Uncapped #27 | Vince Hankes from Thrive Capital

Vince Hankes is a Partner at Thrive Capital where he’s worked on investments in OpenAI, SpaceX, Databricks, and Stripe among others. Vince invests across all stages and currently sits on the board of Airtable, Benchling, Console, Isomorphic, Lattice and Rogo. Prior to joining Thrive, Vince was an investor at Tiger Global. We covered: Non-consensus investing Writing billion dollar checks Buying Carvana at the bottom The value of compounding What matters most to Thrive --- Timestamps: (0:00) Intro (0:50) The evolution of Thrive (4:22) Instagram, Github, and Stripe (7:57) Qualitative, then quantitative (9:39) Writing massive checks (16:48) Winning strategies in venture (25:58) Buying Carvana at the bottom (32:50) Managing conflicts (36:13) AI’s impact on the market (42:25) East meets West Coast investors (45:19) Vertical specific workspaces (49:53) Scale and timing of robotics (51:31) OpenAI vs everything else (55:59) What matters most for Thrive --- More on Vince: https://x.com/vhankes https://www.linkedin.com/in/vincent-hankes/ More on Jack: https://www.altcap.com/ https://x.com/jaltma --- https://linktr.ee/uncappedpod Email: [email protected] --- This episode is presented for informational purposes only and does not constitute investment advice or an offer to sell, or a solicitation of an offer to buy, any securities. The discussion herein similarly does not constitute a solicitation with respect to any Thrive fund or an offer of investment advisory services. Investments identified herein are discussed solely for illustrative purposes and there is no guarantee that current or future investments of Thrive will be similar in quality or kind.

• 0:00Speaker 00

  There's a different way of thinking about concentration, which is when you write a billion dollars into a company, you have to have conviction. You can't be like on the fence about is this going to work or not? You have to have almost dogmatic conviction it's going to work. So how do you build up that level of conviction? The wind up period to doing these investments is super long.

• 0:18Speaker 01

  Like years?

• 0:19Speaker 00

  It could be years. I mean Stripe, we made our first investment almost 10 years before we had this big $2 billion investment, where I invested in a company called Isomorphic at the beginning of this year. We spent 18 months getting to know them.

• 0:31Speaker 01

  I'm very excited to be here today with Vince Hankes, who is a partner at Thrive Capital. He's worked on most of the major investments at Thrive, including OpenAI, SpaceX, Databricks, Stripe, a lot of ones people have heard about. So a very impressive run you've had there and I appreciate you doing this with me.

• 0:49Speaker 00

  Thanks for having me, Jack.

• 0:50Speaker 01

  All right, Vince, I want to start with the evolution of Thrive. So the firm is founded in 2009 when you and I are not yet in, not yet out in the world. And it was a $10 million fund. You fast forward to today, it's a $5 billion fund. Thrive invested in Lattice in 2016. At the time it was like 700. So it's been, it's been an incredible sort of rise. You joined in 2019. It feels like in the last few years, like a huge amount has happened. It's been sort of, you know, skyrocketed into new echelons. So can you just kind of like give your overview of like what this journey has been, both while you were there and maybe even kind of like the broader history back?

• 1:28Speaker 00

  Yeah, I mean, it's been a really fun journey to be on. So when I joined, we were, I was the 25th or 26th person. We had just raised a billion dollar fund, which was really an early stage fund of 400 million and a growth fund of 600 million. So still kind of small in today's dollars. And I think we were just starting to get into some of the bigger bets we were making.

• 1:47Speaker 01

  When you joined, did it feel small at the time? Or at the time were you like, this is clearly becoming one of the platforms?

• 1:52Speaker 00

  It felt, it felt small because I'd say, I was coming from Tiger. We were investing in almost a $3 billion private fund. We had a $15 billion hedge fund. And so coming from that pool of capital to then a billion dollar fund felt smaller.

• 2:05Speaker 01

  Yeah.

• 2:05Speaker 00

  And I think the biggest funds at that time were much bigger than we were. And so we weren't kind of in the position of, we're always thinking about leading or doing the biggest checks into a round. We were just trying to really get into the great companies.

• 2:16Speaker 01

  Yeah.

• 2:17Speaker 00

  Which was different. But if you go back like, Part of the evolution that's so fun to think about is Josh was 26 when he started Thrive, which is crazy to think about. And so like a 26 year old starting a venture fund, first of all, it's like, what does that mean? First is, he didn't go to Silicon Valley and set it up. He did it in New York. You know, he was obviously from the New York area, so that makes sense, but it also kind of made you an outsider to the Valley. The people he recruited is not like, who wants to go work for a 26 year old starting a venture fund in New York? So like, people recruited were his friends and kind of the like misfit type people that would go work for a 26 year old. I mean, you know, Miles, like people like that were coming out of college and young.

• 2:52Speaker 01

  It wasn't so, I mean, it turned out to be unbelievable picking of people that when you look, I mean, there was Will Gabor, Will Gabor, Chris Paig, Jared Weinstein, lots of amazing people.

• 3:00Speaker 00

  Yep.

• 3:01Speaker 01

  But all those people did something that was unobvious at the time. So kind of like, when I think about the evolution, a big part of it is the people that have been around the journey for a long time are people that self-selected into this environment that was different. Do you think that actually selected for some, do you think that selection itself was part of why the talent hit rate seemed so interesting?

• 3:18Speaker 00

  Certainly. Like today, we think about it now that we do have a brand.

• 3:21Speaker 01

  Right.

• 3:21Speaker 00

  People want to work at Thrive.

• 3:23Speaker 01

  Yep.

• 3:23Speaker 00

  We think about recruiting as a lot of the people we want to come join the team are not necessarily the people that come inbound to us.

• 3:29Speaker 01

  Right.

• 3:29Speaker 00

  We go seek them out, always be recruiting.

• 3:31Speaker 01

  Yeah, like, how do you get a contrarian minded person now?

• 3:34Speaker 00

  Exactly. It's hard because we are more consensus now.

• 3:36Speaker 01

  Right.

• 3:36Speaker 00

  So a lot of what we think about and look for are people that aren't looking necessarily to work at Thrive. But at the same time, we're trying to set up kind of, the most important thing about our team is how do we be the place that the most talented young people want to work?

• 3:47Speaker 01

  Yeah.

• 3:47Speaker 00

  And if you don't maintain that, then obviously you can't attract those kinds of people.

• 3:51Speaker 01

  It's an interesting thing about, you know, becoming consensus sort of de facto as you scale like this.

• 3:56Speaker 00

  Yeah.

• 3:57Speaker 01

  When like, I know, you know, I know basically the whole team there, and I think everybody doesn't prefer to be that way, but all, obviously are all pragmatist and acknowledge that there's sort of this like self-reinforcing reality when you become this big. So what is the sort of like internal struggle or thinking around this like, you know, rooted in contrarian, doing our own thing, building something out of nothing, but like now you're kind of one of the top groups?

• 4:22Speaker 00

  I think, I do, let's go back to the evolution, because I think it is, and it's kind of been in the journey. Like, people don't know this, but 2012, we invested in Instagram. Okay, it was important for, obviously it got acquired by Facebook because it's a big deal. More importantly, Josh had spent, I think, a couple of years beforehand just trying to break in and get into this hot company by getting to know Kevin and Mike and the whole team. We got in, we got a $20 million allocation. We had a $40 million fund at the time. Yeah. So in terms of like, big, bold bets. Did you put 20 in? Yeah, we put, we put almost, we put almost $20 million into the company. Out of 40. We had a raise a little bit on top because we couldn't put a 50% position in the fund. But like, big, bold bets were a part of the firm since the beginning. Wow. And obviously it was also important for us because no one knew Thrive Capital, no one really knew Josh.

• 5:06Speaker 00

  But then it's like Instagram, this hot company, Benchmark, Sequoia, and Thrive Capital. And everyone's like, well, who's Thrive Capital? Yeah. And so it kind of got us into the game. You fast forward a few years and we invested in GitHub. Okay, well GitHub obviously was this kind of high-flying developer company. All of a sudden, we invested, literally within months, the CEO stepped down. It kind of went from being consensus to consensus like in trouble as a company. Nabeel, who, one of our partners, went in and was interim CFO of GitHub for a period of time. We got to know the business really well, which is part of the whole pitch of us as we deeply partner with you. We started to see the data, meet the people, built more conviction such that we actually made, GitHub became one of the largest investments we ever made in the firm's history at that point in time.

• 5:49Speaker 00

  And we were able to buy all the shares because it was so non-consensus in the Valley. But part of being in New York, part of being an outsider was like, we weren't basing our conviction off of what was happening, kind of echo chamber of the Valley. We were definitely outsiders to the Valley. And so, take that even further, like Stripe, more recently, if you think about the evolution, obviously the quantums have gone up. But Stripe to me is kind of the evolution of this exact same confidence in making these big contrarian bets. Where COVID happened, all these companies were high-flying, obviously then it all went down and numbers decelerated. Everyone thought, oh shit, like, is this over? And if you were really grounded in the numbers, you were scared. Or it looked like an unobvious deal.

• 6:31Speaker 00

  But if you kind of take a step back and say, okay, well Stripe, what is it levered to? It's levered to the growth of payments online and e-commerce. And I said, Jack. What do you think e-commerce penetration is going to be in 10 years from now?

• 6:42Speaker 01

  A lot.

• 6:43Speaker 00

  A lot, a lot. Like, no one doubts that. You know, Kareem has this line, "It's a lot easier to predict the long term than it is the short term." But everyone in that moment, what are they trying to do? They're trying to predict what will Stripe be in two years from now. And so, we went in, we spent all of our time with Patrick and John, we've known for a long time, we spent time with product, all the things that you would think about, not just the numbers, and we decided to lean in. And then what was unique about that, and I think reinforcing to how we've evolved, is we put in almost $2 billion into the company, but they needed to raise five or six. So, we had to then go help them raise the money. So, a bunch of us went out and pitched to other investors why we had so much confidence to put that much money into Stripe. And this is now in early '23, and so the market environment was not go-go, it's coming off of this post-COVID hangover, and everyone to

• 7:25Speaker 00

  us was basically saying, "It looks way less profitable than Ideon, it's not as good of a business anymore. Patrick and John, they're great, but are they really kind of the founders for the next era of the business?"

• 7:36Speaker 01

  It's interesting, because I think you get categorized for that investment as like consensus, compounding investment type of mindset.

• 7:43Speaker 00

  To us, it's so visceral how not consensus it seemed. It was a really good form, like, formative moment for us in what it feels like to continue to double down at scale with independent conviction.

• 7:56Speaker 01

  You sort of described also like an investing mindset that I would traditionally ascribe to like early-stage investing, but applied at super, like, growth-plus stage. Like, you're talking about the founders, you're talking about the product, you're talking about like the long term, and like, not being too close to the numbers. Do you think that, when you think about Thrive's great late-stage investments, it was more of a growth mindset or an early-stage mindset that led to those decisions?

• 8:23Speaker 00

  I think the growth mindset, if you want to kind of call it that, which is basically a shorthand way of saying it's very quantitative and numbers-driven, is important. But our whole philosophy is, we start with qualitative, we develop hypothesis, and then the hypothesis has to be confirmed by the quantitative. And it has to be in that order because if you start with the numbers and you get so excited about the numbers and then the numbers go down, you lose all your confidence. But if you start with the people and what they're doing and the customers and the product and you build confidence and then they miss a quarter or they miss two quarters, you don't react of like, oh shit, you know, my returns are now going away. You try to unpack why and what happened. Is our assumption on the product wrong? And that's what should change our confidence almost. And so I think like, what do I think my superpower is?

• 9:04Speaker 00

  I spent a lot of my career on the financial side, but now at Thrive, I spent a lot of it empathizing with how do you build a company? What does it mean to hire an exec? How do you build a team? If you kind of intersect those two things, I think that's where our sweet spot is. You know, like is Databricks, Databricks we did a year ago. Why was that a great, you know, time to invest in the company? Well, I'd be like, oh, it's growing really fast. It's got the tail ends of AI. But I think the most important point, it became clear that it was going from this single product company to a multi-product platform. And the value of the platform is much bigger than the value of the single product. And so inherently, there's a mispricing because it's a lot harder to build a multi-product platform than it is a single product.

• 9:39Speaker 01

  You talked about how like, you know, the Instagram investment, whatever number it was, was a huge percentage of the fund. You've obviously made a lot of those like very bold bets early days, but recently too, you've made bets that in, you know, maybe not betting the firm, but are much more aggressive than most venture firms. I think one of the reasons people, you know, often talk about founder-led companies having advantages because like people are willing to like risk it all many times. Do you feel like you all are still doing that because, you know, it's a founder-led firm and you have those dynamics? Like, is it still, is that the sentiment or are you now in a place where you're like, we can't risk the firm anymore?

• 10:16Speaker 00

  Well, I think this is, you know, this is the mentality of why doing what we do is really easy to say, but hard to do. Like in reality, to put that much capital into a single company.

• 10:26Speaker 01

  Yeah.

• 10:27Speaker 00

  It's scary.

• 10:27Speaker 01

  I mean, you've done it with Stripe, Databricks, OpenAI and obviously you guys have a lot of SpaceX.

• 10:32Speaker 00

  Yeah.

• 10:32Speaker 01

  You guys have a lot of capital, but on as a percentage basis, you're very tied to these companies.

• 10:36Speaker 00

  And we think about an ideal growth fund for us is 10 companies. And ideally it's 10 companies. That's it. It's highly concentrated. And why? Because if you believe the power law is true, there's. You know, in some sense, it's easier to kind of catch a company that's really established going to 100 billion or 200 billion than it is to try to pick the breakout company from a pack of a few thousand. And so what we're really trying to do with these big concentrated bets is find what are those great generational technology companies?

• 11:02Speaker 01

  Yep.

• 11:02Speaker 00

  And then concentrate all of our capital into them.

• 11:05Speaker 01

  Would you rather try to pick out of 10 billion dollar companies going to 100 rather than pick 1 billion dollar companies going to 10?

• 11:10Speaker 00

  I think so. I did this, we had a thing with RLPs more recently, and so I cut some of the data because this is something that people talk about a lot. And it was basically, what's the number of trillion dollar companies, 100 billion dollar companies, 10 billion dollar companies over the last decade? And what I see is a decade ago, there were no trillion dollar companies. Zero. The biggest tech companies were 300 to 500 billion dollars large. Fast forward today, there's 10, you know, I think that are around over a trillion. The top are 3 to 4 trillion. Okay, in 10 years from now, what will the biggest be? Probably bigger than that. I mean, all of this stuff that's benefiting AI technology means these companies will get bigger. But the kind of thing that's missed in this analysis is there's been 75 companies in the last decade that have reached 100 billion or more in value. That's a lot of companies. There was only a few hundred in the 10 billion dollar bucket.

• 11:53Speaker 00

  So if you think about picking the 75 out of a few hundred is much better odds than trying to pick, you know, the thousands of unicorns that will get to 10 billion.

• 12:01Speaker 01

  Yeah, I mean, this actually confirms kind of an intuition. I think a lot of people have been thinking and saying, which is that like the winners are getting bigger than ever, which basically what you're saying is the number of 100 billion dollar companies has grown much faster than the number of 10 billion dollar companies.

• 12:14Speaker 00

  Yeah, or like think about it a different lens, more product centered lens, you know, Stripe. Obviously, they dominate in online payments, but now we're talking about stable coins or AI in payments. Who's going to be the company that wins or takes a lot of market share there? Is it going to be Stripe or is it going to be startup? I hope a lot of startups have a shot at gold because that's the nature of what we believe in. But right now, guess who's really excited about it and investing a lot of money at it? It's Stripe. And they have amazing founders, a great technology stack, great talent. And so I think what people underappreciate is these really well-positioned companies that are getting to scale, they benefit from the scale, just like Google and Microsoft and Amazon and Facebook all benefit from that same scale.

• 12:53Speaker 01

  Why is that happening now different than it was happening 10 years ago? Like, why did these dynamics not exist in 2015 in the same? You know, magnitude.

• 13:04Speaker 00

  I think just people don't appreciate the power compounding. The internet, the iPhone came out 15 years ago about, you know, a little bit more than that. And so mobile internet, I think it's not that old. And the great, everyone wants things to happen in a short period of time, but the reality is most of these companies are 10 or 15 years old. It's actually, if you looked at the, we obviously studied a lot of these companies at scale. The vast majority of dollars of enterprise value that get created are in the second or third decade of a company. And so if you think about all of the great companies we talked about now, Stripe, Airbnb, DoorDash, Uber. These companies were all built out of the mobile era. We're now getting into the second decade of their lifetime. And that's where we know historically, if you look at Shopify or Salesforce or Tesla. The second and third decades were far more lucrative in value creation than the first decade.

• 13:48Speaker 00

  Well, now all these companies are coming of age to the second decade. And I think you will realize that scale is really powerful and it just took time for them to blossom.

• 13:55Speaker 01

  Do you think that same thing ought to happen with new startups 15, 20 years out? In other words, like, is what you're saying, does it describe just that all of tech is going to do really well? Or is there some particular reason why right now investing in the big companies is better than investing in these small companies? Some subset of which will compound forever too.

• 14:15Speaker 00

  I don't think this is some rising tide lifts all boats. I think it's more of an expression of the nature of technology is there are benefits to scale. So like, if you get to scale, you have more distribution, you can reach more customers, you can ship new products, you can kind of compound on yourself. By the way, in the talent flywheel, you know, obviously a lot of these companies started with great talent and they developed it. But now if you're a young person, where do you want to go work? You want to work at OpenAI or SpaceX?

• 14:41Speaker 01

  Which by the way, wasn't true 10 years ago. Like, it didn't used to be that the OpenAI sized companies 10 years ago were appealing in the same way that these are now.

• 14:48Speaker 00

  Maybe, but the OpenAI sized companies 10 years ago was Google.

• 14:50Speaker 01

  Yeah, I know, but recruiting against, recruiting against Google as a startup was, was doable.

• 14:56Speaker 00

  It was doable.

• 14:56Speaker 01

  OpenAI right now is very hard.

• 14:57Speaker 00

  I think, in general, I think the market's just got a lot more competitive in technology. So what I'd say is, I don't think this is a rising tide lifts all boats. I think there are a select number of these companies that will benefit from the scale. And when they're very founder driven, they will benefit as they get bigger. And we know with the power law that there are kind of accumulated advantage to those companies. And so all we're trying to do is map our fund strategy to the power law, which is to be concentrated in these really phenomenal tech platforms. I think on the like, you know, the whole asset class in general has matured. So like 15 years ago, how many companies raised a hundred million dollars in capital? Not that many. Now, I think, I think the numbers are something like four or 500 companies a year raise at least a hundred million dollars capital.

• 15:35Speaker 01

  It's crazy.

• 15:36Speaker 00

  That's a lot. Like, how many companies do you know that you would put a hundred million dollars into?

• 15:39Speaker 01

  I don't know, but the 500 a year is a lot.

• 15:41Speaker 00

  And so I just think about it is there's a lot more saturation in the game on the field for picking out the billion dollar company. Like that same, you know, because we were pulling for the same LP event. You know, the average growth check, so say a hundred million dollar plus round is a hundred fifty million dollar round at a billion to two billion dollar valuation.

• 16:00Speaker 01

  Yep.

• 16:00Speaker 00

  At 20 to 100 times revenue.

• 16:02Speaker 01

  Yep.

• 16:03Speaker 00

  Okay, well, that doesn't, to me, that's not growth investing. That's kind of like large check venture investing. And you hope it works, but the likelihood is the vast majority will not work.

• 16:11Speaker 01

  And so you're, in your view, the growth, the, the real growth investing starts at more like the five to 10 billion dollar valuation rounds and things have nine figures of revenue.

• 16:19Speaker 00

  Or said differently, I think about less quantitatively and more, the real growth investing happens when you can actually wrap your head around something that's solidified. And then you can look at the data to substantiate it. And if you can ground yourself in the product and what's solidified and then substantiate it, okay, now we have a baseline that we can work from.

• 16:35Speaker 01

  Yep.

• 16:35Speaker 00

  But if you're investing in a company that's been around for three years and has, you know, 50 million in revenue, that's, I mean, it's amazing momentum. But as you know, building a company, you know, a lot of things can break from there.

• 16:47Speaker 01

  Yep. Given this backdrop, what do you feel like are the winning strategies in venture like now? Obviously, there's this, I don't know how you'd categorize what Thrive does, but like large check concentrated investing and like breakout winners. Are there other strategies other than Thrive that you're very bullish on now?

• 17:07Speaker 00

  I mean, I'm obviously most bullish on the strategy we're executing on. I think there will always be a place for very focused early stage investing. Because at the end of the day, where else can you go put in 10, 20 million dollars into a company and get a billion out? And the reality is if you're good at finding people early and you can help them build companies and you can get a large chunk of their company, you'll be able to drive great returns. I personally think that's gotten a lot harder because of how competitive it is. But there will always be a market for that. So what are you skeptical of now? Or like, what's the hardest part? I'm skeptical. I mean, I think we have bar, we really barbell our strategy. We're either early with companies and we work alongside, we roll up our sleeves. We own a decent chunk of the company. Or we invest when it's kind of becoming a clear platform company.

• 17:52Speaker 00

  We do do stuff in the middle. Like, we call it breakout companies. Like, we invested in Cursor. It's obviously a phenomenal team. There's so much momentum. It's kind of got the zeitgeist and this AI moment of coding. But like, As and Bs are rare. No, but investing in Cursor in some sense should be the exception because that part of the market is so competitive. Yep. There's so much capital chasing these 500 to $2 billion companies that really, a lot of them don't even have product market fit. But we're capitalizing them like they are a company with product market fit and growth. And so I think that, to me, is where I'm least optimistic. Not because I don't think there's going to be winners, there will be winners. But risk of capital loss matters there. If you're investing $10 million checks or $5 million checks, you can afford to have zeros. If you're investing $100 million checks, Yeah. it's hard to have zeros.

• 18:36Speaker 00

  And if you look at the, if you look at the composition of a lot of these growth funds that are $2, $3, $4 billion big, they have 30, 40, 50 investments in a growth fund, which means the average check in that fund is $70 to $100 million. Yeah. But why is it, why did we get to that point in time? Well, because as these funds got bigger in scale, they hired more partners. But it's like the law of people. If you have more partners, you do more deals. If you do more deals, you're less concentrated. It's that, it's that simple of an equation. And if you're not very concentrated and you have a bunch of $100 million checks into mid-stage companies, I think it's just hard. Yeah. How many people work at Thrive now? The whole firm, something like 75 people. Yeah. We're about eight investors. Eight investors, yeah. So this is a good example, like, RLPs. Take our assets and they divide it by investors and they say, okay, put you on a benchmark. Where do you rank?

• 19:21Speaker 01

  Yeah.

• 19:21Speaker 00

  And they look at it and say, wow, you guys have a lot of assets per investor.

• 19:23Speaker 01

  Yeah.

• 19:24Speaker 00

  I'm like, that's the wrong way to look at us. You should look at, because we don't, we don't think about it as, oh, each dollar requires more work. It's basically the investment decision. Each company is a commitment. So if you just flip the numerator of that equation from dollars to companies.

• 19:36Speaker 01

  Yeah.

• 19:37Speaker 00

  We make 12 early-stage investments a year and we make a handful of growth bets a year. That's 18-ish, round numbers.

• 19:43Speaker 01

  Yep.

• 19:44Speaker 00

  On eight people.

• 19:45Speaker 01

  Yep.

• 19:45Speaker 00

  So we're roughly two, maybe three investments a year a person.

• 19:48Speaker 01

  You just put a lot of zeros when you send the check.

• 19:50Speaker 00

  Yeah, exactly.

• 19:50Speaker 01

  That's a good way to do it.

• 19:51Speaker 00

  But, but, but seriously, but that, that, if you, okay, then just on the same benchmark, like who else does two investments a partner a year?

• 19:57Speaker 01

  I mean, there are firms that do that, but yeah.

• 19:59Speaker 00

  But, but it's very different, I think, in the philosophy relative to a lot of the other growth plans that we compete with.

• 20:03Speaker 01

  So actually, when I was asking, you know, the number of people who work there, I was thinking of it this way. Because I was thinking of, let's say, 10 concentrated positions. You know, 12, you know, eight investors, whatever. How that, I guess the net of that is most of the time you're, you're making new investments rarely.

• 20:18Speaker 00

  Yeah.

• 20:19Speaker 01

  So like, what does that look like for you? Like, what's your mentality, given the, I guess, really the infrequency of decisions?

• 20:26Speaker 00

  I mean, we turn over a lot of rocks. I spend a lot of time looking, evaluating, trying to get to know people. Like, you know, there's a different way of thinking about concentration, which is when you write a billion dollars into a company, you have to have conviction. You can't be like on the fence about is this going to work or not? You have to have almost dogmatic conviction it's going to work. So how do you build up that level of conviction? The wind-up period to doing these investments is super long.

• 20:51Speaker 01

  Like years?

• 20:52Speaker 00

  It could be years. I mean, Stripe, we made our first investment almost 10 years before we made this big $2 billion investment. Where I invested in a company called Isomorphic at the beginning of this year. We spent 18 months getting to know them. But how did that journey work? We were partnering deeply with OpenAI. We were thinking about what are the other domains where it might not be kind of on the path to AGI for the core labs? Life Science was one of them. I got in touch with Isomorphic almost just for learning, just to meet people in the industry. And that kicked off 18 months, almost two years of getting to know the company, which then kind of cracked the door open to investment. And so if you look at my calendar, my calendar looks like meeting a bunch of early-stage companies. And then a lot of irons in the fire on new initiatives. And then obviously I spent a lot of time with our portfolio and internal and so forth.

• 21:35Speaker 01

  Is it likely that the next large investment you'll make, you already know that company well? Like, are you basically working out of a relatively confined list and you're definitely going to invest off that list?

• 21:46Speaker 00

  Yes.

• 21:47Speaker 01

  Yeah.

• 21:48Speaker 00

  I think what people underappreciate about the motion to do this is how much work it takes to go create the opportunity. Like, you know, we started in New York, scrappy, having to go get the opportunity. I think a lot of the way ventures have been built is you go to Sand Hill Road, you receive the pitch. We need to raise money. Oh, I have money. Let me do diligence for a month. And that's how it works. That model, to me, is not competitive anymore. You know, we are going, if you look at Stripe or Databricks, we are going to the company. We are saying, this is all we know about you. It's a lot, outside in, inside out. We are willing to make an investment, but we want to kind of engage with you on these handful of things. And then we go do it.

• 22:26Speaker 01

  Yep.

• 22:27Speaker 00

  That's a very different motion. And by the way, there's no process. Like, we don't wait for a process. We kind of have to wait for our point in time. And sometimes things aren't clear, and so we don't do anything. But in that moment, what am I doing? I'm spending time learning about it, learning about what happens with product, customers, people. You get to know people that join the team. You get to know more of the team. So like, a lot of times investors only spend time with the CEO. CEO is one person in the company. You know, do they spend time with the head of engineering, the head of product, with the sales leaders, with people lower than that? You know, you, you really learn how clear the flow of information is in a company by meeting a lot of people on the team. Are people on the same, singing from the same song sheet?

• 23:03Speaker 01

  Yep.

• 23:04Speaker 00

  Do they understand the decision-making framework? You know, the best, the best companies, it's super simple and it just ripples down and everybody knows how to act.

• 23:11Speaker 01

  One of the challenges for a lot of groups, though, is if they can't, if they're not capable of writing a billion-dollar check, these late-stage companies aren't going to give them the right to go spend that kind of time. Because there's a small list that can, you know, the kind, the rounds you're talking about, you know, Databricks round, Stripe round, an OpenAI round, like, you just can't price those rounds. So you don't even get the right to spend that kind of time otherwise. So I guess part of your argument basically here is like, the scale drives a lot of the competitive advantage.

• 23:39Speaker 00

  Yeah, I want to play in a game on the field that's less competitive. And I don't know, how many firms do you know that can write a billion dollar check into a company?

• 23:45Speaker 01

  Three, four?

• 23:45Speaker 00

  It's not that many. So I'm competing with a handful, two handfuls of people versus if you're trying to write a hundred million dollar checks into the growth stage or ten million dollar checks, you're competing with at least an order of magnitude or two orders of magnitude more firms.

• 23:57Speaker 01

  A hundred?

• 23:58Speaker 00

  Yeah, maybe that won't last forever and people will get, you know, capable of doing what we're doing. But today, it's a more advantaged game in the field because there's just not that many people that can compete.

• 24:08Speaker 01

  What's interesting is I think there are a lot of firms in sort of like the size rung below, call it one to three billion dollar firms, who I've spoken with, who I think see what you're doing, what Founders Fund's doing, maybe Green Oaks, I don't know what the number of firms would be, but, and want to. But I think it's actually very hard still, even if you're close to it. Do you know what the thing is that you think, you know, like what's the dominant thing it takes? If you're a leader of a one or two billion dollar firm to get to this? Like what is that, what is the thing preventing more people from doing this?

• 24:45Speaker 00

  It's a question we think about. I do think while some of this seems easy to kind of, you know, articulate as a strategy, as we talked through our journey, part of it has been a long buildup to get to the level of confidence to do that. Because it's unnatural for a single partner to want to make that big of a bet, because it feels like career risk every time you do it, right? And so just in general, building a culture that rewards this, I think is not something you can do overnight. Which kind of goes to the like, why is it hard for firms to do? There's politics. Like, we have a founder-led firm. And you can debate, you know, there are pros to that and cons to that. But I think a lot of the pros are what enable us to do this, which is at the end of the day, we have a super small team. We have clear direction and we can go make these decisive, big, bold bets.

• 25:29Speaker 01

  Yep.

• 25:30Speaker 00

  If you're at a firm that's governed by a handful of people and one partner wants to do it, or even one partner in the handle doesn't want to do it.

• 25:37Speaker 01

  Yeah.

• 25:37Speaker 00

  What happens? Especially if it's viewed as firm reputational risk.

• 25:41Speaker 01

  Yeah.

• 25:42Speaker 00

  Oh, you write a billion dollars into this company. What happens if it doesn't work? Is it going to tank the firm? Well, now, all of a sudden, you have bureaucracy that creeps into decision making. And I think it's hard to compete, partially just because most firms have that kind of setup. They don't have kind of a singular, small team that makes decisions.

• 25:58Speaker 01

  There's a good segue. I want to talk about Carvana.

• 26:00Speaker 00

  Yeah.

• 26:01Speaker 01

  Which was, I thought, one of the most interesting and in the long, you know, in the full arc, it was extremely impressive to me. Where basically, you made an investment in Carvana. I think it was public when you initially did it, but you obviously knew the company for a long time. But you make this investment. It goes down like a lot. And you buy more, you hold, and it ends up doing great. You distribute shares, you know, and you crushed it.

• 26:25Speaker 00

  Yeah.

• 26:26Speaker 01

  But like, that seemed like a nail biter to me because you're, you know, it was a lot of capital. It was a public company and you know, you're Thrive, you're not a public, you know, for the most part, obviously you do it. But I was just like, and you know, and you were, you know, you know, partially proven, but also earlier in your career when you did it, and it worked. So just like, talk me through that whole thing.

• 26:46Speaker 00

  I mean, I think in a lot of ways, this embodies who we are as a firm. You know, the journey of Carvana wasn't just random. Like, I think some people will say, oh, you guys saw the public markets go down and you went and moved on a company. It's like, just like, it's not how, you know, we're not just looking to go do random things. I first got to know Carvana, when I was at Tiger, one of my closest friends was the guy who was looking at it, spending a lot of time with it. So I got to know it then. When I joined Thrive, it was on a list of things, but it kind of traded to a price of public markets where it didn't maybe make sense. And then the post-COVID kind of tech cycle happened. And it was one of the names that went down 50%.

• 27:21Speaker 01

  Yep.

• 27:22Speaker 00

  In six months. And so that kind of ears went up. What are the opportunities? Well, the public markets were moving faster than the private markets. And so one of the things that's nice about our model is, okay, I can write a seed stage investment, or these big late stage, or I can go to the public markets. Well, the public markets move faster than the private markets in terms of pricing. And so we went and spent time on it. But like, going back to the Stripe analogy. A lot of people looking at the company were kind of grounded in, okay, well, the numbers are turning, there's a cycle. If you just looked at the product and the team, who I've gotten to know for a while, it was very clear that companies invested billions of dollars in infrastructure to build out this logistics network that makes it a great company. So it's not just an online listing for cars, it's a logistics company, which is its core

• 28:06Speaker 00

  advantage. The team, you know, is kind of an amazing story. If you look at the LinkedIn profiles of the people of Carvana, they're people that have been there their entire career. And they've tried to hire Amazon execs and have them come in and it hasn't really worked. And they've kind of found this way to self-develop talent that's super unique. And so a lot of the things we got excited about were that. And as it gets to scale, as a business gets better, as it gets bigger, more inventory you have, more people that convert, more people that convert, the better your economics are, the better your economics, the more you invest in that whole flywheel and it spins and spins and spins. And so we made an investment, thinking like, this is one of these could be generational giant companies. I think we first bought shares, it was like a 10 or 12 billion dollar company. And then these car cycle turned, they actually did an acquisition financed entirely by debt, which was, you know, we don't deal up with leverage in the private markets. And so there

• 28:51Speaker 00

  was definitely learnings from that. And the combination of that and a cycle and burning money per car sold meant that the business kind of completely unwound in a short period of time. I mean, the stock went down. Like all the way, like 90%, right? 90 plus percent. So obviously, that's not a fun journey to ride down, in particular because when you watch it get marked every day. Yeah. Like, when you do a contrarian investment in the private markets. Yeah. Your friends might give you, you know, some crap about it or grief about it, or like people you talk to are LPs. But when you're investing in a public stock. Everyone knows every day. Every day you wake up, down 5%, down 4%, down 5%, and you have to answer the question of why. Yeah. Which, if that happened in the private markets, no way. No one could do this job. No, yeah, everyone would sell their shares. Yeah.

• 29:34Speaker 00

  But, you know, where this, where I think we really. Had an advantaged mindset is this was the same period of time that we were working with private companies and what were we doing in private companies? We were going through the, you know, get fit era of private companies. Everyone hired way too much in COVID and now needed to restructure their companies or let go of people and right size the P and L. And so that's what Ernie and Carvana did. They basically said, we can't focus on growth anymore. We have to do a whole 180 shift to focus on profitability. So the whole lens you have to look through the company has changed. It's just like if you were operating, you know, a company, which you were or Lattice, you know, through that period of time, and you said, growth has gone down. Yes, you want the company to keep growing, but during that moment in time, the only thing that matters is getting kind of the trains on track and making sure you're right size in the company for what it is.

• 30:19Speaker 00

  So the lens we started evaluating Carvana through was that lens. They were making a tremendous amount of progress. And so by the end of that year, stock was down a lot, but through the dimensions we were evaluating on them, did they have control on the levers of operating the company? The answer was kind of unequivocally yes, and they were making progress. Now, it wasn't fully where they thought they could get it, but it was making the trend line was very good. And so we ended up doubling the number of shares we bought the company.

• 30:42Speaker 01

  At a very low price.

• 30:43Speaker 00

  For a fraction of the price.

• 30:44Speaker 01

  Yep.

• 30:45Speaker 00

  And so there's also this combination, I think is less.

• 30:46Speaker 01

  Which, by the way, that's a hard move to do. Like, you know, the knife has fallen all the way.

• 30:51Speaker 00

  Psychologically.

• 30:52Speaker 01

  That was the moment that I was like, this is crazy.

• 30:53Speaker 00

  Yeah, well, I think what you learn, even if something goes down 50%, it can still go down 90%.

• 30:57Speaker 01

  Yeah, and after it's gone down 95 more is another halving.

• 31:00Speaker 00

  Yeah.

• 31:01Speaker 01

  Yeah, it's tough.

• 31:02Speaker 00

  But I think, you know, what you realize is in private markets, people don't think about the concept of risk reward that much. But in the public markets, everyone talks about it and the sharp ratio is a thing and you can measure it. And so what we were able to do is double our position size and shares for a fraction of the capital. And so the risk adjusted bet we were making on the data points we had were actually very good. And so we were kind of isolating what we were betting on. And in the fullness of time, obviously, it's really worked out. But I think it took having the ability, one, to operate in a culture where people are used to making big, bold bets. And if you're not used to that, I would have got fired or we definitely would have sold the shares.

• 31:39Speaker 01

  For sure.

• 31:40Speaker 00

  Then you have to have an environment where people aren't just like nitpicking the numbers. Because if all people are doing is nitpicking the numbers, we were going to sell. But we have environments very much grounded in the product and people believe in the product. I don't know if you ever bought a car, used car, but like used car dealers are literally the canonical example of what you don't want to be in sales. And so having a pure transparent online experience is the epitome of kind of what a quality product experience is in this industry. And so people believed in that at Thrive. The number of people like, oh, I bought a car on Carvana and we're so excited about it and sent it to our Slack channel. There were a lot. And so I think people believed in the product and it enabled us to do this. And then in the fullness of time, obviously.

• 32:15Speaker 01

  And it's a good market. I remember at the bottom, I was texting you every day, there's cars everywhere I go. It's a big town.

• 32:20Speaker 00

  It's a big market.

• 32:20Speaker 01

  It's a big market.

• 32:21Speaker 00

  There's cars everywhere.

• 32:21Speaker 01

  I just think it's amazing that you were, the buy at the bottom, I think is what impressed me the most and the ability somewhat is you, but mostly I'm going to give credit to the firm to allow you to do that. I think that is hard to have.

• 32:34Speaker 00

  I think it's a firm thing. I mean, obviously I, going through it personally is, is hard, but I do think the whole firm went through a lot. Our LPs asked about it a lot. Everyone paid a tax for us doing this and I think in the fullness of time.

• 32:46Speaker 01

  Yep.

• 32:47Speaker 00

  We've benefited from it, but in the moment, it's really hard.

• 32:49Speaker 01

  How important is like managing conflicts? Like for Thrive, basically like, you know, you've got to invest in such, you're doing so few with such a large fund that you've got to be investing in like big winners with most of your capital. If you pick something earlier, you conflicted out, like how do you manage?

• 33:05Speaker 00

  Yeah, we take this super seriously.

• 33:07Speaker 01

  Cause like if you do a series A in a company, you can't go do a series D or E or F in something else, right?

• 33:12Speaker 00

  It's part of the calculus. But if you look at the market today, a lot of investors, it's just by the index across the companies that are working.

• 33:18Speaker 01

  Yep.

• 33:19Speaker 00

  And so they don't care about conflicts. And for us, because we're not doing a lot, we implicitly are making kind of a commitment to the companies that we are all in on your company. Cause like a founder's all in on the company, we're going to be all in on this investment.

• 33:28Speaker 01

  No, I'm just thinking it's one thing if you're, if it's OpenAI or SpaceX, it's one thing.

• 33:31Speaker 00

  Yeah.

• 33:32Speaker 01

  And you know, you can't go invest in Blue Origin and that's, I feel sad for you for that, even though it's obviously a good company, but you're in SpaceX. But when you go and invest in the series A of. You know, an ERP or a CRM or whatever, is that, is the category done for you at that point?

• 33:47Speaker 00

  It's not done, but this is, this is, this is the, when people talk about the advantages, we, I think about the advantage of full stack investing, this is maybe in the disadvantages of it. You know, whereas if you're just an early stage investor, you look at a seed or the A, maybe the B. If you can't get it there, you never think about it again.

• 34:04Speaker 01

  Yeah.

• 34:05Speaker 00

  Oh, it's in your, you know, anti-portfolio kind of thing. If you're in our shoes, it's like, I can invest at the seed, the A, the B, the C, the D, but it's public.

• 34:13Speaker 01

  Yeah.

• 34:13Speaker 00

  Who knows when?

• 34:13Speaker 01

  Yeah.

• 34:14Speaker 00

  And so we have a much-

• 34:15Speaker 01

  You can take it private.

• 34:16Speaker 00

  Exactly. We have, but seriously, like-

• 34:17Speaker 01

  No, I know.

• 34:18Speaker 00

  But this happened, I mean, we're joking, but like, this happened in this Thrive Holding strategy that we announced. What is it? We ended up raising a billion dollars in a company. It's not a fund, it's a company. And why did we do that? People are like, oh, well, you're expanding strategies and you're just, it was very organic. We started looking at accounting AI companies.

• 34:38Speaker 01

  Mm-hmm.

• 34:39Speaker 00

  And we were, you know, one of our partners is very good friends with this guy who's running this accounting role strategy. And so we started talking to them about AI tools. Why? Because we're just looking at early-stage AI companies. You know, we started partnering more with them, we thought their thing was interesting. We wrote a growth investment into that company. The technology started working, our conviction went up. And we all of a sudden said, okay, well, wait a second, what's the best way to play accounting in AI? Is it to invest in a software company early?

• 35:07Speaker 01

  Or be the accounting firm?

• 35:08Speaker 00

  Or be the accounting firm. Because we're taking this kind of scrutinizing lens from all sides of the equation, we decided that's the right way to do it. And so also the right way to do it is not in our fund structure, because these assets need a lot of time and you have to do different things than you do in a typical growth fund. And so we raised a dedicated pool of capital towards that strategy. But the genesis of it is very much looking full stack at a company.

• 35:30Speaker 01

  Yeah.

• 35:30Speaker 00

  Which I think is very different. By the way- There's $800 million of venture investing going into the software tools for accounting.

• 35:36Speaker 01

  Really?

• 35:37Speaker 00

  And so, yeah, so we're riding the R and D dollars of the entire industry as the service provider. And accounting sticky, are you going to change your accounting provider because they have 10% lower price?

• 35:45Speaker 01

  No.

• 35:46Speaker 00

  Probably not. Now, the risk is, going back to the competitive stuff, if these startups are so successful that they radically change the cost curve, that you can take your business and go to ChatGPT and do your accounting for 10% of the cost, maybe you'll change. So one risk in our discussion of this is if the change is so radical, should we be doing it now? Or should we be waiting?

• 36:04Speaker 01

  Yeah.

• 36:05Speaker 00

  And I think our assessment of accounting is it was not going to be as radical as it could be. And therefore you actually want to be the service provider because you'll capture the value.

• 36:11Speaker 01

  Yeah. In general, across sort of functions and verticals, do you more fall into the camp at, you know, the moment, you know, let's right now, September 2025? Are you more in the camp that like most jobs are going to be completely overhauled? People are going to have to find new stuff. AI is going to do things end to end in legal, finance, healthcare, et cetera, et cetera. Or are you like, this is just like super sick software and everything's going to get more efficient? Do you think about this question at all?

• 36:39Speaker 00

  We do. I'm probably more in the latter camp.

• 36:45Speaker 00

  I just think we're also humans and in a lot of places, you know, we want to deal with humans, not with software. There are some places where I actually think we'll prefer to deal with software, like customer support is a good example.

• 36:55Speaker 01

  Yeah, of course.

• 36:55Speaker 00

  If, if you're United Airlines.

• 36:57Speaker 01

  Yeah, you don't ever want to talk to somebody.

• 36:59Speaker 00

  But I can call a number and get an instant response from an AI.

• 37:01Speaker 01

  And I don't have to wait ever.

• 37:03Speaker 00

  That's amazing.

• 37:03Speaker 01

  Yeah, of course.

• 37:04Speaker 00

  And so in some functions like that, I think it'll probably shift towards software.

• 37:07Speaker 01

  Yep.

• 37:08Speaker 00

  Now, by the way, there's going to be abstractions of that where rather than doing the actual job, you're going to be managing the system.

• 37:13Speaker 01

  Yeah.

• 37:13Speaker 00

  And so those people will get kind of upgraded in what they're doing. But in certain things like, I don't, I think the value a lot of times is with the humans doing it. And so I think making them techs more efficient is better. Like take creative. Are we going to automate away all the creative people? Probably not. Are we going to make them 10 times as productive? So there's 10 times more creative content?

• 37:31Speaker 01

  I mean, I would guess there's a certain type of creative content that will get automated. And then there's a certain level of it that won't.

• 37:36Speaker 00

  I think more is like you lower the floor of entry. So now someone who wasn't talented enough could probably do it. So they can take their culture and lens and now do it.

• 37:44Speaker 01

  Yeah.

• 37:44Speaker 00

  And then you also increase the output of the people that are really good at it.

• 37:47Speaker 01

  Yeah.

• 37:47Speaker 00

  I don't think you really, it maybe eliminates people on the margin.

• 37:50Speaker 01

  Yeah.

• 37:50Speaker 00

  That you don't need, but I just, I think the vast majority is make people a lot more efficient with their time.

• 37:54Speaker 01

  So you basically, so far you've listed, you know, you, obviously we all believe in like, not search, but like, you know, chat. We all believe in support. I think code gen, although we could talk about that a little bit more. Any other areas that you're like quite bullish on that you're like, this is, this is working now and is gonna, you know, go very far?

• 38:11Speaker 00

  I think the, the thing I'm most bullish on that seems early and broadly, the market hasn't acknowledged it yet is life science. Like drug development should radically change.

• 38:21Speaker 01

  On what dimension do you think it will, will?

• 38:23Speaker 00

  Well, the reason we invest, this company, Isomorphic, started inside of Google, Demis Hospice, who runs Gemini. This is his kind of second project or company. And he won his Nobel Prize for the work he did on protein structure prediction. And so that has now morphed into this company. And the entire objective, well, the mission of the company is cure all disease. It's a pretty big mission.

• 38:44Speaker 01

  It's a good mission.

• 38:44Speaker 00

  It's kind of, it's, it's one of the only companies on portfolio that I think about is having the potential size as OpenAI. I mean, I think it is truly that, if you, if you have.

• 38:52Speaker 01

  Yeah, of course, if you could do that, it's huge.

• 38:54Speaker 00

  It's trillions of dollars.

• 38:55Speaker 01

  Yeah.

• 38:56Speaker 00

  And then when you go spend time with them and what they're working on, you know, the objective is we're gonna take entire wet lab of experimentation and simulate it computationally. Well, if you do that, you flip the entire model of how drug development works on its head. Rather than having this kind of waterfall like.

• 39:12Speaker 01

  You just do it all on a computer.

• 39:13Speaker 00

  Yeah, but now the speed of iteration is different, the scale which you can run computer that's different. And so.

• 39:18Speaker 01

  What needs to be true for that to happen? Like what needs to be different in the future for that to work?

• 39:23Speaker 00

  A lot of things, which is why this is such an interesting problem to work on as a company. Obviously, there's the AI part of it today, which is how do you take all of this process and embody it in a model with the right data and results and stuff? So you can, at the end of, at the end of a computational run, get a good drug. That's a very hard problem. But even once you do that, then you have to run it through trials because it stays regulated.

• 39:43Speaker 01

  Yeah.

• 39:43Speaker 00

  So you can't just come and put drugs into people's bodies in the US.

• 39:46Speaker 01

  Which is gonna take the same amount of time.

• 39:48Speaker 00

  Yeah, and so what's, what's another problem we're working on?

• 39:50Speaker 01

  Regulation.

• 39:51Speaker 00

  How do you work alongside regulators to change the way the FDA thinks about it? Because the, the top of funnel might go up a lot.

• 40:00Speaker 00

  That's another thing. How do you, how do you find people with disease?

• 40:03Speaker 01

  Yeah.

• 40:03Speaker 00

  How do you look for the right biomarkers? We can use AI for that, though. And by the way, there's a huge, there's a huge kind of upswing of startups that are working at Daniel X company. Like, let's go scan your body, take your blood, do it in a high-class experience. That stuff will become more important as you get better drug development because you're going to need better biomarkers to target the right people with the right diseases. So this time from identification to cure is extremely compressed. That, to me, is an area that it feels far away in sci-fi when we talk about it this way.

• 40:34Speaker 01

  Yeah.

• 40:34Speaker 00

  When we go spend time with these companies, the rate of progress feels very early, you know, OpenAI oriented.

• 40:41Speaker 01

  How about like CodeGen? And actually, maybe one of the things I'm curious about is like, can you talk about like the stack from a cursor subscription down to the middle? And like how the, you know, 20 bucks, you know, moves?

• 40:55Speaker 00

  I mean, CodeGen is so fascinating because it's one of these areas where there's been extremely high return on marginal intelligence, to use a fancy word.

• 41:04Speaker 01

  I like that.

• 41:05Speaker 00

  You know, and I'm paraphrasing that from one of our brilliant young people that works on the team, Mohit.

• 41:12Speaker 00

  But because that's the case, you want the frontier stuff. And so all of it goes through frontier models, or most of it. And so what you have is you have this dynamic where the coding companies, which are doing a great job, I think are doing amazing, and they're amazing people.

• 41:24Speaker 01

  Yeah.

• 41:25Speaker 00

  But their subscription, you know, they pay a big chunk of it to a model provider. And then that model provider, you know.

• 41:31Speaker 01

  Pays a chunk.

• 41:32Speaker 00

  Pays a chunk to someone running the compute.

• 41:34Speaker 01

  Yeah.

• 41:34Speaker 00

  In Anthropic's case, they're running Amazon and Google, right? And then that provider pays money to build the data centers. And ultimately, the biggest toll taker there is Nvidia.

• 41:43Speaker 01

  Yep.

• 41:43Speaker 00

  And so if you trace this ecosystem, you know, and you look at the dollars of profit today, I think Stan Drucker Miller said this, 120% of the profit in AI is from Nvidia. Which implicitly means that, you know, they are

• 41:55Speaker 01

  That's good.

• 41:56Speaker 00

  You know, most companies are losing money and they're the ones making money.

• 41:58Speaker 01

  Yeah.

• 41:58Speaker 00

  And so, you know, Cogent is in this fascinating state where these companies are growing really fast. There's lots of promise and potential, but the economic equation is very much unknown.

• 42:09Speaker 01

  Yeah.

• 42:09Speaker 00

  And I think they will figure it out. I think there will be big, big winners that come out of it.

• 42:13Speaker 01

  Yeah.

• 42:14Speaker 00

  But today, what you have is a lot of dollars that are getting handed around.

• 42:17Speaker 01

  Yeah.

• 42:17Speaker 00

  And there's less discretion on who should get valued properly. And really, everyone is getting valued at a high multiple on those same dollars.

• 42:25Speaker 01

  To connect back to an earlier part of the discussion when we talked about, you know, Stripe and how you were obviously understanding the financials, but that came later and more you were understanding, you know, the product, where the market might shape out, you know, those kinds of things. When you think about, let's just take that stack, you know, and you're obviously an investor in both Curse or in OpenAI. And, you know, we talked about a bunch of others. Is it very important for you to think hard about where the money is going to ultimately land? Or are you more able to just think about, you know, dynamics that have more to do with the product, the adoption, the customer, the founders, et cetera?

• 43:00Speaker 00

  I think the answer is both. Like, I think if you're too qualitative, you miss a lot of details that are important. And if you're too quantitative, you miss a lot of the details that are qualitative. So like, you have to, this is, we call this East Coast meets West Coast venture. You know, where East Coast, I'm surrounded by public investors and people that are very quantitative. West Coast, I think, is highly product and people oriented. And so we try to sit at that intersection. The reason it's important is, you know, okay, if you're investing something at a billion dollars, it's a big price. But if it works, we need to believe you can get paid for the risk. So if you have an unknown economic equation and we're investing at those prices.

• 43:33Speaker 01

  Yeah.

• 43:34Speaker 00

  We need to believe it's not a three or four X. We need to believe it's like a 10 or maybe 20 X. If you're investing in something at 50 billion, you know, okay, it's hard to put 20 X's on paper or 10 X's on paper. But you know, that means that the confidence you have to have or the kind of band of outcomes, you have to have a tighter standard deviation on the variance of the outcome in those kind of more certain equations versus if you're investing earlier in the curve, you just need to get paid for the upside. The challenge with that philosophy is if a lot of people believe a lot of things can get big, a lot gets funded.

• 44:05Speaker 01

  Yeah.

• 44:05Speaker 00

  And so you live in these periods of time where the economic equation can be distorted because there's a lot of funding

• 44:10Speaker 01

  Yeah.

• 44:10Speaker 00

  in the environment. And Bill Gurley's talked, you know, at length at this, but you can do all you want on paper. But when you're living the strategy in the boardroom and all of your competitors are raising billions of dollars of capital.

• 44:21Speaker 01

  Yeah.

• 44:21Speaker 00

  The economic equation goes out the window because everyone's competing for a theoretically big prize.

• 44:25Speaker 01

  Totally.

• 44:26Speaker 00

  And so I think right now, what we have is a bunch of companies that are operating in that environment. And so we have to be grounded in where do we think conceptually the value will accrue? And if you look at Cursor, we think distribution matters.

• 44:37Speaker 01

  Yeah.

• 44:38Speaker 00

  And they have amazing distribution with lots of developers, lots of love, and people that use it every day. That's valuable and an amazing team. With OpenAI, they've done a lot of hard work on the model, but it's not just that. They have to scale all the infrastructure to do that. They have to run the inference really efficiently.

• 44:52Speaker 01

  Yep.

• 44:53Speaker 00

  There's a lot of IP in that. There's only, you know, Anthropic and OpenAI are basically the two independent scaled model providers. And then they're competing against, you know, Google and Meta and Tesla. You know, they're competing with big, big companies. That's hard and there lies the value of what they're doing. And so, you know, even if you see, even if you can't know the end state of the financial equation, I think you have to try to telegraph it through what the kind of quality of the product and business model is.

• 45:18Speaker 01

  Yep. Just to move through a couple of the other areas of AI. How do you feel about like, for lack of a better term, like vertical specific, like AI workspaces? So like, you know, we're both investors in Rogo. There's obviously in legal, there's like Legora and Harvey. You know, there's, there's a bunch for different verticals and it's sort of like not the agent doing all the work, but like maybe like a bit more co-pilot type work. Do you feel bullish on those type of companies? Is it vertical by vertical? Do you look at a lot of that?

• 45:49Speaker 00

  We do spend a decent amount of time looking at it. It's kind of, I would say, in the fullness of time, it's a little ironic that if we're one or two innings into a massive technology wave, that we're starting with vertical market software.

• 46:00Speaker 01

  You think that should come last?

• 46:02Speaker 00

  Well, if you looked at the last generation of software as a proxy, you start with the big horizontal categories because they're massive.

• 46:08Speaker 01

  Yeah.

• 46:09Speaker 00

  And then you work your way up the kind of product pyramid because, you know, it's much easier to build the big CRM than it is to build VIVO, which is specific for life sciences.

• 46:17Speaker 01

  Yeah.

• 46:17Speaker 00

  Okay, you go to AI, and who are some of the early adopters of the technology? Lawyers.

• 46:22Speaker 01

  It is surprising.

• 46:23Speaker 00

  And doctors.

• 46:24Speaker 01

  Yeah.

• 46:24Speaker 00

  There are categories that you would not put in the early adopters of technology. Developers, makes sense.

• 46:29Speaker 01

  Yes.

• 46:30Speaker 00

  But lawyers and doctors.

• 46:31Speaker 01

  Surprising.

• 46:31Speaker 00

  It's surprising.

• 46:32Speaker 01

  Yeah.

• 46:32Speaker 00

  So I think from that perspective, there is something interesting to study, which is like, why are these the folks that are adopting early?

• 46:39Speaker 01

  Do you think it's because they feel like they were a little slow last time around, and so they're a little more front foot this time?

• 46:42Speaker 00

  I do think that plays into it. Like, most companies in general don't want to lose out in the internet.

• 46:47Speaker 01

  Yeah.

• 46:47Speaker 00

  Like, you saw that with crypto.

• 46:48Speaker 01

  Yeah.

• 46:48Speaker 00

  How many companies got on the crypto bandwagon?

• 46:50Speaker 01

  Yeah.

• 46:50Speaker 00

  Because they just lost in the internet, and they like, don't want to lose in crypto. So even if it doesn't make sense, they're doing it.

• 46:54Speaker 01

  I mean, the other thing is, a lot of these law firms, just like, take one example, like, they spend all day with startups. Like, they understand the tech.

• 47:01Speaker 00

  Yeah.

• 47:01Speaker 01

  You know, they know it, and so I think-

• 47:02Speaker 00

  And law as a modality is highly text-based.

• 47:06Speaker 01

  Yeah, it works very well for LLMs.

• 47:07Speaker 00

  And the models are very good at that, and so it makes sense. Or doctors, you know, a lot of it is kind of evidence-driven, or publication-driven, or diagnosis-driven, which you can ingest that in modalities that are good with LLMs. So you could argue a difference out of this, which is the reason those are early adopters is product.

• 47:21Speaker 01

  Yeah.

• 47:21Speaker 00

  But I just think it's ironic in the fullness of time that investors are so focused on it.

• 47:24Speaker 01

  Yeah, definitely.

• 47:24Speaker 00

  So early, because it doesn't seem like the biggest markets to go after. But therein lies the kind of opportunity, which is, we are excited about some of them. We invest in ROGO, in financial services. You know, I think the amount of competition in these markets early doesn't, it breaks the heuristics of success historically. Like, the old equation of success in a vertical market was, you get a lot of market share. Why? Because as people professionalize on you, you take a lot of market share. Like, how many competitors are there to Adobe Photoshop?

• 47:51Speaker 01

  Yeah.

• 47:52Speaker 00

  Or AutoCAD?

• 47:52Speaker 01

  Yeah.

• 47:53Speaker 00

  There aren't.

• 47:53Speaker 01

  Yeah.

• 47:53Speaker 00

  Right? And so, how many competitors are there going to be in legal chatbots? Today, there's a lot.

• 47:59Speaker 01

  Many dozens.

• 47:59Speaker 00

  And so now there's a couple of companies that have broken out of the pack and exist. But over time, you would hope that it consolidates to a small few. And so.

• 48:07Speaker 01

  I mean, in general, we're in a moment in time where there's probably more competitors than at least I've ever seen in a lot of these categories. And I think it's because, you know, in that quadrant of like, looks good and is good, like a lot of things like look good and might also be good.

• 48:21Speaker 00

  Yeah.

• 48:21Speaker 01

  And so you have a lot of people flocking there. There's a capital markets to back on.

• 48:24Speaker 00

  Yeah. So anyways, to answer your question, I think we're selectively excited. Like, why do we think Rogo was really interested? It starts with a person. I mean, you know, Gabe, I think he's 12 out of 10. And so we have to get excited about that. The category has properties I think are interesting. Like, I personally believe that exposing data businesses via the chatbot.

• 48:43Speaker 01

  Yeah.

• 48:43Speaker 00

  Is actually more interesting of a thing to look for than to look for like big labor markets.

• 48:48Speaker 01

  Yeah.

• 48:48Speaker 00

  And so I've been spending time, how do you find data assets that you can now expose that way? Because the models are amazingly good at structuring and looking at and searching across big data.

• 48:57Speaker 01

  What else would that include?

• 48:58Speaker 00

  You could, you know, I would love to find one in real estate.

• 49:00Speaker 01

  Yeah.

• 49:00Speaker 00

  CoStar is this amazing, you know, almost monopoly like data asset, you know, is there somebody can go after that? You know, I think there are other categories too, you know, that we could talk about. But in finance with Rogo, what's so fascinating is there's a couple million seats that people can go sell to.

• 49:16Speaker 01

  Yeah.

• 49:17Speaker 00

  And so if you're competing against ChatGPT, is ChatGPT going to prioritize integrating?

• 49:22Speaker 01

  No, it's like perfect. There's not that many.

• 49:23Speaker 00

  Public market research.

• 49:24Speaker 01

  Well, I guess the flip is they're willing to pay a lot and they have a lot of money, like in Bloomberg got really big.

• 49:28Speaker 00

  Of course, but the thing is then if you're ChatGPT, you can't sell them ChatGPT off the shelf. You have to build a custom ChatGPT.

• 49:33Speaker 01

  Better to go get a billion users. Yeah.

• 49:35Speaker 00

  And, and open any scale. And so to me, that's the advantage that they can do. You know, if they have to compete with ChatGPT head on at their own game, it's gonna be hard. But if we can go compete on workflows and doing spreadsheets really well and public market research and exposing all of that data with great sources, that'll be an opportunity for us.

• 49:52Speaker 01

  Yeah. Are there any other areas in general in like the application layers or like the startup side? That you feel like particularly interested in with AI?

• 50:00Speaker 00

  I mean, robotics is the one that is kind of, we didn't talk about, and it's probably next to life sciences, the biggest opportunity. Like, I think the biggest market.

• 50:08Speaker 01

  It could be the biggest just.

• 50:09Speaker 00

  No, the biggest market, today, you know, today, cars are one of the biggest industries globally.

• 50:13Speaker 01

  Yeah.

• 50:14Speaker 00

  They might be the biggest industry globally, which means robots for consumers.

• 50:18Speaker 01

  Yeah.

• 50:19Speaker 00

  Should be the biggest market.

• 50:20Speaker 01

  That's what you would think.

• 50:21Speaker 00

  The utility of a robot in your house doing things is way higher than a car.

• 50:24Speaker 01

  I mean, if everybody in the world had one robot, 10,000 each, doesn't even seem, you know, it makes a lot of sense.

• 50:28Speaker 00

  Yeah, exactly. And so to me, that is biggest market. The question, I think, right now is, you know, are we in 2015 self-driving? Or are we on the precipice of cracking full-stack robots?

• 50:39Speaker 01

  Yeah.

• 50:39Speaker 00

  And I think that's what's the hard question to answer right now.

• 50:41Speaker 01

  Yeah.

• 50:42Speaker 00

  And I've heard arguments on both sides. I've heard arguments that we are not in self-driving. Actually, self-driving is a harder problem because if you make the wrong decision when you're going 60 miles an hour, you kill somebody. But if a robot, you know, doesn't put the apple in the right spot, or it, you know, breaks a dish.

• 50:58Speaker 01

  Yeah.

• 50:58Speaker 00

  Everyone's gonna be okay.

• 50:59Speaker 01

  Yeah.

• 51:00Speaker 00

  And so the problem, while complex, because there's more degrees of freedom, there's more complexity in the environment, is actually, in some sense, easier because the risk of failure is lower.

• 51:08Speaker 01

  Right.

• 51:09Speaker 00

  I've heard other arguments, though, that because the components are brittle and there's a lot of, you know, hardware that has to get built, and also software that has to get built, that was gonna take a long time. So I don't know, but that's, that's an area that we are super excited about. We're investing in physical intelligence, and you know, Locky and Carol and those guys, I think it's an awesome company.

• 51:28Speaker 00

  Yeah, but it's early and it's an area that we're definitely interested in looking for more.

• 51:31Speaker 01

  How do you decide, you know, putting an incremental 50 or 100 million dollars into one of these companies versus just, you know what, OpenAI is definitely working, we've got a great relationship, let's just put more there? You could liken it to crypto or something where like, you know, the right answer, looking back, might have just been like buy Bitcoin all along the way? Like, how have you thought about, you know, that sort of mashup?

• 51:53Speaker 00

  I do think there's some parallels in the buy Bitcoin. You know, the best thing to do is just go along Bitcoin, because at the end of the day. It is kind of the derivative, you know, value indication of everything, you know, meaning all these AI companies have to use models, OpenAI is the leading model, they're also leading consumer product.

• 52:07Speaker 01

  Yeah, you could also just say like, if you believe in crypto, you're sure Bitcoin's gonna, if it doesn't work, Bitcoin's not gonna work, you know, if it works Bitcoin, same kind of thing.

• 52:14Speaker 00

  And this is, this is, being so close to OpenAI, I think this is one of the things that helps us in a lot of ways, and sometimes it can hurt us because we kind of know maybe too much. But, you know, they are well positioned to a lot of things. The investor community has basically now narrowed OpenAI and said, oh, ChatGPT is the next consumer chatbot globally, and that's how you should underwrite the company, and that's what it's gonna do. But, I mean, obviously, you know, Sam Superwell, you know, they, I think what he promotes is this kind of do a lot of small teams betting on new things, and it's a very entrepreneurial culture. And so, I, I would be shocked if there are not lots of new products in OpenAI that are massively successful.

• 52:53Speaker 01

  Well, I mean, as we're talking about a lot of these other categories, it's like, if they are in fact really big, I mean, this was one of the things historically with like Google.

• 53:01Speaker 00

  Fang.

• 53:01Speaker 01

  Yeah. Was like, it's either not that big of a market and they won't compete, or it's a really big market and they'll compete. I think what turned out to be the case in a lot of things in the cloud cycle was, they tried to compete and they just didn't do a very good job at it and they lost the market. You know, it seems like the companies today are much more, probably including Fang, have woken up. I just feel like the incumbents are much stronger than they used to be.

• 53:22Speaker 00

  I think the incumbents are super strong. And why? We've never had global distribution. There, there wasn't ever user connected on the internet prior. You know, that's, you know, again, if you think in long, if you think in decades, not years, a lot of the capabilities right now are a couple decades old. You know, everyone didn't have access to the internet two decades ago, not even one decade ago. You know, it's now you take today. And so, over the next two decades, those companies are gonna be able to flex some of this distribution and technology they have in a way that will be hard to compete with. And so, I think the thing that we absolutely can't have happen is that new companies can't break into that era. Like, I think one of the things that, you know, is Hard is right now, everyone's basically ganging up on, you know, I my mental model for

• 54:07Speaker 00

  you on how the competitive landscape looks like for OpenAI is OpenAI is in a corner and every big tech company has a bazooka pointing at them to try to take them down.

• 54:15Speaker 01

  Yeah.

• 54:16Speaker 00

  Because none of those big tech companies want a new big tech company.

• 54:18Speaker 01

  Right.

• 54:19Speaker 00

  Right. And so we should all want it to be a competitive, fair fight for a new company to break into Mag7.

• 54:26Speaker 01

  Yeah.

• 54:26Speaker 00

  Because that's what our whole ecosystem lives and freezes off of.

• 54:29Speaker 01

  Yeah.

• 54:30Speaker 00

  The flip side of this is, you know, there's these big, going back to this number of hundred billion dollar companies, as the big get bigger.

• 54:36Speaker 01

  Yeah.

• 54:36Speaker 00

  There are just self reinforcing properties like Uber. They have a driver network. They have millions of consumers in their app in a geography. Are they able and best off to do food delivery? You know, it turns out, yes. If you would have said, you know, five years in Uber's journey, was that their focus? Everyone said, no.

• 54:54Speaker 01

  Yeah.

• 54:54Speaker 00

  You know, so now that market is largely kind of coalesced around DoorDash and Uber. So one company did do it without having the right share, but the rest of the market consolidated around a basically an incumbent in a different area.

• 55:04Speaker 01

  Right.

• 55:05Speaker 00

  I think you'll see the same thing in AI. And so this is where we have a hard time, which is I think a lot of our bias is this isn't a risk adjusted better return than OpenAI.

• 55:14Speaker 01

  Yeah.

• 55:14Speaker 00

  And therefore, if we're given a decision, we should do it. At the same time, you can't you can't not take risk because of that. And so we are investing in other companies.

• 55:21Speaker 01

  For sure. I mean, but it's also like, I think one of the things when I think about like Founders Fund and why they're so impressive to me is that they made that calculus for, you know, a decade into like SpaceX and others.

• 55:33Speaker 00

  Yeah.

• 55:34Speaker 01

  And to continually have the discipline to say, it'd be really fun to go make a new investment, but if I know these two things and I can just put more into something that I already own a lot of, I'm like, I find that very impressive, partially because the patience is brutal.

• 55:49Speaker 00

  I think there's a firm that has kind of the most similar strategy. It's probably Founders Fund.

• 55:54Speaker 01

  Yeah.

• 55:55Speaker 00

  But I think they have very similar DNA of making big, bold bets in companies.

• 55:59Speaker 01

  Thinking about like what matters most for Thrive in the next like leg of the journey. And obviously, you know, if I know one thing about Thrive, like you're not going to stand still like I've never known Thrive to do the same thing it did last year. What matters most sort of either organizationally, brand wise, capital wise, investment wise? Like what needs to be true for you guys to like get to a place where you look back and in 2025, Thrive feels like somehow small?

• 56:25Speaker 00

  I mean, we talk about this a lot. What worked for the last decade is not going to work for the next decade. And so you have to evolve, which I don't think is a given for most firms. I think the most important thing for us is we continue to be a place that attracts the most talented and ambitious young people. So at the end of the day, a lot of what we do is new disruptive and you need the right combination of experience and naivete. And you know, as people get older and older in their careers, I hope I continue to learn, but you learn through young people. And if we're not able to attract that kind of person to us, will we attract the right companies and founders? We attract the right investors. We have people now, you know, Thrive is a product. We are building Thrive as a company with our own products and technology.

• 57:10Speaker 00

  And so we attract those people that way, too. And it's going to be how we attract new strategies to grow the firm. And so I do think the single most important thing is we maintain that. And then we also have a healthy dose of, you know, we've got to change. You evolve or die in this industry.

• 57:26Speaker 01

  Love it. Vince, this was super fun. Thanks for doing it.

• 57:29Speaker 00

  Thanks so much, Jack.