Speaker 1If there is a dislocation, no one is better prepared to survive it than hyperscalers. Let's take neoclouds. Neoclouds right now, there's a whole bunch of them. I think at least half of them go away within 36 months. Fireworks is making a lot more money than base 10. The more you customize the model, the more the token changes its value.
Speaker 2This is 20VC with me, Harry Stebbings. Now everyone is calling today peak froth. Prices are out of control. There's too much money. We don't know what's going to happen with this AI bubble. Well, you know what's really valuable in this time? Wisdom. Jerry Murdoch, joining me in the hot seat today, he's the founder of Insight. They manage over $90 billion. Jerry has seen pretty much every technology cycle of the last 25 years. He's invested in some of the biggest companies across those 25 years. And today we debunk whether we are in a bubble or not, whether China will beat the frontier models, whether we are about to have the greatest technology in the world, and whether we are about to face the greatest cyber security threats of our lifetime. This and so much more in what really is an incredible, wise operator truth teller, saying it like no one else is willing to today. This was incredible with Jerry. But before we dive into the show today, every great software company eventually runs into money. Uber had to move it. Shopify had to hold it. Airbnb had to settle it. Money movement stopped being a FinTech problem. It became a software problem. And increasingly, God, it's an AI problem too. ZeroHash is the infrastructure that makes global instant money movement seamless. One API integration for stablecoins, digital assets, and modern payment rails. So builders can stay builders. ZeroHash powers some of the world's largest enterprises and financial institutions, including Kalshi, Stripe, Morgan Stanley, Gusto, and Interactive Brokers. If you're thinking about stablecoins, digital assets, and the future of money, it's time to talk to the team at ZeroHash.com. Visit ZeroHash.com/20VC to learn more. While ZeroHash powers on-chain money movement, MongoDB powers the data behind it. MongoDB has always been the database developers' love. Well, now it's the data platform AI agents need. Agents need accurate context, fast. MongoDB stores, searches, and reasons over your data in real time. JSON native database, vector search, and voyage AI embeddings all in one place. One system instead of ten. No data pipelines to maintain. Ugh, this sounds too good to be true. Build and scale. From your first user to billions of vectors. Run on any cloud, on-prem, or your laptop even. That's why 75% of the Fortune 100 run their most critical apps on MongoDB, moving trillions of dollars every single day. And it's why AI native companies like Eleven Labs run 40 million agents on MongoDB. So if you're building an AI, MongoDB for startups helps you move far faster, with Atlas and Voyage AI credits and dedicated support. Don't build agents that answer once and forget. Build agents that remember and learn from your real-time data. Go to mongodb.com/agents. That's m-o-n-g-o-d-b dot com slash agents. While MongoDB scales the product, Framer scales the story. When a new landing page turns into a pile of tickets and handoffs, Framer helps your team move faster. Here's what I love. Framer is the pro AI website builder for creators, teams, and businesses that care enough to get every detail right. The agents close the gap between AI-generated ideas and production-ready website work, because it all happens where the site actually lives. It lands on the canvas, stays editable, and can be published when the team is ready. So you can build custom code components, create and manage CMS content, optimize SEO settings, and ship everything all in one place. The agents bring speed and scale, you bring taste, judgment, and control. It's an enterprise-level solution, too. Premium hosting, enterprise-grade security, 99.99% uptime SLAs, which is why the world's leading brands, like Perplexity and Miro, build in Framer. Learn how you can get more out of your site from a Framer specialist, or get started by building for free today at framer.com/20vc for 30% off a Framer Pro annual plan. That's framer.com/20vc for 30% off. Framer.com/20vc, rules and restrictions may apply. You have now arrived at your destination. Do you know what? I think I genuinely have the best job in the world, because I get to sit down with people like you. And I'm dumb as rocks, but I get to ask questions that normally I wouldn't be able to ask. And I get to learn from the greatest minds. So thank you so much for joining me for a second time, Jerry. I'm happy to be here. Now, I want to touch first on something that you said to me before, which was you said if the year on war continues to fester, then you expect to see a correction. And depending on the depth of the correction, the AI bubble will burst between October the 26th and March 27. Can you help me understand your thinking here?
Speaker 1Sure. If you look at what happened in 2001, the end of the dot coms, the innovations stopped for a while. And then new innovations came in, the lamp stack, which led to gold out of websites. Google started taking off. 2008, cloud computing. Very slow to take off. And this is because this financial disruptions slow things down. The stream of commerce gets disrupted. And right now with AI, debt is a huge part of this. It's so unique compared to previous cycles. So much debt, all the hyperscalers have taken on much more debt than they ever have before. And the challenge becomes, will these guys get disrupted if the credit markets have a disruption? Which would be certainly what would happen if we had a problem in the overall capital markets.
Speaker 2Okay. The concern for you here is that we'll have a credit market disruption caused by the global conflict, which will then impact the ability for these hyperscalers to borrow cheaply?
Speaker 1Well, that's one potential disruption. I see several that could occur. And I think if it's going to happen, it's going to happen if this Iran war, we can't have it just continue. The reason I say this right now is of complete and utter nonsense. It's just complacency. We've got tremendous red lights that have been going on for a year or more on the credit markets. And there's just complacency. It's like, oh, we're fine. And I don't think people are counting for risk. I mean, if you think about it, those guys that are in the private debt market, the spreads are too narrow between real risk and not so much risk. And they're not really accounting for that. And so I'm concerned about that as one sector, but there's multiple because this AI revolution is incredibly complex. With massive amounts of dollars being spent on it globally.
Speaker 2What are the signs to you that we're seeing a cracking in the credit markets?
Speaker 1Well, complacency is the first thing you look at. When it happened in 2008, 2010, there was a handful of people, which there's always been documentaries about these guys that made money on shorting the housing market. But everybody else in the world had no idea what was really happening. It was complacency complete, you know. It was, you know, really ugly situation where the people that were supposed to be keeping an eye on things, which were the credit rating agencies and the credit risk departments of the big banks were asleep at the wheel and this terrible thing happened. And there was a malaise enforcing this risk. People didn't recognize because historically, there had never been a huge default problem with mortgages and that was the kind of thinking that was there and they didn't realize that the underlying. I see the same thing today in that in the credit markets, there's many opportunities for there to be problems. In the late 90s, you had long-term credit blow up. We just had Leopold blow up because he wasn't accounting for the leverage that he put on his fund. I still see that there's the little warning signs that the complacency is the biggest issue. In Japan, another problem, right? So this is the second time the US has bailed out the yen. Why are they bailing out Japan? That's because Japan holds a trillion dollars in treasuries and if they have to unwind that, if they sell 100 billion worth of treasuries, the market could absorb it. But they sold 300 billion worth of treasuries, a third in order to be able to buy dollars to support the yen. We would have a real problem on our hands immediately, immediate global problem. So I do a lot of backcountry skiing and you recognize the avalanche conditions when they're worse or they're better and you recognize things can be changed. It just easily tipped over. And so the war in Iran, if it gets really ugly, which it hasn't yet, if things collapse and inflation comes back, these are disruptors, all of multiple different opportunities for disruption, all based on the war.
Speaker 2When we look at prior credit market cycles, like you mentioned there, was the challenge not the underlying assets were of poor quality? When we look at the hyperscalers today, yes, Facebook is having a bond issuance. It's priced higher than expected. But Meta's core business is throwing off hundreds of billions of cash flow. They don't need to borrow, really. They could do it off balance sheet. It's an optimization game. The assets are good.
Speaker 1I think you just saw that the free cash flow is the lowest it's ever been in the history of the company, number one. Number two, back in the dotcom bubble, there was a lot of fiber that got laid in the ground and that fiber was always valuable. But the companies that laid the fiber and stuff, they all went bankrupt. So when you're really heavily dependent on debt, and there's a dislocation, the underlying value of the asset declines. It may not decline forever, but it declines pretty sharply in a very short period of time. And that's when you have margin calls. That's the way it goes. What should they do from
Speaker 2here? They should not take out such levels of debt. Like, how do you expect this? Well, I mean,
Speaker 1look, people are making decisions on the risk that they see to their business. If there is a dislocation, no one is better prepared to survive it than hyperscalers. I mean, all the hyperscalers have enough ongoing business, and they've been very consistent. That's why they're worth what they're worth. The Magnificent Seven is there because they've been doing this for a long time. And so they know that they could absorb this. And if it happens, it'll be good for them because everybody else gets wiped out, and then assets become cheaper for them to acquire, and they're still in good shape. The demand for AI compute is not going to change. That's not going to go away. The issue is the ability to fund it in the short term. Let's take neoclouds. Neoclouds right now, there's a whole bunch of them. I think at least half of them go away within 36 months. And if there's an economic disruption, a lot of them go away right away. Can you help me understand that? I can't pass
Speaker 2that over. What will separate the neoclouds that go away and become valueless versus those that retain value and become even more valuable?
Speaker 1Let's change the question around, which head funds are going to go away and which ones aren't? If you looked at Leopold's returns, you think he's never going to go away. And he's probably going to survive this because he still has a good return for the year. But people are going to be a little wary about his risk taking capabilities. And so it's underlying, it's the people running the company. What's going to separate one neocloud from another is who is running it. How are they organizing it? We don't see it, you and I and everybody else, we can't see under the covers how that company is being run. I can tell you, if you look at inference providers, I think fireworks is making a lot more money than base 10. And you look at the efficiency there and you think, oh, well, base 10 is raising money at the same valuation. Well, it's not the same business. I bet on fireworks over base 10, 10 times better business, in my opinion, because they're more capital efficient. That's purely based on capital efficiency? Capital efficiency and their willingness, to make profits on business. I think cursor was pretty smart. And the base 10 contracts from last year with cursor, I don't think there was much profit in it for base 10. They just got revenue and they got scale from it, but they didn't get a lot of earnings. And so if you're not making a lot of money, and you're putting up a lot of money, you're at
Speaker 2risk, you're absolutely at risk. You mentioned fireworks that we had Lynn on the show amazing, where she said that actually specialized intelligence would be the future and that the majority of companies would have their own models trained on their own. Their own data. And that would be very important. Do you think we have a world of millions of specialized models in this way? And a couple of frontier providers? How do you see that?
Speaker 1Well, on two things in the big overall view, if we say that models are there to provide intelligence, and we look at the world, and you got 7 billion people, how many intelligent people do we have in the world? I mean, in some ways, you're going to see that models are going to replicate humans in this sense of being specialized. And being able to do a specific task in a specific way. You know, someone who's cutting a gem has a certain intelligence about how to do that work. That's pretty specialized. And I think you're going to see intelligence is in early days of these models, it's all going to be about specialization and the ability to customize. What's happening is, is that you can't customize anthropic models or open AI models right now, not the big frontier models. You're not allowed to do that. So that's just given an opening, for open source models, to be tuned. As I mentioned on our last call, I thought that open source models and ASICs chips were going to kind of be part of a tsunami of their own. And if you're looking at a frontier model with double dollar digit cost per token, and you're looking at an open source model that's 10, 11 cents per token, while all tokens aren't created equal, it's still enough of a difference that there's going to be a massive adoption. And by the way, it's not like AI is only demands for enterprise customers or a few consumers. It's a global demand by every business in the world today. Even though people haven't quite acted on that demand, it's like websites at first, right? In the nineties, only a certain amount of companies had websites, but the building out of websites has not slowed down. It's massive. It's just the desire for that and the need for website building continues to this day. It's endless. And I think it's the same thing. When you look at intelligence, the demand for it is going to be endless by endless numbers of people. And this is helping creating the opportunity for open source and ASICs chips.
Speaker 2Totally get you on cost efficiency of open source compared to frontier models. But what everyone says is you're seeing the token traffic go towards open models and you're seeing the dollar traffic, the revenue, go towards frontier models. Is that how you expect it to continue? And will frontier just be paid a lot more for harder problems and open source?
Speaker 1That's a great question. I'm going to give an answer, but I want to caveat it this way in that there's opportunity in the answer for short term disruptions that last from three months to a year where economics appear to have leveled out. As long as the frontier model companies, and I'm convinced they have goals for continuous learning and ultimately lifelong learning in these models. And so if they can execute against those goals over time, they're going to be very successful. for the next decade, the demand for those models will never cease. And so they'll just continue to grow. But because the global demand is so massive, I mean, I'd assume that we're probably in single digit demand fulfillment today, low single digits. And I suspect that open source has a long way to go to fill in the need. And of course, it's going to be low cost. And of course, most of the dollars are going to go to the people that can afford to pay for them. I mean, Teslas were really expensive at the beginning, and only wealthy people could afford a Tesla at the beginning. And now that's changed. I think that's the way it's going to work, that only the wealthiest companies and people can afford these models in the early days. And open source is going to be suffering from a very big catch-up game in terms of revenue. But they're going to get a lot of money and a lot of things very, very soon. It's coming.
Speaker 2A token is a token is actually what Gavin Baker said the other day. And Jensen doesn't give a shit whether you put it on a frontier or an open source, he wins at the end of the day. Do you agree with that perspective? And how did you analyze his open source evangelism with his letter?
Speaker 1I disagree with a token is a token. That may be true at the moment with pretty much frontier models. But I disagree with it because companies like fireworks and others are heavily dependent on open source. And I think that's the way it's going to work. Helping companies to customize, the more you customize the model, the more the token changes its value, right? Because the more you customize what's being produced, and some models, they talk a lot more than other models. And so they produce a hell of a lot more tokens, just like your guests,
Speaker 2I assume. And so essentially, you're saying the efficiency gains that can come when you work with a provider like fireworks means that one token goes a lot further than another token,
Speaker 1in a lot of cases. Well, there's two things. So each model is the more it's customized, the more it's going to have a particular, I'll say, style to it. And whether it's a verbose style or a style of brevity, that's going to matter a lot in the overall cost. And I think that what we're going to see is as enterprises and people with money have more time to understand these, more and more customization is going to occur to do things. I mean, when you're talking about agentic systems, it's natural that you think, hey, you're going to use an open source model for coding because they've got that figured out. But for customer service, for onboarding, you can see open source models being really ideal because it's a highly specialized task. And I think that highly specialized tasks are going to be something that pays off a lot quicker and a lot cheaper. If you only have a million dollars to spend, you could spend that million dollars. So I think that customization and getting specific tasks done a lot more efficiently than you
Speaker 2can on a frontier model. How does this not cannibalize frontier models business? I'm not one that wants to see the open AI and anthropic challenge. Their thriving is good for all of us. But I don't understand how that doesn't cannibalize their business, making their TAM smaller.
Speaker 1But don't forget, we're talking about intelligence. You want more of it all the time, and you want different flavors of it, right? I mean, humans have emotional intelligence. They have all different styles of intelligence. We know that learning, some people have more visual intelligence, if you will. And I think that we're going to see the same thing with models. We're going to absolutely see this thing that prohibits the cannibalization of frontier models, at least in the short term. What I've seen with every new wave of technology in my career, the market initially expands. And then the contraction comes when there's a contraction in global markets. And then you see the fallout. And then you start again with more innovation. It's this continuous cycle of Cambrian explosion of innovation, followed by the sort of glacial period. when ecosystems collapse and then they grow back again. And so I think as long as frontier models can continue to innovate because they have the money and they have the ability to do more innovation, there's never been a time yet where the open source model has trumped a frontier model on innovation yet. They might be better at specialization, but they certainly don't compete yet in being able to do complex tasks.
Speaker 2When you think about that challenge of frontier versus open, Alex Karp has said the biggest enterprise customers in the world don't want to work with frontier model providers. They're scared that they're going to eat their lunch to move into that business. Is that true? Or is that Alex rather self-servingly then saying, and Palantir will help implement a full infrastructure that's not that?
Speaker 1Well, look, Alex has a bunch of customers that of course are very worried about that. All the CIA and all the intelligence organizations, of course, they're paranoid about it. So he's, one, got a huge customer base that that's exactly the way those people think. But two, look, there's two issues, right? One is the data. And yes, they've been giving their, I mean, Anthropic's been getting all this data and open AI already for years. So in some ways, the cat's out of the bag, right? I mean, if you worry about from a security perspective, I mean, Apple could already rob my bank tomorrow. They have all my passwords. Apple has everything on me, right? If they wanted to. I think Amazon has a lot of data too. Maybe not. The prize data, but they have a lot of data. Microsoft, Satya Nadella himself came out and said, look, we've got a lot of the data around the communication, how communication works inside an organization. So enterprises have already given up a lot of their secret sauce to the years and they should be cautious. I agree with Alex that enterprises need to be smart about just continuously shoving their data up into Anthropic and open AI. They need to practice discernment and they need to think about what they want to keep behind the firewall and they need to continuously have an iterative conversation about that and be careful. And I think in part, this is what's going to drive the open source opportunity is that, yeah, you know what? We don't want that stuff uploaded into the cloud. We want it behind the firewall. So look, two things. One, recognize that enterprises have already given up a lot to third-party companies and B, yeah, they need to be careful.
Speaker 2Going forward, they need to be careful going forward. And security is front and center more than ever before. We're seeing hacks like we've never seen before. We're seeing open AI and hugging face. Anthropic came out saying, hey, Mayor Culper, our models actually hacked three companies. And it's almost like a brag now to have like a, you know what I mean? Our model hacked companies. Thanks. How do you think about the golden age of cyber that is to come?
Speaker 1Well, there's no question that there's a heck of a lot of complacency around security overall. Even people that think they're getting the job done, they're complacent. They haven't really thought through. I mean, I don't know how many developers are running their models in YOLO mode, but probably a lot. And they're thinking, oh, I'll put the model in the container. I'll put the tools in a container. I'm okay. Well, containers aren't safe. You need sandboxes. This is why the big container company, Docker, said, hey, themselves said containers aren't safe. You better put in a sandbox. And that's why they've had a huge success with Docker sandboxes. That's why E2B is successful with cloud. Cloud sandboxes. People don't realize how important it is to really step up the game on security. Everybody, in my opinion, is underestimating it.
Speaker 2When you think about investing today personally, do you want to do a lot more in security? What can I take from that? I'm a venture investor. You know this. Dude, you know I'm here to ruthlessly make money, Jerry. You know me. What should I take from that?
Speaker 1Well, look, if you look at fireworks as a T, I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I'm lucky I invest in fireworks versus base 10 or core. I mean, so you've got this sort of team of people that have a different take and have a different set of aspirations in what they're doing. They're going to move up the stack. They're going to move up and do a lot more fine-tuning and refinement and customization for people. And they're going to be the best ones at it. That's why they're going to succeed. I think you're going to see the same thing in security. And the most important thing that is underestimated is the need for sandboxes. The truth is there's going to be thousands of different forms of sandboxes. And you're going to need a company that understands how models look at tools and what that behavior is and be able to take that behavior. And optimize for it. Because, you know, these agents we forget sometimes are probabilistic. It's not like a developer says, okay, I'm going to go build this little app over here. And I'm going to pick two different libraries. I'm going to see which one does best. And I'm going to generate my app. No, an agent could say, I'm going to open up 100 different sandboxes with 100 different libraries and then determine which is the best app. And where's all these different tools? That knowledge is in a handful of companies today. And if you look at E2D. And you look at Docker, they're probably the two best at understanding all that stuff. So you start there. Because if you don't get the sandbox right, forget everything else.
Speaker 2I have to ask you, you mentioned Fireworks multiple times. Lynn has margins in the 35% range, she said on the show publicly. Many companies within the AI application layer in particular have very depressed margins lower than that, 20%. Should we just all get used to a lower margin generation of companies? And that is AI, sadly. Or should we think differently about margin in this generation?
Speaker 1Early in a cycle with new technology, it's always a real estate game, right? When they wanted to populate Oklahoma with settlers, they just had this giant date, had all these people out there, pulled down the flag, and everyone ran and just put their stake in the ground and said, this is mine. And it didn't matter if it belonged to Native Americans or not. They just did it. And I think in the same way, you've got people doing the exact same thing. They're picking low margins or zero. Zero margins, in some cases, just to get the customers, to get the relationship, to get the real estate. And so it's a strategy. If you've got capital, you're going to own the real estate, and then you're going to go back later and get the margins built into the business.
Speaker 2So you don't worry about that. You're like, it's a land grab. It's more important to put your flag in the ground, and we can expand margin later.
Speaker 1Well, it's just a strategy. I would not invest in people that build a culture around that idea of low margin. No. That's why I probably lost out on investing in Amazon, because I just didn't buy into Bezos' idea that your margin is my opportunity. And groceries and books and things, yeah, he's right. And compute, he was absolutely right. And he scaled it in a different way. But most people aren't thinking like Jeff Bezos in that regard. I believe that you need to build a culture that works. And if you don't want to give all your company away to venture capitalists, you might think about monetizing and generating margin, effective margin. And you can be clever about it. If I talk about the sandbox example, the newest thing is, you know, most sandbox people make money on compute. Frankly, that's a dumb idea, in my opinion. You want to have a model that says bring your own compute. And we'll make money because we understand how to run sandboxes better. We know how to network them better. We know how to provide traces better. We know how to do all these things that are going to give you visibility into what you're doing. Again, innovation is what should be on the front of your mind, and that innovation better drive margin. So even if you don't have it right this minute, if you're not thinking about it, I won't invest in you.
Speaker 2You said like, hey, we need to rebuild the entire stack. When you think about that and the rebuilding of the entire stack, if you start with chips, we see more and more people coming in at the chips layer, whether it's etched or fractal in the UK. How do you see that?
Speaker 1I said it last February. Look, ASICs chips are really ideal if you're thinking about model components. If you're saying, look, we're at a new phase in this AI build out, or what we really want to do is do a lot of model specialization. You don't need a GPU for that. Too expensive. You can absolutely take an ASICs chip. And so I think the number of people designing chips or ASICs chips is because they recognize that trend and they want to take advantage of it.
Speaker 2Do you need to own the chip layer as a model company today, do you think? When you see DeepSeat building their own chips, you see Anthropic. Now building their own Jalapeno from OpenAI.
Speaker 1I'm not sure Jalapeno is the best name. It bothers me. You know, and I love Mexican food. I love spicy food, but I just not sure about that one.
Speaker 2The next iteration is called Padron Pepper.
Speaker 1Look, actually owning the chip is going the wrong way long term. Short term, it makes sense for larger companies because they want to optimize chipsets for models and that's what they're thinking about. But when I was at the Santa Fe Institute, I'm on the board there, we had a meeting with a bunch of chief scientists from all the major AI companies and what we came back with out of that meeting, two points, was one, we don't know how to measure AGI, even if it shows up, but the second point that's useful to this conversation is that we should focus on the complexity between the model and the agent and therefore the human being to the degree that they're in the loop. That's where the opportunity is. And sure enough. That's where the most compelling place I would focus on in investing is that level, which is, you know, from the loops to customization, multiple things, security, all of that stuff from the model out is where I think it's far more interesting. thing. Going back to the chips, short term, I can see why people do it. Long term, I think it's
Speaker 2unnecessary. I'm an investor in Legora, and they obviously fight intensely with Harvey. When you look at the two of them, you think, God, what a competitive landscape. What have been your lessons over the last few years, decade, two decades, when you have two very well-funded competitors like
Speaker 1this? Fund the guy who is the small startup right now, watching them to battle it out. Particularly in the legal market, the chances of being early and taking, when you're in that competitive situation, you're going to take risks, and you might regret. The first one of those guys that has a security leak and security problem, and it will happen, is going to wreck their market opportunity. And you think, oh, well, the other one's going to win. Well, probably not, because they'll probably both be vulnerable, because they're looking at each other. And they're looking at each other. And they're looking at each other. And they're watching what each other is doing. So for me, I look at that situation like, I want to go for the next innovative young company who's maybe not trying to do all things for all lawyers and be more highly specialized, like GetDynasty is in the trust world. Do something very specific. And by the way, this has been Peter Thiel's advice, is start with a niche, dominate the niche, and then grow it out. And so when you're trying to take a whole ocean like the legal system, I just wonder if it's kind of contrary to Peter Thiel's advice.
Speaker 2Do you worry that we just throw price out of the window? It seems like we've never been less price sensitive. This is crazier than 2021, Jerry. I'm investing every single day on the ground. I consistently have founders say, oh, you know, we're raising 100. And I'm like, oh, well, it's like, how much are you raising? And they're like, we're raising 100. I'm like, that's the friends and family round. And when I said to a founder the other day, we write 25, million dollar checks. And they were like, okay, good. So you're small and collaborative. Have we just lost price sensitivity? And is that okay, given all outcomes can be trillion dollar
Speaker 1companies? It's evidence that we're still in the hype cycle, right? We're in the hype cycle, because expectations are beyond everyone's imagination. And so if you're saying I'm going to be a trillion dollar company, my opening round is 100 million or something, or even a billion, whatever the valuation is, are you just recognize and you have to look in your head and look at the people that are going to take that money. And you're going to recognize that has that number been well thought out? Or are they just doing it because the market's doing it? And I would argue that it looks like anthropic and open AI, those crazy mega rounds, you know, at 100 billion, 150 billion might actually have been cheap. I mean, I think Gavin Baker probably believes that and others believe that. And so for a few companies, yeah. But how many trillion dollar companies are we going to have? Discernment, again, is necessary here, to decide, you know, what really can have the sort of hyperscale type growth associated with it? And which ones are going to be also rounds or a little more of a slower growth opportunity. And we need
Speaker 2to and we need to sort out those a little better. It's slower growth venture anymore, Jerry, if we look at fireworks, you know, it's three and a half years to a billion, it'll be four years to 2 billion if they hit end of year targets this year, four years to 2 billion. Jerry, do you remember when it was slack? We were like, wow, wow. Games. I think I think in the case of fireworks, look, they're benefiting
Speaker 1because of open AI and anthropic, they are the next level. And now with open source, taking off, they're benefiting from that. And so they ride on the shoulders of these model builders, and they're the next layer that needs to get developed. And so they can scale right behind that. But if you're somebody else, and like saying, the app layer, I'm just not buying that. I'm not buying, I'm not buying it for the legal, and I'm not buying it for the app layers yet. But for infrastructure, absolutely.
Speaker 2But I get killed for this. I say publicly triple, triple, double, doubles. Dad, you remember this? Am I glib? And my kid, you are a product of a cycle? Or is this just a new expectation level for venture?
Speaker 1You are glib. It's sometimes not all the time. But right now you are. Yeah, I would argue that general statements don't apply here. You have to be highly specific. If you look at anthropic, and you look at what they've done, anthropic and open AI, it's never been done in the history of the world. It shows the importance of the time. So we are definitely, if we look through the history of venture, in a completely different era. And the frontier model companies have done something extraordinary in the history of the world. I mean, this is definitely on the electricity, whatever you want to call it. It's truly extraordinary what the frontier model companies have done. They've lit the match to AI. And the companies that can follow right on top of them and not get killed by them, but can grow and solve more infrastructure problems and help create an ecosystem around the model companies, those guys can, they deserve those economics. Other categories? No way. Like, for example, neoclouds. No way. I don't buy it. I think some one or two of those neoclouds are going to end up dominating. And a lot of them, at least half of them are going to go away. And they're going to go away with massive amounts of money being
Speaker 2burned as part of it. Does the model routing layer carry enough value to you to be independent?
Speaker 1My opinion is open router has massive amounts of transactions, because people are basically lazy, right? It was easy. Okay, I need to connect to this model, I'm just going to use open router. And open router charges 5% on top of that. Which is a crazy amount of money. That's not going to last. You're going to see exchanges. There's a blockchain company called Akinaki that has just launched Dodex on their main net. And this thing is an exchange to go out and buy inference. And as part of that, all the model routing is done for you. And so I think you're going to see multiple opportunities to an open router type product, where people that are hosting the models themselves will provide you know, through an exchange an easy way to to acquire the inference and the need for an open router type product and particularly paying the 5% markup for the inference won't matter, right? Because that's what those things do. They're not necessary long term.
Speaker 2So if you're on the board of open router, and the $10 billion acquisition comes through, what do you say?
Speaker 1You say, Fuck, yeah, this is great. You know, and like a lot of people, you know, you take the money when you can credit to open router, they're there early, developers didn't see another alternative, they could just go to there, go to the API, and they're willing to pay 5% markup to get their inference. And guess what? Shame on the enterprises for letting them burn all that money. That's a huge amount of money. And so I think that you're going to see a big disruption in that model in the next three, four or five months, actually, not just Akinaki, but Venice, Venice IO is doing that. And there's two or three other guys that are now in the process of building exchanges, that you can go directly to And there's two or three other guys that are now in the process of building exchanges, that you can go directly to get the inference you need without paying the 5% markup.
Speaker 2I think you very accurately said about kind of where we are today, the potential dislocation of excitement dislocation due to external affairs, and then the re blossoming of an ecosystem, so to speak, if you think about that, and you advise me as a venture investor, deploying, say your money today, what would you say to me play the game on the field, Bill Gurley style, be mindful, don't spunk cash into Neo lab,
Speaker 1a billion dollars pre for one person out of open AI, what would you say to me, well, Bill's on the board of the Santa Fe Institute with me, I mean, his his guidance is pretty smart. He's pretty much on point with a lot of things with venture capital. What I would suggest is you look for impact, you look for people that are going to be just they're just way different than anyone else. And you look at them and you realize it's not that they want to build this business, it's that they have to build this business. And if you find that in a person, and you recognize that they have the commitment to it, because the commitment to it is all in, there's no other option, look for that. And look for the fact that what they're going to do has impact if they do it.
Speaker 2When you review the founders you've worked with, where was that most obviously striking?
Speaker 1It's rare, right? Because you could say all the founder driven mag seven companies would qualify, right? I mean, Elon, Jensen, Zuckerberg, they all qualify for that definition. But you look at these other companies that you say, wow, fireworks looks to be like that. A to B is definitely like that. The founder Vignan, he's absolutely going to do it. There's no question in my mind. Oven, this guy came out of Meta as well, his name is Sadi Khan. But Alkosha said this is one of the best CEOs ever seen. And Vinod was one of the best CEOs building Sun. So when someone says that you take it seriously.
Speaker 2Do you think we see a compression in like liquidity timelines, we have cursors scaling to 60 billion? sale in four years. Do we see actually venture cycles get shorter in this environment given
Speaker 1companies grow faster? I think what Cursor did because the team is really smart is they pivoted out of the IDE space and they pivoted and in that pivot they convinced Elon that they could build models. They hadn't proved it yet but they convinced him that they knew enough to do it and Elon was pretty desperate to solve his problem with XAI and so it was a great fit and they got the 60 billion so you hit the bid. If OpenRouter gets a 10 billion dollar you know bid from Stripe you take it. I think those are not the norm. those are events that are happening because the board and the management realizes, hey, maybe what we've built isn't a decade company. Maybe this is something that we need to move out of and we take the win for what we had. And I had a few companies back in the day that I wish had done that. Flipboard was one of them. And I wish Flipboard had taken the billion dollar exit,
Speaker 2but they didn't. What happened there? They had a billion dollar exit on the table.
Speaker 1But they had an opportunity. Yeah, they had two bidders going for them at the time. That was very, very interested in them at around, I'll say within 20 percent of that number. And one of them was Twitter. And the other one was TikTok, the founder of ByteDance. And he got advice from someone called The Coach, who was pretty famous at the time. They said, hey, don't sell your company. And The Coach was unfortunately passing away. And the board bought into The Coach's advice and they stayed with it. And now Flipboard, you don't care about it, right? They missed the opportunity. I think those opportunities happen with a lot of companies. I have a lot of arrows in my back from this situation. So you just have to know when it's
Speaker 2a time to go and when it's not a time not to go. We mentioned, obviously, selling to X. It seems like IPO markets are open for the rare few, for Anthropic and OpenAI when they want to, for SpaceX. But I'm concerned that your air table of the world at 485 couldn't IPO. You can't IPO with less than a billion dollars in revenue today. Does that concern you?
Speaker 1No. I just think that we're at a moment in time where if you want a proper IPO, you need to be on track for that. But I would think Cursor, if they had gone out last summer, if they wanted to, they could have gone. I mean, they would have been taken despite the fact. I think the management team was wise to realize that they weren't quite ready for that and didn't do it. But they could have. Absolutely, they could have. The numbers were crazy. There's always a banker willing to do it. The question is, which bankers and is it the right thing to do?
Speaker 2Do you worry that ads? No. First of all, there's not that many buyers like bending spoons, right? And so there's not
Speaker 1that many buyers there. So I don't. I think the companies, if they're at four or five hundred million, if they have the kind of revenue, the question is, are they going to continue having the revenue? If they haven't already integrated AI in a compelling way, I'm not optimistic about their future. At all. And if you don't have a really thoughtful AI strategy and a thoughtful AI product, I don't believe that you're going to have an opportunity to do much of anything with the
Speaker 2company in two years. Are we not seeing most of the SaaS generation put lipstick on the pig, so to speak? Oh, fuck, let's sprinkle some pixie dust in this. And now you've got an AI co-pilot.
Speaker 1Well, you know what? It's a good thing you mentioned that because we're in a new era now. We've gone to what I call the co-work era. Where it's really more agentic, where I mentioned autonomous agents. And I think to those few companies that have deployed autonomous agents successfully, co-work is becoming the new trend. And as co-work becomes more successful and more stable and more broadly used, I would be really concerned about SaaS companies that don't have some kind of system of record or some kind of AI strategy in place to succeed. Because the co-work era, the SaaS world, is just starting right now. But it's still early days. So you've got time to pivot. If you're a SaaS company, you've got time to do AI and bolt on AI and figure out some other direction. But if you're not doing that now, good luck. Good luck. If you're not doing that now,
Speaker 2dude, I look at PE today. And I like the PE model, but I'm looking at your Tom and Bravos of the world. And I'm just like, ouch. I really like Orlando, and he was great on the show. And I really, I want him to succeed. But fuck, that's a hard job you've got with your Cooper and your Ana plans of the world. Do we just have a vintage, which sucks, and we just get over it?
Speaker 1Well, you know, it's amazing. I mean, in 2001, TPG had a terrible fund and ventures like everybody did. They survived it because they had a whole lot of telecom investments that just evaporated. Forsman Little had a lot of telecom investments, and that led to the end of the firm, firm. It ended, died, no more, Forsman Little. So look, I suppose these PE firms that have challenging portfolios, they have time to do something about it now. But when and if a financial dislocation comes, that's the problem, because they're all levered up. The problem with the PE business is the leverage on the businesses. And if EBITDA drops, churn increases, and if it happens rapidly through a financial dislocation, and there's a margin call effectively on the debt, it's going to be tough. It's going to be really tough.
Speaker 2Dude, a lot of these assets are like four to six X levered. I mean, it's like, it's high.
Speaker 1Yeah, it's high. I mean, look at Leopold was only three and a half X levered, and he had to sell a lot of assets. I agree, it doesn't look good. But look, they have enough EBITDA today. And they have PE firms that know their survivals at stake. And the PE firms have time to come up with some strategies as long as the market stays up. You know, this is the point I was making that the global market is going to stay up. And the global market is going to stay up. Markets are critically important to what's going to happen into the tech sector, critically important. And if you have a dislocation, I think it was Tom Lee that called for a 10% decline or drawdown in the S&P this fall. If he's right, if it's any worse than that, I don't know how people handle it when assets deflate, and you're levered up. I don't
Speaker 2know how you handle that. You said that, like, you know, the 10% drawdown. And you said earlier about FIRE and embedding FIRE with the frontier models. Sam was like, hey, administration, take 5% of frontier models. Do you think the answer when you create FIRE is you have to be owned at least partly by the administration? Well, first of all, that's never happened in
Speaker 1the history of the United States until this current administration. So that's never been necessary. I don't see why it's necessary now. If you look at utilities providers in the UK,
Speaker 2you have your British Gas and British Telecoms. I know they're not now because they were sold and privatized. But, you know, you have your Royal Mail. Like, actually, the majority of utilities were state-owned. But look, I mean, you have a history of socialism
Speaker 1in European countries. Post-World War II, socialism has existed, and people have always supported that. And I do think there was a need for the governments to get involved because there wasn't the capital markets available to them like they were in the United States. Obviously, in the United States, there's been public-private collaboration. But Sam's already built the company to this size without needing... I mean, to give cell 5% to the government. So why does he need to do it now? I mean, it makes sense if like a Manhattan-style project, if we did that for AI 10 years ago, well, fine, you know, do it because it's strategically important to the country. But today, given the size of them, I think the only reason you do it is for political reasons.
Speaker 2Talking about strategically important for the country, do you think it's right that we have export controls on chips?
Speaker 1I think it's important that we think about how we're going to deal with our technology. We need to really have a strategy. I'm not a believer in sort of regulation for regulation's sake. Put it in the context. Give us a strategy. Let's publicize the strategy. Let's debate the strategy. Let's have people responsible for it. We don't need just some regulator to come out and
Speaker 2say, let's just do this. Do you worry about the dominance of Chinese open source models and the ability for backdoors to be introduced into their models? Or do you think this is grossly overestimated?
Speaker 1That's a really good question. The main thing about... The main thing about open source and Chinese models today is, one, all these models are not going to exist in 10 years. There's going to be completely different ones. So if there's backdoors today, they better do what they're going to do now because they're not going to exist in 10 years.
Speaker 2What do you mean by that? Like Kimmy won't be a dominant model in 10 years?
Speaker 1I mean, all the open source models that we're doing right now we're using, they won't be used. They'll be replaced by something else. First of all, within 10 years, I believe we... And I think some people are thinking two or three years. Continuous learning models will come into existence. That means that every generation of every model we have today dies, goes away.
Speaker 2Two things. What is a continuous learning model and why does that mean every generation dies for those that don't?
Speaker 1Because today, one of the most important goals of the model builders, particularly frontier model builders, is continuous learning so that it can do more complicated tasks. Just like humans, like in theory, we're continuous learning, but robots... The physical AI will need to have some ability that maintains its memory so it can continuously do complicated tasks and learn and deal with dynamic events that come into it. And so these models will be fundamentally different than the models that have been trained to date. And so continuous learning models will come in and once they're deployed, there'll be a whole new breed of open source models based on this new capability of continuous learning. And then... Those will evolve into what's called lifelong learning, which is truly more how human intelligence works. But those models, in my humble opinion, will replace every model that exists today.
Speaker 2Does continuous learning and potential lifelong learning not denigrate the value of frontier models?
Speaker 1Well, they're going to replace frontier models. I don't think you can bolt on continuous learning into an existing frontier model. I think they're going to try and the early stages will look like that. But I think ultimately, it'll cause... for a new form of architecture and completely new raining, right? When you train a model today, it's kind of static, dumb, it's trained, then you go out there in the world, right? And so continuous learning models, I think, will be architecturally
Speaker 2different. Would you have done SSI at 30 billion, Ilya's company, which is supposedly coming out with the first version of that continuous learning model end of August? I don't know him. And I don't
Speaker 1do model deals like that unless I know them or someone I trust knows them. So I can't say.
Speaker 2You said there about training being kind of a shot and done. I'm an ambassador in McCore. I think data itself is much harder than people give it credit for in terms of acquisition, cleaning, and deployment. How do you feel about data providing companies as a commodity or as a
Speaker 1valuable asset? Well, data keeps changing. So the thing about data is it's not static. There's, of course, value to context, right? Data gives you the context and memory, right? And so I do think that if you're an enterprise business, your data, the way you do it will be different than the way someone else, take hamburger companies, right? I mean, Shake Shack's data is going to be utilized differently than, say, Burger King will do it or McDonald's. And so I do think that there's going to be highly unique use cases for data that is really important. But you have to have a system where the data continues to evolve and change and the underlying utilization of it can change
Speaker 2as the data changes. I think I buy Lynn's thesis that you'll have specialized models, and part of the training for those models will require additional surplus data. And then you'll see the likes of McCaw go from purely selling to frontier models to selling to enterprises and even mid-market who need specialized data that they might not have. And that massively opens the TAM. That's the $200 billion opportunity. Right now, models are essentially task-driven
Speaker 1to a large degree. With models and frontier models are doing some levels of creativity, but we really went into deep creativity, like go solve climate change. You're going to need a diversity of intelligence. You think about board levels and you think about management teams. You need diversity of intelligence to be able to solve really difficult problems. And so the market is going to change from, let's just solve tasks and do it a great way. Let's do minimal creativity with writing and visual arts, to being, oh, we really need a lot of diversity. I think we're going to need a lot of diversity of intelligence to be creative enough to solve the problems that matter and the problems that we're going to get paid for.
Speaker 2I find everything that we talk about today so exciting. And then I just have one pullback in my mind, which is just a lot of wise people say you always overestimate what you can do in a year and underestimate what you can do in 10. Is that the case here? Am I massively getting ahead of myself when I think about a lot of what we've spoken about and actually calm
Speaker 1down, kiddo? It takes longer than you think. My feeling is, is that continuous learning, it feels like it's two to three years away. Maybe it's 10 years away. We don't know. I mean, we've been thinking we're on the cusp of solving cancer for the past 15 years. And we got a little bump with the new sort of drugs like Katruta to do cancer solving problems with the immune system, but we haven't solved cancer yet. We're managing it better, but we thought we'd be over by now and it hasn't happened. So I think I apply the same thinking to continuous learning models. We are getting a little bit of success with sample efficient models. Sample efficient models means when you just get a little bit of data, a small sample, and you can extrapolate enough beyond that to come up to be useful and to learn, you know, from that small sample. And so learning from small samples is starting to happen, but when they actually become robust enough to be useful, I don't know. And my feeling is these things take a breakthrough from where we are. And just like with cancer, we need more of a breakthrough. And the complexity that they're trying to solve is huge. So I'm not going to bet against them, but I would say what could send us into the valley of disillusionment is a combination of a global financial event and a failure for the models to continue to grow and evolve. And we're going to get to a place that if we don't solve sample efficient models and we don't solve continuous learning, we're going to feel like, hey, our inflated expectations are somehow not
Speaker 2being met. Jerry, I'd love to do a quick fire with you because I could talk to you all day. Who goes out first, OpenAI or Anthropic? It appears like Anthropic. Over or under, Nvidia will be a 10 trillion dollar company in five years? Over. Why is it so mispriced then right now? It's been flat for the last 12 months despite numbers going through the roof. I don't get it. I think it's
Speaker 1because the market doesn't go like a rocket ship forever. You're going to have these plateaus. And I think that there are areas of things not really accelerating as fast as you think it is. We don't know because right now there's these circular transactions that are obfuscating real growth in the market because the hyperscalers are sort of trying to get ahead of the game. But we don't know. You know, I mean, demand is going to have a lot to do with people having money in their pocket. And if you have a 10%, 15% dislocation in the markets, people are going to feel poor. And that's going to affect the credit markets. That's going to affect everything. That's going to affect demand. It always does. I can't believe I'm about to say this to you,
Speaker 2Jerry. But fuck it. We've known each other a while. In the UK, we have a game called Shag, Marry, Kill. Okay. I'm going to apply it to three companies. And the application is, Kill is short. Shag is buy quick, but you'll probably flip it. And Marry is you're in it for long term. You've got Meta, you've got Google, and you've got Microsoft.
Speaker 1I'm going to say because of the scale, I'm going to say long term for all of them. No, really? Here's why. When Meta's got 2 billion users with all their things, when Google's got 2 billion users with all their things, there's a kind of stability in that because consumers are really slow to accept new changes in things. So because of those two companies having such a substantial consumer business, and Microsoft's consumer business is good too, it kind of acts like a buffer, a stabilizer that gives them time to catch up. I mean, let's face it, all three of them have failed on the coding agent side, but I don't know if they're going to fail forever. I think you have to say this mass customer base gives them this incredible time to catch up with problems. And that's why they're going to be trillions of dollar companies for at least a decade. They're going to be as important as they are today. That's not the question you ask, but as an economic buyer, would I hold their stock for long term? Yeah, I would.
Speaker 2Even Microsoft, no model, relatively shitty AI products, you'd still be a buyer.
Speaker 1Yeah, here's why. They control communication for the global enterprises. Microsoft email, as dumb as it is, I mean, Exchange, whatever you want to call it, that's not going away. That thing is a money machine that cannot change. It cannot just disappear. By the way, what's really interesting, we talk about the speed of AI and stuff. They won't be able to control agent communication, but human communication, that's not going away. And they're going to be able to monetize that forever. You can't get rid of it. It's not like it's your cable system at home where you can say, fine, I don't need Infinity anymore. Get rid of it. You're not getting rid of Microsoft anytime soon. It's going to be around. Sadly, Facebook is the same. You're not going to get rid of it anytime soon. And these guys have built these kind of businesses because of the scale that supports their underlying business. And the consumer is, in my humble opinion, the thing that's keeping those companies afloat more than anything. You got a short one of the Mach 7, which you would be- Well, it would be meta. And it'd be meta because that's the one that may become boring. It may become like a telephone company. I mean, it'll just be this malaise, like owning a AT&T or something. That's what you kind of think about it.
Speaker 2So I push back. It's the largest ads business in the world. It's got WhatsApp and it's got Instagram.
Speaker 1Yeah. WhatsApp, I mean, again, they control human communication on WhatsApp in a very meaningful way. They haven't monetized it yet. But those users, they're going to find ways to keep the users. You got 2 billion plus, maybe there'll be 3 billion in five years. I don't know, be at half the world using your application. I'm sorry. That's something that's stable. That's a stable thing. I can say it won't be boring. It'll just generate dividends out to you. So as an economic buyer, you don't necessarily always need growth. You can take big fat dividends and just punch the coupon. At least for the next five years, it's going to be considered a safe haven. The Mach 7 is the Mach 7 because people say, hey, I'll put my money there. I might be underwater for a year or two or less of a return than I had. But long term, those things are going to be there and they're going to benefit with every positive cycle in the markets. Is Apple's AI strategy
Speaker 2unforgivable mistakes or is it genius patience waiting to see how a developing ecosystem plays
Speaker 1out? The answer to that is something that is going to be hard to know. We'd have to go sit down with Tim Cook now that he's retired. Maybe he'd tell us what is the culture around AI at Apple? How are they thinking about it? What are they doing in there? I know they're using Claude Code, huge, massive Claude Code customer, but how are they thinking about it? Did they have anything innovative to say? Have they been intelligent? watchful observers. or are they just dumb consumers? If they're consuming, sorry, they're in big trouble, they're going to suffer. But if they're watchful observers, and they've got something up their
Speaker 2sleeve, then we could be surprised by them. Which PE firm will navigate the next five years best?
Speaker 1Ooh, that's not fair. That's a tough question. I wouldn't want to make that bet. Which will navigate the worst? Well, I don't know who's worse, but my company Insight, they have a very small PE portfolio, very, very small. It almost doesn't even matter. So I think I feel the best about them long term, because they've been really intelligent about how they deploy the capital there. But the people that are all in on PE all the time, I just don't know about that. I think they're highly at risk to any kind of financial dislocation. Which venture
Speaker 2investor do you think has fared most well in the transition to an AI world? Good question. Well,
Speaker 1look, I mean, I think there's five or six firms that have just done phenomenal. The guys like Menlo that did Anthropic, how do you say early, but early enough, you know, they're gonna they're gonna do great. Benchmark, well, they missed Anthropic and OpenAI. They've done amazing with Factory and a bunch of other great ones that we've talked about. So I think, despite the fact that missing the big frontier models, they have a great portfolio. I think Coachla is also phenomenal. I mean, Vinod with Oven and you know, his companies are did amazing. I think Coachla is in that group. I mean, they're just gonna crush it. Coachla, Menlo and Benchmark have all just done amazing.
Speaker 2I have one final one for you. And this is kind of the beauty of what we do, I think, which is seeing the future, hopefully ahead. What seems crazy today that you think will be
Speaker 1quite obvious in five years time? Ah, that's easy. Blockchain for agent payments. Blockchain is in the valley of disillusion right now. It's like, it's really in a bad spot. I mean, IBM CEO came out and said, Bitcoin's at risk of being hacked in three to four years. Tom Lee came out and said, Bitcoin's at risk to be hacked in two years. Google said that Bitcoin's been hacked in two years. And that greed element of blockchain, which is exactly what the Bitcoin thing is all about, in my opinion, is about greed, you know, is bringing down the whole blockchain thing. Well, Solana and Ethereum, they're looking like they have a long term potential. And I do think that new things like Venice or Akinaki, or what Robinhood did with Robinhood chain, great, they got a billion in revenue, probably. Those innovations, whether you're tokenizing stocks, or you're going to do payment rails, or you're going to use blockchain for buying inference, like on Akinaki, or Gonca, those things are going to be real innovations. And people are going to be blown away that blockchain has found true utility, other than some supposed form of utility.
Speaker 2Jerry, I've absolutely loved having you on. No, seriously, I learned so much from you. I love what I do because of shows like this. So thank you so much for joining me. And you've been amazing, dude. Cheers. Take care. But before we leave you today, every great software company eventually runs into money. Uber had to move it. Shopify had to hold it. Airbnb had to settle it. Money movement stopped being a fintech problem. It became a software problem. And increasingly, God, it's an AI problem too. Zero hash is the infrastructure that makes global instant money movement seamless. One API integration for stable coins, digital assets, and modern payment rails. So builders can stay builders. Zero hash powers some of the world's largest enterprises and financial institutions, including Kalshi, Stripe, Morgan Stanley, Gusto, and interactive brokers. If you're thinking about stable coins, digital assets, and the future of money, it's time to talk to the team at Zero Hash. Visit zerohash.com slash 20VC to learn more. While Zero Hash powers on-chain money movement, MongoDB powers the data behind it. Every serious AI company right now has the same problem. Agents need accurate context fast. Most infrastructure, though, it wasn't built for it. Well, MongoDB is. Eleven Labs runs 40 million agents on MongoDB. Seventy-five percent of the Fortune 100 run their most critical apps on MongoDB. Trillions of dollars moving through MongoDB every single day. Instead of stitching together 10 different tools, you get one JSON-native database, vector search, and Voyage AI embeddings in the same system. And it runs anywhere. No lock-in. If you're building an AI, MongoDB for Startups helps you move faster with Atlas and Voyage AI credits and technical support to help you ship. Don't build agents that answer once and forget. Build agents that remember and learn from your real-time data. Go to mongodb.com slash agents. That's m-o-n-g-o-d-b dot com slash agents. While MongoDB scales the product, Framer scales the story. When a new landing page turns into a pile of tickets and handoffs, Framer helps your team move faster. Here's what I love. Framer is the pro AI website builder for creators, teams, and businesses that care enough to get every detail right. The agents close the gap between AI-generated ideas and production-ready website work. Because it all happens where the site actually lives. It lands on the canvas, stays editable, and can be published when the team is ready. So you can build custom code components, create and manage CMS content, optimize SEO settings, and ship everything all in one place. The agents bring speed and scale. You bring taste, judgment, and control. It's an enterprise-level solution too. Premium hosting, which is why the world's leading brands like Perplexity and Miro build in Framer. Learn how you can get more out of your site from a Framer specialist or get started by building for free today at framer.com slash 20VC for 30% off a Framer Pro annual plan. That's framer.com slash 20VC for 30% off. Framer.com slash 20VC. Rules and restrictions may apply.
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