Uncapped #27 | Vince Hankes from Thrive Capital

22:07Oh, I have money, let me do diligence for a month, and that's how it works. That model to me is not competitive anymore. 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 were 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. That's a very different motion. And by the way, there's no process. 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.

22:36But 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. A lot of times, investors only spend time with the CEO. The CEO's one person in the company. Do they spend time with the head of engineering, the head of product, with the sales leaders, with people lower than that? You really learn how clear the flow of information is in a company by meeting a lot of people on the team. Are people singing from the same song sheet? Do they understand the decision-making framework?

23:06The best companies, it's super simple and it just ripples down and everybody knows how to act. One of the challenges for a lot of groups though is 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, the rounds you're talking about, Databricks round, Stripe round, an OpenAI round, 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 the scale drives a lot of the competitive advantage.

23:39Yeah, I want to play 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? Three, four? I don't know. It's not that many. So I'm competing with a handful, two handfuls of people versus if you're trying to write 100 million dollar checks into the growth stage or 10 million dollar checks, you're competing with at least an order of magnitude or two orders of magnitude more firms. Maybe that won't last forever and people will get capable of doing what we're doing. But today it's a more advantage game in the field because there's just not that many people that can compete.

24:08What's interesting is I think there are a lot of firms in the size rung below, call it$1 to$3 billion 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, 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, what's the dominant thing it takes if you're a leader of a$1 or$2 billion firm to get to this? What is the thing preventing more people from doing this? It's a question we think about. I do think while some of this seems easy to articulate as a strategy, as we talked about our journey, part of it has been a long buildup to get to the level of confidence to do that.

24:59Because 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. Just in general, building a culture that rewards this I think is not something you can do overnight. Which kind of goes to why is it hard for firms to do? There's politics. We have a founder-led firm. And you can debate 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. 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, what happens?

25:39Especially if it's viewed as firm reputational risk. 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 a singular small team that makes decisions. There's a good segue. I want to talk about Carvana, which was, I thought, one of the most interesting. And in the full arc, it was extremely impressive to me, where basically you made an investment in Carvana.

26:11I 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 a lot, and you buy more, you hold, and it ends up doing great, you distribute shares, and you crushed it. But that seemed like a nail biter to me, because it was a lot of capital. It was a public company, and you're Thrive, you're not a public, for the most part. Obviously, you do it. But I was just like, and you were partially proven, but also earlier in your career when you did it, and it worked. So just talk me through that whole thing. I mean, I think in a lot of ways, this embodies who we are as a firm.

26:50the journey of Carvana wasn't just random I think some people say oh you guys saw the public markets go down and you went and moved on a company it's not just looking to go do random things I first got to know Carvana because 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 make sense and then the post-COVID kind of tech cycle happened and it was one of the names that went down 50 % in six months.

27:23And 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 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 have 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.

28:02So it's not just an online listing for cars. It's a logistics company, which is its core 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, it's a business that gets better, it's bigger. More inventory you have, more people that convert, more people that convert, the better economics are, the better economics, the more you invest in that whole flywheel and it spins and spins and spins.

28:33And 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 company. And then the used car cycle turned. They actually did an acquisition finance entirely by debt, which was, we don't deal out with the leverage in the private markets. And so there was definitely learnings from that. And the combination of that and a cycle and burning money per car sold meant that the business completely unwound in a short period of time. The stock went down. Like all the way? 90%, right? 90 plus percent. So obviously, that's not a fun journey to ride down, particularly because when you watch get marked every day.

29:12When you do a contrarian investment in the private markets, your friends might give you some crap about it or grief about it, or people you talk to are LPs. But when you're investing a public stock that goes wrong, every day you wake up down 5%, down 4%, down 5%, and you have to answer the question of why. Which, if that happened in the private markets, no way you could do this job. Everyone would sell their shares. But I think we really had an advantage 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 get fit era of private companies.

29:49Everyone hired way too much in COVID and now needed to restructure their companies or let go of people and right size the P &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 a company, which you were, Lattice, 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 the trains on track and making sure you're right-sizing the company for what it is.

30:19So 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, the stock was down a lot, but through the dimensions we were evaluating on, 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 this little trend line was very good, And so we ended up doubling the number of shares we bought at the company. At a very low price. For a fraction of the price. And so there's also this combination that I think is less.

30:47Which, by the way, that's a hard move to do. The knife has fallen all the way. Psychologically. That was the moment that I was like, this is crazy. Yeah, well I think what you learn, even if something goes down 50%, it can still go down 90%. Yeah, and after it's gone down 90%, five more is another halving. Yeah, it's tough. But I think 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 Sharpe ratio is a thing and you can measure it. And so what we were able to do is double our position size in shares for a fraction of the capital.

31:18And 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 where we definitely would have sold the shares. For sure. Then you have to have an environment where people aren't just nitpicking the numbers. Because if all people are doing is nitpicking the numbers, we were going to sell.

31:46But we have an environment that's very much grounded in the product. And people believe in the product. I don't know if you ever bought a used car. But 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 what a quality product experience is in this industry. And so people believed in that at Thrive. The number of people are 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.

32:13And then in the fullness of time, obviously. 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. It's a big market. 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 as 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. I think it's a firm thing. I mean, obviously, going through it personally 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.

32:45And I think in the fullness of time, we've benefited from it. But in the moment, it's really hard. How important is managing conflicts for Thrive? Basically, 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 big winners with most of your capital. if you pick something earlier, you conflict it out. How do you manage that? Yeah, we take this super seriously. Because if you do a series A in a company, you can't go do a series D or E or F in something else. It's part of the calculus. But if you look at the market today, a lot of investors, it's just buy the index across the companies that are working.

33:18And so they don't care about conflicts. And for us, because we're not doing a lot, we implicitly are making a commitment to the companies that we are all in on your company. Just like a founder's all in on the company, we're going to be all in on this investment. No, I'm just thinking it's one thing. If it's open AI or SpaceX, it's one thing. You can't go invest in Blue Origin, and I feel sad for you for that. It's obviously a good company, but you're in SpaceX. But when you go and invest in the Series A of an ERP or a CRM or whatever, is the category done for you at that point? It's not done.

33:51But people talk about the advantages. I think about the advantages of full stack investing. This is maybe in the disadvantages of it. Whereas if you're just an early stage investor, you look at the seed or the A, maybe the B, if you can't get it there, you never think about it again. Oh, it's in your anti-portfolio kind of thing. If you're in our shoes, it's like, I can invest in the seed, the A, the B, the C, the D, when it's public, who knows when. You can take it private. Exactly. We're joking, but this happened in this Thrive Holding strategy that we announced. What is it? We ended up raising a billion dollars in a company.

34:28It's not a fund, it's a company. Why did we do that? People are like, oh, you're expanding strategies. It was very organic. We started looking at accounting AI companies. One of our partners is very good friends with this guy who's running this accounting role of strategy. We started talking to them about AI tools. Why? Because we're just looking at early stage AI companies. 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.

35:01What's the best way to play accounting in AI? Is it to invest in a software company early? Or be the accounting firm. 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, which I think is very different.

35:31By the way, there's$800 million of venture investing going into the software tools for accounting. Really? And so, yeah. So we're riding the R &D dollars to the entire industry as the service provider. And accounting's sticky. Are you going to change your accounting provider because they have 10 % lower price? No. 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?

36:04And 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. In general, across functions and verticals, do you more fall into the camp at the moment? right now, September 2025, are you more in the camp that 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 super sick software and everything's going to get more efficient?

36:37Do you think about this question at all? We do. I'm probably more in the latter camp. I just think we're also humans. and in a lot of places 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. If you're United Airlines. You don't ever want to talk to somebody. But I can call a number and get an instant response from an AI. And I don't have to wait ever. That's amazing. And so in some functions like that, I think it'll probably shift towards software. 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.

37:13And so those people will get upgraded in what they're doing. I think the value a lot of times is with the humans doing it. I think making them 10x more efficient is better. Take creative. Are we going to automate away all the creative people? Probably not. Are we going to make them 10x as productive, so there's 10x more creative content? 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. I think it more is you lower the floor of entry, so now someone who wasn't talented enough could probably do it. They can take their culture and lens and now do it.

37:44And then you also increase the output of the people that are really good at it. I don't think you really, maybe you eliminate some people on the margin that you don't need, but I think the vast majority is make people a lot more efficient with their time. So you basically, so far you've listed, obviously we all believe in not search, but chat. We all believe in support. I think CodeGen, although we can talk about that a little bit more. Any other areas that you're quite bullish on that you're like, this is working now and is going to go very far? I think the thing I'm most bullish on that seems early and broadly the market hasn't acknowledged it yet is life science.

38:18Drug development should radically change. On what dimension do you think it will change? The reason we invest, this company Isomorphic started inside of Google, Dennis Hospice, who runs Gemini. This is his second project or company. He won his Nobel Prize for the work he did on protein structure prediction. That has now morphed into this company. and the entire objective, well the mission of the company is to cure all disease. It's a pretty big mission. It's one of the only companies in our portfolio that I think about is having the potential size as OpenAI. I think it is truly that. Yeah, of course, if you could do that, it's huge.

38:54It's trillions of dollars. And then when you go spend time with them and what they're working on, the objective is we're going to take an 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. You just do it all on a computer. Yeah, but now the speed of iteration is different. The scale which you can run a computer is different. What needs to be true for that to happen? What needs to be different in the future for that to work? A lot of things, which is why it's such an interesting problem to work on as a company.

39:27Obviously 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 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 today it's regulated. So you can't just come and put drugs into people's bodies in the U.S. Which is going to take the same amount of time. Yeah, and so what's another problem we're working on? Regulation. How do you work alongside regulators to change the way the FDA thinks about it because the top of funnel might go up a lot?

40:00That's another thing. How do you find people with disease? How do you look for the right biomarkers? We can use AI for that, though. And by the way, there's a huge upswing of startups that are working. 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 feels far away and sci-fi when we talk about it this way.

40:34When you go spend time with these companies, the rate of progress feels very early open AI oriented. How about CodeGen? Actually, maybe one of the things I'm curious about is, can you talk about the stack from a cursor subscription down to the middle? How the 20 bucks moves? 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. And I'm paraphrasing that from one of our brilliant young people who works on the team, Mohit. But because that's the case, you want the frontier stuff. And so all of it goes through frontier models, or most of it.

41:18And 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 amazing people. But their subscription, they pay a big chunk of it to a model provider. And then that model provider pays a chunk to someone running their compute. In Anthropics cases, they're running on Amazon and Google. And then that provider pays money to build the data centers, and ultimately the biggest toll taker there is NVIDIA. If you trace this ecosystem, and you look at the dollars of profit today, I think Stan Druckmiller said this, 120 % of the profit in AI is from NVIDIA.

41:53Which implicitly means that most companies are losing money and they're the ones making money. Cogen's 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. I think they will figure it out. I think there will be big, big winners that come out of it. But today what you have is a lot of dollars that are getting handed around and there's less discretion on who should get valued appropriately. And really, everyone is getting valued at a high multiple on those same dollars. To connect back to an earlier part of the discussion where we talked about Stripe and how you were obviously understanding the financials, but that came later.

42:33And more you were understanding the product, where the market might shape out, those kinds of things. When you think about, let's just take that stack, and you're obviously an investor in both Cursor and OpenAI, and 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 dynamics that have more to do with the product, the adoption, the customer, the founders, etc.? I think the answer is both. I think if you're too qualitative, you miss a lot of details that are important. If you're too quantitative, you miss a lot of the details that are qualitative.

43:10We call this East Coast meets West Coast venture. 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 in 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, 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 10x is on paper.

43:44But 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. And so you live in these periods of time where the economic equation can be distorted because there's a lot of funding in the environment. Bill Gurley's talked at length at this. 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, the economic equation goes out the window because everyone's competing for a theoretically big prize.

44:26I think right now what we have is a bunch of companies that are operating in that environment. We have to be grounded in where do we think conceptually the value will accrue. If you look at Cursor, we think distribution matters. 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. There's a lot of IP in that. Anthropic and OpenAI are basically the two independent scaled model providers, and then they're competing against Google and Meta and Tesla.

45:04They're competing against big, big companies. companies. That's hard, and therein lies the value of what they're doing. 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 quality of the product and business model is. Just to move through a couple of the other areas of AI, how do you feel about, for lack of a better term, vertical-specific AI workspaces? We're both investors in Rogo. There's obviously in Legal, there's Lagora and Harvey. There's a bunch for different verticals. It's not the agent doing all the work, but maybe a bit more co-pilot type work.

45:42Do you feel bullish on those type of companies? Is it vertical by vertical? Do you look at a lot of that? We do spend a decent amount of time looking at it. 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. You think that should come last? If you looked at the last generation of software as a proxy, you start with the big horizontal categories because they're massive. Then you work your way up the product pyramid because it's much easier to build the big CRM than it is to build Viva, which is specific for life sciences.

46:17You go to AI, and who are some of the early adopters of the technology? Lawyers and doctors. There are categories that you would not put in the early adopters of technology. Developers? Makes sense. But lawyers and doctors? It's surprising. So I think from that perspective, there's something interesting to study, which is why are these the folks that are adopting early? 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? I do think that plays into it. Most companies in general don't want to lose out in the internet.

46:47You saw that with crypto. How many companies got on the crypto bandwagon? Because they just lost in the internet, and they don't want to lose in crypto. So even if it doesn't make sense, they're doing it. I mean, the other thing is a lot of these law firms, just to take one example, they spend all day with startups. They understand the tech. They know it. And law as a modality is highly text-based. Yeah, it works very well for LLMs. And the models are very good at that. And so it makes sense. Or doctors, a lot of it is evidence-driven or publication-driven or diagnosis-driven, which you can ingest that in modalities that are good with LLMs.

47:17So you could argue a difference out of this, which is the reason those are early adopters is product. But I just think it's ironic in the fullness of time that investors are so focused on it, so early, because it doesn't seem like the biggest markets to go after. But there lies the opportunity, which is we are excited about some of them. We invested in Rogo in financial services. I think the amount of competition in these markets early, it breaks the heuristics of success historically. 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.

47:49How many competitors are there to Adobe Photoshop or AutoCAD? There aren't. How many competitors are there going to be in legal chatbots? Today there's a lot. 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. 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. I think it's because in that quadrant of looks good and is good, a lot of things look good and might also be good. You have a lot of people flocking there. There's a capital market to back on.

48:24To answer your question, I think we're selectively excited. Why do we think Rogo was really interested? It starts with a person. You know Gabe, I think he's 12 out of 10. We have to get excited about that. The category has properties that I think are interesting. I personally believe that exposing data businesses via the chatbot is actually more interesting of a thing to look for than to look for big labor markets. 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.

48:57What else would that include? I would love to find one in real estate. CoStar is this amazing, almost monopoly-like data asset. Is there someone who can go after that? I think there are other categories too 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. If you're competing against ChatGPT, is ChatGPT going to prioritize integrating public market research? I guess the flip is they're willing to pay a lot and they have a lot of money. And Bloomberg got really big. Of course, but the thing is then if you're ChatGPT you can't sell them ChatGPT off the shelf.

49:32You have to build a custom ChatGPT. Better just go get a billion users. And open-ended scale. And so to me that's the advantage that they can do. If they have to compete with ChatGPT head-on at their own game it's going to 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. Are there any other areas in general in the application layers or the startup side that you feel particularly interested in with AI? Robotics is the one that we didn't talk about. It's probably next to life sciences, the biggest opportunity.

50:06I think the biggest market. It could be the biggest. Today, cars are one of the biggest industries globally. They might be the biggest industry globally. Which means robots for consumers should be the biggest market. That's what you think. Because the utility of a robot in your house doing things is way higher than a car. I mean, if everybody in the world had one robot, 10 ,000 each, it makes a lot of sense. Yeah, exactly. And so to me, that is the biggest market. The question I think right now is, are we in 2015 self-driving or are we on the precipice of cracking full stack robots? And I think that's what's the hard question to answer right now.

50:41And 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 doesn't put the apple in the right spot or breaks a dish, everyone's going to be okay. 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. I've heard other arguments, though, that because the components are brittle and there's a lot of hardware that has to get built and also software that has to get built that's going to take a long time.

51:18So I don't know, but that's an area that we are super excited about. We're investing in physical intelligence. I know you know Lockheed and Carol and those guys. I think it's an awesome company. Yeah, but it's early and it's an area that we're definitely interested in looking for more. How do you decide putting an incremental $50 or$100 million into one of these companies versus just 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 the right answer looking back might have just been buy Bitcoin all along the way.

51:49How have you thought about that sort of mashup? I do think there's some parallels in the buy Bitcoin. The best thing to do is just go along Bitcoin because at the end of the day, it is the derivative value indication of everything. Meaning all these AI companies have to use models, open AI is the leading model, they're also leading consumer product. You could also just say, if you believe in crypto, you're sure Bitcoin's going to work. If it doesn't work, Bitcoin's not going to work. If it works, Bitcoin will definitely do the same kind of thing. Being so close to OpenAI, I think this is one of the things that helps us in a lot of ways and sometimes can hurt us because we kind of know maybe too much.

52:23But they are well positioned to do 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 going to do. I mean, obviously, Sam's super well. 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 would be shocked if there are not lots of new products in OpenAI that are massively successful. As we're talking about a lot of these other categories, it's like if they are in fact really big.

52:58I mean, this was one of the things historically with like, Google, Fang. It 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. I think the incumbents are super strong. And why? We've never had global distribution.

53:26There wasn't every user connected on the internet prior. Again, if you think in decades, not years, a lot of the capabilities right now are a couple decades old. Everyone didn't have access to the internet two decades ago. Not even one decade ago. It's now you take today. Over the next two decades, those companies are going to be able to flex some of this distribution and technology they have in a way that will be hard to compete with. I think the thing that we absolutely can't have happen is that new companies can't break into that era. I think one of the things that is hard is right now everyone's basically ganging up.

54:06My mental model for 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. Because none of those big tech companies want a new big tech company. And so we should all want it to be a competitive, fair fight for a new company need to break into mag seven yeah because that's what our whole ecosystem lives and breathes off yeah 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 yeah they're 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?

54:53Everyone said no. So now that market has largely coalesced around DoorDash and Uber. So one company did do it without having the ride share, but the rest of the market consolidated around basically an incumbent in a different area. 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. And therefore, if we're given a decision, we should do it. At the same time, you can't not take risk because of that. We are investing in other companies. For sure. I think one of the things when I think about Founders Fund and why they're so impressive to me is that they made that calculus for a decade into SpaceX and others.

55:34To continually have the discipline to say, it would 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 find that very impressive. Partially because the patience is brutal. I think there's a firm that has the most similar strategy. It's probably Founders Fund. I think they have very similar DNA of making big, bold bets on companies. Thinking about what matters most for Thrive in the next leg of the journey, and obviously if I know one thing about Thrive, you're not going to stand still. I've never known Thrive to do the same thing it did last year.

56:10What matters most, either organizationally, brand-wise, capital-wise, investment-wise? What needs to be true for you guys to get to a place where you look back and in 2025, Thrive feels somehow small? 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. To the end of the day, a lot of what we do is new, disruptive, and you need the right combination of experience and naivete.

56:50As people get older and older in their careers, I hope I continue to learn, but you learn through young people. If we're not able to attract that kind of person to us, will we attract the right companies and founders? Will we attract the right investors? We have people now. Thrive is a product. We are building Thrive as a company with our own products and technology, 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.

57:24You evolve or die in this industry. Love it. Vince, this was super fun. Thanks for doing it. Thank you so much, Jack.