The Exchanges

Q So there was some wisdom to figure out which bucket it fit. Is this just for this vertical or it could be generalized? So could you give us like an example of what that looked like in terms of the products and verticals and what fit in one bucket versus the other one?

A Yeah, I mean, probably the, the sort of like most basic example here is, is sort of the invention of the Palantir ontology itself. And so when we first started talking about working with, you know, the U S government and specifically working intelligence, you know, should we have a database table for people and a different database table for money and a different database table for this. And this is super obvious. I think at this point, if you, if you go down that route and you try to deploy to multiple people, your, your database doesn't make any sense. And so, you know, the, the change here would say, well, we need to pull this up to a higher level of generalization. And instead of thinking about specific types of objects, Um, we should allow that to be defined per customer by the forward deployed engineering team. And so that's the sort of origin story of where Palantir famously got its ontology.

AI assessment note: “most basic example here is, is sort of the invention of the Palantir ontology”

Q Yeah, but you wouldn't, don't try this at home. Mindset, right? Like now everyone's sort of, it's become, like Diana Dana said, it's become very commonplace. Has that, one, has that surprised you? And then two, like, why do you think that's happened?

A This was absolutely a surprise to me. That, you know, my first, second, and third pieces of advice to people who are thinking about trying an FDU strategy is like, don't, Don't do this at home. If you can avoid it, like it's, it's probably bad for you. Probably you're going to end up doing services. And then only if you really try hard not to do it and fail, then, well then maybe actually it's a moat for you. If it's the only thing that can possibly work in your market. So what's special about this market, right? Why does the AI agents market, uh, work this way? Maybe the, the starting place is why did Palantir have to adopt this? The Palantir market is not One coherent market, right? So we were working with national intelligence agencies, with national law enforcement, with the military. All of these organizations had some similar projects, right? But even, you know, the difference between a counter-proliferation workflow and a counter-terrorism workflow, one you're trying to figure out, you know, who's building bombs and the other one, well, who's building nuclear bombs and who's building IEDs. And those are actually quite different in terms of how they work. And so there's this incredible heterogeneity, and the market, you should really think of the market as different segments. Inside each segment, you can build something, and, you know, the crossing chasm story a little bi…

AI assessment note: “This was absolutely a surprise to me.”

Q And how does this play out in practice?

A You'll have a product and you go to a new customer site. You, you start working with a new customer and the, the problem that they want you to solve is not a problem that you've ever solved before, but you believe that it's one that with a little bit of work, maybe a lot of work you can solve for this particular customer and you'd be making a huge impact for them. You'd be delivering an outcome to them that would be extremely valuable for them. So you take the product that you have and the FDE with help from the product team figures out how to deliver that outcome, how to build that use case, how to, you know, deliver the piece of software that you've built in a way that actually works for the customer.

AI assessment note: “You'll have a product and you go to a new customer site.”

Q Some, like, Don Draper, like, who wears a suit and has worked in the DOD for 20 years and, like, takes generals out to Steak dinners and things like that. And that's actually not what you guys did, right?

A Well, I mean, there's two angles as one is, uh, we talked to a lot of those people early on and they said, why the hell would I work with a Silicon Valley company when I could work with, you know, a big five defense prime? Uh, and then even when we talked to people who, you know, seemed like they might be successful in this role, it was just very clear to us that they wouldn't mesh with our culture and they wouldn't actually be successful. And when we tried doing something like this, it almost never worked. And so, what we found was very different, and, and I think the difference between sales-led product discovery and FDE-led product discovery is that sales-led product discovery, you're talking to people from the outside. And again, this is important very early on, but it's not as effective as the FDE-led product discovery, where you're solving these problems from the inside. So, you know, the scope of a, of a traditional implementation might be You start with something that's pretty close to what the product does, but you want to be solving one of the key problems that leadership has identified. If you're not solving one of the top five priorities for the CEO, it's probably not going to work. They probably won't have the energy to persist through the much more challenging route of getting effectively a new piece of the product built in a way that worked for them. Then once yo…

AI assessment note: “we talked to a lot of those people early on and they said, why the hell would I work”

Q So in the context of how all these FDE companies price very differently based on outcome, how does that fit in with now the culture doing demos? Because there's this thing in, at least in SAS, or I used to get this pushback from my engineers, demo-driven product development, it would be sort of looked down upon. But in this case, it's different for FDEs, right?

A One of the interesting things that happens there is because you have to go repeatedly show this to new customers, you're forced to give these new demos. But, but actually I think demo-driven development works really well if you have the right kind of product. So, you know, in the early days of Palantir, we actually had one demo. It was a flow where you're, you know, stopping a terrorist plot. And we started this with, you know, just one of our features. And every time we integrated a new feature, we had to think to ourselves, how do I show that this new feature is actually helpful for the analyst who's going through this demo, who's stopping this plot? You know, when we integrated a histogram, we had to say, well, how do we actually use this? How does that work with the existing features that we already had? And we went this, you know, we integrated a map and we had the same question. And if you think about the world from what am I building? Then, you know, you're thinking about your capabilities. You might think of each of these features individually and how to build the best, best version of these features. But when you're building a demo, you're thinking about it from the customers. Perspective and a really good demo is something where you show it to the customer and you are creating desire. In that customer for what you're doing. They have to see what you're doing and just …

AI assessment note: “actually I think demo-driven development works really well if you have the right kind”

Q So the, the common knock that you hear on this from people who don't really know what they're talking about is like, oh, it's just consulting dressed up with fancy marketing speak. Why is that wrong?

A I think before I say, I don't want to tell you glibly why that's wrong, because I think there's actually a real risk that it's right, right? And I think, you know, if you, if you go back to 20 15 and you talk to people about Palantir, maybe you would hear two things. One, that Palantir is evil. Um, but the second thing you hear is that it's a consulting business that is never going to scale, you know, that it's actually like a bad business. It's not a software business. And we spent a lot of time trying to understand whether that was a correct Characterization or not. From a business model perspective, one of the key things that you will see, that you should see, is that it may be the case that you're, when you go into, you do a new deployment at a customer, that you're actually losing money early on. As the longer you're at the customer, first thing is your product, because of the product discovery, gets better suited to what the customer does. And so you no longer need a large team of people at the customer site figuring out what the customer is doing, you know, paving, you know, writing that. Code. The second thing is that you should be earning the right, as Sean would put it, to have access to more important problems at the customer site. And so you should see basically that your cost per value of the outcome you're delivering is going down. And so your profit margins start…

AI assessment note: “your product, because of the product discovery, gets better suited”