The Exchanges

Q That is very, very kind of you, but I want to start with a little bit of context. I always like to understand how someone makes their way into this glorious world of venture. So how did you make your way to Thrive and become a partner at Thrive where you are today?

A Well, I don't know that it's that interesting of a story, but I started my career like many folks. I studied business and accounting in undergrad. I went to a big bank out of school, which was Goldman. And in a lot of ways, going to these big banks is like doing an MBA. It's a two year program for the most part. And if you go there, you want to work on these really complicated big companies. And so, uh, most of what I worked on were that was that it was things like AT&T and Verizon were actually You know, Dell announced it was gonna merge with EMC at the time, and so they shipped us down to Austin, and we worked on carving out a bunch of software companies to go finance that big transaction, and after doing that for about 18 months, I ended up wanting to do something different, and I got staffed on Flipkart, which is this e-commerce business in India, and lo and behold, the largest shareholder was Tiger, and so I worked pretty closely with the folks at Tiger on Flipkart for about three or four months, and as I was gonna leave Goldman, The stars kind of aligned, and I ended up joining Tiger to go work, uh, really on private company investing for this guy, Lee Fixel. Um, and as luck would have it, the first company he handed to me was a software company, and so I spent the first three years of my career with him looking at lots of software companies and trying to really find what…

AI assessment note: “chasing Airtable at the time, and The folks at Thrive, Josh and Miles”

Q Final two questions. I think we learn a lot from wins and losses, and we don't often analyze the wins as well in the same detail. If we start, say on, if we start on the loss and then we'll move to the win, what's been the biggest investing mistake for you and how has your mindset changed as a result?

A Well, I mean, I've made lots of mistakes, so, uh, there's not a, there's not a single biggest, but there's so much to learn. The one that I think stands out the most to me, you know, or at least comes back to me a bunch in my psyche is when I was at Tiger, I flew out to Sydney and spent a bunch of time with the Canva team in person. And, you know, it's obviously now people know about it. It's a remarkable company at the time. It was much smaller than it is now. And At the same time, we were so focused on investing in enterprise software as an emerging category at Tiger. And so, as we were spending time with Canva, you know, I very much, and this is early in my career, but I very much let the pattern matching and the DNA of what I was thinking about of a great enterprise software company creep into us looking at Canva. And the learning, I think, just to distill it down to something is, you know, every company is unique, even within the bounds of enterprise software companies, they're unique. We took this lens of what a great enterprise software company was. We've retrofitted to Canva and we said, okay, well, the churn looks a lot higher than what grade looks like. And, you know, the engagement looks very whimsical relative to deep workflows and integrations. And so we shouldn't value this like a highly recurring software business. We should value it like a consumer subscription …

AI assessment note: “we missed what was so special about the company. And the learning for me is”

Q other question is value accrual at the infrastructure layer versus the application layer. How do you think about value accrual there? Because you quite rightly mentioned earlier, three companies, two trillion, you know, and I think in the prior Application layer, there's about a similar market cap, two trillion, but 50 companies, so much more distributed, ah, kind of enterprise value. Where does the value accrue? Infrastructure or application layer?

A I have to believe it's gonna accrue mostly to the application layer. I think if you think about infrastructure companies as platforms, you know, if you think about the software market as the relatives, the value of AWS and Microsoft and Google cloud versus the software companies built on top or all of the internal software tools built on top, I think it's probably an order of magnitude to one, you know, so I just have to believe where value gets created to end customers is where it will get captured. And the nice part about the infrastructure business is that they're effectively toll roads on that whole ecosystem. And so, you know, applications might compete more aggressively with each other and open AI or Amazon or the infrastructure provider might be able to clip a coupon on it. That's really valuable. We might capitalize it at a high multiple, but I just, I have to believe that there's gonna be a lot more value in the new experiences and applications than the infrastructure.

AI assessment note: “I have to believe it's gonna accrue mostly to the application layer.”

Q Final two questions. I think we learn a lot from wins and losses, and we don't often analyze the wins as well in the same detail. If we start, say on, if we start on the loss and then we'll move to the win, what's been the biggest investing mistake for you and how has your mindset changed as a result?

A Well, I mean, I've made lots of mistakes, so, uh, there's not a, there's not a single biggest, but there's so much to learn. The one that I think stands out the most to me, you know, or at least comes back to me a bunch in my psyche is when I was at Tiger, I flew out to Sydney and spent a bunch of time with the Canva team in person. And, you know, it's obviously now people know about it. It's a remarkable company at the time. It was much smaller than it is now. And At the same time, we were so focused on investing in enterprise software as an emerging category at Tiger. And so, as we were spending time with Canva, you know, I very much, and this is early in my career, but I very much let the pattern matching and the DNA of what I was thinking about of a great enterprise software company creep into us looking at Canva. And the learning, I think, just to distill it down to something is, you know, every company is unique, even within the bounds of enterprise software companies, they're unique. We took this lens of what a great enterprise software company was. We've retrofitted to Canva and we said, okay, well, the churn looks a lot higher than what grade looks like. And, you know, the engagement looks very whimsical relative to deep workflows and integrations. And so we shouldn't value this like a highly recurring software business. We should value it like a consumer subscription …

AI assessment note: “The one that I think stands out the most to me... looking at Canva.”

Q You mentioned that kind of the model still being kind of behind, um, lock and key. Um, can I ask how do you, people often suggest like the commoditization of the model as a challenge when you thought about that when making the investment, how did you get comfortable in terms of model commoditization? And long-term edge for open AI, if that's kind of current edge, potentially being threatened.

A This is a question we talked about a lot. I think part of it, we're already seeing the evidence of, in my opinion, where commoditization of the core model output is not really what people will make decisions on over time. You know, I'm sure there are lots of companies that give similar search results to Google, but the reason these companies get built up to scale is because the ecosystem around them grows. And you're even seeing this. They had launched plugins about a month ago and ChatGPT has taken off and taken the world by storm. I think it's the fastest company in a hundred million users ever in like three or four months. And so even if the raw model is, does get competed against, there are maybe companies like Google or Facebook or Microsoft or some of these startups that can compete on that. I do think, again, the dimension by which people are going to think about this in five years from now, looking back, isn't going to be about The commoditization of the model and the raw output, it's going to be, oh, the ecosystem around the model has become much more robust such that you can do a lot more with the model than just get text outputs, you know, or the convenience of putting these things together such that it's not just text. It's now text and image or video and audio all through one, you know, interface that's complicated. And so these are, you know, again, it's not to be…

AI assessment note: “commoditization of the core model output is not really what people will make decisions on”

Q I, I love that, and I, I totally agree with you. Um, that's lovely to hear. Um, tell me Vince, final one, uh, what does the last five years hold for you? When we sit down in 2028, where do you want Vince to be then?

A Well, hopefully we'll be talking about some amazing AI companies we invested in that created lots of value for us both. But I think, you know, we have a lot of ambition at Thrive as a firm, and I hope to be a big part of us building it and ultimately going and backing some of the next Transformational companies, but also building our team and maintaining this amazing culture that I think we have and attracting some of the most talented people that want to go invest in these kinds of companies to come work with us. And so I hope if we talk again in five years, we're talking about those companies. We're talking about the people on our team. And ultimately, um, you know, we're, uh, we're really excited about all that stuff.

AI assessment note: “I hope to be a big part of us building it and ultimately going and backing”

Q Why do you think it's not obvious? Because you have to assume that essentially we'll move from a search interface to a chat interface as the primary UI of engagement. Is that why? Or are there other reasons why it's not obvious?

A I think a lot of investors get tripped up on trying to be so precise on TAM and market and defensibility and the moats around businesses and trying to map that all to price. And those are so important in the investment decision-making process. But when it's so early in a technology cycle like this, it almost is a little bit more of a venture mindset where there are going to be 50 reasons you can say no, and we're not going to have answers to every question. But we need to really think about the things that can go right. I mean, we're not talking about building the next unicorn or decacorn. We're talking about disrupting search or Google. I mean, that's a trillion dollar opportunity. So sure, I can't put a TAM around ChatGPT, but I can tell you, like, we're not talking about a small prize at the end of the day. And so I think when we say it's not obvious to people, people aren't thinking about it in this lens. They're thinking about it in the box of You know, what does this chat interface do? And oh, those use cases aren't that valuable. And I think it does take a, a higher level of creativity or imagination to ultimately think about the world that way.

AI assessment note: “when we say it's not obvious to people, people aren't thinking about it in this lens.”

Q I promise we're going to bring it back to schedule, but I'm enjoying this too much. Um, and they said, bluntly, your ability to keep a level head is actually one of your strongest points as an investor. How do you think about maintaining an even keel in terms of mindset? It's funny. It's rare, especially among younger investors. How do you think about that and how you do it?

A Well, I think part of it is, you know, you're a byproduct of your environment. I think for me, I've gone through a bunch of different waves in my career, and that's helped me understand what volatility looks like, feels like, and so I don't think you just become level-headed as a person. I think you kind of build into that psyche over time. Uh, you know, someone said to me once, uh, which is a lie that I've been saying to the team a bunch internally is, you know, things are never as good as they seemed, and they're never as bad as they appeared. And I think just keeping in mind that the rest of the environment around you does react to these peaks and troughs of your emotion in the market and the volatility. And ultimately, you know, in good times, people over extrapolate in bad times, people under extrapolate. And if you maintain this kind of more balanced approach, I do think it helps you hold more clearly, you know, what are we ultimately looking for in solving Around for a given investment or person or situation. And I've just found that it's not productive to necessarily get caught up in the emotions. You got to try to think clearly. And if you can remove that noise from the volatility of the emotion, it allows you to focus on the core a lot more easily. But that said, I think you do need to trust your gut and you do need to be emotional and react that way. And so I wouldn'…

AI assessment note: “I think for me, I've gone through a bunch of different waves in my career”

Q unpack from Josh how he does it. He never quite tells me. Wonderful, Josh, but secret sauce he keeps close to has Chest. Uh, I do want to ask, you know, Lee is one of the most special people in this business in my eyes. I love him as a person. He's gifted in many ways. What did you learn from working with Lee and from your time at Tiger?

A First of all, I feel really lucky to have started my career working with Lee's. You know, I think he's a really special investor and I credit, you know, a lot of where I got started to work in closely with him. Tiger also is, you know, very, obviously they've become, uh, in the news a lot more recently, but the firm's been around for more than 20 years and You know, I think if you look at how it got off the ground, it is very much in these kind of hedge fund roots. You know, Chase Coleman, who started the firm, he was in his mid twenties. He was really young. He had this hedge fund mentality mindset coming out of tiger management post the dot com bubble. And the way we thought about investing in companies was very financial. Look at the P and L and understand deeply how do the numbers tell the story of what the business does and how does that ultimately make a good business, a great investment. And I learned a lot just from the financial rigor of doing that. But what's interesting is when you can contrast that to what we do at Thrive and how Josh has built the firm, you know, we, we started from the roots of where Josh was, which was a founder. He was the same age as Chase when he started Thrive, but ultimately he was trying to build a startup. And so the mindset was very much, how do you empathize with the entrepreneur? And we focus much more on The product and the customer an…

AI assessment note: “I learned a lot just from the financial rigor of doing that.”

Q You mentioned that kind of the model still being kind of behind, um, lock and key. Um, can I ask how do you, people often suggest like the commoditization of the model as a challenge when you thought about that when making the investment, how did you get comfortable in terms of model commoditization? And long-term edge for open AI, if that's kind of current edge, potentially being threatened.

A This is a question we talked about a lot. I think part of it, we're already seeing the evidence of, in my opinion, where commoditization of the core model output is not really what people will make decisions on over time. You know, I'm sure there are lots of companies that give similar search results to Google, but the reason these companies get built up to scale is because the ecosystem around them grows. And you're even seeing this. They had launched plugins about a month ago and ChatGPT has taken off and taken the world by storm. I think it's the fastest company in a hundred million users ever in like three or four months. And so even if the raw model is, does get competed against, there are maybe companies like Google or Facebook or Microsoft or some of these startups that can compete on that. I do think, again, the dimension by which people are going to think about this in five years from now, looking back, isn't going to be about The commoditization of the model and the raw output, it's going to be, oh, the ecosystem around the model has become much more robust such that you can do a lot more with the model than just get text outputs, you know, or the convenience of putting these things together such that it's not just text. It's now text and image or video and audio all through one, you know, interface that's complicated. And so these are, you know, again, it's not to be…

AI assessment note: “commoditization of the core model output is not really what people will make decisions on”

Q What have you changed your mind on in the last 12 months, Vince?

A This is probably more, this is not for the rapid fire, but you know, one thing that's become clear as we've kind of come out of or gone into this more difficult environment to operate in is in the good times, we probably over attribute to teams and products, how good they are. And in the bad times, you can't just blame everything on macro, but I think it makes you reflect on the over attribution you probably did in the good times. And so You know, one thing I've changed my mind on is you got to be more balanced about how much credit you give to the momentum of a company from the market environment versus the actual execution they're doing and know that there's the balance there and, you know, good execution doesn't always mean that it leads to great momentum. Sometimes great momentum is also influenced by these market environments or variables that are harder to quantify.

AI assessment note: “one thing I've changed my mind on is you got to be more balanced”

Q How do you approach trust, Vince? Trust is a tough one. It's very difficult. It's like hard to gain, easy to lose. How do you approach that?

A Yeah. I mean, in some ways, if you're trying to, we talk about this as a team from our culture, a lot of when you join the Thrive team, you know, the focus is how do you build trust with the organization? And, you know, I would tell you, trust is one of these things where in great organizations, it can be given by default. In many organizations, you have to earn trust. I think we have a culture in Thrive that definitely You know, people get a lot of trust by default because of how small our team is and how autonomous our model is. For me personally, I actually had, uh, you know, a really great investor that you guys would know told me something that was interesting, which is trust with founders is actually just being very predictable. People want to not feel like they're getting surprised by how you're thinking. They want to understand how you think, how you're going to react and feel like, you know, they understand you. And that ultimately kind of breaks down these boundaries between people and allow you to have some mutual Trust and empathy with each other. And so I think with founders in particular, when we talk about building trust, it's like any partnership, you've got to increase the reps, get in the water in the trenches with them, and they have to understand how you think. And ultimately, I think you've got to telegraph how you're going to make decisions with them and m…

AI assessment note: “trust with founders is actually just being very predictable. People want to not feel like”

Q I promise we're going to bring it back to schedule, but I'm enjoying this too much. Um, and they said, bluntly, your ability to keep a level head is actually one of your strongest points as an investor. How do you think about maintaining an even keel in terms of mindset? It's funny. It's rare, especially among younger investors. How do you think about that and how you do it?

A Well, I think part of it is, you know, you're a byproduct of your environment. I think for me, I've gone through a bunch of different waves in my career, and that's helped me understand what volatility looks like, feels like, and so I don't think you just become level-headed as a person. I think you kind of build into that psyche over time. Uh, you know, someone said to me once, uh, which is a lie that I've been saying to the team a bunch internally is, you know, things are never as good as they seemed, and they're never as bad as they appeared. And I think just keeping in mind that the rest of the environment around you does react to these peaks and troughs of your emotion in the market and the volatility. And ultimately, you know, in good times, people over extrapolate in bad times, people under extrapolate. And if you maintain this kind of more balanced approach, I do think it helps you hold more clearly, you know, what are we ultimately looking for in solving Around for a given investment or person or situation. And I've just found that it's not productive to necessarily get caught up in the emotions. You got to try to think clearly. And if you can remove that noise from the volatility of the emotion, it allows you to focus on the core a lot more easily. But that said, I think you do need to trust your gut and you do need to be emotional and react that way. And so I wouldn'…

AI assessment note: “I've gone through a bunch of different waves in my career, and that's helped me”

Q Why do you think it's not obvious? Because you have to assume that essentially we'll move from a search interface to a chat interface as the primary UI of engagement. Is that why? Or are there other reasons why it's not obvious?

A I think a lot of investors get tripped up on trying to be so precise on TAM and market and defensibility and the moats around businesses and trying to map that all to price. And those are so important in the investment decision-making process. But when it's so early in a technology cycle like this, it almost is a little bit more of a venture mindset where there are going to be 50 reasons you can say no, and we're not going to have answers to every question. But we need to really think about the things that can go right. I mean, we're not talking about building the next unicorn or decacorn. We're talking about disrupting search or Google. I mean, that's a trillion dollar opportunity. So sure, I can't put a TAM around ChatGPT, but I can tell you, like, we're not talking about a small prize at the end of the day. And so I think when we say it's not obvious to people, people aren't thinking about it in this lens. They're thinking about it in the box of You know, what does this chat interface do? And oh, those use cases aren't that valuable. And I think it does take a, a higher level of creativity or imagination to ultimately think about the world that way.

AI assessment note: “investors get tripped up on trying to be so precise on TAM and market”

Q I think we change so much as investors over time in terms of what we value in the companies we invest in and the founders we invest in. When it comes to what's changed and what you appreciate in an investment, what has changed about that mindset?

A It's actually very clear. The thing I've developed the most on in my investing mindset is this deep empathy for the customer and trying to really think deeply about Not just what's the product and trying to write that down on paper, but really to understand how the business is going to get built and mapping those nuances to who the person is, what the product does, how does that manifest itself in the business? You know, do you have a sales intensive product that's going to require people to be kind of constantly out there and on edge and with their customers? Do you have a product that's more middleware and so you need somebody Who's gonna be willing to grind it out and not be in the limelight? Do you have a product that requires a lot of creativity? And that means you need to set up your org to be creative. Well, there are certain org structures that promote that more. And so, you know, when you think about where you can develop as an investor, I think where I have developed the most by far is continuing to understand the connectivity between this rigorous financial lens, uh, very much of where I started at Tiger, To how do you build a company? And at that intersection, you know, it's really hard to get to clarity on, but when you do, it is clear. And I think, you know, the best companies have very, very simple explanations that, you know, it trickles down on the company. The…

AI assessment note: “The thing I've developed the most on in my investing mindset is this deep empathy”

Q or whether there's an alternative mechanism that will kind of bifurcate the market. Now, when we look at like, you know, open AI, it fundamentally says that there will be one model that rules them all versus the world of many models with hugging face and the like being others. How do the two Views differ, and why do you think there will be one model to rule them all?

A Well, I mean, obviously these are my opinions, not the companies, just to make that clear to everybody. I don't think I would characterize OpenAI as one model to rule them all. And obviously there's all kinds of talk right now about it being closed source and the model should be open source for the value of the community and all, all of those factors. But I'd say actually, if you give the company credit for this stuff, which they've released, they have done a lot in the open source and contributed back to the community. Clip was a model that They put out there that helped a lot of the image generation open source models. Whisper was for audio. They open source the inference framework called Triton on top of GPUs and CUDA to ultimately drive more efficacy and scalability of inference. And so they have done a bunch of that side. They obviously have kept the core GPT model behind an API and paywall. But, you know, I think thinking about it as this entirely closed ecosystem in my mind doesn't really give credit to what the company has done on the open side. You know, and the dimension by which we're, I think founders we at least talked to are choosing their model has quickly changed from who's got the biggest model and who has the lowest cost model to these new dimensions, which is if you're gonna build a company today, Harry, you don't wanna have to, you know, think about the scal…

AI assessment note: “I don't think I would characterize OpenAI as one model to rule them all.”

Q Yeah, no, I totally get you. Okay. You're on incredible boards. You can choose one board member for your company. Who would you choose?

A Well, I think it depends on the company, but you know, this is like picking favorites. I'm lucky to work with so many great people. You know, the person that stands out that I've learned so much from is Eric Vishria. He's on the bench link board. He's on the board of this company I work with called airplane. Eric is I think just an incredible blend of has the operational instinct rigor, but also it's fun to be around and he's able to land his messages in a really effective way with entrepreneurs. And he also just has like a really great balanced perspective on being commercial and understanding how all of that works and replaces the strategy of the company. And I found that perspective to be something that I'm continually learning from as I'm listening to him. And when you find those kinds of people, you know, I think you just want to surround yourself with them.

AI assessment note: “the person that stands out that I've learned so much from is Eric Vishria”

Q I totally agree with you in terms of applying that kind of different lens and mindset, but then there are also core that you have to do, which we all do when we make an investment. When you thought top down on market analysis, how did you approach top down market analysis when you were sitting with Josh on this one?

A I go back to as these new technologies scale, It's so hard to be precise about a TAM. And so more of what we got into the psyche of thinking about is if you looked at other big technology movements and releases, how did they scale? I mean, the iPhone went from a million phones a year, kind of post launch to a hundred million in five years. AWS took six or seven years to get to a hundred million dollars of run rate, but they went from a hundred million to ten billion in like six or seven years. Google went from nothing to ten billion in the first six years of monetizing. And so obviously this is rarefied era we're talking, and these are three of the most transformational companies on the planet. But the technology, if you really think about it and the zeitgeist it's captured, I mean, it is of that elk, in my opinion, of the transformation it can have of the world. And so for us, again, it's, it's less about thinking about the exact TAM and it's more about If we think about what the world's going to look like in five or 10 years from now, how are we going to look back and say, wow, I can't imagine the world without this kind of thing. And when you have experiences like that, I mean, that's what gets us out of bed. These are the kinds of things that create new categories, new companies. Um, and so that, that was what a lot of the discussion was. And, uh, you know, maybe that sound…

AI assessment note: “it's less about thinking about the exact TAM and it's more about”

Q Can I ask you a bit of a weird personal one, Vince, but this is a big check for you. Were you nervous about that?

A I think we had the same level of excitement that we've, that we have in most investments. You know, again, I, I give credit to Josh. I give credit to the rest of the Thrive team. We don't have a culture where there's this kind of, you know, sharp elbowed mentality or people feel on edge for making investments because prices are high or checks are really large. We have a culture where we support each other and we have a growth mindset and learn. And so if this ends up not working out, I don't think we're going to look back on this and put all the onus on one person You know, or two people that made a decision. I think we're going to look back on this and say, we got there as a team. You know, it was the right thing at the time, but here's the learnings from it. And here's how we're going to adapt our lens and course correct in the future. And so it is intimidating and it's nerve wracking sometimes to write large checks and investments, but in the right team and culture, you know, I think this is how we enable ourselves to make these kinds of transformational investments. And frankly, I think there are a lot of firms that Could not have done this because their organizations are not set up to make these kinds of big decisions.

AI assessment note: “it is intimidating and it's nerve wracking sometimes to write large checks”

Q Do you think so? I, I, I had Tom, I had Tom Tungus on the show recently, and he said that Google have been the most disappointing of all, and they were his former employer. And he said, terribly disappointing. You know, we've seen AWS partner with Hugging Face. Who do you think is doing well?

A I think it's hard to be dismissive of these companies. If you think about where the best talent in AI is right now, I think it's OpenAI, And then I think you'd, everyone would tell you it is Google and Facebook and Microsoft and Amazon. And maybe there are folks that have kind of dripped their way into the startup startup ecosystem. But by and large, the talent is so clustered in these big tech companies. And so I get it that they're tripping over themselves, trying to figure out how to navigate these giant organizations they've created. But let's not also kid ourselves. You know, we've talked about this outside of the context of OpenAI, Up level it to AI. We work with lots of startups that compete on things like presentations or content creation. You know, what's scary to me right now is if you're a startup, large companies are shipping product. The kind of canonical examples were that, oh, the big incumbent can't move and they're slow footed and you got years to execute before they do something. I mean, Microsoft's 200,000 person company They've shipped AI in Bing, AI in PowerPoint. They're rolling out of the other products. Adobe's got the content creation in their product already. You know, even the big startups like Notion, those, those folks, I've been so impressed with how much they've shipped in their product so quickly. And so if you're a startup, I get that you have t…

AI assessment note: “I've been so impressed with how much they've shipped in their product so quickly.”

Q I totally agree with you in terms of applying that kind of different lens and mindset, but then there are also core that you have to do, which we all do when we make an investment. When you thought top down on market analysis, how did you approach top down market analysis when you were sitting with Josh on this one?

A I go back to as these new technologies scale, It's so hard to be precise about a TAM. And so more of what we got into the psyche of thinking about is if you looked at other big technology movements and releases, how did they scale? I mean, the iPhone went from a million phones a year, kind of post launch to a hundred million in five years. AWS took six or seven years to get to a hundred million dollars of run rate, but they went from a hundred million to ten billion in like six or seven years. Google went from nothing to ten billion in the first six years of monetizing. And so obviously this is rarefied era we're talking, and these are three of the most transformational companies on the planet. But the technology, if you really think about it and the zeitgeist it's captured, I mean, it is of that elk, in my opinion, of the transformation it can have of the world. And so for us, again, it's, it's less about thinking about the exact TAM and it's more about If we think about what the world's going to look like in five or 10 years from now, how are we going to look back and say, wow, I can't imagine the world without this kind of thing. And when you have experiences like that, I mean, that's what gets us out of bed. These are the kinds of things that create new categories, new companies. Um, and so that, that was what a lot of the discussion was. And, uh, you know, maybe that sound…

AI assessment note: “it's less about thinking about the exact TAM and it's more about”

Q Do you think so? I, I, I had Tom, I had Tom Tungus on the show recently, and he said that Google have been the most disappointing of all, and they were his former employer. And he said, terribly disappointing. You know, we've seen AWS partner with Hugging Face. Who do you think is doing well?

A I think it's hard to be dismissive of these companies. If you think about where the best talent in AI is right now, I think it's OpenAI, And then I think you'd, everyone would tell you it is Google and Facebook and Microsoft and Amazon. And maybe there are folks that have kind of dripped their way into the startup startup ecosystem. But by and large, the talent is so clustered in these big tech companies. And so I get it that they're tripping over themselves, trying to figure out how to navigate these giant organizations they've created. But let's not also kid ourselves. You know, we've talked about this outside of the context of OpenAI, Up level it to AI. We work with lots of startups that compete on things like presentations or content creation. You know, what's scary to me right now is if you're a startup, large companies are shipping product. The kind of canonical examples were that, oh, the big incumbent can't move and they're slow footed and you got years to execute before they do something. I mean, Microsoft's 200,000 person company They've shipped AI in Bing, AI in PowerPoint. They're rolling out of the other products. Adobe's got the content creation in their product already. You know, even the big startups like Notion, those, those folks, I've been so impressed with how much they've shipped in their product so quickly. And so if you're a startup, I get that you have t…

AI assessment note: “Microsoft's 200,000 person company They've shipped AI in Bing, AI in PowerPoint.”

Q come up against. My question to your point there, though, is the big question for me is actually in this next wave of AI. Is the value captured predominantly by, ah, incumbents, or is it captured by startups? And I more lean towards 90% of it being captured by incumbents, which isn't great for us as venture investors, but do you agree with me, or do you say something different?

A I think it's too early to call. Maybe that's a cop-out answer, but to put it in context, if you go look back in time at these big technology cycles, they are great moments to create new categories. And so maybe that's a better lens to look at it through. Where will new categories get created? Where being an incumbent or being a startup won't matter. And if you look back at the.com, Google, PayPal came out of it, Google about finding information, PayPal about it, bank online. Social came after, you know, Facebook was connecting all these people online and Twitter was the town square for broadcasting information. You know, mobile, the answer wasn't Salesforce was going to build mobile CRM and that's where all the value was. The answer was you put a computer in everyone's pocket and DoorDash and Uber came out of that because there's geolocation, the ability to have connectivity. WhatsApp came out of that, which was people take it for granted now, but you know, 20 years ago, it was a regional telecom that managed all of your SMS. WhatsApp abstracted that as a, you know, protocol on the internet that was encrypted and allow people to communicate more seamlessly. So in my view, what we're looking for, if I was to answer that question is, yes, if you're going toe to toe right now with an incumbent on their home turf and their shipping, I think it's a hard bet to take the opposite side…

AI assessment note: “I'd bet on the startup, you know, 10 times out of 10”

Q or whether there's an alternative mechanism that will kind of bifurcate the market. Now, when we look at like, you know, open AI, it fundamentally says that there will be one model that rules them all versus the world of many models with hugging face and the like being others. How do the two Views differ, and why do you think there will be one model to rule them all?

A Well, I mean, obviously these are my opinions, not the companies, just to make that clear to everybody. I don't think I would characterize OpenAI as one model to rule them all. And obviously there's all kinds of talk right now about it being closed source and the model should be open source for the value of the community and all, all of those factors. But I'd say actually, if you give the company credit for this stuff, which they've released, they have done a lot in the open source and contributed back to the community. Clip was a model that They put out there that helped a lot of the image generation open source models. Whisper was for audio. They open source the inference framework called Triton on top of GPUs and CUDA to ultimately drive more efficacy and scalability of inference. And so they have done a bunch of that side. They obviously have kept the core GPT model behind an API and paywall. But, you know, I think thinking about it as this entirely closed ecosystem in my mind doesn't really give credit to what the company has done on the open side. You know, and the dimension by which we're, I think founders we at least talked to are choosing their model has quickly changed from who's got the biggest model and who has the lowest cost model to these new dimensions, which is if you're gonna build a company today, Harry, you don't wanna have to, you know, think about the scal…

AI assessment note: “I don't think I would characterize OpenAI as one model to rule them all.”

Q unpack from Josh how he does it. He never quite tells me. Wonderful, Josh, but secret sauce he keeps close to has Chest. Uh, I do want to ask, you know, Lee is one of the most special people in this business in my eyes. I love him as a person. He's gifted in many ways. What did you learn from working with Lee and from your time at Tiger?

A First of all, I feel really lucky to have started my career working with Lee's. You know, I think he's a really special investor and I credit, you know, a lot of where I got started to work in closely with him. Tiger also is, you know, very, obviously they've become, uh, in the news a lot more recently, but the firm's been around for more than 20 years and You know, I think if you look at how it got off the ground, it is very much in these kind of hedge fund roots. You know, Chase Coleman, who started the firm, he was in his mid twenties. He was really young. He had this hedge fund mentality mindset coming out of tiger management post the dot com bubble. And the way we thought about investing in companies was very financial. Look at the P and L and understand deeply how do the numbers tell the story of what the business does and how does that ultimately make a good business, a great investment. And I learned a lot just from the financial rigor of doing that. But what's interesting is when you can contrast that to what we do at Thrive and how Josh has built the firm, you know, we, we started from the roots of where Josh was, which was a founder. He was the same age as Chase when he started Thrive, but ultimately he was trying to build a startup. And so the mindset was very much, how do you empathize with the entrepreneur? And we focus much more on The product and the customer an…

AI assessment note: “I learned a lot just from the financial rigor of doing that.”

Q lost money because of an externality that was outside of our control, which is a very frustrating reason to lose. How do you think about the impact in coming year or so of regulation? Elon has been very clear in saying we can't wait until it's in the hands of everyone, because then it is too late. How do you think about regulation in the next six to 18 months?

A I don't want to speak for the company on anything, because I know this is a topic that's out there Uh, in the mainstream, I think regulation will come to AI and it will be necessary. Like that's, I don't doubt that at all in my mind. You know, I think it has to be done in partnership with the companies that are building because, you know, regulation for the sake of regulation is not going to be what solves the problems people are concerned about. You've got to go understand the nuances. You have to understand the technology. And so I would hope that just like we open AI is, I would hope that other Companies building an AI are also working with regulators to understand what is the technology and help educate them to get to the right decision. I do think, you know, there's kind of some negative stigma going around open AI on regulation and security and safety. And in, in my view, I think they're being pretty proactive. You know, I don't know all the things that they're doing internally, but, you know, as an example on GPT four, we saw the demo in the fall. They didn't just release the product then they took, I think four or five months To test and learn about safety in the edges of the model and then ultimately released it to the world. And so they're not going to get it perfect every time, but I do think trying to let people build with and understand it is important and poorly d…

AI assessment note: “I think regulation will come to AI and it will be necessary.”

Q investing style before a quick fire. I have to ask, I, I would get, you know, in trouble if I didn't Vince, I'm, you know, very charming British guy. Otherwise, uh, the price was high. I reported twenty nine billion dollars. Um, what was the discussion internally around price? Cause you still have to see real upside. Like what was the discussion and how did you project upside scenario planning?

A Well, we certainly had a discussion heated discussion around it. You know, we have a very team-oriented firm, and so we disagree and commit once we make decisions, and we make decisions to this team, and we live by that. No one, no one person makes a decision, and the price here was high, just on an absolute basis. It doesn't matter what company you're investing in, at the prices that this round was done, you know, you're talking about very upper echelon type outcomes to justify good returns, but I, I kind of come back to the The intangible that it's really hard to understand the pace of adoption of these major technologies. And any numbers I would put on paper for you would look insane. You would look at them in a spreadsheet and tell me there's just no evidence to support this. But then you look at these iconic technologies and the great ones all follow that insane curve. And so the balance we try to hold, I think that's what makes Thrive a really special firm. Is we're able to kind of separate ourselves from the kind of quantitative rigor that, you know, we rely on for a lot of investments we do and hold the tension of what could go right. Think creatively, understand how this could look like the most transformative things. And if that happens again, I, this is, you know, we're talking about search potentially getting disrupted or something that enables workflow automation f…

AI assessment note: “we're able to kind of separate ourselves from the kind of quantitative rigor”

Q How do you determine when to throw the financial rigor that you do have in the team out of the window versus when it's needed to make a sound and wise investment?

A It's less about throwing it out the window and it's more about putting it in context. A financial model is a tool to help you make a decision. You need many tools to make a decision. And so it's less about, is that the only thing we use and we throw it out the window and it's more about what's the weight by which we put on the financial rigor and model as the tool to make the decision. And I think for us, there aren't that many iconic companies that could create it. And so no iconic company, you know, at least that we've been a part of, was it clear and obvious in the early days of that technology, they always get priced well ahead. And they look cheap in hindsight because they defy the gravity of the model. And so it's kind of the quintessential humans think linear and the best things happen exponential. You know, we have to understand that, you know, going back to being level-headed, when do our psyche or heuristics break down in an investment decision-making process? And when they do, we need to compensate them with a different tool in our toolkit.

AI assessment note: “It's less about throwing it out the window and it's more about putting it in context.”

Q What have you changed your mind on in the last 12 months, Vince?

A This is probably more, this is not for the rapid fire, but you know, one thing that's become clear as we've kind of come out of or gone into this more difficult environment to operate in is in the good times, we probably over attribute to teams and products, how good they are. And in the bad times, you can't just blame everything on macro, but I think it makes you reflect on the over attribution you probably did in the good times. And so You know, one thing I've changed my mind on is you got to be more balanced about how much credit you give to the momentum of a company from the market environment versus the actual execution they're doing and know that there's the balance there and, you know, good execution doesn't always mean that it leads to great momentum. Sometimes great momentum is also influenced by these market environments or variables that are harder to quantify.

AI assessment note: “one thing I've changed my mind on is you got to be more balanced”

Q lost money because of an externality that was outside of our control, which is a very frustrating reason to lose. How do you think about the impact in coming year or so of regulation? Elon has been very clear in saying we can't wait until it's in the hands of everyone, because then it is too late. How do you think about regulation in the next six to 18 months?

A I don't want to speak for the company on anything, because I know this is a topic that's out there Uh, in the mainstream, I think regulation will come to AI and it will be necessary. Like that's, I don't doubt that at all in my mind. You know, I think it has to be done in partnership with the companies that are building because, you know, regulation for the sake of regulation is not going to be what solves the problems people are concerned about. You've got to go understand the nuances. You have to understand the technology. And so I would hope that just like we open AI is, I would hope that other Companies building an AI are also working with regulators to understand what is the technology and help educate them to get to the right decision. I do think, you know, there's kind of some negative stigma going around open AI on regulation and security and safety. And in, in my view, I think they're being pretty proactive. You know, I don't know all the things that they're doing internally, but, you know, as an example on GPT four, we saw the demo in the fall. They didn't just release the product then they took, I think four or five months To test and learn about safety in the edges of the model and then ultimately released it to the world. And so they're not going to get it perfect every time, but I do think trying to let people build with and understand it is important and poorly d…

AI assessment note: “I think regulation will come to AI and it will be necessary.”