Very into this. Very into this. Does this work? Yeah, let's hope it works. I mean, you're the star of the day, so we need to make sure.
The star always says, it's like the rich person is always telling you how poor they are. The smart person is always telling you how stupid they are. The star is always telling you you're the star. There's a personal equivalent of this I won't go into. We're in a PG audience, but...
No, please. I want to hear it.
I'm just kidding. No, just... Well, you don't want to hear it. I had to kill a few minutes because of traffic, so I exposed that I had always wanted to be on this stage as a comedian.
And you know, for some reason my day job took me in a different direction, but...
Well, you're doing pretty well in your day job. Maybe we all stick to our day job.
I come from a family where if you're not an academic you're a failure, which is...
Yeah. Like I was hanging out with my dad. Our CFO's dad was a very important person in medical history and created radiology. I'm sitting at home with my dad. We're having coffee and he's of course not listening to anything I say. And then I know it's crazy. And then I'm like, 'Yeah, Dad.' And you know, my CFO's dad was Dr. Glazer. And my dad knocks over the tea. He's like, 'You know Dr. Glazer's son.' I'm like, 'Yeah, Dad.'
Right. Yeah. You're on Palantir. Who cares? Right.
I'm like, 'Yeah, it's... Okay. Well, I think I'll go back to my day job.'
Well, you know, as you know, I grew up sort of an upper middle class Jewish kid in New York. So the fact that I was not a doctor, not a lawyer, not in academics made me a failure. So it's...
Child's table at the seder. Yeah.
Exactly. Let's talk about Palantir just for a minute. You guys are obviously crushing it. What's really interesting to me is what are going to be the most high-stakes questions that complex organizations are going to have to ask about where AI is really going to change the work that gets done. Alex.
Well, there's the first wave of AI, which really happened in the military, but then my version of it was partly classified, but you see it in Ukraine and other places.
We're private here. You can talk about classified things. Yeah, no problem.
But I think actually the real problem in disseminating the truth was the truth in America, which is the defining place for AI, which is also super interesting because normally you have a revolution and, like, I spent half my life in Germany, you'd expect a German version, a French version, an American version, but really you have America and China, and this is already completely unique. Because, yeah, I mean, if you think of other revolutions, philosophical, industrial, if you look at the history of Asia, for example, when Deng Xiaoping took over China, he immediately got industrial minds from America, Chinese Americans. And then Japan's rise vis-a-vis China, but these things were pretty intertwined. So Japan rose because it took over Chinese culture and then it took over Western culture of how to do industrial. This is a revolution that is basically, at least the original thinking and research is completely done here and then derivative advancement, fast follower, is China. So that's already super unique. Then that leads to a lot of confusion because the first wave of AI, which was you give us your data, we put it in a model, the model kind of...
Are we still in the first phase or are we moving to...
We're in the... I think we're both in the first and second phase. So a lot of people are in a phase of: you give me your model, I take your model, I run it, I chillax on paying you a lot of money. I get value on very easy use cases. It doesn't work on complex use cases and I may or may not be in danger of outsourcing my primitives, my knowledge, my alpha, what makes my business special, to a model company that will compete with me effectively and put me out of business. But it's this unique phase. So, like, if you just take a neutral example, why is Europe not scared of AI? Why aren't they adopting it on the battlefield even though they have all this information that it's the thing that works? It's because you can still look at the things that don't work and then say, okay, well, this doesn't work, it's not worth it. But then, so let me just get to your question, which is this is all backdrop for what is actually working and then what does it mean to work. The first big difference, like it used to be that the delta between a good software implementation and one that was second rate was real but it wasn't determinative for your business.
And so when we built Foundry, which is a data integration platform, which we're using with you, that would save you time and money and make you more efficient, it would make you A+, but B minus, which would take longer, was still in a range of: if you were better at marketing and you had B minus, or you had a high moat, like just say you're building a certain kind of missile, right? Okay. Yeah, maybe you could build them faster with Foundry, but you have a moat because it's hard to build this missile. And also, say you're a French company or a German company, the German government's going to buy your missile even if it's B minus because it flies and it's German, right? Okay. So we do the same thing, but so what happened, what's happening in the second phase of AI was, yeah, but your missile isn't going on target against the Russians if you do not have a way of putting it there, and that way is going to be an application layer with a model, and without that, interestingly, your B minus missile is a triple plus with this, and your A+ missile is useless.
So that's just binary, and the profoundity of that minimal example is something that we don't have in philosophical systems.
I was going to be an academic and I...
Law degree from Stanford, you have your PhD in philosophy. Your family's got to be somewhat proud of your academic accomplishments.
No, we can go back to that, but it's like, and my dad is like, 'You could have been something with that.' Literally, it's like... But I'm not joking. It sounds like...
You rarely have, when these massive things happen, from modernity to postmodernity, or what is it, let's just take an American example. What does it mean to internalize the First, Second, and Fourth Amendment? The First Amendment being our right of free expression, which is, first of all, the Constitution was given to us by a higher being, so it's already different than Europe. But then First, Second, and Fourth Amendment: right of free expression, right to defend free expression, which is really what the Second Amendment is about, and the right of privacy. These are concepts that are so radical it takes generations. So here you have something that's very... you now have a technology that will make a rocket, to use a very simple example, that was third rate, first rate, and deadly, or you have something without it that will take the first rate rocket and it's not useful. So this is true in every single enterprise, commercial enterprise. And what is it that is special about AI? So just take an example: you have unique ways of understanding how a market would react to a message. Yes.
Okay, you are going to... how do you share those insights with a partner where you only share the insights that you want to share and they want to share with you, and how do you augment them where both the data, the insights, and the models you run against them are sovereign, meaning unique to them, or could be white-labeled and sold to others?
Well, and that's one of the things we love so much about Foundry. Integration of our data cloud on Foundry gave us far more ability to do those things, and we're now able to onboard clients in hours that used to take months, but give them control. I'm going to pivot us back and bring us a little lower to the ground so most of us here can understand the vast majority of what you say. We talk about data sovereignty a lot. We have a lot of CEOs in the room, a lot of CMOs in the room. Alex, what does that really mean?
It means that, well, first of all, and this is a very advanced thing, and we're going to be able to augment this and then put models on it and then train the models so that the models reflect just what you know and do not expose it to the outside. So basically, okay, every business, what is a business? A business meaning something that at some point in the future will provide high quality revenue, meaning free cash flow. Okay. And why is free cash flow what everyone thinks about, analysts, why is this an important concept? Because it basically tells you you have something unique in your business that is valuable enough where you have pricing power so that you can charge more than the cost of the goods. Okay, that is a business. Every business in the end of the day comes down to that: why can you charge more than it costs you to produce it? Because you have some unique way of doing something, whether that's how you build it, how you produce it, how you distribute it, and how you market it. Okay? And preferably it's unique along the whole stack.
And the more unique it is along the stack, the better your financials at some point in the future will be. I mean, there's always a lapse of time, but I basically... I think the free market will get you to pricing parity over an 18-month period, right? Or so. And okay, so in every one of those things, the way you produce it, so supply chain, how you integrate it, what the final product is, what the aesthetics of the product are, and how you explain it to the market, you need to advance your unique capability, learn from the world, and never, ever expose to anyone else how you're doing it. Exactly. And the minute someone else can do any part of those things as well as you can, your pricing parity goes down and at some point your value goes down. I mean, these are like... a lot of times it's okay, so normal software is built to force you to adopt something that's parasitic. So they take every one of those things, turn it into a commodity, and sell it to everyone else. That's how you... we couldn't get financing because I kept telling these VCs, 'Yeah, but we're going to make our partners and clients happy.' They're like, 'Why would I?'
Wait, what? Happy clients?
No. Wait. When you want to start a company and you talk to VCs, what they wanted to hear was clients will be unhappy, but they can't get rid of you. Like they want to hear bad sticky, right?
Yeah. No, sticky is a metaphor for parasitic.
Correct. I get your data, I get it into something you can't get rid of. The thing turns into something I can sell to everybody else who then can't get rid of it. And de facto your multiple goes down and my multiple goes up and all of us are happy and hope at some point you realize you're sad, hopefully after it's too sticky. And okay, so that's how you get... we couldn't get financed because I kept telling people, 'No, we're going to make special operators more lethal and we're going to bring them home.' And they're like, 'But where's the parasite?' I'm like, 'No, we're not doing the parasitic thing.' And then if you look at the stack of what we're doing, Foundry will bring all your data together and protect it granularly. So you could share the data but not share what you don't...
You get to decide what you share and what you don't share with Foundry.
Yeah. And then the application layer on top of it will allow you to do the same thing with open-weight models or closed-weight models. I mean, closed-weight models you need to get them to post-train, but either way you are not going to be seeping your alpha to everyone else. And so at every stack, every part of the stack, you augment what's particular about your business without losing that particularity by giving it to somebody else who's antipodal with that. And that, for those of you who are like VCs and others who besmirch us, we don't let VC... whatever. In any case, I get along with them now that I'm standing on their head. But it's... who are basically, they just want to finance. Someone comes to Palantir for two days, they'll give you like $10 million to start a business, like planting plots. But in any case, the radical thing here is the obvious nature of this, right? And by the way, just to... why did we do this? We did it because we knew we could not win on popularity. So that... if you can't win on popularity, you better win on alignment.
And what I was literally just going to take exactly what you're saying to the next level. One of the things I love so much about the elegance...
You come over to my family. I'm not used to this love. I'm not used to... When did I get all this love?
I can give you later. I promise.
Yeah, please. Please do. I won't believe you if it's positive.
Exactly. This really sits inside of your entire concept of forward-deployed engineers, from the way I see it. Like we have your FDEs in our office every day working with our FDEs.
Well, there's this concept. I mean, another reason we couldn't get financed and every single person made fun of us is we were like, okay, to extend the unique nature of the enterprise into our product and into the enterprise itself, we have to send in people who are highly technical and understand our product and then understand your enterprise so that we can augment our product specifically for you. But that's so different for a software company.
Like we pivoted a huge part of our business to follow you guys on this because it's so freaking efficient.
Yeah. Well, it also gets you, again, it allows you to basically bespoke-build what we have to exactly who you are. And then over time we're training your people. Like we're not a body shop. So we want to train your people to be your own FDEs. And we do that, but we have 4,500 people. We're not going to have 50,000 people. So we need... this is where we need partners because we have to work through you because we're an artist shop. We manage a certain kind of person very well. That's what I do for a living.
