The Exchanges

Q You know, you're the CTO of Palantir. You, you've made, you know, infinite money at this point, and, you know, you're a husband and a father, yet last year you joined the U.S. Army Reserves. Why'd you do that?

A In part, to honor dad's sacrifice. Like, this country has given us more than we deserve to have, and I think, uh, a sign of a, of a functioning society is that those who succeed in it are willing to invest their time, energy, money, resources, attention, and, and give back. Uh, I think that the micro reasons are like, this is the example I want to set for my children. Um, I want to make sure that they have the same gratitude as maybe a generation removed from the visceral violence that we escaped. Uh, they should have the same gratitude that, that I had, that dad imparted in us. Um, and I think, I'm not sure I had A lot of differentiated skills to give the Army at 24, but I think at 44, uh, I've learned a thing or two along the way that I think can hopefully help the Army go faster.

AI assessment note: “In part, to honor dad's sacrifice.”

Q That's when we all first started getting online, right? I think I got AOL in 1993. This is the very beginning.

A Wait, what was that called? AOL, yeah. Hey, growing up in the, you know, the DC area, we know a lot about AOL. But, uh, I, I lived with the whole thing. You know, the first couple of intrusions happened in 88 with the Hanover hackers and Cliff Stoll and those sort of things. You have the Morris worm. Actually, I think Cliff Stoll was 84. Morris worm was 88. Guy at Cornell, you know, right in a worm that, uh, had a finger demon buffer overflow and kind of spread them across Unix machines. By 93, I'm sitting at the Pentagon looking at log files, TS log file, secret log files, figuring out who's doing what. And by 1995, I'm responding to my first ever computer intrusions as an Air Force Uh, special agent in the Air Force Office of Special Investigations.

AI assessment note: “By 93, I'm sitting at the Pentagon looking at log files”

Q What are ways, so we have a lot of listeners who are building things who, you know, interested in helping the Department of War. Like, like, what's the right way to engage? Like, I, I'm, I'm lucky I happen to know you. Like, people don't know you. Like, what's the right way to engage with your team and to, and to work with you guys?

A So we've tried to, uh, declare or tell people in the industry that we're open for business. And what does that mean? That means I've got funding mechanisms and entry points at each stage of the company's life cycle. So at the beginning, there's something called SIBR, Small Business Award. That's very, for early, early stage companies. Um, and then we have something called APFIT, which is, you know, a company, uh, low rate production for companies that have developed something that we need for the Army, Navy, Air Force. And then we have DIU, the Defense Innovation Unit, and the Office of Strategic Capital. So I can, I have many ways to get companies in, and then there's the traditional way. You go try to sell to a service, you build a product that they want, need, to spec.

AI assessment note: “I've got funding mechanisms and entry points at each stage of the company's life cycle.”

Q What was going on in Carnegie Mellon when you were there? What kind of robotics work?

A So what's interesting is that at that point, um, nobody could imagine how aggressively we would get pushed to commercialization. At that point it was, uh, you know, the Robotics Institute existed since I think the early nineties was the only university that really invested in that, that degree. It was a lot of work funded by NASA, by DARPA, um, Uh, caterpillar and deer were actually starting to fund a little bit of kind of more, uh, kind of industrial applications, but it was a lot of, like, applied research for autonomous driving, so navigating on-road, off-road, um, starting to develop the beginnings of perception systems, path planning systems, being able to ship this onto large-scale mobile robots, and actually try to drive intelligently, and a lot of the, um, people around that time ended up being the seeds, uh, that then propagated to all the, Grand Challenge, Urban Challenge, and then Waymo, Aurora, Uber, ATG. It was this really fascinating pocket of talent, actually.

AI assessment note: “a lot of, like, applied research for autonomous driving, so navigating on-road, off-road”

Q You kind of took the opposite direction of what you saw. Well, tell us about your background to start. I think you were Yale undergrad at Harvard Business School and you were, you were at Citadel after that. What's your background?

A I went to Yale for undergrad, like you said, Uh, with a private equity firm called Summit Partners after undergrad. Business school was working at Citadel. Um, I was actually on their long short healthcare team. It was, uh, the worst job I probably ever had as, uh, I was literally forecasting how many people were gonna need knee replacements and hip replacements based on weather patterns and how people were gonna fall and break hips. Uh, that wasn't gonna be very exciting. At the time, I then ran into the folks from, uh, Three G Capital, and that was the group of sort of, uh, Brazilian guys that had rolled up kind of the beer industry in South America. They bought InBev over in Europe, which owned, like, Stella Artois and left, and they had just bought Anheuser-Bosche and

AI assessment note: “I went to Yale for undergrad, like you said, Uh, with a private equity”

Q scream at me online, you know, or something. They really censored us. It is interesting how finally it's kind of opened up, and now, you know, does it feel like the corporations are realizing they have to be more careful not to, not to be extremists and activists, or are they just going to find new ways to be activists the next few years? Like, where are we with this?

A I don't know. I mean, it, it seems like the, the camp's really splitting in two. I think that for the vast majority of companies, they're realizing that the ESGD agenda, it didn't make them more profitable. And it didn't help them actually create. So it's called better societal value became more divisive more than anything. So you're seeing a lot of companies that are walking back from these positions. I think Goldman Sachs this week, no longer is going to force quota systems on board members. You're not going to be having, uh, Disney's drops in the DI, but other companies are leaning in. Costco over the last week has really doubled down on their DI initiatives, continue to have supplier quotas in terms of how they're going to get products.

AI assessment note: “it seems like the, the camp's really splitting in two.”

Q I love it. And so before you go into that, tell us a little bit more about your background and academic career. You, you, you, you studied computer science then or what?

A Yeah, sure. I'll, I'll go way back. So I was actually a computer science and philosophy double major as an undergraduate. I went to a, a small liberal arts school, um, called Bowdoin college in Brunswick, Maine. Um, after that, uh, I did a little bit of work in, in robotics as an engineer at a robotics company, and then studied neurobiology for a couple of years at Duke university, uh, before deciding to go back to grad school. So. Um, at the time I was very interested in, in how the human brain worked. Um, but, uh, ultimately I decided I wanted to design intelligence systems and, um, put them out into the world. And so I started to, to study machine learning and robotics in grad school, um, and got my PhD at Carnegie Mellon university doing that.

AI assessment note: “I was actually a computer science and philosophy double major as an undergraduate.”

Q And now you made a lot of money, and you're stopping, you're thinking, how do I have to go back and just to fight for society again in different ways?

A Yeah, and I had my second of two kids, and that was huge, because I was trying to think, what do I model for these little humans? You know, what's the world they're entering? And so I started reading, like, 15 minutes a day after I put them down, and that grew to, like, three or four hours a day. And I had a really good mentor, Michael Strong, who you know, he wrote me a 17 page annotated syllabus, started with the ancients, moved all the way forward, and it just kind of took over my life. And the first insight I had is there are more people like me who are tech entrepreneurs, who studied STEM or business or something like that.

AI assessment note: “I had my second of two kids, and that was huge, because I was trying”

Q And so what else did you learn? So 10 years in 10 cities, and then all of a sudden you started going into this hyper growth mode and opening tons of them. Like what clicked? Like what, how come you're all of a sudden able to go really fast?

A Interesting they ask that. So the first 10 years I moved to 10 cities, opened up 10 stores. I joined Young Presidents Organization, YPO. YPO said the entrepreneur has to hire professionals to run their company once they built the company. So in 1983 I made a million dollars and a million dollars in the bank. I didn't have any debt because I didn't know how to get debt. I didn't know how to make a business plan. I didn't know what it was. I saved up my money and opened up another store. So I hired some professionals to run my franchise business. I ran the company store. So from 93 to oh three, I took my 10 stores to 25, and took the franchise from zero to 200. And that, and this is a story, oh three, I got 200 stores open and 70 are failing.

AI assessment note: “I joined Young Presidents Organization... So I hired some professionals to run my franchise business.”

Q that means is just people could jam the spectrum. Like China could figure out, okay, you're talking to your 500 boats in this big battle this way. We're gonna totally jam everything. Boats can't hear from you anymore. Now you have all this autonomous stuff that's untethered. What's it do? Is it just stay there and get shot and destroyed then? Or can it keep fighting? Or how's that work?

A So jamming's interesting, right? It's not, it doesn't really zero out The communications bandwidth. What it does is severely degrades it, and only severely degrades in certain frequency spectrums. So you're, you're often able to get out snippets of information, and if you're able to, if you're able to use software to prioritize that information, you can keep connectivity back to headquarters. The other thing is, when you're using AI at the edge, each individual agent Is intelligent, and they know what to do. So each boat knows what to do, and then if they're able to communicate with the swarm, they're able to pass information amongst themselves. So Depending on the policies of the government, you could say, go out into this operating area, here's your mission, here's your objective, and if you get jammed, continue with the mission. So even if you're unable to get communications back, the platforms are still very, very effective.

AI assessment note: “if you get jammed, continue with the mission.”

Q on the brink, especially as we await You know, everything going on right now. Let's go to your background first. Your family immigrated from Moscow to the U.S. after the fall of the Soviet Union, and your father was a nuclear physicist, an expert in applied mathematics. Like, tell us a little bit about your upbringing. You, you really got into the world of cryptography and encryption early on, right?

A Yeah, that's right. So we immigrated in the mid nineties. Um, and I ended up in Chattanooga, Tennessee of all places, going to high school there. And my dad, uh, he was working for TVA, Tennessee value authority, but I was kind of bored, even though he was working on some really cool stuff, which was the deregulation of the energy sector in the U S and the free flow of electricity, being able to trade it based on spot pricing across the country. And he built some of those systems for TVA. Very early on, but still not as intellectually interesting as designing simulators for nuclear power plants. So he got really interested in the mathematics behind the emerging field of elliptic curve, curve cryptography, public key encryption. And, uh, I started helping him out as a high school kid. And, uh, that's what really got me into this industry. Uh, and you know, 30 years later, I'm still doing, doing it in some ways.

AI assessment note: “I started helping him out as a high school kid. And, uh, that's what really got me into this industry.”

Q you for being in DC fighting these battles. These are obviously really important, you know, just to, to end on optimism here on a couple of things, you know, you're immersed in the world of technology and policy. What are some of the most exciting breakthroughs that could give the U.S. advantages over China for decades to come, or what gives you the most hope right now for the future?

A Well, so I talk about the key to the winning this Cold War is really winning the technological race, first and foremost. Yes, you need to deter the invasion of Taiwan, make sure they never take it for just strategic reasons. But in the broader sense, it is really making sure that our economy wins over China's, right? And we're right now at 25% larger. There's a slowing down. If the trends continue, they'll never catch up with us. But if they manage to win the race in, in those four critical technologies, they might be able to. And those four critical technologies are AI and autonomy. I don't have to tell you about the importance of that. Second one, uh, that's closely related is biotech and synthetic biology, and not just in the area of medical sciences that people think about, but in the area of bioenergetics, by manufacturing, be able to produce new materials, uh, new energy sources in the lab. I think a lot of that innovation will be driven by AI and it's very, very exciting. Third one is space. You know, this area as well, uh, places like SpaceX and others that have Revolutionize spacelift, right, uh, democratize the cost of spacelift and, uh, the creation of these new modular satellites that you can put in low Earth orbit at a small price is helping us so much in resiliency, in, in intelligence, surveillance, and reconnaissance, and communication, navigation, really game c…

AI assessment note: “And those four critical technologies are AI and autonomy.”

Q And you know, there's been talk a lot of obviously not just drones, but drone swarms, dozens, hundreds, thousands of AI enabled battle networked, you know, drones, you know, a tradable units acting in coordination. We're trying to build versions of these obviously in different companies. What makes HPM a viable solution against the swarms? Like you can turn off all of them at once.

A Well, that's the thing. It's a wider area effect technology. So where you have lasers, you think of a laser has a very, very, uh, tiny little beam that needs to hit one target at a time and burn through that target and then disrupt it. Uh, a microwave system, especially at the frequencies we're using, can be very broad and spread. So we can spread All of that microwave into the atmosphere and everything in that section of the atmosphere would be affected by that electromagnetic radiation. So it lends itself just by the sheer nature of what we've brought to kind of the army and then the DOD at large. Just the sheer nature of it allows for that, uh, combating of a parallel set of threats. And when you combine that with some of the big data techniques that you see in Automatic driving and other types of industries like that. You have a sensor system that can see hundreds or thousands of things at the same time. AI that can drive basically an effector that can very quickly determine, okay, here are these drones, hundred drones coming from this direction. Hit them with a wall of these frequencies and these waves. Here's another set of drones coming from this direction. Next, shoot the beam over there in a microsecond and put another wall on top of those.

AI assessment note: “It's a wider area effect technology. So where you have lasers”

Q summer with notes from friends who journalists had reached out to, to try to find some dirt on me. So I think this is a culture right now versus to attack technologists, but let's jump into an analyzing them instead and hearing about them. You know, your book's called the geek way. How do you define a geek? You grew up obsessed with computers. Do you count as a geek?

A Yes, but that's being arrogant because geek is a term of praise for me. And I think more broadly in our culture, the definition of geek has morphed and it's now tossed around more as a term of praise or admiration than an insult. And it's not just somebody who likes computers way too much. These days, I think a geek is anyone with two characteristics. Number one, they get obsessed with something and they're tenacious and they can't let it go. And whether that's wine or Star Wars trivia or artificial intelligence doesn't really matter. They just get obsessed and they're, they, they want to solve the problem that, that is obsessing them. And if the solution that they come up with is unconventional, that's okay. They're not constrained by conventional opinion or their mainstream or status quo. They will go where their inquiries take them, even if it's to an unusual place. So these days my shorthand for a geek is a, is an obsessive maverick.

AI assessment note: “Yes, but that's being arrogant because geek is a term of praise for me.”

Q Yep. And tell us a little bit about the early challenges. You built some of these systems. This is not an easy thing to do. What were some of the problems with The first ones you created?

A Yeah, it's been a long and painful journey when I, I found this like 10 years ago, so it's been a sort of a 10 year sprint, I would say. And, um, yeah, just lots of trial and error. Of course, something this had never been done before, so we didn't know what would work, what wouldn't work. And, uh, I think the, the biggest mistake that I made was to go Too big, too soon. So back in 2018, you know, of course we had done hundreds of scale model tests, lab tests, et cetera, but, um, then we said, okay, let's just build the full scale thing in one go. It was this big launch in San Francisco, took the thing out. It was, uh, you know, we were in 60 minutes. It was like a, you know, big thing. And, um, you know, then the system didn't collect plastic and it broke into two. So, um, and that was, I think that was like a, Ten million dollar investment just down the drain in a few months.

AI assessment note: “the system didn't collect plastic and broke into two.”

Q So basically, there's, there's a lot of rivers in, in middle-income countries where, where the plastics, I guess the very poor countries don't have very much plastic. The very rich countries are pretty good at, Putting our plastic away in the dump. Uh, so there's not too big of a problem. So tell us about these rivers you're going after. Where are they?

A Great. So we, um, actually when we started, we, uh, there wasn't really any research on where the plastic was, uh, was coming from. So in 2017, we were, um, you know, the first ones to, to publish a, uh, a study to show where the, um, the plastic is, uh, is coming from. And what we found is that just one percent of the world's rivers, uh, do, You know, roughly 80% of all the, um, the plastic emissions. So it's very concentrated, and mostly in, indeed, these, you know, big coastal cities in, in middle-income countries. So, um, places like, you know, Panama City, Guatemala, you know, Lagos, Manila, uh, Mumbai, Jakarta, you know, those are really the, kind of the, the plastic pollution hotspots in the world.

AI assessment note: “places like, you know, Panama City, Guatemala, you know, Lagos, Manila, uh, Mumbai, Jakarta”

Q And he once used to, he was aiming to join a community in South Carolina, but he ended up by mistake in North Carolina, you said?

A Yeah, he was going to Marion, South Carolina, and, uh, he got on the wrong train out of New York. And ended up in, um, in Raleigh, North Carolina, and didn't know really where he was. So he spent the night there, and the next day, the, one of the managers of the train station said, look, there's a family in Charlotte, North Carolina, from Syria, and I'm gonna put you on the train to, to Charlotte, and he got there, and they had a coffee shop, and, ah, they employed him for a while, and then from there, he was able to make enough money, and He was a peddler. He went on a wagon from kind of the rural community around Charlotte and my hometown, Mooresville, North Carolina, selling everything from cloth to shoes to, you know, pins, needles, whatever you needed, he sold. And over time that morphed into a wholesale grocery business.

AI assessment note: “Yeah, he was going to Marion, South Carolina, and, uh, he got on the wrong train”

Q So, you know, we started the American Optimist to push back on the pessimism and division in our country. What areas of healthcare are you most optimistic about, and what are some of the exciting frontiers that we're tapping into right now?

A You know, there's a lot of talk about behavioral health in this country as of late, and I think, you know, rightly so. It's something that, um, that has, has potentially been under discussed, potentially been stigmatized in the past. Um, and we're seeing a lot of venture investment in this area on the back of it. Folks who are providing talk therapy over telemedicine, um, all well and good. Um, but one of the things I'm most excited about is an entirely different paradigm. For treating behavioral health, uh, psychedelic medicine. So, um, thinking about things like ketamine assisted psychotherapy for treatment resistant depression, thinking about things like MDMA for PTSD, thinking about psilocybin. Um, early clinical trial results for many of these different compounds are really positive, really strong, both for the basic sort of common disease like depression, anxiety, but also for things that are quite a bit more challenging to treat. Substance use, eating disorders, OCD. Um, I think we're on the cusp of both cultural acceptance, but also a whole trove of data being released about the effectiveness of these drugs and these types of therapies.

AI assessment note: “one of the things I'm most excited about is... psychedelic medicine.”

Q And, and, and how come you studied bioinformatics?

A So I did research at UCSF in a gene therapy lab for Parkinson's disease, and that's really where I fell in love with research. And a lot of my work there was sort of analyzing images, uh, in MRI as to see the distribution of, of how injected gene therapies distribute as, as it pertains to gene expression. Uh, and just absolutely loved the idea of, of at the time in 2010 was not a very loved field. Imaging informatics is kind of a backwater. Uh, and, but that we could use what was AI at the time to kind of automate these human tasks. That was so exciting. Uh, and then I was kind of saved because around 20 12 when deep learning came out, all of a sudden my field became one of the most exciting research fields ever.

AI assessment note: “I did research at UCSF in a gene therapy lab... fell in love with research”

Q Awesome. Quick, quick question on, you know, in, you wrote the book on entrepreneurial nation, why manufacturing is still key to America's future. A decade later, what's your assessment of U.S. manufacturing? Are we losing ground? Is manufacturing something that's, that's, that's still really important to our future?

A Very important. We're losing ground, and one of my concerns is the rise of China and our vulnerability on things like semiconductor chips on a huge supply chain, so we ought to be bringing some of it back to the United States, or at least to allied countries. One bill I'm very excited that I'm working with Senator Rubio on is to have the Federal Financing Bank, which basically can lend things to, to, to different agencies, lend to companies if they are Building factories that are critical to the United States, and I, and we can set up 50 factories across the United States in advanced manufacturing. Rubio and I are working on it, so it'll be bipartisan, and that's the type of thing that I think people will support.

AI assessment note: “Very important. We're losing ground, and one of my concerns is the rise of China”

Q How did that work? Do you think you were able to have some success with that between Arabs and Israelis? Obviously, that's a pretty intractable problem.

A Well, you see, we solved the conflicts. Now, at the micro level, it really does work. You know, we had ventures that we supported for 25 years. The partnerships we forged between Israelis and Palestinians and Jordanians and Egyptians and Turks and Arab Israelis and Arab and Jewish Israelis stood steadfast throughout the vicissitudes of the conflict for over 25 years, and so it was even transgenerational, like Yoel Benesh and Abdullah Ghanem, he, Abdullah's, uh, passed away, his children maintained their relationship with Yoel, same with their relationship with Turkey, um, but at the macro level, I mean, the answer is it's a necessary but not sufficient condition for resolving conflict, like economic relations and trade are very important, but obviously many other things have to come together also.

AI assessment note: “at the micro level, it really does work... at the macro level”

Q Let's step back a little bit from the wine process itself and talk a little bit more about cause-centric commerce. This is something, obviously, you're one of the first successful companies in this area that's really focused on commerce, focusing on a cause. Like, why, why, first of all, why do you take that approach? What, what inspired you to do that?

A Well, I loved when I first saw in the grocery stores companies using causes to market their brand and creating alignment and a mutually beneficial relationship between their brand and some nonprofit where they would increase sales. And, um, by doing so, they'd also donate a portion to that cause. I thought it was really cool and it actually spoke to me. I was a consumer that cared about that, but I also thought it was pretty gimmicky that it was, you know, temporary and it'd be A few weeks during October for breast cancer awareness month. And then by November, all of the pink ribbons would be gone. And so the idea was like build it into the brand year round, make it authentic, make it woven into the fabric of the brand.

AI assessment note: “I loved when I first saw in the grocery stores companies using causes”

Q Anything like that where you're investing in something that's working on a really cool problem or like, what are you inspired by lately?

A Oh yeah. Um, there was a really good, uh, article in Fast Company the past two weeks about our, our company called Spora Health. This is a deal We co-led with M-thirteen and refractor. It's, uh, it's telemedicine and telehealth for, for the enterprise, for really big organizations that have, you know, big insurance plans and, and, and, and, and have, um, a lot of employees. It's geared towards their African American employees. And what is geared towards is helping doctors really understand some of the root causes of health disparities for, for African Americans who work in these, in these, um, fortune, 500 companies. Uh, and, uh, the, the CEO, Dan Miller is just a really thoughtful, great entrepreneur. It's, you know, he's already, the company's already kind of, Oversubscribed and we think it's going to be a tremendous business success. He's got a, a great contract with United.

AI assessment note: “our company called Spora Health. This is a deal We co-led”

Q And so, so, so tell us about a few of your products. What are you guys actually doing? What do you could tell me about?

A Sure. So we're doing a few things. I mean, The first product that we worked on is called a Sentry Tower. It is a Solar-powered, infrastructure-independent AI surveillance power that you can put basically anywhere, put it around a military base, a border, critical infrastructure like power plants, desalination sites, and it uses radar, thermal vision, visible spectrum imaging, and a few other sensors fed into a probability model running on a computer that allows you to detect all the people, all the vehicles, all the animals, all the drones that are a couple miles around it. And these things also mesh together, they talk to each other, so you can deploy, you know, strings of these things a couple miles apart and get really good awareness of everything that's going on Around your base, or around your airport, or around your border, whatever it is you're trying to understand.

AI assessment note: “The first product that we worked on is called a Sentry Tower.”

Q And so, and so, and so you've played a pivotal role in a lot of that, this, especially in cell therapies early on. I think you did a lot of research on that long before this acceleration was happening. Can you tell us a little bit more about CAR T and cell therapies and what's happening there?

A Sure. I mean, the CAR T therapy stands for chimeric antigen receptor T cells. It's where we arm T cells with literally a guided missile in order to try to cure certain types of cancer. And it's actually been incredibly successful for blood cancers, not yet for the solid tumors, we can talk about that, but for blood, blood cancers. And it really began in the early 19 eighties. It actually began When my lab, when I was still in the lab, discovered how immune cells are actually turned on, and we discovered the molecular machinery, and a friend in Israel had this idea of using those discoveries to develop this therapy to attack tumors. I had no idea that we can use that information to attack tumors. We tried it in the early 19 eighties. It was the first time we made cars, and it didn't really work. And it took a few more decades to understand more about how to keep T cells activated.

AI assessment note: “CAR T therapy stands for chimeric antigen receptor T cells. It's where we arm T cells”

Q All of the sciences. Did you always want to do computer science, or was that, like, did that come from your parents?

A You know, it's interesting, because my parents are a little bit more old school. You know, they wanted me to be reading books and doing math proofs, but I loved computers as a kid in the, in the mid nineties when the computer boom was happening. I would be locked up in my room building computers, you know, coding and basic and learning the latest and greatest, whatever the most cutting edge thing was. And it was super controversial because the internet was getting going and I would spend all my time then on the internet playing these text based games, uh, that I was trying to learn how to also code myself. And it was not the most, uh, alignment, you know, it's like they would came from a different generation where the internet and, and computers were not a thing. And so they didn't understand what it was going to become. And, you know, so it was a little bit controversial, but I enjoyed it ever since I was eight years old.

AI assessment note: “my parents are a little bit more old school... but I loved computers as a kid”

Q So Boeing, obviously with a cost plus culture, it was a culture that would just spend whatever it took to get things done, not trying to be super efficient. How's that different than maybe insights in the culture of SpaceX? What are some takeaways from there?

A Yeah, polar opposite. So, uh, I joined SpaceX as an intern in 2003. The company was maybe 30 people. Then went back 2004, 50 something people. That's when I joined full time. And even from that point, I felt like this team of, this really small team of people could ultimately do a better job than the thousands of people that were working on this other program. Um, it would take growing the team and everything, but the basic, the basic software that ran the company was all about Performance. It was all about, uh, cost adjusted performance, not extreme over reliability or let's take years and years and years to do this program. It was, let's go quickly and then let's optimize the system for delivering the most performance for the lowest cost. That was basically it. And it was whatever it took to do that is what you did. Um, I remember getting there on day one and reading the employee handbook and on the top of page one was just a single line that was in bold. And it said, uh, this is not a science experiment. So it was all about, we're not trying to do any crazy new technology. We're trying to get, uh, rockets to be much cheaper. And so we will just have to clean sheet engineer them to take costs out of the system. And that's it. And it was almost that simple.

AI assessment note: “let's optimize the system for delivering the most performance for the lowest cost.”

Q But I know he's an amazing man. So he, he, uh, my, my mentor of mine, Milton Friedman was a mentor of his as well. So I, I met him very briefly, but I was a kid. He don't remember me. Um, but he wrote the real history of slavery. Like what was Thomas Sowell's conjecture here?

A So Thomas Sowell's point in writing the real history of slavery was as follows. He said, if you want to use history as a cudgel and as a way of Of undermining and lowering the status of your modern day political opponents. What you would basically do is focus on American slavery and pretend slavery wasn't a worldwide phenomenon everywhere, and also pretend or omit the fact that Britain in particular, but also America to some extent, are a huge part of the reason why slavery ended all around the world, right? What you do is you put the microscope on, on slavery in one country for a few centuries, and the subconscious lesson That, that, that, um, leads to is that white people are evil, black people are noble victims, and that psychology hardens in the modern day and benefits some people politically, right? Now, if you were being objective and you didn't have a political axe to grind, Sowell says, you would tell a more global history of slavery wherein you would be sure to include Certain facts, such as slavery was endemic to Africa before the first Europeans arrived there, had been thriving for thousands of years since time immemorial. The, the slave trade was not forced on Africans. It was absolutely part and parcel of the way in life, of the way of life, as it was not just in Africa, but pretty much everywhere for, for most of human history, most recorded history. 90% of the sl…

AI assessment note: “So Thomas Sowell's point in writing the real history of slavery was as follows.”

Q slavery is why white people are richer, or black people are poorer. I mean, obviously there must be something from a 150 years ago where black people would be poorer, and then therefore they wouldn't be quite as rich today, but how should we think about our national wealth tied to slavery overall? Like, how, how, and it's obviously tied to reparations. Like, how do you think about this issue?

A There's a whole school called the New History of Capitalism that was popularized like 10 years ago. And the way they argued was basically they would look at how terrible slavery was, um, hit you with a bunch of mostly true facts about how bad it was for slaves, and then pepper in statistics like at one point half of American exports in the early 19th century were of slave-picked cotton. It's like, whoa, half of American exports, that sounds huge, right? And then would jump from that Kind of, after that mood had been set, would say things like, America's national wealth is derived from slavery. And that sort of, if you read it all in sequence, it all kind of makes emotional sense. Then when you go back and unpack it, you say, well, hold on. Are, were America's exports the reason we became rich? Right? American ex, half of what? American exports peaked at six percent in In the 19th century. So it was half of six percent, meaning three percent. Three percent of our, of our economy was due to slave picked cotton. Now that's not nothing. Is that the basis of our national wealth? And then you, furthermore, you ask the counterfactual question, well, where would the American economy have gone if we hadn't have slavery? If we didn't have slavery, right? You look at the fact that Egypt had slavery and slave picked cotton at the same time we did. India had cotton that was picked even more…

AI assessment note: “Three percent of our, of our economy was due to slave picked cotton.”

Q So despite not being a PhD in computer science, you're able to work with him. Like what, what were you able to do to add value?

A You know, my, um, my email to him basically said, I, you can pay me whatever you want. I just want to learn how to start companies. And the idea was I was effectively going to be a junior product manager. Um, and Uh, at the time, the idea behind HVF was Max was going to start one company per year, and he was gonna find a CEO one year in to run each of those companies. And so, I joined basically thinking I was gonna look into markets, I was going to basically just be his chief of staff on the business side of things, and there would be a separate person on the technical side of things. And around six weeks in, uh, there was somebody who was pitching him an angel investment, He brought me into the meeting. He asked me what I thought about the company. It was, it was when big data was, was the industry du jour. Um, he asked me my thoughts on the company and I said, I think it's going to make money, but I'm, I'm pretty bored. And he said, hmm, I think you're a lot better at analyzing these companies than you are at rapidly prototyping.

AI assessment note: “I was going to basically just be his chief of staff on the business side”