The Exchanges

Q that listen, and they'll be going, great, great, this is getting good, but which camp am I in? Am I in the one that could raise more and should raise more, or am I in the one that should stay leaner and be more milestone driven and capital efficient? How would you delineate between the founders that should And should not raise those slightly large jumbo seeds versus normal seeds.

A So I think this actually kind of comes back to the market sizing question you asked, which is there are certain companies that have a very deterministic sense of their market opportunity. Let's say they're going and replacing something that already exists. You see this a lot in cybersecurity, for example, I think these kinds of companies, they, they understand the headroom and they understand if I get this much market share in this period of time, like this is how big my business can be and therefore how valuable it can be. With, with a modest degree of confidence. Where I get really conservative in terms of the advice that I give founders that I work with on fundraising is when companies are fleshing out a new market. Like, we just don't know. It could be really large. It could be non-existent. I can tell you that the cases where I've been involved with companies is, is where they've, where they've done that wrong is when they just didn't understand their market yet, right? And I think if you have a poor understanding of your market and there's a non-zero chance that that market could be very constrained, optionality is without a doubt your friend, and I'm very honest about that with the founders I work with.

AI assessment note: “Where I get really conservative in terms of the advice... is when companies are fleshing out a new market.”

Q are doubling, maybe two and a half X-ing, and they're going from seven to 14 or 14 to 28. When I send that to you, Bucky, for a series B or C, I think you're gonna stack rank it against the AI companies and go, this just isn't that interesting. Am I right to be concerned about that? And are we in a fundamentally different world of revenue trajectory scaling?

A Look, so I think core to any VC's job is the ability to prioritize and ruthlessly reprioritize, right? And part of that is just like, what are the best ideas that I have in front of me at any given point in time? I'm gonna spend time on those. And right now, to your point, the bar is going up for what best idea looks like when it comes to growth rates and momentum. Um, we can talk about the quality of that revenue and how it's very mixed, and this has been discussed many times on this show and outside of it, so I don't need to repeat that. But I really think you're right to say that, like, what great looks like has really changed. Um, I think the book is still being written on some of those companies that you mentioned and, and, and their peers in terms of just how durable that revenue is. Again, I'm not going to repeat myself and go down that rabbit hole. But I think what you're seeing is that the pent up demand for intelligence and all of these different areas of like work is just so unbelievably high that the growth rates in the market pool around these companies are like nothing we've ever seen. And I can tell you now as an investor, when I'm out there looking for new ideas, I am often looking for the signals that I saw in companies like Glean or companies like Windsurf that have just had this incredible market pool and reception. And I can tell you that it's almost made me…

AI assessment note: “I really think you're right to say that, like, what great looks like has really changed.”

Q So is the future of venture domain specialization?

A So I think this is, like, a very good segue into, like, theoretically why domain expertise and specializing in domains matters, which is, like, if the game really becomes how do I pick which founders to spend time with and how, when I meet a new company, can I readjust my prioritization of spending time developing insights and rapport with that founder and that company? Domain specialization really, really helps there. So again, there will always be brilliant generalist investors Who can do a good job of this and they just have uncanny instincts for, for startup quality and founder quality. But in my opinion, being domain focused really, really helps with that picking aspect of picking who to spend time with, who to position yourself with for when they, when they do decide to raise. And, and, and then ultimately when they do decide to raise, being able to like reinforce that, like, hey, did I pick the right person to spend time with or not? Or am I just running away with this because I've spent so much time on it, which is a whole nother bias you have to manage.

AI assessment note: “in my opinion, being domain focused really, really helps with that picking aspect”

Q On the picking side, when you've picked and you've picked wrong, what did you not see that you wish you had seen?

A So I would say the single biggest thing that I've changed my mind on as an investor in the 11 or so years that I've been doing this comes down to, you know, what I did before investing, which is I was, as I said, I was a member of Cisco's corporate development team. And at a place like Cisco, when you're a member of a corporate development team, your job is to go and look at markets and technology and figure out, like, what are the lucrative markets? What are the dynamic markets? And then what is the right technology that the company should have to go and prosecute that market? Notice I did not mention founder quality or quality of execution in that entire statement. So I think when you come from a role like that and you move into, to, to venture, it's very tempting to kind of like apply that same lens to looking for great companies. And again, I can't say anything about this that hasn't already been said, but like, it's very, very obvious to anyone who's been doing this for a long time. Like you just get this visceral feel for, it's all about the founders. And so I would say that like the thing that I've really changed my mind on is I used to kind of go around developing Theses and trying to figure out like where the world was going on the level of markets and technology. And now what I've realized is it's not to say that work doesn't matter. It's actually very important and v…

AI assessment note: “Notice I did not mention founder quality or quality of execution in that entire statement.”

Q today. And I think you see that with all of the mega platforms also doing pre-seed. And who did, who won from Winsurf? Neil Mater. Green Oaks led the seed. Neil is a prolific seed investor and brilliant at it, by the way. Um, DST are prolific seed investors. The huge growth firm of old. I don't think you can win venture unless you're doing pre-seed. Discuss. Do you agree?

A Yeah. So this kind of comes back to my, my view that I shared with you about how, if you're going to build one of these mega platforms and sustain a compelling position in the market with one, you really do have to stay dedicated to like the craft of like helping people build things from scratch. And to do that, you have to be in the precedency business. And I think the moment you stop doing that is the moment you lose the instincts for just like how fast these companies can change and how quickly the story can improve. Such that you kind of sit back and are looking for perfection instead of really seeing what these companies can be. And like, I actually think that these AI app companies we keep talking about is a great example of like, if you looked at Harvey at the Series A and you saw its product, you probably weren't that impressed. It was just a very early product. The scaffolding of it was clear. What was possible with better models was clear, but it was still a very early and raw product. And I think one of the mistakes that you could say a lot of investors have made in this wave of AI investing as it relates to these app companies is they failed to imagine what they can be. As the models get better, as their understanding of the pain point gets better, as they spend more time with customers. And so I think where this comes back to this question is if you're not spending…

AI assessment note: “to do that, you have to be in the precedency business.”

Q How do you analyze that? What does it allow you that the other strategy does not focus, but does that increase your velocity to AGI?

A So I think the argument would be, and again, I can't speak for, for the founders of that company, but like the argument that I would, that I would make would be today. There are a lot of decisions that trickle into the R and D and research organizations of say an open AI. That are in service of helping them build better products in the short term, right? Like the model needs to behave a certain way, so ChatGPT can be better, or deep research can be better, or whatever it may be. There are for sure short-term optimizations being made there, and I've seen it with my own eyes when I talk to people that work at those companies. The argument for not getting caught up in that is you can just be entirely long-term. You can make bolder research bets. You can, you can allocate resources differently. You can maintain a smaller team that's more focused, as you said. So I think that's really the, the argument is like, Having to generate revenue and build a business that you can take public someday is, is, is going to come with short term thinking. And if you sort of say, hey, let's, let's assume we have access to capital that we need. And let's say we can just kind of sweep all that aside. What does that buy you? I think it buys you less distraction and more ambition.

AI assessment note: “What does that buy you? I think it buys you less distraction and more ambition.”

Q You mentioned Glean there, and hey, if you invest in Glean, you can't do OpenAI. I'm just intrigued. Is the age of competitive investing over? You know, you mentioned being an investor in Anthropic. You're also an investor in Mistral. Does it matter anymore investing in competitors?

A So I think every firm takes a very different view on this. And I can tell you that when we were at Kleiner Perkins, it was, it was something that we, it was kind of a red line that we wouldn't cross. And the reason for that is because we invested in so few companies and we go so deep with each of those companies that In our mind, it was just too hard to feel like we could really provide that level of service to, to each company in a way that would make conflicts and non-issue. Um, I think it's a little harder for me to speak about kind of how we do things at light speed in that sense. But I think to your point, you're seeing, you're seeing a lot of these later stage investments, um, get made into sort of multiple players. And I think part of that is like, there's just so much demand for capital from these big firms that these model providers want. And I think on the other end, it's really hard to say how this is going to play out to the point that I think there's a need for diversification. as well on the investor side. And so, one argument would be, hey, pick one of these companies, go all in on them. And you can see that's sort of what Thrive is doing with OpenAI. You could also say the same about Founders Fund. Another would be, hey, who knows how it's going to play out? And I think what you're seeing with, say, Andreessen Horowitz is they're, they're trying to invest in eve…

AI assessment note: “I think it's a rational strategy so long as you have buy-in”

Q On the picking side, when you've picked and you've picked wrong, what did you not see that you wish you had seen?

A So I would say the single biggest thing that I've changed my mind on as an investor in the 11 or so years that I've been doing this comes down to, you know, what I did before investing, which is I was, as I said, I was a member of Cisco's corporate development team. And at a place like Cisco, when you're a member of a corporate development team, your job is to go and look at markets and technology and figure out, like, what are the lucrative markets? What are the dynamic markets? And then what is the right technology that the company should have to go and prosecute that market? Notice I did not mention founder quality or quality of execution in that entire statement. So I think when you come from a role like that and you move into, to, to venture, it's very tempting to kind of like apply that same lens to looking for great companies. And again, I can't say anything about this that hasn't already been said, but like, it's very, very obvious to anyone who's been doing this for a long time. Like you just get this visceral feel for, it's all about the founders. And so I would say that like the thing that I've really changed my mind on is I used to kind of go around developing Theses and trying to figure out like where the world was going on the level of markets and technology. And now what I've realized is it's not to say that work doesn't matter. It's actually very important and v…

AI assessment note: “it's all about the founders.”

Q this 50 customer call log to one of your companies that I've done? I want the first meeting. And you're like, you did 50 customer calls for a meeting? Or like, you did this 28 page market analysis for a first meeting? The cost of first meeting entry has gone through the roof, and so you cannot get that first meeting unless you've been at the pre-seed or the seed.

A Look, I would say it's possible if you make a very, very small investment in a company at the very early stages to use that as a wedge to build a compelling relationship with an entrepreneur. But it is by no means a given. I can tell you countless examples of where, uh, let's just say later stage firms or, you know, even just firms that weren't necessarily the lead investor in the early days did something, let's just call it low conviction, thinking they were going to get access where it just didn't serve them. So I think it really comes down to this kind of, at this point about picking once again, which is like, hey, if you're going to start doing that as a later stage firm, you've got to be committed to putting the legwork in to actually use that as a wedge to develop that relationship that does give you the access. Because I think The check itself does not. And so where this comes back to picking once again is like, let's say you do that a hundred times, which of those hundred are you going to put that work in with? Right. And so you have to have taste judgment and, and, and sort of an instinct for, as these companies are developing, like which of those do I need to, to really spend time with? And I think that goes for any investor at any stage, like, which is again, why I believe picking is more important than you do.

AI assessment note: “it's possible if you make a very, very small investment in a company”

Q like Bucky did. And so totally to your point, it helps you win. Can I ask you one, do you even need to pick, my friend? You're now at light speed. You can just wait. I mean, part of me as a friend would say to you, just wait until the C, pay up like Vince did at Thrive for the, you know, thirty billion round, and ride it, baby.

A Look, so that strategy can definitely work, but I would argue, and this is maybe world's smallest violin, that picking is actually much, much harder. In these larger firms that have notoriety in the market. And the reason for that is because the opportunity set that they have access to and the number of founders that are willing to lean in and work with them is just higher, right? And so you just have more inventory to choose from. And I think because you, you have a little bit of magnetism to you as a platform that a lesser known firm doesn't, you just end up having a lot more at the top of funnel to sift through. And I think if you're not very diligent about how you prioritize and manage that, picking actually can be like the failure mode of a lot of GPs at these funds.

AI assessment note: “Look, so that strategy can definitely work, but I would argue, and this is”

Q My question to you is, what do you think the likelihood is plateauing, like we saw in self-driving for many years, or a continuing Progression efficiency that we have been seeing over the last year?

A Well, look, I think, I think when it looked as though pre-training was no longer as lucrative a scaling dimension as it was originally positioned as, um, I think there were a lot of people that were rationally saying, Hey, like progress is going to slow down and, and, and things might be the way they are now. Right. Then this test time compute paradigm came along and now we have things like post-training and reinforcement learning that are presenting additional Uh, additional scaling dimensions that I think, like, it's just really hard to say, and it's really hard to say because there are these amazingly talented people inside of all these research labs that are every day trying new things and trying to figure out what that next scaling dimension might be. So I think the right way to frame the answer is, like, when do we run out of new scaling dimensions? And right now that appears to be very unlikely, at least in the near term, but at some point it could happen. But I also have just learned to never bet against human ingenuity, and given the best and the brightest are now so heavily concentrated concentrated inside of these big labs, trying new things every day. I personally believe like there will always be new scaling dimensions and whether the next one is as steep in terms of progress as the last is hard to say, but it's really hard for me to imagine a world in which we jus…

AI assessment note: “when do we run out of new scaling dimensions? And right now that appears to be very unlikely”

Q Price is always very hard when you have one of these prized assets. It always seems painfully expensive in the short term and like bluntly very prudent in the long term often. How do you think about price sensitivity when paying up for the 0.01% assets?

A So my former partner, Mamoon has taught me many things. And one quote that sticks with me on this one is the best companies always feel expensive. And, and I think that's proven true in every example I can think of. So I think it's really about determining one, like, is this one of those truly special companies? And obviously the earlier you have to make that decision, the much harder it is in the area, it's going to be higher. And I think therein lies probably some reason to be, to be a little bit more constrained on your thinking around price. On the other hand, um, and this kind of dovetails into like a question of like, well, what does it take to win a competitive round these days? Like, I think there's always someone who is going to believe more than the field. Right. And so If that is important to the founder, then you sort of have a hard choice to make. Whereas like, if you think that series A, this is a very special asset and they're pushing price beyond kind of the way your mind can rationalize it. History would say that those companies always feel expensive. Those companies can run and compound for a very long time. And I think especially today when we're in a world where, let's say if you talk about like these agent products that are quite literally going from like going after existing software spend to starting to replace human labor. It kind of comes back to this o…

AI assessment note: “one quote that sticks with me on this one is the best companies always feel expensive.”

Q Do you buy that though? Cause I, I, Dylan always seemed to be brilliant. And across the board, like when you speak to John Lilly, who led the A at Greylock, like he was like, he was clearly brilliant. The company was not hitting, but like he was brilliant. Do you know what I mean? Yeah.

A I mean, I think, but I think you have a lot of very special founders whose companies don't work number one. And so you can say that about A number of founders and a number of companies, but I think you're starting to see more and more evidence of these companies that just took longer than people, than people thought, right? I mean, there, there are just so many now. It's not just Figma that I think you kind of have to stay open-minded to that. And there's another dynamic at play here, which is that I think that so much of the low hanging fruit has been picked off the tree in terms of like software businesses that you can build, that you're starting to see the most interesting companies be those where there's just something deeply technical, like a problem they have to go and solve. It's never been solved before. And I think in doing so that can take in some cases like multiple years to get it right. And so, you know, a recent example of this is Clay, right? Clay is this company that's growing very, very fast on the sales tech side. And if I'm not mistaken, it was like five or six years of, of very little to no growth before, uh, before it took off. And so I think you have to be open-minded to those outcomes. And I personally try to lean into those outcomes because I think sometimes if, if something takes many years to get right, assuming it's something deeply technical and R an…

AI assessment note: “I think you're starting to see more and more evidence of these companies that just”

Q schools me every week. But he's basically very smart in saying to me, hey, we've seen this fundamental transition of, like, capital supply from your, uh, very, very large Franklin Templeton's, you name it, to Thrive and to Lightspeed. Who are doing these rounds and doing thirty billion dollar rounds into OpenAI, for example. Fundamentally, if we continue to see that transition, how much bigger will these mega platforms get?

A Look, I think that's a tough one because it really is somewhat indexed to this question of like how these mega trends like space and robotics and, and, and AGI really play out, right? If we, if we really are talking about companies that are going to get to some level of AGI such that they're going to be, you know, not just multi-trillions, but potentially larger than that. If we're talking about how Starlink and, and, you know, the, the kind of assets being built around that could kind of scale to those heights. These companies may not have to go public for a really long time because there will be so much demand to continue supporting them, uh, from, from the private markets, which as you said, are very, very robust right now. So the honest to God answer is I don't know, but I think we're going to find out as an industry over the next few years, and it's really going to come down to how some of these like truly blue chip assets that are, that are scaling to those levels, um, just how, how they trend and, and, and how the market kind of shapes around them.

AI assessment note: “they're going to be, you know, not just multi-trillions, but potentially larger”

Q What are those signals? That's fascinating. You have such a unique perspective from Glean and Windself in particular. What are those signals?

A So, so first I have to give kudos to my former partners, Mamoun and, and Lee Marie for being, uh, the leads and involved in those two companies. But what I would say is, um, those two companies in particular to me Found this zeitgeist at the senior most decision maker level, right? If you go and talk to a CIO or a CTO of a large enterprise today, they're furiously seeking out ways to apply AI to their business. And the reason for that is because their CEO and their board told them, you're going to get fired because the entire fate of our company depends on leaning into AI if you don't help us do this. So there's this veracity and this appetite to bring new solutions that sort of comprise like what it means to bring AI into business to Into these companies like I've never seen before. And I think Glean found that, um, very early on and the rest is history. It's just been on an incredible trajectory. And, and, you know, I think scaling into a true household name that embodies what like the AI app business of tomorrow looks like. I think similarly with windsurf, they did a really, really good job of going to these large enterprise technology leaders and helping them understand like where the future was going and the role that they could play in shepherding them that way. And I think you're going to see more and more of that, where. Once there's like a magic moment that a CIO sees,…

AI assessment note: “those two companies in particular to me Found this zeitgeist at the senior most decision maker level”

Q Does Anthropic not have to acquire then and move into the application layer?

A It seems very likely to me that in some form or another, Every single one of these frontier model labs will begin building both business and consumer facing products. And I think what you're seeing with open AI is certainly foreshadowing of that. You could argue X is trying to build its own super app around its models as of course. Um, and, and it's hard for me to see how each one of these players doesn't kind of end up in that place. Now there is a unique play here, which is, you know, SSI, Ilya Sitzkaver and Daniel Gross's company, which said, we're not going to do that. And you could say, Hey, that's a really contrarian move, but. What it allows them to do is keep a very lean team and kind of go straight shot towards AGI as they famously talked about.

AI assessment note: “Every single one of these frontier model labs will begin building both business and consumer”

Q assets. What worries me is that we're going to have the haves and the have nots, and everyone will go, well, we've always had that. It's always been a game of one percents, but I mean, truly the one percents, the naught point naught naught one percent. Do you think that's the case? Or do you think there will be a more even distribution of value in a next generation?

A So I think if you, if you pull investors right now and you ask them how many of these really, really valuable companies are going to exist in AI and Defense, in, uh, robotics, in space. Most of them will tell you there's going to be maybe a few of these companies that get to that really, really massive, unprecedented level of scale. On the other hand, I think we're still really early in the super cycle of each of these areas, right? I mean, I think there's a lot of talk about how it's going to be Helsing and Andril. There's a lot of talk around how it's going to be OpenAI and Anthropic, maybe XAI. I just don't think we know. And, and when I look at like a trend like robotics that is still so, so early, but at least in my mind, I've convinced myself that this time is truly different in terms of the, the industrial prep, uh, in terms of the industrial applicability of these products. It really, to me, looks like we could be surprised to the upside. But again, this is, this is sort of our job as venture investors is to be very, very optimistic. So I think that is the number one constraint to this whole experiment playing out favorably will be like, are there more than one or two of these per per mega category?

AI assessment note: “we could be surprised to the upside”

Q Can you unpack that? What do you mean? They pick duds, and that becomes apparent quickly?

A I think ultimately it's really hard when there's so many founders that are coming in your door, which many firms, you know, like Lightspeed or Kleiner Perkins have the luxury of, of, of experiencing. It's very, very hard to figure out, you know, what is the nine out of 10 one and the 10 out of 10 one. And I, and I think you can talk about that in the context of who the great founders are. You can talk about that in the context of momentum, but my point is it's a very humbling job for that reason. And I think to say that no one has to pick that's at an existing firm because the great companies are the great companies. That just hasn't been my experience.

AI assessment note: “It's very, very hard to figure out, you know, what is the nine”

Q assets. What worries me is that we're going to have the haves and the have nots, and everyone will go, well, we've always had that. It's always been a game of one percents, but I mean, truly the one percents, the naught point naught naught one percent. Do you think that's the case? Or do you think there will be a more even distribution of value in a next generation?

A So I think if you, if you pull investors right now and you ask them how many of these really, really valuable companies are going to exist in AI and Defense, in, uh, robotics, in space. Most of them will tell you there's going to be maybe a few of these companies that get to that really, really massive, unprecedented level of scale. On the other hand, I think we're still really early in the super cycle of each of these areas, right? I mean, I think there's a lot of talk about how it's going to be Helsing and Andril. There's a lot of talk around how it's going to be OpenAI and Anthropic, maybe XAI. I just don't think we know. And, and when I look at like a trend like robotics that is still so, so early, but at least in my mind, I've convinced myself that this time is truly different in terms of the, the industrial prep, uh, in terms of the industrial applicability of these products. It really, to me, looks like we could be surprised to the upside. But again, this is, this is sort of our job as venture investors is to be very, very optimistic. So I think that is the number one constraint to this whole experiment playing out favorably will be like, are there more than one or two of these per per mega category?

AI assessment note: “I just don't think we know... it really, to me, looks like we could be surprised to the upside”

Q Can you unpack that? What do you mean? They pick duds, and that becomes apparent quickly?

A I think ultimately it's really hard when there's so many founders that are coming in your door, which many firms, you know, like Lightspeed or Kleiner Perkins have the luxury of, of, of experiencing. It's very, very hard to figure out, you know, what is the nine out of 10 one and the 10 out of 10 one. And I, and I think you can talk about that in the context of who the great founders are. You can talk about that in the context of momentum, but my point is it's a very humbling job for that reason. And I think to say that no one has to pick that's at an existing firm because the great companies are the great companies. That just hasn't been my experience.

AI assessment note: “It's very, very hard to figure out, you know, what is the nine out of 10”

Q schools me every week. But he's basically very smart in saying to me, hey, we've seen this fundamental transition of, like, capital supply from your, uh, very, very large Franklin Templeton's, you name it, to Thrive and to Lightspeed. Who are doing these rounds and doing thirty billion dollar rounds into OpenAI, for example. Fundamentally, if we continue to see that transition, how much bigger will these mega platforms get?

A Look, I think that's a tough one because it really is somewhat indexed to this question of like how these mega trends like space and robotics and, and, and AGI really play out, right? If we, if we really are talking about companies that are going to get to some level of AGI such that they're going to be, you know, not just multi-trillions, but potentially larger than that. If we're talking about how Starlink and, and, you know, the, the kind of assets being built around that could kind of scale to those heights. These companies may not have to go public for a really long time because there will be so much demand to continue supporting them, uh, from, from the private markets, which as you said, are very, very robust right now. So the honest to God answer is I don't know, but I think we're going to find out as an industry over the next few years, and it's really going to come down to how some of these like truly blue chip assets that are, that are scaling to those levels, um, just how, how they trend and, and, and how the market kind of shapes around them.

AI assessment note: “not just multi-trillions, but potentially larger than that”

Q What are those signals? That's fascinating. You have such a unique perspective from Glean and Windself in particular. What are those signals?

A So, so first I have to give kudos to my former partners, Mamoun and, and Lee Marie for being, uh, the leads and involved in those two companies. But what I would say is, um, those two companies in particular to me Found this zeitgeist at the senior most decision maker level, right? If you go and talk to a CIO or a CTO of a large enterprise today, they're furiously seeking out ways to apply AI to their business. And the reason for that is because their CEO and their board told them, you're going to get fired because the entire fate of our company depends on leaning into AI if you don't help us do this. So there's this veracity and this appetite to bring new solutions that sort of comprise like what it means to bring AI into business to Into these companies like I've never seen before. And I think Glean found that, um, very early on and the rest is history. It's just been on an incredible trajectory. And, and, you know, I think scaling into a true household name that embodies what like the AI app business of tomorrow looks like. I think similarly with windsurf, they did a really, really good job of going to these large enterprise technology leaders and helping them understand like where the future was going and the role that they could play in shepherding them that way. And I think you're going to see more and more of that, where. Once there's like a magic moment that a CIO sees,…

AI assessment note: “Found this zeitgeist at the senior most decision maker level”