The Exchanges

Q So what's the most surprising or interesting thing you learned so far?

A Well, the amazing thing that I've learned is just the enormous insatiable appetite that the world has for American technology, and just last week we signed a historic deal with the Philippines, 4000 acres, right next to Subic Bay, uh, where we're gonna build a first-of-its-kind AI-native industrial park, and the goal is really to secure inputs that are vital for American and global supply chains. As you know, we are engaged in a massive re-industrialization effort in the US. A lot of those factories depend on so many different inputs that come from all corners of the world, and right now there is a massive over-concentration of those inputs from China, and so the goal is we are walking and chewing gum at the same time. We need to re-industrialize at home while making sure that all the factories that are in Ohio and in Oklahoma and in Virginia actually have all of the inputs and niche Motors and components that they need to keep running and actually being cost competitive. And so we're looking and triaging interest from a number of different companies, um, in order to consider, you know, what the longterm build out is going to look like in the Philippines. And it's very exciting to actually build this out from a first principles and actually create a platform out of it.

AI assessment note: “the amazing thing that I've learned is just the enormous insatiable appetite”

Q these historical theories on why Europe was so dynamic. And I think there's like certain competition that's really good. That was really helpful to it. Obviously you don't want another world war. And so I think because of the world wars, they've kind of like brought everything together, but then, but then somehow it's just totally stagnated. And your mother was, what did she do for the government there earlier?

A Yeah. So she was a web programmer. So she was You know, not really a politician at all. Um, she was a web programmer for, um, the, the, they call them DGs. It's basically like their equivalent of ministries basically for the DG education and culture. Um, she had a very, you know, sort of small, you know, humble job as a programmer there. Um, she was the editor in chief of a magazine in Paris back in the early nineties, but then left the job market for a long time because one of my sister and I were growing up to be a stay at home mom. And so by the time she reentered the workforce, the industry had totally changed. So she actually taught herself how to code, um, at 47, believe it or not, and, uh, and then just became a programmer. And so she was doing that. And I think, you know, like a lot of Europeans, she really wanted to believe in the European projects of the European Union. But I think it's, it's, you know, for people who really remember what Europe was like in the nineties, um, it's really hard to look back at The last 30 years and conclude that Western Europe today is better off than it was 30 years ago.

AI assessment note: “she was a web programmer for, um, the, the, they call them DGs.”

Q It does kind of feel like the world came our way a little bit, huh? Like from, from the last 20 years.

A Yeah, I, I think there, there's certainly a number of us who've kind of been seeing, inside and outside of government, seeing, like, the trends of the world. I mean, part of the thesis of the book is, if you really go back to 2014, you have the militarization of, you have the annexation of Crimea, the militarization of the Spratly Islands in 15, Iran with breakout capability for the bomb, you've had a pogrom in Israel, the Houthis holding Red Sea trade hostage, global trade hostage from the Red Sea. It, it's pretty hard to look at this and not think, perhaps we've lost deterrence. And as a country that spends a trillion dollars a year on defense, you know, how is this happening? Why is this happening? And I think there are a lot of lessons from our past. You go back to World War II, the early Cold War, the fundamental innovative American spirit that actually provided for our defense. Now we have a huge number of founders who've shown up to invest in the national interest. We have, uh, bold leadership, uh, throughout our military services to seize that opportunity. And I'm, I think this is the moment.

AI assessment note: “Yeah, I, I think there, there's certainly a number of us who've kind of been seeing”

Q Drexel, I mean, the high yield bond market was about seventy billion in the 19 seventies. I think it was 700,000,000,010 years later. Was that in part due to Drexel? Like this increased, must have increased funding For a lot of businesses to be able to issue these types of bonds and be able to do things, right? Like, sounds like it was a very big transformation in American finance.

A Yeah, I would do, probably do almost fully to Drexel and to what Mike created. So Mike came to Drexel in his twenties, uh, coming out of Wharton and he went to Drexel because Drexel was a company research firm on the street. And Mike's view was values created by having information and doing your own. So when he went out with the idea that he could identify companies that were rating went lower, he was sort of like, if you use a sports analogy, it was sort of like Wayne Gretzky. You know, rating agencies, a rate based upon the past, he's investing based upon the future. So Wayne Gretzky said, I don't skate to where the puck is, I skate to where I think the puck is going to go. Uh, as might develop credibility as he, as he talked to institutions about these bonds and got people interested in doing that. Drexel allocated funds to him to invest. He did very, very well with that. He developed, I guess, a cadre of investors who believed in what they were doing. So Drexel started for the first time to do original issues of high yield bonds. They actually, companies that did not have the track record You get investment rating, but that Drexel believed through its research and meeting management and understanding the industry would be successful. They started financing companies that could never get financing before. This is sort of where the term democratization of capital came from. S…

AI assessment note: “Yeah, I would do, probably do almost fully to Drexel and to what Mike created.”

Q Yeah, and Rudy, Rudy was obviously had very high political ambitions, right? So he wanted to do whatever he could to, to make himself look good and take people down.

A Yeah, I would say, you know, the lawyer who was a very, very well-known, uh, defense lawyer at the time that we retained initially, unfortunately died of cancer about a year and a half later, was a guy named, uh, Edward Bennett Williams, who started the Williams and Conley firm in Washington, DC. And when I first met, uh, Ed, this comment to me about Giuliani was, he's the biggest piece of political meat I have seen since Tom Dewey. Now, most people that are listed here have no idea who Tom Dewey is. Uh, but Tom Dewey, also the U.S. Attorney for the Southern District in New York, as was Mr. Giuliani. Tom Dewey went on and used that office to become the governor of New York and came very close to beating Harry Truman, ok, in 1948 to become president of the United States. Uh, so that was Tom Dewey. So yes, Giuliani was very politically ambitious. He probably had never heard of Michael Milk until this case started. That when he woke up the day after the investigation started and he saw the headlines in the paper, he became very interested in, uh, this case helping his political career.

AI assessment note: “So yes, Giuliani was very politically ambitious.”

Q So let's talk about like how AI is changing things right now for firms. Obviously you guys are seeing what's going on. You guys are seeing the numbers. Uh, is it changing how venture capital firms operate? Like, like, like how are people using AI in general?

A Yeah, it's changing how firms operate, um, all the way from the very, very earliest stages of sourcing and identifying companies all the way through things like, you know, portfolio management, LP reporting on the other side. Um, it's actually really fun right now. I'd say when we started standard metrics with you guys, you know, there was in the, in the initial phases, a lot of what we were doing was evangelizing to firms like, hey, you should use software, like software will help you to run your firm better. And, um, you know, now that's still happening, but there's also a lot more that we're learning from firms. They're experimenting a lot. So for example, on the sourcing side for the last decade, plus there've been a bunch of firms that have built data-driven sourcing engines. They're looking at things like GitHub stars. A number of employees on LinkedIn, social media followers. We're now seeing people use large language models to do a lot more qualitative research that complements that quantitative. For example, like what's the tone of what people are saying on Reddit about this company? Um, or much more nuanced.

AI assessment note: “it's changing how firms operate, um, all the way from the very, very earliest stages”

Q So on one hand, these things are, are kind of hedged from a lot of the current AI disruption. On the other hand, isn't it easier to run a business with AI?

A A hundred percent. Um, and that's an area that we've been investing a lot in the past couple of quarters. My mental framework for it is a lot of people think of AI and they think of cost cutting and they're like, oh, we can really optimize our P and L. We can use AI, automate all these jobs, cut costs. That's not the right lens to look at small businesses. And it's not right for really one reason, which is that most of the folks in the back office of a small business are wearing multiple hats. If Susie does payroll route planning, HR, and you automate one of those jobs, you're not coming to Susie and saying, congrats, you just got a 33% discount on your payroll. She's going to walk out of the door and tell you're crazy. So what, what really it is, is it's a revenue growth story. What you have to do is work with your employees and small businesses, figure out, hey, how can we leverage AI to reduce the amount of monotonous work that you're doing and then help you identify, okay, what's the best way for you to take that time and reallocate it to something that generates revenue.

AI assessment note: “A hundred percent. Um, and that's an area that we've been investing a lot”

Q And this is as of the last several months?

A And this is within the last, yeah, three to six months, honestly, when this shift has really happened. And, and there are other steps to To be clear, obviously. But, but I think at this point, you know, you, you, you used to maybe one way to put it is like, I mean, you used to work with punch cards, for example, and you used to work and now in many ways, the medium has shifted away from code and a lot more of it has become basically English. Right. And so, so, you know, we, we obviously use a ton of Devon internally. Uh, we use, you know, windsurf and then the agents inside windsurf internally as well. But at this point, either way, whatever tools you're using, You know, it's not really you typing out the lines of code yourself. It's, it's you looking, understanding what it is that you want to do, thinking about, okay, how do I want to handle this case or this behavior? And you just tell the agent what you want it to do in English, right?

AI assessment note: “And this is within the last, yeah, three to six months, honestly”

Q what we called our smart enterprise thesis. There's like a big paper we wrote on it called The Coming Transformation in 2013 about what's happening to the economy, and there's a lot of like echoes between this coming transformation You know, 13 years ago, and like, what's happening in AI right now? But, so Koli, first of all, like, what was the Smart Enterprise thesis, as far as you're concerned?

A Yeah, I think the most succinct way to talk about it was, you know, early on, and you, obviously we saw this at Palantir, uh, was, we thought there would be a transition that happens from old enterprise software to new. And so, enterprise software one point oh, we always thought would be these, Not dumb systems, but they're almost like databases. You know, they're, they are innovative, but you store your data in them for your business. Uh, you're able to retrieve that data in the future. Think of, think of an ERP, think of a CRM. They're organizing, but they don't help you really run your business or make decisions in your business. And so it was revolutionary, but we thought there was more that software could do. And so with the advent of A, the cloud and B, the commoditization of big data, Uh, we thought there'd be a new generation of enterprise software. We called enterprise two point O where with this idea of man machine symbiosis, you'd now have software systems that help you make decisions. And so Palantir was obviously, I think the most quintessential version of that, but we thought there'd be many vertical software companies that would start around this.

AI assessment note: “we thought there would be a transition that happens from old enterprise software to new”

Q what we called our smart enterprise thesis. There's like a big paper we wrote on it called The Coming Transformation in 2013 about what's happening to the economy, and there's a lot of like echoes between this coming transformation You know, 13 years ago, and like, what's happening in AI right now? But, so Koli, first of all, like, what was the Smart Enterprise thesis, as far as you're concerned?

A Yeah, I think the most succinct way to talk about it was, you know, early on, and you, obviously we saw this at Palantir, uh, was, we thought there would be a transition that happens from old enterprise software to new. And so, enterprise software one point oh, we always thought would be these, Not dumb systems, but they're almost like databases. You know, they're, they are innovative, but you store your data in them for your business. Uh, you're able to retrieve that data in the future. Think of, think of an ERP, think of a CRM. They're organizing, but they don't help you really run your business or make decisions in your business. And so it was revolutionary, but we thought there was more that software could do. And so with the advent of A, the cloud and B, the commoditization of big data, Uh, we thought there'd be a new generation of enterprise software. We called enterprise two point O where with this idea of man machine symbiosis, you'd now have software systems that help you make decisions. And so Palantir was obviously, I think the most quintessential version of that, but we thought there'd be many vertical software companies that would start around this.

AI assessment note: “we thought there would be a transition that happens from old enterprise software to new”

Q FDR brought in RFK's grandfather to start it off, he said, right? 91 years ago.

A He did. So, uh, throughout the years, SEC was never, I'd say, at the vanguard of You know, uh, pushing innovation and, and that sort of thing on the marketplace, but it, uh, at the same time was never kind of blocking it, just standing athwart, uh, progress, uh, blocking the street. And so, um, but, so one example is when I was, uh, a young lawyer and just joined the SEC in the early nineties, um, one day the chairman, Richard Breeden, came into my office and had a big stack of files and said, can you find out You know, why this hasn't been approved yet, and that was, um, the first ETF, uh, exchange-traded fund, and that's, uh, was called, uh, SPDRS, that's the S&P 500 index.

AI assessment note: “He did. So, uh, throughout the years, SEC was never”

Q famously is one of the fastest moving companies ever. It's probably not possible for the entire Pentagon and three million people to move as fast as you guys did at Uber, but can you, can you bring some of that startup speed to the Pentagon? Like, is any of that working so far? Are you, are you, is that even a model at all that inspires you to push harder?

A Absolutely. I mean, every day I wake up And, um, and I think, you know, if, if they have this once in a moment lifetime, this once in a lifetime moment where you have a disruptive president, a disruptive secretary of war, and I'm in this job, I'm not going to do it forever. How do I leave my mark, right? And do, and my mark on behalf of the country. So I wake up every day thinking that way and trying to bring the Uber practices. And some of those are, they're actually kind of normal business practices. When something's not getting done, you call everyone in a room, you do standups every day until you get to the answer. You, someone says, well, you can't do that. I said, well, show me the policy. And you read the, you know, you, you find your way to answers, which is why in two months of owning, being the chief AI, having the chief AI office run in my world, which was a new move, we were able to launch, uh, gen AI, which is Google's Gemini for four million, every, every, uh, employee, military and civilian in the department. And they never had AI on their desktop before. Now it's on every single desktop in two months. So it can be done.

AI assessment note: “Now it's on every single desktop in two months. So it can be done.”

Q I'm really passionate about because I think our government needs to rethink a lot of things around how merit works and how accountability works and all of that, and I want to talk to you about those things, but first of all, like, what's, like, the most interesting or surprising thing you've learned so far, like, running OPM? Like, what shocked you, or what's, what's, what's been new to you?

A Yeah, so this, I, I kind of knew this vaguely, but I would say, like, it's really become front and center, so, um, uh, you know, I've talked about this a little bit, like, When you look at, kind of, the way we do performance management in the government, the system is just, it's just completely broken, and it's just so embedded in the culture. So, quick anecdote, um, you know, everybody gets ranked one through five every year, uh, one being the worst and five being the highest, and, you know, in the government, if you look across, you know, government for long periods of time, about, like, you know, 70, 80% of people get ranked a four or five, meaning, like, 70, 80% of the people are well above, like, average, basically, and Literally, like, 0.2% of people get ranked a one or a two, basically, and, you know, you know, as well as I, having run a bunch of companies, look, there's no magic number that should be in that lower quadrant, but look, it's really hard to hire, and people make mistakes, like, you know, a five to 10% turnover of people who just, for whatever reason, aren't able to do the jobs you need them to do, or you may have made a mistake in hiring, like, it's not unreasonable, but what's happened is, like, everybody's gotten very, very focused on these ratings, like, that's, like, kind of how people, Almost, you know, that that's the highlight of their year is gettin…

AI assessment note: “Literally, like, 0.2% of people get ranked a one or a two”

Q them overlap. You know, in my, in my world, It was really the 19 seventies and the late 19 seventies. They put in a bunch of rules that really broke government, really stopped us from firing people, stopped us from measuring their merit. You refer your book, I think, to the 19 sixties as a problem as well. Like, like, what's the, what's the history of how things broke here?

A Well, I think, um, the, the genesis of the red tape state is, is the guilt arising out of the sixties. Then the changes occurred in the seventies and the eighties. So, so you're right that the, for example, the Civil Service Reform Act in 1978, which made it impossible to hold anybody accountable, you know, was, was at the end of the seventies, but the, there was a kind of a fatal theoretical flaw that they, ah, that they committed, ah, which was to try to create a government that was better than people. They wanted to create governing as a kind of a software program where, If you had a thousand-page rule book, you just comply with the rules, and you could have an extensive procedure, and you prove by objective evidence that your answer is correct, and if you didn't like it, you have a right to complain, and it's just led to this morass.

AI assessment note: “the genesis of the red tape state is, is the guilt arising out of the sixties.”

Q the theory of this again, because, you know, so, so our founders obviously, uh, you know, had a certain view of how this should work. And John Adams famously argued, we want a government of laws, not of men, but, but you're saying we almost went too far where it's not just laws, it's thousands of scripts of things. Like was John Adams wrong or was he saying something else?

A Well, John Adams was a lawyer. He was a very good lawyer, but in his day, law, and until, you know, the 19 sixties and seventies, law involved using judgment. Judges used judgment. Everybody used judgment. Um, and, and so when he said a government and laws, he, he meant you didn't have a potentate who could throw you in jail because they didn't like your political views. You know, that we have a principle in the Bill of Rights for freedom of speech. So, That's fine. That's a, that's a legal protection. He didn't mean central planning. He didn't mean there was no such thing as a rule book telling you exactly how to organize your office and work.

AI assessment note: “when he said a government and laws, he, he meant you didn't have a potentate”

Q really stood up to our cities to save our cities recently. And it's obviously doing something that's similar to what President Trump has been pushing as well. This is becoming an idea as time has come. And we really appreciate your leadership. Tell us about the situation in Tulsa prior to taking action, and how did the city officials feel to take responsibility? Why did you have to step in?

A Yeah, absolutely. Well, first off, it's great to be with you, and I'm a big fan of yours, and as an entrepreneur and leader and everything you're doing with Cicero Foundation, and so, ah, just super pumped to be here with you and have this conversation. Um, you know, Tulsa, so the business community really reached out to me, and the homeless situation was getting out of control. Um, you had people that felt unsafe going to their businesses. They would, they would, ah, pull into the parking garage, felt unsafe. We had incidences where People were walking down the street, and they were getting hit by homeless with a brick. We had muggings, we had people pulling knives on business leaders going to a restaurant, and so it was getting out of control. Um, our mayor at that time, the current mayor in Tulsa, um, basically said, well, I'm gonna fix homelessness by, 2030. And I'm going to fix it by building houses. And I'm like, I called him. I'm like, listen, you can never build enough houses for homeless because you're just going to keep attracting more and more and more people.

AI assessment note: “business community really reached out to me, and the homeless situation was getting out of control.”

Q you know, crime. So I think this was called Operation Safe in Tulsa. I want to hear more of the details because I'm, I think we actually do have a few other governors and legislators who watch our show and follow these things. And I understand you've already removed over 1.9 million pounds of trash and hazardous materials. Is that, is that true? That's a lot. The Tulsa house works.

A Yeah, it was amazing. We literally, through our Department of Transportation, we got it all organized. I sent my highway patrol out, which is the state police, and then we contracted through our Department of Transportation, and we got a vendor, because some of this stuff to clean up, um, you know, these are hazardous, hazardous things, and so we found a 55 gallon drum we filled up with, with used needles, and we can show you some of those pictures, but We removed about 1.9 million pounds of trash and debris, needles, drug paraphernalia. We found stolen credit cards, scrap metal, stolen bicycles. So it's just unbelievable. There were 64 different camps, and you'd be shocked, like literally right off the highway in some wooded areas, some encampments behind people's houses. We had ladies and, and single moms crying, thanking us. For cleaning up, because they had called the police over and over again, and nothing had happened. Car dealerships were having their cars set on fire, and they came to us just thanking us for finally coming in. Because think about it this, Joe, who's thinking about the business owner? Who's thinking about the people that used all their savings to open a dry cleaner, and now nobody's coming to their shop because you've got homeless laying on the street? Who's thinking about the school kids walking to school? So everybody always thinks about the people bre…

AI assessment note: “We removed about 1.9 million pounds of trash and debris, needles, drug paraphernalia.”

Q Let's talk a little bit more about your background, Max. You grew up in Iowa and you went to Stanford as did I, and you're also, The editor of the Stanford review. So I was the editor of Stanford review when I was there. Peter Thiel kind of helped get it going. 15 years before me. What was, was being the editor of the review relevant for all this work?

A Oh, totally. I think I published upwards of 50 pieces while I was the editor of the review. Those were all sort of, you know, tirades. They were opinion pieces. They were rants. Uh, there was a funny one where Palantir was recruiting at the Stanford Computer Science Career Fair, and a group of students, uh, students, uh, for the liberation of all people, slap, uh, um, they were protesting Palantir's inclusion, and I was like, oh, that's odd. This was related to Palantir's work with border enforcement. And so, it turned out that at the same career fair, there were four or five Chinese state-owned telecom companies, and so I wrote a little piece that, you know, if you're, if you're really socially conscious, and you're, you know, you're, you don't, you don't want to work at Palantir for ethical reasons, you've got some good options. You can work for the Chinese state. This is sort of tongue-in-cheek. There was a lot of other stuff. I was following campus activists. I was following campus nonsense. I was one of the first people in America to write a big article about Chesa Boudin, who was the DA in San Francisco right after he'd been elected.

AI assessment note: “Oh, totally. I think I published upwards of 50 pieces while I was the editor”

Q So it's not just a magazine. What are you going to, what are we doing to do something that's intergalactic?

A So intergalactic media is It's American propaganda, and arena is our most important organ, but we don't want it to just be limited to a magazine. We're going to be publishing very high-end coffee table books soon. Those are going to be hopefully available for sale early next year. Um, we're going to do some fun stuff around the semi-quincentennial, the 250th anniversary of the United States. Lots of fun stuff being organized at the federal level there, but we think there's going to be some collectibles that people are going to like. Uh, and related to the hostile media outlets, we're going to be doing more breaking news soon with this, with this thing that we're creating called the arena wire service. Uh, the old wire services used to literally send news across the wires so that they would arrive at these desks. So Bloomberg and Reuters and the Associated Press still do this. And so at newsrooms around the world, they have these receivers where the, where the, where the stories will come in. Um, we want to give people an opportunity to do breaking news and, Announce things with an outlet that doesn't totally hate them. It's impractical to do breaking news on a quarterly schedule in print just because it's, uh, you know, it'd be, it'd be late breaking, uh, to, to put it, to put it mildly. So there's going to be a new section on the website soon. The arena, the arena wire service…

AI assessment note: “We're going to be publishing very high-end coffee table books soon.”

Q Convoy. And what, why didn't those guys just fix it and make a big platform for everyone to use?

A I think one is that one, to get a million trucking companies or to get on a single, single platform is a Herculean task, right? Like, it's like, how do you get so many different companies to say, trust us, come on my single platform. Two, it is a low trust industry. Right? Like people don't want to share all their information because they feel like that will be used against them for negotiation. Like I give an example to people and saying, if you're a truck driver with home base in Austin and you've been out of Austin for last three weeks and now you're in Chicago and you want to get back into Austin and you tell everybody that, hey, my home base is Austin. I've been out for three weeks. I haven't slept in my bed in three weeks. Now I'm in Chicago and I want to bid on a load that is going from Chicago to Austin. Well, if you give them all that information, they're going to give you a really bad price because they know how desperate you are.

AI assessment note: “to get a million trucking companies or to get on a single, single platform”

Q And fleets as well. And I guess a lot of these, a lot of these really top brokers, they're top people make a lot of money and you're, you're helping these people be even more productive. How does that work?

A Yeah. So I think basically what we're building is a, a teammate called Augie. Um, and, uh, people rename Augie. They've chosen all kinds of names for Augie. It's interesting. They even created pictures for it and, and, uh, personas for Augie. Uh, Augie participates in people's like weekly Town halls and monthly town halls. Uh, so it's, it's really interesting to see how, you know, an AI teammate is becoming part of a culture of an organization. Yeah. Um, but really behind the scenes, you know, Augie sort of work, first it works 24 seven. It can, it is multimodal. It can handle emails and texts and phone calls and telegram or any other means of communicating. It does actually, because there's a lot of dispatchers in this business That are in Eastern Europe, and Eastern Europeans only use Telegram, and so Augie has to use Telegram to communicate with them. Similarly, like, there's a large community of drivers that are from, like, Punjab in India, and, you know, those guys use WhatsApp, and the way to communicate to those folks is WhatsApp, so Augie has to use WhatsApp, you know. So it's multimodal, just like you would expect, you know, a teammate to be. And then, I think the other piece with, with Augie is, like, it, it can do a lot of work, and it's defined as what we call workflows, which are these written word docs No different than an SOP in a business. It can follow it relig…

AI assessment note: “works 24 seven. It can, it is multimodal. It can handle emails and texts”

Q the election as Russian disinformation. We want you to be ready to censor that and don't let the Russian disinformation interfere with the election. So they did this knowing that this was real and knowing that it would come out in order to try to prepare them to help the Biden regime censor for the election. I mean, this is actually insane stuff that you, you have crazy here, right?

A Yeah. It's like, it's, it's like you would, you would imagine the Soviet union, right? Or something. And And you had, again, this is kind of the legacy of the original sin of the Russiagate stuff, right, which was they concocted this nonsense, um, and then everything they didn't like later on, whether it's about President Trump or other things, became Russian disinformation or Russian misinformation, Russian malinformation, all this stuff. So yeah, you're right. So the, basically, the FBI authenticated and knew the laptop for Hunter Biden with all the crazy stuff in it, It could have, by the way, implicated Joe Biden in some bad stuff. They knew it was real in 2019, in November of 2019. The FBI starts having monthly, then weekly meetings with big tech platforms about this topic in particular, which is look out for this Russian hack and leak operation. Yoel Roth, who was the former like integrity guy at Twitter in an affidavit said, yes, he specifically mentioned Hunter Biden laptop. And by the way, it's also worth noting when you start connecting some of these dots, which is kind of crazy. There's a guy by the name of James Baker, who was the general counsel at the FBI in During the Russiagate stuff, who's now been implicated in leaking classified information in In 2020, he's the general counsel for Twitter.

AI assessment note: “Yeah. It's like, it's, it's like you would, you would imagine the Soviet union”

Q I'm a more minor player in this whole thing, but I was, I was, I was honored to be throttled by the same people as well. So this is totally, totally crazy stuff. What ended up happening with the lawsuits? You uncovered all these amazing things. We all can kind of see that there's more conspiracies going on, but then what did the courts do? Like where did it go?

A We wanted the district court level. We wanted the appellate court level, the fifth circuit, and then the Supreme court took the case up and then essentially punted based on standing. They said, well, we need to send it back down to the lower court to further establish whether or not Missouri and the other plaintiffs have standing. One interesting side. So as far as I'm concerned, Exposing all of it was the big win. It's still kind of rattling around, but the, the government never wanted that stuff exposed. One interesting sort of side note from it. We can talk about Fauci's depot too, but one of the plaintiffs is a guy by the name of, I'm sure, you know, is Dr. Jay Bhattacharya was a Stanford guy.

AI assessment note: “Supreme court took the case up and then essentially punted based on standing.”

Q Yeah, exactly. Who's paying for this? Totally unclear. Maybe those ones aren't paid for. Uh, are there, are there other lessons or processes at Palantir that you kind of took with you to Apex? Or like, what are the positive things to take away from there?

A So many. So, the biggest problem with that company Synapse was at the end of the day, we were building AI and computer vision algorithms. But we were applying them almost more as a kind of a consultancy, where we'd see a problem space, we'd modify an algorithm, we'd go apply it to something, and it would, we'd get paid for it, it would work well, but it was something that really never took off, right? We were able to make money and pay the bills and grow the team a little bit, but it wasn't really that hyper growth. And when I got to Palantir, the most impressive thing that I saw was you had this underlying platform or set of platforms, right? You had Uh, you had Foundry, you had Gotham, you had others. And these platforms were, sure, you build them, you have to configure them to each customer, but the scalability of them was absolutely incredible. And you could take the same thing you built once and apply it to a completely different type of customer, but they end up having this very similar kind of problem. And it was a, it was almost like a light bulb moment in my head where I was like, wait a minute, like, this is the key to building a technology product that actually can scale. And is really repeatable. And that was, for me, one of the things that I really took away from it. The other aspect, frankly, was just how to work with the government, right? Government is not an ea…

AI assessment note: “this is the key to building a technology product that actually can scale.”

Q It's just, I guess, just north of LAX and north of El Segundo. Um, unfortunately, you mentioned buying the home. You bought a home, I guess it was in, you know, the fires. Can you tell us about this briefly, what happened with this?

A Yes. So, um, My, uh, wife and I, uh, bought our, what we thought was, uh, you know, a beautiful kind of starter home, first home, uh, and we lived there about one year. We had, uh, our twins, which is amazing, and then a few months into that in January, I, uh, get a phone call from her saying, I see smoke, and I said, no worries, there's fires in LA all the time, that's why we pay our taxes, like, the fire department will take care of it, and, uh, about an hour later, I get a call saying, I'm in the car with the kids and the dog, and, like, I can't get out of the, like, House, because there's, like, a line of cars, and it's gridlocked. Like, help me. Um, and I ended up driving from our office home, it's about a 30 minute drive, saw the planes, like, dumping water, and literally, my wife is, uh, like, FaceTiming me from the car, and it's surrounded by flames, the car next door is catching on fire, and I, like, drop my car off at the bottom of the hill, and run, like, two miles, like, straight uphill. Felt like I was in an action movie, so honestly, fun in the moment. Very traumatic for her, and obviously in retrospect, though. And, ah, the entire neighborhood burned down. And, ah, I think the most devastating part of it was the firefighters who, as we were trapped in this gridlock, we'd roll down the window and say, where do we go? And they say, we don't know. We don't even have…

AI assessment note: “My, uh, wife and I, uh, bought our... first home... the entire neighborhood burned down.”

Q So you're talking about low earth orbit. Let's educate our listeners a little bit too. We have, we have LEO, MEO, I think GEO. What, what, what do these mean? And, and, And, and what are the different advantages of each?

A So the simplest way to think about it is how far away from earth are they? So low earth orbit, Leo, you're, uh, somewhere between call it 412 hundred kilometers away from earth, which is actually pretty close, right? Like you think about that distance just going straight up, that's not that far away. And what that means is because you're close to earth for things where they want to look down at earth, or you want to intercept a missile, it's really well located because you're going to be really near the thing that you're looking for. Um, then you could go into MEO, Mio is a huge range, right? Mio is anything from call it, uh, 12, 1400 kilometers away up to tens of thousands of kilometers away.

AI assessment note: “low earth orbit, Leo, you're, uh, somewhere between call it 412 hundred kilometers”

Q Is this because you're doing so many calls as well? It's like, like, I guess it's because what kind of stuff you're doing?

A So it's suddenly like for every outstanding claim that the human has to work, instead of them spending 30 minutes on the phone, the AI agent is doing it. Instead of them having to go navigate these old insurance portals and spend a bunch of time just looking up data, it's brought back. The AI agent brings that data back for the human to then Decide, hey, what is the next step? And you kind of start to see this weird paradigm where our billers are orchestrating these agents as almost like a puppet master, right? Like, hey, intern, go do this. Go on hold for me. I will wait for you to come back with the information. I'll make a decision. And what we find is that they're able to work through three to five times more claims in the same amount of time because they're no longer doing this menial work.

AI assessment note: “instead of them spending 30 minutes on the phone, the AI agent is doing it.”

Q around here, so it's okay. So in general, obviously, there's more things the machine can do than it could before, but what you're saying is it still can't do everything. Is it getting to a point where maybe you can do, like, almost everything, or is there still, like, you have a ton of these billers. In 10 years, will it be doing everything? How do you think about it?

A I think in a couple years. Um, what I would say is that dental billing, like, the difficult part is it's very unintuitive. So it's, it's also not, like, written down. It's not really in, like, the training data, right? Um, and that, like, Unintuitiveness is why we need the billers to, like, sort of correct the system. Also, like, for the billers to teach the engineers, like, why is this the way that it is? Um, and I can maybe give an example of, like, one edge case. So it's like, let's say, um, you got an EOB back from the insurance company, and EOB is basically a receipt on how they adjudicated and or paid the claim, right? This usually comes in the mail, um, along with a check. And it could be that, like, you got this EOB back for this claim, and you're like, I never even submitted this claim. And it turns out that they sent it back Um, under the parent's name instead of the child's name because they're on the same insurance plan, right? And so, like, you'd have to go into the EHR and go figure out, like, oh, actually, I'd never submitted this claim. Let me check the family file. Let me, like, go look at this. And then it turns out you submitted four x-ray codes, and they returned back, oh, we paid you for one code. And you're like, why is this the case? And it turns out, oh, they combined the different codes together, um, in this, like, very unintuitive way, in a way that, l…

AI assessment note: “I think in a couple years.”

Q unitary executive theory. What does that mean? And I guess it was, uh, this act where they were trying to limit Nixon's power at the time, very democratic Congress. And, and, and basically you believe the constitution doesn't actually allow them to do that. So you're able to go faster here. Are we going to get that to the court eventually? Like what's, what's, what's going on with this thing?

A I expect that, uh, to occur. You know, the president ran on impoundment control act being a constitutional, the notion of, of restoring presidential control over the ability to not spend money. And we obviously believe in congressional power of the purse, uh, the notion that Congress sets a ceiling and, and you can't go above that ceiling. That's a, that's a, a hallmark constitutional principle, but the founders never envisioned in 200 years of presidents never, uh, Had to live under the constraint of having to spend every dollar. And that's really something that was imposed in the 19 seventies with the passage of the Impoundment Control Act. And I'll just note, even when they passed that bill, they had to call it the Control Act and not the Impoundment Prevention Act because they recognized the extent to which presidents had this authority. And it's basic common sense. If you as Congress say, look, we want you to do something for a hundred million dollars. We think it's important for the country. Here's the funding. And we can do it for seventy five million or eighty million dollars just as good. Are you really going to ask us to, to, to buy flat screen TVs and, and copy machines at the end of the fiscal year to get the money out the door? That's insane. Everyone knows that's insane. But ultimately there's more to the story, Joe, in the sense that this became a fundamental asp…

AI assessment note: “I expect that, uh, to occur. You know, the president ran on impoundment”

Q the right, people like Elon Musk were upset. They didn't think it cut enough. Um, you know, as far as I can see, it does contain unprecedented budget cuts, uh, in terms of the mandatory savings. I think it's 1.6 trillion dollars. Obviously, there's a lot more to cut in government. Can you walk us through what's the most important elements of the bill and how to think about that?

A Yeah, I think you nailed it. There's a one in .5 trillion dollar in savings to mandatory reforms, which is some of the big structural drivers that we have. Uh, if you looked at the biggest, uh, mandatory reform in history, it would have been 1997 and eight hundred billion dollars adjusted For inflation. So we very nearly double it at 1.5 trillion dollars. Uh, we fully pay for any spending that's in the bill for the border or for defense golden dome. Um, and we've paid for additional tax relief that's in there as well. Uh, so this was a net reduction in deficits of four hundred billion dollars. And so that would have, that would all go to helping with the debt and deficits.

AI assessment note: “There's a one in .5 trillion dollar in savings to mandatory reforms”