The a16z Show - Building the Physical AI Stack | Travis Kalanick on TBPN

Episode Date: July 23, 2026

Travis Kalanick joins TBPN to discuss Atoms, his vision for industrial AI, and why he believes the biggest opportunities in AI lie beyond software. He explains how Atoms is bringing autonomy to mining..., logistics, and food production, why robotics will reshape physical industries, and how lower costs and greater automation could unlock entirely new economic opportunities. Travis also reflects on raising $1.7 billion, building in stealth, regulation, hiring, and what he's learned since Uber.   Resources Follow Travis on X: https://x.com/travisk Follow TBPN on X: https://x.com/tbpn   Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see http://a16z.com/disclosures. Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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Starting point is 00:00:00 Travis Kalanick joins TBPN to discuss why he's betting his next company on industrial AI. He shares his vision behind Adams, explains how autonomy is transforming industries like mining and food production, and discusses why bringing AI into the physical world may be an even bigger opportunity than software alone. Before we start, the last time you're on here, that was, for me, the best moment of making the show ever. John and I, it was totally surreal and we really enjoyed the conversation. But to me, we left that and it was almost depressing because as somebody who started getting into startups in the 2010, you were that guy. And then I was realizing with the show, we had that conversation with you and it was a significant
Starting point is 00:00:55 day for you. But it was sort of depressing because I realized like a moment like that. that would never actually come again where I got to basically interview. It will happen. It will happen. It will happen differently. But, you know, a childhood hero having that conversation, that's one of one for me. I don't think it'll happen again.
Starting point is 00:01:14 There was peak. It was good. But anyways, you've been busy since then. I've been busy. And we're... Look, I'm super excited. It's my first Open AI podcast. I'm very excited about it.
Starting point is 00:01:26 Also, I want to let you guys know that... If you need therapy sessions for what it's like to be a maid man in retirement. Sure. Like, if that's a thing, I can help motivate you guys. Isn't step one of the therapy in this situation, just get a jet ski? No, it's just, it's actually denial. You've got to get over the denial. Okay.
Starting point is 00:01:45 Over the denial? And then the acceptance? Yeah, it's something. I don't know the 12 steps. Yeah, yeah, I, everyone just knows denial and acceptance. They don't know any of the other ones. It's like a bunch of shit in the world. Grieving, bargaining.
Starting point is 00:01:56 There's a couple others in there, but you do go through that. It's natural. Yeah. It happens, but then you start building. Yeah, that's good. If you guys need advice, you need therapy, I'm here for you. I love it. I mean, you know the retard maxing is you're not supposed to do therapy.
Starting point is 00:02:07 I'm just saying there are benefits. Especially with your new partners. They're like, if they're one thing, they wrote into the fundraising round, they wrote into the docs, like, cannot go to therapy. Oh, that would be amazing. Yes, but podcasts are modern therapy for men. This is what men do. They don't go to therapy. You should have, you should have office hours for founders, but they have to just come out on a jet ski while you're going and you're going, and you're going,
Starting point is 00:02:28 70 miles an hour. I'm, I am starting to teach many founders and people in tech world how to water ski, how to wake surf. A bunch of my engineers already, so there was one guy who didn't know how to swim, but I got him behind the boat wake surfing. Whoa. Whoa. Is that a life jacket?
Starting point is 00:02:47 Life jacket. Life jacket. It sounds weirder than it is. But it was still very weird. It's high risk. Yeah, it was good. Potentially. Okay, cool.
Starting point is 00:02:58 The business. Business. Dude, it's business time. Yeah. Got to put on the business socks. Unfinished business. Unfinished business. So, yeah, I announced earlier today.
Starting point is 00:03:07 We did a $1.7 billion raise. There's some noise that's going to happen. Wow. Now. One mallet. That's just fucking, you guys are crazy. You guys are crazy. I'm going to try to trust.
Starting point is 00:03:23 I'm hitting it next time. Come over the top. So much noise. So much noise. All right, but walk it through. I feel you came in very relaxed. Walk us through. I think it's been what.
Starting point is 00:03:38 This has been four months since we talked? Three or four months? I'm like that. Yeah, I think we talk in April or March? I think March. Yeah. Oh, that's right. Early March.
Starting point is 00:03:48 Four months. So, so, yeah. So what happened with the business to unlock the next round? I mean, we continue to go up into the right. But like, the announcement of Adams was we are, We are going to do physical automation, physical AI, what we are calling industrial AI, to transform these industries one at a time. Yeah. We did food.
Starting point is 00:04:13 We moved into mining. We're doing transport. And it's working. And so that's how you go. Yeah. And then, of course, there's like going out of stealth. There's all the things. And it was just the right time.
Starting point is 00:04:27 Yeah. Yeah. So, yeah, we just went to market. We said, when I originally went to market, I was like, these were separate companies. Yeah. Okay? So our mining and transport was a separate thing. Food was a separate thing.
Starting point is 00:04:42 And we had a bunch of other, you know, a bunch of subsidiaries doing cool stuff. And I said, which one do you guys want to do? Do you want to invest in mining? Do you want to invest in food? Do you want to invest in this? And they're just like, we want to invest in you. Yeah. Yeah.
Starting point is 00:04:55 And we heard that, like, we took, like the first five folks we talked to, also. said that. So then what we did is we put the companies together and then sold the equity in a singular entity. Yeah. Yeah. So just put it together. And it's much easier for me. I don't know how Elon does it with all the different companies. Different capitals. It's wild. Well, no, no. The answer is what's been happening, right? It's like more and more together. Guys, he did it for 20 years, though. Yeah. Yeah. Yeah. He's still technically doing it a test. They're different companies. Boring company, neuralink.
Starting point is 00:05:34 Like, he still has a lot of, lots of cool stuff. But the lesson in there for investors is like even with Elon companies, there's such an insane power law where you have a $10 billion company and then you have a, you know, a $2 trillion company. Yeah. Right. And it's like you just want exposure. You want broad exposure. Ideally, you know, you could just invest in the one that breaks out, but you want broad exposure to the category. When things are first getting going, there is a lot of upside.
Starting point is 00:06:00 of having them separate. Sure. Because if somebody wants to invest in a really cool thing, and this is what happened when we first got the transporter mining thing going. If they want to invest in that cool thing, they're like, I don't know anything about food. By the way, food on its own is robotics, real estate, like restaurants, like, you know, and so they want to be exposed to that one thing,
Starting point is 00:06:22 and they don't want to have to underwrite something going across all things. And they're like, well, if you're losing money over here, I want you to lose money over here. So how much of the money I'm putting in is going to go to that. There has to be a theory of the case of how you put it together, how you allocate capital across. And honestly, once you're starting to get to profitability on one or more, then that conversation starts to get easier.
Starting point is 00:06:45 And I think that could be why, I can't speculate on sort of Elon's world. But certainly I'm super excited to have those pieces put together into a single, into a single puzzle. What does go-to-market look like in the mining industry for you? It's the frickin' best. Okay, because specifically, like, when I think of your go-to-market,
Starting point is 00:07:12 it's so good. It's so good. It was deploying young people to a new city in Miami and they're doing a marketing stunt and it's not like you're calling in favors or leveraging your network to, get Uber up and running in a new city. That was something that was organizational design.
Starting point is 00:07:34 So hold on, that's consumer. Exactly. So how is it different? Well, it's just like, well, all the food stuff we're doing is business, almost all of it. Yep. Really all of it. Mining's all business. So look, there is a big thing.
Starting point is 00:07:46 If you go from doing consumer to doing business, I think we may have talked about this last time, that's a whole other ballgame. Yeah. I mean, that takes years off your lifespan. and doing it, like getting good at it and then owning it. But mining go-to-market is cray-cray. Yeah. Like, so I'll just get an example.
Starting point is 00:08:07 A month ago. A month ago. A month ago. Well, yes. You do that. But, but, you know, I can a lot of times, look, when you have very efficient transportation, you can go places. So a month ago, I dropped into deep,
Starting point is 00:08:27 Amazon in Brazil. Okay? Like deep northern Brazil, like Amazon. Places you can't even get a jet ski too. Guys, it's the Amazon of the Amazon. Okay. Okay. And like tiny airports, you're just like, you kind of just dirt.
Starting point is 00:08:45 You slide into the DMs except there's a tarmac, okay? Sure, there you go. And great pilot. Yes, of course. Yeah. And massive iron ore mine that we're operating in there. Okay. And you see, like, we took, we were there for a couple days because we already have customers there.
Starting point is 00:09:01 Sure. A customer is called Valet. It's a massive mining company. Yeah. And they, it's like the world's largest iron ore mine. And you go and you get in a helicopter, just going over one of the sites takes 30 minutes. Wow. Okay.
Starting point is 00:09:18 And it's fascinating. It's so fascinating. And you're learning how the system works. you're sort of figuring out how do I you basically take a kit you apply you you you install it onto a machine and that machine becomes autonomous and some of these machines are like 20 years old
Starting point is 00:09:36 some of them are new and so there's lots of different kinds of machines as well and you're making the mine more productive you're you're making it way safer it is super like they have lots of safety protocols but like it is mining dangerous business it is a
Starting point is 00:09:54 dangerous business. And the OPEX goes down all at the same time. It's kind of a beautiful thing. And then, you know, I went from Brazil and then straight from there dropped into the border between Iraq and Saudi on the Saudi side. So we have a phosphate mine that we're doing stuff there. The signals were jammed. So we had to like, my pilots had to land kind of like old school style, like physical, visual. Is that because of the conflict going on in the region? And just the general, the vibes on the borders there. Yeah. Yeah.
Starting point is 00:10:30 So, but same story. And so go-to-market is wild. It just end up in like crazy places, but it's super needed. And so what's happened is the Pronto technology has gotten past human productivity, which means you go to a gold mine CEO. You talk about go-to-market, you go to a gold mine CEO, and you say, would you like to have 20% more gold per year? Absolutely.
Starting point is 00:10:55 We haven't heard no. Yes. Okay, okay. But they say prove it. Yeah. And that's where the rubber meets the road, right? How long does it take to prove? It used to take a lot longer.
Starting point is 00:11:04 Now, like, once you've proven it enough times, then it sort of gets its own momentum. Gets around. And so we're in that place on Pronto where that momentum is taking hold because there's enough proof points where it's just working in so many different places where people are like, all right, let's go. We're going to think of mining, autonomous mining, almost like enterprise software where you get a pilot. There's like a 10,000 person company, and you've got an enterprise startup, and they're like, I got like eight seats, but it's this huge company. And if we get it, it's huge.
Starting point is 00:11:38 And I've got this other 10 seats over at this other one. It's a pilot, but I swear it's going to work. And they're out there pitching and trying to make it happen. Yeah. But once it works, and in mining, that means human productivity, human level, better than human productivity. Once it works, it goes big. Yeah. And they're like, okay, let's get across all the vehicles.
Starting point is 00:12:03 And so we're sort of in that mode with a bunch of different customers right now. How big is the opportunity to just increase uptime of mining operations? I imagine that there are mines that are trying to operate. 24-7, but getting a night shift in the middle of the Amazon, reliably, everyone's showing up and being, you know, healthy and happy and eager. It gets a lot easier when it's like, yeah, we're still going to have a bunch of people on site, but they're going to be overseeing robotic work. Sure.
Starting point is 00:12:33 So, yeah, I mean, there's two parts of the productivity gain. First is the machine per hour doing more. Yeah. That's part one. Part two is hours and call-out. and all of that stuff, as well as just, you know, the safety protocols change when you have less risk.
Starting point is 00:12:55 So there's a lot of things like this that pile on to each other. My guess is you could even end up 30%, 40% more productive at the end of all of it. And when you do that, the opportunity speaks for itself. A gold mine that's doing 30 or 40% more gold per year is kind of, whoa, but that's for every mineral. that's lithium.
Starting point is 00:13:16 That's like we also go all the way down to quarries. Queries are different because quarries are basically it's about cement, let's just say. That's the main jam. There are others, but let's just go with that. You can't, you don't just go do more rock because you need cement customers on the other side. They're only using so much cement.
Starting point is 00:13:35 Like where to store it. Yeah, exactly. Yeah. And so that's more of an op-x play and there are thinner margins there. But I'm in the game. And it's kind of interesting, and it's a lot of fun. And for that company, for Pronto, they were super, Anthony Lewandowski and the team there, super scrappy, true startup style.
Starting point is 00:13:59 Lean as hell. Like, so lean. Like that Christian Bale movie, I can't remember the name of it. The Machine Institute is like super lean. And I'm like, guys, we had to go from lean to muscular. You got to go to Batman. And that's what we're doing. And you think of that, this.
Starting point is 00:14:13 Lean to muscular. That's a good, that's a good, that's a good, that's good praise. You just want to be muscular. And so you think about enterprise go-to-market. Part of our go-to-market is building credibility with our enterprise customers that we're going from lean to muscular. Because the demand is there. It's ready to go.
Starting point is 00:14:34 They're like, we need you to be muscular. We need the protein powder and the whatever else. What holds you back from? You go to the gym, whatever. What holds you back from scaling? Let's say you do a pilot. It works well. You're attaching hardware to existing systems and hardware that they're using.
Starting point is 00:14:54 And they say, okay, we're getting more out. Maybe we want to place orders for more machines. I imagine lead times on some of this mining equipment could be insane. How much of the stack do you want to own? Say the question again. I'm sorry. Just blank. Go for it.
Starting point is 00:15:13 When we're like right now you're taking existing mining equipment and you're augmenting it with you're bringing you're you're making it AI enabled you're making it autonomous you're making it more efficient yeah and they say great this is working we want to scale up our operation because maybe we need less or we can do more with the same you know human head count yeah but what's the I imagine there's some things that are out of control for for you at that point where they're like okay we need more of this heavy mining equipment let's let's add it to the site but is there like a lag time there? The real lag time is getting, so you have to, so let's say we want to get a bunch
Starting point is 00:15:48 of machines that are in the Amazon up and running. Yeah. Okay. How do you do that? So I've got to ship a bunch of sensors, a bunch of compute, a bunch of equipment and mechanical systems, let's just say, so that a team can then go install it. Yeah. So you're basically building a data center on site? I wouldn't put it that way. I would say, I mean, if you considered a machine with sensors and compute a data center, I mean, you could. But it's really, think of those, there are servers, but I wouldn't say a data center. It's not really like that. Some operations bring, like, an Armada-style, like, shipping container-sized level of...
Starting point is 00:16:28 You just... So you bring in the stuff, okay? You have to install it. Yeah. you have to like bring it up and make sure okay this is a new place how does it does this machine work properly in this new place and calibrate and make sure it's safe and all of this so there's like a process of getting it up then there's change management because that that site's going from there are people that show up in the morning there's all this very regimented process to make sure everything's going exactly as planned and people are exactly where they're supposed to be because otherwise weird things happen on on a mining site. Yeah. So you have to go from that to, okay, we're now running an autonomous mining operation.
Starting point is 00:17:12 It's just a very different thing. So the installation and the bring-up and what we call commissioning are sort of like the things you have to do. And, you know, like, why does it take a long time to install? Because that machine may not even be drive-by-wire. Yeah. So you have a mechanical system. Like if you turn the steering wheel, like it's, you know what I mean?
Starting point is 00:17:35 Yeah, yeah, yeah. It's a mechanical system, a hydraulic system. You're bringing, where you have to go. Actuator that might push a physical button. You're, yeah, you're trying to make electricity then do a physical thing, so then you need physical actuation. Yep, yeah. To do the things because it's not, these machines are not natively drive by wire.
Starting point is 00:17:55 Yeah, so that's not all machines. So that sounds, that sounds incredibly difficult but necessary because you're not going to get a mine to rip out tens of millions of dollars of equipment that they already have. But would you eventually go full stack, like build the entire? I mean, look, we ultimately, I mean, if you go in the mining industry, there's like this term. It's called no entry mine. A no entry mine is a mine where there are no people in the pit. Lights out factory.
Starting point is 00:18:25 Yeah, kind of like that version of it. There might be people in a control center. There might be, but like in that pit. No human. And it's a wildly different calculus from a safety perspective I imagine. Totally different, obviously. And so there's drilling, there's blasting, there's loading, there's haulage, there's crushing. I'm just going through the different parts of the mining operation.
Starting point is 00:18:52 And what you do is you start somewhere and then you start extending to those other areas to get to that no-entry thing. And the no-entry thing is you can have an autonomous thing. Like our haulage system is autonomous. If you're getting into a new place, you can do remote control and move into autonomous. If you want to go super no entry or lower entry, mine, if that makes sense. It's super fascinating. And then you're talking about, you're talking about loaded a two million pound machine that's moving potentially 35 miles an hour down the road. And it's an off-road thing.
Starting point is 00:19:33 The two million pound machine moving 35 miles an hour off-road. Yeah, dude. This is why you have to get a TV. This is the ultimate ATV. So, no, you get in it and you can, you know, you can experience it. I mean, it's not like there's like an amusement park for this, but like I've certainly experienced it where I can get in the machines and check out what's going on. This is like the dump truck.
Starting point is 00:19:58 Are any of these 20-foot tires essentially? Are any of these companies, like, acquisition targets where you would be able to come in and say, like, you're doing a lot of stuff well, but here's all the stuff that you're never going to figure out like us? I mean, look, I would say the way we think about it is the, the haulage part of a mine is where most of the vehicles are. And so, and we think of haulage as the cardiovascular system of a mine. So we're obviously very connected to all the other machines, but we're. We don't do all the other machines, so we're like in an ecosystem. So we can work with them where, like, there's APIs. Because, like, if you're doing haulage, you need to know where the other machines are and what their status is.
Starting point is 00:20:39 Yeah. As an example, there needs to be orchestration and coordination there, which is pretty interesting. In terms of, like, acquisition, like, you know, I do, I have to sort of admit, like, the Uber mentality, my mentality, let's just say. My dune. Yeah, yeah, it's like not, I guess Uber is different today. In my world, we didn't acquire shit. We just built. Yeah, that's right.
Starting point is 00:21:03 I don't know if I have an opinion yet. I'm not, like, religious about it. But if we feel like we can build something, we do. But sometimes people have differentiated awesome stuff, and you're like, let's partner. We're open to it, you know. How would you pitch me if I was a young person, Stanford, CS, new grad, worried about software engineering not being the easy path where I can bounce around from Google and maybe Uber had a cushy job for me. Pitch me on going to the Amazon and building me. And that's awesome. I mean, that's awesome. I thought I just did. I mean, that was a good pitch.
Starting point is 00:21:42 That was the pitch. Do you think, do you think young people are receptive to this pitch? Yet, are we about to be receptive? Why should they be receptive? It's really interesting because I only run into the young people that are receptive. Sure. Like, I'm not out there pitching like lame sauce dude who doesn't want to work. Sure. Sure. Like I don't end up to me. I don't end up in the same room as this guy. Do you want a job where, do you want a laptop job or do you want to be dropped in to a mine in the Amazon and like build, you know, science fiction? This is the thing, right? This is why that Adams thing is cool.
Starting point is 00:22:15 Because you're not dropping a, you're not dropping a fucking app in the app store. You're like automating a two million pound machine going 35 miles an hour carrying gold. Do you do you watch a, um, Do you get a lot of profanity happening today? I don't know why it's happening, but it is. No, it's let it flow. I want to acknowledge it. Do you, do you watch science, do you get inspired by science fiction at all?
Starting point is 00:22:42 I can, I can imagine, like, watching Dune for you. You're just, like, texting pictures to the team. Of course. I'm like, I'm, my fave is Asimov. He's my fave. Yeah. You know, the I-Robot series is, like, just so epic. What is your takeaway from the iRobot series with regard to AI safety, Doom, generally?
Starting point is 00:23:07 Have you ever had moments of maybe we won't figure it out? Won't figure what out? The alignment problem broadly? Like the iRobot, the three laws of robotic is sort of an elegant solution. It's tested obviously. But I love to come back to a world where everyone, both the Doomers and the AI builders, agree that, yep, the three laws of robotics will be sufficient. But I mean, in some ways, well, in some ways in the series, the three laws don't always work out.
Starting point is 00:23:38 Yeah. So I think there's a lot of, I thought there's a lot of nuance to those three laws, even though the laws are sort of so simple. Yeah. I love the intention of those laws. I sort of think of it a little bit differently, which is I have been entrepreneur for a long time. Like a long time. Yeah. And I have failed.
Starting point is 00:24:02 And when I think about why I failed, it's usually because I was building something that nobody liked. So if you build something that people don't like, I don't think you're going to succeed. So how does that relate to your question? He's like, please tell me, because I'm not connecting the dots at all. What are you talking about? Well, if you make something that is anti-human, if you make something that you make something that that doesn't serve people, I don't think you're gonna make it. I don't think you're gonna make it.
Starting point is 00:24:37 And by the way, like, yes, we're using AI to help us make decisions, et cetera, but what do those AIs really, really wanna do almost too much? They wanna please us. So I just think if you're not making stuff that humans want, it's not gonna work out and that's kind of obvious, obviously, but I think it keeps going.
Starting point is 00:24:55 Yeah. And yes, there's the dangers and the things and the miss, but that's my, that's my, starting point for how I think about these things and we can't control all the things. And I do think, of course, you have to have safety situations and there's collisions of like what do I, what do I prioritize first and how do I do it, which is I think where Asimov's laws go. But instead of writing sci-fi books, I'm just doing the thing and I'm making sure the machine stays on the road. Yes. And related to that idea of like doing the thing, making the machine stay on
Starting point is 00:25:31 the road. I imagine that your your world board view is somewhat informed by your contact with reality, the fact that you can see the progress of diffusion, how long drive-by-wire systems took to roll out, and the need for AI to be deployed in like tactile ways that, that, that, you just see it as more positive sum, more, there's more opportunity. I still like you're deploying robots that people want. Right now, robot, I mean, look, there's some point where robots have their own bank accounts and their citizens and all this, we're just not there yet. Sure, sure.
Starting point is 00:26:05 And until we get there, that robot is owned by somebody. Yeah. And that somebody has a bank account. Yeah. And they are paying based on the value you're bringing them. Yeah. Because they like your stuff. So if you are doing things that humans don't like, you're done.
Starting point is 00:26:22 Yeah. And trust me, I've done it. Yeah. I've built things that nobody liked and it sucked. Yeah. I don't recommend anybody do it. If you can avoid it, you totally should. Yeah.
Starting point is 00:26:34 On the business model side, what are you doing now in mining and where do you think it could go over time? Because if you're able to bring in a system that helps someone increase their yield 30 to 40 percent, I imagine eventually you just do some type of JV so that your guys have line incentives. Oh, look, there's, you know, and the instinct should be how to enter up. enterprise company, enterprise software companies do it. Start there. And you guys will know that. You know that. Yeah.
Starting point is 00:27:06 Yeah. What's the answer? Let's just say your enterprise software company, you're making a company more productive. What do you do? Raise prices. Subscription. Or you, the price goes up when you prove that productivity. So there's baseline.
Starting point is 00:27:20 And then based on outcomes, you get a little extra juice. Sure. Sure. And you can say. Or you're always trying to make sure that like you want to be producing, creating more value than you're capturing, but there's this sort of cat and mouse game where you're always trying to get you don't want to give away maybe too much value. Totally.
Starting point is 00:27:38 But here's the thing. You never go to a customer. I don't care what you're selling. Okay. I don't care it's enterprise software. I don't care if it's widgets. I don't care what it is. You never go to a customer and say, give me a percentage of your stuff.
Starting point is 00:27:49 Yeah. You go to a customer and say, here's the price of our stuff. And if it does really well for you, we think we should get a little more scratch. Shish stuff, you know, whatever. You know what I mean. Yeah. Yeah. And it's that simple.
Starting point is 00:28:05 Don't be crass about it. And, you know, partner with folks. And they're down. They want to win, too, you know. It's literally an enterprise. It's an enterprise software style negotiation or approach to the whole thing. Yeah. And the more differentiate your value is, the more you're going to get.
Starting point is 00:28:23 Yeah. What is your process for hiring executives today? Prey. I was hoping you had the Calenic system to achieve a 99%. No, but why would I tell you if you're in. No, I mean, no, but I think you can't. This is one of those things you can tell people exactly what you do, and they're not, they're not Calenic,
Starting point is 00:28:47 so they're not, it doesn't, that doesn't mean they can compete with you. Do you know they could, yeah. Okay, so how would I put it? Look, I think no matter who you go, nobody's nailed executives all the way. It's weird because what will happen is executives talk a fucking awesome game. And there's two things you want an executive to do. You want them to be able to organize at scale, organize and manage at scale, lead. That scale.
Starting point is 00:29:20 You also want them to be epic problem solvers, the most strategic. bad ass problem solvers alive. This is like being left-handed or right-handed. And there's very few people that are ambidextrous. But you need that. Now, somebody's, they're always leaning a little bit one side or the other. The best executives are the ones that are doing both well. But I have come to the conclusion over my years doing the stuff
Starting point is 00:29:45 is the problem solving is the most important thing. If you get somebody who organizes and manages well but cannot solve a problem, they're going to be doing it. ridiculous stuff in a super organized way. And so that's the, and sort of my theory, maybe there's a couple theories on how I manage or how I lead is that the only constraint on your imagination is management capacity.
Starting point is 00:30:11 But what is management capacity? It's really problem solving at scale. Sure. Because if you are doing super well over there, guess what? They're problem solving there. I can create other awesome problems. Yeah. Yeah.
Starting point is 00:30:23 Like I love creating problems. Sure. Go solve those too. Yeah. But if I don't have the management capacity, then I'm effed. Sure. So the management style that I do is sort of problem solver in chief, which is I take the most impactful problems that are not being solved and that's on my desk.
Starting point is 00:30:44 Yeah. Or desk or room or whatever you want to call it. That's where I'm spending my time. So people go, oh, what do you spend your time on? I'm like, it depends what the frickin'n' problems are that matter and it can change. and that's how I roll. But it means once you have a problem solver-in-chief mentality, that flows downward.
Starting point is 00:31:03 That means any direct report of mine must be the deputized problem-solver-in-chief. And they've got there, because there's only 24 hours in a day, I can only solve so many myself. They have to then take that for their world and do the same thing and then do the same thing to their people. Yeah. So the bottom line is you've got to prove
Starting point is 00:31:21 that these folks can solve actual problems. aren't just talking the talk. That's the number one. And then on the interview process, simulate what it's like working together so that day one really feels like week two. And day one, you better be excited. So if you're excited day one, after simulating what it's like working together in the interview process, then day one is really week two and you're still excited, you took a lot
Starting point is 00:31:46 of risk out of the system. That's all I got for you. I have a question about regulation. Uber famously went city by city. Yeah. The AI labs are duking it out over federal preemption. Did you ever have, develop a theory around when federal preemption is better than state-by-state regulation? Do you have a philosophy around this?
Starting point is 00:32:09 It seems like the labs go back and forth on what they want. It's hard to see where the chips are falling. Federal preemption is good when you are pro-regulatory capture. Okay. When you want to squeeze others out, you should get federal regulatory bigness going for you. Yeah. Because then you don't have to do the ground game that you went. Well, no, you're squeezing others out.
Starting point is 00:32:35 Okay. It's just the whole point is to squeeze everybody out. Sure. I never did that. Like, we never did that. We basically never ever proposed or pushed any rule that would be. beneficial to us versus somebody else. We always were trying to open up the market
Starting point is 00:32:55 and we said let the best man win and we just went for it. But I think we got to be careful of some of these close weight things that are creating situations where they need to be regulated
Starting point is 00:33:11 and they want it. I'd be very, I'd keep an eye on that. Yeah. Well, you've got to have customers that love your product and they're willing to write their their representation. When you guys, you know, decide to tell your own hacker to hack the thing and then go to somebody, then go to the federal government and say, then go to the federal government and say, dude, we save the day. Like, you know, you don't have to see me. You guys don't have to do this.
Starting point is 00:33:43 You guys don't have to do it. On regulation, I'm sure you saw the trial lawyers that are fighting back against a. autonomous vehicles because they're worried they're going to be too safe. Yes. I'm sure that's not surprising to you. No. So look, every bad thing that you see in transport, like systemically, anything in transport that you view is systemically bad was most likely pushed by the trial lawyers and the insurance companies.
Starting point is 00:34:12 Wow. Every single bad rule that's weird and dumb. Yeah. the insurance companies and the trial lawyers were in the game, big time. Where do they align? What do you mean? Well, because trial lawyers, I imagine, want more accidents. Insurance companies are the ones that pay for it.
Starting point is 00:34:35 Wait, yes. Yeah, yeah. No, no, remember, insurance companies make margin on accidents. Oh, okay. If there's no accidents, there's no insurance company. In a weird way, they love accidents. Because the premiums go off. As long as it's in their actuarial table, they're pumped.
Starting point is 00:34:49 Wow. Yeah. Right? What they don't like is accidents they didn't plan for. Sure, sure. But accidents that they plan for,
Starting point is 00:34:56 who, business, big insurance outcomes. Yeah. They love. Like I remember, we went to D.C. And the taxi system,
Starting point is 00:35:07 the liability on a ride, if you took a taxi, it might still be this way to this day, was like $25,000 in a taxi. But we went to, we being Uber at the time, went to D.C. And they pushed a one and a half million dollar policy per ride.
Starting point is 00:35:27 Okay? So what does that mean? That means, well, this, you know, accents are going to happen. We're probably, like Uber's probably safer. But it just, you think the trial lawyers weren't pumped about that? You think the insurance companies weren't also pumped about that? They can go get up to a million. Because, by the way, the insurance company might be on the other side.
Starting point is 00:35:46 Yep. And they're like, oh, there's a, there's a one-half million. dollar bank account here that I can get access to on a random accident. Right. What can you share on the transportation side of the business right now? How much is that business in service of mining or food versus? It's number one. So number one is it's, so I call it wheelbase for robots, which is if you're going to do
Starting point is 00:36:12 specialized robots that move and act in the physical world, they're either humanoid. which we're not. I'm not anti-humanoid. I'm just non-humanoid. Specialized industrial robots, right? So that's, it's high-scale, industrial-scale tasks, which means you would not have a humanoid ever do that. That means you've got to be on wheels.
Starting point is 00:36:37 So we've got to build wheels. So that means, okay, well, when food, when supply chain is going into our facilities, that's a freight vehicle. We probably should just turn that into a robot that move stuff. actually interfaces with our facility in a really cool way. When the food is coming out of our facilities, there's probably like a machine that holds food at temperature
Starting point is 00:36:59 that's like a box on wheels. I call them autonomous burritos. And it brings it to your home. And it costs 75 cents instead of like the $12 per drop that it costs like an Uber Eats or a DoorDash today. So it's serving, remember, I'm taking, I'm sort of going through an industry and saying how do we transform it full stack?
Starting point is 00:37:23 How do we automate full stack that entire industry? So, okay, that's the food thing. Obviously, mining's pretty obvious, but you can imagine there's a lot of other machines that move. Like I talked about haulage, but what about grading the roads, the dirt roads? You got to grade them. That's a machine.
Starting point is 00:37:42 What about you spray water so there's not a lot of dust all over the place? That's a freaking machine. Sure. Like, what about the material that ultimately goes somewhere beyond the mine? Well, that's a freight machine. Yep. Like, there's lots of things moving.
Starting point is 00:37:57 Yeah. You know, I saw something that's like, think about just forklifts. I know a company who remain unnamed that's spending three and a half, this is on the supply chain side, three and a half billion dollars a year on forklift labor in their facilities. That probably shows up in the SEC filing if we want to get creative and figure they want to have a great company you're talking about. The same. But you see what I'm saying? Yeah, big opportunity.
Starting point is 00:38:25 If you just solve the forklift problem. Yes. But on solving the problem, what do you think about this distinction between jobs versus tasks? Like a lot of people would have assumed that there would be no more marketing people because the job is just writing marketing copy, but the job is actually much more. Writing copies one task. I was looking at automated. trucking, and I found some stat, like, I think 30% of truck drivers are armed. They carry weapons. And so driving the vehicle is one task, but in that job, you are also providing security from
Starting point is 00:39:02 that payload, and you are also doing other things, refueling the vehicle, maybe some minor maintenance. And so just the steering and gas and brake pressure is just one task that you're doing. How do you think about that in the context of all this? this really gets to the jobs question, I think. Yes. Which is basically like, okay, well, if I do everything that we are imagining on food, which is I have industrial real estate, which is manufacturing and logistics, I automate the manufacturing, which is production, robotic food, robotic food machines, robots,
Starting point is 00:39:38 and I have robotic couriers, what happens? Food, the price of food goes down. Yeah. Okay. When the price of food goes down, remember, robots don't have bank accounts. When the price of food goes down, what happens? More people have more money. Yeah.
Starting point is 00:39:53 Jevin's paradox. What do they do? You start eating more? They just started having 10 burgers a day. Everyone's going to be fat. This is hilarious. That's not what I'm saying. That's so funny.
Starting point is 00:40:05 That's not what I'm saying. No, what I'm saying is when once you... I'll say, I was going to get three pizzas. I'll take 30. You feel like it's not the price. Yeah. No, no, no. So what happens, you have more money to do other things.
Starting point is 00:40:23 But remember that money is only ultimately going to humans. Yes. So it's the things that get automated go down in price. Yes. Which they create surplus. Yes. To do what? Yes.
Starting point is 00:40:34 To do other things. Yeah, this is the ball in. So it doesn't always have to be, oh, marketing's automated, but sort of, and there's still people doing it. It's like, whatever, there's going to be. a hundred other new things that come out because there's this excess of capital and progress continues. Yep. Yeah.
Starting point is 00:40:51 And as long as humans still have things that we do that robots cannot. Yep. It's go-go time, man. It's going to be super prosperity. We talked about the plumber that is paid like LeBron last time. Yeah. It's going to be across a thousand categories. And some categories, we don't even know.
Starting point is 00:41:09 Yeah. Like we don't even know what they are today. Yeah. Yeah. Yeah. You raised $1.7 billion. why didn't you raise more? That's a good question.
Starting point is 00:41:18 Because last time we were here, you talked about like, oh, well, if you were doing something and it was easy, you weren't going hard now. It seems pretty going pretty hard, but. Look, you have to stop somewhere. No. No, it's like, but like, look, as you can imagine today, my phone's blowing up.
Starting point is 00:41:39 I mean, I'm pumped. Like A-16, these guys, we should have done business at Uber. That's right. If we did it business at Uber, my 2017 would have been a different year. Yeah. Yeah. Okay? Totally.
Starting point is 00:41:50 So that's why I called it unfinished business. Yeah. And so, but yeah, like my phone's blowing up. Like, we're probably just going to do a second. We'll do a second close. Yeah. I figured. Come back for the second close.
Starting point is 00:42:08 Run it back. No, I mean, we're not going to do a big announcement on the second close, but like, you know, those people who. who are texting me and hitting me hard right now. You know, no, well, we'll see. We'll see. You know, we'll see. Depends on what the previous text makes.
Starting point is 00:42:27 If you're a homie, if you're not a homie, you should talk to one of my homies. Yeah, I did come away from the last conversation thinking, all right, there's a lot of exciting companies in physical AI and you could spend years and years and years trying to find all the best teams or you could just give. TK a big pile of cash and just say go cook and uh you know sometimes the easier route is it's better yeah and I think there's this thing physical AI people are like well is that a humanoid is that a world model is it and so on this one I sort of dial the language a little bit and I'm calling it industrial AI yeah it's like okay this is a full stack software robotics sensors machinery like a full stack solution to automating an industry
Starting point is 00:43:15 and that's kind of how we think about it and it's industrial so it's like heavy atom stuff yeah well thank you so much this was incredible you want to get a signature can we get an autograph sure why not we get something which they can figure it out back there
Starting point is 00:43:32 oh we got a gong we love to sign it we love to sign it in the raft we want to hang it in the rafters we're trying to build our museum of business the museum of business grows one gong strong longer today. And we will see you in Austin. Yeah. Next time you're on your commute, if you see two jet skis moving out of your,
Starting point is 00:43:51 you know, out of sight coming in, it's probably us. That's us. If it's not, you're. Guys, let me know if you want to learn how to slalom ski. Oh, yeah. If you want to learn how to wake surf like, well. I've only been water skiing once or twice. I go at 20 years ago.
Starting point is 00:44:06 I go at 7.30 in the morning. Okay. Morning. And I'd say half the time I'm out there at 8.30 when I'm. leave the office. That's amazing. I love it. That's what we do.
Starting point is 00:44:16 Beauty of summer. Thank you so much for coming out on the show. Always a pleasure. Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcast, and Spotify. Follow us on X at A16Z and subscribe to our Substack at A16Z.com.
Starting point is 00:44:44 Thanks again for listening, and I'll see you in the next episode. This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product. This podcast has been produced by a third party and may include pay promotional advertisements, other company references, and individuals unaffiliated with A16Z. Such advertisements, companies, and individuals are not endorsed by AH Capital Management LLC, A16Z, or any of its affiliates. Information is from sources deemed reliable on the date of publication, but A16Z does not. guarantees accuracy.

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