The long-term average intelligence is going to be free, and the average intelligence will get smarter. Land, permits, energy — see, this is the thing that is going to get priced for the next three to five years. And hold up, Nikesh Arora joins us in the studio. Oh yeah, baby. Palo Alto Networks CEO, $280 billion company, for this incredible session today. And we discuss Leopold Aschenbrenner's situational awareness imploding — sad face. Airtable being acquired by Bending Spoons for $1.285 billion — sad face again, and they were worth $1 billion before. Anthropic's model breaching three companies — oh god, when do the security problems end? That and so much more in this incredible conversation.
Absolutely right on trend, absolutely wrong on portfolio construction. It's almost like it was inevitable. If you bought in in April, May or June, you've been wiped. We did a hedge fund, but it appears it wasn't hedged, right? And we lost all our money in a week.
I think it's a bit of a gold rush moment. I think every consumer app will get rewritten in the next five to ten years.
In the face of insatiable demand, all things are possible. A Palantir can do it. They came back from 15% growth four years ago. Why can't you do it, kids? Work harder.
Team, it is so good to be back. And we have the one and only Nikesh joining us. Nikesh, thank you so much for agreeing to join Rory and me and Jason.
I am a little apprehensive watching Jason and Rory there in their full glory. So let's see how this sort of plays out for me.
We have Professor O'Driscoll in the corner. But we're going to start on the news of the day, and the news of the day is Airtable, one of the big names from the last decade, has been bought by Rory, European-based.
The company was doing $485 million, growing 20% year-on-year, ultimately at a $1.285 billion acquisition price.
It's not the outcome that everyone quite wanted or expected, but it's what we have today.
Rory, why don't I hand over to you first? I'm sure you've got some perspective.
Well, you know, we're all going to do the Airtable side of the analysis, but just worth pointing out the Bending Spoons side. I'm buying stuff at 2.8 while I'm trading in the market at nine to ten times revenues. They're going to do this all day, every day. And I think, as we said a few weeks ago, one of the big advantages is they're in the game with capital and a traded currency to hoover up a whole bunch of this stuff. So on their side of the table, totally get it. You know, obviously on the Airtable side, you know, a lot of comments on: is this giving up? Is this a reflection of where SaaS is? If we weren't anchoring off the 11 billion, it would be a great price. If you said someone set up a company 10 years ago, grew it to $450 million in revenues and sold for 2 billion plus or minus, they'd be like, that's an amazing outcome, right? But of course, we all anchor off the 11 billion 2021 price and it feels like a lowball. But I think it's still a great value creation achievement, and you know, we have a talented entrepreneur on the show with us and we need to start with that. It's a great outcome.
Can I ask Nikesh one particular question on it, Harry, if it's okay? Because I was going to ask you. I have a lot of interesting thoughts on this deal, whether Airtable matters in the age of agents and AI, but I mean, Nikesh is also one of the best dealmakers out there. The shocker to me with Airtable wasn't the price, because I think it's low market. The shocker to me is no one else stepped up. No PE firm, no Thoma Bravo, no Vista. It's 20% at $500 million with some AI dust going on it. Do you think there was even another offer? That's the — I just assume someone would outbid them.
And you're asking me that because I'm like...
You're the deal — you're a dealmaker par excellence.
We just happen to have the king dealmaker on the show.
Yeah. Look, I, you know, I met Howie a few times. He's a great guy. He's built a great business. I think, I don't know, to Rory's point, there's a bit of founder fatigue here. I think he's been through a lot of sort of ups and downs in terms of sort of internally and in the market, but it's got a good product. I think the broader question, which Jason hits on, right, is, you know, what is going on in the SaaS marketplace. You know, you see dislocation — is this a pricing dislocation or is it a fundamental change in the long-term growth rate that people expect out of SaaS? If it's a fundamental change in long-term growth rate people assess, then the multiples are right now, you know, and that's I think where the market is grappling with this. I think the people you mentioned, Jason, the PE guys, they might have a full roster of stuff they'd like to sell to Bending Spoons as opposed to what they'd like to buy against Bending Spoons. So I think they'd be caught in this sort of demand and supply problem right now. They, you know, they have a lot of inventory.
It just worries me. I let you — we just — I, because you see more deals than we do on the acquirer side, right? I mean, we see it on the target side. It's just...
When you look at long-term growth businesses...
Yeah. Say that again. Sorry.
So, we stick to long-term unprofitable — currently unprofitable long-term growth businesses. But yeah...
I get it. And that might be the answer. I just — with, I mean, when Francisco Partners raised $22 billion to do deals sort of like this, right? You know, Thoma Bravo was like, we're looking for AI-infused B2B companies. You know, we could pick at Airtable, but it did do that. It did infuse AI workflows and others, and I don't know that it's growing, but it did that, right? 20% at $500 million in AI workflows isn't nothing. I just would have — for all the founders out there looking to be picked up, this one would have seemed to me to be just above the fold. Like, they should have leaned in on this one, not the one growing 8% and shrinking because it was destroyed by AI and it's cash flow positive and it has plenty of cash. So all the boxes you check, right, are sort of there as an attractive target, and yet no one outbid them.
Well, look, Bending Spoons did buy them, so clearly somebody saw value there. Not everybody's seen it, but Jason, I want to go back to something you said around AI infusion. I'm a little wary about this AI infusion stuff, and this is what I talk to my team every day from an operator perspective. I say to them, you know, are we Mercedes? We're trying to sprinkle a little bit of AI in our car and say I have a little bit of AI. Are we Tesla? Are we making sure that our car will drive, you know, the next 10 exits by itself and might have to grab the steering wheel once in a while, building a Waymo? And the question back to you is, did Airtable do a bit of a Mercedes action, a little Tesla action, or a little bit of a Waymo action? Because my biggest fear is a bunch of people out there in the garages getting funded by Harry and Rory, and they're going to build Waymos of the future, and we'll be busy putting lipstick on the pig.
It's a tough — it's a tough one, right? But...
Yeah, it is. And I — because I didn't feel, Jason, that this was the kind of category that PE would sweep up. Because, kind of merging the two sets of comments, one is, yeah, they definitely — you're trying to add some AI pixie dust, but you're fundamentally your core productivity app. And you've been the proponent, Jason, that, you know, oh my god, look at all you can do with Lovable. If I wanted to build my own CRM and I wanted to be personalizable, 10 years ago I might have used Airtable because it's way more configurable than Salesforce. But today, if I'm the nerd that wants to build my own CRM, I might just go to Lovable, Replit or Claude Code and just bang it out from scratch. So if you want to do that, I'd call you a person with no — low imagination, or there's so many other cooler things to build. The last thing you want to build is a CRM.
I agree, and I — yeah, and I am a person with low imagination. I cop that. But I agree. But the point is this: what it means if you own a horizontal productivity app that's mainly individual user. I just think that's one of the tougher categories for PE to get their head around.
Ironically, given the Evernote purchase, this is right in the Bending Spoons sweet spot. If you think about it, this is, you know, just like Evernote, it's like the people who have stuck with this product are going to stick with it. They're going to apply their formula. Maybe what I'm saying slowly as I process is capitalism works, and it ended up in the arms of the best owner of that product, which is the people who can take it and turn it into a cash flow machine. I bet you two years from now it's doing 600, not 900, but I bet you it's $300 million of free cash flow.
Yeah. Or more, right? Just double the price. And your data is locked for two years, right?
You know, to your point, I don't think PE has the stomach or the willingness to do that, but I don't think it's what they do real well, right?
But yeah, I think their stomachs might be full. I think it's unfair to say they're...
That's exactly right. As I often say to people when they show me a turnaround deal in my business, right, I say, look, if I wanted a shitty turnaround deal, all I have to do is look at my portfolio. I'll have four of them already. I don't need a fifth problem, right? I make problems on my own accidentally. I don't need to go actively, proactively say, let me get more of this shit. You're exactly right. Anyone in PE who's done five software restructurings in the last 12 months, they need a sixth like a hole in the head.
Nikesh's points — I mean, both his points are obviously great. The one on the Waymo versus the whatever. We can come back to the founder fatigue. That one's a tough one today because another way to look at Airtable is, man, so early to no-code, right? Such a clever product back in the day. Like, there were two products that I wasn't even smart enough to understand why they were cool in the day. There was Airtable, which turned a database into a spreadsheet, so I understood it, right? And then there was Notion, which turned a database into a document that I didn't even realize. And they were both so clever pre-AI, and they both took off in different ways. But we don't really — you know, Supabase is doing a million Postgres databases a week on its own. We don't need — we didn't — we don't need that no-code database today. And as a founder, you know, after all these — what, founded in 2013 — it's tough to pick yourself up. And he already picked himself off the floor, right? Already did the layoffs, already got profitable, already rebooted, already went founder mode again. I'm all in. And you're looking at yourself and you're like, can I do it another 13 years? And it's a tough one today when you've already done the — the — whatever. I'm sorry, Nikesh. What's below the Waymo? The T — well, when you've already kind of checked the box and done it, and you're like, god damn it, I got us to 20% growth — just, it's tough to not tap out. We're human beings, it's tough to not tap out.
I mean, one of the things that's interesting here, and I've said this in the context of venture in general, is your comment, Jason, is like basically the technology trends moved on from the thing they built. And you know, one of the things is, you know, one of the weird things about venture with the holding private for longer thing, right, is now the holding period of venture is longer than the technology platform change cycle. So if you join halfway through, right, this is coming at you. And you know, in the old — yeah, 20 years ago, which I like, this would long since have been public. It would be trading as common stock and it would just get hoovered up like on that basis. It's like a lot of these late-stage rounds long since would have been public in another world. I think the biggest fear right now is something that was started 10 years ago. Is it past the point of, yes, rebuilding, and are you better off building from scratch than trying to tinker with something that was built 10 years ago? I think that's where the challenge is.
That's interesting. I mean, you've done some recent acquisitions. Like, it's interesting. It used to be my mental model was apps last longer because end users are pretty, you know, get kind of stuck in place and they keep them forever. And the infrastructure market moves quickly. But we've definitely seen some of the apps companies get stranded, right? And that whereas the infrastructure companies that have been able to evolve to link in — you're absolutely right — to link into the AI demand have been able to actually kind of go from strength to strength. I mean, look at Datadog. You know, we were investors in Grafana, privately held. You guys are killing it, but you're co-attaching to the AI trend. And the poor little apps companies, there's just nothing to co-attach to to give you lift.
I think that's — I think it's a moment in time. I think one of the things which we all know, we don't talk about it too much, is AI still has a lot of false positives. There are too many edge cases that it can't solve. You still need grinders to solve the edge cases. The Waymo doesn't drive on the street without tons and tons of people being paid for labeling and tens of billions of dollars to find every tree and mark it. So it's the equivalent of sort of the Waymo marking the tree — that's a tree, idiot. That stuff needs to happen for a lot of enterprise for AI to be effective. So I think until that process — sort of we go through that process, we sort of leverage AI, put all the hoops around it from a machine learning perspective, there's life for infrastructure businesses. And the choice we have in the next five, six years is: can we build all that plumbing, all that guard railing with machine learning and chain the core engine to some version of AI at the right price? We survive. If you don't, then, you know, maybe Bending Spoons it is.
Bending Spoons it is. On Bending Spoons it is, those kids. Okay, leave us on.
Now, final question before we move on is just like, does this put a marker in the ground in terms of enterprise value for companies like this? If you're a Notion that raised $10 billion last time, how do you feel looking at this? If you're a Monday.com — again, two products with similar motions — it was a shocker to see it, right? Especially the way everybody presented it, right? Enterprise value and all this. But Rory's right. It's market low. It's market low. And...
I think one of the things that's going to happen either like the Leo...
What's the hedge fund guy? Sorry, that we might not even talk. We already forgot about him.
Okay, I already forgot about him. Okay, so I think one of two things is going to happen. We're going to forget about Airtable tomorrow because other stuff's going to happen.
Or what I think might happen is this is the one where people capitulate, both founders and investors, where they say, look, folks have already had markdowns since 2021, but they're not consistent. This deal in many ways was everyone capitulated. The late stage got 1x, the founders made 150 — a lot less than they thought, but certainly enough to survive even today in San Francisco with rents up, right? Everyone said they capitulated to the markets. And I think we're also all in board meetings where we're seeing the opposite: 30% growth at nine figures, where we're going all in, guys, right? We're 20% growth. But we may see a quiet wave of Airtabling. It's time, guys. It's like how we did it. It's time. It's time to compete. He's a great founder, but like that time has moved on and it's time to capitulate. And that's a question right there. It may create more conversations or it may be forgotten about in three hours. Not sure which. But it was a jaw-dropper for a brief moment in time, like losing most of your hedge fund during your wedding. But we move on.
Well, I mean, we'll talk about that. That's a brilliant transition. Leopold Aschenbrenner, famed wonder kid who wrote the situational awareness piece, which was an incredible memo that then he parlayed into a $225 million vehicle that at one point had $4.5 billion of assets. Really rode the wave, so to speak. He did it with FX leverage. And in the past week, it kind of came crashing down, and then Ken Griffin and Citadel bought his public book for a reported $1.6 billion. Ken has made out like a bandit, reportedly making about $300 million on the back of it in a very short amount of time. How did we think about this? He was the wonder kid of the AI wave.
I mean, I think he was absolutely right on the trend. I mean, absolutely right on the trend and remains to date right on the trend. In other words, the data just last week about capex absolutely supports his memo. So conceptually right on the trend and then absolutely wrong on portfolio construction. If you accumulate a portfolio of high-volatility stocks with FX leverage, the math makes it clear your probability of getting wiped out once is just very high. It's as simple as that. Absolutely right on trend, absolutely wrong on portfolio construction. It's almost like it was inevitable.
I'm really sorry. How do your investors let you get to that place? Because you made him 10x last year and you probably don't question anything, and he did amazing, you know. And which of us really — let's ask ourselves honestly — when someone makes you a 10x, do you sit there, is your first response, yeah, but what can go wrong? I was like, ooh, can I put in more money? You know, that's what happened. And my wife said when I was talking about it, she said, I don't want to see any schadenfreude. She was like, there's a lot of schadenfreude, laughing at the... I feel sorry for him. It was a tough call to have to go through that, just to put it out there on a human level. I mean, he was clearly wrong on the bet. But that was a brutal week.
Will he be okay? It says that he's still managing both a private and a public, but he's got his Anthropic position. And then other people are like, oh, no, no, lawsuits are coming and it's not going to be okay. Is he going to be okay?
I think he'll be fine. I promise you he's not going to be caught at the same place again. So, you know, good news, he's learned a lesson and he's going to survive to sort of live.
I'd ask.
I mean, Harry, it's your job to mentor some of these younger kids like Leo. So I think maybe you could step in. What? He's 26 or something like that.
25. Yeah. So I think you've got — it's time for you to become the elder statesman in the industry and start mentoring him on leverage, when to lever up to 4x, when not to. I mean, in all seriousness, I mean...
I need someone smart. I've read it.
Grouping plants and, you know...
Expanding homes with, you know, multiple people living in the same house. Don't bother him.
I assume his LPs or his investors knew this was a highly levered fund, right? Am I wrong, Rory? I mean, if they know it's FX levered, then they know there is black swan issues when there's short squeezes and others. And I don't think that his investors should cry if they knew how it was playing. I mean, my limited experience as an LP in funds with leverage, not quite this much, is, you know, it's not free.
I have a feeling — I have a feeling his LPs didn't lose any money. If you are up 440% and you go down a billion, you're back to where you started. So I think it's fine.
The interesting thing about that — not quite, because actually this is where I think it could get a little hard. It all depends on timing, right? Because the hedge fund things are weird. If you came in early, you made a ton of money and then you lost two-thirds of what you made and you still made money, right? Brutal comedy. If you came in in the last six months, you might have been wiped 80%. Right? Because hedge funds, unlike venture funds, people come in at different times at different bases. So I think the real — and I thought even perhaps Jane Street had put in some money recently, but a bunch of people had put in money, and if you bought in in April, May or June, you've been wiped. And then to your comment on those people — I mean, the litigation — I mean, I think fundamentally, yes, he will be fine. And there's a long — Larry Fink, who, you know, founded and runs BlackRock, had a blowup early in his career. There's lots of people who had blowups early in their career. Nikesh has worked for one of the most aggressive risk-taking human beings on the planet, that's SoftBank. He's seen ups and he's seen downs. So you can survive...
What? What's — 4x is for babies.
Genuine comment here. So you can survive and 10 years later be well successful in France. I think the crux of the near-end question will be those investors who came in late, who, let's be really direct here, will be pissed. You put money in a hedge fund in April and you lose 90 cents on the dollar in July, you're going to read the docs real carefully. And if there's any disclosures that weren't made or if you've done something beyond the remit of the fund, you will have liability and all this will happen. In the end, it'll all — this is America, everyone will sue everyone and it'll all be fine. But there will be some dynamics going on now because if you can imagine going back to your investment committee and saying, you know, we did a hedge fund, but it appears it wasn't hedged, right, and we lost all our money in a week. But if you're Collison on the other hand, you came in on day one, you still made out great.
Well, that's a relief. I was worried the Collisons would be short of cash, so that's good to know that at least their whole... Rory, I don't have any cash in Silicon Valley. Well, they'll be fine. They need money to buy PayPal, so...
They do, and they need money to buy what was it? OpenRouter. I mean, they're doing such a lot. I mean, actually, we were just talking about it. It's been interesting to see them do all this corporate development while still private. Just super interesting in terms of, you know, a lot of this stuff would be marginally perhaps easier with a public stock, but...
I had a CEO of OpenRouter on the show on Friday, Rory. So there we go.
I'm excited for this next topic because with Nikesh, I think we've got the most pressing person. Anthropic's models breach three companies too. This is obviously on the back of the OpenAI and the Hugging Face debacle.
Really? Anthropic breaching three models. Also, is this just like the most epic beginning of like a bull run in security? Like first and foremost, this is all flex, right? They all want to tell you how good their models are, how powerful they are. So it's kind of bizarre because normally if you end up breaching somebody's infrastructure, it's not a good thing, but we're all saying, look, look at these models, they're so powerful. So fine, granted, they're all very powerful. I think the first things our friends at Anthropic and OpenAI should have done, which I've told them, just point your models at your own sandbox to make sure the sandbox doesn't have any zero-day vulnerabilities and make sure your sandbox is your first capture-the-flag exercise. But they decided to give a target and say, go to the wild, persist, take as long as you want, or go capture a flag. So fine, you know, we have these models which have these capabilities. I think the challenge we have from a cybersecurity perspective is we're finding vulnerabilities which would take us days, months to find. The average time to patch a vulnerability or zero-day vulnerability found in the wild is 55 days. Just think about that. These things are finding vulnerabilities in split seconds and then turning around and building an attack on the back of that. So I think the fundamental speed at which cyber attacks will happen and need to be defended changes. Now, this is good for us. It's kind of like, you know, the sound of revenue. But I think from a more fundamental perspective, I was thinking this capability is going to show up in six months. I think I said that with you, Harry, and it showed up in four months. And I think in two, three months from now, open source will have distilled all these capabilities. We'll find open source models out there which you can fine-tune if you're an attacker to actually do this from a task basis. So it's going to change the game.
How are your enterprise customers reacting? Because this feels to me like the mother of all — I mean, security sells on fear and this is terrifying. So what are you seeing in the enterprise customer base when this is knowable?
Sure. Look, the good news is the flex that Anthropic did with Mythos has every CEO talking about Mythos. I spent eight years trying to get CEOs to talk about cybersecurity. Couldn't get them to do it. And Dario did it in one fell swoop. So this is goodness. He saw everybody like all hot and heavy about Mythos and the capabilities of Anthropic and how these models are going to go attack your infrastructure. I've never had so many CEOs call their CISO and say, are we ready? What's going to happen to us? Well, the answer is you're not, because what being ready means is that I have no vulnerabilities either in my code, any vendor that I've got deployed in my infrastructure, any open source I'm using. That is fundamentally not true. Now, we found 14,000 vulnerabilities in open source in the last 14 weeks testing open source packages. So it's a bunch of stuff that's been used out there. So, A, every company has vulnerabilities. They've got to figure out a way to patch them. B, these models will figure out misconfigurations. If you've left the door open, if you've got a device configured wrong, if you've got a piece of software configured wrong — and there's tons of that out there. Not every IT person building infrastructure or configuring infrastructure is a genius. There's misconfigurations. All these things need to go away. So at the base, as the face of it, a lot of organizations are going to have to go fix a bunch of these vulnerabilities and misconfigurations. On the flip side, even if you fix most of these, the bad guy just got to be right once. So he's going to find one, she's going to find one, to get into infrastructure. The question is, what is your time to detect and respond in that circumstance? The average time to detect and respond is four days. How are you going to get it down to a minute? So it's not a fear problem. It's a capability problem. It's an infrastructure readiness problem. And now it's come to bear. See, it's time to pay your taxes.
Yeah. I mean, that's the last sentence. I mean, you're right. We can argue fear versus thing, but what you're basically saying is the security infrastructure that you had a year ago is wholly unfit for purpose in the next year, and you, Mr. Enterprise Buyer, are going to be buying a whole load more stuff, or you're going to be the weakest link when these capabilities are everywhere.
Yeah, you said it so well, Rory.
I mean, it just feels so good. I don't mean to be...
I think you should be on the podcast talking about how people need to buy more cybersecurity. I'm just going to buy the stocks. But...
Now, Nikesh, can we get him some swag? I mean, Jesus, he's a basic... Give Nikesh a hard question.
I want to ask Nikesh as my — I want to ask him as my cybersecurity therapist. I had two Fable issues and they're internal security, but I'd love to get your — and you can make fun of me for this. Like, I've got — I pretend to have a thick skin. I don't, but I love criticism.
I already figured I don't have a thick skin the first 30 seconds of this conversation.
Okay, good. So I'm building an app for the SaaStr community. It's called SaaStr Connect to help with recruiting. The details don't really matter, but it's the biggest thing I've built, right, myself in this era. And I'm among other things, I've got a Google Doc. It's called Jason's Gems. It's my ideas on how to improve that. It's just ideas. They're just scratches, okay? No one's seen them. It's not ready. Just a side doc I keep. So the other day I went into Claude and I just turned on the Google Drive connector since it's one of the three primary connectors. This is not esoteric. This is not third party. And I never knew. It went in, scanned all my docs, found Jason's Gems, found the ideas. Fable then went and changed my code and my algorithm without telling me. Never got a notice. Never was told. Never was in a changelog. Never was anywhere. I only found out later when the agent flashed conflict with Jason's Gems when I was trying to fix something else. I mean, I'm not saying it's terrifying, but how can organizations deal with this fact when an LLM will go out and change your core code, your core corporate OS without even telling you? What if you have a thousand employees doing this? And this is just — oh, and the hack, the part I didn't tell you is the way it did it is it MCP'd in. So I had Google Drive to Claude to Fable to MCP, and so it was able to do whatever it wanted, probably thinking it should implement Jason's Gems, but it shouldn't have, and it never asked me and it never told me it did it. Is this scary? Is it not scary? Is this Orwellian? What happened?
The wild west.
It's wonderful. It's the wild west. And part of the challenge is the good news is that — or the bad news, I know which way you want to look at it. I think the small business entrepreneurs, people playing with their own stuff, are doing this without any regard for security.
Same reason you're on TikTok.
So people are doing that with no regard for security. They want to experiment with open cloud. They want to connect to all their stuff. They have no idea if all that data is being used for training. They have no idea what credentials are going to get used, what permissions these agents have. And that's happening all over the place. On the enterprise side, there is some cohesion around it. I think the most obvious ones are people saying you can't use this. Now, that only encourages people to use it more. So, but there is this stream of thought saying if I don't allow you to use it, I have time to go figure out how you're going to use it. The challenge you have, Jason, is — and I think this is burden. You know, when the Wright brothers built a plane, they didn't invent TSA. That was not the first thought that crossed their mind. No, TSA came a lot after. So you don't think about security when you start playing with new things and cool technology. And that's what's happening. You're seeing people play with open cloud. You're seeing people play with agents. You're seeing people play with all this stuff with LLMs. Everything's happening. LLMs are training on data if you're not careful because that's the value of giving. And what is the adage? That if the product is free, you're the product. Well, guess what? So we are the product of all these post-training data that has been collected by every model out there on our consumption, which is not regulated, ring-fenced to the enterprise use case. That's why enterprises are paying a lot of money for all the free stuff that consumers are getting. So we are the product. It's learning on all your behavior.
Is the security architecture a year from now — is it more the same, better, faster, or is there some new things that you just have to do utterly differently to protect? I mean, is it just same problem, just higher velocity, or is it, oh, we never even thought about that before?
Yes, both of the above. Okay, both of the above.
Look, I mean, fundamentally, cybersecurity is kind of a very straightforward thing. If it's a known bad, I'll stop it at the door, right? You show up with guns blazing, I know who you are, and I've got security at the perimeter. I'll stop you.
Yeah, it's a known bad, I'll stop you at the door.
The problem is no cyber attack happens because I stopped a known bad. Every cyber attack happens because...
You didn't know it was bad until it got into your infrastructure. The question becomes, if you know it's a known bad, you stop it at the perimeter. If it gets through, how quickly can you find it and stop it before it creates harm or damage? So from a cyber perspective, you want to be in the perimeter business. You want to be on as many perimeter endpoints in the world as you can because that becomes a sustaining business. The more perimeters I'm on, the longer my tenure for my business is. So I'm on endpoints, I'm on devices, I'm on servers, I'm on firewalls. I'm protecting the perimeter from multiple infrastructure set of components in the world. That's good. That's kind of good. Now the question is how quickly I find known bads will change using AI, right? There's a concept of data classification. You had to write static rules. Guess what? An LLM can sus it out much faster from a content perspective. You know, we track every malicious website in the world. Can AI tell me it's a malicious website much faster? Yes, it can. So the ingredients of my perimeter security will change using AI. The act of stopping things in line will still be needed. So when people tell me, oh, OpenAI is going to eat my lunch or Anthropic is going to eat my lunch — guess what? They're in no perimeter security scenario, which means I still need to block the bad guy. They need to be the ingredient in my product. They're not going to take me out of business because people have all kinds of infrastructure on the perimeter. The other part is if you want to sus out all the bad stuff in your infrastructure and find out the bad actor — guess what? Imagine collecting all your enterprise data and running an LLM right on it...
And say, find me all the abnormalities. Find me behavior that you've never seen before.
Now I'm ingesting 19 petabytes of data a day. Think about it. 19 petabytes of data a day of enterprise data to look in it for anomalous behavior. I have machine learning techniques. I have static techniques. I have rules that I look at it. Guess what? I'm going to throw some LLMs in there just for fun to see what they find. Now, if I can find the unknown bad actor in your infrastructure much faster using LLMs, I can detect it and block it. Right now, we run at one minute.
Machine learning. This is a good thing. The only problem is I only have 1,200 customers who've bought and deployed it. I need to get the rest of the world to go buy it and deploy it. So that's the second half of the problem. The third part is there is stuff which is new which does not have any security guardrails that have been built. Agents. The world is talking about agents. We can have a whole episode, 90 minutes, on what are agents, what is really an agent, how do you give agency and how do you control an agent? People tell me they have identified stuff, but then I ask them, does it actually have agency? Like, what does that mean? I'm like, a Waymo has agency. They can drive you into the wall without human intervention. This is a bad problem. But most people haven't actually given agency to their agents. So they're running glorified workflows which are seemingly agentifying things. But when you start giving agency to things, when pieces of code can decide what happens next, we're going to have a whole different conversation around how do you secure those agents? How do you build kill switches? How do you intercept them in line? How do you stop them from doing bad things?
Yes, like Jason's agent, which is a bad thing, and took Jason's Gems, and now the whole world will find out what Jason's Gems are.
We said open, we said China. Whether we have comment on it, Moonshot closes $3.5 billion at a $35 billion valuation. And if it's free, you're the product. Moonshot's free.
I think one of the comments on the 'if it's free, you're the product' is totally true, especially on the consumer side. The interesting thing here is I'm not sure how it's true, put it another way, unless you're one of the — really interesting things about these open-weight models is the impact they're having and the ability to be a drag on price for the US, you know, closed-source frontier model companies. It's not as — and if you're running the inference as well, then I get the model, I get the business model. The model is free and the inference is how you make your money. It's not as clear to me long-term if it's possible to continue on a sustaining basis offering open-weight models without monetizing in some way. And we'll see what it is when people like Reflection and Thinking Machines start — when these models start to happen in the US. It will be interesting to see, you know, what the business model is of which an open-weight model is a part, right? It's definitely not, hey, download it, have a go, and you can do whatever you want wherever you want, right? I mean, look, open source has evolved the business model of support, so it'll be just interesting to see, you know, what version of 'if it's free, you're the product' emerges for these companies in the medium term.
I'm going to give Harry a sound bite. Good. Average intelligence is going to be free in the long term, and the average intelligence will keep getting better.
Exceptional intelligence will be paid for.
Can you give me some tone with that, Nikesh? That was all monotone. I want like drama. Come on. You got to deliver the sound.
I was watching somebody speak the other day, and they said if you whisper loudly into the mic, people lean over and pay more attention. So I'll say it again. I'm saying in the long term, average intelligence is going to be free, and the average intelligence will get smarter.
Oh.
But do you think we'll rely less on frontier intelligence? We won't need it.
Oh, no. We'll need exceptional intelligence. We need exceptional intelligence to discover the cure for cancer. We need exceptional intelligence to send rockets to the moon. We need exceptional intelligence to build a space data center. Those are exceptional intelligence tasks. They are still going to require exceptionally intelligent people or exceptionally intelligent models, and people will pay for it because the outcome is so spectacular. I don't think you need to pay $6 a million tokens to answer a call saying, how can I help you? I'm so sorry your network connection is not working.
Agreed. Yes, customer support will not be using frontier models.
Maybe. But my limited — listen, of course you're right over the long term. Right, in the short term, customer support is requiring more and more tokens to do more and more sophisticated resolution.
And guess what? Those are the primary candidates that all these open models are going after with open-weight fine-tuning, saying, I don't need hallucination, I need...
