Inside Coatue: $70B Hedge Fund’s AI & Retail Strategy

Michael Barton, Sector Head at Coatue, joins Sourcery to unpack how one of the world’s largest hedge funds is navigating tectonic shifts in markets. From the Gamestop meme stock saga and the rise of retail investors, to Coatue’s $70B multi-strategy platform across public equities, privates, and credit, Barton shares a behind-the-scenes view into how ideas are generated, trades are sized, and risks are managed. We cover Coatue’s unique approach, sitting at the intersection of public and private tech investing. And why AI is the biggest tech wave yet, bigger than Web1, Web2, or mobile. Barton explains where he sees value accruing in the AI stack, how retail sentiment now drives price action, and why the next hedge fund edge comes from integrating data science, practitioner insights, and AI-native workflows. This conversation reveals how Coatue is positioning itself for the future of markets, and what founders, investors, and institutions should learn from these shifts. KEY POINTS ​Coatue’s Scale & Strategy: ~$70B AUM, with ~$25B in public equities, alongside private and credit strategies​Rise of Retail: Gamestop and Reddit proved retail investors can move markets—forcing funds to adapt new risk frameworks​Idea Generation & Investing Discipline: Successful investments at Coatue require both deep analysis, differentiated insights and the ability to distill a pitch into a few sentences that win buy-in from the team​AI’s Impact: Advertising is the first major AI use case driving revenue growth; Coatue sees AI as the largest tech wave yet, reshaping companies, investing processes, and even their own hedge fund workflows​Winners & Losers: Value will accrue differently across the AI stack (labs, agents, infrastructure, cloud); the challenge is identifying which layer ultimately dominates Michael Barton: https://www.linkedin.com/in/michael-lord-barton-jr-390b4145/ Molly O’Shea: ⁠https://x.com/MollySOShea⁠ Sourcery: ⁠https://x.com/sourceryvc⁠ SPONSORS • Brex—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, & travel. As a Sourcery Listener you get: 75,000 points after spending $3,000 on Brex card(s), white-glove onboarding, $5,000 in AWS credits, $2,500 in OpenAI credits, & access to $180k+ in SaaS discounts. On top of $500 toward Brex travel, $300 in cashback, plus exclusive perks (like billboards..) visit → https://brex.com/sourcery • Turing—Turing delivers top-tier talent, data, and tools to help AI labs improve model performance—and enables enterprises to turn those models into powerful, production-ready systems. Visit: https://turing.com/sourcery • Carta—Carta connects founders, investors, and limited partners through software purpose-built for private capital. Trusted by 65,000+ companies in 160+ countries, Carta’s platform of software & services lays the groundwork so you can build, invest, and scale with confidence. Visit: https://carta.com/sourcery • Kalshi—The largest prediction market and the only legal platform in the US where people can trade directly on the outcomes of future events: https://kalshi.com/sourcery Follow Sourcery for the latest updates! https://www.sourcery.vc/

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  The best companies we are seeing today that are going AI native are winning. Before I worked at Co2, I was working at Melvin Capital. Many of you guys probably heard of Melvin as the hedge fund that would short GameStop. We went from probably the best performing hedge fund in the world to basically down 50% in two weeks. And the reason was we didn't realize like how powerful retail could be when they focus all their energy on the single stock. The way to source ideas now and come up with new stocks to invest in, a lot of that is coming from the internet. If you go on Wall Street Bets, like people are posting real work there. And now there's just been this kind of proliferation of information. There was a company called AppLove. I had the CEO, Adam Frugie, come to our office. I messaged at the time my boss and I said, hey, you have to get in here right now and meet this guy.

• 0:45Speaker 00

  He's like, I'm busy. And I'm like, trust me. The first use case of AI truly is driving these advertising businesses to grow faster than you would have thought. Any job that exists in the US where you work at a computer at some point can be automated, including my job. So I think as that starts to play out, there's going to be a lot of revenue opportunities.

• 1:21Molly O'Shea?

  Michael, welcome to Sorcery.

• 1:24Speaker 00

  Thanks for having me.

• 1:25Molly O'Shea?

  We have so much to cover today, but to start, let's talk about you. Who are you? What do you do?

• 1:31Speaker 00

  Well, I'm from Cincinnati, Ohio, and I live in New York now. I work at Co2, which is an asset manager. We do both public and private. And my main focus is I work on the public equities. And now we have a retail product that we're also working on.

• 1:46Molly O'Shea?

  Sorcery has had a lot of fun with tech over the last year or so. One of the most fun Podcast we did in the last couple of weeks was with Keith Raboy. And this was when he just rejoined Open Door as board chair. The funny thing about that was specifically like the cult sentiment behind it. How has the public market evolved?

• 2:08Speaker 00

  If you look back, maybe, you know, six, seven years ago, the idea of retail investors like was was not a thing. Right? Like, you know, what I love about the public markets is that anyone can invest in it. Right? So, you know, I would debate. It's actually kind of how I got started. Like, I used to debate stocks with my grandfather. And he worked in the plumbing industry, so he, you know, he wasn't a professional stock picker, but he loved investing. And so he would invest in, you know, companies that he thought were long-term compounders. He loved Warren Buffett and the idea of value investing. Well, fast forward to, you know, a few years ago with companies like Robin Hood and retail trading. And then just the internet broadly, more and more people have gotten into investing. And the impacts on the market have been huge.

• 2:50Speaker 00

  And so before I worked at Co2, I was working at Melvin Capital. And so, you know, many of you guys probably heard of Melvin as the hedge fund that would short GameStop. And so I lived through this period where we went from, at the time, probably the best performing hedge fund in the world from a return perspective, like single manager, long, short equity, to basically down 50% in two weeks. And the reason was we were at the time betting against GameStop. And we didn't realize like how powerful retail could be when they focus all their energy on the single stock. And so you've seen that same excitement with Open Door. They've got a great team and there's been just a lot of excitement around what they could do.

• 3:31Speaker 00

  And the stock, you know, I was at 700% or something on on that excitement. So the market dynamics have, you know, very much evolved. And like, it has created both new opportunities and new risks. You know, on the risk side, like, the idea of a GameStop. Going up what it did because of the internet and Reddit and people getting excited was not a thing that existed up until that point, right? Like any point when people were short of stock, there were squeezes, but it was always catalyzed by something. Volkswagen Porsche was a potential acquisition. This was just a lot of guys and girls on the internet deciding like they were

• 4:11Speaker 00

  gonna buy it. And it went up and people had to cover and it completely changed investing and the risks that people think about.

• 4:20Molly O'Shea?

  How did that change your role and like what kind of data and information you pull from?

• 4:25Speaker 00

  I think one of the best parts about the public markets is that because anyone can invest in it, ideas can come from anywhere, right? And so I think what you've seen over the last few years is the emergence of all these different channels of information. So if you think about like investing, you know, in the public markets 15 years ago, right? You would get quarterly earnings reports, you know, eight K's, annual earnings reports, 10 K's, and then you would, you know, management would speak. But that was kind of it. Like, other than that, you're reading the Wall Street Journal and the New York Times. And like, that has completely evolved, where now a lot of people, including all the retail investors, have opinions on stocks and are doing interesting analysis. And if you go on Wall Street Bets, like, people are posting

• 5:08Speaker 00

  real work there. And now there's just been this kind of proliferation of information, you know, people like you, having amazing guests on the podcast, offering interesting insights. And so we are tracking today, like, a lot of different data, right? So like, you know, we look at how often stocks are mentioned on Reddit, and we look at Twitter, and we look at, you know, how things are trending on the internet all the time, on Reddit, all these things. But we also like, the way to source ideas now and come up with new stocks to invest in or new analyses to do is like, a lot of that is coming from the internet now. And so that's sort of the world we live in.

• 5:45Molly O'Shea?

  So in terms of Co2's fund, how big is the fund and what's your main portfolio that you cover?

• 5:50Speaker 00

  Yeah, so the Co2 as a whole is probably, it's around 60 billion of assets under management. On the public equity, so we basically have public equities, which is around 25 billion. And then you've got a privates business and then a credit business too. So I focus almost all my time on the public equities. The nice part about doing both is I also follow OpenAI and Anthropic and am very in tune to what's going on in the private markets. A, because a lot of those are impacting the public stocks, especially today. But also because when our privates team is looking at a private investment, there's a lot of times often interesting insights from the public markets.

• 6:30Speaker 00

  You know, my knowledge of how digital ad works might, you know, impact some business or how they think about it, you know? So, but mainly I focus on TMT investing in the public markets, trying to find, you know, stocks that are going to go up and then trying to find stocks that are going to go down. It's internet, China internet, cloud, and then we have a pretty tight knit team. So we all, you know, we all work together, kind of the core group of us.

• 6:57Molly O'Shea?

  Any particular names? I know Jack Griffin, thank you to Jack for the intro. But I know he mentioned that you found AppLovin for them?

• 7:05Speaker 00

  AppLovin, yes. It's a pretty crazy story and it kind of like goes into, you know, how you find ideas. What ended up happening was there was a company called AppLovin. I think at the time it was like a $20 billion market cap company. And the name is amazing, right? Like AppLovin, it sounds like, it's almost like, it's like a meme name to begin with. And this business was, they do mobile gaming ads, right? So whenever you're playing like Candy Crush or like pick, the best way to describe it is when you walk on an airplane and you see everyone looking and playing the Solitaire, you know, these various games, they're the guys that serve the ads in those games. And I never had heard of the company. I didn't know what they did. And a buddy of mine, you know, called me, he was like, hey, you should take a look at this thing.

• 7:50Speaker 00

  Like it's pretty small, but something's happening here. It's starting to grow really fast. And so I had the CEO, Adam Frugie, come to our office and I met him. And I literally knew nothing about this company at that point, besides they do mobile games. And I met this guy and I will never forget this moment. I messaged at the time my boss and I said, hey, you have to get in here right now and meet this guy. And he's like, I'm busy. And I'm like, trust me. Within five minutes of meeting Adam, you knew that there was something really special here. I mean, this guy was the most locked in person I have ever met. And so after I walked out of that meeting, I was like, okay, we need to figure this out. And what ended up happening was

• 8:34Speaker 00

  a lot of what we were seeing in the digital ad market at the time was basically pure play happening with app loving. And so the idea is like, like AI is this big thing, right? And one of the places we're seeing revenues actually happen are at digital advertising companies. And what's happened is over the course of time, if you think about Facebook, right? Their goal is to serve you the right ad at the right time. And all of the AI learnings from L L M's and everything that we've seen over the past couple of years is directly impacting their ability to serve those ads better. And so when I first joined Code Two, I remember one of the first things I had to do was explain

• 9:19Speaker 00

  why Facebook could probably grow 10% or more, right? Cause they're going through this period where they, you know, with IDFA and kind of Apple, they lost their ability to track. And so there were questions around whether they could really grow above 10%. Well, fast forward two years, they're growing like, you know, mid to high twenties right now, right? And so that was like an impossible thing to kind of imagine at the time. But what happened was the underlying ad engines got better with AI. And so the way Adam, and so you kind of knew that when you had met Adam. And the way he was talking about what they were doing and that basically they had used GPUs on their advertising business and they were going from, you know, they were growing like, I think 15% before.

• 10:02Speaker 00

  And all of a sudden the ad business is growing 15, 50, 70. And the stock at the time was, you know, a $20 billion market cap company. And I remember I like, I was like, okay, so if you kind of believe this to be true and if you just listened to him and just believed what he was telling you and you put that in a model. You know, one of the things we do is we make discounted cash flow analyses to try to see what a company's worth. You literally could not make the discount cash flow analysis in your worst case scenario be less than like a three X. And it was the most remarkable thing I've ever seen. And so then we got to know him better, developed a really close relationship with him.

• 10:40Molly O'Shea?

  Sorcery is brought to you by Brex, the financial stack trusted by more than 30,000 companies, including one in three venture-backed startups in the US. Nearly 40% of startups fail because they run out of cash. Brex is literally built to help founders avoid that. Unlike traditional banks that let your money sit idle, chipping away at it with fees, Brex's design to help you spend smarter and move faster. Their all-in-one solution combines checking, treasury, and FDIC protection into one powerful account. You can send and receive money globally at lightning speeds, get 20 times the standard FDIC coverage through their partner banks, and even high yield from day one. With same-day and even same-hour liquidity, access your funds anytime.

• 11:25Molly O'Shea?

  Companies like Scale AI, DoorDash, Service Titan, Hims, Anthropic, Flexport, Robinhood, and Plaid, trust and use Brex. Start today at brex.com/sorcery. That's B-R-E-X dot com slash sorcery. Tracking these companies over time, especially one in the ad space, what does that also tell you about how AI is being implemented within the companies? Because ads are, what some would say, going to be one of the most disrupted areas. So how do you see that being affected with AI?

• 11:59Speaker 00

  That's interesting, yeah. Well, I think broadly, we're at this point in the market right now where there's been a lot of committed spending to build out this AI infrastructure, right? You're seeing new outlets every day, OpenAI doing a deal with Nvidia, or doing a deal with AMD, or there's some new data center built. And there's all this money going into it, right? Because in order to run these GPUs and do whatever the use cases are, you first need to build the infrastructure to do that. And so we're at this weird point where the market's a little unnervy, worried that we're in a bubble. Like, we're spending all this money, hundreds of billions of dollars, and yet where's the revenue? Right? Like, ChatGPT charges, what, 100 bucks a month or whatever it is, right?

• 12:44Speaker 00

  Like, that's not enough to offset that. But I think when you actually dig deeper... What what we've kind of come to the conclusion is there's actually a lot of AI revenue today happening. Now, it's not enough. You have to believe there's going to be more, but like a big part of that is advertising. So like, the first use case of AI truly is driving these advertising businesses to grow faster than you would have thought. And so if you think about like, two years ago, what did I think Meta's revenues were going to be? Maybe I thought they would grow 15%. Well, they're growing 25. So that that kind of incremental revenue growth, that's AI.

• 13:23Speaker 00

  Now, it's not generative AI, but that is GPUs accelerating machine learning to find and serve you an ad for a snowboard that you might not otherwise have seen. So that's sort of, we're seeing that happen, and it's happening across the board. AppLovin is growing really fast because of this. Meta's growing, call it 20, high twenties percent. Google Search, which, you know, grew, search, maybe people thought it was going to grow sub 10% is now growing mid teens. And so that's kind of the first impact. What's also happening is the recommendation engines of all these companies are getting a lot better. Like, you may have noticed this, but like, when you're on Instagram, like, the reels they're serving you are like, they're more addicting.

• 14:09Speaker 00

  And if you look at Instagram time spent, basically it was flat for, I don't know, maybe 18 months to six months ago. And now, you know, you would spend 40 minutes a day, and now that's gone up like 15% in just, in just the past six months because they basically took those GPUs and put it at the recommendation engine, and now people are spending more time, right? And that's also more, more ad dollars. So advertising is like a huge place. I think the big question, and it's what you're getting to, is like, well, what happens like in agentic commerce? And what happens, you know, to these ad models when you have a shopping agent doing everything for you? And my view is that it's early, it's very early.

• 14:53Speaker 00

  Like, we had OpenAI announce the Shopify and Etsy integration a couple of weeks ago. The product today is not at a place to really be that useful, but you can kind of see where it's going. I think that from a shopping perspective, we are going to be in a world where the old world was, I want to buy something, I go on Google and type in, you know, red shoes to go skateboarding in, and it would come up with a list of results. The next step is going to be, I go to Gemini or Chat GPT and say the same thing, but it knows a lot more about me and will suggest better products. In that world, there's probably no advertising.

• 15:34Speaker 00

  And then the ultimate end, which I think is the most exciting, is a lot of the products that you end up buying, like if think about Instagram, right, then you like the more and more I'm getting advertisements for things I never even knew I wanted. And then like, you know, I clicked the button and it shows up. I sort of Toby at Shopify kind of made this comment, I actually agree with it, which is, those were actually not impulse purchases, like I actually secretly wanted those things, but no one had ever shown them to me, right? So like, I would never have gone on Google search and just like looked at, you know, looked up that interesting steak knife. But when it was showed to me, I bought it. Now imagine a world where you're in Chat GPT or you're in Gemini.

• 16:16Speaker 00

  And instead of asking it for something, it's just telling you, hey, like, you're going on this trip, like, I think you, you know, need a new ski coat. Or like, hey, I just found this interesting product because of a conversation that you and I were talking about in like a separate chat. And I think that's going to drive consumer spending for these goods a lot higher. And I think when you think about advertising, there might not be like an ad per se, but from the merchant's perspective, instead of spending, you know, 20% of my revenue on marketing in the form of ads and 2% of that is going to Shopify, that split probably changes. So that 20% that I'm spending on marketing

• 16:56Speaker 00

  to, you know, maybe it was Meta, is now going to like that profit pool is going to be more going toward a Shopify or. The actual agent players themselves, OpenAI or Gemini. But like, this is like early in, like we are, people are debating this like literally every day.

• 17:13Molly O'Shea?

  This one hasn't come out yet, but I had Alfred Lin on. I think this will come out before it. And he spoke and also Reid Hoffman spoke at Forerunner's AI Conference back in like summertime that Kirsten Green throws. And one interesting thing that Alfred said was, things that happened three months ago are not relevant today. Things that are happening today are not going to be relevant in three months. And things are moving so fast, it's really hard to predict, but you have to be active. You have to be watching what's going on and like gathering as many data points as possible to like adjust accordingly. And then another thing, and I'm curious for your perspective on this, was Reid Hoffman was talking about how business models define different generations of technology. Advertising was majority of the last one. We don't really know what the AI business model is yet. Do you have any idea?

• 17:59Speaker 00

  On your first point about things changing, I mean, tha- that could not be more true. And it is also like, this has been the longest year of my life. Like, I feel like we're at this point in tech where the implications of AI, like, they are going to be big. It's not a question of like how big they're going to be. It's what is actually going to be impacted and who's winning from this and who's losing from this? And that changes like literally every day. And so you, like, part of, a big part of my job is, you know, I'm not making an investment, closing my eyes and waking up in five years, right? Like, stocks are priced every single day.

• 18:42Speaker 00

  I'll give you a great example, like, uh, OpenAI did their dev day a couple of days ago.

• 18:45Molly O'Shea?

  Yeah, oh my god.

• 18:46Speaker 00

  Like, this was so insane, they get up and if you got named in the presentation, like, by the way, you could argue a lot of these companies that are kind of named in the presentation to go and be part of this like... Agent layer like like it might not actually be a good thing like if everyone's using chat GPT and now you just got like sort of you added additional layer of like maybe disintermediate like it might actually be good but if your name got mentioned bang you're up five and the best was like Mattel like the toy company right like not even a tech company like they got mentioned in this thing Mattel the toy company stock went up six percent like in a second and

• 19:29Speaker 00

  so but that's just like highlights sort of where we are because because we don't know how this all plays out and everyone's trying to figure it out any sign of you being a AI winner or AI loser like gets priced in the stock very very fast and so you know part of our job is to stay at the forefront of what's happening and figure out the implications like real time and do analysis around that and the way we sort of do that and I think it's it's a unique thing with code two but I actually think it's underappreciatedly the most important part of tech investing is that the best way to figure out what's going to happen in tech is to actually talk to the

• 20:12Speaker 00

  practitioners of that tech and so what I mean by that is we spend a lot of time not only talking to the the company CEOs and the management of the actual and having relationships with the management of the public companies but we talk to the private companies we talk to open AI and anthropic we talk to the researchers because these are the people every day living and breathing this sort of tech this AI that is going to change a lot of things and they all they all have super interesting insights but if you don't do that and you're just sitting in your computer and trying to you know build a model or forecast the next five years or the next quarter you miss these big waves and I think the part of what makes code two has really

• 20:57Speaker 00

  successful over the last 20 years and and today is that we by being at the front of tech like tech goes out in different forms whether it was you know you know web internet web one web two like there have been winners and losers and new markets and all these kind of tech waves We think the big one right now is AI and I'm not, that's not a hot take, but we think it's actually bigger than any of these previous waves. But we spend a lot of time focused on actually meeting the people in the industry. Because that's where you're going to get these insights. They'll, they'll tell you, like, they will tell you what they think. You know, the way Adam Frugie at AppLovin was telling you, hey, like, we're gonna, this revenue is going to grow a lot faster than people think.

• 21:42Speaker 00

  And often, like, you know, those are the best kind of tidbits of information to get because these are the people doing this every single day. And the last thing I'll say on this is that, like, when you have these big tech waves, every single time

• 21:59Speaker 00

  when things are inflecting positively, so think about like, when people got excited about AI, they realized in order to do AI, you needed Nvidia GPUs. Even the most like bullish person in the world about how big AI could be, probably underpredicted the amount of GPUs you needed. And the same is true on the inverse side, like when things are, when companies are getting disrupted, that pace of disruption normally happens faster than you think. And so if you can find those big trends and the winners within those trends, you can do all the modeling in the world and the valuation work and the DCFs and the the, the analysis, but normally it ends up being better than you think to the upside and worse than you think to the downside.

• 22:43Molly O'Shea?

  A question I'm interested in is in the early inning of like this AI cycle, maybe in the last year or so, like, none of this really existed. Like, I feel like now it's like actually taking adoption and there's actual applications. But in the beginning, it was a lot of marketing hype. And I'm curious how you like deduce down who is real, who is not, and like, how do you determine whether or not like they're actually making progress or it's like a consulting presentation?

• 23:11Speaker 00

  Totally. Well, you, what happened was you got to the point where if you, as a public company, came out and didn't say how you were going to benefit from AI, like, no matter what industry you're in, people instantly were like, oh, they're behind. So then, yeah, you saw a lot of companies basically talk about AI, like, before it was actually being implemented. I actually think you say, see the same thing at, like, even in the hedge fund industry today. But I think where we are in this cycle is that

• 23:43Speaker 00

  We're now actually starting to see revenues from these companies. I mean, like, a year ago, right? You could point to, I, there was a, there was a big AI scare in the summer of 2024, right? Where there was all this build out happening. And there was a moment where everyone kind of woke up and we're like, okay, so we got ChatGPT.

• 24:04Speaker 00

  What else do we have? And like, literally, I remember like this, and it became like, public discourse around the investing world. Like, you couldn't really point to anything else. And, I mean, these stocks at this point were like, tanking. Like, the, the power and utilities companies, the infrastructure companies, like, uh, any, a lot of the tech companies. They were, these stocks went down, I mean, some of them are going down, you know, 15 to 20% in the course of three weeks, right? It's like a disaster if you own these companies. And, and nothing's like, changed. You just, there were nerves in the market, and you didn't have, like, a lot of things to point to, to say, no, like, revenue's coming from there, and revenue's coming from there, it all makes sense.

• 24:44Speaker 00

  And I remember in that moment, we had this really amazing conversation with one of the head engineers at XAI. And he's like, guys, here's how I think about it. The tech, two days, so this was summer of 2024. The models today, where we are today, and you know, where we are, fast forward, you know, 14 months is a very different spot. But where we were in the summer of July of 2024, the models are good enough to have a lot of applications that will generate revenue. And the way he talked about it, he was like, each model's like a, a child, right? So, you, with each kind of breakthrough in the model, architecture, or you're training on, you know, more GPUs,

• 25:29Speaker 00

  the IQ level of that child goes up. And I remember at the time, he was like, today, I think the IQ is about, of, of the, the child, is about 100. Well, you know, 100 IQ in this economy, like, there's a lot of work for 100 IQ person to do. But remember, it's a child. And The child can't work right away. So you have to go, the child has to sort of grow up, be, you know, uh, figured out how to use and, and, and his point behind that was the tech's good enough, but we just then need to spend the, there's going to be a lag to developing applications for that tech. And so fast forward a year, you've seen that, right? There've been early breakouts of use cases. The first one's coding, like that's the big

• 26:14Speaker 00

  one, right? You have these companies that are generating a lot of revenue today, uh, cursor, um, you know, Windsor before they got acquired, like their companies cognit, like their companies generating a lot of revenue and that's sort of the first use case. Okay. Agentic coding. My view is that the reason that's the first use case is a lot of the guys that are working on building AI in these labs, they code. So like, what's the first thing they're going to try to figure out? It's going to be how to make their jobs better. That is now starting to broaden out to a lot of other industries. We're now starting to see companies start to generate revenue and products that actually look pretty good

• 26:56Speaker 00

  for a lot of other things, whether it's building an Excel model, right? So going after the financial services space or, um, you know, we're seeing this with obviously like call centers. My view broadly, and this is my view, I'm not sure this is everyone's view at code too, but my view broadly is that any job that exists in the U S where you work at a computer at some point will likely can be automated, including my job. Um, and so I think as that starts to play out, there's going to be a lot of revenue opportunities.

• 27:32Molly O'Shea?

  One thing that we talked about before was positive, negative indicators on if companies are not hiring anymore, if they're doing layoffs, if AI is going to be automating more jobs. So how do you view job automation with picking companies and betting on them?

• 27:51Speaker 00

  There are two camps here. There's the camp that says, AI will make workers 10x more efficient. And therefore, you probably actually want to hire more workers because, you know, companies, industries are competitive, right? So if your workers are 10x more efficient, you're going to hire more workers than your competitor, because then you're going to be able to do more things. The other camp says, and this is the camp I'm in, says, you're probably gonna get, you're gonna get more efficiency, and it's orders of magnitude way higher than 10x. I mean, if you think about me, right? Like, my dream with AI is that instead of having, you know, a few analysts work for me,

• 28:34Speaker 00

  I have 20 agent analysts doing their same job. And those two guys that work for me also have 20 or 30 agents that are working around the clock. And so, like, we, I want to kind of see that world happen. But I think in a lot of industries where you're, where you're starting to see is, people aren't, there are some example, some extreme examples, but it's not that people are getting fired today, or their jobs are being automated today. It's that the hiring's slowing. You know, you've seen these charts of this kind of college grad software developer chart. And if you think about what's the first obvious use case in the market

• 29:17Speaker 00

  of an AI application people are using for work? It's software engineering. And so my view is like, that is a little bit of a tell how this plays out. So hiring slows, headcount growth slows. For the stock market, that's good. Because if you think about, let's take the magnificent seven, right? Company like Amazon or company like Meta. If they stop growing headcount, they, these are companies that grew revenues 20% for years, and headcount kind of grew in line with that. If they stop growing headcount and they just make it flat, the margins are going to increase. The profit, the EPA, the earnings per share growth is going to accelerate. And the stock is going to go up a lot. So the market will view that positively.

• 29:59Speaker 00

  Um, I think that's true across all industries. I think where it gets tricky and the big question that people are asking is, well, if you start, if jobs get replaced across these different industries, like, A, what are they gonna do? Like what new industries, do new industries emerge that, you know, they can work in? And there are debates around that. And then if not, like, you know, Amazon's stock price might have gone up a lot, but who's going to buy the, the goods if, you know, there's unemployment? And so I think people are still trying to kind of figure, figure out those debates.

• 30:38Speaker 00

  And like, I'm pretty optimistic that th- this will happen a little slower than some of the fear mongers think, but there will have to be new industries for these, for a lot of people to work in, um, or other ways of making money. And I think that's sort of one of the reasons, and you've seen, you know, one of the reasons that it's important for the average American to be investing in the stock market now, right? Because AI is going to benefit all these companies and the stock market's going to go up. And we might be at the front of a multi-year amazing run in the stock market because these companies' revenues are going to go faster, their costs are not going to be as much as you would have thought, your margins are going to go up and the market's going to go up.

• 31:22Speaker 00

  And so, um, I think it's the most exciting time to be investing in the public markets because of that reason.

• 31:28Speaker 02

  In today's high-speed business world, staying ahead means using the smartest tools possible, including the powerful capabilities of artificial intelligence. Meet Turing Intelligence. Turing builds customizable AI systems designed to solve your mission-critical challenges, no matter your industry. From expert guidance to tailored projects, Turing helps top companies realize AI that's more capable, more adaptable, and more effective. With Turing, discover how AI can accelerate your business growth. To learn more, visit turing.com/sorcery, spelt S-O-U-R-C-E-R-Y. That's turing.com/sorcery.

• 32:04Molly O'Shea?

  I covered Klarna's IPO and Sebastian was really clear about when they were doing their turnaround, reducing headcount, freezing hiring, now they're just like waiting on attrition. And same with Open Door, well, Open Door has to go through a lot more right now. To resurrect themselves and do a turnaround, but they're counting on severely slashing headcount and hopefully deploying more AI agents within. And then I'm curious, between all of this, how do you price? How do you set long-term and short-term price targets in this environment?

• 32:39Speaker 00

  Yeah, it's a great question. The last thing, just one, one thing on your previous point, like I, I, I think the, the most exciting thing is like, these companies are all going to be revolutionized with AI. It's not just forget the revenue growth and the, like, the actual workings of the company. The best companies we are seeing today that are going AI native are winning. AppLovin's a great example. Like, the way Adam Farugi, I mean, he's notoriously known. I think they've got the highest EBITDA per head of any company in the world. And that he like loves, he loves this statistic. And his view is, A, everyone at the company needs to figure out how to use AI, like now. And if you're not, like, you're fired.

• 33:20Speaker 00

  But I am setting up the company not for what the tech is today, but where the tech is going. Because it's changing so fast. I want to be ready in two years when the models are significantly better and can, the applications are significantly better and can automate these different parts of the role or the, you know, the workforce. I want to make sure that my company's in a place to take advantage of that. And you're seeing other companies maybe less aggressively have this mantra. And those are the ones that are going to win. And this is something that, like, a big theme of Co2 is we take a lot of the learnings that we see from the public and private companies and how they're implementing tech, and we do it ourselves, right?

• 34:01Speaker 00

  So we were, you know, Philippe and Thomas were early investors in the, you know, in the cloud transition, right? And so Co2 was like, became cloud native. All of a sudden, you had these best companies talking about, you know, how they're able to use all this data and get it into one place and do data science on it. And so we built out this data science platform like over the course of those years. And it's been amazing. And so kind of like thinking about how this tech will transform CO2. Like that gets accelerated massively in the in the AI world. And like my belief and something that I'm I spend a lot of my time on is how do we use AI internally? And how do we build a workforce and reimagine the workflows?

• 34:43Speaker 00

  Especially in a space where like, you know, as you know, most financial service companies, whether it's a hedge fund or a bank are like the last guys to adopt tech, right? And so we think that there's like huge moment where we're able to create kind of the investment fund of the future. And like it's it's happening now, like my views that.

• 35:01Speaker 00

  Like this is I tell my friends this and they like laugh. I think that today 85% of what I do. Like basically can be done by AI. And it's not a question of is the tech ready? It's how do we implement the tech? And so like we're hiring a class of analysts to come in and like help me with this problem. And basically figure out how to reimagine the workflows that we do every day from I come in the morning, check my email to see all the different sell side notes. You know, I spent two hours doing that because you have to read everything. But like, there's only a few important ones to like, how do I build a model in the click of a button? How do I like take disparate data sets and bring it together? How do we do like every single step of the investment process? How can we use AI to?

• 35:46Speaker 00

  Almost automate it. But then if you can do that, those six new analysts we hire in three years are basically sector heads with 25 agents working around the clock. So it's this really exciting time.

• 36:01Molly O'Shea?

  Are you worried? For your job.

• 36:03Speaker 00

  No, so the nice part about the hedge fund industry is it's not that people intensive, right? So we don't need to cut people costs. There's just a huge prize for becoming like exponentially like what we are trying to go and find ideas to invest in, right? And the constraint in ideas is the amount of time you have, the places to look. Like you only have so much time, right? I can only spend so much time looking and poking around different areas. But if I have 25 agents able to do all that, working around the clock, like I fundamentally believe we are going to be able to find better ideas faster. And even more importantly, like I don't think other firms are going to adopt this that fast.

• 36:48Speaker 00

  And we're going to be light years ahead. And so the pitch I've been giving to the analysts that we're trying to hire is like, hey, we're going to teach you this investment process, but we're going to go and reimagine it together. How do we do this with AI? And in three years, you know, when you're an analyst, a full-time analyst, you're going to be exponentially more efficient, better at the job, and significantly better than your competition because they're just going to start, you know, be picking up these things. So like, I think I timed it perfectly where I I'm not going to be replaced by AI yet. I just want to like, control it, you know? I want to be like the, yeah, the the last, uh, maybe the last analyst.

• 37:26Molly O'Shea?

  The AI captain.

• 37:27Speaker 00

  The AI captain, yeah, exactly, exactly. Um, on your point of like pricing the stocks, though, so it's really tricky because on one hand, the main focus of code two is like picking long-term winners. So investing on a multi-year horizon. And like what that literally means is like, take Meta for example, right?

• 37:52Speaker 00

  I have a model for Meta for what I believe they're going to do in revenue, in EBIT, in profit and earnings and free cash flow out to 2031 right now.

• 38:04Speaker 00

  So I'm projecting like what they're gonna do in the long term and what multiple, I think the business will get assigned to the business in that year and what that stock price is and what the return looks like. So you have your kind of like long-term view. And the other way we do it is we literally build like you maybe did in college, like a discounted cash flow analysis. So saying like Meta's market cap should be worth today, the sum of the future free cash flow that's generated discounted back, right? But as you know, like stocks are moving all the time. So you have to have a long-term view of a business. You know, what's going to happen in the industry? Are they gaining share? How are the margins going to evolve over time?

• 38:48Speaker 00

  How's the company, you know, the earnings profile going to evolve? But then you also better be damn sure you have a good idea of what's going to happen next quarter. And so what happened in the hedge fund industry is early on, when you think about like Julian Robertson and Philippe, my boss, was an analyst for Julian, like he sort of invented this, we're going to do fundamental analysis and invest on a multi-year timeline. And over time, we're going to be right. Well, then what happened was you had guys come in who said, we're going to be more short-term focused. We're going to focus on the quarters and really like, you know, and data played a big role in that, right? All of a sudden you could track credit card data and early on, like no one had that credit card data. So that was an amazing strategy.

• 39:32Speaker 00

  And then the idea evolved further into like, we're going to have kind of a bunch of different managers who are hyper-focused on their sector and within those sectors can pick winners and losers and really focus on the alpha piece. And then as a fund, we're going to control for all the other things, the factors and the, you know, the shorts and the long, we're going to make sure we're running market neutral and we're going to squeeze this alpha out. Well, now we're at a point where I think the winning strategy is how do you invest in a, how do you have a really good idea of who's going to be a long-term winner and a long-term loser? But then marry that with.

• 40:13Speaker 00

  A real focus on the short term and we spend a lot of time on the short term. I do because my view is that the long term is simply a collection of quarters. Right. And so you want to make sure that you you have an understanding of how, you know, we go from here to here, but also what that path looks like. Because it also creates great opportunities to buy a stock lower because, you know, like Netflix is a good example, like you knew what the end state for Netflix was going to be. But at every little hiccup, your stock might be down 20%.

• 40:50Speaker 00

  And so, you know, trying to make sure in those moments, you're not, you know, massively sized before it goes down 20. Because even if you're a long term investor, let me tell you like that is going to be an ugly day in the office.

• 41:03Speaker 00

  But then knowing when these things have overcorrected and being able to size up in those moments when there's a hiccup.

• 41:10Molly O'Shea?

  Because Co2 is concentrated in technology. How do you balance out these market cycles that just so favorable towards AI? And what some would say is a bubble.

• 41:21Speaker 00

  That's something we think about every day. So broadly, we're investing on the long side in tech. So, but even within that, like if you think about the NASDAQ, right? So the NASDAQ's up, I think maybe 17% or something this year. And the AI trade has been like a winning trade. But within that, so even so, if you pick the right stocks, you know, within that, maybe you're slightly above the NASDAQ, but within that there's been kind of specific sectors within that have moved very differently. So like AI infrastructure, right? Like the the build out of AI, the data centers, the constellation, energy, the new, the power needed

• 42:05Speaker 00

  to to, you know, power these GPUs, those stocks are up like 50. And then you would say, you know, well, Microsoft's like probably an AI winner and Meta is probably an AI winner. Like those stocks are up like, you know, 25. And so even in a moment where the market is going up a lot because of excitement around tech, you need to make sure that your book is sized appropriately where you're capturing like the winners even within that because that's how you kind of drive outperformance. So that's sort of when the market's going up, that's how you think about it. But even this year, there have been crazy moments. And like, I was like, I, I remember like, I was basically so excited. I was like, we need to like, take on more risk.

• 42:49Speaker 00

  And, you know, this is the 30 year old, uh, me saying that. And one of Philippe's amazing qualities is that he is like the best risk manager I've ever seen. He has this sense of when something is about to go wrong. Like I, like it is incredible. Like he, and it's, it's really been great for him. I mean, and you know, uh, in different moments in these drawdowns, he's been able to base, uh, we call it cutting gross, but going from, let's say you're a hundred percent invested to 50% invested. So you're sitting at 50% cash very quickly and he gets the timing right. And then tariffs came.

• 43:29Speaker 00

  And when Trump came out and put the, you know, the, you remember like that day where he's got the, the board with all the tariff prices? I remember like sitting there, you're like, oh God. And so I think one of Philippe's best qualities is he understands how to bet on these tech trends and he's really good at picking stocks. But his single best qualities is risk management.

• 43:54Molly O'Shea?

  How do you get his buy-in on a new trade? What's like the process to get through?

• 43:57Speaker 00

  I think there are a lot of people that can pick stocks, but what really matters at COTU is you have to be able to do the analysis. You have to be able to pick stocks, you know, that bet on longs that go up and find shorts that go down. But the key piece is how do you then convince Philippe and Thomas, uh, his brother?

• 44:22Speaker 00

  And the rest of the group that you're right ultimately to get that name in the book and then have it play out, right? There's a lot of people who I've seen come through CO2 and it was true at it was true at Melvin too. I mean, this is true at any hedge fund where they're really smart. They're really good at picking stocks. They have great ideas, but they were never able to convince the person above them who's ultimately the decision maker to put that in the book. So this is a bit of an art and I think the most important thing is, you know, you spend 95% of your time doing all this deep work and all this deep analysis.

• 45:04Speaker 00

  But can you take that, you know, thousand line Excel model and all the expert calls and all the nuances around margins and growth rates and sequential growth and all those things? And can you summarize it and simplify it into a three sentence pitch? That when he hears that pitch, he's almost ready to buy the stock before even opening the model because the pitch is so good. And it that is a skill that I'm still developing. I mean, I, I think that Thomas, Foose Brothers, probably the, the best I've ever seen at this skill. He can take something incredibly complex and get the idea down to three sentences

• 45:49Speaker 00

  where you hear it and you're like, that's a great idea. And then you go into the model and you go into the details and show why that's happening. But you, I spent a lot of time thinking about how do I make a pitch very simple? And get it in the book.

• 46:07Speaker 02

  Sorcery is proudly sponsored by Karta. Karta is transforming the private marketplace, connecting founders, investors and limited partners through software purpose-built for private capital. Trusted by more than 65,000 companies in over 160 countries. Karta's platform of software and services lays the groundwork so you can build, invest and scale with confidence. Karta's fund administration platform. Supports over 9,000 funds and SPVs, representing nearly $185 billion in assets under management, with tools designed to enhance the strategic impact of fund CFOs. For more information, visit carta.com/sorcery. That's C-A-R-T-A dot com slash S-O-U-R-C-E-R-Y.

• 46:53Molly O'Shea?

  Talking about AI and how value is accruing, it's really interesting because there's so much,

• 47:02Molly O'Shea?

  there's so much innovation happening on the private side, but it's not, you know, it's like OpenAI, it's anthropic, it's all of these like research labs, it's models, it's a lot of things on the private side that are impacting the public side. But I'm really curious because Co2 does both private and public. How does, how does that inform your decisions? We'll start there and then I want to ask about valuations.

• 47:25Speaker 00

  As I said before, when you're investing in tech, you want to be talking to the practitioners. So one of the best parts about Co2 is that we do both public and private investing. And we spend a lot of time with each other from a team perspective, but we also spend a lot of time, you know, I spend time talking to OpenAI and, you know, these various private companies to kind of get a lay of the land of what's, of what's going on. I think that we're at this point, at least in my, you know, eight, nine years doing the job, I've never seen a moment where,

• 48:02Speaker 00

  where the private companies are impacting the, the outlooks or, said differently, I've never seen a moment where private, a few private companies are impacting so much public market cap in a way like today.

• 48:19Speaker 00

  And so I think just like having an understanding of really what's going on in both. Areas helps you A be a better public investor, but B be a better private investor. And like, there's also this idea where like, it used to be that you could be an investor and it's one specific sector, right? So you covered restaurants. And when you cover restaurants, the restaurant world wasn't changing that much, or maybe it was, but it was all kind of within that ecosystem, right? Today, you need to have an understanding of the entire AI value chain to like, figure out what's going on and like, who are the winners and losers? Meaning like, you know, I, I need to understand how many GPUs Nvidia is planning on selling next

• 49:03Speaker 00

  year and who they're going to sell them to, and have an idea of what that looks like. Because those GPUs go into each of the cloud players' businesses. And we're at a point where your cloud revenues are 100% dependent upon how many chips you get. So you have to have like, an idea of like, okay, how many? And you've, you get a lot of insights from kind of seeing the entire ecosystem.

• 49:25Molly O'Shea?

  Where do you think value is going to accrue between all those layers?

• 49:29Speaker 00

  Undoubtedly, there are going to be a lot of public winners. Or the public, like, I think Meta is going to be, like, Meta is going to accrue, and they already are today, a lot of value. So, and there like, are different offshoots. I think the biggest question right now is, I, I like, I was talking to a, a friend of mine who does reinforcement learning at Anthropic. And he kind of laid out this case study of what you're just asking of like, let's take a coding agent, right? Let's take Cursor. So you have Cursor.

• 50:01Speaker 00

  It is the most loved, most used, like, coding agent. They've figured out this one specific area and they're crushing. Well, then you have the labs. So you've got Cursor here, then you have the labs. OpenAI has their own coding agent, but they also have a lot of other things, right? So they have, they're doing coding, and then they're going to do a lot of other different things. And then you've got Google, who basically is the labs, plus the Cursor, plus their own cloud, plus their own little mini Nvidia with their TPUs, plus a search business, plus data on everything. So who wins in this? And I don't think, I don't know the answer yet.

• 50:44Speaker 00

  But the funny thing is, if, if I just gave you that case study, you'd be like, oh, well, Google's going to win, because they have like, that plus everything. Well, they're also the slowest and the all the people love to use the thing on the far end of that spectrum, the cursor. So I think this is going to be true for a lot of things. Like is cursor and then the next iteration of that for all the different applications or agents that you'd want to use, are they the winners because they're so specialized? And they're so they gathered this, you know, adoption among the workers. Are they going to be the winners or is it going to be OpenAI in kind of the middle? Or is Google going to be able to take the vast amount of data they have and their ability

• 51:27Speaker 00

  to do things cheaper and they can also like, you know, their cloud business, they they own it. They don't have to pay for like, or are they going to be the winner? And I think this is going to be the biggest debate over the course of the next few years. But I don't think we're at a point where you need to answer that debate.

• 51:42Molly O'Shea?

  Fair.

• 51:43Speaker 00

  Like, I think all three win for a while.

• 51:46Molly O'Shea?

  I think it's really interesting just seeing how much there's a premium added to these companies, even on the earliest stages. So like Karta, they report series A companies that have AI enablement in their name, or if they're doing that, they get a 30% premium. You're looking at OpenAI, they just raised a $500 billion secondary. Like, it's insane, but like, I've had a poor from Altimeter on. He explained OpenAI's valuation. I also asked, I think I asked Alfred about this and maybe Elad Gil, who's also coming on. And they all have different explanations for this, where it sounds actually more justifiable

• 52:29Molly O'Shea?

  for OpenAI versus these younger companies. And it seems like you can actually see the compounding happen there and the reliability and the predictability of that revenue over the next couple of years versus like these smaller players. And even at the family office level, like, we consider investments and we're like, okay, do we think like this, let's take chip? Do we think this new chip company has a chance of beating Nvidia? Or should we just like do some more Nvidia leaps? Like, what should we do? And so it usually just comes down to like, oh, that's like less risky. Like, let's just do that and like, let's just hedge that one. I don't really know what the question is on this.

• 53:06Speaker 00

  No, I mean, I think it's just like, like, OpenAI, you can, we're investors in OpenAI.

• 53:13Speaker 00

  The OpenAI five hundred billion dollar round, like it makes sense to me. Like I get why there's a lot of like, I get why people want to do that because, you know, if you're when you're it's I always look at private investments from, you know, public markets background. So I have a lot of like analogies in the public markets, right? OpenAI has got what eight hundred million weekly active users.

• 53:35Molly O'Shea?

  So crazy.

• 53:36Speaker 00

  Spending like spending my by my estimates, close to the amount of time every day that is spent on Instagram.

• 53:47Speaker 00

  Like Facebook is a, I think like it's close to, it's like a two trillion dollar, it's a two trillion dollar company. OpenAI is, you know, five hundred billion dollar round. They've already got all these users like,

• 54:00Speaker 00

  could OpenAI go from a five hundred billion dollar company to a two trillion dollar company where Facebook is today? And by the way, I think that Facebook is going to become like, you know, much larger market cap. Like I think Facebook is going to be, you know, a three X in five years. So if the two goes, you know, six, what could the five hundred go to? Like that makes sense because you've got users and engagement. You know, they're building modes real time. The more we're talking to chat GPT, the more information it has about us, the more the way, you know, it'll better serve us products and ads and, you know, Sora like, you know, was really fun. Like, I don't know, does it become a social company? Like, do they go and build a cloud? Like, there's so many optionality plays with OpenAI that aren't in the model

• 54:45Speaker 00

  that you have that the model like you have works. Like if they do that, it works. And by the way, we haven't added like any of these additional opportunities. Plus the fact you have just such talent density there and you've got a leader that is going out aggressively, you know, acquiring compute and infrastructure and building the data real time and they have like this like guys like that makes sense. I think where it gets much harder is investing in, and and I say this with, I don't spend my time doing this. So this is just a view from the from the outside. But I think it gets much harder at investing. Behind this proliferation of new companies. It's one of the things with AI that's great. Like, we track this. It's like, it's never been easier to start a company with AI, right?

• 55:30Speaker 00

  Like, the fact that you can, on coding agent alone, two guys in a, you know, in a dorm down the street can build software in a way that they couldn't have built previously, like, you're seeing a proliferation of new companies, right? And the prize is so big in any of these markets. I mean, if you think about the TAM for AI, the easiest way I think about the TAM is there's $20 trillion in labor spend. Software, I think, is like a $1 trillion. So, $1 trillion of the 20 is software. Like, that $20 trillion is up for grabs. So, like, the market opportunity is huge.

• 56:09Speaker 00

  But picking the winners and losers in that is, like, really difficult.

• 56:16Speaker 00

  Well, yeah, because also, like, you just, every day, you know, you invest in a new startup, and then you're just waiting for OpenAI's new launch of, like, you know, like, the N8N, right? Like, you saw, like, here's our version, like, and you're like, oh, well, okay. So, and there's so many examples of that. Yeah.

• 56:35Molly O'Shea?

  What is it called? Sherlock? Sherlocking or something?

• 56:37Speaker 00

  Yeah.

• 56:38Molly O'Shea?

  I think that was with another one. I know we covered this a little bit, but I want to touch upon it again. So, sorcery sponsored by Brex, they're all about performance, spending smarter, moving faster. We love Brex.

• 56:52Molly O'Shea?

  For you particularly, what are the metrics that you track within these different companies to determine their success?

• 56:58Speaker 00

  It kind of depends on the industry, but broadly, like, the, you know, we have this sort of, as I told you, like, a five, six-year view of these companies. But in the near term, what we're tracking is broadly inflections, right? Inflection in the digital ad business, that's inflection in growth rates. In, you know, the cloud business, inflection in growth rates, inflection in margins, where you have a quarter that is better than people think, or worse than people think, and helps prove out your thesis faster, right? Because if you think about, like, if we have a five-year view of what a stock's going to be...

• 57:42Speaker 00

  Like ideally, we want the market to figure out that's where it's going as quickly as possible. And so you'll like, we say like, IRRs get pulled forward, right? And so when you have a moment of inflection, that's where your IRR can get pulled forward and the stock reprices higher, kind of more toward your view. So, but like, we're tracking everything, like, you know, I'll give you an example. We're tracking, you know, everything from credit card data to email traffic to, uh, I mean, we, my analyst sent me this today, like, we go through every Thursday, we sit down and we have KPI tracking using some real time data set or a mixture of them for every single company we cover.

• 58:25Speaker 00

  Like, even if I'm not looking at, uh, even if we're not invested in the company, I look at that tracking every single week because that tells you something might be changing and that might be a source of a new idea. Or it kind of gives you, it gives you an understanding of like where we are in the broad economy. And so those are sort of like table stakes and basic, but you take all that together. You're looking at the ad market and e-commerce and payments. And you have an understanding of like where you are in the economy, are things getting faster, things slowing. You know, like ads have been really great, uh, in the third quarter, but like about a week ago, they started to slow. Is that like consumer spending slowing or is that just a weird shoulder period?

• 59:09Speaker 00

  You know, in, in, in the time. But where I think the data science gets like really interesting is when you can take differentiated data sets and piece them together to get a unique view of something happening that other people can't see. So like a good example of this was, uh, one of the companies that we invest in is Reddit. We love Steve Huffman, we love the team. Uh, we think that Reddit is going to be a much bigger business over time, that it's going to be this great ad platform and that really like in the AI era, there's really only one place where actual human generated content exists and the value of that content is super valuable, like really valuable because it helps train the models. If OpenAI wants to have a shopping assistant, right?

• 59:53Speaker 00

  All the reviews in the world are on Google. Like they don't, they're not on OpenAI on ChatGPT today. So where do they go? They have to go to Reddit. Like what are they willing to pay Reddit? To be able to use that data to ultimately build the shopping assistant that's gonna take over the market. The answer is like, probably a lot.

• 1:00:12Speaker 00

  But there was this moment where, you know, search, as you know, is being like re-architected, right? Like you have AI overviews and now you have ChatGPT. And Reddit at the time was growing users and then there was a little bit of a hiccup. And the hiccup was related to AI overviews being shown. So if you think about like old world, you type in something in Google, Reddit was like one of the top links. Well, now you got an AI overview that is like taking up your screen. So Reddit's now down here and you're like, okay, they they just like missed this metric. The market's freaking out because it's very easy to say, well, oh, they were only growing because of, you know, Google. And now AI overviews just took their entire slot like this thing will never grow again.

• 1:00:56Speaker 00

  Like that's how the public markets react, like this will never grow again. So the stocks, you know, plummeting.

• 1:01:02Speaker 00

  But what we figured out was we we were basically able to figure out that in the old world of Google, when you typed in a Google search, Reddit came up, maybe I'm just gonna use fake numbers, but 10% of the time. And within AI overviews, when they first started showing them, when AI overviews were like 5% of search, they were showing up like 2% of the time. You're like, that's that's not great. Well, then AI overviews became 50% of the search in like two months. And within that, though, it went from 2% to 15%. So it's actually higher than in the old world. But because, you know, it went from zero to 50 and like that was the disruption.

• 1:01:44Speaker 00

  The second we saw that, our takeaway was A, like those problems are gonna be fixed. And B, that's proof that Reddit's actually like more valuable in an AI world because they're showing it more because consumers wanna see it. They liked seeing the answers and the citations of Reddit. So you, that's where you have the confidence with that data science to say, I figured out the tech change. And now like we like the stock even more. And this is how, you know, the narrative, you know, the user numbers are gonna be fine now. And now the narrative is this gets out is gonna be not their unclear AI winner loser. No, like they're gonna be in AI winner camp and that means your multiple goes higher. And the stock went up, you know, a lot when when the market figured this out.

• 1:02:29Molly O'Shea?

  Reddit is one that I find fascinating to watch because I didn't understand why anybody was paying them that much money for their data. Like, it just didn't make any sense.

• 1:02:38Speaker 00

  Well, and the funny thing about that is it's, that's actually changed. Like, the, the thinking, even from Reddit, is changing a lot. Like, what, what happened was OpenAI went out and basically trained on Reddit data, ChatGPT, right? And they, it sounds like may have not asked for permission or done their, you know, they, at that time, it was just a, you know, you were going out and trying to build this model. And so what Reddit did, and, you know, Google did the same thing and all this. And what Reddit did was basically say, okay, you guys, hey, you know, we're not going to sue you, but you took our data, so just pay us a licensing fee. And I think it's ballpark fifty million dollars for Google. So Google pays Reddit fifty million dollars a year to kind of A, have trained in the past on

• 1:03:22Speaker 00

  it, but B, have updated data. And, and ChatGPT does the same thing. So the view was like, okay, Reddit's corpus of data is growing, but like, the incremental, you know, conversations that are happening are pretty small in the comparison of the whole thing. So whatever that deal was in the beginning, like, it's not going to get better, right? That fifty million dollars isn't going to go up. That was the view. I think that's what everyone thought, including the companies. But then, as AI evolved, you started to realize that incremental data that happens is actually way more valuable because, like the shopping assistant example, if you want to build a shopping assistant, and Reddit is one of

• 1:04:06Speaker 00

  the primary sources on the internet where people are talking about products and what's good and what's bad, like, like, there were rumors that Zuckerberg goes and, you know, is hiring people for a hundred million dollars a year to build this model. So if he's willing to do that, what do you think, you know, Google or OpenAI is willing to pay Reddit for the key piece of data that may determine the success of the entire shopping agentic TAM? My guess is higher.

• 1:04:35Molly O'Shea?

  I have one last question. This one is going to be really difficult. Are you ready?

• 1:04:40Speaker 00

  I'm ready.

• 1:04:41Molly O'Shea?

  You're ready? There is some confusion around the name COTU. I know Philippe and Thomas are French. But a previous partner I used to work for would call it Koatoo.

• 1:04:54Speaker 00

  Oh, yeah, that's wrong. That's just factually wrong.

• 1:04:57Molly O'Shea?

  Sorry, Mark. Sorry to call you out, too.

• 1:05:01Molly O'Shea?

  Can you please explain to the class where the name Koatoo comes from?

• 1:05:05Speaker 00

  Yes, so I'm glad I know this one. Koatoo is a beach in Nantucket. So it's a beach in Nantucket. I believe Philippe spent time there, so. Yeah, you know, it's funny, I, my entire time at Koatoo, I've never like heard anyone talk about.

• 1:05:26Molly O'Shea?

  The beach?

• 1:05:26Speaker 00

  But actually, that is, that is not true. The what we're building a, so we're redoing our office. We're basically building a second floor because the firm's expanding. We need more room. And so we're, people were coming up with names of the new, the new conference rooms. And Thomas's idea was to name them Other Beaches in Nantucket. Yeah.

• 1:05:48Molly O'Shea?

  You kind of do need a beach and a hedge fund in Midtown. Why not?

• 1:05:51Speaker 00

  Yeah, well, it's a, as you know, Midtown is like a stormy sea. And so, and every day in the market feels like a stormy sea. So any, any, you know, beach would be, would be good, so.

• 1:06:03Molly O'Shea?

  Okay, well, it's a good way to end it.

• 1:06:05Speaker 00

  Yeah, well, I appreciate you having me. Thank you so much.

• 1:06:07Molly O'Shea?

  Of course, and hopefully you get a podcast studio in this new office.

• 1:06:11Speaker 00

  I think we might do that.

• 1:06:12Molly O'Shea?

  Do it.

• 1:06:13Speaker 00

  If we do, and if we do anything, we're gonna have you on.

• 1:06:15Molly O'Shea?

  Thank you. I was gonna just show up, but I appreciate the invitation.

• 1:06:19Speaker 00

  Of course.

• 1:06:20Molly O'Shea?

  Thanks, Michael.

• 1:06:20Speaker 00

  Awesome. Thank you.

• 1:06:22Molly O'Shea?

  Hey, it's Molly. If you enjoy our interviews, check out our newsletter, sorcery.vc, where we deliver a once a week top deals and tech headlines email, and also go deeper on our podcast interviews. Subscribe to Sorcery today. And don't forget to subscribe to the podcast on YouTube, Spotify, Apple, or wherever you listen. Link in description to sign up.