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Palantir CEO Alex Karp on Tokenmaxxing & Taste

AITBPNJune 4, 2026 at 10:46 PM23:33
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TL;DR

AI is rapidly transforming enterprise operations, but success hinges less on raw model power and more on judgment, integration, and trust, amid rising political and regulatory risks.

KEY POINTS

Shift from hype to practical deployment

Early excitement around artificial intelligence has given way to a more sober phase focused on real-world implementation. While the technology is widely accepted as transformative, many organizations are এখনও struggling to translate its capabilities into consistent operational value. This gap has exposed the difference between experimentation and scalable business impact.

“Token-maxing” and shallow usage concerns

A growing issue in enterprises is overuse of AI tools in low-value ways, such as excessive querying or redundant automation. This behavior, likened to compulsive usage, creates the illusion of productivity without delivering meaningful outcomes. Companies are increasingly seeking ways to curb inefficiencies and refocus AI use on tangible business problems.

AI enhances but does not replace core systems

Large language models can accelerate coding, analytics, and workflow automation, but they do not replace the underlying infrastructure required to run complex organizations. Critical systems—such as supply chains, defense operations, or industrial processes—require structured data environments and long-term integration that AI alone cannot provide.

Security and data control remain central

Enterprises handling sensitive or proprietary information are reluctant to rely on public cloud AI systems. Concerns around vulnerabilities, data leakage, and compliance are pushing companies toward on-premise or tightly controlled deployments. The ability to secure and manage these systems has become a key competitive differentiator.

Market expansion through competition

The surge of new AI companies has both cluttered the market and expanded it. Increased competition validates demand and encourages adoption, especially in sectors like defense and government. However, it also introduces confusion as firms struggle to distinguish between superficial capabilities and deeply integrated solutions.

The importance of “taste” in AI adoption

A critical but less tangible factor in successful AI deployment is decision-making quality—referred to as “taste.” Organizations must identify which problems are worth solving and how to apply technology effectively. This human layer of judgment cannot be scaled or automated easily, yet it determines whether AI investments deliver value.

Public skepticism and reputational challenges

Despite strong investor enthusiasm, many AI companies face distrust from workers, operators, and the general public. There is a growing disconnect between financial success and societal acceptance, with concerns that AI adoption prioritizes profits over practical or ethical considerations.

Rising risk of regulation or nationalization

Political momentum is building around stricter oversight of AI, driven by fears of economic disruption and lack of accountability. If companies fail to address public concerns transparently, governments may impose heavy regulation or even consider nationalization in extreme scenarios. This risk is compounded by policymakers’ limited technical understanding.

Workforce impact depends on upskilling

AI is not inherently reducing the need for workers but is reshaping roles. Employees who are trained to use AI effectively become significantly more productive and valuable. However, messaging that emphasizes job cuts over capability enhancement risks fueling political backlash and accelerating regulatory intervention.

CONCLUSION

AI’s long-term impact will depend less on technological breakthroughs and more on how organizations apply it responsibly, integrate it securely, and maintain public trust in an increasingly volatile political environment.

Full transcript

Yeah. Yeah. Get in here close. This is good. >> Feel good. Okay. Feel good. >> How is it going? How is AIP con this time around? What's changed? >> Um, well, we we're in a phase. All each one of these things like marks a time. First of all, you guys are even more baller, more successful. >> Thank you. Thank you. >> Some tendies in your pocket. >> I think it might have been part two. We got to say thank you. >> You know, it's like blew us up. Biggest guest. >> You're looking bigger and stronger somehow. Hey, are you more attractive in your personal life now? randomly. >> Well, here's what we're actually focused on. Dead hangs. >> So, you came on last time. You said your dead hangs around like 5 >> Oh, no. It's It's Well, it's plateaued in the last couple months at 5:30. >> 5:30. Okay. So, we The thing is like people are going to hear that. They're going to think hanging on a bar. You got to go and do it. The audience has to go try to do it. We've started doing it. We're still in the >> under between Yeah. between >> somewhere around a minute 30. You feel like your tendons are going to rip. 30 130 dead hang is respectable. Okay. >> 2 minutes is super elite. >> It doesn't feel respectable when you have the five minute number. You're looking at the bank strength matters. No. Um the the the thing is I don't want to go into rabbit hole in training. The single biggest mistake people make is they try to hang every day. You need recovery. It's like anything else. So if you want to mimic and get progress, you just do what I do, which is once a week you hang as long as you can. Doesn't have to be super macho. And then that's your day. So like just say you can do one 30 >> but multiple sets or >> no no you know one day a week you do your maximum >> max. >> Wow. >> So like let's say you could do two minutes. Okay. >> You try to do at least 1:30. You fight to get to 1:30 but you don't fight to get to 2 minutes. Got it. >> That's your dead hang day. And then you can basically [ __ ] around the next day. Do whatever you want. Don't overdo it. But you could do two times one minute with a long break. >> And then can you just screw around do less and less and less. two days before if you two-minute dead hang you do like four times 15 seconds the day before you take off >> and you do that just keep doing that and you're dead what the mistake people make is they hear my ball or time >> [ __ ] that guy I mean the mistake you're making is not doing a course this could be a whole new revenue revenue line of >> pound you guys have for you guys call in so um yeah I mean the dead hang is a it's like And also some of it's genetic. Like my other metrics are elite, but that this is somehow alien territory. >> God-given gift. >> What about uh what about breathold underwater? >> I don't do that. And I'm not sure I have like I grew up swimming. I think I'm weaker at that. Like I bet you I'd be in your guys. >> I I'm a dive master. I can hold my breath for three minutes. >> And I'm just Yeah. I'm just Yeah. So I think I think you'd be crushing me on that honestly. But you have like the lung capacity of a wave. That's true. That's true. I mean like you got like you guys not moving and not using it's like you're like like you're like a like a like a whale floating out there under the ocean waiting to surface. True. >> So no I say I'll tell you the difference. Uh, and god, they're always minding me out there. But like, okay, when we first met, it was like AI, it may be real. Okay, then I would say somehow until about two weeks ago, >> there was like a holy [ __ ] this is real, but >> somehow it's not working, but we're not allowed to say it publicly because we'll look stupid. Yeah. >> And then there's a lot of investor hype. Yep. >> Um, there still is like investors printing attendees. So, you have the investors on one side. I think people realize it's real, but you know, it's like, you know, you have the whole token maxing. Yep. >> And people are on to that and then so there's a whole value lecture there. Y >> um >> uh you have a political situation >> um where you know people who do not understand basic economics are winning the political argument. So you can you could we could talk about where AI >> there's a lot here. Let's break it. Let's break it up. Let's start with the token maxing thing. Let's start with what's what's real. Uh how are you actually thinking about deploying AI? >> First of all, what what is your what is what is Palunteer's philosophy around token consumption? >> Well, like we okay, we have a product that will allow you to be I mean internally it's called something but externally but really we call it the demastatory like get off masturbation thing. internally. Sure. It's like people are just like >> print like sitting there all day kind of like a porn addiction and enterprises are like okay we knew this we believe this will create value but we cannot have people just like some people >> checking the weather with it just like and just re rearranging deck chairs on their personal Titan. >> It's literally like porn like people are like full on >> it feels it feels so >> yeah toolshaped objects tool-shaped objects you're looking at more than you want. You hope no one notices. You're kind of before dinner. >> It feels productive to have every email classified. >> Here's what it comes down to. Like business problems >> can never be I mean sometimes they can be solved purely with money and just spending more. But very often >> actually I think it's the opposite. So just to give you a weird anal. >> No, and I was going to say very very often it's more the opposite where it's about figuring out the right way to do something and then you can use capital to fuel that process. But >> let me give you a thing that is too generous for you guys. Okay. It it it's taste plus money. >> Okay. >> And there is no like AI like if you look at like pick any issue you want to talk about token mechanism maxim maxing uh what's going on with deploy codes are other people going to build ontologies why are why why does the our political class not understand AI especially in Europe? It's like yes because all these things can be scaled in a very valuable but largely going to commodified way but you can't scale the taste of like what is the business problem you want to have to solve and need to solve at the end of the day whether it's in the for whether it's the Ukrainians fighting the Israelis commercial entities it's there's somebody sitting there who's like okay but this problem is valuable this problem isn't and once that value that problem is always has that problem >> always almost always but not always has attributes. So there are some problems you could solve with this like I want to write a report on GDP growth in China. Right? Okay. But if it's a problem that requires a knowledge store like I want to understand the specialized way I underwrite. We're going to have a guest here. I want to understand the specialized way I drill for oil and gas that's both legal, ethical, and reduces the cost of production. I want to change the the the supply chain of my industry. Whether that's military or whether that's building boxes or whether that's cars. These things require actual precise ongoing processes. They are enhanced by large language models. They are not replaced by large language models. And then you get to security issues like but for us like the whole myth of things is just a boon because like yeah we could take any model their model open model >> sure open model we can identify we can now identify uh vulnerabilities at like 10 100x. Yeah. But then who patches them? >> Yeah. How do you patch them on prem? How do you patch them on prem so that your specialized knowledge stays on prem? Like if you're any business or intel services, a lot of these things are very similar. Like you're not putting your classified data in a public cloud. Same thing if you're like you have a special way of farming soybeans. Yeah. >> But you're not. So it's like how do you have how do you so all these problems are exposed identified and then you always have a thing of where's the charisma which people really underestimate and it's it's not global there's no global charisma now like so right now the large language models are very frontier companies are super charismatic with investors >> I'll give you some news they're >> super not charismatic with enterprises and the people like in a way >> even with enterprise >> no no I mean it's >> because I understand what the No, no, no. The enterprise people. I have a secret. I have a secret. Like, every company has a secret way of selling. You know what my secret way of selling is? Don't even call. Don't, don't come talk to us. There's a frontier company. Go spend two days with them. And if you're lucky, after you're done, I'll let you in my door. They're like clamoring. They're like They're like, "Hey, I'll take your bad brand." Which we have a great brand in Enterprise, but like it it's like it's like secret knowledge because the investors love this. They're like, "Hey, my stocks are all up. Everything's up. I mean, Palunteer's done very well. But it's like and you know you guys are doing very well I imagine right and it's okay we're we're you know we can but I'll tell you what you go down the street you talk to a marine you talk to a bus driver you talk to the person who owns the bus driving company >> they are not happy do not like these people token maxing that it looks like masturbation at their that's cost them money they they're like and honestly then you have something we're not allowed to talk about in this country likability Like a Palunteer, we have I think we have like 50 100 million global fans. We have like 5 million people that wake up in the morning literally calling me Satan. >> Mhm. >> I didn't know I had that kind of >> warm hand. But uh you know it's like that's what they believe. >> Yeah. >> And like and they really believe it. Okay. >> What people are not allowed to really address is like we have fans and enemies. >> Yeah. >> Yeah. >> These people polarizing. >> Yeah. We're polarizing which means both sides. Yep. >> These people have one side. >> Yep. >> They're just It is. So it's like you and it's like it's a really >> social media companies too have the same problem. >> Yeah. >> Everyone uses them but no one likes them. >> Yeah. But but then they also live in a circle and that circle's printing money. Y >> So it's like you know when you look in the mirror and you just printed a lot of money >> you look pretty fresh. Is part of it is is part of it that that some element of the technology let's just say LLMs is so magical that the companies involved that the companies that are making and selling frontier intelligence can be bad at a bunch of other things and still grow >> well no no they are magical at a certain kind of thing allowing you to write for example code now that code doesn't can't be used as a knowledge store so if you look at code in like three different ways like just using pound jersey as a model we have code That's basically infrastructure. So what what are the Ukrainians using? What is the department of war using? What do a lot of our enterprises? We call that primitives. It's basically hardcoded things that that understand the world low way do you do? It would take millions of technical hours and an understanding of all these enterprises to do it. So it's it's much more like how do you build a steel beam? Then you have like code that is written by FDs. >> Okay. So that's kind of managed. It's the reason why FDAs work. The secret is it's actually managed on something that we as a product. So you're writing to a code base. We're managing that. We're increasing our product. It's not just random people write. Then you have let's call it free code. >> That free code is that's magical. Like you can do it very quickly. It's almost right. It doesn't have to be exact >> dashboards financial stuff probabilistic stuff where you you have to get one analysis. >> It was magical. By the way, it's magical. It not only creates and it's magical in a way. And I know people don't like the porn thing, but it's also addicting. It's like, you know, it's not good for you, but >> you know, it may lead to damage. >> One more dashboard, >> one more time. It can't hurt that much. I know my doctor says it I shouldn't do it, but it's like it's like that, right? And you just keep go and like and if you're involved in the that thing, you're also making money. >> Yeah. >> And then last not least in certain circles like if you have you want to be a Russ researcher or you believe essentially it's a religion. So like you know and like one of the things is very charismatic especially to people who've never had a religion because all of a sudden that hole in your heart that was yearning for I don't know I would say you know a a established religion Judaism, Christianity, Islam is like being filled. >> Yeah. >> And and all the answers are there but it is very very successful at doing things that a company has to do. >> But it is not actually solving the problem that enterprises are. It is now it can solve them. That's the trick. It's not It's not binary. It's not like you can't say they're not valuing. They're totally putting our business on steroids. Like without LM, nobody would be talking about our ontology, about Apollo managing SEC exploits, about our ability to manage an enterprise essentially as turning all these companies into FDES. These deploy codes, we love them because now every company wants to deploy code. You know how you do that? >> You replatform on Palunteer and like and it actually works. It's not somebody with no taste, who's never done enterprise, who has no earthly clue how these things work, who's done something else, and is like just imagining they know how to do it, right? >> Yeah. as part is part of this moment quite entertaining for you because you guys have been working on understanding businesses at a deep fundamental level creating you guys have effectively been doing the work that it that people are promising AI could do for 20 years now but actually doing it finding all the really rough finding all the really rough edges and uh and not and and being at point where you don't have to oversell the technology. You can sell both things. But now there's maybe >> Here we go. We got it together. Um, now there's maybe >> Oh, it's the wrong side. That's why. Flip it around. >> The dyslexic. >> There you go. There you go. Living the brand. >> We got that. I don't know. All this stuff wasn't recording. >> I I trailed off. But uh but is part of it entertaining to you that it feels like >> you know Palunteer has always been in some ways um not had competitors because there's nobody with Alex Karp running a company that is does what Palanteer does besides Palanteer. But at the same time, there's been tens of billions of dollars deployed now to effectively do what Palanteer does, but just selling the intelligence part, not selling all the underlying kind of infrastructure that you >> Well, they're doing two things. They're selling they're trying to sell the intelligence part and they're trying to pretend if you just hire a bunch of people and let them run around their FTS. Now, the the very cool thing is when you've been in your basement doing your thing and everyone kind of use it as the freak show, it it's really interesting and and great to have adoption. The pretty ironic thing is half the people adopting now don't even know they're copying. But now the copying thing, it helps and hurts. Where it hurts is in the beginning it puts clutter in the market. >> Yeah. Um, and there's there's no doubt about it where it helps and then we saw this with defense tech honestly. So like in defense tech we were the only people we were the first people despite what I I love these honestly other podcasters they're interviewing people who are paring things I said 20 years ago they don't know it and it's like oh that's so insightful. It's like yeah of course it's insightful. Karp said it 25 years ago. Uh and like but it's but so that kind of that part is super weird but uh and like but um but it's but what really happens when we see is like it expands the market. So like in defense tech, we would not be doing this well in just purely in government unless there weren't 50 companies that were doing similar things because then the people are like okay first of all >> you view it as like offbalance sheet sales resources where other people are basically >> well it's off well no that that's the large it's they do two things they increase the size of the market because de facto nobody wants to find underwrite a market where there's only one person. >> Sure. So like if you're the one person the percentage of the defense budget you can get is much smaller and two they set up a comparator. It's like you know you may not like the freak show. Okay if like but have you noticed the people who are serious buy it and then then it changed and then three it changes the standard now what you're seeing now is like that times 100x. >> Yeah. >> And it does change like recruiting retention and like how you build a company and we're always think you have to think about how to being dyslexic. huge advantage there because like you don't have a playbook and now that need you need things to shift and we're doing that. Um the the the central thing though that is just cannot be developed even if you understood the playbook. A lot of these things are like appear like it's like you know LLM code appears like palenture code but isn't for a deployed thing appears like pounder it isn't ontology you could theoretically copy parts of it but they're essentially structures that are built deep into organizations that we own and by the way take you three years and in three years we're in a completely different world but there is this magical thing called taste like in the end of the day the reason why you guys have done so well it's of course there's aptitude and diligence showing up and all those things. Yeah. But you have to be able to differentiate between two people who are in business, one of whom is saying something that sounds weird, that is insightful, one of whom is paring something that sounds weird and that's all they're doing. And a lot of people, very few people can do that. And you the same thing like the enterprises that succeed, there is a taste arbiter. And at Palanteer, we have taste art. We have taste in every product, taste in every deployment, taste in every casting. Who puts the people there? How do you put them there? How do you organize the thing? Our ontology then does that technically. How do you manage the whole or ARG with taste? Who should be in charge? What data set should come in? What what are what are the ways in which you protect? What is what should you push into the public crowd? What should be on prem? What what should I mean leaving aside the law and like wars or ethics? What do you want to protect? What should you protect? What should you not protect? Because quite frankly, you want that to be out there so you can get more data. All those things are arbited by taste and then you have to have the credibility of having taste. That's a real problem for a lot of these places because they don't have they they're popular with their friends. They don't they really don't understand how unpopular they are in enterprise. Like they think it's like oh yeah like the way I think I have a problem with like professors at Colombia. It's like no it's a real problem. Like they think I'm Satan and uh you know it's like I I I think you know we grew up in the same community. let's talk about Haidiger. They're like they don't want to talk about Haidiger. >> So it's like it's like Yeah. And so that's just a it's a weird thing. It's going to be a super The one thing I would say for anyone listening >> if you're listening to this and you're chillaxing and not active. I'm not saying you have to agree with me politically or anything. >> Yeah. >> There the like partly because of this dynamic and very self-inflicted because I I I tell you I can't name names. I called many of the titans of this world and and like started this six months ago like every couple days >> we're going to be national >> call every couple days >> like some of them are like yeah we're going to be I mean you know it's like honestly they're like the bat they they find me very entertaining like I'm not sure like so they call cuz it's like it's like oh yeah this is going to be entertaining you're going to pick up so any case so I've been telling them for six months we're going to be nationalized >> yeah you talk >> we're going to be nationalized and they're like why would anyone one nationaliz never happened in America. It's never Why would anyone nationalize us? We're so likable. We're creating so much value. Like, okay, I'm not going to debate that. I know how likable I am. I'm not going to tell you how likable you are. But I am telling you, and you know, the momentum on this is on the side of people in national. Now, we don't get our act together and figure out ways we can say, "Hey, look, there are problems here. We're going to deal with these things are not going to Yes, they are going to create opportunities. You have to talk openly about how these things are valuable because we have adversaries. you can't just say these all that stuff. So the primary risk honestly to Palunteer and a lot of these other countries is and then it's going to be nationalized before national it's going to be regulated by people who don't understand this and now they'll tell you in private I'm working on this I'm d and this and this lobbyist it's like not going to work. So like that's something like if you're listening to this and you're like look you know you don't have to agree with me on all my proclamations. I got a lot of by the way there's some people who think I'm saying we should have a draft too lazy to read. I'm just saying we should like in a world where everything is changing, everything is changing. Don't we have to find some communal structure to remember we're American? You don't like my you don't like my idea of like we all do a week in the park? Great. Come up with some other idea. We kind of have no idea, you know, and like and then they're like, well, I'm saying I I do not want to draft just to be explicit. They're like, oh, that's pro war. No, honestly, you know what? Most of our wars are fought because no workingclass person is making a decision. You start making sure everyone is involved in everything. I'll see you how few wars we fight. It's actually the anti-war position. But any case, disagree with everything. If you're We have on the right and on the left people uh people who have no earthly clue what they're talking about, right, left. >> All they're talking about is how much they hate us. And those of us who are sensible in the middle, >> you know, too many of us are chill waxing like it oh like nationalization. It can't happen. America would never do that. >> Sleepwalking into and you guys have tendies to protect now. You guys should be on the front line of this. Like you got full Oh, I'm sorry. I have a I have a full on very impressive uh corporate leader coming on. So, I got I got >> Last question. Last question if we have time. Uh >> how are your conversations going with Fortune 500 CEOs around headcount planning? There's been so many layoffs this last year that people were saying, "Hey, we're getting so much out of AI. We're able to, you know, cut back here or there." uh people inside tech often know like these maybe there's just reduction because there needed to be a reduction the or got bloated maybe they do need to fund some AI business model yeah the business just doesn't have momentum but how are those conversations going what does it look like >> like the the like I by the way I talked to fortune 500 companies I talked to unions I talked to soldiers I talked to fire it >> if you upscale somebody >> they're more valuable Sure. >> And like all these whether it's people working on batteries, people work driving trucks, people corporate leaders, and again this is where I think we have to be very careful to be more disciplined on the corporate side. Like if you run around saying AI allowed you to fire twothirds of your workforce and you did it because maybe your competitor's kicking your ass. Yeah, >> that could that is a really like you might as well just go sign up for Bernie Bernie Sanders manifest. And part of the thing is they really believe that can't happen. So they're free riding on the fact that it could >> like we have and it just cannot work anymore. These things are very very explosive. The American people sense that there is something dangerous here. And when people are playing with that fire, it's like it's a they assume the fire won't burn their hands. That's not the world we're in. That fire is going to consume us. And what we see, again, the war fighting example is just the most neutral, not for everybody, but like the soldiers at the bottom have gotten much more valuable. And and I don't even just mean the special operators, which obviously they're in a different league, but like every the people doing a lot of the operations now are doing our product. They're high school vocationally trained. You see this everywhere. The the the modern enterprise is going to have like we have a a true like very very very smart uh person coming on and it's like you're going to have a very smart executive. He's much better at hiding it than I would be if I were him, but that's you can talk to him about that. But um uh um and uh and then very talented, creative people with taste all up and down the stack. In any case, I think this is time for me to >> I think this is time >> we uh >> Thank you so much. >> Great to catch up. Always fun.

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