20VC: Micron Will Be More Valuable Than Meta | How Export Controls Helped Not Hurt China | Power is the Bottleneck to AI | Why Dario Has Done a Disservice to AI with his Labour Replacement Messaging with Aravind Srinivas, Founder @ Perplexity

I have nothing to lose. I came from nothing. I never even imagined my slip to be doing all this. A $20 billion company. 45 million users. Over a billion searches a month. Built in three years by 400 people. These numbers, like, doesn't motivate me. It's hard to get motivated by well. You want to get motivated by impact. This is perplexity with no founder and CEO, Aerovin Shrinivas. No one's ever in a comfortable position that no one can relax. They forced Google to redesign their homepage. Then bid $34 billion to buy Chrome. More than their own valuation. Complexity changed Google.com more than any product manager of Google has ever done. Now you look at AI mode. It looks exactly like perplexity. He doesn't do defense. He doesn't do comfortable. His words attack attack attack. That's my motto. Go all in and try your best. Be on the offence all the time. Aerovin, that perplexity has done many shows. This is the single best podcast he has ever done. You know what I hate with podcasts when people sit on the fence? Aerovin has really strong opinions in the show's day. He says that Mike from will be more valuable than matter. He says that the resistance today, say to centers will continue and get worse. He says the biggest problem today is the lack of power. He claims that perplexity has changed Google more than any Google PM. You want opinions? This is the show for you. Aerovin was on stellar form today and this was such a joy to do. But before we dive into the show today, if you're a finance professional, you know the month and nightmare chasing down missing receipts and fighting without dated tools that your employees hate using. It's time to enter the era of Navan. Navan is an AI-powered travel and expense platform that gives you control and real time visibility into every dollar spent. The experience is seamless for employees too. They can book a trip in just seven minutes, which is a fraction of the 45 minute industry average. 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That's V-A-N-T-A.com/20VC for $1,000 off. You have now arrived at your destination. Arab indeed. I am so excited that we get to see this. We've done one remote. And then we did one at Founders Forum last year. So thank you so much for joining me in person. Thanks, Laura Harry. It's a weird start, but just roll with me on it. I asked this as the best founders that I meet. Are you motivated more by the fear of failing or by the thrill of winning? - Thrill of winning. - Why? Because I have nothing to lose. I came from nothing. Like, I never even imagined my slip to be doing all this. So my life has already been extraordinary. Beyond any level of imagination. I was just an India like doing my undergrad and just training neural nets with graphics cards that people in the labs were using for playing video games. It was all for fun. My path led me all over here. For my mom, just getting a job was success because we were financially lower middle class in India, which is not even like lower middle class in UK or the US. And so from there, all we wanted to do was get a job in Google. Being an engineer at Google was considered a win. And so I'm already doing remarkably well compared to that. Ambition we had as a family. So there's really nothing for me to lose. That's why anytime I try to act like I'm trying to avoid failure and being on the defense. I remind myself that like that's the stupidest thing to do. It's better go all in and try your best. Attack, attack, attack. That's my motto. When you review then, what are you not being aggressive enough on today? Well, I think today, maybe in the early days, we'd be very, very loud on social media talking about reflexes. It was Google and I used to do that myself a lot. And some people don't like me for having done that. Today, I'm a lot more measured in how I talk about our products, competitors and stuff like that. But it's not a lack of aggression or anything. It's just that like that is boring. People already heard that enough for me. Do you regret being so bold in your messaging? No. So it's not a nuance and maturation of message. It's not style and I need something new. Not just that I kind of don't think it's a relevant framing anymore. We worked on search for Plexity started out of search. We built the first answer engine in the world that people know perplexity even today. If you mentioned the name perplexity people will think, oh, that's an answer engine. We built a lot more things after that. We built a lot of agents, browser agents, deep research, computer. We built so many products after that, but we're still known for that first product. The mark has already been made. We changed the roadmap of Google. You could argue that I or the company perplexity changed Google.com more than any product manager at Google has ever done. Made that argument for me. Well, nobody ever wanted to ship an answer engine at Google. Nobody wanted to tinker anything on the interface that made them $250 billion a year. And then now you look at AI mode. There's not even any difference like the font, the citations, the specific building of inline text, inline hyperlinks, suggested follow-ups. The whole experience is literally looking like perplexity, except it's still not as good. It's not bad or good for you that they learn from you and adapt. It's both good and bad in the sense. I knew this like around end of 2024, this is going to happen. So it never caught me by surprise at all. It was just a matter of time. I still am surprised that the quality is still not there, because I regularly test every product out there. But I'm happy that honestly, they changed Google to be what it should be. I believe that the frontier is where the money is. The frontier in AI is not about answering questions anymore. It's about actually going and doing work for you. You know, like we still have the state of the art deep research in the world. And that's actually where people are subscribed to pay for our pro or max products. It's not for getting answers in the traditional way. They're asking for sophisticated research reports. They're asking for agents that go and do things for you. And so we wouldn't have been able to do all that. If we were sitting in 2024 thinking we have everything settled here. We're we're good and comfortable. No, the answer engine was always a lead gen for the frontier products we built. You need something right? Like think about it. Every company needs to have one successful product to build the next set of products in AI. Nobody can sit comfortably thinking they have it all sorted out, including anthropic. If anthropic things, quad code is already a bin in six or 12 months from now. They won't even be around. It's an uncomfortable fact about the whole field. Would you argue today? You just told me if you don't mind me coding you here before we started that you think open AI isn't ready for an IPO. Would you have believed you would be in a position to say this two years ago when nobody had wanted to deal with any product other than chat GPT? Think about it. So anyone even in such a massive advantageous position can be put in a position where they're no longer the kings. They're fighting from behind. That's the state of the field. It's less about perplexity or anthropic or open AI and not having modes or having modes. Can I push back on you that? Yeah. I would stand by it two years ago even when they were a dormant and they asked are the dominant consumer products. But I would stand by it because I don't think they are financially ready. When you look at the balance sheet of that. Maybe I'll decouple that. I'll decouple that. Let's decouple that being like financial readiness for an IPO versus perception of a dominant leader. Yeah. Do you perceive them as a dominant leader right now? Yes. In what consumer search? Well, except there's no money there, right? It's been commoditized. Like, for example, why are they going all in on codex? Because that's where the money is. We're doing the same on computer and tropics doing the same on cloud code. Google doesn't yet have a product in this category, but I'm sure they're going to come after that. Meta is trying to launch hatch for $200 a month. You see what's happening, right? But there has to be more money than just code codex. It's not about code. That's the main thing. The money, at least in non advertising. I'm not talking about advertising revenue in non advertising subscription or use such based revenue. The money is in whatever is the frontier. Today the frontier is about going out there and doing things for you. Do you not think then that there will be a $100 to $200 billion advertising business for open AI? You have to be proven. Let's work through the categories of advertising. Who's the number one advertiser on Google Amazon? It's the number two booking.com number three or four. I think six p.d. So how much do you think booking.com spends on Google 16 billion something like that. Some crazy amount like that. How do you book your hotels or flights today? Do you book it on chat GP or do you book it on Google? Google. Why is that discovery? I would like to see the options. Exactly. Right. So the interface is less about conversations and more about exploration. So when the decision making is more subjective and vibes based, you don't need an objective answer engine. And you think about the other category of advertising direct consumer products, fashion, whereas most of that advertising budget going into it's going to meta Instagram because you're just browsing your just like doom scrolling or whatever you call it. Right. And so the chat interface doesn't capture that user intent, that user behavior right now, which is why it was never a great fit for advertising. It also fundamentally corrupts the trust that people have when they go into a product and they want the accurate answer, which is what you know, perplexity is known for. And then you're like, Hey, by the way, you asked for the best protein shake, but by the way, these are good protein shakes. If you can check out it kind of like hurts the trust that people have in your platform, in your product. That's another reason why if you think about it, like, like what meta or like, I think some other companies in the past have tried to put ads inside messaging apps and emails and it's never really worked out. It works out in China in we chat because there's no other way for them to fund the whole thing. So the whole economy and user behavior has been optimized around gameifying. It's not how things work in America. So I am bearish on advertising to really take off in the chat interface. I'm happy to be proven wrong there, but I'm bearish on that. There are two hours that I want to unpack that the first and just taking kind of chronologically and how you said them, the money's in the front here. The more I hear this kind of the more I question it because I think that we dramatically overestimate how important frontier models are to do quite basic work. Yeah. So frontier doesn't mean a frontier model. Frontier just means whatever is the frontier outcome you can have right now, the AI. The Greg Brockman recently tweeted the models no longer the product. And it's funny because you know that as a leader of a frontier lab, he has all incentive to say the model is the product. And that's what Google people tell. I think one of the Google people keeps waiting that model is the product. And so the reason Greg's right is because if you take code X or perplexity computer or a clot code, what is that? It's an orchestration system. It takes a model pairs it with an agent harness. And what is an agent harness? Think of it. The simplest way of describing it is like rules for how the agent loop should run. What are all the skills and sub agents and connectors and tools and accesses? Without the harness, you don't necessarily capture and convert the intrinsic intelligence in the model into valuable output tokens. The output tokens, if you're, if you're literally just a reseller of model tokens, you have no business because the model will get commoditized. So even if you're a model builder, you don't have a business as an infer layer, you have some business on serving those output tokens. But as an application layer or a model builder, you don't really have a business. If you're just a reseller of tokens that come directly out of the model, you have business. If you know how to take the model grounded and valuable context, orchestrated with a really good agent harness connected to the right set of tools and connectors, whether it's personal connectors of business connectors and provide the experience to people in one single unified system. The way we differentiate ourselves at perplexity is we don't just orchestrate across tools and files and connectors. We also orchestrate across models. That is the differentiation that anthropic and open AI cannot claim because you wouldn't find GPT 5.5 inside the clawed code harness. You wouldn't find clawed Opus 47 or eight inside the code X harness. These are competing with each other. You would find both these models inside the Lexi computer. That way we can increase the token value per watt per user. If you assume that whatever decides the dot, like the price, the dollars is the power watts fundamentally. That's the thing that nobody else can subsidize other than the government. You know that whoever provides the most valuable output tokens with the least amount of power, expanded to produce them generates the greatest value to the end user and has the most pricing power has the most value. And so that is the orchestration problem to solve. The most important metric in AI is token value for what per user. What does it mean for the value of open AI and anthropic if model is not the product and it becomes a utility something you can switch into and switch out. Interface. Everyone thinks we're all building the model layer or the race. We're not actually. I would even argue that building models is a way to stay at the frontier, but you have to own an interface in which valuable AI output tokens are generated. The most valuable tokens. It doesn't have to be the product. This is a single most important thing to like unlearn for most founders. And I had to do it too, which is to be successful in AI product layer, whether you're a model builder or not. It's not about building something that gets a billion users. That mentality has to completely shift. There are a few power users who are propelling this token economy right now. If you look at like all these crazy stories of how there's this one engineer who got Amazon spent like half a billion dollars in a month because of some stupid way they set up like agent loop and cyclo code. Okay, maybe that's a mistake, but there are real engineers in matter in other companies spending like 10 million a year per engineer on these coding tools. There are users in perplexity computer. There's one user, I think, who spends upwards of like $10,000 a month, something like that. Crazy. And not like basting it. They're not wasting money. Their business runs using agent loops that are running inside these harnesses. And they use these products in sophisticated ways that I couldn't even conceive when we were building the product ourselves. Even internally, instead our own company, there are some people who've set up this kind of like multi agent hierarchy and agent loops that looks like it's own software architecture. And I often just asked these guys to come explain to the rest of the company, Hey, like what are you doing with these tools? Like you clearly are consuming it way over, you know, what we thought and the average person the company would do. And single biggest differentiation between those who use agents a lot and those who don't is whether they run repetitive cron jobs, whether you use AIs as one of tasks, you just delegate a task and then it gets done. That's like kind of using it for a deep research or like whatever, like one single task versus the AIs like continuously monitoring something for you. The AIs continuously like triggering based on certain events and going and doing certain things, giving you alerts. You set up workflows that keep running for all the time. Every time you get an inbound email, like, or every time there's a latency spike, it has to identify which part of the code base costs that it has to go and do the root cause analysis. And then identify the right engineer. All these things, this is where the frontier is. And so going back to my main point, these products are not going to be used by, you know, 100 million people, but they will generate revenue that's going to be higher than the advertising revenue of Google or matter. It's going to happen. I do just want to focus in on a specific element that when you were saying like the power uses because I think one of the core numbers is actually not many of them said they've been 300 million on anthropic, which was not to be about. Yeah. It'll be interesting to know from him if that 300 million came from, you know, what is a distribution of crossing plays? So it works out to be a cell was on developers within Salesforce. So it's about 3.8% of developers salaries. What percent of developer salaries do you think will be spent on tokens in 24 months time? Because that fundamentally changes the value of open air and anthropic. If it stays at 3.8%, they will not be $5 trillion in companies. But if it's 100% like Brandon at McCourse, that it will be in a year, they will be 10 trillion dollar companies. Well, I think they can certainly be 10 trillion dollar companies, whether it's going to be a full percent of the developer payroll today or not, because there's a lot of non-developer work that'll also be done with agents. And that's actually what we focus on for complexity computer. We're not going after the developer market. We're going after anything that non-developers do basically your finance department or your corb dev or your like sales reps or your data science teams. That's actually even bigger market. Like think of it as like cloud code multiplied by 10. That's the size of that market. If I push your developer salary spend, what percent of tokens spend as a portion of salary, do you think we'll see in 24 months? It's hard to say. I think the costs are going to go down. That's why it's hard to say. You think the cost will go down because this is the kind of the challenge that we've had. We thought when we went from chat to agent that costs will go down and token costs will go down. They've gone up. Yeah, for now. Help me understand that and how that changes. I think in software, you kind of want to pay for the frontier. It's kind of like if you know some engineer is awesome. If you know you have like on the next chapter, would you rather hire that person? and not hire people who are medium engineers, but not Jeff Dean level. With the same amount of budget you have, yes. Let's say you had a million dollars. You could hire five people, worth 200K, or you could hire one Jeff Dean and pay them a million. What would you do? - One Jeff Dean. - Yeah. So I think you would pay for the frontier, but what stays frontier keeps changing? In 12 months from now, let's say, thought experiment, there is an open source model as good as Opus 48. You still have to pay for inference. Nothing is truly free, but it's gonna be like, let's say, 10 times cheaper than Opus 48. And when you pair it with the right agent harness and all the connectors get up everything, all your developer workflows work fine. Why would you assume that the token span is gonna be still high? It's not gonna be for the same things you're doing today. It's not gonna be. But there might be a different set of things you might do with the frontier that you're not conceiving today. My prediction would be agents that are like completely autonomous software engineers. Today, I think we're all using tools like Cloud Code or Code X to write code, but not as literal software engineers. There is a large way that people that is now barish on your frontier models who open eyes in your anthropics because they're realizing that you can actually do a lot with open models for a fraction of the price. What you're saying is actually, that is true, but we will still pay for the frontier and so they will still accrue great value. That's right. And I think this distinction, it feels like a contradiction. It's not though. It feels like two things cannot be true simultaneously, but that's not quite the case. In fact, I would argue that the frontier is increasingly gonna be a thing that very few individuals might even want. Like you could argue that after a point, like it's not even interesting that they ask in rate software, you've normalized it, right? Let's say that's gonna be the case. Instead of companies being built with like tens of thousands of software engineers unlike the past, there'll be a lot more companies with smaller software teams than each of us will be using a lot of AIs. That's actually good for the world. We'll be seeing a lot of different businesses. We'll be seeing allocation of software labor in places that was never even possible. Whatever's the frontier is gonna be things that AIs going and designing chips, AIs designing drugs, AIs figuring out how to build robots, AIs figuring out how to cure cancer. These are applications where you don't have like 10 million users. It's like a few companies, but the effect of that work will touch a lot of human lives. I think to me that that's where the frontier is headed. You could also see that from the moves that frontier labs are making, anthropic, bot of a web lab, could be for the talent, could be for the infrastructure to run like web lab experiments, but imagine taking all those tokens and putting it in the mid-training instead of just tokens from GitHub. So then that's gonna produce something interesting. Turn off, is there an asymptote to frontier problems to be solved? I know that sounds ridiculous, but if you are continuously on the chase for the next frontier problem, you get to cancer, you get to climate change. And my word, I hope they solve both and like, haven't that's a huge amount to solve? But if you're on the treadmill of continuously solving, is there an asymptote to that? - Well, there's no mathematical argument to there being a cap on the amount of economic value one can create with AGI or ASI like systems. And Elon has a good argument for this. Like he very says money loses all meaning in a post AGI economy because you be producing an abundance of energy and labor and fundamentally the economy is grounded to energy and labor if you can produce an abundance of them about what meaning does money have. And so I don't think we run out of things to solve at the frontier. I think we're always gonna be creating like, like why did people even want to understand the universe? Like, like, why did we want to understand subatomic particles, quantum physics, black whole theory, you know, the origins of the universe? Like what is the purpose? But we still went ahead and did it because that's kind of what the purpose of humanity has always been to understand the unknown. You know, David Dawesch's famous for saying this, right? Like we are the only species capable of being curious about what is already familiar. Like you can stare at a fruit and you know that it's a mango and like you know exactly like how it tastes. You know how it looks, you know the shape. You know what seasons it grows and stuff. But you can still look at it and ask one more question about it that you haven't asked before. Other animal species cannot. Once they have it in their mental model, what it looks like and touches and feels like, they're gonna ignore it. It's not so long and interesting to them. - Can I see you mentioned about agent usage and you said if you do repetitive task first as one off say, cron jobs, I think some of them said it's we're gonna have 24/7 AI and they've talked about a hardware product that's gonna come out. Do you think we will have continuous agents running? - Yeah, I think so. And I think that's kind of why I believe the orchestration problem I talked about maximizing the token value. - Can you just help me answer, sorry when you say the orchestration problem? - Yeah, so okay, so there are like four objectives, intelligence and accuracy and then privacy and cost. You know these are all competing with each other. So you can argue that you could max out on intelligence and accuracy by building giant, giant data centers and spending a lot of power to you know run them and you could miss out on privacy and cost because everything will be centralized and you're gonna be paying a lot. You could argue that everything can run locally and so that'll be good for privacy and cost but may not be frontier intelligence, may not be frontier accuracy. The solution is to figure out a sweet spot, you know, use local models when necessary, use server side models when necessary and orchestrate across local models and server side models, ground in invaluable personal context. Sometimes the intelligence might already be there but the system might not work because the harness isn't grounded in the right set of tools. So build a world class harness that can even make an okay-ish model appear great and be able to use the right model for the right task and the right part of the task sub agents and even like utilize the compute we all have in our own devices all that, you know, doesn't need to be always on a server. That is an orchestration problem, a router, an awesome router, a master orchestrator router. Now if you do that, you can realize the vision of a 24/7 AI. We thought people freaking out about going bankrupt because no one's gonna be able to afford a 24/7 AI from TRII running on the server. Imagine you turn it on and you could never switch it off unless something crazy happened. The thing that most people worry about those AI is like, oh, what if it does something crazy? But the real concern actually is the cost. Nobody's gonna be able to afford a cron job at the fidelity of few seconds that runs all the time. The bottleneck there is actually orchestration and local compute. And so I believe one needs to build a continuously learning local model that can save you on like compaction, context windows and try to preserve as much compute locally and rely on the server side frontier only necessary and keeps learning, keeps adapting, keeps evolving. And that model is not just a model, it's a model plus the harness, plus the local chip and the compute and the ecosystem of devices that controls. That system is gonna be your own intelligence. Essentially the data center moved to your local device and you get to control it, you don't get to worry about somebody like spying on you or looking at all your tokens, very valuable personal tokens. Imagine you have like very sensitive deal materials. Let's say you're doing a deal and then a frontier lab has all your tokens that you used to like write a memo. Imagine somebody could hack into that server and steal your deal from you. You wouldn't want that, right? I'm gonna be honest, it's much more valuable things to people to steal from. (laughing) - And London pays me see. But yes, I can feel you. - I mean, you're not just yet not a London VC, you've had like 400 million dollars fund last time we read it. So imagine like you're already making your moves for the $4 billion fund. - Everyone has certain levels of like sensitive stuff and so I think that's where I believe that the 24/7, always on agent, is gonna be realized by the company that wants to play the role of the orchestrator, not the model builder, not the frontier model builder but the orchestrator. And I think that's what we wanna do. Computers has been positioned explicitly as the agent orchestrator, the musicians in the orchestra are these sub agents that utilize these different models, think of them as the instruments and the tools, the connectors, the models, these are all the instruments and the musicians are the sub agents and the symphony is the work and the system is the orchestra and computer is the orchestra conductor. That's how it's been positioned. So what it orchestrates keeps evolving, right? It changes, it changes from you know, models to files to tools, the chips to devices but it doesn't even matter like you don't care as long as it orchestrates things correctly and maximizes the token value for what for user. If you can solve this problem, you will capture the most economic value in AI, long term. Short term it might look like, oh like this lot of labs revenue is growing, you know, exponentially this that but long term this is the one objective that truly matters. Who is best positioned to do that? I believe it's us because you have the incentive of not token maxing, you have the incentive of delivering the most value to the user. Every time any part of the AI stack improves, our product improves since the beginning of the year and tropics models have made tremendous progress but what's also true is that our revenue has more than triple since the beginning of the year. Triple since this beginning of the year and a lot of tanks to model progress made by Anthropic and we also brought our burn down tanks to open AI competing with them and bringing down the cost of the same capability. And now with progress in open source and local models and local chips, we're gonna move some of the inference back to the local devices and bring down the cost even more. Every time any part of the AI stack where there is chips, models, harnesses, any of these gets better, our system improves tremendously and if our system improves tremendously, our users love it and they pay more, they spend more and so our business grows. To your question of who's best positioned winning that world for that. objective of being an orchestrator is the one whose product or business benefits from other people's progress at any layer of the stack. If Jensen produces a better chip, it's great for us. If Darry produces a better model, it's great for us. If Apple produces a better device, it's great for us. And I love the fact that we are able to be a very positive player at every layer of the stack and not have to rely on any one person to win. When we look at the different providers that we set to serve as our devices on device, when we look at the service site, a lot of people who want an AI infrastructure bubble, which is a funny stupid and moronic, to what extent do we have a data center supply problem today from what you see? I think the biggest problem is actually in power. So let's break down. What is a data center? Is it like you just buy a bunch of chips from Dell or Super Micro? No, that's just one part of it. You actually have to go secure land or you have to lease something, lease a property. You have to buy a bunch of turbines to generate power or you have to work with like power suppliers, grid suppliers. You also have to work on cooling. There's a lot of other work you got to put in that is far, far slower. You have to get permits to do all these things. And so usually what's happening is there's a lot of lead time doing this. And the models that are already in use today, these have been trained in the hopper generation. So the black will generation model, I think the first model that's black will generation category is mitos and it's already scary that people are already like freaking out about it. So imagine that everyone pre-trains a model on like a million or like hundreds of thousands of black walls. Now those models are going to be far more powerful than what exists today. And then the very rubens are coming next year in full capacity. Like like all the data centers of error rubens will be in next, you know, used next year. That model will be even more powerful. So I think there is a certain physical build out time that always bottle next frontier capabilities. That's why there's a value in that layer whoever knows how to do this puts together a bunch of GPUs and chips and networking and power and cooling and actually like orchestrating all this software layer on top and is able to convert that into frontier output tokens. That vertical integration has a lot of value. So that's why the markets are pricing infrastructure companies with a higher P.E. ratio than companies like Meta for example, even though Meta bulls a lot of inferrors is valued as a software company. When we see like you know, matters capat expand and it wanting to increase the last few days and think about raising more and more money to increase capat expand. I get it with a lot of the AI providers that you're open as you're on through office because they are making money from the AI products. For matter, the capat expand correlates to increasing accuracy on ads, which is like a six to eight percent bump in revenue. I get it. But for the capat expand, it doesn't make sense. Yeah. Well, I believe like they are understanding what the market's saying. You know, they don't think they're dumb. Do not see what's being said. I think they're introducing a lot of subscription products. Basically the company needs to not just be a social platform, maximizing engagement and turning that into ad revenue. And I think that requires them to launch a lot of like agents subscription based products and maybe even a medical out that that runs out sort of risk like what Elon's doing at SpaceX. And maybe once they do that, the narrative might change. But to go back to my point, it might not be inconceivable that micron, the supplier of HBMs might be more valuable than Meta in the next six to 12 months. It's already like a trillion and Meta is like 1.3 to 1.4 trillion. Can you help me understand that because memories are already a massive bottleneck. It's increased 5X in price in terms of the cogs, right? But people are going, wow, micron is fully priced at this point. Why is it not fully priced? Because it's still the bottleneck. Whatever is the bottleneck will command the price. AMD is doing really well because CPUs became a bottleneck again. Agent loops, agent harnesses are all running on CPUs. The tokens are produced by the frontier models on GPUs, but whatever work, let's say like claw generates a coding script that decides to download 500 files from different websites and then you know, munges a lot of data and transforms it into certain ways and generates a plot and then host it on a website that you can share with your people. All that compute is running on CPUs. Agents are using CPUs more than humans. And so suddenly there's a rise in enterprise CPUs and the beneficiaries of these are like Intel and AMD. So then they get to be the bottleneck. Like whoever's going to be the bottleneck will win. And so infer is the bottleneck right now because there's a lot of demand and we just don't have the supply. And so whoever supplies memory, SSDs, storage, CPU compute, suddenly these are all like interesting. Like they're more important than companies that are just building data centers and not knowing how to turn that into a valuable output. Do you believe your nebias and your core waves will be a sustainable multi hundred billion dollar company in the future or is it solely a short time supply problem? I certainly think they can be sustainable. Yeah. I think there are some I don't like look I don't know particularly which of those is going to win. And there's also other players like Crusoe and Firebird and there's a bunch of companies. It's all about being resourceful. You got to take power from areas where there's a lot of natural resources and the cost to bring up the data centers is pretty cheap and the time to bring up the data centers cheap. And yes, service is reliable. Like if somebody commits the buying hundred thousand GPUs from you, the service should be pretty good and you should be able to secure the supply ahead of time plan well. And I think some companies are even innovating on the power layer generating their own power is one way to bring down the margins. And so I think there's certainly like a value in that layer because it's hard to replicate work. That's how I say it. You could argue that opening I can do all the work that core V was doing. And that's kind of what they wanted to do with Stargate. But why is core V more successful at building data centers than opening I thought to do and operation the intense operation intensive. You got to focus. You got to like spend most of your time securing permits like figuring out power figuring out like bottlenecks and the supply chain here and there and constantly plan ahead and like test all these systems carefully deal with like random physical issues that you know arise in like you know running a data center. There's something called TCO you know cost of operations. You got a factor that in. So that said I don't think there's value if you're just like a server renter. If you're just a GPU server rack renter. If you're just leasing it to different companies on certain hourly pricing rates. There's not a lot of value. You have to actually build some software on top kind of like how AWS did it's called Amazon web services not Amazon servers right. You have to have some software orchestration on top that allows you to get software margins on top of what you're doing. I think that's why you're seeing moves like NBS like going for the AI model inference. You know taking open source models or hosting your models. That's a business model of certain other companies like fireworks and you know based in and all that. But you could imagine NeoCloud just going for that business. That was exactly me my question. So I just had the co founder of NABIS on the show and the really clear takeaway was the challenge that he has which is there's a huge amount of money that wants just capacity and compute with the awareness that he needs to build a full start product. If you want to have a long time sustainable business. Yeah. That was a core realization for me. When I look at the inference layer like you said fireworks or base 10. How do you think that plays out? Do we have standalone 100 billion dollar companies in inference alone or do we see that? It's all about working backwards. Like what does it take to build a 100 billion dollar company? 10 billion in revenue. Exactly. 10 billion revenue 30 to 40 percent growth margins. Good amount of net income. Good cash okay 10 billion in revenue is not that inconceivable for a company that can both do AI hosted inference and server capacity and data center buildouts very operationally well. You know there are some factors beyond their control like open source models continuing to be awesome. If open source models stop to actually be good. Where the gap between them the frontier is like more than 12 months like 15 months 18 months. Then I don't think these companies really have a business model because they're only going to be able to rent capacity to open air and drop it. That's exactly what Romana and Abia said. He said if consolidation happens and there's a panthropic and open AI or two or three dominant fronts that is the biggest threat to that. That's correct. Yeah. But you got to make a leap of faith assumption that the models from China or Nvidia is making good progress on their models in the neutron. So there's going to be enough factors in the market to keep consolidation as an outcome from like starting from happening. But you don't control your own destiny if you're those companies. That's basically the problem. Okay so we can have standalone companies that are 100 billion dollars in inference alone. So I'm just pillaging you for your knowledge. When we look at the model selection companies like an open router or like factory AI just release that kind of model selection or model routing product. Yeah. Which did very well and launched. Is that 100 billion dollar companies in the model selection and routing business? Probably not. I think you can just be a provider of router. You have to use the router to produce something meaningful. Actually most of the business value of open router is less than the router even though the product is called open router. It's not routing across models there. It's actually just routing across different end points of the same model. Okay so maybe let's ask this question. If you wanted to use cloud opus or I don't know like GPT-5 files developer. Why would you not want to just use it with your own API key versus using it inside open router? Number one argument. The single simplest argument is to why you would want to do that is model fallbacks. Sometimes your API keys might not have the rate limits or even if you have the rate limits there might be an error on opening i-servers that you know don't guarantee you the response time you need to run your application and open router would go and they would pay for a capacity. for like one year ahead with their funding they have and secure the rate limits and multiple endpoints across multiple different providers of open AI models be it bedrock or Azure or open AI themselves. And so that routing is valuable. It's essentially an infer a problem they're solving, which is reliable token supply. It's not actually, oh, like they're lowering the cost by deciding if this prompt should go to like GPT or cloud or something like that. That's not what they're actually selling to the developer. That's not actually the business model. And then for a lot of these Chinese open source models, you probably don't want your API tokens going to let's say you don't want API tokens going to China. And let's say you don't have the bandwidth to work with like different inference providers or verify who's good and who's not. You're just trusting open router to take care of all that and then you know, they're going to like supply the tokens to you. So it's routing not at the level of like, oh, like deciding which model is cheaper or tasks. It's more like a reliable token supply. And I think there's some value in that layer. Definitely. Otherwise, they wouldn't have these many users and these many trillions of tokens being routed a month. But it's not like, you know, high gross margins business. It's the way the business model works with them is actually they would secure a discount from the motor providers by guaranteeing a lot of supply, but they would still charge the user listing price on the API. And that difference is their margins. We spoke about bottlenecks and you said about HPM, high-poundless memory and micro on the value that they have to say and what it can be. What bottleneck will we have in three years that we're not discussing today? I think power will remain the bottleneck. It feels like that to me unless something dramatically changes in the way data center buildouts happen. I actually believe that there'll be a lot of resistance to building data centers. It's because people incorrectly think that data centers consume a lot of water or eat up a lot of power, which isn't both both are untrue. Sauti even made the statement that it's like a can of water or something in terms of how efficient these companies are. Do you think that's why that putting out resistance to them? I don't know. I think it's because it's a symbol of job losses increasing wealth and a lot of things. It's a lot of things. It's a lot of apprehensions fear about like what's going to happen, channelizing in so many different ways. Sometimes it's channelizing through hatred for wealth and equality and like wanting to tax people. Sometimes it's channeling through like concerns with environment and like climate change. Sometimes it's channelizing in a way where you're all like, oh, like the price of the grid is going up because you guys are building all these data centers and then all like I'm paying more for my phones and laptops now because the RAM prices have gone up because you guys went and bought all of it. So I think there's a lot of different ways in which it's getting channelized, but the common sentiment is like like a pretty bad sentiment about AI. Do you think it will be meaningful to use the development of those data centers? I think right now 40 out of 100 are not being developed because of public resistance. Yeah, so that's where the power bottleneck is. You could see maybe certain countries seized opportunity for this and allow these model builders to build data centers there. Elon's going to space to do that. So that's going to be an interesting experiment because there's a lot of energy from the sun that can be harnessed there. There's a lot of natural resources in other countries. Regulations might be more friendly. So we're still going to see data center build out. It might not not happen in the US, but the fact that you have to solve physical problems, like you actually have to deal with the supply chain, the permits, securing power, like making sure like things work and getting the lead times lower and lower. You're not solving problems like cloning some SaaS apps here, right? Or like you're building a go-to market team or like doing better marketing against the competitors products. Yes, those are also hard problems, but these are like much harder. Problems where like you're not in full control if you're destiny and you need a lot of capital and connections and like the right people sometimes even like political help to unlock progress. And so that's why this will continue to remain the bottleneck in my opinion. And there's a lot of risk as well because if you do encounter another deep seek moment here where there's a vastly more efficient model that's been built with a very different vertically integrated architecture and you built out all this capacity and you're like damn that's I overbuilt. That's something farmer efficient that can run on people's local devices in the MacBooks. There've been those PCs. Yeah, like you're probably freaking out then. How likely do you think that is? It's probably like 20% 30% chance. The reason I think there are some possibilities that because of the export controls. So the deep seek is not building within video stack. They're building the Huawei stack. And because there are export controls on not just the Nvidia GPUs but also on HPMs. These architectures that deep seeks building are far more like memory efficient. They've made innovations on the KV cache to be really small enough that you can host it on the SSDs and they don't need high bandwidth memory for inference time. And they're going to have a completely different architecture for inference completely different architecture for storage because they're not allowed to use the 3D nands. So their architecture is not just a model architecture. The model architecture is already pretty different. They've made innovations on the attention layer. They made innovations on like the training algorithm so that it doesn't consume a lot of interconnect capacity. So basically their whole stack is getting vertically integrated to their hardware and their chips and their fabs and so on. And so that's a very different bet from what America is making. Do you think the export controls have helped or hurt us? Juries to lot. Short term is helping because my belief, the only reason why there is even like a 12 month cap between open source and frontier is export controls. And so it's definitely helped and definitely like companies are going to probably lobbied very hard for it. But there is a chance that because of that they now get really good at the physical layer. And one advantage they have is they can actually build data centers a lot, lot faster. Power is not a problem. Permits are not a problem. People are not a problem. Labor is not a problem. Expertise is not a problem. And so by forcing them to go out there and build all this, you're converting them to a far more like potent competitor. Do you think we sow dramatically under us? Matt John is K. Foto sees. I think so. If AI is like not just digital, that's also physical AI. You got a book, fabs, robots, chips and harness the energy really well, package it into local devices. I think they have a lot more advantages than America. How important is it that we have our own TSMC in the US? TSMC is actually there is a fab of TSMC in Arizona. Like a lot of people talk about this, but TSMC is investing like $150 billion into building American fabs. They've already invested $40 billion or something like that. 60 billion last time in check. So there is a TSMC in Arizona that's coming up. There's also Intel. And that's why you know, American government owns 10% of Intel and VD on SouthPanco and 5% each. There is a lot of investment going into an American fab as well as TSMC is investing into its American fabs, Elon's building terror fab. Like I think people have woken up to the importance of building fabs, but this is also why China is particularly very, very competent. Given the capabilities of China that we just mentioned that really articulately, I know it's a ridiculous question, but it's not a, if I were to say to you, your job is to make sure America stays competitive. What would you do to ensure that you retained competitiveness in an increasingly strong China? I think take physical infrastructure a lot more seriously and continue funding it and not like how all these, I wouldn't say meaningless. It's more like not propagate fake news around data centers about how data centers are polluting, contaminating water or like they're sucking up all the water and actually be fact driven. And so, you know, I hope our product helps there. Like you can go to flexing ask any question and get fact checked on your assumptions. But yeah, like it's very important that we educate the public about what's actually going on in a language that easily understand and not fear monger. Okay, like not be like, oh, all your jobs are going to go away. Like this is that like there's going to be lots of amazing companies that are going to get built with far fewer people getting multi billion dollar, multi hundred million dollar evaluations with like 20, 30 people and propelling like trillions of dollars of new GDP. Like let's talk about how to enable that. Let's talk about how to build that and create a more positive future together instead of oh, like 90% of the jobs are going to be gone. Like you're all going to get screwed over by our models and like it's it's our it's our moral duty to tell you all this. Like well, like that doesn't make any sense to me. Like you can win by saying that and also like complaining about not being able to build data centers fast. Do you think we've done a complete disservice by having the marketing message that Dario has had that all jobs are going and it's all doom and gloom? Yeah, I think so. I mean, I think you know, they have contradictory messages in their own like different social engagement so far where the most reason when I heard was there is no evidence that AI is taking over jobs. There needs to be a consistent communication around this. And I also think that very little is being spoken about how AIs can help you build companies in a very, very different way like the current AIs where a generic AI so many things you would hire people for you can do it with agents. But one way of looking at it is like, oh, like what happens to all the jobs? But the other way of looking at it is like, hey, like I never had the chance to go build out a company on this idea that I've been having all this while and maybe me and a group of friends can come together and build this and can you guys figure out a way to give us compute credits or, you know, Amazon gave a lot of compute credits. So a lot of startups like when we started for Plexigy, we had like around $200,000 worth of Amazon credits and GCP credits and Azure credits that are almost like together are committed to it. literally this was worth like a million dollars in compute credits. Now in today's world it's going to be like a million dollars of computer credits and we're doing that like we're funding this thing called a billion dollar build where we're giving a million dollars of computer credits to any group of people who have a credible path to building a billion dollar company. And I want like thousands such companies to be built. What did you think of Sam Altman giving two million dollars of tokens to YC companies in ancient? I think we should do more of that. Yeah, that's the right thing to do. We should do a lot more of this because you want new companies to be built and even if they're worth multi hundred million dollars, it's good. If there are thousands of them like that's a lot of new GDP. I spoke to Anne Bordesky before the show and she said how AI piled the team is for you. How big is the team today? It's like 400 people. 400 people. How big will it be in two years time? I don't know it's hard to say maybe 800 thousand. So will companies follow the same headcount trajectory that they have always followed and we will just solve new problems or will they be dramatically more efficient with much fewer number of people? Definitely, they'll be dramatically more efficient. And that's why I am a believer in building a lot more efficient companies and being an example for all these companies ourselves. Like people should look at complexity and be like, oh, like with 400 people, you can build like a multi, I don't know, like 20 billion, 20 billion dollar company. And so that means with like 40 people, I could probably build a billion dollar or two billion dollar company. And that's totally doable, totally doable. And so for us, maybe that means with 4,000 people, we could be worth 200 billion. We could be worth two trillion dollars with like 10,000 people. That doesn't mean it's bad for all the 100,000 people who did not hire for a typical two trillion dollar company. I would rather have those 100,000 people be split into groups of like 100,000 groups like that. And each of those thousand groups are worth a few billion dollars. That's awesome. And I think a lot more people need to be entrepreneurial. There are people who would be bad employees in any company because they're just like difficult to work with. They don't listen to like instructions. So like they don't follow like road maps or not, they're not like easy to collaborate with. But maybe the flip side of that is those, those are the kind of qualities that founders typically have. Aaron, there is a population and a very large population that are not AI-nated people that are not using AI to improve workflows, improve efficiency. What would you advise them? Get started. First steps, get started. And channelize your curiosity. You don't need to use AI as to do your existing work. If your existing work is boring to you, you probably want to enjoy it even if you use AI as to do it. You got a lot of heat for saying people don't like that job. So I didn't say, if you actually listen to my interview, I did not say that. So people want clickbait articles and they take something I said in one sentence and out of context and make it into headline. What did you say? I specifically said this. Hey, like there are a lot of people who don't enjoy their jobs. By the way, the fact that thing went viral is not because I was completely wrong. I think a lot of people resonated with the fact that I was actually honest in saying a lot of people don't enjoy their jobs. And that has nothing to do with your economic position of standing in society. You might even be like really wealthy, but doing a job that you completely don't enjoy and like destroying the peak years of your adult life, working on something that is horrible or depressing. My point is that if that's you and if the reason you could never leave your job is because you were always worried about how would you build a company from scratch. There are all these things to figure out. If you hire a lot of people, you have to set up an office, this is that. That's changed. For the first time in history, you can get started on an idea with one or two other friends and maybe have a real genuine shot at building a billion dollar company. Totally got that. Everything that we've discussed today has been on the back of unprecedented demand. Up into the right, we need more memory, we need more data center supply, we need on demand and service. Everything is up into the right. Seeing some cracks in an Uber's saying, I'm not sure I'm getting the productivity gains that I thought Microsoft lining with them, putting a $1,500 token budget, do you think we will have a continuous up into the right acceptance that productivity gains are unwavering? We have to do this. Or will that be faltering along the way? I mean, I'm sure there's going to be faltering along the way and people are rightfully freaking out about token maxing, which is why I think you need some form hybrid eugenic inference. You need some amount of inference computer on locally that you're not paying for tokens on, on meter and thousands essentially. How will the best companies of the future structure token budgets? My hope is that they don't have to understand that. They will be able to work with an orchestrator who does it for them. It's not going to be easy for you to constantly keep track of which models are the best at what things and how do you allocate? Oh, this is the budget for coding, this is the budget for finance. Like, how do you even understand which models are good at each of those things and how much do you spend on each of these divisions? You're not going to be able to keep track. I had a friend on the show the other day, I say that Google will be the token king. They can produce the lowest cost tokens out of anyone. They own full-stat TPUs, data centers, networking, power, procurement. Do you think that's true that they will be the lowest cost token producer? They have advantages. All advantages, one needs to have to be that. But they underestimated the importance of coding models. And so they're far behind the frontier right now. So again, they can catch up totally capable, totally computer team. But today they're not way to the frontier. I was shocked the other day. I saw the CloudFly announcement that now agent traffic has overtaken human traffic for them. Why are you shocked? It was quicker than I thought. Okay, personally. I thought that would happen, but in two years, maybe not now. How does the world change when agent traffic far exceeds human traffic? I think people are just going to have a lot more agency. But the websites go away. Does design not matter? Does the advertising model of the internet die completely? My belief is that the advertising model, or on like travel, or shopping, or like fashion, are not getting disrupted by agents because the judgment is not objective. Anything where the judgment is objective, the transaction is based on objective judgment, that's going to get disrupted by agents. Anything where the transaction is more subjective, like the decisions are more subjective. Like, what is the best piece of furniture inside this spot? Like, why this particular table? Or like, those kind of things. Probably for the mic, you would buy an objective decision. The table, you probably are carrying about the aesthetics of the room. I think that's kind of how I feel the world will split and subjective things will still be ad based, objective things will be agent based. I watched your commencement speech on the back of speaking to Samarit Excel and he said, I had to watch it. So obviously it watched it. And one of the points you made was the defining skill of the area is asking better questions. Yeah. What question is no one asking today that maybe everyone should be asking? I think people need to ask more about like, okay, assuming I have a lot of agency available to me. What do I do? Imagine like, I gave you a head count of like, 100,000 people, or 10,000 people. And you know, enough compute credits to run those agents. What would you do? Like, let's say I ask you, Harry, like, you know, let's say you have suddenly like, 10,000 agents at your disposal. What would you do? I remember you telling me or not me, but in some episode of yours where you said you only did this podcasting because you felt like you didn't have an arbitrage to go over and deals 100%. Well, I still do. I mean, I love what I do. But yeah. Okay. So you've gotten some amount of distribution. So now as you mean that you have, let's say you could spend $100 million on eugenic inference and grounded with all the connectors and stuff. And it's all working. What would you do with that capability to further your goals? Like, what should your goals even be then? I think that's the question I would ask. Assuming that in the next three to five years, you're going to be able to like delegate whatever digital task you want. And with the right harness and agents and like, be able to delegate that fundamentally would be to build an agentic infrastructure to be able to find, identify, outreach, set up when great investments and have the media sit on top and power that there's intensely difficult to do and would be the hoodie grail to investing. But like that would power my end goal ambition is. Yeah. So your goals to be the run like a 10 to 100 X larger fun, right? That's basically what I'm hearing from you. So let's assume that's like a 40 billion dollar fund from 400 million. Then all you got to ask is like, assuming I have all the headcount I need to do this like how much faster can I do it? I think that's how I would frame this question. I think Elon has like a similar thing he spoke about once where, okay, assume that a task somebody tells you a task is going to take 10 years. Ask the question, what would it take to do it in 10 months? Maybe it's impossible to do it in 10 months, but you'll probably get pretty far asking those questions compared to somebody who takes it for granted that it's going to take 10 years. All right, interview. We put it on you. It was your 10 year. And how does that look in a 10 month time frame? Very interesting question. I think our mission beyond any level of capitalism is to make the planet more curious. The product is always intended to help people ask the next question. My goal is to truly realize that like that level of agency that needs to exist in this world is quite not there. I think that needs to be grounded in numbers, dude. To make it like possible, I it's like me saying, I want the best investments. Which is why I have 40 billion dollar funders. Sure. I can say the same thing like two trillion. You know, it doesn't matter. Like 100x, 10x, 1000x. These are all like motivational milestones. Do you think in public, you'll be a trillion dollar company? Anyone can be a trillion dollar company. SK high necks in Samsung are worth a trillion last last couple of weeks. Did you know Samsung started off as a grocery store? They started selling dried fish. The SK Group started off as DexStyles company. So anyone can be worth a trillion dollar company. And like you just have to work your way towards that. I mean the exact same logic for you that you laid out for how can a company be worth a hundred billion dollars. Okay, you said you need to make a ten billion dollars in revenue. Isn't that the same for trillion? Like you need to make a hundred billion dollars in revenue. And there was actually some very interesting data that Co2 revealed. I didn't know if you saw it recently, which basically says about the probability of reaching the next level of value. Yeah, it's higher. It's much higher. So when you're a billion, it's like much more likely to reach 10 billion, 10 billion, much more likely. Yeah, that's true actually for even people. Like it's way more likely for a person with hundred million dollars in the good network to become a billionaire than someone with 10 million dollars. Are you not worried about the wealth inequality? Being blunt, we both are very lucky now to live in kind of nice worlds and rarefied as a you not worried by just how much money a very small number of people have and how hard it is for everyone else. I'm not gap is getting bigger. I think the way to like ensure that that doesn't remain the case is to distribute the benefits more widely. By the way, the people who are using our tools, like I've had an Uber driver. I'm not even like making this thing up. An Uber driver in San Francisco once told me that he watched one of my YouTube interviews very explain how you can build a product or a web app with an AI from scratch. I went on to do it and used AI to add like billing and all that and that makes more passive income for him than driving Uber's. And so he actually reduced the amount of time he's driving Uber because he loves web coding new apps that that already tells you that for the person with agency and a positive outlook for the future, anything is possible. And so if you keep communicating all the negative things you can about AI and built in equality all the time and that's the only thing news and press rights about I think it'll perpetuate and people will only think the bad things. And so it's very essential that if you think you're already doing well, it's very essential that you talk about what are all the things that can go well and give hopes to people who are once upon a time like you like you you didn't you you started this podcasting circuit like when you had nothing right so nothing exactly so it's possible. So you got to you got to talk more about that than be like oh I feel so guilty that I made it and now I'm like you know what about all these people who haven't made it like you can also make it like I think I have a more pessimistic view of actual general public which is I don't think that many people have agency I think a lot of people have been and you got to help them like I think that's that's the most important thing they got to help themselves. People will help themselves once they see that okay like I kind of want to be like this guy let me work hard you need an example right it's not like nobody can become getting shape like it takes discipline you got to get rid of bad habits and now is the best time ever to change your life in 12 months the ability to go from nothing to to actually billionaire in 12 months is now possible yes look I'm not saying everyone's going to make it and everyone's going to be worth a billion dollars isn't not the caption from this this show arevind everyone's going to make anyone has a potential to make it it's it's as likely for perplexity to become worth two trillion dollars as a founder who's yet to secure your funding to where it be worth a billion dollars equally hard you just have to give yourself in the shots of the goal be curious that's that's a message from the commencement speech be curious we have space ice we have anthropic we have open air going public feels like someone's kind of shot the gun and the race is on is there enough money to fund three such large I there will be some reallocation for sure there might be some holders of like sas stocks who would put it into anthropic or something let's say you believe that enterprise AI is going to take off you might want a hedge between having a lot of Microsoft stock in Salesforce stock versus like putting some of that into anthropic so let's say like Vanguard of BlackRock own like you know cumulatively they own like 200 billion dollars of Microsoft and Salesforce they might be like okay I'm going to take 30-40 billion of that and put it in anthropic fine you know not a bad bit to make what happens to the enterprise sas companies that are public trying yeah fine they have to weather the storm is it a storm or is it a continuous precipitation I think you have to bring down the costs and produce new value this force has done well because they always went and bought the next thing if you're just selling the same software you're probably not going to be around IBM is still around because they went and bought red hat and hashicarp and now they're buying console and so there are ways for these companies to stay alive and extend their lifespans and stuff so obviously going to be hard to preserve a brand that's as relevant I don't think IBM brand is that relevant anymore in terms of like evoking an emotion and people to go use their products but as a business it's going to be awesome you know it's going to be fine I have to finish on you said IPO in 2028 I had to ask this I woke up to this in my like you know group where we have a team what's up and it's like oh Garvin IPO 2028 I hope I hope it can be sooner than that when do you know when you're ready is there like a billion in air you're 500 million air on now more than that far more than that actually really we're not ready to share it but growing really fast rather than you grow as much more cheating profitability today I think in general by the way you can look at public markets people want top line growth more than bottom line efficiency right now because it's very hard it's it's rare where you definitely need one you need to have a model in place to get the bottom line efficiency when that becomes the objective and and you need to also like have a pact to getting there where you cost an efficient stay where you expect to be significantly better in two to three years we're training our own models post-training it on top of amazing open source models and that will bring down the cost that we currently spend on frontier model tokens we expect to continue to use frontier models for designing new experiences and new capabilities that do not exist today in our products but whatever exists today in our products right now we expect to completely rely on like models we own and serve ourselves and that's going to be the best way to bring down the cost and increase our margins will the largest enterprise in the world will be fine tuning open models to have tailored models that are much more specific to them absolutely because it's in your incentives to bring down the cost does that not provide another backcase for the large front end model providers frontier model providers will only remain relevant if they remain a different tier if for six months you're not seeing a new capability it's bad for them and so that's the uncomfortable nature of this field you know once ever in a comfortable position like I said in the start no once no one can relax this is fucking a horse yeah it's gonna get even harder that's the nature this is the the price is too big like you've never seen like like taken through up I think it's worth like one to one and a half trillion something in that range that's basically the valuation of meta and this always created in like six years meta took like 20 years to build so the price is so big and so no one can no one can be comfortable and anyone is winning today can lose tomorrow including including the model providers pre this year there was like a three month period where people are like oh perplasty what's happening with perplasty alone do you pay attention do you give a share of course I pay attention to all that you care there was one in particularly in San Francisco to remember they're like oh it was the company you're sure yeah we were voted the most likely to fail cursor was loaded the second most likely to fail open AI was voted the third or something you didn't give a share I feel like we're all doing well cursor I think it's getting sold SpaceX open AI is going public soon we tripled our revenue since that judgment was made so we're out down the burn by more than 50 percent I also feel most of those people who sit down these like meetups and what don't actually build anything useful I agree well yeah okay we're gonna do a quick fire on because I get to you all day first one what's one widely how belief that you think is completely wrong I think a lot of people are obsessed but like you know I didn't find a mode in the first year or two of their company I think like the only shot you have to move fast like we'll loss in my mind like moving fast as a way of expressing humility because you you're constantly making contact with the world and trying to question your assumptions all the time where are you still moving too slow internally today I think we can be even more I pulled it's insane I'm saying this because we are building some of the most interesting AI products and internal adoption of our own products are competitors products can be even higher and this is despite us being extremely agent-filled internally and trying to delegate as much to agents and so yeah that's where that's a big area for my hope is that we can turn this company almost into an AGI and that doesn't mean no humans work here but there will be an AGI that has all the context it needs to run different divisions of the company in a semi-autonomous way with some scaffolding provided by humans here and there and that's not going to feel scary at all we'll normalize that feeling very fast it's just going to feel like the 10x engineers running certain aspects of the company if I gave you unlimited money what would you do today that you're not doing I'll build data centers you would yeah in space I don't have expertise to do that but I would start with land on earth you know I think there's a lot of land and maybe you can be resourceful in securing permits and power in different countries but I would start there you know I like I said like I think physical infrastructure buildouts is like the return of the industrial age again like like the four fathers who built the industrial revolution oil pipelines steel bridges factories producing cars all these things that we take for around it today, we're built by people who spend a lot of time thinking about how to scale these things in a cost-efficient way. And so we need to do that a lot for AI. Yeah, that's what I would do. Of course, you cannot just be building infero. You need to be able to utilize all the infero, the producing valuable output tokens to the user. But we're already good at doing that. So, infero is the thing I would focus on. You can buy and hold for 10 years. SpaceX, Anthropic, or OpenAI. Three IPOs coming in the next few months. Which you buy and hold for 10 years am I? SpaceX. Why? It's an NF1 company. Anthropic and OpenAI can claim they do whatever each other does. But SpaceX is the only company building based infrastructure for connectivity. Have you been on a flight with Starlink? No. You should. You will hate being on a flight without Starlink after that. Imagine you can record this. I can watch this podcast by flying on a plane. Starlink lets you do that. That's just one aspect of the business. And small aspects of the business. Yeah. I'm excited about possibilities of travel from Australia to San Francisco in 30 minutes. All this feels like sci-fi, but I'm excited about all these possibilities. What job does not exist today that will be incredibly common in five years' time? I think it already exists. So, if the forward deployed engineer is definitely on the rise, I guess people with a really good sense of quality control. Maybe a better way to answer this is most jobs that exist. Like valuable jobs that exist are usually like reincarnations of something that already existed. So, I don't think we're going to see completely new things. This is going to reincarnate in different ways. You can advise your little sibling who's finishing university today and just on a computer science degree. One thing. Take your years. Don't give into like FOMO and trying to max out on something here in the short term. Don't go to Twitter and feel like a loser that people on frontier labs are getting so rich and like everything feels hopeless to you or something. There is so much more to build. Like we're just getting started. The application layer, era or like infrastructure buildouts. There's like a lot of opportunities. We are seeing more spin outs from OpenAI Anthropic you name it every single day. Do we have hundreds of these Neo labs and vertical models? No. Not a big believer and too many of them. I think you've got to produce some differentiation. That's the most important thing. Like I, if you would do you call deep seek on your lab? No. I think very stupidly for me. I don't call it a Neo lab because I attribute Neo labs like spin outs from larger labs. I see. And kind of verticalized, which is probably wrong on both axes, but it's horizontal and it's not a spin out. Yeah. I mean, I kind of like the idea of labs taking a differentiated bet. Okay. If somebody really questions the transformer architecture itself or somebody really questions needing to build on Nvidia GPUs or something like that. The foundational bets makes or somebody goes out and builds for robotics models. I think that's like somewhat uncorrelated and different and that makes sense for a lab. But I feel like there are like just labs for the sake of being lab and I don't think they're going to make it. Can you paint for me? What's the most plausible story where a popularity becomes a trillion dollar company? What do you do then? Equestration layer? I mean, accuracy and orchestration is like two goals that have been consistently true since the beginning of our company. So I think we'll continue to do that. We'll be orchestrating across devices, chips, models, tools, files, connectors, everything right? So what would I do once that happens? I don't know. We'll chart our path to 10 trillion. Are you happy now? Are you enjoying this? Of course. Like, there are so many things I could be doing if not for this. I think the process is what motivates you. So you ask me, I think, some earn between you need to give me a number of where you want. I don't work like that, actually. Like for example, like these numbers like getting to 2 trillion or 20 trillion are exciting but like that doesn't motivate me. It's hard to get motivated by wealth. Who's the smallest person you've met? Final one. You've met Jensen Huang. You've met the best of the best. I've been fortunate enough to. Who's the smallest? People are smart in their own ways. It's hard to compare. I've met Jensen, Elon, all these guys and like Bezos. What was it like meeting Elon? Amazing. Elon's like a very focused person. He might not appear that way on Twitter but you know, with a lot of like random tweets. But he's extremely laser sharp focused on whatever he's doing at that moment in time. Actually, the one skill that as an entrepreneur that I would really like to take, like build from somebody like him, like take from somebody like him and have it for myself is that ability to just zone out of all the other things that's happening in your business or other businesses and just focus on that limiting problem right now. Like the bottleneck problem and ignore everything else. It's very hard to do. Like even within Prophecy, I cannot just focus on like one part of the business alone. It's very difficult. Like I'm always looking at other things simultaneously. And his style is to just always look at the limiting problem and just ignore everything else. That's very hard to do because you actually have to be really good at concentration. You have to be really good at ignoring even important things which are distractions your core objective right now. Who's Jensen Huang, who is who he'd be? Far better. Jensen is so true seeking. It's insane. Like he or somebody else told me or read in a book that he is so intense that he wakes up every day and tells himself that he sucks and like he's so intense that he tells everybody around him that there's 30 days away from going out of business. Think about it. $5 trillion. I guarantee to make $500 billion in revenue in the next two years has the most advanced chips in the world. And he operates with that mentality that he could be 30 days away from going out of business. That is what it takes to be Jensen Huang. And there's so much to learn from these guys. There's so much to learn. There's one aspect of like you know being comfortable where you are thinking you made it that that feels good to get here so far. But these guys are not stopping like I don't think Elon wants to stop it. If you look at a space package with SpaceX it's structured around creating a colony in Mars with a million inhabitants building enough compute in space. It's not like motivating to be worth a 10 trillion in network or something. If he does these things I'm sure he's going to get there. But it's more motivated around like making the impossible things happen. And having like that long term outlook like you I think that has been the biggest thing to learn from maybe these two individuals in particular. A lot of people view this like entrepreneurship as like oh if it wins if if I win and have a great outcome and I sell my company I would have like generational money. I don't have to work ever again. And then what you end up just staying at home and like your kids will obviously have like trust funds and they're not going to get inspired watching their dad play papal. Yeah. You're not going to set the right example for them. They're not going to be able to take your belt and multiply it because they didn't watch somebody who actually did that. You did it before they were like adults. And so I think you always need to be doing something. Jensen said some recently that he hopes to die on the job or something like that. Like that's the attitude you need to have. Like you got you need to work forever. I was so upset that when Jensen said if I'd known how hard it was going to be I wouldn't have done it when he did I didn't know if she saw that into you. I was like oh yeah I think it's pretty hard but you do it despite that. I think I think that's how it works. You do it despite that. Aaron listen this has been so fantastic to you. I so appreciate you taking the time while you're in London. So thank you so much. Thank you very much. Appreciate it. But before we leave you today if you're a finance professional you know the month and nightmare chasing down missing receipts and fighting without dated tools that your employees hate using. Navan is an AI powered travel and expense platform that gives you control and real time visibility into every dollar spent. 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