Valuetainment - March 03, 2026


“Start With One Superstar” - Palantir Co-Founder REVEALS How The PayPal Mafia Found The Top 1%


Episode Stats

Length

6 minutes

Words per Minute

228.46165

Word Count

1,546

Sentence Count

143


Summary

In this episode, I sit down with Palantir co-founder and CEO, Alex Blumberg, to talk about how he got his start in Silicon Valley, how he went from a nerdy kid to a computer scientist at Stanford, and what it's like to work with Peter Thiel and Elon Musk.


Transcript

00:00:00.000 I want to start off with your background.
00:00:03.220 Palantir, when you say Palantir to the average person,
00:00:06.200 some is good, some is bad, some is neutral, some are scared.
00:00:09.620 You know, it's good if they know who you are,
00:00:11.280 but one of my favorite signs on the old defense secretary, Rumsfeld,
00:00:14.780 he had a sign on his desk and it said,
00:00:16.060 if nobody is angry at you, you might not be doing much.
00:00:19.280 Do you subscribe to that?
00:00:20.580 Oh, totally.
00:00:21.220 Okay.
00:00:21.560 Totally.
00:00:22.180 At what age did you subscribe to that?
00:00:24.880 Pretty young, actually.
00:00:25.840 I was a pretty obnoxious kid.
00:00:27.080 Were you?
00:00:27.600 Oh, yeah, I had all sorts of opinions.
00:00:28.880 I always have.
00:00:30.260 Tell me about your parents.
00:00:31.160 Who were your parents?
00:00:31.640 I met my parents.
00:00:32.560 My parents were awesome.
00:00:33.620 My mom passed away a long time ago.
00:00:35.620 My dad's not doing well, which is sad, but they're amazing people.
00:00:38.520 My father was very competitive.
00:00:40.100 He was one of eight kids.
00:00:41.140 He brought them all out to California.
00:00:42.920 He was our chess coach when we were little for fun.
00:00:45.000 He was a chemical engineer.
00:00:46.460 And we won the state championship when I was a kid,
00:00:48.860 and my brothers did too, and we thought we must be really smart,
00:00:51.260 and then he kept winning 20 years in a row.
00:00:53.000 So he's just a very competitive guy.
00:00:54.260 Everything, every game, every sport,
00:00:55.600 but a really optimistic, positive, competitive guy.
00:00:58.000 Chess.
00:00:58.300 So you guys play chess.
00:00:59.160 How old were you when you won the championship?
00:01:01.380 I was the K-6 champion twice in a row in fifth and sixth grade,
00:01:04.980 and we won the nationals in junior high school.
00:01:07.300 But it's because we worked really hard at it because he was a good coach.
00:01:10.400 You had to spend 30, 40 hours a week to be the best.
00:01:13.500 And this is in Fairmont?
00:01:14.960 We grew up in Fremont, California, and Silicon Valley,
00:01:17.680 and these were tournaments in California and around the country.
00:01:20.320 Who were you in high school?
00:01:21.840 It was a public high school.
00:01:23.100 I was a nerdy guy.
00:01:23.900 I was a valedictorian, and I had a bunch of really smart friends who taught me a bunch of stuff about,
00:01:27.900 you know, we went way ahead in math and science and stuff.
00:01:30.380 So at what point did you and Peter Thielen cut?
00:01:34.460 Because I think when I heard a story about you were still in college and you were doing something with them,
00:01:38.980 how did that relationship start?
00:01:40.560 You know, a lot of the smartest kids in Stanford computer science were going to PayPal at the time.
00:01:44.820 It was something where I really admired the talent that was there.
00:01:46.560 You have to realize that company, there was one company started by Peter Thielen
00:01:50.220 and a bunch of his smartest friends.
00:01:51.380 Max Levchin started it and David Sachs.
00:01:53.120 All these guys were there, Reed Hoffman.
00:01:54.800 And there's one company that Elon Musk started with Roloff and a bunch of other really smart people.
00:01:58.900 It was called X at the time.
00:02:00.260 And X and Confinity merged to make PayPal.
00:02:02.160 They were fighting each other and they merged.
00:02:03.500 So it was all the smartest friends around, both Elon and Peter.
00:02:06.000 No surprise, it was a place you wanted to be.
00:02:07.500 They actually rejected me my freshman year, but they let me in my sophomore year to go help them.
00:02:11.460 Was that like the place everybody wanted to work in?
00:02:13.500 Not everyone, but I think for me it was when I noticed a lot of the smartest, most interesting people going in there.
00:02:17.940 So it was when I was trying to fight.
00:02:19.180 How was the story coming to you guys?
00:02:20.960 Because, you know, it's kind of like, well, you know, at that time when you look at the numbers,
00:02:26.160 it's not like Elon is today's Elon.
00:02:28.200 No, no, it wasn't.
00:02:28.760 It wasn't.
00:02:29.280 They weren't who they were today.
00:02:29.600 But how did you know that these, would they talk about it in the small circles?
00:02:34.220 Well, I mean, I was a computer scientist.
00:02:36.100 I was already ahead.
00:02:36.940 I'd already done most of the undergrad work before I got there, which is normal nowadays.
00:02:40.760 And so I met a lot of the smartest other computer scientists, and they were all trying to go work there.
00:02:45.580 And their smartest friends were working there.
00:02:47.520 And then I was the editor of the Stanford Review, which Peter had started.
00:02:50.820 So I met people that way too through it.
00:02:52.780 Got it.
00:02:53.160 So Peter's way, how proactive was Peter of trying to get it in front of all the smartest kids coming out?
00:02:59.780 Oh, this is the most critical thing to do for these businesses.
00:03:03.380 So Peter was very good at that.
00:03:04.880 That's what we spend a lot of our time on now, flying up to see all the kids at Harvard and MIT this week.
00:03:08.740 We spend a lot of time on this.
00:03:10.500 So walk me through it.
00:03:11.480 So what does that look like?
00:03:12.380 Is it, you know, do you go straight to the top?
00:03:15.840 Do you establish relationships?
00:03:17.680 Are there programs to go meet the kids?
00:03:19.380 How does that work out?
00:03:20.280 Honestly, it's a good question.
00:03:21.000 People don't ask.
00:03:21.740 So Palantir, we had a whole playbook when we started that, you know, Palantir hired a lot of the top talent.
00:03:25.640 And so you'd have your fellows.
00:03:27.740 You'd have your spies.
00:03:28.720 You have your advisors.
00:03:29.880 You have all these, like, spies.
00:03:30.960 Spies.
00:03:31.060 These young men and women on your team, and they're, like, talented computer scientists, and they help you map out who the other best people are.
00:03:37.280 And they help you throw parties, and they help you get to know them.
00:03:39.760 And you know professors there as well.
00:03:41.300 And you just have people who are young, smart, technical people who are social, and they're there, and they're mapping it out.
00:03:46.780 And they're helping you meet the right people.
00:03:47.820 So when I come in, there's different groups we've met.
00:03:49.600 And people who want to work with us, we want to learn from them.
00:03:52.480 So it's a mutually beneficial thing where you're getting to know all the top talent, and you're helping connect them to your top companies.
00:03:57.140 And it just becomes a way to work with them all.
00:03:59.300 But how do you filter them out?
00:04:00.440 Like, how do you know?
00:04:02.000 It's like a chicken and egg you start with.
00:04:03.420 So I'll have a superstar from my portfolio who's, like, one of our best engineers who just came from MIT.
00:04:08.980 And they have, like, five or six of their smartest friends in the younger year.
00:04:11.440 And you'll go meet those kids.
00:04:12.460 They're the smartest guys you know.
00:04:13.580 So it's a network.
00:04:14.320 It's purely word of mouth.
00:04:15.860 So you're recruiting smart guys hanging out with smart guys.
00:04:19.960 And they would say, you have to meet John.
00:04:21.500 He's the smartest guy I know.
00:04:22.580 So you're asking them who's the smartest guy.
00:04:23.640 Yeah, and then you might talk to them, and you might work on projects with them, so you get to know a little bit.
00:04:27.280 But, yeah, you're just purely through the network.
00:04:29.140 I mean, it's a lot of things.
00:04:30.480 It's the same way if you're a football coach or you're a baseball coach.
00:04:32.680 You've got to do this for talent and tech.
00:04:34.000 But what do you look for?
00:04:34.820 So in football, you may look for speed.
00:04:37.920 You know, like, right now I met with one of the law firms that represents a lot of young talent.
00:04:42.640 Nowadays, they're recruiting kids at 10, 11, 12 years old.
00:04:44.860 I said, so what do you look for?
00:04:46.280 They said coachability and personality.
00:04:48.320 I said, why personality?
00:04:50.260 Personality equals sponsorship.
00:04:51.600 You've got personality, I can get some sponsorship money.
00:04:54.100 You're coachable.
00:04:54.800 We can put you.
00:04:55.280 Of course, you've got to have the physical abilities.
00:04:57.240 What did you guys look for?
00:04:58.360 You know, it depends if you're hiring an entrepreneur or hiring an engineer or an engineering leader.
00:05:02.680 It's because they're different.
00:05:03.120 Give me both.
00:05:03.520 An entrepreneur needs to have opinions.
00:05:05.840 An entrepreneur needs to be able to say, here's my hypothesis about the world.
00:05:10.520 Here's why I'm right.
00:05:11.500 Usually, they want to have some chip on their shoulder, something they're trying to prove.
00:05:15.040 They will have to be someone.
00:05:16.020 You can tell they're ambitious.
00:05:17.100 They believe in things.
00:05:18.700 You need smart, interesting, curious people to build things.
00:05:22.320 But you need to have, like, a certain level of leadership and opinions about the world, I think, to build things.
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00:06:06.240 If you enjoyed this video, you want to watch more videos like this, click here.
00:06:14.320 And if you want to watch the entire podcast, click here.
00:06:17.080 Thank you.
00:06:25.540 We'll see you next week.
00:06:25.700 Bye.
00:06:25.980 Bye.
00:06:26.040 Bye.
00:06:26.160 Bye.
00:06:27.260 Bye.
00:06:28.420 Bye.
00:06:29.380 Bye.
00:06:30.340 Bye.
00:06:34.500 Bye.
00:06:35.120 Bye.
00:06:36.360 Bye.
00:06:37.580 Bye.
00:06:45.260 Bye.