The AI Bubble WILL Burst | Should we be fearful of Chinese Open-Source | Jerry Murdock

If there is a dislocation, no one is better prepared to survive it than hyperscalers. Let's take Neo Clouds: I think at least half of them go away within 36 months.

Jerry Murdock 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 cybersecurity threats of our lifetime. This and so much more.

Fireworks is making a lot more money than base 10. The more you customize the model, the more the token changes its value.

Ready to go?

Do you know what? I love my job. 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 Iran 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?

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 Lampstack, which led to a rolled out of websites, Google started taking off. 2008, cloud computing, very slow to take off.

And this is because there was, you know, these financial disruptions slow things down. The stream of commerce gets disrupted. Andright 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, can 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?

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?

Well, 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. And the reason I say thisright now is of 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.

What are the signs to you that we're seeing a cracking in the credit markets?

Well, 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? And what you had was, you know, a 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 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 problems associated with credit.

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, you know, the leverage that he put on his fund.

I still see that there's these 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. And 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 you just see, like, 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 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.

Can I ask you though, when 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 that'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.

I think you just saw that the free cash flow is the lowest it's ever been in the history of a company, number one. Number two, you know, back in the dot-com 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, you know, 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 here? They should not take out such levels of debt? Like, how do you expect this to play out?

Well, I mean, look, I mean, what 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 Neo Clouds. Neo Cloudsright 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 will go awayright away.

Can you help me understand that? I can't pass that over. What will separate the Neo Clouds that go away and become valueless versus those that retain value and become even more valuable?

That stains the question around which hedge 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. 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 Neo Cloud 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'd bet on Fireworks over base 10. Ten times better business, in my opinion, because they're more capital efficient.

That's purely based on the capital efficiency?

Capital efficiency and their willingness to make profits on business. I think Cursor was pretty smart in that 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 risk. You're absolutely at risk.

You mentioned Fireworks there. We had Lynn on the show. You had Lynn on the show, Amazing Founder, 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 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?

Well, 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 the early days of these models, it's all going to be about specialization and the ability to customize. What's happening is that you can't customize Anthropic models or OpenAI modelsright now.

Not the big frontier models. You're not allowed to do that. So that's just given an opening, I think, for

open source models to be tuned. As I mentioned on our last call, I thought that open source models and ASIC 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 of.

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, you know, haven't quite acted on that demand, the more it's like websites at first,right?

In the '90s, 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, you know, when we look at intelligence, the demand for it is going to be endless by endless numbers of people. And this is helping create the opportunity for open source and ASIC chips.

Totally 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 take the majority of easy?

That's a great question. I'm going to give you 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 as they, if they can execute against those goals over 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. Single digits, 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,right? 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. And so I think that's the way it's going to work. 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.

A 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?

I 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 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.

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 in a lot of cases.

Well, there's two things. So each model has, and as 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 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 talk 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,right? And a lot cheaper.

You can take your, if you only have a million dollars to spend, you could spend that million dollars on customization and getting specific tasks done a lot more efficiently than you can on a frontier model.

How does this not cannibalize frontier models business? I'm not one who wants to see the OpenAI and Anthropic challenge. They're thriving as good for all of us. But I don't understand how that doesn't cannibalize their business, making their town smaller.

But don't forget, we're talking about intelligence. Intelligence is, you want more of it all the time and you want different flavors of it,right? I mean, humans have emotional intelligence. They have, you know, 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, you know, 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 sort of Cambrian explosion of innovation followed by these sort of glacial periods 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 sort of complex and being able to do complex tasks.

When 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 moving to 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?

Well, 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 that. 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, you know? And yes, they've been giving their, I mean, Anthropic's been getting all this data and OpenAI already for years. So in some ways, the cat's out of the bag,right?

I mean, look, if you worry about from a security perspective, I mean, look, 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, Sacha 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 look, 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 OpenAI. 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, you know, 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 going 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 OpenAI and Hugging Face. Anthropic came out saying, hey, mea culpa, our models actually hacked three companies.

And it's almost like a brag now to have like a, do you know what I mean? Our models hacked companies. Thanks.

Yeah.

How do you think about the golden age of cyber that is to come?

Well, 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 so are they, and they're thinking, oh, I'll put it in the model in a 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 it in a sandbox. And that's why they've had a huge success with Docker sandboxes. That's why E2B is successful with 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.

When you think about investing today personally, do you want to do a lot more in security? Like 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?

Well, look, if you look at Fireworks and said, gee, I'm lucky I invest in Fireworks versus base 10 or CoreWeave or any of the other inference providers. Why? Because that team was the geniuses that understood Python the best.

PyTorch in particular. 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, you know? 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 a hundred different sandboxes with a hundred different libraries and then determine which is the best app,right? And what was all these different tools? That knowledge is in a handful of companies today.

And if you look at E2B 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 sandboxright, forget everything else.

I 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?

Early in a cycle with new technology, it's always a real estate game,right? I mean, 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 taking low margins or 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.

So 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.

Well, it's just a strategy. I would not invest in people that build a culture around that idea of low margin. Now, that's why I probably lost out on investing in Amazon because I just didn't, you know, I didn't buy into Bezos' idea that your margin is my opportunity.

In groceries and books and things, yeah, he'sright. And in compute, he wasright. He was absolutelyright. 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, you know, 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. And so again, innovation is what should be on your front of your mind. And that innovation better drive margin. So even if you don't have itright this minute, if you're not thinking about it, I won't invest in you.

You 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?

I said it last February. Look, ASICs chips are really ideal if you're thinking about model customization. If you're saying, look, we're at a new phase in this AI buildout where 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, sort of ASICs chips, is because they recognize that trend and they want to take advantage of it.

Do you need to own the chip layer as a model company stage, you think? When you see DeepSeek building their own chips, you see Anthropic now building their own jalapeno from OpenAI.

I'm not sure jalapeno is the best name. It bothers me.

You know, I love Mexican food. I love spicy food, but I don't know. I'm just not sure about that one.

That situation is called padron pepa.

Look, actually owning the chip is going the wrong way long term. Short term, it makes sense for larger companies because they want to optimize chip sets 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, well, 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 this 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, I think that's where the most compelling place I would focus on in investing is that level, which is, you know, from the loops to, you know, customization, multiple things, security, all of that stuff from the model out is where I think it's far more interesting.

Going back to the chips, eh, short term, I can see why people do it. Long term, I think it's unnecessary.

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 this?

Fund the guy who is the small startupright 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.

And 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 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.

You know, do something very specific. And by the way, this has been a lot of advice. 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.

Do 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 mean, like I'm investing every single day on the ground. I consistently have founders say, oh, you know, we're raising a hundred.

And I'm like, oh, wow, it's like how much are you raising? And they're like, we're raising a hundred. I'm like, that's the friends and family round. What the fuck? And like when I said to a founder the other day, we write $25 million 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 companies?

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. You know, I mean, and so if you're saying, I'm going to be a trillion dollar company, my opening round's a hundred million or something or even a billion, you know, whatever the valuation is, 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? And or are they just doing it because the market's doing it? And I would argue that it looks like Anthropic and OpenAI, those crazy mega rounds, you know, at a hundred 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? I think 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 to sort out those a little better.

Is 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 two billion if they hit end of year targets this year. Four years to two billion.

Jerry, do you remember when it was Slack, 18 months to 10 million and we were like, wow, wow.

I think in the case of Fireworks, look, they're benefiting because of OpenAI and Anthropic. They are the next level,right? 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 scaleright behind that. But if you're somebody else and like saying the app layer, I'm just not buying that. You know, I'm not buying it. I'm not buying it for the legal and I'm not buying it for the app layers yet.

But for infrastructure, absolutely.

But I get killed for this. I say publicly, triple, triple, double, double stat. Do 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?

You are glib sometimes, not all the time, butright now you are, yeah. I would argue that general statements don't apply here. You have to be highly specific. Look, if you look at Anthropic and you look at what they've done, Anthropic and OpenAI, 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,right? I mean, this is definitely on the level of inventing fire, you know, 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 followright 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, Neo Clouds. No way. I don't buy it. I think some, one or two of those Neo Clouds 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 burned as part of it.

Does the model routing layer carry enough value to you to be independent?

My opinion is OpenRouter 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 OpenRouter. And OpenRouter 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 mainnet. 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 OpenRouter type product where people that are hosting the models themselves will provide, you know, through an exchange, an easy way to acquire the inference. And the need for an OpenRouter type product is, and particularly paying the 5% markup for the inference will matter,right?

So because that's what those things do. And my humble opinion is that they're not necessary long term.

So if you were on the board of OpenRouter and the $10 billion acquisition comes through, what do you say?

You say, fuck yeah, this is great. You know, and like a lot of people, you know, you take the money when you can. And look, credit to OpenRouter, 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. I mean, that's a huge amount of money, by the way. And so I think that you're going to see a big disruption in that model in the next three, four, 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, get the inference you need without paying the 5% markup.

I 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.

Yeah.

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 Labs at a billion dollars pre for one person out of OpenAI.

What would you say to me?

Well, I think Bill's on the board of the Santa Fe Institute with me. I mean, 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, 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. And look for that and look for the fact that what they're going to do has impact if they do it.

When you review the founders you've worked with, where was that most obviously striking?

It's rare,right? Because you could say

all the founder-driven Mag 7 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. It's one of my companies. And A to B, the founder of Vignon, he's absolutely going to do it. There's no question in my mind.

Aavin, this guy came out of Meta as well, his name's Saadi Khan. But Uncle Oshus 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.

Do you think we see a compression in like liquidity timelines? We have Cursor scaling to 60 billion sale in four years.

Yeah.

Do we see actually venture cycles get shorter in this environment given companies 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 bid from Stripe, you take it.

I think those are not the norm. Those are the abnormal. 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 that I wish Flipboard had taken the billion dollar exit, but they didn't.

And you know.

What happened there? They had a billion dollar exit on the table.

Well, 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% of that number. And one of them was Twitter and the other one was TikTok, the founder of ByteDance. And founder, you know, 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 I think the board bought into The Coach's advice and they stayed with it. And now Flipboard, you don't care about it,right? You 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 a time to go and when it's a time not to go.

The one I love is one of my dear friends once said to me, you know, Harry, I've never regretted making millions of dollars. And I say this from my G650.

I always remember that. Can I ask you, we mentioned that obviously Cursor 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 Airtable 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?

No. I just think that we're at a moment in time where, you know, 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.

And so, you know, there's always a banker willing to do it. The question is, you know, which bankers and is it theright thing to do?

Do you worry that Airtable is the start of a much broader generational cohort that will be sold at a mega discount to last round?

No, I don't. First of all, there's not that many buyers like bending spoons,right? And so

there's not that many buyers there. So I don't, I think the companies, if they're at 400, 500 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, yeah, 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 company in two years.

I mean, 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 oh, now you've got an AI co-pilot and oh, there you go.

Right.

Well, 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 cowork era, where it's really more agentic, where we're, I mentioned autonomous agents. And I think to those few companies that have deployed autonomous agents successfully, cowork is becoming the new trend.

And as cowork becomes, you know, 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 cowork era, it begins the threat. So the threat to the SaaS world is just startingright now. But it's still early days. So if 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, dude, I look at P today and I like the P model, but I'm looking at your Tom and Bravos of the world and I'm just like, ouch. Like 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 Anna plans of the world.

Yeah.

Do we just have a vintage which sucks and we just get over it?

Well, you know, it's amazing. I mean, in 2001, TPG had a terrible fund and vintage like everybody did. They survived it because they had a whole lot of telecom investments that just evaporated. Horseman Little had a lot of telecom investments and that led to the end of the firm.

Firm ended, died, no more Horseman 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, you know, a margin call effectively on the debt, yeah, it's going to be tough.

It's going to be really tough.

Dude, a lot of these assets are like four to six X levered. I mean, it's like, it's high.

Yeah, 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 survival's at stake.

And the PE firms have time to come up with some strategies as long as the market stays up. I mean, you know, this is the point I was making that, you know, the global 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'sright, you know, and if it's any worse than that, I don't know how people handle when assets deflate and you've got, and you're levered up.

I don't know how you handle that.

You've said that like, you know, the 10% drawdown. And you said earlier about FHIR and inventing FHIR with the frontier models. Sam was like, hey, administration, take 5% of frontier models. Do you think the answer when you create FHIR is you have to be owned at least partly by the administration?

Well, first of all, that's never happened in the 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, you have your British Gas and your British Telecoms. I know they're not now, but because they were sold and privatized.

Yes.

But you know, you had your Royal Mail. Like actually the majority of utilities were state-owned.

But look, I mean, you have a history of socialism in European countries. Post World War II, socialism has existed and people have always supported that. And I do think there was a need for governments to get involved because there wasn't the capital markets available to them like they were in the United States.

And obviously in the United States, there's always, there's been public-private, you know, collaboration,right? But Sam's already built the company to this size without needing to give sell 5% to the government. So why does he need to do it now,right?

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.

Talking about strategically important for the country, do you think it'sright that we have export controls on chips?

I 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. You need to 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. You know, we don't need just some regulator to come out and say, 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?

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 open, 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.

What do you mean by that? Like Kimi won't be a dominant model in 10 years?

I mean, all the open source models that we're doingright 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, every model we have today dies, goes away.

Two things. What is a continuous learning model and why does that mean every generation dies for this?

Because it's a goal. Like today, one of the most important goals of the model builders, particularly frontier models, is continuous learning so that it can do more complicated tasks. Just like humans, like we're in theory, we're continuous learning, but robots, so 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 sort of 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.

Does continuous learning and potential lifelong learning not denigrate the value of frontier models?

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 in the early stages will look like that, but I think ultimately it'll call for a new form of architecture and completely new training,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 different ultimately.

Would you have done SSI at 30 billion, Ilya's company, which is supposedly coming out with the first version of their continuous learning model end of August?

I don't know him and I don't do model deals like that unless I know them or someone I trust knows them. So I can't say.

Got you. You said there about training being kind of a shot and done. I'm an investor in McCaw. 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 valuable asset?

Well, data keeps changing. So the thing about data is it's not static. And so, you know, there's of course value to context,right? Data gives you the context, the memory,right? And

I do think that if you're an enterprise business, your data, the way you do it,right, will be different than the way someone else. Take hamburger companies,right? I mean, Fitjack'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 as the data changes.

I think I buy Lin's thesis that you'll have specialized models for companies and part of the training for those models will require additional or 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 a $200 billion opportunity.

Right now, models are essentially task-driven to a large degree. With models, you know, and frontier models are doing some levels of creativity, but we really wanted to deep creativity like go solve climate change,right? 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 of intelligence to be creative enough to solve the problems that matter and the problems that we're going to get paid for.

I 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.

Right.

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 down, kiddo, it takes longer than you think.

My feeling 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,right?

And we got a little something. We got a little bump with

the new sort of drugs like Keytruda to do, you know, 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 that these things take a breakthrough from where we're 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 being met.

Jerry, I'd love to do a quick fire with you because I could talk to you all day, literally. Who goes out first, OpenAI or Anthropic?

It appears like Anthropic.

Over or under, Nvidia will be a $10 trillion company in five years?

Over.

Why is it so mispriced thenright 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 because the market doesn't go like a rocket ship forever. You're going to have these plateaus,right? And I think, you know, that there are areas of things not really accelerating as fast as you think it is.

We don't know becauseright 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.

At least short term.

I can't believe I'm about to say this to you, Jerry, but fuck it, we've known each other a while. In the UK, we have a game called Shag, Marry, Kill, okay? And 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 the long term. You've got Meta, you've got Google, and you've got Microsoft.

Because of the scale, I'm going to say long term for all of them.

No.

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, they're really slow to accept new changes and 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 stability, 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, in my humble opinion. They may not be as important as they are today.

That's not the question you asked, but as an economic buyer, would I hold their stock for long term? Yeah, I would.

Even Microsoft with a no model, relatively shitty AI products, it'd still be a buy.

Yeah, 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.

It controls, by the way, you know, what's really interesting, we talk about the speed of AI and stuff. They won't be able to control Asian 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, you know, your cable system at home. You can say, fine, I don't need Infinity anymore. Get rid of it. You're not getting rid of Microsoft 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 Mag 7, which would you be?

Well, it would be Meta. It would be Meta. And it would be Meta because that's the one that may become boring. It may become like a telephone company, you know? I mean, it'll just be this malaise like owning an AT&T or something, you know?

That's what you kind of think about it. Whereas I think.

Even when you mean the largest, so I push back, it's the largest ads business in the world. It's got WhatsApp and it's got Instagram.

Yeah, 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 they'll be 3 billion in five years.

I don't know. We got half the world using your application. I'm sorry. That's something that's stable. That's a stable thing. I can't say it might be boring. They'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, you know, punch the coupon. At least for the next five years, it's going to be considered a safe haven,right? The Mag 7 is the Mag 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, you know, with every, you know, positive cycle in the markets.

Is Apple's AI strategy unforgivable mistakes or is it genius patience waiting to see how a developing ecosystem plays out?

The answer to that is something that it's 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? You know, I know they're using Claude Code, huge, massive Claude Code customer, but how are they thinking about it? Do 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 sleeve, then we could be surprised by them.

Which PE firm will navigate the next five years best?

That's not fair. That's a tough question. I mean, I'd have to look at the portfolios to see it. 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, anything.

Which venture investor do you think has fared most well in the transition to an AI world?

Oh, good question. Well, look, I mean, I think there's five or six firms that have just done phenomenal. You know,

the guys like Menlo that did Anthropic, how do you say early, but early enough, you know, they're going to do great. I think Benchmark, while they missed Anthropic and OpenAI, they've done amazing with, you know, Factory and a bunch of other great ones that we've talked about.

So I think despite the fact they're missing the big frontier models, they have a great portfolio. I think Košla is also phenomenal. I mean, Vinod with Aavin and, you know, his companies there did amazing. So I think Košla is in that group of, I mean, they're just going to crush it.

Košla, Menlo, and Benchmark have all just done amazing.

I 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 quite obvious in five years' time?

Blockchain for agent payments. Blockchain is in the valley of disillusionright now. 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 Lean came out and said, Bitcoin's at risk to be hacked in two years.

Google said that Bitcoin's being hacked in two years. And that greed element of blockchain, which is exactly what the Bitcoin thing is all about, in my humble opinion, is about greed, bringing down the whole blockchain thing. While 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 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.

Jerry, 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.