO and the rest of the board.
0:13:31 And the thing I find ugliest about this
0:13:33 is that Howard Schultz,
0:13:35 as I said, this is a holistic problem with Starbucks.
0:13:39 Howard Schultz is responsible for many of the problems
0:13:41 that they’re dealing with right now.
0:13:43 We mentioned China as an example.
0:13:45 This whole China investment thing,
0:13:47 this was all Howard Schultz’s idea.
0:13:49 He was the one who was pro-China
0:13:50 and who wanted to go and invest.
0:13:52 And I think the status that they wanted
0:13:56 to open up a store in China every nine hours.
0:13:59 And now it’s obviously backfiring on the company
0:14:00 and he’s shitposting them.
0:14:01 So I’d like to get your take
0:14:03 because this is a guy who’s sort of
0:14:05 the iconic American CEO.
0:14:09 He is known as sort of an impeccable businessman.
0:14:10 But I look at what he’s doing now
0:14:13 and I’m kind of like this behavior is pretty childish.
0:14:16 – Well, so just some disclosure.
0:14:18 Howard Schultz and his VC firm, Maveron,
0:14:22 run by this really wonderful thoughtful guy named Dan Levitan
0:14:26 invested in my e-commerce incubator in ’99
0:14:28 where I closed on my first round of funding
0:14:30 along with Goldman Sachs, J.B. Morgan.
0:14:32 So we closed on around in December ’99,
0:14:35 the concept was to punch out retail e-commerce companies.
0:14:37 And as you can imagine, six months later,
0:14:40 it just didn’t work ’cause the entire market imploded.
0:14:41 Which by the way is a good thing.
0:14:42 I’ve always said that fast failure
0:14:43 is the next best thing to success.
0:14:45 But so I have a little bit of bias here.
0:14:47 I do think that like Howard will go down
0:14:49 as one of the great consumer CEOs of all time.
0:14:50 He’s created a tremendous amount of value.
0:14:53 He’s legitimately and deserves to be a billionaire.
0:14:57 It’s just really bad form to shitpost the company.
0:14:58 Is that fair?
0:14:58 Have I done that?
0:14:59 I don’t think I’ve done that.
0:15:00 Well, maybe I have.
0:15:01 Well, shit, I don’t know.
0:15:02 But I’m a megalomaniac too.
0:15:06 So anyways, yeah, what he’s doing is not helpful.
0:15:07 What it signals to me is he’s planning
0:15:10 to be the CEO the fourth time
0:15:13 that he’s making a play to come back.
0:15:14 Can we get a hard prediction?
0:15:16 Will Howard Schultz return again?
0:15:17 I don’t know if the, enough dynamics there.
0:15:18 Let me go this way.
0:15:20 We have not heard it.
0:15:23 I’m almost entirely confident predicting Howard Schultz
0:15:25 is not gonna be quiet around this issue.
0:15:28 Let’s move on to Delta and CrowdStrike.
0:15:31 Your thoughts on Delta’s comments and the lawsuit.
0:15:33 I think the bigger learning here is that Lena Khan
0:15:35 has never been more important to our economy.
0:15:37 And she’s the FTC chair.
0:15:40 The concentration in the tech industry is just too great.
0:15:41 And what that means is,
0:15:43 is that the entire fucking airline industry
0:15:45 can be shut down or most of it,
0:15:48 except for the ones that had really rudimentary technology
0:15:51 Southwest, they were due for a break.
0:15:53 You basically can have the airline industry
0:15:56 in the largest economy nearly shut down
0:15:57 because these companies are dependent
0:16:00 upon a small number of technology vendors.
0:16:04 Since the outage CrowdStrike has declined nearly 25%.
0:16:06 I thought it was gonna give up 10% and then go back.
0:16:08 It’s not, it’s gone down further.
0:16:11 Still think it’s probably a buying opportunity.
0:16:14 But this is, this to me says more about the concentration
0:16:17 of power and how it can impact consumers and the economy.
0:16:21 The insurance, the settlement itself, they’ll figure it out.
0:16:22 They’ll come to some sort of,
0:16:24 they’ll come to some sort of accommodation
0:16:25 and all parties will move on.
0:16:27 Am I missing anything here, Ed?
0:16:30 – Well, the only thing I would add is,
0:16:31 I listened to his comments on CNBC.
0:16:35 This is the CEO of Delta who is talking about,
0:16:36 what a disaster it was
0:16:39 and how upset he is about the whole thing.
0:16:41 The way that I would describe those comments
0:16:46 coming from a Fortune 500 CEO is small dick energy.
0:16:49 And the reason that I say that
0:16:50 is that if you think about the damage to Delta here,
0:16:52 it’s actually really significant.
0:16:53 There’s the financial damage
0:16:56 where you had five, 6,000 flights canceled.
0:16:59 And then they also had to cover all of the customers
0:17:00 who were staying in hotels
0:17:02 and all these other expenses associated.
0:17:05 But there’s also the reputational damage.
0:17:08 And I would bet there are many people
0:17:10 whose flights got canceled,
0:17:12 who don’t really know what CrowdStrike is,
0:17:14 who kind of heard of it
0:17:16 and who ultimately believe that their vacation
0:17:19 and their week was ruined by Delta.
0:17:23 So I think this is a really big issue for Delta.
0:17:26 I think it’s big enough to warrant
0:17:28 possibly a termination with CrowdStrike
0:17:30 or at the very least,
0:17:33 it warrants considering a termination with CrowdStrike
0:17:34 and stating that publicly.
0:17:37 I think it speaks to a larger point,
0:17:38 which you’ve sort of hinted at here,
0:17:41 which is, why doesn’t he just end it with CrowdStrike?
0:17:45 Why doesn’t he switch to another cybersecurity provider?
0:17:46 And I think the answer is,
0:17:49 one, these companies have gotten too big.
0:17:53 And two, it would just suck to do that.
0:17:58 When it comes to enterprise SaaS and tech infrastructure,
0:18:02 you end up with this deeply dependent relationship
0:18:03 that makes it really hard to leave.
0:18:07 CrowdStrike has got this a 95% retention rate
0:18:11 over the 20 years of operation, 95% retention rate.
0:18:12 Do we think that’s because CrowdStrike
0:18:14 has an incredible product?
0:18:17 Or do we think it’s because CrowdStrike has made it
0:18:20 so that if you try to leave, it’s a total nightmare?
0:18:22 – Yeah, so you’re exactly right.
0:18:23 And you’re making the same point.
0:18:25 Ed Bastion is the CEO of Delta.
0:18:27 He’s not afraid to fire people or companies.
0:18:29 I mean, but he can’t.
0:18:33 And my guess is that once CrowdStrike figured out
0:18:34 an agreement with Microsoft,
0:18:36 it’d become more definitely integrated.
0:18:38 And you have Microsoft, you’re just trapped.
0:18:39 So all you can do is sue them,
0:18:41 but you can’t actually fire them or switch them.
0:18:43 And it goes to the point that the industry
0:18:45 is too concentrated.
0:18:47 Let me use this as a segue into talking about
0:18:49 one of my favorite things, airlines.
0:18:51 I would argue amongst the big three,
0:18:52 well, actually it’s Southwest too.
0:18:55 I still think Delta’s probably done the best job
0:18:58 in an environment where it is increasingly difficult
0:19:00 to establish any sort of differentiation.
0:19:02 I was a Delta person before.
0:19:03 – Why’d you switch?
0:19:06 – ‘Cause daddy flies private now and you knew that.
0:19:07 Anyways.
0:19:10 Fucking jerk.
0:19:13 Anyways, gets a girlfriend.
0:19:16 And now he thinks he’s like, why do you do that?
0:19:20 Anyways, Delta’s not a good job.
0:19:23 And they do the least bad job of all the domestic carriers
0:19:26 with the exception of JetBlue Mint.
0:19:28 Think about the competition there.
0:19:30 Consumers flying a company, they get angry,
0:19:33 they can switch, but Delta can switch.
0:19:35 Why don’t you fly Delta anymore?
0:19:37 (laughing)
0:19:42 We’ll be right back after the break
0:19:44 with a look at Microsoft and Metas earnings.
0:19:46 And if you’re enjoying the show so far,
0:19:49 hit follow and leave us a review on ProfG Markets.
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0:22:00 a Ben and Jerry’s podcast about joy and justice
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0:22:05 Would you have $25,000 to post bail?
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0:23:27 – We’re back with ProfG Markets.
0:23:29 Microsoft posted earnings that beat expectations
0:23:31 on the top and bottom lines.
0:23:34 The stock fell, however, on its disappointing cloud results.
0:23:36 Revenue from Azure and other cloud services
0:23:38 slowed from the previous quarter
0:23:39 and also fell short of expectations.
0:23:42 That’s the first time since 2022
0:23:44 that Microsoft has failed to meet
0:23:46 or beat expectations for that segment.
0:23:49 Meanwhile, investments in that area are accelerating.
0:23:53 Capital expenditures rose 78% to $19 billion
0:23:56 with nearly all of it going to AI and the cloud.
0:24:00 Scott, initial reactions to Microsoft’s earnings.
0:24:02 – What seemed to spook everybody
0:24:04 was just the arms race and the spending race
0:24:06 that all these companies have now entered into.
0:24:09 And the stat that just blew my mind
0:24:11 is that the capital expenditures
0:24:13 of Amazon, Meta, Microsoft, and Google
0:24:15 will spend about $200 billion this year on CapEx,
0:24:19 double what the US government spends on Homeland Security.
0:24:20 The entire revenue production
0:24:23 or entire revenue spawned by the AI companies,
0:24:24 their front-end applications
0:24:28 or what they get selling these chips is about $20 billion.
0:24:30 But the analysis you guys have done
0:24:32 has shown that there’s been about $3 trillion
0:24:34 in inspired increase in market capitalization.
0:24:37 So we have an industry that loosely speaking
0:24:39 is trading at 150 times revenues,
0:24:42 which is just striking.
0:24:45 And some people would argue is unsustainable,
0:24:47 but it was the CapEx
0:24:48 that kind of freaked everybody out here.
0:24:50 But their business,
0:24:54 every part of their business seems to be on fire.
0:24:56 What’s interesting is that people talk about,
0:24:58 investors talk about flows.
0:25:00 And that is you can find the best company in Argentina,
0:25:02 but if the flows are consistently
0:25:05 out of the Argentinian market, the capital flows,
0:25:09 the market’s bigger than any individual company’s performance.
0:25:10 And the flows here are interesting.
0:25:14 And that is when people start to have any wisp or concern
0:25:16 around the future of AI and its valuation,
0:25:19 their go-to is to go to the infrastructure place.
0:25:21 The same thing happened to Cisco in 98.99
0:25:23 where people start saying on the front end,
0:25:24 they’re not entirely sure
0:25:27 the winners and losers are will just invest in the infrastructure
0:25:29 or the steel on the ground, if you will.
0:25:31 And we see this now in terms of flows.
0:25:33 And that is the software layer,
0:25:34 Microsoft, Meta, Google and Amazon,
0:25:39 their CapEx is up 31%, but their revenue is only up 19%.
0:25:40 Whereas the infrastructure players
0:25:44 or the hardware layer that’s NVIDIA, AMD and ARM,
0:25:46 their CapEx is actually flat to down.
0:25:49 It says minus 8%, 2022 to 2024,
0:25:52 but their revenues are up 146%.
0:25:56 – Yeah, it’s interesting that Wall Street
0:25:59 has really latched on to that CapEx issue,
0:26:01 this CapEx investing.
0:26:04 But there’s a reason they’re doing that.
0:26:07 And that is sales are slowing.
0:26:10 But by the way, barely sales went from,
0:26:12 in the cloud division for Microsoft at least,
0:26:17 sales went from 31% two quarters ago to 29% last quarter.
0:26:21 So sure it’s a slowdown, but it’s still a crazy big number.
0:26:23 But it’s not actually slowing
0:26:25 because there’s a lack of demand.
0:26:28 In fact, it’s the opposite, there’s too much demand.
0:26:32 And according to Microsoft, they can’t keep up with it.
0:26:33 And so that’s why they’re making
0:26:37 these huge CapEx investments, $19 billion
0:26:38 in the previous quarter alone,
0:26:41 which is up 80% year over year.
0:26:42 We’re kind of witnessing
0:26:47 one of the largest CapEx investment movements in history.
0:26:48 Because it’s not just Microsoft.
0:26:52 This is Google, which doubled it last quarter.
0:26:55 It’s Meta as well, which we’ll get to, it’s Amazon too.
0:26:58 Everyone is sort of full tilt on the AI CapEx.
0:27:02 And we’ve discussed before how maybe there’s a danger there
0:27:05 that maybe they’re investing too heavily in the space.
0:27:07 You made the point that all the dogs
0:27:08 are barking up the same tree.
0:27:10 But the question that I would pose to you
0:27:13 based on this earnings report is,
0:27:14 the demand is there.
0:27:18 Companies want to pay them for the compute
0:27:20 and they can’t keep up with it.
0:27:24 So does Big Tech really have a choice
0:27:27 other than to just plow billions,
0:27:31 tens of billions of dollars into AI CapEx?
0:27:34 – Yeah, so there’s been a dramatic shift
0:27:37 in the way the boards approach CapEx
0:27:38 in terms of strategy.
0:27:40 And generally speaking,
0:27:43 when we’re on a board and the CEO brought you a plan
0:27:46 that included billion dollar plus CapEx,
0:27:47 you were to say, okay,
0:27:51 we want the lowest CapEx relative
0:27:53 to the potential return, right?
0:27:56 Would we rather do a billion dollar CapEx
0:27:58 or a series of 10, 100 million dollars
0:27:59 that feel a little bit more reasonable
0:28:01 and see what happens.
0:28:04 Now, what’s shifted, especially among Big Tech companies
0:28:06 because of the dramatic increase
0:28:08 in their price earnings ratios,
0:28:10 or that is access to cheaper capital
0:28:12 versus the rest of the economy.
0:28:14 It used to be this is gonna cost,
0:28:16 this will give us an advantage,
0:28:17 but it’ll cost a lot of money.
0:28:19 Hmm, I don’t know, let’s think about this.
0:28:21 We want to be careful.
0:28:24 Now, when someone, Andy Jassy comes in
0:28:28 or Jeff Bezos comes into the Amazon board and says,
0:28:31 I think we can get everything we sell
0:28:32 to people within 48 hours
0:28:35 by building out this unbelievable infrastructure
0:28:38 or fulfillment network that’s largely been avoided
0:28:41 because everyone just wants to be lowest cost
0:28:44 in terms of how to get things from point A to point B
0:28:46 that we see an opportunity.
0:28:47 And the board says,
0:28:49 well, how much would that cost to be able to do that?
0:28:50 We know consumers would love it.
0:28:54 And Bezos goes, oh, it would be so much fucking money.
0:28:56 It’d be tens of billions of dollars.
0:28:59 And the board hears that and goes, perfect.
0:29:01 Because what these companies have
0:29:03 is access to cheaper capital than anyone.
0:29:07 So AI is not only presents a bold, brave new world
0:29:09 with growth and potential for them,
0:29:12 it positions them to leverage their core competence
0:29:15 and that is to outspend every other company
0:29:17 in the economy, except for a few.
0:29:20 So these companies, just as a large investor
0:29:21 has to go big game hunting
0:29:24 because I remember I worked for a hedge fund
0:29:26 and I used to bring him ideas and he’d say,
0:29:28 I’m not interested in putting 50 million to work.
0:29:30 I have to be able to put 500 million to work.
0:29:33 These companies love AI because they,
0:29:35 A, they see real potential in growth
0:29:38 and that it’s a seminal technology and B,
0:29:41 it’s a place they can put tens of billions of dollars
0:29:43 to work because they have access to that money
0:29:47 and 99.9% of companies don’t.
0:29:51 So this is kind of you can see why they’re spending so much
0:29:54 and this is their, it’s kind of like capital as a weapon
0:29:58 as that strategy was sort of forged by Amazon
0:30:02 and then Netflix and that is get a leadership position,
0:30:06 access to cheaper capital and then just go gangster
0:30:08 in terms of your spending, right?
0:30:11 Netflix spending $17 billion a year on content,
0:30:13 that’s probably more than the entire media industry
0:30:16 spent on content in the decade of the ’80s.
0:30:18 But that’s, they love that
0:30:20 because it plays to their advantage.
0:30:21 And it was, I think this is a,
0:30:25 this is a cat-backs arms race that plays to their strengths
0:30:27 and they’re happy to engage in it.
0:30:32 – Moving on to Metta, who had a very strong quarter.
0:30:33 Just run you through the numbers here.
0:30:35 Revenue grew 22%.
0:30:37 That’s the fourth consecutive quarter
0:30:41 of 20 plus percent sales growth for Metta.
0:30:44 Net income rose 73%.
0:30:46 Daily active users also grew.
0:30:48 Here’s a great start from Mia.
0:30:50 Over 40% of the world’s population
0:30:54 is currently using Metta’s platforms on a daily basis.
0:30:57 40% of everyone on Earth,
0:30:59 daily active user on a Metta platform.
0:31:04 But CapEx is also still growing as with Microsoft,
0:31:06 record CapEx for Metta this quarter.
0:31:10 And Zuckerberg said that number would continue to grow.
0:31:13 Scott, your initial reactions to Metta’s earnings.
0:31:14 – I mean, I hate to admit it,
0:31:16 arguably one of the best run businesses in the world.
0:31:19 You know, I mean, the number you cite that just jumps out,
0:31:21 40% of the world’s population
0:31:23 is on a Metta platform every day.
0:31:26 I bet 90% of the world that advertisers
0:31:27 have any interest in reaching
0:31:29 are on this platform every day.
0:31:32 And they have unbelievable ad stack, unbelievable technology,
0:31:35 ad impressions and average price per ad,
0:31:40 both increased 10% or EPS of 73%, unbelievable.
0:31:42 Just absolutely unbelievable.
0:31:43 And I hate to admit it
0:31:46 ’cause I don’t like the company or the management team,
0:31:49 but I’m on Metta platforms all the time.
0:31:50 – Yeah, I wanna get your reaction
0:31:55 to an article that came out about Metta last week.
0:31:57 According to the Wall Street Journal,
0:31:59 Facebook and Instagram have been running ads
0:32:01 that have been steering users
0:32:05 to illegal drug markets online.
0:32:09 In other words, there are ads for drugs on Instagram now,
0:32:14 ads for cocaine, opioids, other drugs,
0:32:18 and Metta has been collecting revenue on those ads.
0:32:19 Thoughts on that news?
0:32:21 – I think that the people running Metta
0:32:23 are generally awful people.
0:32:26 If you have the incentives to get wealthy,
0:32:29 which are everywhere in the United States,
0:32:30 to be wealthiest, to be loved,
0:32:32 you will make a series of incremental rationalizations
0:32:34 to do things that are perhaps bad
0:32:35 for your customers and the nation.
0:32:38 So the fact that they’re running at,
0:32:43 they would run ads for, I don’t know,
0:32:47 tied pods as launch if someone would pay for it
0:32:49 and they thought they could get away with it.
0:32:52 So I’m not, it’s one of those stories I file
0:32:56 under the notion of shocking, but not surprising.
0:32:57 What are your thoughts?
0:32:58 – I think it’s more of the same.
0:33:00 And I think the question is whether this will
0:33:06 instigate any changes, but my instinct is no,
0:33:08 because you’ve been calling for changes
0:33:13 on this very problem for years and years.
0:33:19 So have our politicians, so has government,
0:33:22 and we keep on hearing the same story every time.
0:33:25 So I’m sort of beginning to develop
0:33:27 kind of a nihilist view of it.
0:33:31 And I’m starting to think that, you know,
0:33:35 this isn’t gonna do much to Metta,
0:33:36 and it’s not really gonna do much to the bottom line.
0:33:37 – Yeah, I don’t know.
0:33:41 I find the whole thing, the whole thing’s discouraging,
0:33:44 but you just can’t get around it.
0:33:48 The combination between, you know, genius management,
0:33:50 an incredibly deep talent pool
0:33:53 that is trading well-being for the Commonwealth,
0:33:58 for shareholder value, feckless political leaders,
0:34:02 a population that is addicted to the affirmation of others.
0:34:03 It all adds up to a company
0:34:07 that’s gonna be extraordinary for shareholders and has-men.
0:34:08 – We’ll be right back after the break
0:34:10 with a look at Bill Ackman’s failed IPO.
0:34:22 – Your mom hates it
0:34:25 when you leave six half full glasses on your nightstand.
0:34:28 It’s a good thing mom lives on the other side of the country,
0:34:29 and it’s an even better thing
0:34:34 that you can get six Ikea 365 plus glasses for just $9.99.
0:34:36 So go ahead, you can afford to hoard
0:34:38 because Ikea is priced for student life.
0:34:41 Shop everything you need for back to school at Ikea today.
0:34:45 – Looking to buy or sell a used vehicle?
0:34:47 Forget the selection and protection
0:34:48 of BCAA auto marketplace.
0:34:50 Try some random guy off the internet.
0:34:52 – Some random guy.
0:34:54 – Yes, we offered zero security.
0:34:56 – I can pay in crypto.
0:34:59 – Plenty of questions. – Is it still available?
0:35:01 – And zero convenience.
0:35:04 – 46 messages and I still make up.
0:35:07 – BCAA auto marketplace helps you buy and sell vehicles.
0:35:12 Visit bcaa.com/marketplace and avoid some random guy.
0:35:19 – It’s new, it’s blue, and it was made for you.
0:35:21 Introducing the thirst quenching summer berries
0:35:23 Starbucks refreshers beverage
0:35:25 where natural berry flavors meet juicy bursts
0:35:27 of raspberry flavored pearls.
0:35:29 It’s our most blutiful drink yet.
0:35:32 So try it while you can, only at Starbucks.
0:35:41 – We’re back with Prodigy Markets.
0:35:43 Bill Ackman has canceled his plans
0:35:46 to take Pershing Square USA public this week.
0:35:48 As we discussed on the show in June,
0:35:51 Ackman sold 10% of his investment company
0:35:54 to raise capital for his new soon to be public fund.
0:35:57 Then he hit the road to drum up investor support
0:36:00 to the tune of $25 billion.
0:36:02 But after weeks of lacklustre interest,
0:36:05 he cut that fundraising target twice,
0:36:08 first to $4 billion and then to $2 billion.
0:36:11 Now he’s pulling the listing all together
0:36:14 and he says he’s rethinking its structure
0:36:16 to address investor concerns.
0:36:19 Scott, a $25 billion closed end fund
0:36:21 would have been the largest of its kind.
0:36:24 Ackman went from eyeing a new record
0:36:27 to slashing his target by more than 90%,
0:36:30 canceling this thing altogether.
0:36:34 You also made a prediction about this story
0:36:35 a few months ago.
0:36:36 Let’s play that.
0:36:41 – So just as BlackRock has lost a lot of business
0:36:44 and taken a lot of grief for its impact investing
0:36:46 and focus on ESG,
0:36:48 Bill Ackman is kind of becoming the face
0:36:50 of the kind of anti ESG.
0:36:53 And I think that he’s gonna lose some investors
0:36:55 and come under some pressure.
0:36:59 The first quarter that his fund underperforms the marketplace.
0:37:00 I think people are gonna accuse him
0:37:02 of having taken his off the ball.
0:37:04 And I think a lot of investors
0:37:07 who actually appreciate impact investment and DI initiatives
0:37:10 or are pissed off of the way he’s handled this
0:37:13 are going to very loudly and publicly withdraw
0:37:14 or redeem from his fund.
0:37:17 I think we’re gonna start to hear from his investors
0:37:18 about his activities.
0:37:21 – Reactions? – Me neither than I was right.
0:37:25 First off, let’s talk about every hedge fund manager
0:37:28 or every private equity firm dreams of captive capital.
0:37:29 Now, why is that?
0:37:32 The way a hedge fund or alternative investment manager
0:37:36 goes out of business is mismatch durations.
0:37:37 What do we mean by that?
0:37:40 You invest long, but you raise money short.
0:37:43 So you invest in small companies or micro cap
0:37:46 or even private investments that are illiquid,
0:37:48 but your investors have redemption rights
0:37:49 and overnight the economy goes down
0:37:52 or for whatever reason they don’t like your performance
0:37:54 and they put in a redemption notice
0:37:56 and you have to sell down your positions,
0:38:00 which puts pressure on the value of those positions
0:38:03 thereby even decreasing an already probably lackluster
0:38:06 performance resulting in more redemptions
0:38:08 and you enter into a doom loop.
0:38:13 And even worse, if you have investments in illiquid assets
0:38:14 and you start getting more redentions
0:38:16 than cash on hand or liquid investments,
0:38:19 you have to put up something called a gate,
0:38:20 which has just kidding.
0:38:23 I said you would get money back on 30 days notice
0:38:25 or receipt of a redemption notice.
0:38:27 Gates are up and you can’t get your money back.
0:38:28 Once you do that,
0:38:30 you’ve effectively signaled the end of your fund
0:38:33 because once you bring your gates down again,
0:38:35 everybody submits the redemption notice
0:38:37 ’cause they don’t wanna get caught again.
0:38:39 Captive capital is every alternative
0:38:41 investment manager’s dream.
0:38:43 And one way to do that, there’s several ways to do that.
0:38:45 What Apollo and Berkshire Hathaway have done
0:38:48 is they’ve essentially started as insurance companies.
0:38:50 You have a massive amount of captive capital.
0:38:53 Another way to do that is to take the company public
0:38:55 because you get, while the share price,
0:38:57 the people who bought into the Cypio could sell their shares.
0:38:59 That just puts pressure on the stock price,
0:39:01 but Bill and the Pershing Square Fund
0:39:04 would have their capital and it’d be captive
0:39:07 and it’d be theirs and no one could call and ask for it back.
0:39:11 Now, the other story here is that I think we have hit
0:39:16 peak signaling or peak drunken texting or peak
0:39:17 kind of bullshit from communication,
0:39:20 from people who think that they can go on CNBC
0:39:23 with chunky glasses or that people are really fascinated
0:39:26 by Bill’s thoughts on DEI
0:39:28 when he has absolutely no domain expertise here.
0:39:30 And some of his viewpoints are seen as somewhat aggressive
0:39:32 and a bit reckless.
0:39:35 And lately he’s tweeted and though he deleted this tweet,
0:39:36 a conspiracy theory that there was no proof
0:39:38 that President Biden had actually signed
0:39:41 his resignation letter and just weirdness like that.
0:39:43 And when you’re Ottawa teachers
0:39:44 or the Michigan State Pension Fund,
0:39:48 you have so many choices of good fund managers
0:39:49 who will underperform the S&P
0:39:52 like every other fund manager minus their fees.
0:39:54 They’ll say, you know, we just don’t need to put up
0:39:55 with this bullshit.
0:39:59 And this kind of what I’ll call tweeting for awareness
0:40:03 thinking if I’m famous, people will want to invest in my fund.
0:40:06 Hit, I think it’s peak a few days ago
0:40:10 when Kathy Wood put out the following tweet.
0:40:11 Open quote.
0:40:14 As a result, our trading related capital tax losses
0:40:18 should offset trading related capital tax gains for years
0:40:23 and underappreciated asset associated with our strategies.
0:40:24 What is she saying there?
0:40:26 – I can’t even tell you.
0:40:27 I don’t know what she’s talking about.
0:40:30 – What she’s claiming is that they’ve lost so much
0:40:32 of other people’s money who were stupid enough
0:40:34 to invest in their fund
0:40:36 that it’ll offset losses in the future, right?
0:40:38 These losses will offset gains in the future.
0:40:42 And this is an underappreciated asset
0:40:44 as a result of their strategy.
0:40:46 Let me get this.
0:40:49 This is a good thing that you’ve lost this much money.
0:40:53 I mean, talking about trying to turn chicken shit
0:40:56 into chicken salad and believing your investors
0:41:00 and people on Twitter are this fucking stupid.
0:41:03 No, our losses, our destruction in your capital
0:41:05 is a feature, not a bug.
0:41:07 And she ended up deleting that tweet.
0:41:11 But I think in general investors are just getting fed up
0:41:15 with adventures in social engineering or commentary
0:41:17 or people trying to pretend they’re anything more
0:41:19 than just shitty fund managers
0:41:22 by thinking they can spin shit a different way.
0:41:24 And this is evidence of that.
0:41:26 I mean, this market, this IPO went from him saying,
0:41:31 I’m gonna raise $25 billion to $2 billion to zero.
0:41:33 That is pretty dramatic.
0:41:34 The market has kind of spoken here
0:41:36 and that is, you know what?
0:41:40 Your day job should be getting us returns, positive returns,
0:41:42 not trying to talk about social engineering
0:41:44 or spin your losses into something positive.
0:41:46 I think this is actually an interesting moment.
0:41:49 There’s this internet term you might have heard of,
0:41:51 extremely online.
0:41:53 I’m just gonna read you the internet definition
0:41:55 of extremely online.
0:41:57 To be extremely online is to post
0:42:00 and to see what has been posted as very important.
0:42:02 It is also to risk misunderstanding
0:42:04 what is seen on your screen
0:42:07 as too representative of the rest of the world
0:42:09 to think our niches are bigger than they are.
0:42:11 Whereas being online may simply be a matter
0:42:13 of having a phone, to be extremely online
0:42:15 would designate when the habits common
0:42:18 to communicating the screens seep into our awareness
0:42:21 and our identity and our behaviors
0:42:23 regardless of the screen’s presence.
0:42:27 Now I’m gonna read you Bill Atman’s sales pitch
0:42:29 when he proposed a $25 billion offering
0:42:32 which went to four and then two and then zero.
0:42:37 Quote, I have built a relatively large following on Twitter.
0:42:39 I have built up a large base of institutional
0:42:42 and retail followers that follow our every move.
0:42:46 Media interest is valuable in attracting investor interest
0:42:49 and also in creating liquidity for our shareholders.
0:42:51 I will be completely unrestricted
0:42:53 in terms of my ability to update our shareholders
0:42:55 about developments in the portfolio.
0:43:00 This is the internet definition of what it means
0:43:02 to be extremely online.
0:43:05 But I just love this story because for the first time
0:43:09 it’s put a literal dollar number on the delusion
0:43:11 of some of these extremely powerful
0:43:13 and extremely online individuals.
0:43:17 And the number is so big, it is so comical
0:43:20 that I would expect and I would hope
0:43:22 that it’s kind of shaken Bill Atman up
0:43:24 and it’s kind of made him think,
0:43:28 okay maybe I don’t have everything figured out.
0:43:30 – Yeah, I thought that was well said.
0:43:35 It was so lately I’ve found out
0:43:36 I’ve gotten a bunch of shit online
0:43:40 for some of the things I said about the election and the race
0:43:43 and Trump’s assassination or failed assassination attempt
0:43:46 and Megan Calley and some conservative podcasters
0:43:47 said my comments.
0:43:49 – Elon Musk, sorry, I just wanna point out.
0:43:52 Elon Musk said that your joke about Melania Trump
0:43:55 was quote, mean and cruel.
0:43:58 And that to me was one of the earliest indicators
0:43:59 that the right has gone woke
0:44:01 and that they have turned into the snowflakes,
0:44:03 but sorry, go ahead.
0:44:05 – Yeah, and just to be clear, this is a joke
0:44:08 and I actually got it off of a meme
0:44:10 is that Melania was seen yelling into a phone.
0:44:11 You had one job.
0:44:13 – How cruel of you, how cruel of you to say that.
0:44:16 – Yeah, whereas marking the disabled is just fine.
0:44:20 So I went on, I haven’t been on Twitter in a year and a half
0:44:23 but I went on ’cause I wanted to see these comments.
0:44:27 And the thought I had was that these folks
0:44:29 say the most ridiculous things,
0:44:33 but they’ve aggregated an audience of sycophants or bots
0:44:37 and they’ve blocked everybody that pushes back on them.
0:44:39 And they’ll say something ridiculous
0:44:42 and they get all this positive reinforcement.
0:44:43 And the thing that struck me was not only
0:44:45 how delusional these people are,
0:44:47 but just how small their world is.
0:44:51 And that I thought, okay,
0:44:53 I’ve been off of Twitter for a year and a half
0:44:54 and occasionally I do miss it
0:44:56 because I’ll get forwarded a link to an article
0:44:58 and I’d like to see the article and I can’t see it.
0:45:01 But what you realize when you’re off Twitter
0:45:05 is that it’s not only a bubble, it’s a really tiny bubble.
0:45:08 It just doesn’t have a hell of a lot of impact.
0:45:09 It’s an interesting communications.
0:45:13 But these people, they enter into this self-manicured,
0:45:16 self-reinforcing ideological bubble.
0:45:20 And I bet online that Bill Ackman probably,
0:45:23 when he’s on Twitter all day tweeting,
0:45:26 that he thinks, okay, my fund’s gonna be huge
0:45:28 and people love me online.
0:45:30 And I put out something saying Harvard’s DEI
0:45:33 is whatever, and I get 50,000 likes
0:45:35 and all this activity on Twitter.
0:45:39 And what you forget is nobody under the age of 30
0:45:44 uses Twitter, the person making investment decisions
0:45:49 on the behalf of ADIA or of the Florida State
0:45:53 pension program, they’re not on Twitter.
0:45:56 And these folks have literally entered
0:45:59 into an alternative universe where their idols
0:46:04 are Elon Musk or Kanye or tech libertarian brothers
0:46:05 who have a huge following online,
0:46:09 all talking to each other, all reinforcing each other.
0:46:11 And Senator Michael Bennett once said to me,
0:46:14 I was meeting with him about something and he said,
0:46:17 I said, well, Twitter says this and this
0:46:19 and he’s like, Scott, he’s like,
0:46:21 you’re under the impression Twitter is a much more
0:46:24 important place in the world than it actually is.
0:46:26 He’s like, the majority of voters don’t give a shit
0:46:29 what Twitter thinks or what’s happening on Twitter.
0:46:32 – You’ve said that to me before and it’s struck me too
0:46:33 because you’re off it now.
0:46:35 And I forget what the situation was,
0:46:37 but I said to you, everyone’s talking about this.
0:46:39 He said, no, no, no, everyone on Twitter
0:46:41 and your small following might be talking about this.
0:46:43 And it was absolutely right.
0:46:44 But that’s what happens if you’re on Twitter
0:46:45 and you’re on something all day,
0:46:47 you are where you spend your time.
0:46:50 And this is what has happened with Bill Ackman.
0:46:53 These folks are all figuring out that Twitter
0:46:55 is its own world and it’s a pretty small world.
0:46:58 And that is not how fund managers
0:47:00 or people in the real world are thinking.
0:47:02 – This is just how fucking toxic the platform is.
0:47:05 I did not know Elon Musk said that about me
0:47:07 and I’m already like just fucking angry.
0:47:11 – Don’t worry, I tweeted about it, I defended you.
0:47:12 I called him a snowflake.
0:47:14 – I’m literally, let me get this.
0:47:19 He goes on Jordan Peterson and says that his daughter
0:47:21 who went through transition is dead to him,
0:47:23 but I’m the cruel one.
0:47:27 – I believe he said, what mean and cruel people they are.
0:47:29 – That’s how people describe us.
0:47:32 Mean and cruel, the mean and cruel podcast.
0:47:34 Oh my God, watch out.
0:47:36 Yeah, anyways, let’s move on.
0:47:38 I feel like I need to shower.
0:47:40 – Okay, let’s take a look at the week ahead.
0:47:45 We’ll see earnings from Palantir, Uber, Airbnb and Disney
0:47:48 and we’ll also discuss Apple and Amazon’s earnings.
0:47:50 Scott, any predictions?
0:47:52 – Well, I think we said it.
0:47:57 We’ve hit peak tweet among alternative investment managers.
0:48:00 I think the bloom is off the rose.
0:48:04 I think people are like, just because you’re on CNBC
0:48:05 and have a large following on Twitter
0:48:08 does not mean that your SPAC makes any fucking sense
0:48:12 or that you can wallpaper over your shitty returns
0:48:16 or that support for your anti-DEI movement on Twitter
0:48:18 translates into investors thinking
0:48:20 they wanna give you captive capital.
0:48:21 I think there’s gonna be a lot of,
0:48:23 I think there’s gonna be more discipline,
0:48:24 not amongst politicians,
0:48:26 ’cause the person who started this
0:48:29 and it worked for him was Trump.
0:48:30 Trump would say, outrage is things online
0:48:32 and people that tickle people’s sensors
0:48:34 and it’s worked for him.
0:48:35 He is the Twitter president.
0:48:37 I don’t think it’s having that same sort of
0:48:41 efficacy or results for financial managers.
0:48:42 I think this is a much more serious business,
0:48:44 other people’s money and the people allocating
0:48:46 or making the biggest decisions around institutional
0:48:49 investment just have a different criteria.
0:48:51 – This episode was produced by Claire Miller
0:48:53 and engineered by Benjamin Spencer,
0:48:54 our associate producer is Alison Weiser,
0:48:56 executive producer is Jason Stavis and Catherine Dillon.
0:48:58 Mia Silverio is our research lead
0:49:00 and Drew Burris is our technical director.
0:49:02 Thank you for listening to Proficy Markets
0:49:04 from the Vox Media Podcast Network.
0:49:06 If you like what you heard, give us a follow
0:49:08 and join us on Thursday for our conversation
0:49:12 with Mark Mahaney, only on Proficy Markets.
0:49:17 ♪ Lifetimes ♪
0:49:24 ♪ You help me ♪
0:49:29 ♪ In kind reunion ♪
0:49:37 ♪ As the world turns ♪
0:49:41 ♪ And the dawn flies ♪
0:49:44 ♪ In love ♪
0:49:53 – Support for the show comes from Into the Mix,
0:49:55 a Ben and Jerry’s podcast about joy and justice
0:49:57 produced with Vox Creative.
0:50:00 Into the Mix is back for a new season
0:50:02 and welcomes you in with four new stories
0:50:05 that take listeners beyond the headlines
0:50:07 and into the lives of ordinary people
0:50:09 fighting for justice in their communities.
0:50:11 Starting with Ainez Bordeaux,
0:50:13 an activist and St. Louis native
0:50:16 who fought to shut down the workhouse,
0:50:18 a notorious pretrial detention center
0:50:21 that she says functioned like a debtor’s prison.
0:50:24 Subscribe to Into the Mix, a Ben and Jerry’s podcast
0:50:26 to listen to the first episode
0:50:28 of the special three-part series out now.
0:50:38 [BLANK_AUDIO]

0:00:01 (upbeat music)
0:00:04 Support for the show comes from Into the Mix,
0:00:07 a Ben and Jerry’s podcast about joy and justice
0:00:09 produced with Vox Creative.
0:00:12 Ainez Bordeaux is a self-described hellraiser,
0:00:15 and she became an activist after being caught up
0:00:16 in the criminal legal system
0:00:19 when she couldn’t afford her bond.
0:00:20 And without a trial,
0:00:23 Ainez was sent to a St. Louis detention facility
0:00:25 known as the Workhouse,
0:00:28 notorious for its poor living conditions.
0:00:31 Here how she and other advocates fought to shut it down
0:00:33 and won on the first episode
0:00:36 of this special three-part series out now.
0:00:39 Subscribe to Into the Mix, a Ben and Jerry’s podcast.
0:00:45 Support for the show comes from Into the Mix,
0:00:48 a Ben and Jerry’s podcast about joy and justice
0:00:50 produced with Vox Creative.
0:00:53 Ainez Bordeaux is a self-described hellraiser,
0:00:56 and she became an activist after being caught up
0:00:58 in the criminal legal system
0:01:00 when she couldn’t afford her bond.
0:01:01 And without a trial,
0:01:04 Ainez was sent to a St. Louis detention facility
0:01:06 known as the Workhouse,
0:01:09 notorious for its poor living conditions.
0:01:12 Here how she and other advocates fought to shut it down
0:01:14 and won on the first episode
0:01:17 of this special three-part series out now.
0:01:20 Subscribe to Into the Mix, a Ben and Jerry’s podcast.
0:01:24 – Scott, have you ever made a significant pivot
0:01:25 at one of your businesses?
0:01:28 And if so, how did you know is the right time
0:01:29 to make that change?
0:01:31 – Yeah, I’m not sure there is a significant business
0:01:35 that’s ever been built without something resembling a pivot
0:01:38 or iterating the business strategy.
0:01:42 So my first firm, Profit Brand Strategy,
0:01:44 was initially profit market research.
0:01:45 And we used to go out and do surveys
0:01:46 with the internet and computers
0:01:48 and try and find a different way to collect data.
0:01:53 And what we found is that what brands and clients appreciated
0:01:54 was the interpretation.
0:01:57 So we turned to Profit Brand Strategy
0:01:59 and we became a consulting firm at L2.
0:02:01 We were totally focused on the luxury space.
0:02:02 And then P&G called us and said,
0:02:04 “Would you ever do this for P&G?”
0:02:06 And the name of the company was Luxury Lab.
0:02:08 And I hung up the phone and said,
0:02:10 “Our new name is L2.”
0:02:15 And pivoted to or into consumer products at section,
0:02:17 my online education started up.
0:02:20 We initially thought we were gonna be the Netflix of business
0:02:23 that it would be short form videos for B2B.
0:02:25 And that was gonna be so expensive
0:02:26 to produce that kind of content.
0:02:29 So much of that content was available elsewhere
0:02:31 that we pivoted straight into online education
0:02:35 focusing on upskilling the enterprise or AI skills.
0:02:38 So I don’t think I’ve had a business where we didn’t pivot.
0:02:41 I think you just look at the data
0:02:45 and you are thoughtful about what are the opportunities?
0:02:49 And there’s nothing like facing the enemy.
0:02:51 There’s just no market research like launching a business
0:02:54 and seeing what people are actually willing to pay for
0:02:56 to inform your decision making.
0:02:59 And a lot of times clients will come to you and say,
0:03:01 “We’d love it if you could do this.”
0:03:05 And so you’ll get signals from the market.
0:03:09 And what I would suggest is have a solid board
0:03:10 and have your kitchen cabinet of people
0:03:14 that you can propose stuff to and bounce stuff off of them.
0:03:16 And also talk to your colleagues and your employees.
0:03:20 And I’m trying to think if we’ve done a pivot here,
0:03:24 I guess we’re sort of we had our adventures in television.
0:03:26 Now we’re kind of, I wouldn’t say all in on podcasts,
0:03:28 but I think we’re devoting the majority
0:03:32 of the human capital property media now to podcasts.
0:03:37 So the market is an unbelievable muse and advisor.
0:03:39 And you just wanna surround yourself with smart people
0:03:40 who can help you interpret the data
0:03:44 and make sure that you’re not speaking to yourself.
0:03:45 It’s very hard to read the label
0:03:47 from inside of the bottle sometimes.
0:03:50 (upbeat music)
0:03:54 – Welcome to First Time Founders.
0:03:59 One of the most promising use cases for AI is code generation.
0:04:02 That is doing the work of a software engineer.
0:04:06 Already in the US, an estimated nine in 10 software developers
0:04:08 are using AI coding tools.
0:04:11 My next guests created one of those tools.
0:04:13 And less than two years after launch,
0:04:16 it’s already one of the most popular AI coding assistants
0:04:18 in the world.
0:04:21 Last year, they had less than a thousand users.
0:04:24 Today, they have more than 600,000.
0:04:27 Now, after raising a $65 million funding round
0:04:31 at a $500 million valuation,
0:04:33 they’re looking to take over the industry.
0:04:37 Next up, compete with the likes of Microsoft and OpenAI.
0:04:40 This is my conversation with Varun Mohan,
0:04:42 CEO and co-founder of Codium,
0:04:44 and Jeff Wang, Codium’s head of business.
0:04:47 Varun, Jeff, welcome.
0:04:47 – Thanks for having us.
0:04:48 – How was the flight?
0:04:49 You just got in today, right?
0:04:50 – Yeah, we took a red eye
0:04:53 and we I think slept one hour each maybe.
0:04:55 And then when we got to the hotel earlier today,
0:04:56 maybe we slept another hour.
0:05:00 So we’re in perfect condition to do this podcast.
0:05:02 New York code spells are super fun.
0:05:04 You get like this matchbox room.
0:05:06 You know, you’re right next to the wall
0:05:08 every location you are, so perfect.
0:05:10 – Well, I appreciate you being here
0:05:11 and appreciate you joining,
0:05:15 despite getting one hour of sleep last night.
0:05:17 – It’s like two, I suppose.
0:05:19 – Yeah, yeah, good enough.
0:05:22 So you guys are the second AI company
0:05:23 that I’ve had on this podcast.
0:05:28 The previous one I had was an AI for finance company,
0:05:31 more or less replacing bankers,
0:05:35 though his argument is that he’s not replacing bankers.
0:05:37 I’m just gonna start this with the same question
0:05:39 that I asked him, which is,
0:05:42 are you guys at Codium replacing programmers?
0:05:46 – Our vision is actually to give developers
0:05:48 the ability to dream bigger.
0:05:50 And I know that that sounds very vague,
0:05:52 but I think there’s one way of looking at it
0:05:54 that we could just go out and replace
0:05:57 like low-skill labor or low-skill developers.
0:05:59 But I think that that’s not a very rich idea.
0:06:01 We wanna take the best developers
0:06:03 and make them 10 times as leveraged.
0:06:06 And the reason why we think that this is only going to lead
0:06:09 to more developers existing is unlike other professions,
0:06:11 there’s no limit to the amount of technology
0:06:12 the world can actually consume.
0:06:13 – Yeah. – Right?
0:06:15 I don’t think you would ever just be like,
0:06:18 hey, guys, stop making technology.
0:06:19 If we can actually make it so that
0:06:22 the next great invention happens 10 times faster,
0:06:23 we will just only get 10 times
0:06:25 the amount of invention in the world.
0:06:29 – So a program is generally fans of yours, would you say?
0:06:30 – I hope so.
0:06:33 Yeah, I mean, our message is not to replace developers,
0:06:34 I would say.
0:06:36 The Wave Room actually got me on board
0:06:40 ’cause he said like everyone that touches a product,
0:06:42 almost half the people continue using it.
0:06:45 So when you have that, you know there’s something there,
0:06:46 you know there’s some value, right?
0:06:47 And some excitement.
0:06:49 – Is that higher within the industry?
0:06:52 I mean, 50% retention basically of the customers.
0:06:56 That’s, do we know what it’s like for other AI tools
0:06:57 or is it too early?
0:06:59 – Yeah, I think for a lot of consumer products,
0:07:02 it’s usually in the, if you can get it above 10%
0:07:05 at the long tail that is considered very good.
0:07:07 That’s largely because consumers,
0:07:10 unlike companies, if they get bored of something,
0:07:12 they throw it away very quickly.
0:07:14 And these products are not collaborative also.
0:07:16 This is like a single player product.
0:07:18 So it’s actually very easy to churn off of the product
0:07:20 because you aren’t chatting with other people.
0:07:23 So it does mean it is providing a lot of leverage
0:07:25 and developers stay more in flow state
0:07:27 using products like Kodium.
0:07:29 But yeah, hopefully we can make it even better.
0:07:31 – I mean, you’re up against a lot of different tools.
0:07:34 And I mean, I feel like code generation
0:07:35 was one of the first things that people said,
0:07:37 “Oh, AI is going to take over this thing.”
0:07:41 But I feel like the biggest competitor in your space
0:07:43 is GitHub Copilot.
0:07:45 What does the competitive landscape look like
0:07:48 in the AI code generation space?
0:07:50 – There are reasons why we are able to compete directly
0:07:51 with Copilot.
0:07:54 One of them is that we have full repo context awareness.
0:07:56 So as the user is typing,
0:07:58 the results are highly personalized
0:08:01 and we’re seeing like a 30 to 40% boost in accuracy
0:08:03 just having that code base be available
0:08:06 and giving tools for the user to point to
0:08:09 what they’re working on and trying to figure out their intent.
0:08:12 So just the quality of our code suggestions
0:08:14 are very competitive.
0:08:16 And then the thing that we’re really kind of trying
0:08:19 to lean in on though is our ability to deploy
0:08:21 onto like a private server.
0:08:24 And people can host Kodium inside their company
0:08:26 or in their work environment.
0:08:29 And for example, if you’re like in the defense space
0:08:31 or like the finance or healthcare space,
0:08:33 they can’t use Copilot at all.
0:08:35 And that’s kind of where we are focusing right now,
0:08:38 our efforts, but then we have some things down the pipe
0:08:40 where we’ll just be competitive
0:08:41 even on the cloud front too.
0:08:43 – What does it look like for a programmer?
0:08:46 I mean, it sounds like you’re sort of typing in
0:08:49 and then it gives you a list of auto suggestions
0:08:51 for what comes next.
0:08:53 What does it actually look like if you’re a programmer?
0:08:56 And please explain it to me as if I’m five
0:08:59 ’cause I don’t program, I don’t, not a coder.
0:09:02 – Yeah, so a little bit about like the way software
0:09:03 sort of gets built.
0:09:06 So developers write code and what’s called an ID.
0:09:09 It’s this application that enables you to debug code.
0:09:11 So if there are bugs, you could run it.
0:09:14 You can actually see what the errors are, iterate on it, right?
0:09:18 And then right before the code gets pushed into production,
0:09:20 it goes through a review process.
0:09:22 And other people in the company take a look at the code
0:09:23 and actually review it.
0:09:26 And then after that, it goes and it actually gets deployed
0:09:28 into production and it’s on a website or whatever,
0:09:32 where end users can actually touch the product in the end.
0:09:36 And right now where codium is mostly focused is in the ID.
0:09:38 So that’s where developers actually write the code.
0:09:40 It provides value in multiple ways.
0:09:42 So as developers are writing code,
0:09:46 it fills in passively starts filling in more and more code.
0:09:48 And because of the fact that we actually do train
0:09:51 our own models for that passive AI,
0:09:54 we actually found that around 50% of all software
0:09:57 that is getting committed by a developer
0:10:00 is actually accepted and generated by codium.
0:10:02 So that’s the amount of leverage
0:10:05 that just autocomplete is providing to end users.
0:10:08 But to add to that, we also provide a couple of other pieces
0:10:10 of functionality that is super valuable,
0:10:13 despite what level you are as a programmer.
0:10:15 So you can even chat with your code base.
0:10:17 And this probably seems like a very basic piece
0:10:20 of functionality, but when you’re a new developer
0:10:21 and you’re coming into a company
0:10:23 and you have millions of lines of code,
0:10:25 it takes a while to actually onboard
0:10:26 onto that new code base.
0:10:29 And what we’re finding is even at the largest enterprises,
0:10:32 the time it takes to onboard onto a code base
0:10:35 goes down from four to six months to four to six weeks
0:10:37 with a product like codium.
0:10:40 – I wanna focus on how you started this company.
0:10:45 You were a software engineer at a self-driving vehicle company.
0:10:48 So you were kind of working on AI there, I feel like.
0:10:53 And you originally had an idea to start a company
0:10:55 not for writing code with AI,
0:11:00 but for something called GPU virtualization,
0:11:02 completely different company from codium.
0:11:03 It also had a completely different name.
0:11:05 The name was Exa Function.
0:11:09 Can you explain the first iteration of this company
0:11:11 before it became what is now known as codium?
0:11:12 – So to add a little color there.
0:11:14 So I graduated from MIT,
0:11:16 worked at this company called Nero.
0:11:18 It’s an autonomous goods delivery company.
0:11:19 And actually a lot of the learnings
0:11:20 that I had from autonomous vehicles
0:11:23 are actually making their way into the space
0:11:24 we’re in right now.
0:11:25 – Oh wow.
0:11:28 – And maybe to paint some clarity on that.
0:11:30 In 2015, TechRunch basically wrote,
0:11:32 this is the year of AVs.
0:11:34 And in 2024 now, the quote is,
0:11:36 is this the year of AVs?
0:11:38 And you can see how there’s probably going to be
0:11:39 a lot of parallels to generative AI
0:11:42 where we are going to severely overestimate
0:11:44 what is going to happen in a year.
0:11:46 And one of the cool parts about generative AI
0:11:48 is how easy it is to make a demo,
0:11:50 but it is tremendously hard
0:11:51 to make something production ready.
0:11:52 And if you make a claim
0:11:54 that you are going to get rid of a developer,
0:11:56 that is a massive, massive claim.
0:11:57 And in fact, I would actually argue
0:12:00 that is a harder problem than autonomous vehicles.
0:12:01 Because ultimately,
0:12:02 if you look at autonomous vehicles,
0:12:04 all you need to do is press the accelerator
0:12:06 or decelerator or turn a steering wheel.
0:12:07 – That’s a great point.
0:12:08 – Think about the number of different things
0:12:09 a developer actually needs to do.
0:12:11 So I actually led a team
0:12:13 to build large scale deep learning infrastructure.
0:12:16 So how do you run these models at scale
0:12:18 and sort of left the company
0:12:19 with this vision of deep learning
0:12:22 and the idea of running these large models
0:12:24 was going to affect many, many industries.
0:12:25 And we had a small team of people.
0:12:28 We had eight people managing upwards of 10,000 GPUs.
0:12:32 We managed close to 20 to 30% of an entire data center.
0:12:34 And we worked with a lot
0:12:36 of these large autonomous vehicle companies
0:12:37 when we started this company, Exafunction.
0:12:38 Because our mission was,
0:12:41 how do we make it easier to run deep learning models?
0:12:42 But what ended up happening?
0:12:44 This is where startups can always get disrupted.
0:12:46 And it sounds silly to get disrupted.
0:12:48 We were making seven figures in ARR,
0:12:51 but we realized actually most of the models
0:12:53 would probably become these transformer based models.
0:12:56 And these are the models that underpin the GPTs,
0:12:57 the models that open AI has.
0:12:59 – What is a transformer based model?
0:13:00 If you could explain for us, yeah.
0:13:02 – So the basic idea is,
0:13:04 so we now know of prompting, right?
0:13:06 You know, use chat GPT, you pass in a prompt
0:13:10 and notice how it streams tokens one at a time, right?
0:13:12 That’s actually a property of these models
0:13:13 that are called transformer models,
0:13:15 that they are what are called auto aggressive.
0:13:17 They actually generate one token at a time.
0:13:19 And this is very different
0:13:21 than a lot of other classification tasks in the past
0:13:22 where you pass in an input
0:13:25 and it just gives you the entire answer all in one shot.
0:13:28 But this actually like slowly generates the entire thing,
0:13:30 sort of one word, one token at a time.
0:13:31 And we started noticing actually
0:13:34 that that was how a lot of models were starting
0:13:37 to look like once open AI came out with GPT-3.
0:13:39 And the beautiful thing about the model
0:13:41 that is truly crazy is because of the way it is trained,
0:13:43 it can do it in an unsupervised way.
0:13:45 So one of the things that was very different
0:13:49 about models in the past is you needed a lot of label data.
0:13:51 But these models are trained on the entire public internet.
0:13:53 The label data is the internet.
0:13:55 So because of that, you suddenly got these models
0:14:00 that could take in basically trillions of tokens of code
0:14:03 or text and this was not possible in the past
0:14:05 and this created these new sort of generative models.
0:14:06 And in the middle of 2022,
0:14:09 we had this business that was a GPU virtualization business.
0:14:11 The idea was we made it simpler
0:14:14 to run applications on GPUs.
0:14:16 And we found out that most applications
0:14:19 would probably be these transformer models.
0:14:21 And if all of what we were doing
0:14:22 was running transformer models,
0:14:24 we would largely become a commodity
0:14:26 because they would become a race to the bottom, right?
0:14:28 It would be the equivalent of asking,
0:14:31 like they would ask Varun how cheaply can you run this model?
0:14:33 I’d say I can do it for a dollar.
0:14:34 Then they would ask Jeff how cheaply you can do it.
0:14:36 He’d say 50 cents and we’d go back and forth
0:14:37 until no one made any money.
0:14:40 And this is the commodification of this entire space.
0:14:43 But what we did see was we felt that this technology
0:14:45 would be like the early coming of the internet.
0:14:47 There would be a brand new set of applications
0:14:48 that would be created.
0:14:50 And we were early adopters of GitHub’s product,
0:14:52 GitHub Copilot, and we thought that that was just scratching
0:14:55 the tip of the iceberg of what the future would look like.
0:14:57 And that’s where Codium sort of came about.
0:15:00 But it was, as you can imagine, a very rough experience
0:15:03 because we basically said buy to all the revenue that we had
0:15:05 and we had to start all the way back down to zero.
0:15:10 So, I mean, that to me is like the mother of all pivots
0:15:14 where not only are you changing the entire business
0:15:16 as you know it, you’re also doing it at a time
0:15:17 when things are going really well.
0:15:20 I mean, you said seven figures ARR.
0:15:22 My understanding is that you’d also raise $22 million
0:15:24 for this company.
0:15:26 Like things are going right.
0:15:30 And then you turn around and you tell all your employees,
0:15:32 actually would scrap that.
0:15:34 We’re going to do a whole different thing.
0:15:38 If I were a software engineer who worked at Big Tech
0:15:40 and had quit to go work at ExoFunction
0:15:45 and the CEO told me that, I’d be a mixture of like pissed off,
0:15:46 freaked out, concerned.
0:15:49 How did you rally the team
0:15:52 and how were you able to make that pivot so successfully?
0:15:53 – So I’ll say a couple of things
0:15:55 about the composition of the team.
0:15:57 Largely they were people that we knew.
0:15:58 And that’s actually very important
0:16:00 because they would be people that would go
0:16:02 into the trenches with us.
0:16:04 They were people that knew the caliber of people
0:16:07 that both me and my co-founder were.
0:16:08 And also on top of that,
0:16:10 we picked a problem space
0:16:13 where we were all passionate about it.
0:16:15 And I 100% knew at the time
0:16:19 there were products like mid-journey that were taking off.
0:16:20 Small team of people, eight people
0:16:23 that were making tens of millions of dollars in revenue.
0:16:24 And frankly speaking,
0:16:26 when we decided to pivot the company,
0:16:27 we knew for a fact,
0:16:29 none of us were that passionate about image generation
0:16:31 despite the fact that it is a very cool area.
0:16:32 And if we had picked it,
0:16:35 our team wouldn’t have had I guess the mental fortitude
0:16:38 to dig deep enough to actually build the problem space.
0:16:41 And then I guess the sort of third part
0:16:43 is actually that we actually were able to take
0:16:45 a lot of the infrastructure expertise
0:16:46 that we had as a company
0:16:48 to actually go out and build the application
0:16:49 significantly faster.
0:16:51 We were very quickly able to train our own models
0:16:52 and run them at massive scale.
0:16:54 And right now, Codium is one of the top five
0:16:56 largest generative AI apps
0:16:57 in terms of text in the world.
0:17:00 And that largely is because the original composition
0:17:02 of the team was these people
0:17:05 who are effectively GPU infrastructure experts.
0:17:07 But all said and done, everything that I said,
0:17:11 it comes down to you need a very truth seeking company.
0:17:13 And at the time,
0:17:15 even if we were at seven figures in revenue,
0:17:18 I did not know how we would 10x the amount of revenue.
0:17:20 And we could continue to lie to ourselves
0:17:23 and have a slow but certain death as a company
0:17:25 as the technology commoditizes, right?
0:17:27 And we all run the same kind of models.
0:17:28 Or we could just say,
0:17:31 there is a high probability that we will die,
0:17:33 but there’s a space that we could be very passionate about
0:17:34 and it could be very big.
0:17:37 I think we just decided the latter was
0:17:39 the more rational choice it is very hard to make.
0:17:43 But in retrospect, it was the obvious choice, right?
0:17:45 – Did you have any data showing you
0:17:47 that you were going to crash and burn at that point?
0:17:48 Or was it just a hunch?
0:17:50 And part of the reason I asked that
0:17:53 is because if I were your investor,
0:17:55 I would wanna be like, oh yeah, yeah.
0:17:58 It’s very clear to me that you guys have to pivot.
0:18:01 – We were cashflow positive then.
0:18:02 We were cashflow positive then.
0:18:04 – So you just had a feeling?
0:18:06 – We had a feeling.
0:18:08 It’s just because, and this is a little bit of a curse
0:18:11 of being a venture capital, venture-based business.
0:18:13 If you’re making millions of dollars in revenue,
0:18:15 that is not a venture-backable business.
0:18:19 And if we can’t figure out a path to get that to 100,
0:18:21 then that is not a business that we could build.
0:18:25 We could continue to keep it as an eight to 10% team.
0:18:26 We have another mentality in the company
0:18:27 beyond being truth-seeking
0:18:29 that we are a very lean company.
0:18:30 By the time we raised our Series B,
0:18:32 we had barely spent our seed round.
0:18:35 And I think that’s just because we don’t think capital
0:18:38 is a limiting factor in building a good business.
0:18:41 It’s you have to build a great product that customers love.
0:18:43 And that is usually not just you had more money.
0:18:46 – We’ll be right back.
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0:21:18 – We’re back with First Time Founders.
0:21:20 One of the things you mentioned
0:21:23 is that you are training your own models.
0:21:25 I mean, this is an AI application,
0:21:28 but most AI applications that I am aware of,
0:21:32 they’re purely building the application layer,
0:21:35 and that is they’re basically using someone else’s model,
0:21:38 usually open AI, and they’re tweaking
0:21:39 and they’re building off of that model
0:21:41 and creating their own application.
0:21:42 You guys are different.
0:21:44 It sounds like you guys are,
0:21:45 I don’t know what you’d call it,
0:21:48 full stack AI from the model to the application.
0:21:49 Is that right?
0:21:50 – That is correct.
0:21:52 Actually, even at the kernel layer,
0:21:55 we’ve done some, like we’ve written some code
0:21:57 even at the infrastructure layer
0:21:58 so that we could set the models on top
0:21:59 in an efficient manner.
0:22:01 And the reason we have to do that
0:22:03 is because of the latency issues we talked about.
0:22:05 For example, if you are a passive AI
0:22:07 and you take, let’s say one second
0:22:09 to show up the suggested code,
0:22:10 people are just going to stop using that.
0:22:12 They don’t want to get out of flow state
0:22:14 and pause and wait for results.
0:22:18 – How many other AI startups are doing,
0:22:19 what should we call it, the full stack,
0:22:23 the infrastructure to application?
0:22:24 Are there many others?
0:22:26 I just, I mean, off the top of my head,
0:22:29 I’m like anthropic like open AI,
0:22:32 but I guess they’re mainly kind of infrastructure layer, right?
0:22:34 I mean, isn’t this super rare?
0:22:36 – I think in my mind,
0:22:39 there’s maybe a couple of unique things about code
0:22:41 that make it so that you can actually do this here.
0:22:42 And you’re totally right.
0:22:44 Most of the large companies that are even successful
0:22:46 are largely built on top of an API,
0:22:49 but we genuinely felt to build a best in class app here.
0:22:51 We needed to become vertically integrated.
0:22:55 And for us, it was also not a complex thing for us to do
0:22:58 in that we have the technical talent inside the company
0:22:59 to actually go ahead and do that.
0:23:02 Maybe one of the unique aspects of code
0:23:05 on why we can do this is code can actually be run.
0:23:08 Like let’s say I am a illegal AI tool
0:23:10 and I’m redlining a bunch of documents.
0:23:12 The only way to know if that is good
0:23:14 is for a human to go in afterwards
0:23:16 and actually take a look at it.
0:23:17 For code, you can actually,
0:23:19 if you make an edit to a code base,
0:23:21 you can actually run the code and validate
0:23:22 it is doing the right thing
0:23:24 without a human in the loop at all.
0:23:26 And what that means is there are ways in which
0:23:29 you can close the loop in intelligent ways
0:23:30 that you can actually,
0:23:32 if you specialize on that application
0:23:34 and you are vertically integrated,
0:23:37 you can build an even better app for code.
0:23:40 And we’ve taken advantage of this in many, many ways.
0:23:42 And we realized if we didn’t do this,
0:23:43 we’d be shooting ourselves in the foot.
0:23:45 And I’ll give you even a simple example
0:23:47 of how this manifests itself.
0:23:49 Right now, I mentioned this.
0:23:51 Codium is, processes over a hundred billion tokens
0:23:53 of code every day, which is over 10 billion lines
0:23:54 of code every day.
0:23:56 If we passed that through OpenAI,
0:23:57 we would have gone bankrupt.
0:24:00 And there was a recent article from the Wall Street Journal.
0:24:01 – And why is that, sorry,
0:24:02 because you would have to pay for it.
0:24:03 – Because it would be too expensive.
0:24:04 – Exactly.
0:24:08 – And not the best for our particular application
0:24:09 on top of that.
0:24:11 And if you look, there was a recent article
0:24:13 on the Wall Street Journal about how GitHub Copilot
0:24:16 was spending tens of dollars per user per month.
0:24:18 And that’s actually because even GitHub,
0:24:20 Microsoft’s product is not vertically integrated.
0:24:22 They are relying on external models
0:24:24 to build their application.
0:24:27 And we view that as, hey, the model and the product
0:24:28 and the infrastructure are so critical
0:24:30 to delivering a great experience,
0:24:32 why would we not have control over every piece of that?
0:24:35 So my understanding is you guys don’t use
0:24:38 the actual data of your individual users.
0:24:42 So how is the model getting trained then?
0:24:45 – So we actually do sort of two different things.
0:24:48 And I’ll let Jeff add on how this affects our enterprises
0:24:50 and the customers that use the product.
0:24:52 So first of all, we use permissively licensed code
0:24:54 that is available on the public internet.
0:24:56 And we also attribute it on generation time.
0:24:59 So we actually take sort of copyright
0:25:01 and licensing very seriously as a company.
0:25:03 But on top of that, when we release product
0:25:04 from our user data, you’re right,
0:25:06 we don’t take the data from our users,
0:25:08 like let’s say when they’re auto-completing stuff
0:25:10 and copy that code and put it into our training set.
0:25:13 But we can see, hey, users are accepting
0:25:14 these types of suggestions more
0:25:16 and these types of suggestions less.
0:25:19 So we have preferences on what users and humans like.
0:25:21 And that actually informs us to actually build products
0:25:23 that are better and more willing to use.
0:25:25 And then that actually has a virtuous cycle
0:25:26 and that now people are willing to try
0:25:28 more complex things on our product
0:25:29 because the easier things they have,
0:25:31 high confidence that they work.
0:25:33 And suddenly the frontier of what we are actually able
0:25:36 to experience as we are able to give the user
0:25:37 increase more and more,
0:25:39 largely because we have a product that is so well beloved.
0:25:42 We now have over 600,000 users that use our product.
0:25:43 – Yeah, it’s unbelievable.
0:25:45 – I think one thing we might have glossed over
0:25:48 in the beginning was codeon made a very conscious decision
0:25:51 to make the product free for individuals.
0:25:53 And if you think about, you know,
0:25:57 Varun just said co-pilot loses $10 to $20 a month per user.
0:26:00 That’s after they’ve been paying a subscription to, right?
0:26:02 So having that infrastructure background,
0:26:05 being able to make it efficient to deploy these models
0:26:07 and then giving it out for free for individuals,
0:26:09 allowed us to build this very large user base,
0:26:12 probably the largest user base for a coding assistant.
0:26:14 – Yeah, I mean, just the data here,
0:26:17 you started out last year with less than 1,000 users,
0:26:19 by the end of the year, you had half a million.
0:26:21 – Yeah, and we have over a million,
0:26:23 millions of downloads across all the plugins.
0:26:24 And the reason why that’s very important
0:26:26 is because of what we just talked about.
0:26:27 If we roll out multiple models,
0:26:29 if we are changing the temperature
0:26:31 of the thresholds here and there,
0:26:33 we are getting so many signals
0:26:35 as to what is the appropriate settings to tweak.
0:26:38 And I think every hour we’re getting like a million signals.
0:26:41 So we can run all these experiments on these free users
0:26:43 of all these models we train
0:26:44 to really, really get the best results
0:26:45 that you could possibly get.
0:26:48 And then only when we’ve validated like, okay,
0:26:49 we’ve trained this model,
0:26:51 this is better than all the other ones we’ve trained.
0:26:53 These are the settings that makes the best results.
0:26:55 Then we could deploy that to our on-prem
0:26:57 or enterprise users, right?
0:26:59 Because we can’t, after we’ve deployed it,
0:27:00 we can’t really get that much more information from it.
0:27:01 It’s completely,
0:27:04 it can be hosted even in an air-gapped environment.
0:27:06 So I think that’s a big element
0:27:07 of why we are successful
0:27:09 of being able to deploy these models.
0:27:12 Because if somebody’s trying to start from scratch right now,
0:27:14 how are they gonna know that their model is good?
0:27:16 How are they gonna tweak the model, right?
0:27:18 Without a very large user base.
0:27:19 So that’s part of the secret sauce
0:27:21 is having that free user base.
0:27:24 – Yeah, and you, it’s still free,
0:27:26 which is what I find pretty fascinating.
0:27:28 And you said, I was just reading your state,
0:27:30 your like mission statement,
0:27:33 you are quote committed to having a free tier forever.
0:27:36 The natural next question is,
0:27:39 how is it gonna get properly monetized?
0:27:41 And how are you gonna maintain that,
0:27:43 that free tier into perpetuity?
0:27:45 – I think people underestimate kind of the demand
0:27:47 for both just the on-prem instance,
0:27:49 but also some of the teams features we add
0:27:50 on the SaaS product.
0:27:52 So we have a free individual tier,
0:27:56 but if you create a team and add on-board users to it,
0:27:57 that is a paid product.
0:27:59 And there are things like analytics
0:28:01 and actually bigger models and seat management
0:28:04 that are going to be better than the free product.
0:28:06 But we are committed to making the free product
0:28:08 the best coding assistant out there, no matter what.
0:28:10 So whatever other coding assistants come to market,
0:28:13 we will make sure our free product is still the best one.
0:28:14 We wanna make sure, you know,
0:28:16 disincentivize others from entering,
0:28:18 but we want people that always have the option.
0:28:20 We don’t want them to get forced to buy a co-pilot,
0:28:21 for example.
0:28:22 – And then maybe one thing to add to Jeff,
0:28:24 like we monetize enterprises, right?
0:28:27 So we have some of the largest Fortune 100s,
0:28:30 F-thousands, even over 10,000 developers on our product.
0:28:33 And those companies, obviously they want security guarantees,
0:28:34 they want personalization
0:28:36 for many, many repositories that exist.
0:28:37 And they also want support
0:28:40 across all source code management tools.
0:28:44 Less than 10% of Fortune 500 companies are on GitHub cloud.
0:28:45 And that is the competitor that we have,
0:28:46 that is GitHub co-pilot.
0:28:48 And they have committed to making their product
0:28:52 differentially better if you are on GitHub cloud, right?
0:28:55 So we want to take the approach of almost being Switzerland.
0:28:58 We don’t care what programming language you write.
0:29:00 We don’t care what ID is you use.
0:29:03 We don’t care where you store your source code.
0:29:06 And ultimately, we also just don’t really care
0:29:07 what seniority the developer is.
0:29:10 We will provide the maximum amount of leverage there.
0:29:13 Whereas a lot of the larger players in the space
0:29:15 are focused on being tied to another brand.
0:29:17 And the reason why we don’t think that that makes sense is
0:29:20 we think AI is such an up-leveler.
0:29:23 We think it deserves to be in a category of its own.
0:29:26 – You recently raised $65 million
0:29:29 in a round led by Kleiner Perkins.
0:29:32 It valued you at half a billion dollars.
0:29:35 Congratulations.
0:29:37 What is that money going to be used for?
0:29:39 – I think the way we would like to think about it is
0:29:41 we have ways of spending cash,
0:29:42 not only to train models,
0:29:44 but to also make it so that we can build
0:29:46 a better user experience for the end user.
0:29:48 But one of the cool things for us is our product
0:29:50 has such high ROI that we think that there will be
0:29:52 a real payback period on that.
0:29:55 Enterprises and companies will see enough value there
0:29:57 that they will be able to eat the cost
0:29:58 that we will need to spend upfront.
0:29:59 But also on top of that,
0:30:01 we want to spend a lot on making sure
0:30:03 that we can become better partners for our customers.
0:30:05 We’re onboarding some of the world’s largest companies
0:30:08 and we’re onboarding tens of thousands of developers.
0:30:09 That’s going to take a little bit of effort
0:30:11 to make sure that we do that properly.
0:30:13 One company that we’re working with right now
0:30:15 that we have a multi-year engagement with,
0:30:18 they account for 0.15% of all developers in the world,
0:30:20 it’s just that one company, right?
0:30:23 So, I’m a little bit of a different type of founder
0:30:24 in that I do not like the idea
0:30:26 of spending money unnecessarily,
0:30:28 but if it comes down to we are doing it
0:30:29 because we make our customers more successful
0:30:32 and our users more happy, we’ll do it any day.
0:30:35 – How have you guys restrained yourselves
0:30:36 in terms of spending?
0:30:40 Because I mean, yeah, the story, the narrative in AI
0:30:42 has been that it is an arms race.
0:30:45 And the thing that I hear about in the venture industry,
0:30:47 or at least what AI founders are being told,
0:30:50 is just go out and raise a shit ton of money
0:30:53 as much as is even possible.
0:30:56 One, because you just want to develop a war chest.
0:31:00 And two, you want to get the headlines.
0:31:02 You want to be the AI company that’s working
0:31:05 on co-generation, the AI company for finance,
0:31:06 whatever it is.
0:31:09 So I guess sort of two questions for me here.
0:31:12 One, is that accurate to your experience?
0:31:16 And two, how have you been so responsible
0:31:19 in terms of spending while you see all of these headlines
0:31:21 of other companies spending so much money
0:31:23 on talent and training their models?
0:31:26 – I think Varun mentioned earlier that we run very lean.
0:31:28 And the reason we’re able to do that
0:31:31 is we hire people that are generalists or ex-founders
0:31:33 and they’re capable of doing many job roles at once.
0:31:37 So our company size is probably like a little misleading.
0:31:39 It’s probably way more effective,
0:31:41 not just infrastructure, but the headcount also.
0:31:42 – What is the headcount?
0:31:44 – So right now we’ll be almost about 55
0:31:45 at the end of the month, I think.
0:31:47 And then the thing is like the people we hire
0:31:49 are able to just slot into different roles,
0:31:50 almost out of moments notice.
0:31:52 It’s like, oh, we don’t even have a marketing team,
0:31:53 for example.
0:31:55 The product’s growth has been organic,
0:31:57 but we do want to do some marketing experiments
0:31:59 to make sure that we are getting ourselves out there,
0:32:00 just as an example.
0:32:02 And then people, randomly someone will be like,
0:32:04 I have an idea, okay, go do it.
0:32:07 And then we all of a sudden have a Google ad strategy.
0:32:09 All of a sudden we have a bunch of blog posts.
0:32:12 We’re on podcasts like with you and Elson.
0:32:14 But I think that my point is,
0:32:16 part of the function of not spending the money
0:32:19 is just being very, I guess, practical
0:32:21 of where the money goes and running lean.
0:32:23 And I think when there is a moment that says like,
0:32:25 hey, we need to train a much bigger model
0:32:26 and we need to spend this much money,
0:32:28 we’re all for it, actually.
0:32:31 We actually are very conscious about what the ROI is
0:32:32 of everything we do.
0:32:35 – Yeah, how do you maintain that culture of leanness
0:32:38 and what would be your recommendation to other companies
0:32:41 that are maybe not as big as you, but trying to be?
0:32:44 – This is quite probably the hardest problem
0:32:46 that we’re trying to solve right now.
0:32:49 ‘Cause we wanna hire people that are very good,
0:32:52 very technical, maybe they’re generalists,
0:32:54 like I said earlier, but it’s very hard
0:32:55 to hire those people.
0:32:57 So actually, this is probably one of the things
0:32:59 we focus on in the next month
0:33:01 is what is our recruiting strategy?
0:33:03 How do we hire the best people?
0:33:05 Maybe part of that is getting Kodium’s brand name
0:33:06 much more aware.
0:33:09 Maybe it’s like a big push of user adoption.
0:33:11 Maybe we’re just gonna have to be scrappy
0:33:14 and be very creative of how we hire people.
0:33:15 For example, I don’t know if other companies
0:33:18 are just like pinging every ex-founder on LinkedIn,
0:33:19 but we are, right?
0:33:23 So we are trying to scale with creative means.
0:33:25 – One other thing is like as a company,
0:33:28 I think culture is, we have some cultural principles
0:33:30 and we run lean as one of them,
0:33:33 but who would wanna say you don’t run lean?
0:33:36 So I think, how do you actually live that out?
0:33:38 We are a five days a week in-person company,
0:33:40 so we don’t do remote work.
0:33:42 We don’t really do hybrid work either.
0:33:45 So people see what it’s like to work at the company
0:33:49 and until very recently, our CTO was ordering snacks.
0:33:51 And that’s not to say that’s a great use of his time.
0:33:53 It’s more just that no one is high enough
0:33:56 to not do some work to test a hypothesis.
0:33:58 And we don’t hire specialists at the company
0:34:01 until generalists outgrow that role.
0:34:03 And I’ll give you another example of this.
0:34:06 When we ran that GPU virtualization company,
0:34:07 even though we were making money,
0:34:09 we never hired a sales rep.
0:34:11 And that’s not because I don’t believe in enterprise selling.
0:34:13 No, we have a great VP of sales now at the company
0:34:15 and I think we might have in terms of talent density,
0:34:18 one of the strongest enterprise sales teams in the world,
0:34:20 actually, but why didn’t we hire someone?
0:34:23 I just didn’t believe that if we added one new person,
0:34:25 I would be setting them up for success
0:34:28 because the reality is if I could not get $1 of additional
0:34:33 sales, I cannot expect someone else to get $10.
0:34:35 So this is one of those things where we have a mentality
0:34:38 of we try to do it ourselves and then we try to eliminate
0:34:39 ourselves from the role.
0:34:41 We give away our Legos.
0:34:43 We let someone else take that over that understands
0:34:46 the role much more, but we don’t do things prematurely.
0:34:50 And I think there’s a tendency across people that the idea
0:34:52 of building a scalable organization is really valuable.
0:34:54 And I do see that that you do want to build
0:34:57 a scalable organization, but sometimes people get too excited
0:35:00 about this notion of org building or fundraising rather
0:35:03 than the idea of having customers, having users.
0:35:05 Because ultimately, people that join our company
0:35:07 don’t care about how much money we raised,
0:35:09 as long as we will survive.
0:35:11 And our customers genuinely don’t care.
0:35:12 Let’s look at it this way, right?
0:35:14 If you look at a company as big as JPMC
0:35:16 that makes hundreds of billions of dollars,
0:35:20 to them, does it make sense if we raised $100 or $200 million?
0:35:21 It all looks like peanuts to them.
0:35:23 It’s all like 10 basis points of the amount of revenue
0:35:25 that they make a year.
0:35:26 So to them, what they really care about
0:35:28 or companies of this size is,
0:35:30 are we the best partner for them?
0:35:32 Are we the best product to them?
0:35:34 And as long as we’re laser focused on that,
0:35:36 we should do whatever it takes to build that up.
0:35:39 We’ll be right back.
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0:36:17 Visit bcaa.com/marketplace and avoid some random guy.
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0:37:22 – We’re back with first time founders.
0:37:24 Sort of a more personal question.
0:37:29 I mean, you started this company in 2021
0:37:31 sort of just as the AI hype was bubbling up
0:37:35 and you now find yourself at the epicenter
0:37:37 of the hardest industry
0:37:39 and you are one of the hardest companies
0:37:41 in the hardest industry.
0:37:43 Just a personal question for both of you.
0:37:44 How does that feel?
0:37:47 Like what has it been like getting used to
0:37:50 being the guy in AI?
0:37:52 – I told this to the company.
0:37:56 I tell everyone just get ready to get destroyed.
0:37:59 Assume that something very bad is going to happen always.
0:38:02 And this is where us having gone through that pivot
0:38:03 is very critical.
0:38:05 Things are going very well for us as a company.
0:38:07 A lot of the reason why we haven’t spent a lot of money
0:38:09 is now we make money, which is a unique property
0:38:12 about a lot of companies apparently in this space
0:38:13 where most companies talk about vision
0:38:15 rather than actually building a product that people use.
0:38:18 But I just, I tell everyone get ready
0:38:20 for something really bad to happen.
0:38:22 And this is why it’s like very important
0:38:26 that we hire people that are truly in it for the long run.
0:38:28 And I tell people this when they joined the company,
0:38:30 I think we could be a company
0:38:32 that’s worth over a hundred billion dollars.
0:38:33 I think we can.
0:38:35 And that’s largely because the total adjustable market
0:38:37 of what we’re building
0:38:38 and the amount of impact that this can have
0:38:41 given how important technology is could be massive.
0:38:44 But also a series of bad decisions that we make
0:38:46 could completely kill the company.
0:38:48 And that will happen very fast.
0:38:49 And I think this is where us building
0:38:51 a very truth seeking company.
0:38:53 And that actually is very hard
0:38:55 because people want to believe
0:38:56 that what they’re doing is correct.
0:38:59 And they want to embrace psychological safety.
0:39:01 And what I tell people is, hey,
0:39:04 if you feel something is wrong,
0:39:07 lean into what you think is wrong and tell everyone.
0:39:10 Tell everyone, because we should not have pockets of people
0:39:12 that want to report up the chain
0:39:14 and tell their manager or tell me,
0:39:16 we have a very flat company or tell me,
0:39:17 things are going fine.
0:39:19 I would much rather hear everything is on fire
0:39:21 and have paranoid people at the company
0:39:23 than people who are just happily going to work.
0:39:25 And this is why I think startups
0:39:27 are so much harder than big companies.
0:39:29 It’s actually not that, you know,
0:39:31 you’re taking a massive risk on the monetary side.
0:39:34 You still can make a six figure salary, right?
0:39:36 These are not people that are living hand to mouth.
0:39:40 But the really hard part is the lack of psychological safety.
0:39:42 We make a bunch of people at the company
0:39:43 make a series of bad decisions
0:39:46 and the entire thing can go to zero.
0:39:48 Whereas if you’re at Google,
0:39:49 you have very little accountability.
0:39:51 If your team doesn’t perform well,
0:39:55 Google makes so much money that you are a rounding error.
0:39:57 You will be shuffled to some other part of the company.
0:39:59 You never really need to deal with the impact
0:40:02 of your decisions and consequences of your decisions.
0:40:04 And that’s why it’s always a little bit of a funny statement
0:40:06 when someone at a big company is like,
0:40:08 I work at a startup at a big company.
0:40:10 No, no you don’t.
0:40:14 Imagine the idea of you potentially losing your job
0:40:16 every quarter or every month.
0:40:17 Exactly.
0:40:19 One thing that the way I think about it
0:40:21 is radical transparency.
0:40:23 And we have a lot of conversations within our company
0:40:26 of let’s be super transparent about everything.
0:40:28 And even in my personal life,
0:40:30 I’m like, I’m just gonna be like totally upfront.
0:40:35 That’s the cleanest, most kind of hygienic way to operate.
0:40:41 Do you ever feel that there could be too much truth?
0:40:44 Do you feel that there’s a possibility
0:40:46 that if you’re encouraging everyone
0:40:48 to tell the truth, tell the truth, be transparent,
0:40:52 tell me everything, that they’ll kind of go overboard?
0:40:54 I think this is the hardest part about a startup.
0:40:57 The two things that I say is a startup is really hard
0:41:00 because you need to be both irrationally optimistic.
0:41:02 Because if you’re not optimistic,
0:41:04 the answer is always Microsoft is gonna beat you, right?
0:41:04 Right.
0:41:06 It’s the biggest company of all time.
0:41:07 They have the most capital.
0:41:08 They have the most people.
0:41:09 They have the most distribution.
0:41:10 Why does any company win?
0:41:11 But clearly that’s wrong, right?
0:41:12 There are companies that have beat Microsoft
0:41:13 at different areas.
0:41:14 We always say this,
0:41:16 oh, they have the most capital they’re gonna win.
0:41:18 Yes, yes, it’s very easy from my perspective to say that.
0:41:19 Exactly, right?
0:41:22 And then HBS, I try to think about what Harvard Business
0:41:25 School would say 10 years from now for us as a company.
0:41:28 And I tell people this, it’s like, we fail.
0:41:31 And what they write is in a world
0:41:34 in which technology was changing,
0:41:36 Microsoft had all the distribution in the world.
0:41:38 They had this property called GitHub.
0:41:40 It was inevitable that they would win.
0:41:41 And because of that, they won.
0:41:42 They won the entire space.
0:41:45 And all of these startups, it was a fool’s errand.
0:41:46 Why did they even try?
0:41:48 And then the world in which we win,
0:41:50 they were going to write in a world
0:41:54 in which the technology was getting disrupted so materially.
0:41:56 There were a set of companies,
0:41:57 and one of which was Codium,
0:42:00 that had such a technological advantage
0:42:02 that there was no way a slow-moving gorilla
0:42:03 like Microsoft could even compete.
0:42:05 So what I think is very hard–
0:42:06 – Very hard, yeah.
0:42:07 – Yeah, exactly.
0:42:08 They will write whatever the future looks like
0:42:10 and the history will be written by the victor.
0:42:12 And no one will know exactly
0:42:14 what the pages of the book look like.
0:42:18 And I think the hardest part about a startup is,
0:42:19 you do need to be irrationally optimistic
0:42:21 to believe that you can win.
0:42:24 Because by default, if you don’t, you will definitely lose.
0:42:26 But then also uncompromisingly realistic,
0:42:29 which is that sometimes, actually,
0:42:33 there’s no point continuing in a particular direction.
0:42:36 This is where I think it comes down to what you just said,
0:42:38 which is that if you were too truth-seeking
0:42:41 and everyone is paranoid all the time,
0:42:43 it could lead to paralysis.
0:42:45 And I think there’s a fine line there.
0:42:48 There’s a fine line where one time we lost a deal,
0:42:49 and we actually, every day for dinner,
0:42:52 talked about it for two weeks in a row for multiple hours.
0:42:54 We talked about the implications as a company.
0:42:55 And that was very useful.
0:42:58 But if we extended that out to an entire year,
0:43:00 we would not go anywhere.
0:43:01 – Yeah.
0:43:02 – So you’re totally right.
0:43:03 There’s a level here.
0:43:05 But what I do feel most companies do
0:43:08 is probably err on the side of not being truth-seeking enough.
0:43:11 They become too complacent with what they’re doing.
0:43:14 And I think the thing to really think about,
0:43:15 and this is not true at a big company,
0:43:17 which is why you really need to think about it
0:43:19 at a startup is you do not win an award
0:43:21 for doing the wrong thing for longer.
0:43:24 So the sooner you can rip the band-aid off,
0:43:25 the better your company will be.
0:43:27 You will be way happier that you did it.
0:43:30 It is going to be incredibly painful for a week,
0:43:31 but just do it.
0:43:32 – I love that.
0:43:34 You guys have been generous with your time,
0:43:36 so we’ll begin to wrap up here.
0:43:39 Jeff, I’ll ask you this question.
0:43:41 What do you think has been the greatest challenge
0:43:44 that this company has faced in the past couple of years?
0:43:48 – I think the pace at which things switch
0:43:50 is really challenging.
0:43:53 We relied on some technology features
0:43:54 to be the selling point.
0:43:56 And then our competitors would come out
0:43:58 and it’s like the same thing all of a sudden.
0:44:01 And every time that there’s a news release
0:44:02 for one of our competitors,
0:44:04 we immediately go into like a code red
0:44:06 and go into a competence room.
0:44:08 Reverse engineer what they’re doing.
0:44:09 And this is constant.
0:44:12 This is like every month this is happening.
0:44:13 The question is like, will this last forever?
0:44:16 Like will we just always be panicking?
0:44:18 And the question that answers probably yes, right?
0:44:21 – I think for people listening to this podcast,
0:44:26 you too are the closest thing to AI experts as we’ve had.
0:44:30 You’re kind of on the front lines of this.
0:44:33 What would be your advice to anyone
0:44:35 who is working in the AI industry
0:44:37 or who wants to work in the AI industry?
0:44:39 And I think that doesn’t just have to be founders
0:44:43 but engineers, product managers,
0:44:44 business operators, et cetera.
0:44:46 What’s the most important thing
0:44:49 that they should understand about AI right now?
0:44:51 – There’s an interesting property about AI right now
0:44:54 in that it is actually imperfect.
0:44:56 You know, when you use the products,
0:44:58 sometimes says the wrong thing.
0:45:00 And despite that, it is actually very useful
0:45:01 in some domains.
0:45:03 That’s not like anything in the past.
0:45:05 When you used the internet
0:45:08 and you ordered something off Amazon in 2002,
0:45:10 it’s not like they would ship you something incorrectly
0:45:12 or maybe they would do that, but that’s not,
0:45:13 there was no expectation going in.
0:45:16 You would buy one book and you would get a different one.
0:45:18 And somehow that is still fine right now,
0:45:20 which is a cool part of the technology,
0:45:22 which is that it actually gets perfect.
0:45:24 It’s going to usher in a brand new set
0:45:26 of applications as well.
0:45:29 But I think the key thing to really think about
0:45:31 is not to think about, go back from a demo
0:45:33 and try to build that today.
0:45:36 So think about what products can you build today
0:45:38 that are actually imperfect,
0:45:41 but still can generate a lot of value.
0:45:43 And that is a lot harder than you would think
0:45:46 because in a lot of domains, if you are imperfect,
0:45:49 like let’s say you’re reviewing a legal document
0:45:51 and it actually completely reviews the document,
0:45:53 but 10% of the time it’s wrong.
0:45:55 You can’t give that to an end customer.
0:45:58 So actually thinking about the trade-offs of
0:46:02 how good does the quality need to be to ship your product?
0:46:04 How fast does the experience need to be?
0:46:06 In a world in which the quality is not perfect,
0:46:07 it better be fast.
0:46:09 There’s no world in which I’m going to wait 24 hours
0:46:12 for something, and the quality is imperfect, right?
0:46:16 And then if the quality is imperfect and it is fast,
0:46:18 how quickly can I correct it?
0:46:20 And these are all important factors of a product.
0:46:22 If you don’t hit the sweet spot here,
0:46:24 you will have a product that’s a cool demo,
0:46:26 but no one will ever use it.
0:46:28 I think this is the most important thing
0:46:29 to really think about.
0:46:32 Adding AI to just any field that exists
0:46:34 doesn’t just suddenly make the product usable.
0:46:37 It needs to be a product that is useful in its own right.
0:46:40 – I think if you give away a product for free
0:46:42 and everybody keeps using it
0:46:45 and a lot of people keep trying to get it,
0:46:47 then you know there’s something of value
0:46:48 and there’s product market fit.
0:46:50 And I think if you look at a lot of these AI tools
0:46:52 and AI demos, maybe they’re not realizing that.
0:46:53 Maybe they’re just building something
0:46:56 that is a cool demo or it’s like a really,
0:46:58 it pushes the limits of the technology,
0:46:59 but it’s not actually building something
0:47:02 that people want or will find value from.
0:47:03 I think that’s maybe our biggest message
0:47:05 to other founders or other people
0:47:06 that are building products in the area.
0:47:08 It’s just think like if I gave this away for free,
0:47:11 is everybody gonna wanna use it and keep using it?
0:47:13 I think that’s maybe something people miss.
0:47:15 – Do you think maybe that’s the model that,
0:47:17 I mean, I was gonna say software founders,
0:47:19 but maybe all founders that you should just start
0:47:22 with giving the product out for free
0:47:24 and see where things take you from there.
0:47:26 – It worked really well for chat GBT, right?
0:47:27 – Yeah, yeah, exactly.
0:47:28 – And it worked well for you, yeah.
0:47:30 – That’s actually an interesting principle
0:47:31 that Jeff just said.
0:47:33 Obviously, in some scenarios,
0:47:35 the reason why chat GBT could do that and open it,
0:47:37 it could do that is they own the infrastructure.
0:47:38 And if another company did that,
0:47:39 they would have gone bankrupt.
0:47:43 So you do need advantages in particular places
0:47:44 to be able to do that, but at the very least,
0:47:47 if you did burn money and you gave it away for free,
0:47:49 if no one runs to use the product,
0:47:51 you’re probably in a world of trouble.
0:47:55 – That’s a great place to end.
0:47:57 Varun Mohan is the founder and CEO of Codium.
0:48:00 Jeff Wang is the company’s head of business.
0:48:01 Guys, thank you for joining us.
0:48:02 That was awesome.
0:48:03 – Yeah, thanks for having us.
0:48:04 – Thanks for having us.
0:48:09 – Our producer is Claire Miller,
0:48:11 our associate producer is Allison Weiss,
0:48:13 and our engineer is Benjamin Spencer.
0:48:15 Jason Stavis and Catherine Dillon
0:48:17 are our executive producers.
0:48:18 Thank you for listening to First Time Founders
0:48:20 from the Vox Media Podcast Network.
0:48:22 Tune in tomorrow for ProfG Markets.
0:48:25 (upbeat music)
0:48:50 – Support for the show comes from Into the Mix,
0:48:53 a Ben and Jerry’s podcast about joy and justice
0:48:55 produced with Vox Creative.
0:48:57 Into the Mix is back for a new season
0:48:59 and welcomes you in with four new stories
0:49:02 that take listeners beyond the headlines
0:49:04 and into the lives of ordinary people
0:49:07 fighting for justice in their communities.
0:49:09 Starting with Ainez Bordeaux,
0:49:10 an activist and St. Louis native
0:49:13 who fought to shut down the workhouse,
0:49:15 a notorious pretrial detention center
0:49:18 that she says functioned like a debtor’s prison.
0:49:21 Subscribe to Into the Mix, a Ben and Jerry’s podcast
0:49:23 to listen to the first episode
0:49:25 of this special three-part series out now.
0:49:35 [BLANK_AUDIO]

0:00:01 (upbeat music)
0:00:04 Support for the show comes from Into the Mix,
0:00:07 a Ben and Jerry’s podcast about joy and justice
0:00:09 produced with Vox Creative.
0:00:12 Ainez Bordeaux is a self-described hellraiser,
0:00:14 and she became an activist
0:00:16 after being caught up in the criminal legal system
0:00:19 when she couldn’t afford her bond.
0:00:20 And without a trial,
0:00:23 Ainez was sent to a St. Louis detention facility
0:00:25 known as the Workhouse,
0:00:28 notorious for its poor living conditions.
0:00:31 Here how she and other advocates fought to shut it down
0:00:33 and won on the first episode
0:00:36 of this special three-part series out now.
0:00:39 Subscribe to Into the Mix, a Ben and Jerry’s podcast.
0:00:42 – It’s almost time.
0:00:45 Verizon Small Business Days are coming
0:00:47 from August 5th to the 11th.
0:00:50 Small and mid-sized businesses can get a tech check
0:00:53 and advice on how to get the most out of Verizon Business
0:00:55 with guidance on the best solutions
0:00:57 for your specific needs.
0:00:59 Meet with their experts, get one-on-one advice,
0:01:02 three tech checks, and other special offers.
0:01:06 Give your business the VIP treatment it deserves.
0:01:10 Call 1-800-483-4428,
0:01:13 or go to Verizon.com/smallbusiness.
0:01:17 That’s 1-800-483-4428,
0:01:21 or go to Verizon.com/smallbusiness.
0:01:23 – Episode 310.
0:01:26 Three-1-0-0 could belong in Los Angeles County in 1910,
0:01:28 the first public radio broadcast was conducted
0:01:30 from the Metropolitan Opera House in New York City.
0:01:33 Having sex with me is like the opera.
0:01:35 No one has any idea what the fuck is going on
0:01:39 and at the end, there’s a fat guy sweating and yelling.
0:01:44 ♪ Go, go, go ♪
0:01:46 (upbeat music)
0:01:54 Welcome to the 310th episode of the Prop G pod.
0:01:57 By the way, our first joke, actually in 1910,
0:01:59 the Boy Scouts of America was established.
0:02:00 That’s just too easy.
0:02:04 There’s just too many jokes about Scout leader Patrick,
0:02:07 and the bottom line is I was a Boy Scout,
0:02:09 and it was one of the nicest experiences I had as a kid.
0:02:12 The Boy Scouts is taking an immense amount of shit.
0:02:13 It is a wonderful organization,
0:02:15 or I should say it was a wonderful organization for me.
0:02:17 I was raised by a single mother,
0:02:19 and every Wednesday night, she would drop me off
0:02:22 at, I think, it was a junior high school in Culver City.
0:02:23 I was 42.
0:02:24 I was a wee below.
0:02:27 I was a Boy Scout, and then there’s a transition period.
0:02:29 It’s like puberty scouts where you’re a wee below
0:02:30 and you wear a different scarf.
0:02:33 And true story, I used to wear my Boy Scout uniform
0:02:34 to school, including in junior high,
0:02:37 which was just such a big hit
0:02:39 with the ladies and the cool crowd.
0:02:42 It really sort of established my social currency
0:02:44 showing up in my Boy Scout uniform,
0:02:46 but they were really good people.
0:02:48 The crew, if you will, everyone needs to find their crew.
0:02:51 And Boy Scouts for me was a group of kids
0:02:55 who maybe weren’t the coolest, so to speak.
0:02:56 Maybe weren’t the most social.
0:02:58 Maybe weren’t the most athletic,
0:03:00 but wanted to find their own crew.
0:03:03 We used to go camping once a month outside of LA County.
0:03:07 I gave them an appreciation for nature, leadership.
0:03:10 The Scout leaders there were incredibly generous
0:03:11 and thoughtful and nice.
0:03:15 And we used to have to do things like plan out your backpack.
0:03:16 And I used to do that with my mom.
0:03:20 And then at the end of the weekend of camping,
0:03:22 we would go through, we’d make these lines
0:03:25 and make sure that there was absolutely no sign of us
0:03:27 that we had been at that campsite.
0:03:30 And we used to study for and take tests for our mare bed.
0:03:31 It’s fire safety and not tying.
0:03:35 By the way, both those things have come in real handy for me.
0:03:37 I had a joke lined up, as you can imagine,
0:03:38 incredibly crude and inappropriate.
0:03:40 And then I thought about just how wonderful
0:03:41 the Boy Scouts were to me.
0:03:45 Anyways, so again, welcome to the 310th episode.
0:03:47 In today’s episode, we speak with Matthew Ball,
0:03:50 the CEO of Apilion, a startup advisor
0:03:53 and the former head of strategy for Amazon Studios.
0:03:54 Matthew has sort of, not sort of,
0:03:56 Matthew’s developed a following
0:03:59 just ’cause he’s got such a big fucking brain about tech.
0:04:01 And he speaks in sort of this,
0:04:04 almost like you’re asking chat GPT a question,
0:04:07 except it comes back not with an anodyne answer,
0:04:09 but with a really thoughtful nuanced answer.
0:04:11 He reminds me a little bit of Josh Wolf
0:04:13 ’cause Josh Wolf has one of those brains
0:04:16 that’s just like, I’m on a 286 Intel
0:04:19 and he’s on a Pentium or a GPU.
0:04:20 And they have different styles,
0:04:22 but they’re both these incredibly bright people
0:04:24 who have this incredible range around technology.
0:04:27 Anyways, I had not heard of Matthew
0:04:28 and then I interviewed him
0:04:29 and I immediately went on YouTube and found out
0:04:31 this is gonna be a resource for me
0:04:33 around any question I have around technology.
0:04:37 Okay, before we get to that, let’s bring all of this back
0:04:39 to our favorite subject, me.
0:04:41 I am an Aspen and I absolutely love it here.
0:04:42 I used to come here in the winter,
0:04:44 now we only come in the summers.
0:04:46 My strategy is the following.
0:04:49 I’m pretty much taking not all, but most of my money
0:04:52 and I’m buying these beautiful places around the world
0:04:55 where I hope my sons will just find irresistible
0:04:57 and they’ll come spend a lot of time with me.
0:05:00 In addition, I’m going after a 0.1% strategy.
0:05:01 I think it’s terrible and I’ll fight it,
0:05:03 but I think it’s going to happen.
0:05:05 I think income inequality is only gonna get worse
0:05:06 around the world.
0:05:08 And what’s interesting about people I find it interesting
0:05:10 is that the poor and the middle class
0:05:12 are much more interesting in the sense
0:05:13 that they’re much more heterogeneous.
0:05:15 If you look at their apparel they wear,
0:05:18 if you look at their culture, their food,
0:05:19 it’s pretty local.
0:05:24 So the middle class and Laurentian people in France
0:05:29 dress French, eat French food, vacation in French places.
0:05:32 The very wealthy or the wealthy are incredibly homogenous.
0:05:34 They all party in St. Barthes, they all wear Hermès
0:05:37 and they all send their kids to American universities.
0:05:40 There’s definitely sort of an elite lifestyle
0:05:41 that has been globalized
0:05:43 and there’s two real global consumers.
0:05:47 There’s the wealthy person who buys the same products
0:05:50 and has the same experiences and then there’s teenagers.
0:05:51 That’s also a global cohort.
0:05:56 They listen to Taylor Swift and where Nike,
0:06:00 actually they’re wearing Adidas or Adidas recently
0:06:04 or Hoka or on, Nike’s really shit the bed lately.
0:06:05 But those are the two cohorts
0:06:09 that have emerged globally until about 20 years ago.
0:06:13 Another cohort emerged globally and that is the tech buyer.
0:06:15 That is the MIS or the head of operations
0:06:17 typically are the same person who went to the same schools
0:06:18 and buy the same products.
0:06:20 So what do we have here?
0:06:22 We have the emergence of global brands
0:06:24 that typically are in one of three categories,
0:06:29 technology, Microsoft and NVIDIA are global brands.
0:06:32 Brands that target teens, see above Adidas
0:06:33 or even the North face.
0:06:36 And then brands that target the very wealthy,
0:06:39 almond hotels or Chanel.
0:06:41 Anyways, fascinating, total right turn
0:06:43 from what the script is here.
0:06:45 And my producer is just sort of sitting there
0:06:47 shaking your head like, what the fuck is he doing now?
0:06:50 Anyways, I also saw last weekend,
0:06:52 and I’m super excited about this,
0:06:54 got tickets, took my kids and their friends
0:06:57 to see Deadpool and Wolverine.
0:06:59 I think it’s called Deadpool and Wolverine anyways.
0:07:02 And it amassed $205 million in domestic ticket sales
0:07:03 during its opening weekend.
0:07:06 The most money this year and a historic record
0:07:08 for an R rated film.
0:07:09 Wow, didn’t know that.
0:07:10 I loved it by the way.
0:07:12 I absolutely loved the one-liners.
0:07:14 I think Ryan Reynolds is incredibly talented.
0:07:16 Actually, so is Hugh Jackman.
0:07:17 They’re both crazy fucking talented.
0:07:21 Hugh Jackman can sing like no one’s business.
0:07:23 What was that movie, “The Great Entertainer”
0:07:26 where he played Barnum or Bailey or whatever it was
0:07:27 and then died, was in that movie?
0:07:29 God, “Watchings and Dies.”
0:07:30 Zach Braff, who knew Zach Braff could sing?
0:07:31 Did you know that?
0:07:34 I did not know that Zach Braff could sing.
0:07:35 That was an outstanding movie.
0:07:37 I think musicals are especially impressive.
0:07:39 That’s gotta be really hard to pull off.
0:07:41 Anyways, absolutely loved “Deadpool.”
0:07:42 But I’m struck a little bit.
0:07:45 One, Hollywood will pretend that the movie’s business
0:07:46 is back, it’s not.
0:07:49 It’s still off 20% from its pre-pandemic levels.
0:07:52 And I think the majority of the interesting content now
0:07:54 is on the medium or the small screen,
0:07:56 specifically your television or your phone.
0:07:57 Why is that?
0:08:00 Because the type of money that’s required
0:08:03 to make a feature motion picture is so extraordinary now
0:08:06 that everybody just goes to these 10-pull franchises.
0:08:07 I mean, I think this is the third
0:08:09 or the fourth “Deadpool” movie.
0:08:11 And there’s not as much what I call
0:08:13 license for creative content.
0:08:15 And I even think about, what other franchises
0:08:17 that have been launched in the last few years
0:08:19 that’ll get three or four sequels might be frozen?
0:08:20 I don’t know, there’s probably something else.
0:08:24 But my son at camp just went and saw Minions 4
0:08:25 or Minions 5.
0:08:28 I mean, there just isn’t, there isn’t a ton
0:08:30 of originality, whereas when I tune in,
0:08:31 I’m about to watch “Presumed Innocent.”
0:08:33 Everyone says, “That’s totally binge-worthy.”
0:08:36 But I do think you’re gonna continue to see
0:08:39 a leaking of influence and return on investment.
0:08:40 And one of my pieces of advice,
0:08:43 reductive generalizations in terms of advising young people
0:08:46 and on a career media is the return on your invested capital
0:08:48 is gonna be inversely correlated
0:08:49 to the size of the screen.
0:08:51 And if you wanna be on the screen,
0:08:52 everyone’s like, “Well, I’ll start doing
0:08:55 cute little videos, but then hopefully I’ll get a TV show.
0:08:57 And then who knows, I’ll hit the big time
0:08:58 with a big, and be on the big screen
0:09:01 so I can see my face really, really fucking big.”
0:09:04 So there’s a certain prestige or vanity aspect
0:09:07 or a psycho, if you will, or a psychic return.
0:09:09 What is really interesting or I find interesting
0:09:13 is I get 20 to 30 emails a day asking for advice.
0:09:15 And it’s wonderful that people would reach out to me.
0:09:17 It’s also a little bit frustrating
0:09:19 ’cause I think that this is a really thoughtful email
0:09:20 from someone who’s very sincere
0:09:21 and I can never get to all of them.
0:09:23 By the way, if you’re out there, I apologize.
0:09:25 I just can’t get to all of them.
0:09:27 But I’m increasingly over the last two years
0:09:28 getting a lot of emails from people
0:09:31 in the media industry asking what do they do next?
0:09:34 That they say I’ve been very critical of the rider’s strike.
0:09:37 I thought that was literally like the head up your ass
0:09:38 shit for brains.
0:09:42 I don’t understand strategy negotiation of the ages.
0:09:44 And I’ve said all along that this industry
0:09:45 attracts way too much human capital.
0:09:47 There’s 180,000 people in Sagaftra.
0:09:49 There should probably be 10,000.
0:09:52 And as evidence of that, 83% of them didn’t qualify
0:09:53 for health insurance last year
0:09:55 ’cause they made less than $23,000.
0:09:56 I wanna crush your dreams.
0:09:59 If you wanna go into a vanity industry, fine.
0:10:01 You wanna go into modeling, fashion, sports.
0:10:03 You want your own jewelry design level.
0:10:04 You wanna be a fashion designer.
0:10:05 I mean, seriously, you know
0:10:08 if you’re trying to go into a vanity industry, that’s fine.
0:10:12 But you have to set up guideposts for yourself or metrics
0:10:15 that if you’re not in the top 10% pretty quickly,
0:10:18 you should get out the quote unquote top 10%.
0:10:20 If you’re in the 90th percentile of actors,
0:10:22 that means you’re an Uber driver.
0:10:24 If you’re in the 99th percentile,
0:10:26 that means you make a living, not even a great living.
0:10:29 I know some actors who you would all know.
0:10:31 You think, wow, they’ve been in series.
0:10:33 They make a good living, not a great living.
0:10:35 Unless you’re in the 0.1%,
0:10:37 it is a very difficult way to make a living.
0:10:40 Whereas most industries and non-romance industries,
0:10:42 just being the top half and you can make a decent living.
0:10:45 And if you’re in the top 10% much less the top 1%,
0:10:47 boy, oh boy, are you going to kill it?
0:10:50 But anyways, back to Deadpool and Wolverine.
0:10:52 What else is popping off the screen?
0:10:53 What are we watching?
0:10:55 The Olympics, who would have thunk it?
0:10:57 I didn’t even know the Olympics were on.
0:10:59 And my feeds on my platforms
0:11:03 are all these amazing people doing amazing things.
0:11:04 By the way, by the way,
0:11:06 speaking of opening ceremonies at the Olympics,
0:11:09 I love Celine Dion.
0:11:12 I did not know this.
0:11:12 I did not know this.
0:11:15 I see her visage or image and I think,
0:11:19 oh God, lame Canadian, lame Canadian coming my way.
0:11:21 And then when they’re about 15 seconds, I’m thinking,
0:11:22 wow, she’s pretty good.
0:11:25 And then within 30 seconds, I’m fucking crying.
0:11:27 (upbeat music)
0:11:30 Wow, is she talented?
0:11:35 And by the way, France, Parisians, oh my gosh.
0:11:38 Generally speaking, a group of very disagreeable people.
0:11:40 I used to go to France a lot for business.
0:11:42 My company L2 focused on luxury brands.
0:11:44 The home of luxury is France.
0:11:44 I used to go to Paris.
0:11:47 No joke, have a series of meetings with everyone
0:11:50 from LVMH to Chanel to Clarence.
0:11:53 Just a ton of brands, right?
0:11:56 Dior, Chloe, we would spend a week and have jam-pack.
0:11:58 And almost every meeting I’d come out of,
0:12:00 I think, Jesus Christ, that was a shitty meeting.
0:12:03 Basically, French people who would cross their arms,
0:12:05 we would say something and they would argue with us
0:12:06 and then speak to each other in French
0:12:07 and there’s disdainful tones.
0:12:09 Like, who is this stupid fucking American?
0:12:11 And we’d be on the way to the airport.
0:12:12 And I would say to my colleague,
0:12:14 I always went with the same people,
0:12:17 usually who were covering Europe without reason or luxury.
0:12:19 I’m like, God, that was just the worst meeting I’ve ever had.
0:12:20 And then I’m not exaggerating,
0:12:22 we’d get a call from the client saying,
0:12:24 that was amazing, we wanna see you again.
0:12:26 They just have a different mentality.
0:12:28 Also, people will say that Parisians
0:12:29 are different than the French,
0:12:32 but I have come to appreciate one thing
0:12:34 or more than one thing about France.
0:12:36 There is something in the DNA of the French,
0:12:37 there’s something in the water
0:12:40 where they have an easier time
0:12:42 crafting the most beautiful things in the world.
0:12:44 If you just look at the panache, the style,
0:12:47 the touch points of the Olympics and the opening ceremonies,
0:12:49 I think, wow, I wish I was there.
0:12:50 I actually got invited to the Olympics
0:12:52 and I said to my kids, do you wanna go to the Olympics?
0:12:54 ‘Cause I thought, gotta take your kids to the Olympics
0:12:55 at least once.
0:12:57 And they said, no, we have no interest.
0:12:58 And it struck me that the World Cup
0:13:00 has become so dominant the last four years
0:13:03 and slowly but surely the Olympics
0:13:05 have actually decreased in popularity.
0:13:07 Although from a business standpoint,
0:13:09 it seems to be enjoying a little bit of a bump.
0:13:12 An April MBCU had already sold more than 1.2 billion
0:13:14 in advertising for this year’s games.
0:13:16 That’s a record for Olympic ad spending.
0:13:18 A lot of this should be adjusted for inflation
0:13:20 ’cause I think a lot of these numbers are a little bit,
0:13:21 I don’t know exactly.
0:13:23 A lot of this doesn’t feel Apple’s Apple’s.
0:13:24 And it was back to the Olympics.
0:13:25 The other thing that’s really struck me about the Olympics
0:13:28 is you can get is the difference between streaming
0:13:31 and broadcast or linear.
0:13:34 Watching the Olympics I find on MBC
0:13:36 is actually a quite frustrating experience
0:13:38 because they say, and now we’re headed to three meter diving.
0:13:41 You’re like, well, I’m not sure I’m into three meter diving.
0:13:43 Whereas if you watch it on Peacock,
0:13:45 you can actually sign up and pick a sport.
0:13:47 So if you just really wanna see surfing all day long,
0:13:48 you can watch it.
0:13:50 Speaking of streaming, it is beginning
0:13:53 to kind of consolidate, if you will.
0:13:55 So there’s this great chart from Antenna
0:13:58 looking at committed versus curious.
0:14:00 And that is people who are just trying it
0:14:02 versus the people who are committed customers.
0:14:04 And it’s interesting, you would expect Netflix
0:14:07 to be at the top and their ratio is 2/3 to 1/3.
0:14:11 So 2/3 of people are committed, 1/3 are curious.
0:14:13 I think curious is a polite way of saying people
0:14:15 who might churn out, who sign up to download
0:14:17 all of Ted Lasso and then churn out.
0:14:18 Next, and this really shocked me,
0:14:22 was Hulu at a ratio of 35 to 65.
0:14:24 So if you wanna think about a market capitalization
0:14:27 or a dominant player, Netflix is two to one,
0:14:31 basically hardcore customers who are likely renew,
0:14:33 versus the next player, which is one to two,
0:14:35 which has got a dramatically impact margins
0:14:38 because Hulu has to reinvent its customer base
0:14:39 every goddamn 18 months.
0:14:44 Paramount Plus comes in about the same level at 36.64.
0:14:49 Disney is 40, 60, some more committed.
0:14:51 Peacock is at 35.
0:14:52 Max is at 28.
0:14:53 That really shocked me.
0:14:55 I always think of Max and specifically HBO
0:14:57 as having me able to tap into the zeitgeist.
0:15:01 And Apple TV Plus, who I think has spent 20 billion so far
0:15:03 on programming for Apple,
0:15:05 TV Plus for their effort here is 32.68.
0:15:07 I wonder if they kind of regret it.
0:15:11 I wonder if Apple TV Plus is not nearly the kind of,
0:15:15 I don’t know, train wreck that the mixed reality headset is.
0:15:16 But I wonder if they had to do it again
0:15:20 if they would spend $20 billion original scripted drama.
0:15:22 Anyways, the market continues to consolidate.
0:15:23 I am loving the Olympics,
0:15:26 but also what I found is I’m spending most of my time
0:15:28 watching it on TikTok.
0:15:30 But I love the idea of amateur athletes.
0:15:33 Things have happened since the Olympics
0:15:34 over the last 20 years or 30 years
0:15:37 and make me wonder if why it has not done as well.
0:15:39 Is it because professional athletes are involved?
0:15:40 I don’t know.
0:15:42 Is it because they’ve brought in things like,
0:15:43 I don’t know, mountain biking,
0:15:45 which I think is important to establish
0:15:49 a younger customer base, but it does lose the purity.
0:15:51 But more than anything in our editor-in-chief,
0:15:53 point of the south Jason Stavros,
0:15:55 I think the key to a luxury brand going back to France
0:15:57 and luxury brand is the following.
0:15:58 It’s scarcity.
0:16:01 It’s the illusion that you are part of a tribe
0:16:02 that says something about you.
0:16:03 It’s self-expressive benefit.
0:16:06 Actually, there are really two things that luxury offers.
0:16:07 Only two things.
0:16:09 The first is it makes you feel closer to God.
0:16:10 Why?
0:16:13 Because the majority of these very artisanal handcrafted
0:16:16 illusive products with a domain of religious institutions.
0:16:18 The religious elites figured out a way
0:16:19 that they needed to manipulate the masses
0:16:22 and make them feel like we are closer to God
0:16:24 and you need to do what we tell you to do
0:16:26 and also to provide them with comfort.
0:16:27 So what we’re gonna do is we’re gonna invite you
0:16:30 to these places of worship, these temples, these mosques,
0:16:32 these churches, these chapels,
0:16:33 and we’re gonna fill them
0:16:34 with the most beautiful things in the world.
0:16:38 We’re gonna engage the most incredible, sophisticated,
0:16:41 impressive artisans to build frescoes on the ceiling.
0:16:42 We’re gonna have incredible music.
0:16:45 We’re gonna have the most gorgeous pageantry
0:16:47 and candles and smells.
0:16:48 And you’re gonna get the sense
0:16:50 that there’s a decent chance of God hangs out here.
0:16:51 And we’ve been doing this for hundreds,
0:16:52 if not thousands of years.
0:16:55 And as a result, we associate fine things,
0:16:57 artisanal things with being closer to God.
0:17:00 And when you see the mesh on a boutique of a net-a-bag
0:17:01 or the slip on the back of a 9/11,
0:17:02 you feel closer to God.
0:17:03 It stills you.
0:17:06 It’s a very rewarding experience to be in the company
0:17:07 of this type of artisanship.
0:17:09 In addition, the second thing
0:17:11 is that it increases the likelihood
0:17:13 that you’re gonna procreate.
0:17:14 Why?
0:17:15 Because it says something about you.
0:17:17 Ergonomically impossible menolablonics
0:17:19 make your legs seem longer.
0:17:22 This makes you seem more elegant, more feminine.
0:17:25 Having a Panerai watch or a Porsche means your kids
0:17:27 or the kids that you or mate and you decide to have
0:17:29 are more likely to survive
0:17:30 than someone who is wearing a swatch watch
0:17:32 and driving a Hyundai.
0:17:35 So it’s the ultimate expressive, self-expressive benefit.
0:17:38 And by the way, this has been the best performing asset class
0:17:41 over the last 30 or 40 years, whether it’s modern art
0:17:42 or whether it’s a luxury business itself.
0:17:45 On a risk-adjusted basis, luxury has performed better
0:17:47 than even, yes, you guessed it, tech.
0:17:48 And it’s produced, I think,
0:17:50 the second or third most billionaires.
0:17:52 This is an unbelievable business.
0:17:54 And it has huge motes by virtue of the fact
0:17:55 that it has heritage.
0:17:58 You cannot recreate Chanel right now.
0:17:59 You just can’t.
0:18:01 You can’t have that story.
0:18:03 You can’t have that heritage.
0:18:06 And if you’re able to establish that illusion of scarcity
0:18:07 and artificially constrict supply,
0:18:10 I go into the Panerai store here in Aspen,
0:18:12 see above, Douchebag, Prilish Douchebag,
0:18:13 but they always say to me,
0:18:16 oh, that’s a limited run or we don’t have that one.
0:18:18 These are not difficult items to manufacture,
0:18:20 but they create the illusion of scarcity.
0:18:21 Who’s best at this?
0:18:22 Who’s best at this?
0:18:25 Hermes, who get this as double the market cap of Nike.
0:18:27 Jesus Christ, that blows my mind.
0:18:30 Anyways, the illusion of scarcity.
0:18:32 Also the learning here, personally,
0:18:35 there is the illusion of scarcity that you want to create.
0:18:37 You want to have boundaries.
0:18:40 In my brand, I absolutely say no to 95%.
0:18:43 Now granted, I’m in a position of privilege,
0:18:46 but creating a sense that you’re, I don’t know,
0:18:47 your brand or your person, if you will,
0:18:49 has a touch of exclusivity to it
0:18:52 once you’ve established some domain expertise
0:18:53 and some credibility.
0:18:56 I think it’s key to creating margin, if you will.
0:18:58 So it’s the same way with a services company.
0:18:59 Let me translate this to B2B.
0:19:00 What are you doing B2B?
0:19:02 In my opinion, what’s the best way to market?
0:19:04 You put out thought leadership.
0:19:05 They get some awareness.
0:19:07 With L2, we put out a ranking
0:19:09 and you create a reverse inquiry model, if you can.
0:19:12 That way it changes the entire tone of the conversation,
0:19:13 right?
0:19:15 And you try and create an illusion of scarcity
0:19:16 that you’re doing them a favor
0:19:17 by them signing up as membership.
0:19:20 The entire membership model and hospitality right now,
0:19:22 whether it’s Maison Estelle or Soho House
0:19:25 or Casa Chiprione, that entire thing has just exploded,
0:19:28 although I think it’s probably saturated at this point,
0:19:29 is all based on the illusion of scarcity.
0:19:31 Gee, can you recommend me?
0:19:34 So I can pay $7,000 a year to then go buy drinks
0:19:36 at what is essentially a nice restaurant.
0:19:38 This again is the master of illusion of scarcity.
0:19:41 This is what has become a branding.
0:19:44 The ultimate, ultimate rejectionist exclusionary
0:19:46 artisanal brand is U.S. higher education.
0:19:48 To a certain extent, the U.S. has become a luxury brand
0:19:50 because of our fucked up immigration policies.
0:19:51 But you get the point.
0:19:54 Scarcity, luxury brands equals margin.
0:19:55 And let’s bring it home.
0:19:57 Some wonderful moments from the Olympics.
0:19:58 Simone Viles, Jesus Christ.
0:20:00 That shit’s just inspiring.
0:20:02 She gets a lot of attention, so I’ll move on.
0:20:04 Two best friends from America,
0:20:06 I think they’re called Cookin’ and Bacon,
0:20:09 or best friends who’ve been going to the Olympics
0:20:12 three or four times or one just made her like fourth trial,
0:20:13 finally made the Olympics won a medal.
0:20:14 That was a nice moment.
0:20:16 The Philippines won its first gold medal.
0:20:18 And finally, finally, there was a gymnast from North Korea
0:20:19 who won a silver medal in the Olympics.
0:20:23 She didn’t win gold, but her execution was flawless.
0:20:24 Get it?
0:20:27 Anyways, go six rings, go Olympics.
0:20:32 We’ll be right back for our conversation with Matthew Ball.
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0:24:00 (upbeat music)
0:24:09 Welcome back, here’s our conversation with Matthew Ball,
0:24:12 the CEO of Opelion and author of the revised book,
0:24:16 The Metaverse, Building the Spatial Internet.
0:24:17 Matthew, where does this podcast find you?
0:24:19 – In Midtown Manhattan.
0:24:20 – So let’s bust right into it.
0:24:23 You’re one of the go-to experts on the metaverse,
0:24:26 a topic that we just haven’t paid much attention to
0:24:28 since some of the hype faded.
0:24:29 Can you give us a state of play?
0:24:32 Where does the metaverse and spatial computing stand today
0:24:34 in 2024?
0:24:36 – So overall, those in the industry talk
0:24:38 about these three different peaks for the theme.
0:24:41 The first happened in the late 80s, the early 90s,
0:24:43 that’s where you had really all of the terms
0:24:44 that we talk about today.
0:24:48 Spatial computing came onto the scene roughly ’91, ’92,
0:24:52 the metaverse in ’92, you had the advent of virtual reality,
0:24:56 artificial reality, certainly cyberspace, the matrix,
0:24:58 they all came out of that early period.
0:25:01 And that was sparked by the emergence
0:25:05 of graphical user interfaces of the internet at large,
0:25:08 of 3D computing, simulation and video games.
0:25:12 And they all attempted to capture these terms,
0:25:14 what the future might look like.
0:25:15 And we very quickly realized
0:25:17 that those technologies were premature.
0:25:21 15 years later, we had this second burst of activity.
0:25:24 Second life ends up on the cover of Time Magazine,
0:25:26 and there’s a belief that we’re going to see
0:25:28 the metaverse finally come to fruition.
0:25:30 And then the following two to three years
0:25:32 after that peak for second life,
0:25:35 you have the starting of nearly all of the modern efforts
0:25:38 to build wearable glasses and goggles,
0:25:41 magic leap, you have the Snapchat acquisition
0:25:43 of Virgins Labs, you have HoloLens,
0:25:45 you have Oculus VR.
0:25:49 And then we kind of encountered this 10 to 15 year stagnation
0:25:51 in the hardware side.
0:25:53 And then in 21 and 22, we had this other burst
0:25:56 where there was general consensus that finally,
0:25:59 the technologies had matured,
0:26:01 the internet infrastructure, computing technologies,
0:26:03 even some of the wearables that we imagined
0:26:05 we might one day wear,
0:26:08 that they had all matured to the point in which finally,
0:26:12 this 30 year old term, roughly 70 year old conquest
0:26:15 and 100 year old idea was ready for prime time.
0:26:18 And then it got hoisted onto the front page of the news
0:26:19 by Mark Zuckerberg.
0:26:23 So we had this long progress of technology and progress
0:26:27 suddenly lead us to this belief that it was imminently here,
0:26:29 if not changing the world already.
0:26:32 And so where are we in 2024?
0:26:36 I think the focus on that hype, the name,
0:26:39 and the relative un-success or general lack of success
0:26:41 of meta suite of metaverse products
0:26:43 has led to a belief that the idea
0:26:47 has come and gone, been Julie rejected by consumers,
0:26:50 but actually the progress of all of the constituent parts
0:26:54 has continued, not just with more child
0:26:57 and leisure oriented activities, Roblox and Fortnite,
0:27:00 but indeed had mounted displays at large,
0:27:02 general computing simulation,
0:27:03 and the creation of virtual worlds
0:27:05 using artificial intelligence.
0:27:09 But now at scrutiny has shifted elsewhere.
0:27:12 – So give us the tax work definition of the metaverse.
0:27:14 What is the metaverse?
0:27:15 – The best and easiest way to understand it
0:27:20 is a 3D shared and live version of the internet.
0:27:23 The internet as we have it today is best understood
0:27:27 as a dozen or two common protocols and a suite of standards
0:27:29 that enable the consistent, comprehensive,
0:27:34 and coherent exchange of data across 110,000 autonomous
0:27:37 and independent networks,
0:27:38 hundreds of millions of different servers,
0:27:40 billions of different devices,
0:27:42 supporting about 5 million applications,
0:27:46 billions of websites, all exchanging information.
0:27:48 And yet what that internet lacks
0:27:50 is really three fundamental elements.
0:27:53 First is the ability to transmit again,
0:27:54 coherently, comprehensively,
0:27:58 and consistently 3D information for it to be shared.
0:28:02 What you and I are doing right now, live Zoom,
0:28:04 is essentially one of the few things we ever do
0:28:06 on the internet that’s truly shared.
0:28:07 And essentially everything that we do on the internet
0:28:09 is not actually live.
0:28:11 When you and I go to theNewYorkTimes.com,
0:28:14 not only are we disconnected from the New York Times server,
0:28:16 but even when the New York Times updates,
0:28:18 we’re still looking at the old version of it.
0:28:20 And so the metaverse is best understood
0:28:24 as a shared, live, and 3D augmentation
0:28:27 to the existing internet as we experience it today.
0:28:29 – So technology is generally speaking,
0:28:33 everyone was happy to kind of pronounce crypto dead
0:28:36 about a year ago, and it’s come roaring back.
0:28:39 Voice was super hyped, it’s come down a bit,
0:28:40 it might come back.
0:28:44 This does feel as if it’s been, I wouldn’t say forgotten,
0:28:45 but it feels like there probably
0:28:47 is still some opportunity there.
0:28:48 Where do you see the greatest opportunity?
0:28:51 What industries do you think will register
0:28:53 the greatest leverage or success
0:28:56 around metaverse applications?
0:28:57 – Well, I think to start,
0:29:00 one of the unfortunate consequences of Meta’s name change
0:29:04 was the strong association with these technologies
0:29:06 and their concepts with virtual reality
0:29:09 or social workrooms that we would use to engage
0:29:12 in lieu of Zoom call or physical meeting.
0:29:14 Most of the pioneers in the category
0:29:16 strongly separate the two.
0:29:18 Some don’t even believe that virtual reality
0:29:19 has much of a future.
0:29:21 Neil Stevenson, who coined the term,
0:29:23 talks about it being central to his idea
0:29:24 of the future in the ’80s,
0:29:27 but he has essentially disavowed the requirement
0:29:30 of virtual reality or augmented reality from the metaverse.
0:29:33 So when you go to some of the larger businesses
0:29:37 in the category, whether that’s of Epic Games or Nvidia,
0:29:39 they have no requirement nor expectation
0:29:41 of a near-term solution for this hardware.
0:29:43 But if you’re gonna talk about
0:29:45 where we’re seeing these imminent opportunities
0:29:48 that are perhaps not covered extensively,
0:29:50 I think there’s two great examples.
0:29:55 The first is in the use of actually these headsets
0:29:57 in more industrial use cases.
0:29:59 Four years ago, the United States performed
0:30:00 its first ever live patient surgery
0:30:02 using a mixed reality headset.
0:30:04 The first was spinal fusion.
0:30:07 The second was the removal of a cancerous tumor
0:30:09 on a spinal column.
0:30:10 The United States is now performing
0:30:14 between four to 600 surgeries a year using these devices.
0:30:17 And the results, they’ll preliminary, right?
0:30:20 We haven’t seen a decade of patient outcomes,
0:30:23 do show that the surgeries are typically performed faster.
0:30:25 They’re more accurate.
0:30:27 They are, in some instances, much cheaper.
0:30:30 And most of the surgeons that perform this talk about it
0:30:33 in the same way that they did GPS in the early ’90s,
0:30:35 are revolution in how they perform
0:30:38 a relatively complex and yet routine process.
0:30:41 And yet one in which we’re still not able to do nearly
0:30:43 what we can with the technology today
0:30:46 that we imagined a few decades ago.
0:30:49 – It does feel like a healthcare is an obvious example.
0:30:52 And so talk to me a little bit about gaming.
0:30:53 I’m an investor.
0:30:55 I’ve made one of my largest investments
0:30:58 about three years ago in epic games.
0:31:01 It’s not much of this is around syntax or nomenclature
0:31:04 ’cause I think of, I think of Fortnite as the metaverse,
0:31:06 to a certain extent, I don’t,
0:31:08 I’m trying to figure out where gaming ends
0:31:10 and the metaverse begins.
0:31:14 And give me a sense for, now speaking as a,
0:31:16 advise me as a shareholder of epic,
0:31:19 how the metaverse will impact gaming
0:31:22 and who you see as sort of the winners in that space.
0:31:24 – So you’re right that a lot of this is a debate
0:31:25 over terminology.
0:31:28 In fact, even Spatial, which Apple has embraced,
0:31:30 has its origins, as I mentioned, in the early ’90s,
0:31:32 but it was never contemplated to actually connect
0:31:33 to the physical world.
0:31:36 It was just a description of a 3D space in a computer.
0:31:38 And so all of these terms, the metaverse included,
0:31:41 have kind of been perverted, reapplied in scenarios
0:31:43 it was originally not intended for
0:31:45 and become a part of corporate propaganda, right?
0:31:49 We’re Spatial, not metaverse, we’re metaverse, not Spatial.
0:31:51 I interviewed Tim Sweeney,
0:31:53 the founder and CEO of Epic recently,
0:31:55 and he likened the metaverse to a stock price.
0:31:57 He said, when something cool comes out, it goes up.
0:31:59 When something lame comes out, it goes down.
0:32:01 And more often than not over the last three years,
0:32:03 lame things have come out.
0:32:04 And certainly when you take a look
0:32:07 at those leading use cases, Fortnite is one such example.
0:32:10 They at least don’t capture the pop culture imagination,
0:32:13 the way that it did three to four years ago.
0:32:15 But it’s a good way of understanding the proliferation
0:32:17 of these technologies and trends.
0:32:20 Roblox, as an example, it has an advantage over Epic,
0:32:21 as you know, as being on mobile,
0:32:24 has about 375 million monthly active users.
0:32:28 That’s more than the entire active user base
0:32:30 of the Switch platform, the Xbox platform,
0:32:32 and the PlayStation platform.
0:32:35 Nearly all of its users are under 18.
0:32:36 And so you’re seeing something that,
0:32:39 despite being concentrated at a younger demo,
0:32:42 is nevertheless larger than another category
0:32:45 that spans all age demographics.
0:32:47 The other interesting thing about that category is,
0:32:50 of course, those younger users have no interest
0:32:54 in the capital M, M word, its trends, its significance.
0:32:58 It’s just a form of habit and how they socialize.
0:33:00 But when you talk about the companies such as Epic,
0:33:03 when people talk about the internet,
0:33:04 the internet is in some regard,
0:33:08 not unlike the constitution in the States,
0:33:12 in the sense that it was never meant to say static,
0:33:16 and yet it hasn’t really been updated for several decades.
0:33:18 The consensus is that the standards
0:33:22 which would support a shared live 3D internet
0:33:24 have to come from private business.
0:33:26 And therefore you need other private businesses
0:33:30 to willingly adopt standards and technologies
0:33:33 another entity owns and operates.
0:33:36 And therefore you need to trust Epic looks like
0:33:39 through its strength of existing platform,
0:33:42 its economic engine, and then its stewardship
0:33:45 by a more philosophical controlling shareholder
0:33:47 looks like one of the most likely entities
0:33:48 to pioneer those changes.
0:33:52 – There’s a chapter, I guess it’s an updated chapter
0:33:54 in your book that explores the century-long history
0:33:57 of AI and AI philosophy.
0:33:59 And also the six ways this technology controls
0:34:01 the metaverse, walk us through those.
0:34:03 – So I think when you take a look at many
0:34:05 of the technological impediments to building
0:34:07 what many have imagined, whether that’s a headset
0:34:10 or just a digital twin, a persistent simulation
0:34:13 of San Francisco as Tesla is now seeking to build,
0:34:17 a lot of the time we are facing literal laws
0:34:18 of physics constraints.
0:34:21 That’s actually why the Vision Pro is so expensive
0:34:26 and yet so unrewarding for many users.
0:34:27 And so we’re now starting to see these different ways
0:34:31 in which our dreams are being made real through AI.
0:34:34 Number one is that when you take a look at an HMD
0:34:36 head mounted display like the Vision Pro,
0:34:39 the best way to talk about what you can’t do
0:34:41 is to compare it to the device many of us have.
0:34:44 A Xbox Series X, a PlayStation 5,
0:34:46 those are 10 pound devices.
0:34:49 They’re the size of two or three different shoe boxes.
0:34:51 That’s despite the fact they don’t need a battery.
0:34:54 That’s despite the fact they don’t need a screen.
0:34:57 And yet they don’t need a mobile connection.
0:35:00 We don’t worry about the heat that they generate too much
0:35:02 because they’re feet and feet away from you.
0:35:06 They don’t need cameras to understand the world around you.
0:35:09 And they don’t need to take safety precautions, right?
0:35:11 To understand that there’s tax returns on the table
0:35:13 or that you’re about to stumble over an object.
0:35:18 Shrinking a 10 pound relatively underpowered device
0:35:19 that doesn’t need two of the heaviest things
0:35:22 that can have a screen and a battery
0:35:24 into something portable and wearable.
0:35:26 We haven’t found the science
0:35:30 that would allow us to overcome those challenges.
0:35:31 And yet through artificial intelligence,
0:35:35 we are actually starting to kind of co-opt that system, right?
0:35:37 We’re starting to come up with smarter ways
0:35:40 to have the system predict what you’re going to do
0:35:42 so that it doesn’t have to process it.
0:35:44 That processing requires battery, for example.
0:35:48 It requires tax on a limited GPU.
0:35:50 In fact, when you’re wearing a headset,
0:35:52 one of the biggest challenges
0:35:55 of just power reservation or preservation
0:35:58 is when you see the Vision Pro,
0:36:00 you’re actually looking at a reproduction of the world
0:36:04 around you from three to four different external cameras
0:36:06 that have to be stitched together.
0:36:07 But those cameras are actually captured
0:36:09 about an inch and a half in front of your eyes
0:36:12 and on an obtuse angle.
0:36:13 It’s artificial intelligence
0:36:16 that is bringing all of those images together,
0:36:19 shifting it back onto your eyes
0:36:22 and then making it seem like it’s coming from your eyes.
0:36:24 So that’s just one such example
0:36:28 of literally if we want to have lightweight portable devices
0:36:31 that are comfortable, powerful, able to do what we want,
0:36:34 it’s actually not a question of lithium ion advances,
0:36:35 not entirely.
0:36:38 It’s not about how many nanometers we have
0:36:39 for how many different transistors.
0:36:41 A lot of the time it’s how much smarter our systems
0:36:44 can be with scarce information.
0:36:45 The two bigger elements
0:36:48 are just about actually producing the world.
0:36:49 There was a lot of scrutiny,
0:36:51 and I know you’ve covered this around Galaxy’s Edge
0:36:55 at Disneyland and as expensive as that was,
0:36:57 it’s shocking to most people to realize
0:37:00 that the cost of making a virtual Galaxy’s Edge
0:37:02 is actually not necessarily less
0:37:06 than it was to produce a physical theme park.
0:37:09 And if you actually want to staff that with individuals
0:37:12 who can bring to life Naboo or Navarro
0:37:16 or the planet of Hoth, it becomes more expensive still.
0:37:17 And so with artificial intelligence,
0:37:19 we’re starting to see this reality
0:37:23 that if you wanted to produce the Disneyland of your dreams,
0:37:26 have it populated as you might imagine
0:37:28 and also allow you to do essentially everything
0:37:28 that you would want to do
0:37:31 and by extension can’t do in a theme park.
0:37:32 We’re talking about billions of dollars
0:37:36 in annual investment that is starting to shrink down
0:37:37 into the hundreds of millions
0:37:40 and where the cost curve might bring it even lower still.
0:37:42 – Something that I don’t think gets enough attention
0:37:47 is the application or applications of the metaverse and AI
0:37:51 in terms of simulation or its use on the battlefield.
0:37:53 And you have a chapter on this,
0:37:56 give a sense for where you think this intersects
0:37:58 with military strategy.
0:38:00 – So the best way to do this is to talk about
0:38:03 one of those terms that has kind of been forgotten
0:38:05 and even Microsoft moved away from,
0:38:06 which is digital twins.
0:38:10 Digital twins a few years ago became so common
0:38:13 because every company that felt obliged
0:38:14 to have a quote unquote metaverse strategy
0:38:16 just said, let’s make a digital twin.
0:38:18 And they very quickly realized
0:38:20 that sure it had some signaling value.
0:38:22 They got their employees to feel good about it.
0:38:23 They tested some new technology,
0:38:25 but they realized they didn’t really know
0:38:27 what they were going to do with it.
0:38:29 And one of the problems, and this comes back to AI is,
0:38:33 there are really five different levels of digital twins
0:38:34 that we talk about in the industry.
0:38:37 And the advanced ones require artificial intelligence.
0:38:39 And most of them were level one.
0:38:40 Level one is a digital twin.
0:38:42 It’s like a physical miniature.
0:38:44 It’s a model, a diorama.
0:38:45 Teams feel good about them.
0:38:48 Executives like having a diorama of their corporate campus,
0:38:50 but it reflects a statement.
0:38:52 It’s a point in time.
0:38:54 And it doesn’t have much applied value.
0:38:58 Level two digital twins take that original digital twin
0:39:00 and they make them real time using IoT
0:39:01 and other simulated systems.
0:39:04 You’re now having a live reproduction of that environment.
0:39:07 Level three are predictive digital twins.
0:39:09 They can tell you what’s likely to happen.
0:39:11 Level four are prescriptive.
0:39:14 They provide actual recommendations to the individuals.
0:39:18 And then level five, we talk about autonomous digital twins.
0:39:21 Those that can produce prescriptions and predictions
0:39:25 at such a high velocity that a human agent
0:39:28 can’t actually effectuate those changes effectively.
0:39:30 So that’s level one to five.
0:39:33 And by three, four, five, we start to get actual utility,
0:39:36 but we require high levels of accuracy,
0:39:39 sophistication, and velocity from AI systems.
0:39:41 We have two other axes.
0:39:43 One is the volume of data.
0:39:44 Obviously you can have a digital twin
0:39:47 that captures individual vehicles or fleets,
0:39:48 and that’s a very big distinction.
0:39:51 And then we have the amount of other network
0:39:52 digital twins you have.
0:39:54 Are we talking about a factory plant
0:39:56 or a McDonald’s in Manhattan?
0:39:59 Or are we talking about one plugging into the entire corpus
0:40:02 of a simulated environment of a Manhattan?
0:40:03 So once we understand this scope,
0:40:06 you start to talk about how these technologies
0:40:07 are being used today,
0:40:10 in particular in battlefield testing,
0:40:13 where you’re saying we have all of these systems
0:40:15 that can today do a decent job
0:40:17 of predicting and prescribing activities
0:40:19 for a relatively stable system
0:40:21 with relatively low cost of failure.
0:40:24 And by that I mean a production facility.
0:40:26 Pretty stable in what it’s going to do.
0:40:28 And the consequence of a line pause
0:40:31 is real for General Motors or Tesla,
0:40:33 but it’s not life-threatening.
0:40:35 There’s still a belief that we don’t have the level
0:40:36 of prediction or prescription,
0:40:40 let alone autonomy, to bring that into an active battlefield.
0:40:42 And what we are however seeing,
0:40:44 in the UK as a pioneer here,
0:40:47 is the use of this in active training,
0:40:52 in better simulation of what may or may not go right or wrong.
0:40:54 And in general, this connects to your earlier point,
0:40:57 which is the technologies that are almost always used
0:41:01 to actually test this, especially with human agents,
0:41:03 is the Unreal Engine out of Epic.
0:41:07 – You also had an edition of the book
0:41:08 where you’re talking about big techs fight
0:41:10 over undersea cable infrastructure
0:41:13 and Starlink versus Amazon’s project.
0:41:15 Kuiper, I’d love just,
0:41:17 you have such a big brain around,
0:41:18 I don’t even think he’s the metaverse guy,
0:41:22 I think he’s more like kind of like the cutting edge tech guy.
0:41:24 I look at Starlink and I see something
0:41:27 that has the width of the Amazon
0:41:28 and that this thing could be potentially
0:41:31 one of the most valuable companies in the world.
0:41:32 And some of this is just,
0:41:35 I’ve had such an incredible experience with a product
0:41:37 when it’s offered on planes.
0:41:39 Talk to me about Starlink,
0:41:44 if you agree that it’s got that sort of potential
0:41:47 and product excellence and moats
0:41:48 and who are the competitors
0:41:51 and where are they relative to Starlink?
0:41:52 – So I love this question
0:41:54 and it actually gets to the earlier point
0:41:56 around updating or supplementing
0:41:59 the internet protocol suite as we know it.
0:42:03 There was a largely under covered fight
0:42:05 going on between the big giants
0:42:07 to actually own the submarine cable infrastructure
0:42:09 of the internet.
0:42:12 Meta, as you called out in 2018,
0:42:16 they owned 0% of what we call the internet backbone
0:42:19 or the oceanic backbone.
0:42:22 By the end of this year, the free internet foundation
0:42:27 estimates that Meta will own 12 to 13%
0:42:31 or own, co-own, or be the capacity owner, right?
0:42:33 Essentially a leasehold like a wireless tower
0:42:35 of all submarine cable infrastructure,
0:42:40 about 170,000 kilometers of cable.
0:42:43 They will own the cables that connect 47
0:42:47 to 55 different African continental countries.
0:42:49 And it’s believed that out of the 12 to 13%
0:42:53 they own worldwide, 40 to 50%
0:42:57 of all of the African continental internet infrastructure.
0:42:59 That has led to additional escalation
0:43:01 from Google and Amazon companies
0:43:04 that were much farther ahead in purchasing
0:43:06 and owning these fiber optic connections.
0:43:08 When you talk about Starlink,
0:43:10 you’re again talking about another system
0:43:13 that we don’t have a traditional competition
0:43:17 or comparison for, but is now roughly 70%
0:43:21 of all low earth satellites that we have globally,
0:43:23 including all of those of China and NASA,
0:43:27 where they’re expected to put up another 12,000
0:43:30 in the next 12 months, up to 30 to 40,000 more.
0:43:33 And the cost and velocity advantages
0:43:38 they have over any other competitor is astonishing.
0:43:40 And so I’ll bring that back, which is you say,
0:43:42 okay, so what’s the challenge
0:43:44 with updating the internet protocol suite?
0:43:45 The challenge with the internet protocol suite
0:43:46 is it’s decentralized.
0:43:49 No one mandates a protocol’s adoption.
0:43:50 We’ve proposed many.
0:43:54 And so one classic example is the internet protocol suite
0:43:56 does not differentiate between any packet of data.
0:43:59 It doesn’t know what’s real time you and I talking
0:44:03 and it doesn’t know what’s an email or a Netflix stream.
0:44:06 And so you and I may have our call dumped
0:44:08 because there’s congestion in the network
0:44:10 and a network hop just says,
0:44:12 well, we’ve got to pick between these two.
0:44:15 So let’s dump Scott and Matt to let the email through,
0:44:19 severing the connection, not just delaying ours.
0:44:21 To get everyone to agree,
0:44:25 you need 110,000 networks,
0:44:27 millions and millions of different routers
0:44:29 to all say, let’s accept it.
0:44:32 And there’s no simple, let’s classify this versus that
0:44:35 because all data has different demand needs.
0:44:36 And so when you start to talk about the scope
0:44:39 of Meta’s ownership of cable infrastructure
0:44:43 or Starlink, you start to have a private party
0:44:48 that can forcibly or effectively produce new protocols
0:44:50 that reshape how the internet manages
0:44:51 and discriminates traffic.
0:44:53 I’m not talking about net neutrality.
0:44:56 I just mean like the fundamental understanding
0:44:59 of data and routing to start to change
0:45:02 the way the most profound technology
0:45:05 the last 50 years operates in a way that
0:45:08 at least in some regions of the world
0:45:11 and potentially globally through Starlink,
0:45:14 nothing else can even propose an alternative.
0:45:16 And that’s where you get into something truly remarkable.
0:45:19 And that’s a moat that would perhaps take
0:45:23 50 years to even try to chip away at.
0:45:25 – So you’re bullish on Starlink.
0:45:28 – I think it’s remarkably hard not to be.
0:45:30 – Yeah, that’s my sense too.
0:45:32 What other, okay, so Starlink, what other companies
0:45:34 when you look at how all the moons are converging
0:45:36 or not converging here, what other companies
0:45:39 are you especially optimistic about?
0:45:42 – So before I shifted over to interactivity
0:45:45 and gaming at large, I was primarily focused
0:45:47 on Hollywood and media.
0:45:50 I was the head of strategy for Amazon Studios,
0:45:52 which ran at the time, essentially what users
0:45:54 think of to be as prime video.
0:45:56 And I’m very familiar with your perspective
0:45:57 on generative AI.
0:46:00 Look, I think that technology is remarkable.
0:46:04 And I think you can kind of tell the general fears
0:46:08 around that technology by how the criticisms have changed.
0:46:10 A year and a half ago, it was the number of digits
0:46:11 that were on a finger.
0:46:15 Right now, most of the criticisms that I see are that
0:46:18 it looks great, yes, but it doesn’t have the nuance
0:46:21 of a human expression, of a human performance.
0:46:22 They say it’s plugey, right?
0:46:26 The lighting is bad, it’s not dramatic.
0:46:31 And just the fact that we have gone from visual deformities
0:46:37 to a normative sense of like taste is extraordinary.
0:46:42 And of course, the funny thing about that is
0:46:45 to even believe that the visual presentation
0:46:48 or the performance is flawed is to assume
0:46:51 that there’s a uniform human response to those things
0:46:52 when we know that there isn’t.
0:46:55 Which is to say, an expert may say that doesn’t land
0:46:58 the way that cinema or Scorsese would,
0:47:01 but that assumes that every viewer would.
0:47:03 The pace in which that technology is improving
0:47:04 is remarkable.
0:47:07 I think the ethics of how a lot of the training data
0:47:10 has been used are often reprehensible
0:47:15 or at worst, willfully ignorant of the ramifications.
0:47:17 But having gone through this fire wave
0:47:20 of virtual production and real-time production,
0:47:23 which we realized was probably 10 to 15 years
0:47:26 ahead of schedule, I think that we are very quickly
0:47:29 coming to that fundamental change point
0:47:32 for how generative AI is used in workflows
0:47:35 for video game, for music, for cinema at large.
0:47:38 And I use cinema deliberately
0:47:40 as opposed to just movies or content.
0:47:43 – So it’s had a strategy for Amazon Studios.
0:47:46 How do you think AI, if you will,
0:47:48 is gonna sort of crawl up to stack a Hollywood?
0:47:52 Is it the existential threat
0:47:55 that the WGA claimed it was and yet got no protections
0:47:56 from it, as far as I can tell?
0:47:59 Or do you think it’s actual?
0:48:03 Or is it a productivity tool that potentially lowers costs
0:48:06 and some media companies adapt, others don’t,
0:48:10 but on the whole, the media ecosystem stays robust
0:48:11 and some there are winners and losers?
0:48:12 Or is it really gonna start,
0:48:15 is it gonna disrupt Hollywood?
0:48:19 Is Hollywood the next Detroit at sort of the feet of AI?
0:48:21 What are your thoughts here?
0:48:23 And if you were still advising Amazon
0:48:26 or traditional studio, where do you think,
0:48:30 how do they best defend or go on offense here and leverage AI?
0:48:31 – Well, we have to keep in mind
0:48:33 that one of the reasons I think that Hollywood
0:48:36 has been more skeptical around generative AI
0:48:39 is the lessons of the last few supposed waves.
0:48:41 When you take a look at Netflix,
0:48:43 Netflix in many ways or streaming video,
0:48:45 democratize video distribution
0:48:47 and it changed the monetization,
0:48:50 but it did nothing to alter the cost structure of production.
0:48:52 It’s one of the reasons why fans decry
0:48:55 the fact that streaming has replicated the cable bundle,
0:48:56 but it’s more expensive.
0:48:58 Well, of course, we haven’t come up
0:49:01 with any real innovations to the production cost.
0:49:03 We produce more expensively than ever before,
0:49:06 in part due to the competitive intensity
0:49:09 brought about by the democratization of distribution.
0:49:11 You go back 15 years earlier, you get to VHS,
0:49:13 a new channel, a new monetization scheme,
0:49:18 but it didn’t again change how we produced.
0:49:21 Digital film and the advent of computer generated imagery
0:49:24 in the early ’90s, in many ways,
0:49:28 was expected to change production and democratize it
0:49:30 by eliminating sound stages,
0:49:34 but the cost of digital cameras at the time,
0:49:37 the cost of CGI, actually elevated budgets
0:49:39 to the point in which anyone who wants to have an epic
0:49:42 or a spectacle, the films that do best in movie theaters,
0:49:45 requires often, not exclusively,
0:49:47 but often hundreds of millions, if not more.
0:49:49 Hollywood is therefore kind of attuned
0:49:52 to this idea of the new disruptive technology,
0:49:54 doesn’t change production,
0:49:57 therefore maintains the merits of project financing,
0:50:02 of distribution slates to diversify risk of sound stages.
0:50:04 And in many ways, the actual cost
0:50:07 of running generative AI systems right now,
0:50:10 plus the importance of distribution
0:50:12 that they’ve spent 15 years trying to build up
0:50:14 through streaming, has led many to believe
0:50:16 that yes, it’s a disruptive force,
0:50:19 it is more likely than not going to affect
0:50:22 below-the-line workers and supporting systems,
0:50:26 but many believe that especially with the law on their side,
0:50:29 that it’s still gonna shake out mostly for them.
0:50:33 I’m skeptical because I think that we have never before seen
0:50:38 an actual massive disruptive force on the production side,
0:50:41 and one that in classic disruption theory,
0:50:45 suggests that many of their existing resources
0:50:49 become at best distractions
0:50:53 and at worst cumbersome cost hurdles for them.
0:50:56 And so this is to say, it’s a little bit difficult
0:50:59 to predict the outcomes, but I do think that everything
0:51:02 that we expected from YouTube that we didn’t get,
0:51:06 which is to say a massive volume of independent creatives
0:51:10 that have never touched nor gone through a traditional pipeline,
0:51:12 and yet are producing content that doesn’t look
0:51:14 like a $300 million Marvel film,
0:51:17 but looks like a 40 or $50 million Marvel film,
0:51:21 only it is more easily updated and edited,
0:51:24 changed, customized, frankly, transplanted,
0:51:27 and re-imported into an immersive environment,
0:51:31 into a storybook form, that’s gonna be really hard to slow.
0:51:34 And crucially, because Hollywood will no longer
0:51:37 own the distribution levers, can’t stymie either.
0:51:42 – The only place I would take exception is that,
0:51:43 I do think on the production side,
0:51:45 there has been a globalization, right?
0:51:47 They’ve brought down some production of the RIs
0:51:51 gone up by producing stuff in South Korea and Spain.
0:51:53 I think Netflix has done a pretty good job with that.
0:51:55 Would you agree with that?
0:51:56 – Depends on how you wanna define that.
0:51:59 Do I think that Netflix has done an outstanding job
0:52:02 in Spain and South Korea, in Australia?
0:52:06 Absolutely, I think investors often overlooked
0:52:08 Netflix’s advantages because they compared it
0:52:11 to HBO domestically, a business that had 50 years
0:52:13 of investment competing against one
0:52:14 that had a few years of investment,
0:52:18 without appreciating that in many foreign territories,
0:52:20 Netflix is HBO, not just to the consumers,
0:52:22 but to talent, to production expertise.
0:52:25 They own sound stages, they pre-booked sound stages
0:52:29 that they financed the construction of for years.
0:52:33 At the same point, there isn’t much evidence
0:52:35 of the routine repeatability, low-loan,
0:52:38 efficient production investment
0:52:40 of those foreign internationals hitting over here.
0:52:43 We have Squid Game, but Squid Game
0:52:45 was now three plus years ago.
0:52:47 We had Money Heist before that,
0:52:49 a title that they didn’t actually produce,
0:52:50 but purchased the license to.
0:52:53 I think that is to say, Scott,
0:52:54 I think that by American standards,
0:52:57 where we’re used to five to $15 million per hour,
0:52:58 Netflix has excelled in diversifying
0:53:00 their international production
0:53:02 to the two to $5 million budget level
0:53:05 when servicing those regional customers.
0:53:07 But I haven’t yet seen so much evidence
0:53:08 that they’ve been able to substitute
0:53:12 the American diet for high-cost scripted shows,
0:53:13 which much lower,
0:53:17 more efficient international scripted shows on balance.
0:53:19 We’ll be right back.
0:53:25 Support for the show comes from Fetch.
0:53:27 I love doing ads for Fetch.
0:53:29 I am a huge dark person, I think you know this,
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0:53:35 We think he’s a dox, and by the way,
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0:53:42 and she’s not gonna do anything,
0:53:45 except maybe rear up her hind quarters against you,
0:53:48 whereas the little one will snap your finger off,
0:53:49 the little cute one.
0:53:50 Anyways, pet parents know better than anyone
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0:53:55 but they also know that it’s only a matter of time
0:53:57 before the unexpected happens.
0:53:58 And the unexpected is also, unfortunately,
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0:55:34 (upbeat music)
0:55:39 – It feels as if we’ve written about this
0:55:41 at the kind of the streaming wars, if you will,
0:55:45 are just this great case study and economics.
0:55:49 Overinvestment because the markets are willing to replace
0:55:52 or say, well, we want growth over profits,
0:55:55 so there’s a massive overinvestment.
0:55:56 And now we’re going through a shakeout.
0:55:59 Cost-cutting and consolidation.
0:56:01 As you look at the landscape here,
0:56:02 of all the different streamers,
0:56:04 who do you think the winners and losers are?
0:56:07 Who are the consolidated oars and the consolidated ease
0:56:10 and any kind of off-market predictions
0:56:13 about what might play out in the next 24 months?
0:56:14 – Well, I think we have to start from the fact
0:56:17 that even as recently as 2020,
0:56:20 it’s remarkable how profitable that category was.
0:56:21 People talk about pay TV,
0:56:23 but I think it’s generally underappreciated
0:56:25 that if you can believe it,
0:56:28 pay TV or network television distribution
0:56:33 was a top-decile EBITDA business in the United States.
0:56:38 The median industry has a roughly 13, 14, 15% EBITDA margin.
0:56:43 Network distribution was around 37 to 40% in 2020.
0:56:48 That compared with renewables, nicotine, and oil and gas.
0:56:49 Why?
0:56:51 Because the amortization that you netted
0:56:53 against your operating income was enormous
0:56:55 because you had to build pipelines.
0:57:00 Any system that said just shifting from a top-decile
0:57:05 to a top-quartile category,
0:57:07 meant that you were gonna lose roughly one-third
0:57:09 of your profit margins,
0:57:11 that you probably had two times the cost structure
0:57:12 that you needed.
0:57:14 And that’s before accounting for the fact
0:57:16 that your two biggest competitors,
0:57:18 non-traditionally, are Amazon and Apple,
0:57:20 which need not a dollar of direct margin,
0:57:23 and you’re competing against a business Netflix
0:57:25 that said we don’t care for 20 years.
0:57:28 There is no way, there has never been,
0:57:31 a way to run away from that system.
0:57:33 And so all of the outcomes
0:57:35 that I think have long been predicted,
0:57:36 seem as inevitable now.
0:57:40 There’s too many players, the cost structures remain too high.
0:57:42 And that’s before you even take into account
0:57:45 the aforementioned generative AI displacement.
0:57:48 There’s nothing the average American still,
0:57:52 in 2024, does with their free time more than watch TV.
0:57:54 And I don’t think that that share of time
0:57:56 is even going to last as a result of video gaming,
0:57:58 social media, and other practices
0:58:01 that we see from the younger generation.
0:58:04 And so we’re going to see more companies go belly up.
0:58:06 We’re going to see more companies merge
0:58:09 and like Paramount and Viacom,
0:58:12 find out that despite their doubled size,
0:58:15 they’re gonna end up half the size they were.
0:58:17 – So take it a step further.
0:58:19 I’ll put this out there.
0:58:23 Time Warner survives, Disney survives, Netflix survives.
0:58:25 Other than that, I feel like all bets are off.
0:58:26 What are your thoughts?
0:58:27 – How do you mean survive?
0:58:31 Like as going concerns or direct to consumer business?
0:58:33 – My sense is they’re all recognizing,
0:58:35 even the deep pockets of Amazon and Apple realize
0:58:38 they don’t have the appetite to make the requisite investments
0:58:41 to be kind of standalone big competitors here.
0:58:43 And everyone’s looking for a dance partner
0:58:45 or to get acquired.
0:58:47 It just feels like the whole,
0:58:49 there just isn’t enough room for all of these players.
0:58:52 And what I’m putting to you is who do you think
0:58:55 it’s acquired sooner rather than later?
0:58:58 Might we see one of them actually get unplugged?
0:59:01 – Well, look, I think it remains very hard
0:59:03 to imagine what the independent future
0:59:05 of Alliance Gate or stars will be,
0:59:07 especially as a separated entity.
0:59:09 They kind of have all of the drawbacks
0:59:11 they had as a combined entity,
0:59:13 plus none of the narrative and none of the ability
0:59:16 to at least tap into two segments of the value chain.
0:59:20 AMC has been looking for a dance partner for 15 years,
0:59:23 clearly overestimated its value over and over
0:59:25 to the point in which there’s no dance partner
0:59:26 to find for them.
0:59:29 But the more important aspect is,
0:59:31 look, if you take a look at WBD,
0:59:34 these days it’s circling less than $7 per share.
0:59:36 It’s a collection of assets
0:59:38 that seem increasingly out of whack.
0:59:40 You have the Turner sports regime
0:59:43 that’s apparently about to lose its NBA assets.
0:59:45 You have CNN, you have HBO,
0:59:48 which as of now is decoupling further still
0:59:50 from the rest of Macs.
0:59:51 I think it’s important to recognize
0:59:55 that under current leadership,
0:59:57 WBD has actually sold off
1:00:00 most of their plausible growth story.
1:00:05 They’ve renewed a deep into 2030s distribution agreement
1:00:06 with Bel-Canada.
1:00:09 They’re apparently renewing their sky distribution deal
1:00:12 in Germany, in Italy, in France.
1:00:14 They’ve renewed a South Korean distribution agreement,
1:00:17 an Australian distribution agreement with Stan,
1:00:18 at the point in which you’re saying
1:00:22 we’re gonna downsize our domestic business in HBO.
1:00:24 We’re going to start licensing all of our content
1:00:27 to Netflix and anyone else who will buy it.
1:00:29 In all of the international territories
1:00:31 that have the highest streaming penetration,
1:00:33 we’re going to retreat and license
1:00:35 for the next decade to come.
1:00:38 And then you’re giving up your most valuable rights
1:00:39 on the Turner side.
1:00:42 CNN has no strategic adjacency
1:00:44 and the stock price has lost 75%
1:00:48 since it debuted only two and a half years ago.
1:00:50 It’s very hard to imagine
1:00:53 that that current structure can endure.
1:00:54 And that’s not even talking
1:00:55 about the video game side of this.
1:00:58 – And Matthew, before we go here,
1:01:00 we have a lot of young people who listen to the pod
1:01:03 and are working hard,
1:01:06 trying to establish currency in a professional marketplace.
1:01:08 And I think anybody that looks at your background
1:01:09 and what you’ve achieved
1:01:11 and the seat you’ve sort of created for yourself.
1:01:15 And I think that is a really cool profession.
1:01:17 Can you give us a little bit of the backstory
1:01:19 about how you got to where you are now
1:01:22 and any advice you might have for young men and women
1:01:27 who are looking to establish what feels, smells
1:01:29 and looks like a really cool, well-compensated career?
1:01:32 – So I’d say two things.
1:01:35 Growing up in the early 90s,
1:01:39 I was a relentless user of these really hard to use systems.
1:01:41 I was a big pirate in the 90s.
1:01:42 I was on IRC chats.
1:01:44 I was using MS-DOS.
1:01:48 The use of those products often provided, I think,
1:01:51 a intuitive understanding of what was around the corner.
1:01:52 Why?
1:01:55 Because often the systems that,
1:01:57 especially Hollywood starts to bring,
1:01:59 feel regressive at the time, right?
1:02:00 I’ll give you an example.
1:02:02 Like TV everywhere is one of the biggest disasters
1:02:04 that Hollywood has ever invested.
1:02:06 Do you remember ultraviolet, Scott?
1:02:07 – Mm-hmm, yeah.
1:02:10 – And it was one of those things where
1:02:13 if you had been a pirate and I don’t endorse piracy,
1:02:15 I’m talking about the products
1:02:17 of using these experimental technologies,
1:02:20 you all of a sudden realized that what you were being asked
1:02:23 to use was a woefully inadequate version
1:02:25 of the already-cluge systems
1:02:27 that you were doing 10, 15 years ago.
1:02:29 And then when that’s put in parallel
1:02:31 with a product like Netflix that, yes,
1:02:32 came from an independent company
1:02:33 that didn’t own its destiny,
1:02:36 that was licensing content that had all of its flaws,
1:02:39 that didn’t have live sports and live news,
1:02:41 it provided me with a much clearer understanding
1:02:44 of this is at minimum a better model
1:02:46 and at maximum a better model
1:02:47 that is competing with companies
1:02:50 that don’t even know what a good model looks like
1:02:52 and are to some extent ignorant
1:02:54 of what consumers are already doing.
1:02:58 And so I do think that using those technologies constantly,
1:02:59 which in the case of crypto
1:03:02 means going through truly terrible systems
1:03:04 and often losing your money as a result of it,
1:03:06 not saying that you should speculatively invest,
1:03:07 there’s no substitute for that.
1:03:09 You cannot learn it by reading blog posts
1:03:11 and going on Twitter.
1:03:14 The second thing is, I would say I’ve done a good job
1:03:18 in my career of constantly switching out of a category
1:03:22 where I believe the big strategic problems have solved
1:03:23 and then focusing on the categories
1:03:26 where you only have hard
1:03:28 and sometimes intractable questions.
1:03:30 In the case of the metaverse or VR,
1:03:32 that means going after a field
1:03:34 that you’re gonna get wrong a lot of the time.
1:03:36 It’s part of the reason why I’ve updated this book,
1:03:39 it’s a 70% remake from only two and a half years ago.
1:03:43 You can’t think of the metaverse the same way in 2024
1:03:44 after the Vision Pro,
1:03:47 after the crypto crash and resurgence
1:03:49 and after the advent of AI.
1:03:53 But if you can be relatively unsentimental
1:03:54 about going for, in my case,
1:03:57 streaming video was really hard in 2013.
1:03:58 You didn’t know who to hire,
1:03:59 you didn’t know the business model.
1:04:03 It was darn hard to get an app on a Samsung TV,
1:04:04 any television.
1:04:06 But by 2017, 2018,
1:04:08 we essentially figured it out,
1:04:09 which is why 2019,
1:04:13 we saw every single service on earth come to market.
1:04:16 I pivoted out to an uncertain category.
1:04:19 And when you have the opportunity to learn,
1:04:20 go to labs,
1:04:23 talk to entrepreneurs on Slack day in and day out
1:04:25 about something no one has figured out yet,
1:04:29 but most people think is about to become significant,
1:04:31 you end up with a multi-year advantage
1:04:33 that you can continue to compound for.
1:04:37 Matthew Ball is a CEO of Apelian,
1:04:38 a diversified holding company
1:04:39 that makes angel investments,
1:04:41 provides advisory services
1:04:43 and produces television, films and video games.
1:04:45 He’s also a venture partner at Makers Fund,
1:04:47 Senior Advisor to KKR,
1:04:48 Senior Advisor to McKinsey and Company
1:04:51 and sits on the board of numerous startups.
1:04:53 The fully revised and updated edition of his book,
1:04:56 “The Metaverse” is out now.
1:04:58 He joins us from Midtown, Manhattan.
1:05:01 Matthew, you’re one of these guys.
1:05:03 You remind me a little bit of Josh Wolf.
1:05:06 I don’t know if you know him from Lux Capital.
1:05:11 But I feel like I’m working with a 286 or a 386 ship
1:05:13 and the way you guys are able to process
1:05:15 and distill information is just,
1:05:18 it’s not only impressive, it’s really inspiring.
1:05:20 Appreciate you sharing our thoughts with our audience
1:05:22 and congratulations on building
1:05:24 such an impressive career for yourself.
1:05:26 – Thank you. It’s very kind.
1:05:28 (upbeat music)
1:05:31 (upbeat music)
1:05:37 – Algebra of Happiness.
1:05:40 I was invited to speak at something called
1:05:42 White Dudes for Harris,
1:05:45 which was a Zoom call that Garner get this,
1:05:48 160,000 people and raised about four million bucks.
1:05:49 So I got to speak for two or three minutes.
1:05:52 And my favorite thing is I got to speak
1:05:54 after the governor of Minnesota.
1:05:56 And before, Luke Skywalker, that’s right,
1:05:59 Mark Hamill spoke after me.
1:06:02 Initially, I thought I’m so sick of identity politics.
1:06:04 I don’t want to be associated with an event
1:06:08 that identifies me based on my bage-ness
1:06:10 and the fact I have outdoor plumbing.
1:06:12 But I signed up for it because,
1:06:14 and of course, all the Trumpers weighed in and said,
1:06:17 “If we did this, it would be accused of being racist
1:06:18 “and bigoted and blah, blah, blah.”
1:06:20 I think you have to take gestures
1:06:21 with the intent that they’re given.
1:06:23 And this was, let’s be honest,
1:06:27 this was non-whites and women have absolutely been ignited,
1:06:31 enthralled, motivated, inspired
1:06:34 by the prospect of a president Harris.
1:06:35 I love that.
1:06:38 I think it’s been very difficult not to get swept up
1:06:39 and come a lot, if you will.
1:06:41 And regardless, I want to be clear,
1:06:42 she was not my chosen candidate,
1:06:43 but neither was Bill Clinton.
1:06:46 I was supporting Michael Dukakis, remember him?
1:06:48 But I’m all in.
1:06:49 I think she’s a competent person.
1:06:51 And I think the person she’s running against
1:06:53 is not a great role model for young men,
1:06:55 and that’s not what I’m here to talk about.
1:06:58 Vice President Harris has received a lot of grief
1:07:02 from Vice President nominee, J.D. Vance,
1:07:03 for not having kids.
1:07:06 And that’s just not true.
1:07:09 Vice President Harris is a stepmom, if you will,
1:07:10 to two kids.
1:07:13 And my stepmother just played
1:07:16 such a positive role in my life.
1:07:18 My dad’s been married and divorced four times.
1:07:20 He had a daughter by his third marriage,
1:07:23 but his wife, Linda, his third marriage,
1:07:26 was the first person to spoil me.
1:07:28 Do you remember that, the first person?
1:07:30 For most people, it’s their grandparents, right?
1:07:32 And my grandparents were not around.
1:07:34 So some background, Linda had been told
1:07:36 that she could never have her own children.
1:07:38 And so when this little,
1:07:40 when this eight-year-old and Levi’s corduroys
1:07:42 and an OP shirt and missing his two frontiers showed up,
1:07:46 she was just in love, like moment one,
1:07:47 and used to spoil me rotten.
1:07:50 I’d come over and she’d have like chocolate
1:07:52 hidden around the house.
1:07:54 She’d take me to Toys R Us,
1:07:57 and she’d see me eyeing the remote-controlled P-51 plane
1:07:59 and say, “Well, what about this?”
1:08:00 Even though I was too embarrassed to ask
1:08:01 ’cause it looked expensive.
1:08:03 The first person who spoils you,
1:08:04 you just love the rest of your life.
1:08:06 Anyways, my stepmom, Linda, spoiled me.
1:08:10 She was also really good in terms of encouraging my father
1:08:12 to be more involved in my life.
1:08:13 She and I spent a lot of time together
1:08:15 ’cause my dad was on the road,
1:08:17 so I would go out to my father’s every other weekend
1:08:19 and basically hang out with Linda.
1:08:21 And she was such a positive role model for me
1:08:23 and was such a loving person.
1:08:26 Reason I bring this up is I think stepparents
1:08:29 are very much underrated and overlooked,
1:08:30 including the vice president.
1:08:33 I think that it is an especially strong signal
1:08:35 of your humanity, your generosity.
1:08:38 And generally speaking, your capacity to love
1:08:40 when you do what most stepparents do,
1:08:42 and that is love those children like they’re your own.
1:08:44 (upbeat music)
1:08:46 This episode was produced by Caroline Shagren.
1:08:49 Jennifer Sanchez is our associate producer
1:08:52 and Drew Burroughs is our technical director.
1:08:54 Thank you for listening to the Propg Pod
1:08:56 from the Vox Media Podcast Network.
1:08:58 We will catch you on Saturday
1:09:00 for No Mercy, No Malice, as read by George Hahn.
1:09:03 And please follow our Propg Markets Pod
1:09:05 wherever you get your pods for new episodes
1:09:07 every Monday and Thursday.