a16z Podcast - Jack Altman & Martin Casado on the Future of VC

Episode Date: September 3, 2025

Jack Altman sits down with Martin Casado, General Partner at a16z, to unpack the shifting dynamics of venture capital and why media matters more than ever. They cover a16z’s evolution from generalis...ts to specialized platforms, the rise of AI infrastructure, and why today’s fiercest battles are often for talent, not market share.Timecodes:0:00 Introduction0:27 Importance of Media for VC3:50 Evolution of a16z7:00 Specialization10:32 Value of Distribution13:16 Staying Power in Infrastructure19:49 The Conflicts Dynamic26:32 State of Play in AI30:48 The Future of Coding34:58 Significance of Open Source39:48 Marc Andreessen’s Leadership44:02 The Only Sin in VC48:37 Scaling a Lot of Board SeatsResources: Listen to more from Uncapped: https://linktr.ee/uncappedpodFind Jack on X: https://x.com/jaltmaFind Uncapped on X: https://x.com/uncapped_podFind Martin on X: https://x.com/martin_casadoStay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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Starting point is 00:00:00 Today on the podcast, we're sharing a feed drop from Uncapped where Jack Altman sits down with Martin Casado, A16Z general partner. They talk about the shifting dynamics of venture capital, why media now matters in a way it never did before, how A16Z evolved from generalists to specialized platforms, the rise of AI infrastructure, and why talent competition might be more fierce than market competition. Let's get into it. 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
Starting point is 00:00:32 is being created, but they're all competing like totally different companies spaces are competing with the same talent. So the first time I can remember where the actual talent competition is like way more fierce.
Starting point is 00:00:45 Martina, I'm really excited to be doing this here with you today. Thanks for making time for it. And one of the things that I was just chatting with you and laughing about on my way in, there were like many other podcasts going. There's like one like before and after us
Starting point is 00:00:58 and I talked about this with Mark about how like podcasts are like this future thing of media. And basically my question for you is sort of like, as somebody who's been on the inside of a firm that's dominated this, you do a lot of it yourself. Like what's your experience about like the importance of media for venture capital? So I think it's probably important to recognize that it's never been a thing, really. Like if you look at a lot of historically good investors, they want very public.
Starting point is 00:01:25 I think about like they're the greats, like Maritz, Pingley, Doug Leone, and in, like, Fulte, like, they're just not very public. And so historically, there's been no correlation to be between public or not. Yeah. I think a couple of things have changed in that time. One of them is the traditional media just turned on tech and it hates tech, right? And so in the past, you know, when I was a founder, to get a, like, a lukewarm to positive article
Starting point is 00:01:50 is pretty straightforward. And the VCs would help with that. Like, you know, they would know a few reporters. It was very easy. But now it's actually very dangerous because, like, you go talk to them and, like, who knows what they're going to say. And so in a way, like, if you want to help a portfolio, you do want to build a bit of a platform.
Starting point is 00:02:03 You do have to go straight. So I think that's one thing that's changed. The second thing is, so if you're traditionally in enterprise, take from the enterprise standpoint, like, marketing has been something that you build brick by brick, right? And it's like, you put content out there and people rid of it. And like, it's durable over time. And so you get this kind of compendium and you build a brand over time.
Starting point is 00:02:26 And it feels we're in an era now where it just becomes. so episodic that if you don't understand, like, the current zeities, you just can't even get a voice at all. And by episodic, I mean, like, today, GPT5 launch, right? It was, it was massive. Like, if you didn't know that that was going to happen, you would have been drowned out. And if you did know, you could draft on it.
Starting point is 00:02:47 And so, and then it just feels like for some launches they go, they're a big deal, and then they just disappear forever. So I just, so much of the nature of how we consume and think about content has changed. And so I do think that venture capitalists, one, they need to, like, if they have a message, they want to get out, they kind of have to go direct because, I mean, if it's your own platform, it doesn't hate you. That's one. But then also to help your portfolio company, I think you need to build an in-house capability so, like, they can know how to, like, most effectively message. And you can't really borrow a page from traditional marketing. And this is from someone that's come very much from the age of traditional marketing. It's just different. Yeah, I mean, one of the things that I've been very surprised by is, you know, there's always room for, like, another podcast or something. Like, that, like, people consume a lot of this stuff. And I think people in tech find it sort of like a,
Starting point is 00:03:34 it's almost like a halfway between working and like watching Netflix where it's like, I'm passively learning, but it's like low stress. And people would like rather consume a good podcast than like a new Netflix show. Yeah, for sure. And I'll also say, like, there's always a concern that there's too much content. But that's been concerned has been around forever. There's always been too many books to read. There's how many than too much like, you know, TV to watch.
Starting point is 00:03:53 There's always been too many webpages to read, et cetera. So it's always been an order. list that starts with the most important and goes to infinity. So the question has always been, how do you be in, like, the top 10 or the top 20? And that changes all of the time. I do think you're right. I think people like to consume things that they can consume casually that is relevant to their interests. And so it's actually a great time now that you can actually be in that top 10 for the set of people that you care about.
Starting point is 00:04:16 Totally. So I want to talk about your time at Andreessen and like what's evolved, which has obviously been like a lot. Can you sort of give the picture of what it was like when you joined? Well, when do you want to start? When I was a founder or when I actually joined as a GP? Maybe when you joined as a GP, but then let's connect it back to when you... Okay, so when I joined it was 2016, so I've been here almost 10 years. Yeah, that's a lot.
Starting point is 00:04:38 In the wild, so I think it was the ninth general partner. I think the firm has 75 people. Not only were we all generalists. Like, you know, you can do whatever you want. That was kind of part of the pitch. You know, you can kind of do whatever you want. But like most of us had done some pretty serious time operating. Like, my journey of my startup was about 10 years, let's call it.
Starting point is 00:05:01 And so many of us, like, we're so tired of the space we came from. We did something totally different. Yeah, you know, like, you know, and so it was very, very different than that. So generalists, a few people in the firm. And then actually, the investing team alone, you really had GPs. Yeah. And we were all the same. And then you had relatively junior partners that couldn't write checks that actually would
Starting point is 00:05:20 bounce between the GPs. Like, so there's no alignment at all. So it was a very, very different structure. So I guess one of the things that's interesting, then over the evolution is that, you know, it started in this generalist version. And now you're running a distinct platform. And the way the firm is shaped is there's a ton of autonomy. You know, Mark was talking about this on the podcast where basically part of the idea was like, we can recruit these amazing GPs because they get huge autonomy, but we're going to have specialists, you know,
Starting point is 00:05:44 sort of leaders for things. Yeah. And so I guess what does that change meant for you? What's it been like to go from generalists to a specialist, I guess? Yeah. So I think it's important to maybe talk about why a change is necessary. So the historical context is interesting. I think there's two things that are important. One of them is the model of venture came out when, like, tech was like a non-market. It was like this total speculative stuff.
Starting point is 00:06:08 And when you meant tech, you meant everything from like bio to software. Everybody was a generalist. Often, it was just kind, it wasn't like really a profession. It was like, you know, if you wanted to play money, you'd do it. And so, you know, they made decisions that made sense at the time, but that no longer makes sense.
Starting point is 00:06:24 So, for example, it's a historical quirk why, you know, we venture capital uses like the same model that you'd use for like a dentist office or something, like a partnership where everybody's equal, right? Like that makes sense for a small service organization, but you can never scale that. And so there's all these decisions that were made when the market is much smaller that as AOM grows and as the market grows, like, there's many companies, many more companies you can deploy in now. You'd have to restructure the firm. And so, kind of our view is like, we definitely want to scale. We definitely thought we had the best platform for founders. And also, the markets were so large, you didn't have to be a generalist. Like in 1980, if you did enterprise infrastructure software, how many companies can you invest in?
Starting point is 00:07:08 Not a lot. Two or something like this. Now, you know, someone can have an entire career investing in databases alone, right? And so as the market grows, clearly you have to specialize. And so when I joined, we were all generalists, often that hated our own disciplines. because, you know, we've kind of been through it. Can I see a question about something? Yeah, yeah, of course, yeah.
Starting point is 00:07:25 Do you have to become specialist as the market grows or as the firm grows? In other words, is that the specialization choice downstream from growing the firm? Or do you think it's downstream from the market growing? I think it's ultimately the function of the market, and I'll describe why. So if you believe that this stuff is competitive, right, which I do, then you need to end up with a product that is competitive. And because it's adaptively competitive, like, let's say you've got two firms that are competing, you're always going to be looking at, like, what the weakness of the other one is. And so, like, for example, if a certain firm can't do seed, then, of course, you know, you'll want to do seed,
Starting point is 00:08:07 or if they can't do large checks, you want to do large checks. What happens is everybody ends up getting as many products as they can so that they don't have any weaknesses, which will naturally happen. Now, you can only do that if the market is large enough. And so now you have a high AUM, right? You've got a lot of products. I've got a growth fund. I've got a seed fund.
Starting point is 00:08:26 I've got a venture fund. And then you have to ask the question of how do you scale that? And my venture was not built to scale. And I think this is why we've seen the industry go this way, which is the market has increased a lot. You know, funds want to be competitive. In order to be competitive, they have to find out kind of like what products that they offer that are actually competitive.
Starting point is 00:08:43 This drives to hire a UM. And as a result, you know, you have the specialization. When you're. No, just that said. But there's also kind of this internal thing, which is assuming that you want to scale AOM independent of the market, you have to solve this problem because you just can't scale like a consensus org of generalists, like it's just not something you can do.
Starting point is 00:09:04 Like the people issues on the inside. You just can't get through good decisions. Is that way you mean? Well, I just think conflicts, well, there's many, many issues, right? But one of them is you wouldn't ever have a, a structured approach to tackling a market. So you can never know that you've got good coverage because maybe everybody wakes up in the morning
Starting point is 00:09:24 and they said they all like the same thing. And so I just don't think you could actually, even from a numbers game scale it, because you don't, you're not carving it up enough where you actually know that you've got like a uniform focus. You don't know if you have, are hiring people that can cover the certain areas. I actually just think, even just from a strict number standpoint,
Starting point is 00:09:40 it doesn't work. How valuable is the specialist thing when you're in these competitive situations? Like I imagine that a lot of the times when you're competing to win a deal, it's up against a firm that or a partner that is like more or less generalist, I would think. And I'm curious how that plays out sort of in the day to day. So I'm not, yeah, it's hard to answer how much it helps in the competitive situation.
Starting point is 00:10:08 I think my experience is a lot more powerful that founders know that I've been a founder. And I know this is such a cliche thing to say. But I do feel that resonates much more than, like, I got a PhD in computer science or I know infrastructure, right? Right. Because the reality is most founders know a lot more than I do about whatever their area is, even if I've got a high-level thing. So I think in the competitive situation, it's not hugely, but what I think it is very helpful for is, like, I am primarily a Series A investor. And at Series A, you have to have some thesis on how the tech hits product and how the product hits the market. And unless you've been very close to both of these things, that's a hard thing to do.
Starting point is 00:10:53 Now, if I was a growth investor, it wouldn't matter. I just look at numbers. But, like, for where I am, I think you kind of have to understand. Yeah. And an interesting offshoot question from that is, you know, when we were talking earlier about how important is media, you're like, it seems really important. But, you know, there's a lot of great examples of investors who are all over, you know, all over media and social media. There's a bunch of examples, phenomenal investors who you never hear about if you go on the internet. Yeah, I literally don't know if they're correlated at all.
Starting point is 00:11:20 Mostly the best investors, I have known in the last 20 years, had no media presence and they had no interest in it. Totally. And then I'm wondering, I think, you know, around being a former founder, like as I'm just like thinking through names, I can think of like a lot of examples of both. I definitely think founders appreciate it. And I'm, you know, speaking as somebody who's a former founder
Starting point is 00:11:39 and that's a nice thing. But like, it also, I wonder if that's also an uncorrelated thing or do you think that has more of a correlation somehow? Okay, so I'm just going to get. I said, I would guess that founders really appreciate reach. And so I don't think a founder's like, Martine, I saw you on that podcast. You seem smart, because everybody sounds pretty smart on podcasts
Starting point is 00:11:58 and articulate and whatever. I do think a founder would be like, hey, listen, like when you really believe in something, boy, like, you talk a lot about it. You know, I will have the opportunity to talk about it. You know, you will help me kind of break through the bootstrap problem of zeitgeist understanding and brand. And so I do think having a platform, matters more and more.
Starting point is 00:12:19 And again, a lot of this is just because the media has turned on tech so heavily. Totally. Like, there just aren't a lot of options. Yeah. Again, I mean, I think sometimes we and VC kind of overweight our importance in these things. Most companies with great brands
Starting point is 00:12:34 did not do it through a VC firm. Totally. Right? And it's not like, you know, we somehow can single-handedly make great brands, but we are an accelerant. We are a platform. You know, and there is actually a lot of signaling
Starting point is 00:12:45 as a result of a line of the good firm. So I think all of that matters. Yeah, I do think that it's, there's this question of, like, are the top VCs getting to do the great deals because they were the top VC or are they in some sense helping make them? And I, you know, my own instinct is that for the most part, it's the former and like, you know, companies are just almost exclusively made by the founders.
Starting point is 00:13:07 I totally agree 100%. I think that the primary reason to create a distribution channel as a VC is so the portfolio can get out there and reach to people. This is very hard what we do. It's not because like whatever. Martin needs to be famous or Martin needs a brand. Like, that doesn't really matter. That never comes up in like a closing situation.
Starting point is 00:13:23 I mean, I've done so many deals, right? That's never been a thing. But I do feel that a number of our companies, you know, once they're ready to launch, you know, we can provide a benefit. And so I think that is ultimately the benefit to the portfolio. But I've never seen a company when I lose by marketing. So I just don't think that that's the high order.
Starting point is 00:13:41 Totally. Okay, I want to jump over and talk about AI a little bit. And in particular, I'm interested in talking about like infrastructure because it's something I know relatively little about and so I want to like learn from you about like first of all like what is it if you could like put some like broad you know kind of you know a broad fence around what the term is yeah so I do computer science infrastructure so I'm like a computer science maximalist I think it's like the meta discipline that you can like you know solve other other disciplines with right like we solve granted unified field theory and
Starting point is 00:14:11 physics goes away and then we just go on to biology type thing right so I do computer science So infrastructure is the stuff used to build the apps. So you sell to technical buyers, people that use computer science to solve business problem. So like if the company sells to marketers, that's not infrastructure. But it is developers, database administrators, networking, that's core infrastructure. I mean, and so like depending on how you count, this is a multi-trillion dollar industry. But like the important thing is like the actual buying and use behavior is a very technical thing. So that's that's our definition of infrastructure.
Starting point is 00:14:45 Okay, so when you're looking like compute network storage databases, yeah, now models like that dev tools, that type of stuff. And it seems to me from, you know, just my viewpoint is that when these new paradigms come cloud, mobile, you know, AI, it seems like that's like a very good moment for, you know, infrastructure because the board shuffling a lot and new infrastructure's being laid. Yeah, yeah. And so when you're looking at it, is there any broad way that you think about, you know, will this will this continue to exist over time? Will the models or, you know, you know, you know, you know, whatever, AWS in the past, will they do it? Will there be, you know, a need for somebody, third party? Like, how do you even start to think about what will play out over time, just like at a structural level in infrastructure? So can I say something that's probably, that may not be true, but I feel very strongly. That's what we're here for.
Starting point is 00:15:31 This is like a total. That's what the whole thing's about. This is like an inflammatory opinion that's self-serving, that may not be true. So, but it's an observation. Here's my observation. In software, the true differentiation is technical, right?
Starting point is 00:15:48 You know, now there's, of course, brand stuff and business stuff, but, like, you know, if you have two products, like, it comes down to a technical problem. And that almost always comes from the actual infrastructure that, you know, that the software is built on, right? So if I built, like, two, let's say, dog walking apps, the fact that, like, it's got three or four features,
Starting point is 00:16:10 like, you know, That's a very light differentiation, but like one being super fast, one being super slow. That's like an infrastructure. So the companies that provide infrastructure, I think ultimately they are the, they are like the source of value. They are the source of differentiation. And so while there are fewer infrastructure companies, my bet, and this is my inflammatory opinion, is that they just have better multiples and them more durable because they service
Starting point is 00:16:38 everything above it, but they're the thing that provides it. And actually, Sarah Wang, who is an investor on the growth fund here, and I did a, you know, kind of relatively loosey-goosey public market analysis where, like, where are the multiples of companies that are infrastructure versus apps? And they just have higher multiples for this reason. Does that make sense? That does make sense. So, like, so my, so my view is, is the infrastructure is where the value is.
Starting point is 00:17:01 Every time you have a platform shift, you'll get a new set of infrastructure companies. And then a bunch of apps get built on top of those. But like the value is going to accrue. largely to the infrastructure, because that's where the differentiation ends up happening. So you don't need to have a platform shift necessarily in order for you to have, you know, like important infrastructures with good multiples. Like I just think it's a durable part of any sort of application. But then the question is, what happens when it matures, like the clouds do and becomes an oligopoly
Starting point is 00:17:31 and they no longer can private investors invest on it. But every time we've seen that happen, you see a layer of infrastructure evolve on top of it. So maybe say it this way. So the way I view the world is you've got a bunch of app developers who are non-tactical. And they want to develop apps to solve all sorts of like consumer problems and business problems and whatever. So their goal is to build an app for a non-technical user. So why would they kind of invest heavily in technology? So they will pick up whatever is easiest to use technically.
Starting point is 00:18:04 And so, you know, the companies that fill that need are the ones that provide a lot of the value of the true difference. Yeah. Does it make sense? And so I always think that will always be something that you can make it faster, you can make it easier, you can make it more reliable. It'll always be kind of the bedrock that apps get built on. And, you know, until like people stop wanting to produce apps, like, you'll always need to produce. And this is totally independent of like macro shifts or platform shifts.
Starting point is 00:18:30 How do you think about if or when the big players are going to decide to like enter those markets and like how that might impact things? You know, like in cloud, like, whether or not AWS was going to offer something directly, now, whether, like, you know, Open AI or Anthropics and offer something directly, or are you like, if I'm investing at the Series A or B, that's not that important, you just have to think about great entrepreneur, big market, and that's okay. Yeah, I mean, I mean, I worked at VMware for four years. We were the big incumbent. And so, like, we're always worried about the shadow that is cast by these incumbents. But the reality is, like, it's not nearly as strong as ever. everybody's worried about. And it's very hard for these big companies to execute. And so, you know, ReInvent is like the AWS conference. And I swear being an infrastructure investor for so long, every time they have reinvent,
Starting point is 00:19:21 I have to play therapist to all the founders. They call them like, oh, they're entering our market. They're entering our space. Like, they're doing all those competitive stuff, et cetera. And I still today can't really think of a company that ADWIS has put out of business, even though to enter the market. And the reality is it kind of compete with everybody.
Starting point is 00:19:35 And so, I mean, if the market will bear an independent company, then that requires your own sales force, your own focus on customers, your own support, your own technical differentiation, right? And like, no big company can, like, build a small company in a big company because they have too many centralized service. And if the market won't bear an independent company, there's no company to build anyways. And so my view is, as long as the market is continuing to expand, which software is continuing to expand, if you enter an area that's viable, as it expands, you will fill that expands. And if that doesn't work, then the market is either not big enough or it isn't expanding fast enough.
Starting point is 00:20:11 And I just feel like if you take the historical view, this is the case. I strongly agree with that. When you think about, like, markets in AI right now and, like, how things are evolving, one of the things I thought was really interesting from talking to Mark was, like, basically as, you know, you all sort of ambitiously grow the firm, one of the biggest whole, one of the biggest issues is companies running into each other in this, like, conflicts dynamic. Yeah. And obviously, you're becoming prominent within a, you know, area to a degree where you're going to just, I would imagine, just companies, as they grow, they grow into each other.
Starting point is 00:20:46 Yeah. And what's your experience with that? It's such a complicated problem because you can do, you can try and do everything, right, and still end up with conflicts. So it's actually pretty good to categorize the conflicts. And so perhaps the most common conflict is one company that, two companies that you've invested in, one pippets into the other one. Yeah. Right? And this one, it's basically impossible to do anything
Starting point is 00:21:07 because companies have to figure out the right business. You're on the board or not, and you don't control it, and they do that. So that one, I feel like no investor can, you know, there's nothing an investor could do. There's another more pernicious type of conflict of existing portfolio companies. I'll get to the net new companies soon, which we're seeing a lot now, which is imagine you have an old, imagine you have a tech revolution like AI. And you have a set of old companies
Starting point is 00:21:35 doing things the old way. And you have a set of new companies doing the new thing. And the old company wants to pivot to using AI to do what they did before. But the reality is, is the old way is not the AI way. They're not AI native, right? And so now there's this question where she's like, well, when we invested in this company, it was doing X, whatever it is. And now it wants to do X with AI. But the reality is the AI way of doing it is entirely different and they've got no chance. So then you have, you know, the dilemma, going to the founder and saying, listen, we're investing in one of the new space,
Starting point is 00:22:07 but it's AI and you're not AI, which, of course, that's not going to work. Or you just don't do the deal. I run into this one a lot. We've got a very large portfolio. And today, we've just been like, hey, listen, we're going back to the portfolio companies that we have. Actually, this just happened last week, the founder of economy, since you can't invest in this, this is the space we're going into.
Starting point is 00:22:25 They haven't even done it yet. And we try to do the right thing. Yeah. There. So that one is, I think, the toughest one for all investors today just because, like, you never want to kind of bet against your own portfolio, but like the reality of them doing, like being actually competitive is very low.
Starting point is 00:22:40 I think the most, and then there's, there's one more, which is kind of like this fun stage thing, which is like we've got a growth fund. They do their own thing. We've got like an early stage, they do their own thing. And like sometimes the communication isn't always perfect and you can kind of end up in like, you know, conflicts that way. The one that we simply do not do is, you know,
Starting point is 00:23:00 and I always have this talk track. You probably heard me say it. I borrowed it from Chris Dixon, but it's very, very effective. Where you basically say, for any company that I'm an investor in, if I'm talking to another company that looks similar, I'll ask the founder, I'm like, listen, is this your mortal enemy? You only get one. You can't, you know, 21, you only get one.
Starting point is 00:23:19 But if this is your mortal enemy, we'll do everything together to kill it, and we won't invest in that. But like, you have to name your mortal enemy, and you can't keep changing it. And I think at least that gives them the power to decide who it is, but not kind of hamstring investment efforts. Totally. that makes sense. I mean, it's also funny because I think a lot of times, you know, two companies that look the same but are serving very different segments of the market. Those are actually, they might sound like competitors or they're actually never going to bump into each other versus two companies offering, you know, different products to the same customer are much more likely to bump into each other. Well, 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,
Starting point is 00:24:02 They're all competing, like, totally different companies' spaces are competing for the same talent. So the first time I can remember where the actual talent competition is like way more fears than the market competition. Well, 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
Starting point is 00:24:19 has nothing to do with it, but we were interested in that candidate and one of your partners sold that candidate on one of their... Totally. It's a very real thing. And what's interesting is like, you often don't even know, right? Like, you know, like, they'll say, oh, I'm, you know, I'm talking to a health care company, you know, or whatever. And you're like, okay, well.
Starting point is 00:24:36 What's tough, but I guess it's also like a 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. This 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.
Starting point is 00:25:01 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 another thing 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,
Starting point is 00:25:16 mega-acquihire acquisition things. It's like certain experiences are just worth a huge amount. Yeah, 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.
Starting point is 00:25:37 And he was like the one guy that could make it work. And so he just basically got these crazy, at the time, crazy offers. And he'd jump between all the router companies and do that. And there are very few teams that could do this. And so we've always seen this episodically in the industry. We're just kind of seeing the new version. And listen, the businesses are working and they're doing great. We're kind of seeing it on steroids.
Starting point is 00:25:55 Yeah. I mean, you know, if you're a fang-sized 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, in 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 SPAC craze? And then now we've got these queer and aqua hair things.
Starting point is 00:26:29 I 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 markets try to do to get access either to the talents 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,
Starting point is 00:26:47 I'll do it where to act will hire. But again, I feel like this is all normal in the sense of, you know, we've seen it in different shades in the past. Yeah, totally. It's like an evolutionary response. What are the markets right now in AI that you feel most confident are totally working? What are the ones where you feel like they're on the horizon
Starting point is 00:27:06 and 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. Creating an image, creating music, you know, creating speech.
Starting point is 00:27:26 And we don't think about these. markets as much because we're all so focused on, like, the frontier labs. But, like, it's cheaper to build these models because they're smaller. And then, like, you know, people need content. And, like, actually, like, the economics are so simple. Like, I, you know, like, whatever. Imagine you're an artist and you're like, okay, I'm going to, I'm going to draw a picture of Martine, right?
Starting point is 00:27:49 Like, how long would that take you? A while. Whatever. Three hours and it costs you 400 bucks, right? But if I have a model to it as a hundredth of a penny type thing, right? So you've got a four orders of magnitude difference in economics. So that's why we've seen those types of companies. I think like 11 labs or whatever do very well.
Starting point is 00:28:05 So like that's clearly working. And this is content creation where the marginal cost of creation goes to zero. I actually think the whole kind of lowliness, companionship stuff is definitely working. It's just this very fragmented market. So I think it's, you know, I think the unit economics 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, you know, that will do fine. Code seems to be working incredibly well.
Starting point is 00:28:34 Yes. And, you know, we, you know, you see this in, you know, in cursor and the whole thing. The areas that I don't know, I mean, they're working, 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 agentic-e, auto-beating. These are the 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, so the Biddle Bucket was like, was companion, was actually like, you know, like, like the friend, the emotional, like the character that
Starting point is 00:29:11 AI is like there's a long tail of companies that are that are basically emotional support and our friends and our entertainment. It's probably also a big component of the usage of like the main models and so. Yeah, 100%. Like that's clearly working in this sense that people are willing to pay for it, the engagements grade, et cetera. From an investor standpoint, it tends to be kind of long-tailed and fragmented and kind of spread and stuff. And then that enterprise agentic workflow type stuff.
Starting point is 00:29:31 That was the fourth one I mentioned. That's like, you know, chatbots. I mean, clearly it's working and 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 content creation one where it's like. Totally. It's just a model. Those ones we're still trying to understand.
Starting point is 00:29:53 Yeah, I mean, one way to think about that is like how. How confident are you that highly skilled work will get replaced in, let's say, like, 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. It somehow has to, like, mimic exactly what I do.
Starting point is 00:30:36 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, not as exact, and they need a lot of guidance. And I think that's an area where there 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,
Starting point is 00:31:01 we've got lots of investments, we're very excited about it. We think there's a great future there. But, 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, 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 who obviously knows a lot, too.
Starting point is 00:31:23 And it was great. He's amazing. It's 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 they themselves experience, but clearly it's going to get there. So, yeah, I'm curious.
Starting point is 00:31:40 So just so, you know, AI in general has this problem, which is so dazzling. People conflate, oh, this is dazzling with 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 are magic. And then somehow that dopamine, you know, hit.
Starting point is 00:31:56 What's really funny is, so I posted this on X and, you know, like this study that was saying that people experience 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, this is crazy. I've been using it and I'm so productive. And then the reply to that is like, that's what the study is saying. Yeah, yeah, yeah, yeah. Which I'm sure for some people there, but, you know, there is this thing. Literally, there is an endorphin hit. These things are absolutely magic,
Starting point is 00:32:22 but I don't think 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, it's pretty routine, right? Documentation. It's great a writing documentation, right?
Starting point is 00:32:40 There's a lot of boilerplate stuff it knows. The thing that I use it for the most is, you know, writing code isn't just writing code. A writing code is like understanding the frame, It's knowing how to deploy it. It's knowing how to run the tool chain. And there's no first principle way of knowing that type of stuff. There's not like some core computer science fundamentals
Starting point is 00:33:01 on deploying to Netlify. 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 be very effective. don't, it may not be as effective. And so I think that, like, studies like this that are purely observational are hard
Starting point is 00:33:26 to read into because, you know, it's just like, this is like, 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. Listen, I remember an other epochs of developing. productivity. Like when the IDE came out, when a higher level length is, when Oop came out,
Starting point is 00:33:54 like we get so enamored with the tool set. Like, I'm just going into programming. I'm going to everything in it. And it turns out these were great advancements in computer science and they helped the best practices and they helped architecture and engineering. But at the time they came out, they were just so cool. Like that just kind of took a lot of her focus. So I think we're seeing that. So it's like this drop of productivity is not like necessarily code requires you to drop productivity. I think it's just so cool. I'm going to try. with everything. Yeah, it does seem like it's on a path to, like, you know,
Starting point is 00:34:21 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. It does seem like we'll get to a place where, like, you can... It's so clear. I mean, this is incredibly obvious. I mean, you can literally just scope into a subset of things that are obvious, like, it's really good at writing text. It's really good at writing documentation.
Starting point is 00:34:35 Yeah. 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, there's clearly, these things are obviously good at. Yeah. I just think we get so enamored with it. maybe we start using it for stuff that it's not so good at
Starting point is 00:34:50 or not so equipped to deal with, et cetera. But yeah, this is very clearly, it's going to change software. And sorry, I don't need to ramble on. No. I just have to say, I have been in software for a long time since the late 90s. We disrupted everything, right? We disrupted the back office.
Starting point is 00:35:06 We disrupted hotels. We disrupted everything. It's the first time I say that we're probably getting legitimately disrupted as a discipline, right? 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.
Starting point is 00:35:21 Yeah, 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, open AI as open source model. And I know this is like thematically and spiritually important. Like, why do you, why do you think that it is such a critical part of the way that, you know,
Starting point is 00:35:43 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 closed 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, you know,
Starting point is 00:36:06 and then it kind of keeps the people that are closed 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 in the past, academia, VCs, startups were all very pro-open source because they understood that it was a very important part of a healthy competitive ecosystem.
Starting point is 00:36:31 And 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, were decrying how dangerous it was in relationship to AI. The implications of this to me are huge, right? I mean, of course, you know, the national security implications are pretty straightforward, which is like if somebody else does the open source or proliferates, and that's not good for U.S. interest, but for the industry, it's terrible, right?
Starting point is 00:36:55 I mean, this is kind of how you actually create monopolies if, you know, you're not allowed to create something that enables everybody else. And again, it was very dramatic when, like, the Node Close was like, open source is bad, and Founders Fund is like, open source is bad, and you had academic saying open source is bad. And so I was much more interested in, like, trying to reset the discourse than, like, like any specific open source release yeah and i guess a lot of that probably came down to like how uh 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
Starting point is 00:37:32 steel man in your mind you know at the moment when closed source was like such a strongly argued like if you had to you know argue why you think people were saying that like what would have been i really think it's the legacy of boastrom right like so you know boathstrom wrote the book super intelligence in 2014. Terminator's waking up. We got a continuum. But this is before all of these things, right? That like, like Boastrum's book was a thought experiment.
Starting point is 00:37:53 It was like this platonic ideal of AI. And then somehow that created this, you know, a very interesting kind of intellectual journey on the perils of AI. But then, you know, like GPT2 lands and these two things got totally conflated. You also got, there's a lot of incentive for people to be dumery, I think. Like it like gets a lot of clicks. It was like... Yeah, but it's the weird thing historically.
Starting point is 00:38:19 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 risks, right? We were running critical infrastructure on it. We had totally new types of attacks like the Morris Worm, which had actually taken down computer system. So we're at this space.
Starting point is 00:38:39 We're 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 were like, this is great, the technologist 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 for both sides of the debate. Like, I'm not a, you know, I'm not just, you know,
Starting point is 00:39:02 pro-innovation at all cost. But, like, that's not what was happening. And so, like, maybe you're right. Maybe it's like the duber's got more a click, but I think it's something more than that. I just think that there was an existing intellectual legacy that came from Bostrom that had some very influential people, right?
Starting point is 00:39:16 Like, Elon was pilled by that. You know, Eric Schmidt, Moskowitz, and they had very legit concerns, but they were kind of already primed and, like, you know, there was already kind of that ready. So when it happened, I just think they were already ahead of the game. It took a while for the rest to catch up. And now I listen, when I listen to the discussion, it just feels more even-handed, which, thank God,
Starting point is 00:39:41 I don't have to, like, be on Twitter 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 would say that like there aren't real risks. No, there's totally real risk.
Starting point is 00:39:54 It was just a totally lopsided debate. It's so crazy when VCs are talking against open source. I mean, to me, I mean, and like no academics are talking in defense of it. Now, now we have a bunch of academics in defense of it. I mean, like, I think the right people got mobilized, but it really took some, some rallying to get the right folks back into the conversation.
Starting point is 00:40:12 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. One that I thought was a really interesting point from Mark when I talk 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. And so many partnerships or trying to get other people to a no and like that is like the common
Starting point is 00:40:46 function 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 yeah i'm just curious how you feel and you know your experience you know in the last couple of years in ai land so one of the reasons mark is such a great leader is he his intuition on the temperament of people is 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. There's definitely a more aggressive.
Starting point is 00:41:25 I mean, the reality about AI has been a lot of money that's already been lost in absolutely record time, right? Right? So just because, like, the upsides aren't great, doesn't mean, like, the down. Like, there's been a lot of money, you know? And so, you know, as a firm, we tend to be fairly disciplined and do a lot of market analysis. And he thinks are coming.
Starting point is 00:41:42 And so, like, you know, he's very good about, like, pushing the team. And 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 a road to or compromised by doing that. On 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 what was in his head. what he was saying that. But I just think if I was going to add a little bit of nuances, my observation of Mark is he's very good at pushing when people need to push,
Starting point is 00:42:17 but he understands the situations when, like, 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, macro, you know, shift in order to get the right one without being too overbearing. Yeah, I think, you know, some of that conversation was in relation to like, you know, fund sizes and what's possible. And I think some of it was articulating just like these companies can be enormous. This opportunity is like, you know, quite oversized relative to what's.
Starting point is 00:42:48 Yeah, yeah, but I mean, but again, I just think it's a important to note, which is, it's a per person thing. 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 to the people. This is an intellectual landmark, which is set in a infinite. is 100% the right one to do.
Starting point is 00:43:09 Yeah. But what's important, he's so good at that. Yeah, it is in relationship to the mindset of the people that he's talking to. And what. And what flagposts do you have to put out to get people to the right place? And 100%. And then I have seen him very subtly, depending on who is the audience. Yeah, yeah, yeah.
Starting point is 00:43:25 You know, he'll like move that flag post to different places. Where do you normally experience yourself there? 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 ten. 10 for aggressiveness. I would say my team is a 5 or a 6 out of 10. There's people on my team that are 10 out of tens. There's people on my team that are 3 out of 10.
Starting point is 00:43:48 So I think, like, if you did a normal distribution, I'd say we're 6 and a half to 7. And so for us, you know, he, I mean, 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 the, I mean, being a leader of people is always in relation to, you know, pulling, you know, minds.
Starting point is 00:44:07 and it's right. So that's always how it goes, which is, you know, it's a rare thing. It's rare to be able to do multiple versions of that at the same time with lots of different. No, exactly. And it's just, it's just, it's hard to appreciate from the outside because you have to actually see the conversations. Yeah. It's something that he's just phenomenal at. And the very kind of nuanced different takes where he kind of knows where people are, you know, kind of nudge them 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.
Starting point is 00:44:34 Yeah. 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 extremely special founders. Is there ever a version in these kind of moments when a good founder and, you know, a great market with like exceptional traction or some configuration like that? Yeah. Where 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
Starting point is 00:45:07 I think it answers this question. So it's very simple. So the way that we think about investments, and the reason is, is the only way you can scale because you can actually distribute this kind of algorithm to a team is the only sin
Starting point is 00:45:19 is picking the wrong company in a certain space. Because of that conflict things? Because you're conflicted out of the winner. Like, investing in a space that doesn't work is fine. I mean, like, there's no way you can actually predict whether a space is going to work or not. I mean, that's like weather prediction, right?
Starting point is 00:45:39 But in a given space, if you know all of the companies, you do the work, you can most likely, you know, 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 VC. So I don't care of VC's think it's interesting. If there's five founders in a space and they're good founders,
Starting point is 00:46:03 man, they're betting their families, their fortunes, you know, their time. So it's probably a real space. And then we do the work to understand the space in all the teams. And then we make a pick within that. I mean, that's really how we think about it. That's true within AI as anything else, right? The thing that's harder is, and I've evolved so much as an investor, I used to think like, oh, we get good deals, like price matters, outcome matters,
Starting point is 00:46:29 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 you're saying? it doesn't matter at all. I'm saying, so, so, so, so, we don't know what the TAM is because it's growing so fast. Like, nobody knows valuation.
Starting point is 00:46:47 So I think this is, it's 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.
Starting point is 00:47:11 You just need to be in the best one. You have to be in the best ones. And the market will just produce what produces on someone. The market is the market. And listen, either you believe that the stuff is expanding very quickly in markets are efficient or not. And listen, having been through the dot-com, boom, and bust,
Starting point is 00:47:28 the reality is the market was actually pretty smart. And if you put the bets in the right companies, that would have been generational wealth. 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 and damn.
Starting point is 00:47:44 Is the rational sort of behavior then to, you know, obviously 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? So does that ever push you to being like, I'd rather wait around or two here? All the time, right? Yeah.
Starting point is 00:47:58 All the time. So, I mean, yeah, this is all very rough heuristics, right? Like, you know, we get it wrong all of the time. you know, I've made, you know, like, I've made so many mistakes. And so you're just trying to beat the market, right? You're just trying to have, but, but yeah, very often, like, our discussions are, like, do we actually know who the winner is? Yeah.
Starting point is 00:48:19 Like, you know, and often we wait for that reason. Basically, the earliest that you feel confident you can pick it. Yeah. And so, like, listen, when we do see, normally it's, like, the person that did the thing in the big company, and now I was doing the thing, it is the world expert. And the thing is a very technical thing. And, like, somebody else isn't just going to wake up and decide to do it, who's a good founder, right?
Starting point is 00:48:36 Yeah. Because it's like the pool of people that. do it are like five and like this one's the best of the five like 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 best approach best team best market and then in these types of way and this is where market this is this comes from mark and mark is totally right like if you think you can ask want the market like i think you know it's very tough and so just being the best deals um as a final topic i want to just hear your
Starting point is 00:49:05 perspective on the board relationship and board roles in general yeah yeah and maybe as like a prompt on this i feel like um 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 um you know i often will hear common wisdom that you know it can be 10 or 12 or 15 um but it seems like you know you found a way to do more than that and be very effective with those founders and so i just want to hear sort of your perspective on like what's that relationship what do you think is sort of like the limiting factor here if any how does it all play out yeah um i mean i do think that like a lot of the common was on boards came from like that earlier year in bc when you know it's like people would literally
Starting point is 00:49:49 choose vc for like a life choice or whatever right and i think if you come from like pretty serious operating like you do and like i do like we've just got a lot of hours into the day to throw at it VC 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 and the day, I mean, how much does that, like, like, board worth 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?
Starting point is 00:50:24 I'm actually curious what the most common answer is, but I could imagine. What do you think it would be? Yeah. I would think they would probably say it's something like, you know, yeah. you know, 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.
Starting point is 00:50:41 I'm like, no, that's an invite. That's not a board, right? And so a lot of, you know, there's a lot of this belief that, like, a board member is somehow helping with company building. And almost like, it's actually hard for a board member to be like the best friend of a founder for those types of things because, like, you know, you're a fiduciary and you do governance. And so, like, the actual board work itself is just not a lot from the fiduciary governance standpoint.
Starting point is 00:51:05 So often implicit in this question is, is, like, non-board stuff. Like, how can you be helpful to a company and 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. But, like, it's not the boardwork. It is the other stuff. And so I would say to, you know, anybody listening to who is a VC, you can take as many board as you want. The actual boardwork itself is not.
Starting point is 00:51:30 The question is, can you still be available? to founders and add value, whether you're on the board or not. A lot of the companies I spend the most time with, I'm not even on the board on it. Yeah, that's what's funny to me is, you know, 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 seeds.
Starting point is 00:51:46 No, there's no board seat. And they're sort of decoupled. Yeah, exactly. So I feel, I feel like we need to be very clear. Like, a board is to keep everybody out of jail and to, like, do the right thing for the shareholders. And like, like, the actual work requirements to that are relatively little.
Starting point is 00:51:58 Yeah. That's actually not the hard thing, but we use it as a proxy for the hard. 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. And it's not a board thing. It's like the help the company type thing. And I just think this is like the new era VC. Like, you help these companies with more than just one person who shows up, you know,
Starting point is 00:52:24 off the goth field, like, I don't know, every Thursday. Yeah. Well, that's a great place to leave it. Martin, thanks going for making time for this. I really enjoyed it. It's a plunge, and that was great. Thanks for listening to the A16Z podcast. If you enjoy the episode, let us know by leaving a review at rate thispodcast.com slash A16Z. We've got more great conversations coming your way. See you next time. This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product.
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