$39B founder says his company could 100x in 5 years

Sam's database on how long it takes to become a millionaire: https://clickhubspot.com/elft Episode 851: Sam Parr ( https://x.com/theSamParr ) and Shaan Puri ( https://x.com/ShaanVP ) talk to Brett Adcock ( https://x.com/adcock_brett ), the founder of Figure.ai. — Show Notes: (0:00) Intro (3:29) Hark, a human in a box (8:00) zero constraints (17:32) rapid prototyping (21:38) What are the robots doing? (23:45) what about the hype is real? (27:54) finding the best people (30:14) $20M dollar salaries for engineers (32:03) How Zuck is buying his way into AI (35:44) Auditing Brett's 2026 predictions (42:33) reducing your buckets (44:00) show us your home screen (46:17) hitting rock bottom 3x (57:22) who inspires Brett — Links: • Hark - https://hark.com/ • Cover - https://www.cover.ai/ • Figure - https://www.figure.ai/ — Check Out Sam's Stuff: • Hampton (joinhampton.com): My community for founders. Average member does $25m/year. Many of the guests are members. Get after it...apply: http://joinhampton.com/mfm — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Shaan uses Mercury across all of his companies. you can too: http://mercury.com/ Mercury is a fintech company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N. A., Members FDIC • I run all my newsletters on Beehiiv and you should too + we're giving away $10k to our favorite newsletter, check it out: beehiiv.com/mfm-challenge My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano /

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Sam Parr?

  I think if you Google Brett Adcock net worth, according to Fortune, you're worth $19 billion. So that's like a pretty good swing. How's that make you feel?

• 0:07Speaker 01

  I don't care about that at all. Give like zero shits about that.

• 0:21Sam Parr?

  Okay, so you Brett Adcock, the the short of it is that you were raised in a rural area of Illinois. You started a company called Vettery, which we sold for over $100 million. Then you took a company public called Archer, which is like unmanned, uh, flying planes, I guess, helicopters. And then now you have a company called Figure, which is worth, I don't know how much, 40 something, 30 something, 50 something billion dollars. You have another thing called Cover, which stops or aims to stop school shootings. And then now you have a new thing called Hark, which you've raised money in the billions of dollars. And you seem worn out.

• 0:54Speaker 01

  Great. He was like busy, man.

• 0:56Sam Parr?

  So you've been on, this is your third time on, I think you, I think you've been on one time each year the last three years. You said, you were telling a story about how, I think it was right when Figure started. You basically said like, I had, I was worth, I don't know how much, tens of millions of dollars. I put almost all of it into Figure to get started. And at one point you were like, I have a mortgage on my house and the rest of my money is in Figure. And some of the money is in Archer and that's not doing so great right now. And since then, I think if you Google Brett Adcock net worth, according to Fortune, you're worth $19 billion. So that's like a pretty good swing. How's that make you feel?

• 1:32Speaker 01

  I don't care about that at all. Give like zero shits about that.

• 1:36Sam Parr?

  You're a super competitive guy. I think you said something like, I just want to, you said like win a bunch of times last time we hung out. It was like, I want to win for these reasons. I'm, I'm very competitive. I want to kick ass. I think that like, you definitely have to care about this a little bit. And you actually have to, I think you care a lot about Figure being the biggest company in the world. You talk about like, you definitely have this like Napoleon energy of like, I want to be the best. I want to conquer.

• 2:01Speaker 01

  I think maybe the way I would characterize is like, we're just, like, we're just now, like, these companies of mine are just not hitting the inflection point. And they're really early, like, they can be like really big. So if it works, this will like 100x, 1000x from here. So most of my energy is like, how do I make sure that works? There is no flat line here. It's either like it goes down or goes up, right? Either like it's binary, either the robots go out of scale or they don't go out of scale. So in like five years' time, it's either going to be a very big thing or very bad. And so all my energy is going into making this like 1,000 or a million x from where we're at here. And so it's, it's like the pressure's on to like really just deliver.

• 2:39Sam Parr?

  Where are you now? What's the outlook now for the next five years then? I think last time you were on, three years ago, we said that, I think I said it. Uh, I was like, you'll probably be in the 40 to 50 million dollar valuation range, which I think you are now. But in terms of like, you're still lacking output of robots. Like you still need, we still need that to come. When, where are you going to be in five years? What's your prediction?

• 3:02Speaker 01

  I think at a high level, I think the AI work that we're seeing here now is going to be so much, it's going to be like 100 times bigger than the internet. It's just like, everything is just so, it's just working so well. Like the system is working well, like deep learning works. And everything's happening faster than I would think. And my, like, you know, having done like 15 years of like software and internet, like it was just like, nothing was happening faster on a trend line. Here it's happening like that in AI.

• 3:30Sam Parr?

  Can you give an example of something that has happened that's blown you away?

• 3:32Speaker 01

  We started at, so Hark, I have a new AI lab called Hark. About a year ago, I was like very interested in this idea of like, kind of building this AI to human symbiosis digitally. It's like, um, Figure is going to be like, I think Figure is going to be like the max ceiling of AGI of like being able to put that out. And then there's going to be a version of this in the digital world. It's going to be like a human is going to have this like AI pairing. It's going to have like, ultimately maybe your own AI weights, your own memories, maybe your own hardware. It's like really close. And fundamental to that thesis was like, you got to figure out how to get AI to use computers general purpose. You would never hire an assistant that couldn't use a computer. So you got to be able to like give things out to it that can like do everything you can do. Financial models, book flights, like order DoorDash, whatever you need to do.

• 4:13Speaker 01

  You need to be able to do all autonomously, but only one in a thousand websites have APIs. So in most, you know, like most computer use globally is on the, on the internet and browser. My main inclination within two or three years, you'd have a system that you'd be able to talk to and say, go do this or do that. And to be able to like go off, go online and like, maybe, maybe like use the internet really well, like almost like a robot would, where you can like move the mouse and use the keyboard. That's what we have to do to solve like general purposeness for around a computer is you, you can't rely on API or MCP. You have to figure out how to like navigate like a human can. Now at Hark, we've, like, we just released our first, uh, kind of model and research preview, um, last week. It's really hard for us to find now something that we tell it to go do on the internet and it can't do.

• 4:57Shaan Puri?

  What did you guys do differently than the other? Cause everyone's trying to do computer use, right? So like, I think Elon's got Macro Hard and ChatGPT had their computer use thing. Everybody's doing it. You guys feel like you've cracked something. What'd you guys do differently?

• 5:10Speaker 01

  Okay, there's a couple of things we did a little differently. First is like, everybody's tackling this from like using APIs and MCPs. Like the reason why OpenClaw got so great, it was like, it could only, it couldn't use the browser, it couldn't like go on and use DoorDash end to end. Cause DoorDash has no consumer API. So we tried to figure out how to use, like, how to look at a screen. And one is we spin up a virtual computer for every agent. So they don't need like a MacBook or anything. So you can just spin up as many of these environments as you want in the sandboxes. And, uh, and then you need to give it ability to like, look at a screen and use like move the, move the cursor and use the keyboard.

• 5:41Shaan Puri?

  Yeah, but I used ChatGPT's computer use and it was doing that. I was like, hey, book a massage and it opened up a browser and I saw the mouse going. And it was trying to type the thing and it would scroll the results. It was bad. It didn't work well, but it was, it wasn't trying to use APIs or, or MCP. It was trying to use the internet.

• 5:57Speaker 01

  Yeah, I don't know if I, yeah, it's got to work well. I mean, that's the whole, but like, if it goes and fumbles the internet, it's like, the whole point is like.

• 6:02Shaan Puri?

  So that's what I was saying. What'd you guys do to make it work well? Was it like an algorithmic breakthrough? Is it?

• 6:06Speaker 01

  It was in our post-training, like it was in our, we have a reinforcement learning process that we think is maybe nobody else in the world has done.

• 6:13Sam Parr?

  Well, let's get some context behind this. Okay, so Figure, that is shockingly easy to understand. Humanoid robots and that business is going to be massive if it works. If you can crack the code, I think you said there's unbounded, uh, demand. Hark, I don't entirely understand what that is. Can you kind of explain like I'm idiot? Because Sean, you should see, I got the deck and it was just you talking for like an hour in front of a screen. And then there was a list, there was a list of a team and it was like 100 guys who just moved here from China, who had like the greatest backgrounds ever. And you, it seemed like you pretty much just raised money because the team was amazing. And, uh, that's all the deck was. It was just you talking in a video.

• 6:57Speaker 01

  Well, I mean, that's kind of all we had of time was started. So, okay, what is Hark?

• 7:02Sam Parr?

  I think the best way to become successful is to see how other people did it, whether you're going to copy them or just use it as inspiration. Because then now you know what's possible. So starting at the age of 24, I did this relentlessly and I was very methodical about it. And I created a spreadsheet where I tracked roughly 50 people who were uber successful. And I looked at the year that they were born, the year that they started their apprenticeship. And then the year that they started the first thing that made them successful, finally, the year that they broke through. And I aggregated all this data along with the stories of what they did to be an apprentice and what they did to finally break through. And I put it together in a database and HubSpot went and found this thing that I frankly even forgot about, but it did change my life.

• 7:42Sam Parr?

  And they resurfaced it. They made it even better and they put it into a thing that you can download for free right now. So if you click the link in the description or click the QR code right here, you can see this database that I made when I was 24 and it changed my life. And so if you're looking to become successful or you're already successful and just want some more inspiration, check it out.

• 8:00Speaker 01

  I strongly believe like AI will head in two directions, like, uh, like, and then at some point, maybe even like, maybe like head together. Like the first is love AI out in the physical world that will like do everything in the, in an environment for you. Like laundry, dishes, cooking, like run the supply chain end to end, be in healthcare. The vessel for that is a humanoid robot. It's just a human form. And it will just go out and do like, you like want one piece of hardware that can like, you know, the hardware capable of doing everything. And you put like smart AI into it and it'll go off and do everything in the world. That's what Figure is working on. Secondly than that, there's going to be this like really close, like digital, like AI to human symbiosis that forms. You're going to have like this very special thing that you can like talk to, that's with you everywhere you go, that will know all your stuff.

• 8:42Speaker 01

  Have access to all your memories, have access to all your accounts and systems and be able to actually go do things for like a superhuman assistant. It'll be like, um, maybe the closest thing is like Jarvis from Iron Man. And it will be able to do like, it'll be like superhuman in almost every way. It'll know everything about your life. You'll be able to access it at any moment, whenever you need it. It'll be in the background, helping you out at all times. If you're on a flight, if you're on a flight with like a long layover or you're in a flight with like maybe say a short layover and you miss it, it'll like already have backup plans. Already help you like figure that out. Like it'll just be something with you everywhere you go. We don't have that. We have like really good coding agents. We have really good chatbots. But we don't have like something that can go off and like be my Jarvis. In order to get there, we need to work on the like model side. It's got to be just better than text chat.

• 9:26Speaker 01

  It's got to be able to use computers, have like basically near perfect memory, be able to talk to you like, just like a human would back and forth. And, uh, we have to have vision in the system. It's really like look at the world and understand what you're seeing with it. And I think secondly, you need to have, you need to fix the, the interface to AI. You have like, um, AI over here and a human and you have like an old hardware system in between, like a, call like a MacBook or iPhone. They were designed 20 years ago. They're a complete rubbish for AI. They're not the right interface. So we went out and we are out there designing what we think comes like after the iPhone for AI. And it's like an upgrade cycle. We see this all the time in startups. You guys see it, right? Like we're, and we're in an upgrade cycle with the computers and phones. They're just going to go away.

• 10:10Speaker 01

  They're going to be a new ones. They're going to be all AI computers and phones and systems. And they're going to be great. They're going to be all real time. You can always access them and you want, they'll always be like understanding what's happening. And they'll always be able to reference things, what's going on. You'll be able to abstract away most apps. You'll probably not have an app store. You'll probably have an AI operating system. Uh, it'll be perfect for you. You'll ultimately have your own weights on your own devices that you'll own and have with you everywhere you go. It'll be like a really great, uh, pairing. And we hired an incredible team. Teams like, you know, maybe like 80 or 90 now. Uh, the guy that leads, uh, hardware design abs, previously designed for last several generations of iPhone, MacBook, MacBook Pro. Like he's just like the, he's a stud. He's great. So we're designing what we think are the next generation of AI devices that will kill the phone and computer.

• 10:55Speaker 01

  And then, uh, we're designing the next generation of AI models. The models need to get a lot more multimodal. They need to get a lot more expressive. Like the text encoding is just not enough for us to like really have a, like a, like a real AGI feeling with AI. So we're working on that. We have our first AI, we did our first research preview or computer using AGI. That we came out last last week, I think we were like top on some like the leading like, you know, browser or computer use benchmarks in the world. And they'll keep getting better. This will keep getting better and better. Like every month, we'll just like, it'll be better and smarter at using a computer and faster. We're working on a couple of different types of technologies internally on the AI side. And then we'll launch the ability to use Hark on like traditional browser and iPhone and Android in about a month. So you'll be able to start using it and then we'll have hardware coming.

• 11:38Speaker 01

  We're working on now, we actually have a hardware in the lab now, we're using testing this. It's crazy shit. Like the stuff is like a sci fi movie hardware.

• 11:45Shaan Puri?

  What do you think those devices look like? You know, people have been speculating because Johnny Ive, you know, got his shop got acquired by OpenAI and you've seen the videos of the puck and then the like this little puck and then there's like an earring. I don't know if that's real or if that's fake. There was like a leaked commercial for the Super Bowl. Again, is that real or is that fake? What's the story of that? And then what do you think these devices end up looking like? Are these watches, glasses, something else altogether?

• 12:08Speaker 01

  I think I've like really changed my mood on this a lot last like year or so. But we have a really strong opinion here internally. Our opinion is that we, what sits in the middle is devices that could possibly reach a billion units a year in the world. The only kind of things that we have like that in the world right now are computers and phones. They kind of meet that. I call it mega, call it mega devices. And then you have things in the ancillary around it, like orbiting this like big thing. That are like AirPods, AirPods and you know, like a watch or things like this that are like, they don't sell a billion units a year. They're like 3% of like Apple's revenue and they're like, they help the ecosystem as a platform. What we care about at Hark is trying to solve what's in the big middle piece. To solve that, you gotta take down the computer and the phone.

• 12:53Speaker 01

  There's no way around that. So you have to rebuild a new computer or new phone. That's better and replaces your existing systems end to end. And then what's around there is things that like you will have, we will even have at Hark that are like helps with the family of devices. That are not a billion units a year, but important for the ecosystem.

• 13:12Shaan Puri?

  My understanding, right? You're, you're kind of saying the next, the, the next device, it might be like a phone. It's just going to be an AI native first phone, right? You're not going to try to change the form factor.

• 13:22Speaker 01

  No, I'm not saying that at all. You're going to want to like really radically rethink everything. Uh, the, like the first version hardware we have now in our lab is like, unlike anything I've ever seen in my whole life.

• 13:31Shaan Puri?

  Okay.

• 13:32Speaker 01

  What lives outside of here on the edge are like, like glasses and pendants and wearables and things. They're not, they're not the main show. In fact, like the Meta glasses are probably one of the worst products I've ever bought. They're just horrible. They're horrible. Like I can't even like figure out how to use it. It doesn't have its own network. It piggybacks on the iPhone network. It means your app needs to be open on your phone. The pairing's long, like it doesn't work well. Like, I can't think of any reason why I would need this thing strapped to my head for 14 hours a day. Like, it's just like the wrong device. It's, it's not like, the end state is BCI in the brain. And we're going to have like AI language devices for the next 10 years before that. And that like, that's, that's the path. And it's not glasses. Glasses, I think, I don't even know if glasses will make our top like 10 list of devices.

• 14:15Shaan Puri?

  When you're, when you and your team are like brainstorming, do you have a framework on how you can think outside of pre-existing norms? Because when you're talking about, like, I, I literally can't imagine at all what you're talking about.

• 14:27Speaker 01

  Let's, let's get down to like the substrate level here. Like first order, what, what has changed? What's changed is we have like a new type of computer, which is the, I think of AI as a new type of computer. New type of automation that's here. The automation can do a few things that are like, like when we're designing this, we want to design around like key principles that could be like 10x better. If it's like one or two times better than your phone or computer, you're not going to use it. It's gonna be like literally 10x better. What are things now that like a deep learning brings that are like 10x better? There's a few of them. Like one is AI can like basically now like think and use computers and systems for you, just like a human can. It can like talk to you. It can like see, it has like visual understanding. It has a real time speech to speech. It can, uh, it can use computers and systems for you as fast, close to as fast or around as fast

• 15:10Speaker 01

  of a human can. Over time, it'll be just as good as a human and faster, um, in terms of success rate. So you have a system that's like, almost like human liking capabilities. It also can like have memory, meaning you can put memory into it and it like won't, it won't, it won't forget anything. I mean, you're perfect over time. So you have a system that's almost like a human in a box. That has all the same like fortitude as a human has. And it's almost like the ability of like, you almost like, if you could bring a little human around with a computer on your, on your shoulder everywhere you went. That'd be insane. Like we're just like, it was only for Sam though. Only Sam could see it. Only Sam could talk to you and only was like there to help with Sam. And that was like your whole life and it's getting smarter and better along the way and had perfect memory and could use computers and talk to you and see. You'd be like, damn, that thing would be like, uh, it'd be like be able to do anything you do on a computer.

• 15:54Shaan Puri?

  Okay. So your first step where your team is like, just like, let's just get rid of like any constraint ever. What would be the coolest magical thing if we had like a little guy on our shoulder that was AI all knowing and could see and hear everything we see in here and then give advice to us?

• 16:08Speaker 01

  Like, like what is the thing that's going to bring, that's going to fundamentally reshape all this?

• 16:13Shaan Puri?

  Okay.

• 16:13Speaker 01

  And then from there, like, we gotta like, we gotta design around that system. The competitive advantages here are that it, uh, is human like capabilities and it has almost near perfect memory, can go back and reference over time. My phone doesn't have that. Like I put a contact in my phone like last week and I was like, I was like busy when I was like putting the phone number in. And like a day later, like somebody's like, hey, did you, did you call that person? Like, I don't even know the name. I forgot. I can't even ask my phone. Like it's just like, it's so stupid. Like the whole system is. And then I go in there like order DoorDash like a monkey, like every day. Now I'm pushing things. Like I don't do any of that now with Hark. It does it end to end for me on my drive to work. I just like, say, order me coffee and it's just done. It does it all for me in the background. I don't have to touch anything. It's all abstracted away. And it's like, if you had that little human with you everywhere you go, you would just say like, it'd even predict probably Brett, you want coffee today?

• 16:58Speaker 01

  And I'd be like, eh, yeah, I do. Like let's get, let's order, but you know what? Make it a double shot today. And you know, like routed to the Hark office instead of figure. Like I can like, I would just, and done. I got it. Let me take care of it. I'll stay like a monkey on my phone for the next like three minutes, like trying to do checkout, DoorDash.

• 17:12Shaan Puri?

  It's almost like the phone is like a tool and it's like a hammer, right? If you want the hammer to do anything functional, you have to pick up the hammer and start swinging it. Whereas the next generation is basically like having a handyman next to you at all times. And so you just tell them, hey, can you fix that window? Just go fix the window. You don't have to pick up the hammer and start figuring out how to use it.

• 17:31Speaker 01

  Start, start there. And then from there, you gotta rapidly prototype. So when you come over, like we have, like, we've, we've designed everything you could possibly think of. We 3D printed it.

• 17:40Shaan Puri?

  What were the designs that didn't work, but were kind of cool?

• 17:43Speaker 01

  What were designs that didn't work that were kind of cool? The thing is, we're building like many different devices now that cover like a pretty wide area of this. We have some pretty crazy stuff that we were like designing. So like, it's not like you look at that and you're like, that looks like a, that looks like this. And well, that does over, well, over here. So it's like, it's not as easy as drawing those parallels. It's like pretty quite radical. But we, we rapidly prototype all this. We have like a fabrication facility that does this stuff. We like, we have a whole design studio where we work on this. I like, you like use this stuff like over the coming like weeks and months. I'll like either carry it around with me, wear it, whatever, we end up doing it and we'll like kind of down selection. We, we had like one of the biggest telecom CEOs in, in the world here that I actually helped, um, with, with the work with like Steve Jobs on iPhone one. And he was here two weeks ago and he'd just come from meeting Tim Cook.

• 18:28Speaker 01

  Uh, you know, Tim Cook's on his way out as Apple, but he's like, was over there at Apple and came over here and we, he saw our stuff. And he's just like, holy shit, man. This is the first time I've ever seen anybody that could possibly take out, like take out the big guys.

• 18:40Shaan Puri?

  Well, is it true to say that with like Archer, Figure and Hark? The, the hard problem seems like, can I just mass produce this?

• 18:48Speaker 01

  The hard problem is not that. We think, we believe now the most important constraint to really solve is like building a really intelligent robot system that can put out to the world. Like there's a bunch of robots you can go buy now. You can buy some from China and you get them and they're complete crap. They can't do anything. Like you can joy stick around. That's all you can do. And you like hit a button and it waves. It's got no hands. It's got nubs. And you're like, what do I do with this thing? It's a toy. It's like, it's like, it's like when I, early when I bought, I bought a DGI drone like years ago and I was like playing around with it. And then like a day later, I was like, what do I do with this thing? And uh, it was like, it was like hard to set up. It didn't really work well. Like, you know, whatever. It's just like, I flew into a bunch of trees. Like this didn't work. I was like, this is, what am I doing with this thing? Robots are like that now. Like where you can, we can go manufacture a ton of them, but like if they're not really smart, like it's not really going to be that helpful.

• 19:32Speaker 01

  We're trying to crack like the true human level intelligence of Figure. Like we really want to tackle like, how do we make it so I can put it into any home? It can do every, every, every job I'd want it to do. That's what we're working on. We think that's the largest, like, like, you know, think about the largest like gap in the schedule of what we need to go solve for. Like it's that. Then beyond that, like, you know, people generally sometimes confuse like consumer electronics manufacturing with car manufacturing. There is no company, big company in the world that would look like, say like, uh, uh, I'm scared of manufacturing this consumer electronics at high rate if there's so much demand. Like this is just possible to go do. I mean, you can make them, you make, we make a billion phones almost like, you know, pseudo by hand in the world and with some automation. But cars is a different story. Cars like you will die trying to manufacture cars.

• 20:16Speaker 01

  There's like, there's like a lot of companies, like you just like, it's so, and having seen like, you know, BMW is a commercial customer of us. I have a meeting in BMW and a few other groups like. It's gnarly. The reason why cars is so hard is that you can't hold the part in your hand. Phones, you can just like always hold in your hand and go change or whatever, move and hold like cars you can't. You physically can't. You need robots that like literally pass it to other robots that put things on the chassis. And if any of those break across like thousands or eight hundred robots, your day is your whole line is down. And so it's just like, it's like huge giant robot you're building that's building the car. And with Figure, you can hold any part in your hand. So I think we're like, if we're like between cars and like consumer electronics, we're like over here. Closer to like, you know, we're like, you know, the forty percent level over here by like cell phones.

• 21:00Speaker 01

  Like we, you know, we just made our one thousands EVT robot for Figure three last week or week before that.

• 21:06Shaan Puri?

  When you say you made a thousand, those are a thousand that go to customers like BMW or you're just making prototypes internally? What does that mean?

• 21:13Speaker 01

  We have like two bit like large customers. We have us as like, as like an engineering or like AI research org that needs like robots like here, like every engineer needs a robot. We need like every lab needs robots, like we need like to do tons of testing. There's just a lot of work we need to go do internally. We call like maybe like engineering fleet we need to go to. And the second one is go to customers. So we have it going to both right now. We've actually shipped out robots to our third customer this, this, this week.

• 21:41Shaan Puri?

  When they go to customers, what do they do? What, what, what can the robot do? What maybe can't it do at this?

• 21:46Speaker 01

  We do a lot of like logistics stuff right now and packages. We have other stuff we've done in manufacturing, mostly just manufacturing logistics, just stuff we've done in the past. But like, we're also talking to folks about other industries.

• 21:57Shaan Puri?

  And at this point, when it goes to a customer and it's doing, I don't know what you said, like packaging work or what is that like sorting or carrying or what is it doing?

• 22:05Sam Parr?

  They just did a live YouTube video and they had hundreds of thousands, maybe millions of views of people watching this robot sort packages off of a conveyor belt.

• 22:12Shaan Puri?

  Yeah, I saw that. So is, is that the type, is that like, would that, give me an example of one of the jobs.

• 22:17Speaker 01

  Yeah, that's, that's an example of like us, like a very close to like one of the, one of the works we do.

• 22:23Shaan Puri?

  Is that customer like, oh, this is awesome because I can't find the labor to do this. It's too expensive to humans. This is way cheaper. Or is it just like, hey, look, today it's not faster, cheaper or better necessarily, but like it's an investment in the future where two years from now, that cost curve is going to work and it will be faster, cheaper, you know, whatever.

• 22:41Speaker 01

  No, no, no. It's like, uh, it's the pitches like they come to us and they're saying like, we're dying with labor. It's like, we're like, we have like really high turnover. Some areas have over a hundred percent turnover per year. It's really expensive to find talent. We have like a, just a large talent shortfall. The talent's really expensive, like wages are going up and we like, we don't have a solve for this. We can't figure out how to automate all of this work and we need you to come in and help us. We have an ability to make a lot of good money in our contracts and the customers make like really good ROI on this. Like you gotta think like a robot can do like multiple shifts per day, work seven days a week, like we can like have a lot of uptime. The task you saw like on the, on the, on the like logistics line that we should live stream is actually a real use case for one of our customers.

• 23:24Speaker 01

  That needs to be done in three seconds a package and initially it's gonna be done in five hours a day. Like I think it's like five days a week. We did that two hundred hours straight at two point nine seconds a package. So we're already at human speeds. We're already doing this here now. They're already having ROI. And we're now in the early stages of like getting these out to these customers and scaling it up. Over time, it will just put billions out to these groups.

• 23:49Shaan Puri?

  Hey, let's take a quick break. You know that feeling when strategy is done, the brief is written, everyone's aligned and you realize someone still has to sit down and actually create all the content? That someone is usually you and it's due tomorrow. Well, the Breeze assistant from HubSpot can help. It works right inside HubSpot. You can draft a campaign copy, blog posts, emails, all in your brand voice, all using your actual customer data. So you don't create just content, you create content that converts. Check out hubspot.com, the agentic customer platform for growing businesses.

• 24:17Shaan Puri?

  Can you help me with like the kind of truth first fiction? Cause one of the weird things is as an enthusiast or a layperson who's, who's excited about this future, you can't really, it's like really expensive or hard to test this, right? So I'll see like a, a Chinese robot and it's twenty grand. If I want to buy this robot, I have no idea really what it can do. I see, uh, you know, Elon will go out there and say, we're gonna, we're gonna build a million of these things in the next year. We're gonna ship them. Then you get like one X and they're showing their hand and they're like, look at our hand. Look at this. This is the best hand you've ever seen. And then there's this service in San Francisco where they'll send a robot in to clean your apartment and they're like, yeah, that works today. So can you help me separate fact from fiction? It seems really hard compared to most categories where I can just try the products quickly online or buy them and, and test them out.

• 25:00Speaker 01

  Yeah, a hundred percent. Um, so, uh, I think a few things. One is, um, the amount of like noise in the market for a signal is just like, it's like, like you mentioned, it's like, it's like, it's, it's out of control. Like the, like there's just so much bullshit out there in the market. It's like really hard to tell what the hell is going on. So let me summarize what I think is like the most important and work backwards. Where I think the most important thing to do is to be able to ship robots autonomously at scale and useful work environments. Like they can like, you know, cook your dinner, like, like clean your dishes, like, um, make your bed, like run the supply chain end to end. Work in healthcare, build a building, like do logistics, like that sort of stuff.

• 25:43Speaker 01

  That stuff requires fundamentally onboard AI that you can run. So you can do like autonomous work. You can't solve it with code. You need to do it autonomously. You need to do it over a long period of time. And you probably need to move around and use like something in your hands and move, move, move stuff through the world. You know what I mean? It's like, you gotta like do, do stuff economically, like you gotta move like electrons around. So I think at a high level, like what we care about is not like the best robot that's doing backflips and running the fastest mile or dancing or in a parade or running outside in the woods. Like, you know, we don't care about that stuff.

• 26:17Sam Parr?

  Dude, I can't wait till I see a figure like on a smoke break at the BMW fact like.

• 26:22Shaan Puri?

  I could have been a great back in high school, but I blew it. Now I'm working at a BMW factory.

• 26:27Sam Parr?

  I've made jokes with you before where I was like, you started with Vettery, which is just like a job recruitment thing. Now you're on these world changing things and you were like, well, Vettery actually is world changing and here's why. And you gave this pitch. It was very good. You're very good at pitching. You're very good at raising money. You're very good at being charismatic and convincing people of stuff. When you're crafting a pitch to recruit and convince people to change their lives, to uproot their lives and to trust in you and to come and build a company. How do you craft that pitch and what was that pitch for some of your companies?

• 26:57Speaker 01

  I mean, most of all these are online. I mean, the figure master plan is on the internet, on the site. Arches was up for a long time, like posted about it, like, I think like deep down, I really want to find folks that really care and are obsessed. And I'm like, I think most of my time is not, I know you want to know about the pitch. Most of my time is trying to find those folks. I found that even in the Bay area, where it's probably like the richest AI and engineering like, uh, folks in the world. Ninety percent of everybody out here is not good at their jobs.

• 27:26Sam Parr?

  How do you tell who's good and who's not?

• 27:29Speaker 01

  I technically assess them, all of them. Yeah.

• 27:32Shaan Puri?

  To do that, does that mean you need to be as good or better than them technically to be able to assess somebody?

• 27:37Speaker 01

  I need to know like a certain guiding principles, like for instance, I need to know like if A, if you did the work or if you like watch somebody do the work. If you've done the work, it's like, it's like, it's like a scar you're carrying with you. It's like, it's like dug into you. Like you know, all the details. You can talk about it freely. You don't need to think. You'll understand how to like reverse engineer everything you've done and discuss it. The folks that haven't done it can't do that. They just like, they can't even go like, they get one layer and they just like instantly blow up. They can't talk about it. They don't know why.

• 28:06Shaan Puri?

  Out of a hundred candidates who sound good, how many, like their resume looks good, the recruiter thinks they're good. Out of a hundred candidates, how many do you, would you say actually hit that bar?

• 28:16Speaker 01

  I'll give you an example. We have like a really challenging process to go through to be a mechanical engineer here at Figure. You have to be able to build like actuators from scratch. There's bearings and motors and, you know, we have a, we have a, we have a gearbox. We have like other sensors inside the system. It's a really, it's very compact. You know, uh, it's just a very difficult thing to do, uh, and like really hard requirements. We've been doing ten case studies a week for six months and have not hired anybody.

• 28:45Sam Parr?

  That's insane.

• 28:46Speaker 01

  It's insane.

• 28:47Sam Parr?

  But when you do get someone qualified and their competing offers are companies that are larger or, or more liquid than you and the offers are, I, I, I, I think they're like tens of millions of dollars a year, right?

• 29:02Speaker 01

  The AI side is certainly like that, but the AI side has gotten, um, and it's, it's mostly all driven from meta. Like at Hark, like I've never seen, I thought maybe like Meta was like paying these people for like, like a year ago and it was like, it would go away. They've not stopped.

• 29:16Shaan Puri?

  So what are they like, what's a crazy story that you've heard?

• 29:18Speaker 01

  We gave an offer to somebody that was really senior that was like, they were coming from X at AI, like XCI completely blew up. Like everybody just laughed and about it six months ago. It's just like every, it was just like, like macro hard, like got fully disbanded. Like there was basically a bunch of stuff that happened. We interviewed a pretty senior guy on the AI infra side. It was great. I think I gave him like a really good package, like a series A stock at Hark. And it was, I don't know, I don't know, 15, 20 million dollars of stock.

• 29:44Shaan Puri?

  Over four years?

• 29:45Speaker 01

  Over, we do five, like for uh, my companies in the early days and we transitioned to four a little bit later. So we're still a five. And uh, you know, I was like, I think we're like, I think we can like 10x Hark here pretty quick. And so I was like, okay, you have like, you know, 15, 20 million. I think 10x you have a few hundred million dollars. I mean, 10x more time, you have a few billion dollars. And I think we can do it. I think we like, we have to like, obviously it's gonna be hard, but I think we can do it. And he got an offer for, to go to Meta for 36 million of four years of our shoes. And he was like, it's kind of guaranteed cash, you know, like go there and I have to like wait. It's like, oh, maybe like 200 million dollars at Hark or 20 million dollars or maybe like 36 for sure at Meta.

• 30:24Speaker 01

  And he left and went to Meta and they've been doing that, like every candidate we spoke to speak to is like making some absurd, absurd thing. It's never stopped. It's been, it's been at it since like, for like a year, a year and a, they've been buying talent. They've been buying their way into the AI race.

• 30:36Shaan Puri?

  What, what do you think of that strategy? Like, you know, even if you kind of hate it, do you respect it? Do you just think it's a fool's errand? What do you think of that?

• 30:42Speaker 01

  I really like it. I think like the AI space is, what I found is the folks that really understand how to do like language pre-training and mid-training and post-training, especially pre-training. And the infra around supercomputing and data and evals and all the right stuff you need to get put in place to do that right. And the amount of folks that really understand the right kind of like recipes that transformers do well in. And you know, around MOE or whatever you're going to look at, I think it's really hard to find. It's actually really hard to find the actual folks that know what they're doing. I think there's probably, my rough calculus now is probably like, a rough back of the envelope is probably like 20 to 30 people in California know how to build really good AI models.

• 31:21Shaan Puri?

  Wait, so, but is that trickling down? So you said that there was a senior guy, but like, are even some of the less than senior, the 20-somethings, the young 30-somethings, are they still getting eight figures a year?

• 31:31Speaker 01

  No, the like, the junior guys, like the guys in like their twenties, you know, like the like late twenties or something are getting like, they're making like a few million total. So they're making like 200, 250 in base. They're making like another million or whatever, like in, in a year and like uh, our shoes every year. And so they're going to pay like a million to like, you know, like 750 to like 2 million or so range per year. And that's uh, that's been driven up by Meta and but then all of the other labs have, have like, have, have like followed comp.

• 32:01Shaan Puri?

  When, when I asked you, what do you think of that? You said, I like it. Were you being sarcastic or you're, you're saying, no, actually that is smart, given how hard it is to get this talent?

• 32:08Speaker 01

  I think it was really smart and I would have done the same thing if I was, I was, I was Mark. I would have bought my way into the race. And I think he's like, he's doing that now. I, I don't think I would have done that. I want to understand it and I want to like first order, like find the right folks that really care deeply about this and not hire like, like mercenaries. And he, so he hired a bunch of mercenaries. They're just purely money driven. He, they came over there. Then no other, nobody wants to go to Meta. They just, they're going there because they're getting paid a guaranteed RSU package by sitting around. And what's happening is like, you don't need like a thousand people or 500 or 300 to design AI models. You make a really good team of 20 or 30 or 40 people. And that you can get there without doing this.

• 32:51Speaker 01

  And those people probably would care more deeply about the mission and where you're at and be more committed than just to be purely throw money at the problem. But I think if I was like, I, I think it was a really good strategy and it's working. I think hats off, like really good execution, their recruiting efforts and how they're structuring this stuff. And uh, it's like, I think it's, I think it's like paying off for them. Jury's still out if they can like actually ship real products. I think like the problem I have with those groups is they've just traditionally have not been able to do things new well. I mean, I think Facebook is probably, Meta is going to go down to like one of the greatest acquirers in all time. With like, you know, Instagram and WhatsApp and different way, they like bought their way into those spaces. Uh, but like, you know, if you look at like the Ray Bans and everything they're doing, it's just like, it's, it's not great work.

• 33:35Speaker 01

  And so I think the question really is how do you really do great work here? I think like, we're even talking like, we're, we're using like the Hark system right now and it's so good. It's so much better than anything I use today.

• 33:45Shaan Puri?

  You gotta send it to us.

• 33:46Sam Parr?

  Yeah, can we use it?

• 33:47Speaker 01

  Well, yeah, we used you guys early on that. Yeah.

• 33:49Shaan Puri?

  It's like research preview. There's like 500 PhDs and then me and Sam.

• 33:52Speaker 01

  Yeah, exactly. No, we'll like, like every other platform.

• 33:55Sam Parr?

  Hark, what's the weather outside?

• 33:57Speaker 01

  I can answer that. Yeah, no problem. So like, I, I, what I'm trying to say is like every week there's like five or 10 like junk AI slop startups are like, things are coming out. They're just like not very good. Like this whole space has gotten to a point where like, there's just not great things coming out the door. I think this stuff in coding is probably really excellent right now, but everything beyond that is like, just kind of like not great.

• 34:17Shaan Puri?

  On January 1st of this year, you've made four predictions for the year. I want to check in and see how, how you think they're going. First one, uh, number one, humanoid robots will perform unsupervised multi-day tasks in homes they've never seen before. Driven entirely by neural networks, long time horizons going straight from pixels to torques. How are we doing on that one? On track, off track or done?

• 34:38Speaker 01

  On track.

• 34:39Shaan Puri?

  On track. Yeah, four months.

• 34:41Speaker 01

  Yeah, I'm like, I see every day like what we're doing. Like we're on track. The hard part here is um, we already do pixels to torques.

• 34:50Speaker 01

  It just means like, we're just taking camera feeds and we output like where to put the motor, like put the, like, you know, we want to put a, we want to like tell the motor like what to, what to do to get to the hand in the right spot or the joints. So we already do that. Um, getting into a new house has never seen do work. That's the hard part of this problem. Um, we're working on that. I'm working on that every day. It's where I spend about three, four hours a day, every single day, 70s a week on this problem.

• 35:12Shaan Puri?

  So if a figure robot showed up in my house, what would it, what's the bottleneck right now? Like it wouldn't know what to do. It wouldn't know where to go. It wouldn't be able to, you know, fine tune, handle by dishes. Where would it suck for me?

• 35:23Speaker 01

  We can fold laundry like as an example, but then going to a new place where we're folding in different location with different lighting and maybe different like table height and different types of laundry and different like types of scenarios it's never seen before. It's like, the model's like out of distribution. It doesn't know what to do. It's like, if you removed all the pyramid data from the, the pre-training of LLMs, it wouldn't know how to talk about pyramids. And we're just like, we don't have enough of that data out there. It's not on the internet, so you have to go out and collect it. So what we need to know is like how much of that data we have to go sample in the world to be able to train the model, to be able to go into your house and say fold clothes is like an example.

• 35:59Shaan Puri?

  Hey, stupid question. Why do all the robot companies care about folding clothes and, and doing laundry? Wouldn't it be commercial better just to say, hey, we're going to build like the best warehouse worker? Cause there's already 20 million of those in the world and that represents this much billions. And of course that buys us the runway to like get the robot folding, you know, robot done. But like, why do you care about that at all today? Why not just industrial work that people don't want to do, companies need done, they're ready to pay and it's not like my home where there's all these other sensitivities. Why do you guys care about that right now?

• 36:30Speaker 01

  Uh, we didn't care about it in the past. We like, when we first launched, we're like, we're gonna basically do the commercial side to pay for the home long-term. And uh, that was the strategy. It made a lot of sense. Like there's like, we can charge a lot more in the commercial market. It's like much easier to do. It's like lower variability. We're in like a little work site, just 24/7, just so much simpler. Uh, what I've learned now is that the home is super solvable today. So like, we can like not go work on that problem and just like sit here and work in a warehouse, but me or none of my guys want to solve that problem. We want to solve a robot that can go into any environment just through language and do work. We want to be the first to do that. You can probably do that with a hundred robots and a 50-person team. So that, that company overnight would be a trillion dollar market cap.

• 37:12Sam Parr?

  That sounds good. Do that.

• 37:13Speaker 01

  We're doing that. That's what we're doing. Like we're gonna solve that. I think we'll be the first, we call it like solving general robotics.

• 37:18Shaan Puri?

  In iRobot, don't they attack the humans? I don't remember this movie very well.

• 37:23Speaker 01

  Yeah, don't worry about that.

• 37:24Shaan Puri?

  Not that part of iRobot.

• 37:25Sam Parr?

  Who could win it? Who could win in the, who can win in a fight right now? Can a, can a human still win?

• 37:30Speaker 01

  Yeah, he can still win.

• 37:31Sam Parr?

  Okay. Uh, where did the other prediction start?

• 37:33Shaan Puri?

  Other prediction, um, one you had on here, daily AI usage will shift. People will move beyond text to highly multimodal voice agents with persistent, uh, persistent memory will become common, which will push AI closer to the synthetic human intelligence we've imagined in sci-fi.

• 37:49Speaker 01

  We're doing that at Hark. We will ship that in a month and our first version of it, it'll get better and better. Uh, I think we're on track for that.

• 37:55Shaan Puri?

  Have the labs ever, like has ChatGPT or Claude, have they ever released the data on this? Like I use a ton of the voice thing. Sam, do you use the, the voice stuff a lot?

• 38:02Sam Parr?

  Yeah, I don't type really at all.

• 38:04Shaan Puri?

  Yeah, I wonder, it's probably already a huge percentage.

• 38:07Sam Parr?

  It's gotten to the point where like our offices need to change, like these open air offices that are like popular in startups, they're kind of whack right now because like, I want to talk in private.

• 38:16Shaan Puri?

  Yeah. Yeah, a lot of engineers have microphones now where they're whispering and they're just like in hushed tones, whispering to their computers.

• 38:24Sam Parr?

  Yeah, like I didn't, I was like talking last night and I was like, Claude, why am I so indecisive? And then my wife was like, gay. Like she was like, I was like, man, dude, chicken to hear everything I'm talking to Claude about now. Yeah, no, I, I, I, I talk all the time, but it's embarrassing.

• 38:39Speaker 01

  Yeah, like even speech still like sucks. It's still not great. Like it's um, it's like almost like you set up, you have to go there, you have to like turn on, like it doesn't like really remember what you just talked to it about. Like it can't do tool calling and computer use very well. Like it's just like limited and these like, you have to use it for a certain session. I don't know if we'll hit it this year, but certainly in 2027, you will hit like a full human Turing test with speech. You'll be able to take a phone call from an AI system on your phone and I'll be able to fool you guys. I'll be able to have like a human call you and a robot call you. And I don't think you guys will be able to tell the difference. Uh, that's, that's a 2027 event. I feel pretty shocked.

• 39:14Shaan Puri?

  Today's podcast is brought to you by my friends at Mercury. They make the world's best banking product. I think you know this already. I use Mercury for all of my businesses. I think I have like maybe seven or eight businesses. We use Mercury as our business banking across all of them. And now they actually just launched a personal banking account. So I have my personal account there. I moved off of Wells Fargo and Chase. I'm just all in on Mercury. Why? I like products that are easy to use. I like products that get me and the problems that I have. So like very easy to make a joint account with my wife. Very easy to spin up virtual cards. One click and I get savings yield. It just has all the stuff that I need in one place. So if you're looking for the best banking product on the market, it's definitely Mercury. I will fistfight anybody who disagrees with me on that. Go to mercury.com/personal and learn more. Mercury is a fintech, not an FDIC

• 39:58Shaan Puri?

  insured bank. Banking services are provided through Choice Financial Group and Callum N A, members FDIC.

• 40:04Sam Parr?

  All right. What's the third and fourth?

• 40:05Shaan Puri?

  Yeah. Over the past 10 years, school shootings have increased by 10x. In 2026, the first full scanning system capable of detecting weapons from a 20-foot standoff will be built and beta tested in a K-12 school.

• 40:16Speaker 01

  Ah, man, we're gonna be, well, we'll have our first, we're building our full-scale system starting in October. And I think it'll, well, I think we'll bring it up before end of the year. I don't know if we'll be at a K-12 school. So we might miss this one by a quarter.

• 40:29Sam Parr?

  Do you have separate CEO running that one? Or you're the CEO also of that company?

• 40:33Speaker 01

  I have a chief engineer from JPL and NASA. That's like really good. And it's mostly a pure engineering project. Project. There's like really not much to do on the business side. Like there's, you know, we have like some supply chain stuff and other things, but most of it's just like purely, can you build a system that can tech weapons? Well, it's partly like a hardware problem. It's probably an AI problem. It's like roughly like a large scale. And it's like an instant deep in, deep tech, deep engineering problem to solve. And my whole team is just all of engineering. They're really good. We actually made a pretty big change of cover. We would already be in market by now. And I like I pivoted the whole technology system about a year ago. We were building this like, we

• 41:12Speaker 01

  basically, I found a way to do everything very cheaply in in silicon and chips. And reduce the price by like 90%, make it much more scalable, make it work better. And we pivoted. The problem was that the fabrication times for designing your own chips and getting them out took about a year. So we just got those chips in like, a couple of months ago. And we're testing them and they're awesome. Now we need to make more. And there's another six month lead time to make even more of them. So it's just like, we're like dealing with like real silicon, long fabrication of very difficult chips, lead times now. We'll be out of this at some point. But it's not like chips you can go off and buy it, you know, off a shelf. These are like custom designed cover chips that like nobody's really ever designed before. That we had a special fabricator in Europe that had to go make up. And it took about a year.

• 41:58Sam Parr?

  Hey, you are firing on all cylinders right now professionally, it seems. And I'm, and I, I actually would like to know, like, what's the trade off for the life that you're living right now? Because you're very optimistic. You seem excited. But what are all the trade offs?

• 42:13Speaker 01

  Yeah, about five years ago, I had like a, like, you know, like having kids and the companies, I had an issue where like, I think in my life is like three pockets. I have like work, which I care deeply about my family. I have like three kids. They're pretty young right now. And then I have like the call like the other stuff where it's like a friends in town, or you need to go to the annual golf trip, or like, it's a bachelor party, or like, you know, it's a wedding in like, Europe, or whatever it is, like in this bucket over here. And I felt like I needed to make a decision on like, I didn't need to do like, if I want to use any of these well, I kind of like, I can't do all three. And what I wanted to do really well is like family, and I want to do like business stuff. I want to just like, I want to be like, A plus in those areas. And so I basically stopped the

• 42:55Speaker 01

  third bucket. I don't like, I don't like do anything anymore over here. So like, I had a friend in town from a college. It was like my freshman roommate. And he was like, I'm in town for 10 days in the Bay Area. I want to meet up. I haven't seen him. It was like, you know, for a long time. This would be great to get a coffee. I was just like, oh, man, I'm gonna be real. I don't have any time. I can't, I can't meet you. He's like, I'll make myself available, come to you. I was like, I literally have no time. Every minute I'm away from one of these two is a minute I'm away with my family or work. And there's almost a limited amount of time I can put in both those buckets.

• 43:24Sam Parr?

  Can I ask you about your workflow? You made a joke. You're like, I don't use Slack. If you're comfortable, could you just like, hold up your phone right now? What's on your, what's on the home screen of your phone? What's your app setup? What do you got?

• 43:36Speaker 01

  All notifications.

• 43:37Sam Parr?

  Oh, well, you gotta open it up.

• 43:38Speaker 01

  Oh, what's my?

• 43:39Sam Parr?

  Oh, so you have just tons of texts.

• 43:41Speaker 01

  This is like my, those are all, I think, Slacks and texts. I mean, I use Slack. I just can't get through it during the day. I have Hark going through it. And then they Hark text me. It gets important. I need to look at it with a link.

• 43:52Sam Parr?

  So what's your setup like? What's your like, do they, when you're, do you use a laptop at all? Are you only on the phone?

• 43:57Speaker 01

  I use a laptop. Yes. Laptop a lot. Laptop and phone. I would say I use Hark now for all my AI stuff end to end. Even like tracking, like stuff I'm doing on engineering projects, recruiting, all of it. I do a track. It's in my, it's in my email. It's in my Slack.

• 44:12Sam Parr?

  What about your to do list?

• 44:14Speaker 01

  That's all in Hark. Hark made us all there.

• 44:16Sam Parr?

  So what about before Hark?

• 44:19Speaker 01

  I would, my to do list was done in the Google Doc. I had like a doc called Replanning, and it would constantly keep updating every week. I had come in on Sundays usually, and update my plans for the week. And I updated there.

• 44:31Sam Parr?

  And what about health? Are you doing anything for health?

• 44:33Speaker 01

  Yeah, I do like, I've gotten like, access to some special doctors and things now, where they basically send you through like, the quarterly blood tests, and like, the whole body scans, and like, the CT scans of the heart, everything. And it's been honestly, pretty unbelievable.

• 44:49Sam Parr?

  What was unbelievable about it?

• 44:51Speaker 01

  The amount of data you get back, and the thoroughness of all this. Like, like, for instance, like, you know, if you get a, you can get a CT scan of your heart for like, 100 bucks. I think you can basically prevent heart attacks. You can get a full body MRI. And I think you can like, have early cancer detection. A lot of blood work and find some anomalies that you can go fix and better for your health. So there's like, maybe like a dozen of those.

• 45:12Sam Parr?

  Yeah, but the solution to all those things are probably things you're unwilling to do. It's like, you're probably willing to eat whole foods. But like, it's like, get up, go for walks, exercise, and that was outside of your buckets of, of, of focus.

• 45:25Speaker 01

  Yeah, unfortunately, I haven't been able to have enough time to exercise enough. But, you know, eat right. Like, I've, I've like, I eat pretty well now. Yeah. I mean, listen, like, someone's got to give. I can't sit here all day, eating it. Like, I gotta go work. I like, I like, you know, I want to go crush these businesses.

• 45:42Shaan Puri?

  When you, you wrote in like our prep doc, you said, I went all in on my first three startups, and I pretty much hit rock bottom every year. Can you describe what you mean by rock bottom? And what is your method of dealing with rock bottom? What's the conversation you have with yourself? Or kind of the entrepreneurial strategy you have when you kind of hit those lows?

• 46:03Speaker 01

  Yeah. I, I basically, almost for like 15 years, was like, always running out of money. You know, at Vettery, we, we had a couple pivots early on. We ended up raising like a $500,000 convertible note in 2015. I, at that point, I think I took out like a 50 or 100,000 dollar loan. I was not paying myself a salary. I was in New York City. I was like, so broke. I was in the negative. We raised the convertible note. It did not look great. And I think it was like, six months later, we launched the marketplace at Vettery, and it just like completely took off. And then a year later, we sold for 110 million. And I think that period from 2012 to 2017, which is like, was like,

• 46:47Speaker 01

  I like, I had like, basically like debt. Things weren't working. And it's hard.

• 46:53Shaan Puri?

  And what's, what's the inner monologue? What do you tell yourself?

• 46:56Speaker 01

  The inner monologue is like, this really sucks. Super painful. I think at that point, you just got to go like day for day. You just got to make it like day, you got to make, when things get really bad like that, you got to build a punch list, and you just got to get through it. Like, there's only way out is through. So you need to build a punch list. And you need to get to day to day. You got to go day to day. You can't go week to week, two days, can't look at Friday, you look, you got to go every, every, you got to get to the next day. Pile through it.

• 47:18Sam Parr?

  I was training for this ultra marathon, and I hate like really long distance running. And I read this story about this guy who kind of helped me. And he was like, just, all you got to do is like, pick something like, it doesn't matter if it's 100 feet or half a mile in the distance, even though you have 49 miles left to go in the race. Just pick something half a mile away, and tell yourself, once you get there, then you'll consider quitting. And then you get there, and you're like, okay, maybe I have a little bit more. And you pick another thing, just like only 200 yards away. You're like, okay, I'll consider quitting when I get to that.

• 47:46Speaker 01

  No, it was like, great. I think exactly how I thought about it. But it was like, it's like, okay, so then I sold Vettery. And then I was doing Archer. I was like, oh, man, I just made 110 million, be like 12x all the venture guys. And then I was like, we're gonna raise money. I'll be raised money, it'd be fine. And like, everybody's like, what are we, what are you doing?

• 48:01Sam Parr?

  For Archer?

• 48:02Speaker 01

  Yeah, everybody's like, what are you doing? We're not gonna fund this. What are you talking about?

• 48:05Sam Parr?

  How do you fight that inner monologue, where everyone says you're stupid and wrong, and this is silly? Just go do software?

• 48:12Speaker 01

  It's coming from a place of conviction. Like, I know I'm right, because I've done the work. I understand it. I'm on the floor.

• 48:18Sam Parr?

  Yeah, but the odds are still against you, right?

• 48:20Speaker 01

  But that's, that's, that's the game. That's when you play this game. It's like, you like, sign up, and like 95% of everybody around you will fail. Like, remember what Vettery, we like, we started at the NYU incubator. I was like, so excited. We got in like the, one of the like, the semesters. And there was like, I think it was like 50 companies that were there. We started in Soho. It was great. We had a great time. The, I think, if you look back, like, I think like five years later, me and one other guy are the only two people that made greater than $0. One of our team, 48 companies went to zero. And I was just like, holy shit. If you're around this game for long enough, like, everybody dies. And that's everywhere. It's been like that since for 20 years. And I've been watching around. You're like, you see all the TechCrunch stuff, and things on X

• 49:04Speaker 01

  about people raising money, and all this, and just like, over time, that all just kind of fades away. And it's just really brutal. So I had to like, I had to like, you know, I had to like, I bought a house. And like, I had to put all the rest of the money into Archer. And then I had like a stock lockup. So even while I was coming over to figure, like, the stock was like unlocking, I was funding, figure with stock from Archer, because I had no other cash. Stock was coming down. The stock was just like, literally like a falling knife. Well, at that point, it was just like, I think it went from like, Ten bucks to like two and it's since like gone up a lot, but like, uh, I had to take a second mortgage on my house. That'd be even fun figure.

• 49:45Shaan Puri?

  We asked you one of your philosophies and you said, um, I believe that doing hard things is easier in many ways than doing easier things. Can you explain?

• 49:53Speaker 01

  Like, everybody's trying to do easy things. When you work on harder things, you have like less generally, like overall, probably there's like first order, like less competition. You have probably like a hard thing probably means like it could be a potential like really big TAM, really big exit if it works. You have like, it's like, you know, risk reward trade. You have folks that probably want to work on hard things, probably like the best overachievers in the world that kind of wants to work there. Generally, like, you know, hard things have this like binary payoff for investors. They were like, really want to fund those things because they could have like a hundred X return for the portfolio. And I think there's like a nonlinear curve to scaling here of the difficulty here. I mean, like, I think a lot of the hard things are not like 10 or a hundred times harder.

• 50:34Speaker 01

  I think the hard things sometimes are like two or three or four times harder, maybe five times harder, but they're not a hundred times harder. So you might have a hundred times better payoff, but it might be like three or four times harder. I'll give you an example in robotics. I think like largely building like quadruped robots, like four-legged dog robots versus humanoids, like probably humanoids are probably like three times harder than that. Maybe four. That's it. But like, there is really no, I don't think there's like really a real market for humanoid, like, like those dogs. I think it's just like a niche thing. I don't think it's a real business for it. And I don't know anybody that really at this point like really wants to spend a lot of time on that. So like you do humanoid, it's like, okay, three times harder, but it's probably like a million times higher payoff, probably like a million X or billion X higher ROI for that.

• 51:16Speaker 01

  You know what I mean? For investors, for humans that want to work there, get stock and participate in upside and for everything else. Like, why would you ever like, want to work on like, like four-legged dogs? What economic value can like a robot dog bring at scale? Like, if you really understand it, like, I think there's, everybody's trying to do the easy work and it just becomes really difficult. You know, like, look at, look at all the AI slop, like open claw harnesses out there today. It's all crap. It's all not good. They're all gonna go, I don't think any of them will make it long term. You might have some consolidation here and there for aqua hires and stuff, but like, that's gonna go all the way.

• 51:50Sam Parr?

  Dude, you talk in so many absolutes. Has that not gotten you in trouble ever?

• 51:55Speaker 01

  I don't know. I mean, mark my words, like, like you think like, have you guys even used open claw since then?

• 52:01Shaan Puri?

  No, I don't know how to.

• 52:05Shaan Puri?

  I, I never, I never trusted open claw to set it up. I was not.

• 52:08Speaker 01

  Yeah, I used to use it. I don't use it anymore. It's not very good. Like, the wave's over. I don't know. Just, I'm just trying to say like, I think it's like, I think the most important thing you can do as a founder is to think through what you're gonna actually go do. Cause you're gonna spend the next 10, 15 years doing it. And it'll, it'll like, it'll map the whole course, the probability course, it's like a probability weighted decision of like, or probability of like, of like potential outcomes.

• 52:30Sam Parr?

  Well, but you're, you're, you're, you're talking about a very particular game. Like, like, for example, uh, you're, as you've said, you're like, we're gonna be a trillion dollar company or we're gonna go bankrupt. Like, it's, it's binary. Most business is not binary. You're, you know, you're playing the game where binary is the outcome and that's what you like. But it's not like that for a lot of people. Um, like for a lot of people, if they can build a really cool 10 million dollar a year business, that's a massive home run.

• 52:56Speaker 01

  Is it? We're like, if like, they can do that well, and you look back when you're seven or you're 80, would they, would you have asked the same person, hey, you built a really cool five or 10 million dollar business, you did it for 30 years, you didn't do anything else, you didn't try anything else while you were doing it, you just like work on that business, would you have gone back 30 years ago and tried to take a bigger swing?

• 53:12Shaan Puri?

  Like, would you have taken a different swing than Vettery? Vettery was like that.

• 53:16Speaker 01

  Vettery is my bridge. I started inside of Vettery for like seven years. Like, we literally built like a marketing automation tool for us internally. And then like a year later, I was like, oh man, look at this. It's outreach.io. And it was like a billion dollar company. We built that internally a year or two prior. And then like watching all this different stuff happen, and I was like, man, we like, we actually did some of this work internally. It's like value less than some other groups out there. Like this whole decision of like what you spend time on is like super critical, uh, for startups, assuming like there's a, and I do think startups are like, I think it is kind of binary. Even guys that get the $10 million, there's probably like another 90% of those folks that just didn't make it when they're out there trying. So I think it's just, I think it's just hard. And I think dude, kudos to guys getting to like five or 10 million in business. Those, that's, that's hard.

• 54:02Speaker 01

  Um, especially doing that if we maybe look a little bit of capital or no capital coming in.

• 54:06Shaan Puri?

  Hey, let me ask you real quick about your, your, uh, other stuff you've seen. So I'm sure because you're doing really interesting work, you meet other founders that are doing interesting things in, you know, unrelated spaces and not humanoid robots, but equally cool, interesting peek at the future. I think you've probably seen more of the future than, than us and definitely more than most of the listeners. Can you give us, uh, anything that you've seen or heard or read about? A founder you've met that's doing something that's like, oh yeah, you, you guys, you guys realize, right? The future is actually gonna look like this. And we're just, you know, not, it's not evenly distributed for all the rest of us yet.

• 54:40Speaker 01

  I like, I like looking at, I like trying to think through this problem of what was the world gonna look like in 30 years? Where's, where everything's headed?

• 54:48Speaker 01

  I think we have an energy problem, like not an energy consumption, like a generation problem. So how we, maybe both, but like ultimately, how do we like generate more energy, uh, as like a species? I think there's like, there's like a, there's like a secular trend here that you want to go ride and really help. And I think there's, um, a lot of work done correlating this to like, like standards of living for humans. So I think there's a lot of work here. Like what is the next generation? Is it solar? Is it wind? Is it nuclear? Like, and then there's a bunch of different trades inside of here for fusion and fission and the rest. Like, I think it's a really exciting area. I think it would take a long time, but you need like, you need like really great entrepreneurs like they're stopping that stuff.

• 55:26Speaker 01

  I think AI is just gonna dominate a lot of stuff in the next 10 or 20 years for all of us here. I think it's gonna be like a hundred, we all lived through the internet. Like, I think it's gonna be a hundred times bigger than the internet. It's gonna be so, so big. It's gonna, it's gonna, AI is gonna eat the whole internet. It's gonna eat it all up. And, uh, I think it's gonna be extremely like large trend, both physically and digitally.

• 55:48Sam Parr?

  What, are there any products that you're looking at or companies that you're looking at now that are not already the mainstream that you think are good examples of what you're talking about?

• 55:56Speaker 01

  I mean, we're working on this stuff at Harreken Figure. Um, it's unclear. We're still in this spot where like, it's really not clear who's gonna do well here in this stuff. And we're in this like foggy area for a lot of these stuff of like, there's been no breakout here. Uh, there's been early wins and early breakouts, but there's like a next leg here that we're gonna go through. And we're like, we're in it now. I think we'll know more in the next year or two, what that really looks like. But, um, I mean, I've used like every AI device out there, haven't been super thrilled. Um, I don't know if you guys are seeing stuff in the market for these type of things, but like, I haven't like, you know, been like, man, this is like a crazy, great product.

• 56:34Sam Parr?

  I like the small stuff. Like, uh, like whisper, whisper flow has like pretty meaningfully changed how I communicate.

• 56:41Speaker 01

  Yeah.

• 56:42Sam Parr?

  That's been pretty cool. I think that's been my big standout the last six months. What about, last question, what about, um, people who inspire you? Because you're, um, you have very high standards. Who or what type of entrepreneur, who are they, dead or alive, that you lay in bed and you're like, how would this person react to this situation? Or how do I have an attribute similar to the attribute this person has?

• 57:06Speaker 01

  I think I really admire the folks that are like fully dedicated in their craft. You really watched the Michael Jordan documentary. He's just like, he's just like, I just want to be like the best in the world at this. I think for like, for startups have that same thing too. And I think first and foremost, like, you know, what I can read, I'd ever met Steve Jobs, but like, my lord, like stories I've heard and everything else. The guy was just like an unbelievable operator and product led founder. I've also got the note Jeff Bates was pretty well. He invested in Figure and he's been here a lot of times. And I think, uh, I think Jeff's has, has been a really good soundboard for a lot of things we've gone through. Um, I had Jensen in here last week again, like we are fairly close and I think Jensen's just an unbelievable operator as well.

• 57:46Speaker 01

  He's very hands-on, has a very unique way of managing Nvidia and its organization last 30 years. And it's, uh, I, I think he's like, I think he's done a lot of really good things.

• 57:55Sam Parr?

  What advice did Jeff, uh, give you that was meaningful?

• 57:58Speaker 01

  Jeff said, well, last time he was here, he's like, listen, you're at a really interesting period because like you've figured out how to do this somehow. In the next year or two, you're, they're gonna figure out how to break through and really get this like working in a bigger way, or you won't. And like, this is like your, it's game time for you now. And you gotta just get wired in and like figure out how to break out and make this thing work and scale it. And you're at a really interesting point. I don't know how you got here and I don't know why you got here, but you're here. And you need to figure out how to like your next, you know, you're on the big field now and your next big push is gonna like make or break it. So I think he's largely right. Like, I think we're like, we got robots now doing this stuff autonomously with AI models, which is crazy. I think four years ago, you'd been like, I'd been like, no way, like no way you could.

• 58:36Sam Parr?

  Dude, four years ago I came to your office and you just had a knee working. And I was like, oh, that's a knee. That's cool. It, all it was, was a knee. You had like, there was five engineers. You're like, this guy just got done building the Tesla X or Cybertruck or something. This guy did this amazing thing. This guy cured cancer. Look how the knee moves and the ankle has dorsiflexion. And we were just sitting around looking at this knee and that was like the coolest thing.

• 59:00Speaker 01

  I know, man. It's like, and then now we have like AI that's working on a humanoid robot. We're taking in cameras. It's doing inference on board. It's outputting where all the joints go. You know, it's, it's unbelievable. And, uh, it's crazy. It works. And, um, and yeah, the next leg up is just like making that work at a higher scale. So I don't know. He's been great. I think there's, um, I don't know. I think those are kind of some like, I think really good folks to look up to that really like, like love their craft deeply and really care.

• 59:27Shaan Puri?

  Well, Brett, I think it's time for you to get back to work, my friend.

• 59:30Speaker 01

  Great. Thanks, guys. It was good to see you again.

• 59:32Sam Parr?

  Thank you so much, dude. All right. That's it. That's the pod.

• 59:46Shaan Puri?

  All right. Let's take a quick break. I want to tell you about Marketing School. It is a podcast that is part of the HubSpot Podcast Network. And it is run by Neil Patel and Eric Su. And these guys are both marketers who are running businesses. And so if you want real world tactics from practitioners who are actually out there in the field doing it, this is the podcast for you. Check it out wherever you get your podcasts.