Jack Altman & Martin Casado on the Future of VC

23:50Well, in AI, it's even crazier than that, which is the market is so big and it's growing so fast, even companies that seem like they're competing end up in totally different places, just because so much white space is being created. But they're all competing like totally different companies, they're competing with the same talent. So the first time I can remember where the actual talent competition is like way more fierce than the market competition. Actually, what's funny about that is I've heard of people getting upset with their investors because and they're like, I know this company has nothing to do with it, but we were interested in that candidate and totally a partner sold that candidate on one of their partners.

24:25And it's a very real thing. And what's interesting is like, you often don't even know. Yeah, I like, you know, like they'll say, oh, I'm, you know, I'm talking to a healthcare company, you know, or whatever. And you're like, okay, well, what's, I get, what's, what's tough, but I guess it's also like the blessing overall. I think there's a lot more good ideas than there are talented people to work on those ideas. And I think one of the hardest things right now is like clustering talent densely enough behind a good idea. Yeah, it's also, this happens when there's these large infrastructure buildouts.

24:53This happened with the cloud too, which is there are these moments in time where to build the system, you have to have experience with the system at scale, right? This happened with the internet. This happened with like the big cloud data centers. And this is the case with AI, which is like, it's one thing to like go to school and know AI and be a good researcher. It's nothing to have actually trained a very large model. You know, like maybe what? There's 30 teams that have ever done it. And that's part of where you see these like mega aquahire opposition things. Like certain experiences are just worth a huge amount.

25:21Yeah, yeah, 100%. And like the market always normalizes these things. By the way, I mean, this is all ancient history now, but the exact same thing happened in the internet. I remember once there was like basically one guy that ever wrote a BGP stack, which is like it's a way that kind of routers talk on the internet. And he was like the one guy that could make it work. And so he just basically got this crazy out at the time, crazy offers. And he'd jump between all the router companies and do that and there were a few teams that could do this. And so we've always seen this episodically in the industry.

25:49We're just kind of seeing the new version and the, listen, the businesses are working and they're doing great. It's we're kind of seeing it on steroids. Yeah, I mean, you have your, if you're a fang -size company, what's it worth to have like the one or two or three people who really know how to do something huge? Yeah, I also feel like tech always figures out a way around kind of regulations and markets like, you know, and like the late 90s, it was like, you know, you could IPO a company for very little, you know, with not a lot of market traction, remember like the whole spec craze? And then now it's got these clear aqua hair things.

26:29I think the reality is is in hot markets, people know that there's a lot of value to be had. Nobody knows exactly where it is. And so, you know, there's all sorts of things, you know, the market's tried to do to get access to the talent or the companies or whatever it is. and we're kind of seeing our version of that now, whether it's these like, I will hire an individual one, I'll do it. We're gonna acquire. But again, I feel like this is all normal in this sense of, you know, we've seen it in different shades in the past. Yeah, I told it, it's like an evolutionary response. What are the markets right now in AI that you feel most confident are totally working?

27:04What are the ones where you feel like they're on the horizon and you know, should be working very soon? And then what are the ones if any that you maybe have low confidence will work period? Yeah. So the diffusion markets are all working. So any area where you bring the marginal cost of creating something a piece of content to zero is clearly working and creating an image, creating music, you know, creating speech. And we don't think about these markets as much because we're also focused on like the frontier labs, but like it's cheaper to build these models because they're smaller. and then people need content.

27:41And actually, the economics are so simple. Like, you know, like whatever. Imagine you're an artist and you're like, okay, I'm gonna draw a picture of Martin, right? Like, how long will that take you? Oh, wow. Whatever, three hours and it costs you 400 bucks, right? But if I have a model, do it as a hundred of a penny type thing, right? So you've got a four orders of mammoth to different synachronomics. So that's why we've seen those types of companies, you know, I think like 11 labs or whatever do very well. So like that's clearly working and this is content creation where the market cost of creation goes to zero.

28:13I actually think the whole kind of low -wingness companionship stuff is definitely working. It's just this very fragmented market. So I think I think the Uniteconomics are fine. I'm not sure like from an investor standpoint how you think about it, but like it's a use case that will be solvent that will do fine. Code seems to be working incredibly well. Yes. And you know, we, you know, you see this in, you know, in in in cursor and in the whole thing. The areas that I don't know, I mean, the work, but I don't know how the economics actually pencil out are the enterprise use cases at this point that are kind of a bit more agenticky, automated.

28:54These are ones you're putting in the middle bucket. This is like what you're saying is like kind of working, but not 100 % sure yet. No, no, no, So the ones that are, well, so the middle bucket was companion, was actually like, you know, like, like to friend the emotional, like the character that AI is, like there's a long tail of companies that are basically emotional support and our friends and our entertainment. It's probably also a big component of the usage of the name models and so. Yeah, 100%. Like, that's clearly working in this sense that people are willing to pay for it, the engagements, grade, etc.

29:25From an investor standpoint, tends to be kind of long tailed and fragmented and kind of spread and stuff. And then that enterprise agentic workflow type stuff. That was the fourth one I mentioned. That's like, you know, chatbots. I mean, clearly it's working. And there's, there's companies that are doing it. But it tends to be, you know, if you look at the companies, like, you know, there's a lot of like bespoke work going on. Like it's just a different type of economic model than the Contracration one where it's like, totally. It's just a model. I mean, those ones were still trying to understand.

29:53Yeah, I mean, one way to think about that is like, how confident are you that highly skilled work will get replaced in, let's say, legal finance accounting tax, like those kinds of areas? So, I think the way I view it is actually very simple. So, if the use case is the model is creating content, and that content is whatever, it could be language, it could be image, that clearly works. right? So, okay. If the model is automating something a human being would do and we conflate these two things all the time, that's totally different, right? So, if I'm like model do this thing instead of me, that's not content creation.

30:34It somehow has to like mimic exactly what I do. That area still needs a lot of work, it seems to me. And so they clearly can do some work of a human. But you know, you know, not as exact and they need a lot of guidance. And I think that's an area where there's still holds a lot of promise. But like the economic case isn't as obvious, right? Like make me a picture versus like go browse the web for me. Yeah. And so it's kind of that second one, the automating what humans do, where we're still like, we've got lots of investments. We're very excited about it. We think there's a great future there.

31:05But like the economic case isn't nearly as good as make me a picture. Totally. Let's to double click on code for a second. Yeah. Obviously, you know a lot about it through cursor, you were technical CTO. Like, where do you think we are right now? You know, like I, I just posted one with Guillermo who, you know, and I was, you know, obviously knows a lot too. And it was great. It was like, this is both the future. And it's also at the moment, you know, it's not obvious that it is in today's, you know, incarnation. It's not necessarily producing quite as much value for engineers as even Dave himself's experience, but clearly it's going to get there.

31:39So yeah, I'm curious. So just so you know, AI in general has this problem, which is so dazzling people can flate. Oh, this is dazzling, whether this is useful, right? Yeah. That's for everything. Right. It's not just code, right? It's like, you're so impressed. Like these things were magic. And somehow that dopamine, you know, hit. Well, it's really funny. So I posted this on X and, you know, like this study that was saying that people experienced their own programming as plus 20 % and like the observed results are minus 20 or whatever. And what was funny was there were a bunch of reply threads where somebody was like no, no, no, no, this is crazy.

32:12I've been using it and I'm so productive. And then the reply that was like, that's what the study's saying. Yeah. Which I'm sure for some people there, but you know, there is this thing. There is literally there is an endorphin head these things are absolutely magic, but I don't see it makes it very hard to think clearly about the actual utility. Right. Now, so I think you can say a few things like, you know, like there's a lot of things that it does very well that programmers don't like to do that like is pretty routine, right? documentation. It's great writing documentation, right? There's a lot of boilerplate stuff it knows.

32:42The thing that I use it for the most is, you know, writing code isn't just writing code. Writing code is like understanding the frameworks. It's knowing how to deploy it. It's knowing how to run the toolchain. And like, there's no first principle way of knowing that type of stuff. There's not like some like core computer science fundamentals on deploying to to nullify. Like that doesn't exist. And so it has all of that knowledge, which is clearly very useful. The writing code itself, I think it's still clearly very early days. I mean, if you constrain how you use it, it can be very effective. And then if you don't, it may not be as effective.

33:21And so I think that like studies like this that are purely observational are hard to read into because, you know, it's just like, this is like, you You can use it for anything and because they're so magical, I do think people tend to use them for stuff that they may not be so good at, just because the experience feels good. And so, my guess, like any new technology will develop best practices. I feel very strongly we're going to get a 10X in productivity, but like it'll take us a while to get, listen, I remember an other epochs of development productivity. Like when the IDE came out, when it higher level length is, when OOP came out, like we'd get so enamored with the toolset, like object -growing and programming, I'm going to do everything And it turns out these were great advancements in computer science and they helped the best practices and they helped architecture and engineering.

34:06But at the time they came out, they were just so cool. I just kind of took a lot of a focus. So I think we're seeing that. So it's like this dropper productivity is not necessarily code requires you to drop productivity. I think it's, of course, it's just so cool. I'm going to try it with everything. Yeah, it does seem like it's on a path to like, you know, in the same way that like people have been saying this about self -driving cars and it seems like it's going to become true. So it just seems like we'll get to a place where you can. It's so clear. I mean, this isn't incredibly obvious. I mean, even literally just go up into a subset of things that are obvious.

34:32Like it's really good at writing tests. It's really good at writing documentation. It's really good at like dealing with a bunch of like, you know, long tail framework stuff that you don't know. It's good at teaching you things. I mean, this clearly, these are obviously good at. I just think we get so in the abort with it, maybe we start using it for stuff that is not so good at or not so equipped to deal with it, Tetra. But yeah, this is very clearly a, it's going to change software. And sorry, I don't mean to ram along. I just have to say, I have been in software for a long time, since the late 90s, we disrupted everything, right?

35:03We disrupted the back office, we disrupted hotels, we disrupted everything. This is the first time I say that we're probably getting legitimately disrupted as it is upon. Like what it means to be a software engineer is changing pretty fundamentally, I think it's because of AI. So it's kind of fun to like actually be the disrupted for a change. That's awesome. Yeah. Another topic I wanted to get your thoughts on was, like, why is open source so important to you? And, you know, like I saw, you know, you were really excited about, you know, opening up his open source model. And I know this is like thematically and spiritually important.

35:38Like, why do you, why do you think that it is such a critical part of the way that, you know, this plays out? So I think open sources, historically, one of the best mechanisms that shows a healthy ecosystem, right? And what normally happens is somebody does something close source, it turns out to create a market, and then somebody releases open source, and it stops a monopoly from forming and enables everybody else. And then it kind of keeps the people that are close source to continue to be innovators and allows everybody else to come in. So it's just been very, very healthy. And the thing that really worried me last year, and the past, academia, VCs, startups, are all very pro -opin source, because they understood that it was a very important part of a healthy competitive ecosystem.

36:31And the thing that really, really worried me last year was the people that should be championing open source, like VCs, like startup founders, like academia, where it declined how dangerous it was in relationship to AI. The implications of this to me are huge, right? I mean, of course, the national security implications are pretty straightforward, which is like if somebody else does the open source of proliferates and that's not good for US interest, but for the industry is terrible, right? I mean, this is kind of how you actually create monopolies. If you're not allowed to create something that enables everybody else.

37:05And again, it was very dramatic. I'm like, the node coast was like open source is bad and founder's fund is like open source is bad and he had academic and open sources bad. And so I was much more interested in like trying to reset the discourse than like any specific open source release. Yeah, and I guess a lot of that probably came down to like how potentially dangerous was the technology, you know, and so like if you thought it was extremely dangerous, for example, then there is a argument for like massive containment. I got, or what was the seal man in your mind, you know, at the moment when closed source was like such a strongly, are you like if you had to, you know, argue why you think people were saying that like what would have been?

37:42I really think it's the legacy of Boastron, right? Like so, you know, Boastron wrote the book Super Intelligence in 2014. Terminators were like, no, we got to continue. But this is before all of these things, right? That like like Boastron's book was a thought experiment. It was like this platonic ideal of AI and then somehow that created this, you know, very interesting kind of intellectual journey on the Parals of AI. But then, you know, like GPT -2 lands and these two things got totally conflated. You also got, there's a lot of incentive for people to be do -mary, I think. Like it, like, gets a lot of clicks.

38:16It was like, yeah, but not a storm. It's the weird thing historically. Like, let's take the internet as an example. So like, I was there during the early days of the web. We had a lot of examples of like how it actually changed the dialogue when it came to to risks, right? We run a critical infrastructure on it. We had totally new types of attacks, like the Morris worm, which had actually taken down computer systems. So we're at this space where like, okay, well, it makes you more vulnerable if you use it. And we have new attacks that you can attack with it, right? And yet, academics are like, this is great.

38:49The technologists for this is great. So you had this very even -handed debate. What was so weird about the AI was it wasn't even handed. Like I'm all four both sides of the debate. like I'm not a, you know, I'm not just, you know, pro innovation at all costs, but like that's not what was happening. And so like maybe you're right, maybe it's like the doopers got more clicked, but I think it's something more than that. I just think that there was an existing intellectual legacy that came from Boastron that had some very influential people, right? Like Elon was killed by that. You know, Eric Schmidt, Moscow, it's like, and they had very legit concerns, but they were kind of already primed and like, you know, there was already kind of that ready.

39:30So when it happened, I just think they, they were already ahead of the game. It took a while for the rest to catch up. And now I, now I listen when I listen to the discussion, it just feels more even handed, which is thank God, I don't have to like be on Twitter. Yeah. Talking shit about this, like I did for so long, just I feel like the right voices are in the room. For sure. And obviously this isn't like, you know, I don't think either of us is saying that like there aren't real rest. No, totally, it was just a totally lopsided debate. It's so crazy when VCs are talking against open source. I mean, to me, I mean, like no academics are talking in defense, but now we have a bunch of academics in defense of it.

40:06I mean, like I think the right people got mobilized, but it really took some rallying to get the right folks back into the conversation. Yeah, yeah, absolutely. I want to ask you just a couple more questions about sort of the structure of the firm and sort of your own work outside of the specifics of what you're investing in. Yeah. One that I thought was a really interesting point from Mark when I talked to him on the podcast was basically around, you know, like, how do you sort of drive the right overall aggression of the firm? And he said something to the effect of like, when you're in a market moment like this, the right answer is to just encourage people to do more.

40:42And so many partnerships are trying to get other people to know. And like that, it's like the common function. Yeah. And, you know, he was basically describing something where like, It was like, how do we get people to a yes? And like, how do we take advantage of this? I'm just curious how you feel and your experience in the last couple of years in AI land. So one of the reasons Mark is such a great leader is he has intuition on the temperament of people is almost perfect. And he will drive like the right behavior relative to that. And so like if he thinks people are being too conservative, of course, he'll drive them to be more aggressive.

41:23There's definitely more aggressive. I mean, the reality about it, yeah, there's been a lot of money that's already been lost in absolutely record time, right? So just because the outside is aren't great, doesn't mean like the down, like there's been a lot of money. And so as a firm, we tend to be fairly disciplined and do a lot of market analysis. And he thinks we're coming. And so like, he's very good about pushing the team. I mean, I think he's absolutely right to do that because, you know, there is already a foundation of discipline that like is not going to be eroded or compromised by doing that.

41:56On the other hand, there are individuals who are like, don't shoot from the hip like everything. And then he actually tempers his messaging a lot with those. And so I would say again, I mean, you know, I don't know if it was in his head or do you saying that, but I just think if I was going to add a little bit of nuances, my observation of Marik is he's very good at pushing when people need to push, but he understands the situations when that's probably not the most appropriate thing. And so I think this is a core issue of leadership, which is you need to provide kind of the right kind of macro, you know, shift in order to get the right one without being too overbearing.

42:35Yeah, I think, you know, some of that conversation was in relation to like, you know, fun sizes and what's possible. And I think some of it was articulating just like, these companies could be enormous. This opportunity is like, you know, quite oversized role. Yeah, but I mean, but again, I just think it's important to know, which is, it's a person. If you take, you know, him and his word, it would be an infinite fund deployed infinitely. Yeah, yeah. Right. So like this is a, it's calibrated. This is an intellectual landmark, which is set. And it's a 100 % the right one to do. Yeah, but it's in relation.

43:11Yeah, he's so good at it. Yeah, it is in relationship to the mindset of the people that he's talking to and he knows that and what flag post you have to put out to get 100 % and 100 % and then I have seen him very subtly depending on who is the audience. Yeah, yeah, yeah. You know, he'll like move that flag post to different places. Where do you normally experience yourself there? Are you do you feel you're often needing to get pulled into more aggression or into more conservative. I think I'm a seven out of 10 for aggressiveness. I would say my team is five or six out of 10. There's people on my team that are 10 out of 10.

43:46There's people on my team that are three out of 10. So I think like if you did a normal distribution, I'd say we're six and a half to seven. And so for us, you know, he, I mean, he, he, he pushes pretty hard, but I know he knows that he's getting like, you know, like a step forward as opposed to like, yeah, and I think that's like one of that mean being a leader of people is always in relation to pulling minds and asserts. So that's always how it goes, which is a rare thing. It's rare to be able to do multiple versions of that at the same time with lots of different things. Exactly. It's just hard to appreciate from the outside because you have to actually see the conversations.

44:20It's something that he's just phenomenal. And the very kind of nuance different takes where he kind of knows where people are, kind of nudge him in the right direction. to the extent that we are in somewhat of like a gold rushy in the good sense moment, you know, overall. Do you think, does it change your perspective at all about what you need to see to want to make an investment? So like maybe a specific version of this question is in a somewhat stabilized time, I think most, you know, most people would agree that you should only back extreme special founders. Yeah. Is there ever a version in these kind of moments when a good founder and a great market with exceptional traction or some configuration like that.

45:02Where you say, actually, you know what? That works here and that can produce something really big. So do you know how we think about investments? Because I think it answers this question. So it's very simple. So the way that we think about investments, and the reason is the only way you can scale because you can actually distribute this kind of algorithm to a team is the only sin is picking the raw company in a certain space. because it becomes that conflict thing. Because you're conflicted out of the winner. Like investing in a space that doesn't work is fine. I mean, there's no way you can actually predict whether a space is gonna work or not.

45:37I mean, that's like weather prediction, right? But in a given space, if you know all of the companies you do the work, you can most likely, at least tilt it, like you can do the work to determine if you think one is better than the rest. Like it's something you can actually put. So the way that we view the world is, First, you have to identify legit spaces. We think that founders are smarter than VCs. So I don't care if VCs think it's interesting. If there's five founders in a space and they're good founders, then they're betting their families, their fortunes, their time. So it's probably a real space.

46:09And then we do the work to understand the space and all the teams, then we make a pick within that. I mean, that's really how we think about it. That's true within AI is anything else, right? The thing that's harder is, and I've evolved so much in investor, I used to think like, oh, we're getting good deals, like price matters, outcome matters, tam matters, and more and more, especially with AI, that's what you have to throw away. The market is the market. And that's what matters the most, your saying? It doesn't matter at all. I'm saying, I'm so, so, so his, so we don't know what the tam is because it's growing so fast.

46:45Like nobody knows valuations, So I think this is, it's a contrary to like common belief. I think in these times where you don't know the tam and things are moving quickly, you definitely want to pick the best team. You definitely want to pick the best team. I don't think you should overthink the space, but like asking questions about like tam or valuation or value makes a lot less sense because that's actually what's uncertain. You just need to be in the best one. You have to be in the best ones and the market will just produce this on something. The market is the market. And listen, either you believe that the stuff is expanding very quickly in market.

47:21It's our efficient or not. And listen, having been through the .com boom and bust, the reality is the market was actually pretty smart. And if you put the bets in the right companies, they would have been generation one. The same thing with cloud, the same thing with mobile. And so the goal is finding the right companies. And like, really, if there's one change, I would say, is you need to throw away too many thoughts about market sizes in town. Is the rational sort of behavior then to, obviously, do you want to invest as early as possible, but you want to invest as early as possible when you know that you've got the right one?

47:54So does that ever push you to being like, I'd rather wait around or be here? Oh, yeah, all the time, right? Yeah, all the time. So, I mean, yeah, this is all very rough surestics, right? Like, you know, we get it wrong all of the time. You know, I've made, you know, I've made so many mistakes. And so you're just trying to beat the market, right? You're just trying to have. But yeah, very often, our discussions are like, do we actually know who the winner is? Yeah. And often we wait for that reason. Basically the earliest that you feel confident you can pick it. Yeah, and so listen, what we do see is storm is like the person that did the thing in the big company, and now I was doing the thing, it is the world expert.

48:31And the thing is very tactical thing, and somebody else is just going to wake up and decide to do it, who's a good founder, right? Is it like the pool of people that do it are like five? Yeah. Like this one's the best of the five. That's kind of like for early investments the way that we think about it. And then most everything else is actually the result of a lot of market work. And then this is our best guess like this is kind of the best approach, best team, best market. And then in these types of ways, and this is where market, this is, this comes from market. And market is totally right. Like if you think you can ask why the market, like I think, you know, it's very tough.

49:00And so just being the best deals. As a final topic, I want to just hear your perspective on the board relationship and board roles in general. And maybe as like a prompt on this, I feel like you've done something which I find very impressive, which is it seems like you're able to manage successfully many more board seats than a lot of people. And you know, I often hear common wisdom that you know, it can be 10 or 12 or 15, but it seems like you know, you've found a way to do more than that and be very effective with those founders. And so I just wanna hear sort of your perspective on like what's that relationship?

49:36What do you think is sort of like the limiting factor here if any? How does it all play out? Yeah, I mean, I do think that like a lot of the common wisdom on boards came from like that earlier year in DC when, you know, it's like people would literally choose DC for like a live choice or whatever, right? And I think if you come from like pretty serious operating like you do and like I do, like just got a lot of hours of the day to throw at it, DC is also involved that we've got better platforms that actually really help with these things. And so, you know, between like actually, you know, the hours in the day, I mean, how much does that take?

50:09Like, bored, where's take? I mean, you're a board member, you know, I actually find that like, can I just take a step back just because let's talk about what boards mean? Like, I always ask when I invest in a founder, like, like, what is a board for? What do you think they say normally? I'm actually curious what the most common answer is, but I couldn't ask them. What do you think would be? I would think they would probably say it's something like, like governance and approvals or something like that. No, that's what they should say. That's what you and I would say. They say to provide guidance, to help with hiring.

50:41I'm like, no, that's not a board, right? And so a lot of, there's a lot of this belief that a board member is somehow helping with company building. And almost like, it's actually hard for a board member to be the best friend of a founder for those types of things because you're up to do sharing and you do governance. So like the actual boardwork itself is just not a lot from the fiduciary governance standpoint. So often implicit in this question is, like, non -board stuff. Like, how can you be helpful to accompany in everything else? Because that can take a lot of time. And I do think this is where like, you know, having a big platform to lean on, being totally available helps a lot.

51:20But like, it's not the boardwork. It is the other stuff. And so I would say to, you know, anybody listening who who is a VC, you can take a speddy board as you want. The actual boardwork itself is not. the questions, can you still be available to founders and add value whether you're on the border? A lot of the companies I spend the most time with are not even on the border. And that's what's funny to me is people talk about this with me. There's some board seats I have that are, you know, the founders asking quite a lot less than, you know, some seats. No, there's no board seat. And they're sort of decoupled.

51:49Yeah, exactly. So I feel like needing to be very clear. Like a board is to keep everybody out in jail and to like do the right thing for the shareholders. And like, like the actual work requires that are relatively little. That's actually not the hard thing, but we use it as a proxy for the hard thing. The hard thing is like, how do you add a lot of value? And for that, I do think like this and you have to, like in my case, listen, I have the pleasure of working with the best team I've ever worked with my life. They're fucking amazing. We've got like a phenomenal platform. Like it's fucking amazing and I get to leverage all of that.

52:15And it's not a bored thing. It's like the help the company type thing. And I just think this is like the new era of VC. Like you help these companies with more than just one person who shows up, you know, off the goth field, like, I don't know, every Thursday. Yeah, well that's great place to leave it. Martin, thanks for making time for this. I really enjoyed it. It's a pleasure. That was great.

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