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

0:00 I think if you Google Bret Adcock net worth, according to Fortune, you're worth nineteen billion dollars. So that's like a pretty good swing. How's that make you feel? I don't care about that. Give like zero ships about. I feel like I can rule the world, I know I can be what I want to Okay, so you uh Brett Adcock, the the short of it is that you were raised in a rural area of Illinois. You started a company called Vetery, which we sold for over a hundred million dollars.

0:31 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 forty something, thirty something, fifty something billion dollars. You have another thing called cover, which stops uh or aims to stop school shootings and then now you have a new thing called hark Which you've raised money at in the billions of dollars.

0:52 And you seem worn out. Great. 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 uh you were telling a story about how I think it was right when figures started You basically said like I had I was worth I don't know how much tens of millions of dollars

1:10 I put almost all of it into figure to get started. And at one point you're like I have a mortgage on my house. And the rest of my money is in figure. And some of the money's 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 nineteen billion dollars.

1:29 So that's like a pretty good swing. How's that make you feel? I don't care about that. I will like zero shits about that. You're a super competitive guy. I think you said something like I just wanna w uh you said like win a bunch of times last time we hung out. It was like I wanna win for these reasons. I I'm I I'm very comp I w I want to kick ass.

1:48 I think that like you definitely have to care about this a little bit, and you actually have to I think you a I 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 wanna be the best, I want to conquer. I think any way I would characterize it is like we're just The like we're just now like these companies of mine are just now hitting the inflection point. And they're really early. Like they can be like really big. So

2:12 If it works, this will like a hundred X. Thousand X 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 it 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 gonna be a beer very big thing or very bad.

2:30 And so All my energy's going into Making this like a thousand 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. Where where are you now? What's the uh outlook now for the next five years then? I think

2:44 Last time you were on, three years ago, we said that I think I said it. Uh I was like I you'll probably be in the forty to fifty million dollar valuation range, which I think you are now. But in terms of like You you're still lacking output of robots. Like you still need we still need that to come. When where are you gonna be in five years? What's your prediction?

3:02 I think at a high level I think the AI work that we're seeing here now is gonna be so much it's gonna be like a hundred times bigger than internet. It's just like everything is just so It just working so well. Like the system is working well. Like deep learning works. And

3:18 Everything's happening faster than I would think. Am I true like you know, having done like fifteen years of like software on the internet, like it was just like Nothing was happening faster on a trend line. Here is happening like that in AI. Can you give an example of something that has happened that's blown you away? We started at so Hark, I have a new AI lab called Hark.

3:36 About a year ago I was like very interested in this idea of like kind of building this AI to human symiosis visually. It's like um figure's gonna be like I think figure is gonna be like the max ceiling of A GI of like being able to put that out and then There's gonna be a version of this in the digital world. There's gonna be like a human's gonna have this like AI pairing, it's gonna have like Also mean maybe your own AI weights, your own memories, maybe your own hardware. It seemed like really close.

3:58 And fundamental to that thesis was like you gotta figure out how to get AI to use computers general purpose. You would never hire an assistant that can use a computer. So you gotta be able to like give things out to it that can like do everything you can do. Financial models. Book flights, like order door dash, whatever you need to do.

4:13 It needs to be able to do all uh autonomously. But only one in a thousand websites have APIs. So in most You know, glob like most computers globally is on the on the internet and browser. My in uh mean my inclination within two or three years you'd have a

4:27 system that you'd be able to talk to and say, go do this or do that, and then be able to like go off uh go online and like maybe maybe like use the internet really well. Like a almost like a robot would where you can like move the mouse. And use the keyboard. That's what you have to do is solve like. general purpose this for around a computer is you You can't rely on API or MCP.

4:43 You have to figure out how to like Now they 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.

4:53 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. What did you guys do differently than the other'cause c everyone's trying to do computer use, right? So like I think Elon's got Macro Hard and Chat GPT had their computer use thing. Everybody's doing it. You guys feel like you've cracked something. What'd you guys do differently? Okay, there's a couple things we did a little differently. First is like everybody's tackling this from like using APIs and MCPs.

5:15 Like the reason why Open Claw 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 try to figure out how to use like a how to look at a screen. And one is we spin up a virtual computer for every agent.

5:31 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. Yeah, but I use Chat GPT'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 A APIs or or uh M C it was trying to use the internet. Yeah, I don't know if I it's gotta work well. I mean that's the whole point. But like if it goes on where it fumbles on the net, it's like the whole point is like it's so that's what I'm saying. What did you guys do to make it work well? Was it like an algorithmic breakthrough? It was in our post training, like it was in our reinfor we have a reinforced learning process that we think is M maybe nobody else in the world has done. Well get l let's get some context behind this because okay, so figure that is shockingly easy to understand.

6:20 Ro humanoid robots and that business is gonna 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 kinda explain like I'm idiot? Because Sean, you should see I got the deck. And it was just you talking.

6:38 For like an hour. in front of a screen and then there was a list uh there was a list of a team And it was like A hundred guys who just moved here from China. who had like the greatest backgrounds ever.

6:49 And You it seemed like you pretty much just raised money because the team was amazing. And uh that that's all the deck was. It was just you talking in a video. Well I mean that's kinda all we had at the time. We started. So okay, what is heark?

7:02 I think the best way to become successful is to see how other people did it, whether you're gonna copy them or just use it as inspiration, because then now you know what's possible. So starting at the age of twenty four, I did this relentlessly and I was very methodical about it. And I created a spreadsheet where I tracked roughly fifty 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 Hub Spot went and spo this thing that I frankly even forgot about, but it did change my life 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 twenty four 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. 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

8:07 Of AI out in the physical world that will like do everything. In the in the in the environment for you. Like laundry dishes, cooking, like s run the supply chain into and Be in healthcare. The vessel for that's a humanoid robot. It's just a human form. And it will just go out and do like

8:21 You like want one piece of hardware that can like, you know. hardware capable of doing everything and you put like smart AI into it and go off and do everything in the world. That's what Figure's working on. Simpler than that. There's gonna be this like really close like digital like AI to human symbiosis that forms.

8:36 You're gonna 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, 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. 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.

8:58 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 f like a If you're on a flight with like a long layover, or you're in a flight with like maybe say a short 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 chat bots. We don't have like something that can go off and like Be my Jarvis.

9:20 In order to get there, we need to work on the Like model side, it's gotta be just better than text chat. It's gotta 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.

9:34 The system. It's really like look at the world and understand what you're seeing with it. I think secondly You need to have um you need to fix the it the interface, the AI. You have like um AI over here in a human and you have like a old hardware system in between. Like a call like a MacBook or iPhone.

9:50 They were designed twenty years ago. They're complete rubbish. Very high. They're not the right interface. So we went out and

9:58 B we are out there d 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?

10:07 Like we're and we're in a upgrade cycle with the computers and phones. They're just gonna go away. They're gonna be a new one, they're gonna be all AI computers and phones. and systems. And they're gonna be great. They're gonna be all real time. You can always access them anyone. They'll always be like understanding what's happening and they'll always be able to reference things w w 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 really great.

10:34 Uh parry. And we hired a credible team. Teams like you know, maybe like eighty or ninety now. Uh the guy that leads uh hardware design abs. Previously designed for last several generations of iPhone.

10:46 MacBook, MacBook Pro, like he's just like the stud. He's great. What we think are the next generation of AI devices that will kill the phone and computer. And then uh we're designing the next generation of AI models. The models need to get a lot more multi multimodal. They need to get a lot more expressive. Like the text and coding is just not enough for us to like really have a like a like a real A G I feeling with AI. So we're working on that. We have our first

11:09 AI pre we did our first research preview or computer using AGM. that we came out last last week. I think we were like top on some of like the leading like, you know, browser computer use benchmarks in the world. And uh it'll keep getting better this will keep getting better and better. Like every month we'll just like it'll be better and smarter using a computer and faster. We're working on a couple other 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.

11:35 So um you'll be able to start using it and then we'll have hardware coming. Um we're working on now. We actually have a hardware in the lab now. We're using Tassinus. It's crazy shit. Like the stuff is like a sci fi movie hardware. What do you think those devices look like? You know, people have been speculating because Johnny I you know got his his his shop got acquired by OpenAI and You've seen the videos of the puck and then the 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? Wha what's the story of that? And then what do you think these devices

12:05 end up looking like are these watches, glasses, something else all together. I think I've like really changed my mood on this a lot the 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.

12:21 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. Call like mega devices. And then you have things on the ancillary around it, like orbiting this like big thing. that are like airbods, AirPods and you know, like a watch or with things like this that are like

12:39 They don't sell a billion units a year. They're like three percent of like Apple's revenue and they're like they're they help the ecosystem as a platform. What we care about Uh, Hark is trying to solve what's in the big Middle piece. To solve that, you gotta take down the computer and the phone.

12:53 There's no way around that. So you have to rebuild a new computer or new uh phone. That's better and replaces your existing systems. And And then what's around there is things that like you will have. We will even have at HARC that are like a helps with a family of devices.

13:08 that are um not a billionaires a year but important for the ecosystem. My understanding right, you're s you're kinda saying the next The the next device. It might be like a phone. It's just gonna be an AI native first phone. Right, you're not gonna try to change the form factor. No, I'm not saying that at all. You're gonna wanna 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 my whole life. Okay. What lives outside of here on the edge or like

13:34 Like glasses and pendant and wearables and things. They're not they're not the main show. In fact, like the metaglasses are probably one of the worst products I've ever bought. They're just horrible. They're horrible. I give you I 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 and the pairing's long, like It doesn't work well, like

13:54 I can't think of any reason why I would need this thing strapped to my head for fourteen hours a day. Like it's just like the wrong device. It's it's not. Like w the in state is BCI in the brain. And we're gonna have like AI language devices for the next ten 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 classes will make our top

14:13 Like ten list. Uh devices. 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.

14:27 Let's let's get down to like the substrate level here. Like first order What what has changed? But what's changed is we have like a new type of computer, which is the like the A I think of AI as a new type of computer. You talk about automation, that's here. The automation can do a few things that are like

14:42 Like e when we're designing this, we want to design around like key principles that could be like ten X better. I if if it's like one or two times better in your phone or you're not gonna use it. It'd be like literally ten X better. What are things now that like a deep learning brings that are like ten X better? There's a few of them.

14:56 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 of speech, it can uh it can use computers and systems for you as fa close to as fast, around as fast. of a human can, over time it'll be just as good as a human and faster. Um in terms of success rate. She have a system that's like almost like human like in capabilities. It also can like have memory, meaning you can put memory into it and like won't it won't it won't forget anything. I mean near perfect over time.

15:25 Do you have a system that's almost like a human in a box? that has all the same like affordance 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 and only Sam could talk to you, and only was like there to help with Sam.

15:44 And that was like your whole life and it was 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. Okay, so your first step Where your team is like

15:56 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 and hear and then give advice to us? Like Like what is the thing that's gonna bring That's gonna fundamentally reshape all this. Okay. And then from there, like we gotta like we gotta design around that system. The competitive advantages here are that it

16:19 uh is human like in capabilities and it has almost near perfect memory it 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, uh somebody's like, Hey, did you did you call that person? Like, I don't even know the name. Forgot. They can't even ask my phone. Like it's just like it's so stupid. Like the whole system is

16:39 And then I go in there like order door dash 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 They'd even predict probably Brett, you want coffee today? And I'd be like, Uh yeah, I do. Like let's get let's order a but you know what, make it a double shot.

17:02 Today. And you know, I groute to the Hark office instead of figure. Like I can like I was just and done. I got it. Let me take care of it. I'm thinking like a monkey on my phone for the next like three minutes like trying to do checkout door dash. It it's almost like the phone is like a tool in the 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.

17:21 Whereas the next generation is basically like having a handyman next to you at all times. And so you just tell him, Hey, can you fix that window? Let's go fix the window. You don't have to pick up the hammer and start figuring out how to use it. 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 three D printed it. What were the designs that didn't work but were kinda cool?

17:43 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

17:56 That looks like a that looks like this and it will that does overwhel over here. So it's like it's not as easy as drawing those parallels. It's like pretty quite radical. But we w 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 kinda down selection. I mean, we we had like one of the biggest telecom CEOs in in the world here that actually helped um With with the work with like Steve Jobs on iPhone one.

18:25 And he was here two weeks ago. And he just come from meeting Tim Cook. Uh, you know, Tim Cook's on his way out as Apple, but he's like Wizz over there at Apple and Came over here and we he saw our stuff. And he's just like

18:34 Holy shit, man. This is the first time I've ever seen anybody that could possibly take out like take out the big guys. It 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? The hard problem is not that.

18:50 We think we believe now the most important constraint to really solve is like bu building a really intelligent robot system we can proud to the world. Like there's a bunch of robots you can go buy now. You can buy some from China and you get'em and they're complete crap. They can't do anything. Think like you can enjoy sticking around. That's all you can do.

19:06 And you like hit a button and it waves. And you're like, what do I do with this thing? It's a toy. It's like it's like when I it's like when like early when I bought a D 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? Yeah 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 floated 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'em, but like if they're not really smart, like it's not really gonna be that helpful. We're trying to crack like the true human level intelligence of figure. Like we really want to tackle like

19:37 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

19:50 Beyond that, like You know, people generally sometimes confuse like Consumer electronics manufacturing with car manufacturing. There's no company big company in the world that would look like say like uh

20:01 Uh, I'm scared of manufacturing this consumer electronics at a high rate if there's so much demand. Like this is just possible to go do. I mean you can make'em b uh you make we make a billion phones almost like, you know, pseudo by hand in the world and then with some automation. But cars is a different story. Cars like you will die trying to manufacture cars. There's like there's like lot of company like you just like it's so And having seen like, you know, but B and W is a commercial customer of us.

20:22 I haven't been in BMW and a few other groups like It's gnarly. The reason why cars are 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. So 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 de is your d your whole line's done. And so it's just like just like huge giant robot you're building.

20:48 That's building the car. And with figure you can hold any partner hand. So I think we're like if we're like between cars and like a strong electronics, we're like over here. Closer to like you know like you know the forty percent level over here by like cell phones. Like we you know, we just made our one thousands uh E V T robot for figure three last week or week before that.

21:06 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? We had like two bit like large customers. Uh we have a us as a uh as like an engineering and 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.

21:27 Uh there's just a lot of work we need to go do uh internally. we call like maybe like engineering fleet would need to go to and then second one is go to customers. So we haven't going to both right now. Uh we've actually shipped out robots to our third customer. This this this week. When they go to customers, what do they do? What what what what can the robot do? What and maybe can't it do at this point. We do a lot of like logistics stuff right now and packages. Uh we have other stuff we've done in manufacturing. Mostly just manufacturing logistics is stuff we've done in the past.

21:54 Um but like we're also talking to folks about Other industries. 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? 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. Yeah, that So is is that the type of like would that be give me an example of one of the jobs that just want to do that? That's an example of like us uh uh like a very very close to like one of the j one of the works we do. Is that customer like, oh this is awesome because I can't find the labor to do this. Uh it's too expensive to pay 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

22:37 Two years from now, that cost curve is gonna work and it will be faster, cheaper, you know, whatever. 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 talents are 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 this work. And uh we need you to come in and help us.

23:04 We have an ability to make a lot of good money. in our contracts and the customers make like really good ROI. Uh on this. Like you gotta think like a robot can do like multiple shifts per day, work seven days a week. Like it we can like have a lot of uptime. Uh the task you saw like on the on the on the like um logistics line that we should live stream was actually a real use case for one of our customers. Uh that needs to be done at three seconds a package.

23:27 And this thing's gonna be done five hours a day. Like I think it was like five days a week. We do 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.

23:40 And uh we're now in the early stages of like getting these out to these customers and scaling it up. Uh over time it will just put billions out to these groups. 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.

24:01 It works right inside HubSpot. You can draft 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. Can you help me with like the kind of truth first fiction? Cause uh one of the weird things is

24:21 as an enthusiast or a lay person 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 wanna buy this robot. I have no idea really what it can do. I see uh you know, Ewan 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'em. Uh then you get like one X and they're showing their hand that they're like, Look at our hand, look at this is the 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 and test them out.

25:00 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 out it's out of control. Like the There's just so much bullshit out there in the market, it's like really hard to tell what the hell's going on.

25:19 So let me summarize what I think is like the most important and work backwards. What I think the most important thing to do. is uh to be able to Ship robots autonomously. uh scale in useful work environments.

25:31 Like they can like, you know. Cookie 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 Your logistics. Like

25:42 That sort of stuff. That stuff requires Uh fundamentally onboard AI. You can run? So you can do like autonomous work. You can't solve it with code. You need to do it autonomously.

25:52 You do over long periods of time. And you probably need to move around and use like something on your hands and move move move stuff through the world. You know what I mean? It's like really gotta like do do stop economically. Like it move gonna 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

26:15 You know, we don't care about that stuff. Dude, I can't wait till I see a figure like on a smoke break at the BW fact. I could have been a great back in high school, but I blew it. Yeah, so like Like for us, like we really want to show and demonstrate the ability to do like real things over long periods of time autonomously. Who's closest to doing that? Who's kind of most most bullshit?

26:37 Not doing that. Man. There's like so many groups out there, I don't want to name names, they're all teleoperating the robots and all their videos, and it's like Dude, do get accused of that though all the time. We we haven't put out a single thing ever that's ever teleoperated. I don't think we've e ever done it. Like we We used some tele op internally for like data collection and

26:55 For like it's it's good for like you can like you can do a lot of testing on some of the robots sometimes, but like It's gotta be like this bad thing now. It's like the equivalent of a self driving of like some dude in like Kentucky is driving the car And it's driving around the passenger, everybody's taking a video of it, they're posting on the internet. Like, look at this and it's just like, dude, that's like completely faked.

27:12 But one thing that I've never understood Um and it's I've been wrong many times is how fraud happens. But but I'm always like when you have hundreds of employees And you're doing something fraudulent or you're doing something sketchy or you're doing something that's highly exaggerated. My hope, and I think this happens most of the time, is people are like Hey, uh I work here. This is bullshit. I can't I'm not gonna do this.

27:33 Think there's like this like in somehow in the robotic space it's be kinda become okay. And it's like for me I just like This is the worst thing I've ever seen in any industry I've been in as an entrepreneur. How do you know when you watch those that that it's teleoperated? The ones that are like running fully autonomously we'll like write that in the headline'cause it's so hard. I remember like Tesla put a video out one time of a guy like the robot folding.

27:56 And then like in the bottom right was like a like a teleoperation hand glove you could see in the video. Uh so there's like you like people get caught like doing that. You you you just know in industry, people will comment at the company later, like, hey, this is like no wasn't autonomous. So like if you're in the industry you know like you can follow it. It's also really tough. I I don't know if there's any other company in the world that we've seen

28:17 That you can watch do autonomous work with AI on board on useful work with a humanoid. I we haven't really seen it. I don't uh maybe there is. I don't I haven't seen it. I've made jokes with you before where I was like You started with vetery, which is just like a job recruitment thing. Now you're on these world changing things. And you were like, Well veter veteran actually is world changing and here's why and you gave this pitch.

28:36 It was very good. You're very good at pitching. You're very good at raising money. You're very good at um being cr charismatic and convincing people of stuff. When you're crafting a pitch to recruit and convince people to ch 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? I mean

28:56 Most of all these are online. I mean the figure master plan is on the on the internet on the site. Archer's was up for a long time. Like I think like deep down I really wanna 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 was probably like the richest A I and

29:18 Engineering like uh folks in the world. Ninety percent of everybody out here is not good at their jobs. How do you tell who's good and who's not? I technically assess them. All of them. Yeah.

29:30 To do that, does that mean you need to be as good or better than them technically to be able to assess somebody 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 watched somebody do the work. If you've done the work It's like

29:44 It's like it's like a scar you carry 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 disgust it. The folks that

29:58 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. 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 y would you say actually hit that bar? I'll give you an example. We have like a really challenging process to go through to be a mechanical engineer here at

30:19 A figure. You have to be able to build like Actuator some scratch. There's no 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.

30:32 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. That's insane.

30:44 It's insane. 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

30:56 I I I I think they're like tens of millions of dollars a year, right? The AI side is certainly like that. 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. So what are they like what's a crazy story that you've heard?

31:17 Can we give an offer to somebody that was really senior that was like They were coming from X Ed AI, like X D I completely blew up. Like everybody just laughed and about it six months ago. It was just like like Macrohar like got fully disbanded. Like there's 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

31:35 A really good package like of series A stock at HARC. And it was I don't know. Oh, fifteen, twenty million dollars of stock. Over four years? Over we do five like for uh my companies in the early days, and we transition to four a little bit later. So we're still a five. And uh you know, I was like I think we're like a I think we get like ten X hark. Here.

31:54 Pretty quick. And so I was like, Okay, you have like you know, fifteen, twenty million, I think ten, you have a few hundred million dollars, maybe tense 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

32:09 To go to Meta for thirty six million. A four years of our shoes. And he's just like it's kinda guaranteed cash. You know, I go there and I have to like weigh this like maybe like two hundred million dollars a Park or twenty million dollars, or maybe like thirty six for sure, uh meta. And he left and went to Meta and they've been doing that like every candidate we spa speak to is like

32:27 Making some absurd Absurd thing. They just haven't stopped. They've just been out they've been at it since like for like a year or year now. They've been buying talent. They've been buying their way into the AI race. What what do you think of that strategy? Like, you know, even if you kinda hate it, do you respect it? Do you just think it's a fool's errand? What do you think of that? I really like it. I think like The AI space is

32:44 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. In the info 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.

33:03 And you know, around M O E or whatever you're gonna 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 twenty to thirty people in California. know how to build really good AI models.

33:19 Wait, so but is that trickling down? So you said that there is a senior guy, but like are even some of the less than senior, the twenty somethings, the young thirty somethings, are they still Getting eight figures a year. No, the like the junior guys, like the guys in like their twenties You know, like the like late late twenties or something, they're getting like a f they're making like a few million total. So they're making like Two hundred, two fifty in base.

33:40 They're making like another million or whatever like in in a year in like uh our shoes. Every year. And so they're gonna pay like a million to like you know, or like seven fifty to like two million or so range per year. And that's uh that's been driven up by Meta. And but then all the other labs have have like have f I've like followed comp. When when I asked you what do you think of that, you said I like it. Were you being sarcastic or you're s you're saying no, actually that is smart given how hard it is to get this talent? I think it was really smart. And I would have done the same thing if I was

34:10 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 wanna understand it and I wanna like first order like

34:21 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, Trivin. He they came over there. There's no other nobody wants to go to Meta. They just they're going there'cause they're getting paid A guaranteed RSU package. By sitting around.

34:37 And w what's happening is like you don't need like a thousand people or five hundred or three hundred to design AA models. Like a really good team of twenty or thirty or forty people. And that you can get there without doing this. And those people probably would care more deeply about the mission and where you're at and be more committed. Just purely throw money at the problem.

34:56 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, the recruiting efforts and how they're structuring the stuff and Uh it's like I think it's I think it's like

35:08 paying off for them. Jury's still out if they can like actually ship real product. I think like the traditionally have not been able to do things new well. I mean, I think Facebook is probably gonna meta's gonna go down to like one of the greatest ac acquirers in all time. with like, you know, Instagram and WhatsApp and different way. They've like bought their way into those spaces. Uh but like you know, if you look at like the

35:29 Ray Bans and everything I was doing I was just like It's it's not great work. 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.

35:43 You gotta send it to us. Yeah, can we use it? Well, yeah, we get you guys early on that. Yeah, for sure. It's like research preview, there's like Five hundred PhDs and then me and Sam. Yeah, exactly.

35:53 Park, what's the weather outside? I can answer that, yeah, no problem. I th I I what I'm trying to say is like every week there's like five or ten like junk AI slot startups are like things that 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.

36:10 I think The stuff in coding is probably really excellent right now, but everybody beyond that is like just kinda like not great. On January first of this year, you've made four predictions for the year. I wanna 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.

36:30 Long time horizons going straight from pixels to torques. How are we doing on that one? On track, off track, or done? Oh try. On track. Yeah, four months.

36:40 Yeah, I'm like I see every day like what we're doing. I think we're on track. The hard part here is um we already view pixels to torque. It just means like we're sticking camera feeds and we output like where to put the motor like put the like you know, we wanna put a W 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're gonna do that. Um

37:00 Getting into a new house has never seen new work, that's the hard part of this problem. Um we're working on that. I'm working on that every day. It's from where I spend about three, four hours a day. Every single day. Seven days a week on this problem.

37:10 So if a figure robot showed up in my house, what would it uh what's the par 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 my dishes. Where would it suck for me? 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 L O Ms they wouldn't know how to talk about pyramids. Right. And we just like we don't have enough of that data.

37:45 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 a good example. Hey, stupid question. Why do all the robot companies care about folding clothes and And doing laundry with it. Wouldn't be commercially better just to say, Hey, we're gonna build like the best warehouse worker'cause there's already

38:08 twenty million of those in the world and that represents this much billion's 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 w 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? 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.

38:35 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 veritability. We're in like a Little work side just work twenty four seven. 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 n me or none of my guys want to solve that problem.

38:58 We want to solve a robot that can go into Any environment just do language and do work. We wouldn't be the first to do that. You can probably do that with a hundred robots and a fifty person team. So that that company overnight would be a trillion dollar market cap.

39:10 That sounds good. Do that. We're doing that. Like we're gonna solve I think we'll be the first we call it like solving general robotics. An iRobot, don't they attack the humans? I don't remember this movie very well. Not that part of IR Who can win in a fight right now. Can a can a human still win? Yeah, human can still win. Okay. Uh where do the other predictions um One you had on here. Daily AI usage will shift. People will move beyond text.

39:38 To highly multimodal voice agents with permissi per uh persistent memory will become common. Which will push AI closer to the synthetic human intelligence we've imagined in sci fi. We're doing that at Hark. We'll 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.

39:54 Have the labs ever like has Chad GPT or Claude have they ever released the data on this? Like I use a ton of the voice things. Sam, do you use the the voice stuff a lot? Yeah, I don't type really at all. Yeah, I wonder it's probably already a huge percentage. It's gotten to the point where like o offices need to change. Like these open air offices that are like popular in startups, they're kinda whack right now because like I wanna talk in private.

40:15 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. 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 she was like damn, dude, she can hear everything I'm talking to Claude about now. Yeah, I know. I I I I talk all the time, but it's embarrassing.

40:37 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.

40:53 I don't know if we'll hit it this year, but certainly in twenty twenty seven you will hit like a full human terrain 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 ya. I don't think it has a military difference.

41:08 Uh that's a that's a twenty twenty seven event. I feel pretty sure. Today's podcast is brought to you by my friends at Mercury. Uh 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 uh I like products that are easy to use.

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42:02 All right, what's the third and fourth? Yeah, over the past ten years school shootings have increased by ten X. Uh, in twenty twenty six, the first full scanning system capable of detecting weapons from a twenty foot stand up will be built and beta tested in a K twelve school. Ah man, we're gonna be uh we'll we'll have our first we're building our full scale system. Starting October. And

42:22 I think it'll br well I think we'll bring it up before the end of year. I don't know if we'll be out of K Toll School. So we might miss this one by a quarter. Do you have separate CEO running that one or you're the CEO also of that company? I have a chief engineer from JPL at NASA that's like really good. And it's mostly a peer engineering project project. Uh, there's like really not much to do on the business side.

42:41 Like there's You know, we have like some supply chain stuff and everything, but most of it's just like purely can you build a system that can detect weapons well. It's partly like a hardware problem. It's probably an AI problem. It's like r roughly like a large scale and it's like a and just like a deep in deep tech deep engineering problem to solve. And my whole team is just all of engineer. They're really good. We've actually made a pretty big change of cover.

43:01 We would already be in market by now and I like I pivoted the whole Technology. System about a year ago. We We're building this like

43:10 We basically th I I found a way to do everything very cheaply in In Silicon. And ships. And reduce the price by like ninety percent, 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

43:28 A couple months ago. And we're testing them and they're awesome. Uh, now we need to make more and there's another six monthly time to make even more of them. So it's just like we're like dealing with like real silken long fabrication of very difficult ships. Lead times now. Um, we'll be out of this at some point.

43:43 But uh it's not like chip shouldn't go off and buy it. You know. off a shelf. These are like custom design 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 uh it took about a year. Hey, you are firing on all cylinders right now, professionally, it seems.

44:00 And I'm and I'm and I w I actually would like to know like w 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? Yeah, about five years ago I had like a

44:14 Like uh you know, like having kids and the companies I had an issue where like I I think of my life is like three pockets. I have like work 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 friend's in town or you need to go on the annual golf trip or like

44:31 It's a bachelor party or like you know, it's a wedding and like Europe or whatever it is, like in this bucket over here. And I felt like I needed to make a decision to like I I didn't need to do like if I want to do s any of these well, I kinda like I can't do all three.

44:45 And what I wanted to do really well is like family and I wanna do like business stuff. I wanna just like I wanna be like A plus in those areas. And so I basically stopped the third bucket. I don't like I don't like do anything anymore over here. So like a fr I had a friend in town from a college and was like my like And he was like

45:03 I'm in town for ten days, I'm in the Bay Area, wanna meet up. I haven't seen him as like you know, for a long time. It's be great to get a coffee. I was just like I'm I'm gonna be real. I don't have any time. I can't I can't meet ya. 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.

45:23 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 h hold up your phone right now? What's on your what's on the home screen of your phone? Wha what what's your app set up? What do you got? Oh well you gotta open it up. Oh what's my so you have just tons of text. I mean I even use slack, I just I can't get through it during the day. I have heart going through it and then they heart text me

45:48 I think it's important, I need to look at it with a link. So what's your setup like? What's your like d do they when you're do you use a laptop at all or you only on the phone? I use a laptop. Yes. Laptop a lot. Uh Laptop and phone. I would say I use Hark now for all my AI stuff end to end.

46:03 Um, even like tracking recru like stuff I'm doing on engineering projects, recruiting, all of it, I do a track it's my it's in my email, it's in my Slap. What about your to do lists? That's all in Hark. So what about before Hark? Um, I would my to do list was

46:19 Done in the Google Doc. I had like a Docker called replanning and it would constantly keep updating every week. I come in on Sundays usually And update my plans for the week. And I updated there. And what about health? Are you doing anything for health?

46:32 Yeah, I do like um I've got I've gotten like access the some special doctors and things now, or they basically send you through like uh the quarterly blood tests and like the the whole body scans and like the Yeah, C T scans of the heart, everything, and it's been Ac honestly unbeliev pretty unbelievable. What was unbelievable about it? The amount of data you get back and the amount of thoroughness of all this

46:52 Like uh like for instance, like like we know, if you get a you can get a CT scan of your heart for like hundred bucks. Uh I think you can basically prevent heart attacks. You can get a full body M R I 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.

47:08 Um so and there's like maybe like a dozen of those. 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. Yeah. Unfortunately I haven't been able to

47:25 have enough time to exercise enough. But you know, E right, like I've I've like uh I eat pretty well now. Yeah. I mean listen, like someone's gotta give. I can't sit here all day and like I gotta go work hard. I I low I I like you know, I wanna go crush these businesses. When you uh you wrote in a in like our prep doc, you said

47:44 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 the entrepreneurial strategy you have when you kinda hit those lows. Yeah.

48:02 I um I basically almost for like fifteen years was like always running out of money. You know, at Vetery, we we had a couple pivots early on. We end up racing like a$500,000 convertible no. twenty fifteen.

48:17 I at that point I think I took out like a fifty or hundred thousand dollar loan. I was not paying a salary with a New York City. I was like so broke. I was n in the negative. We raised the convertible no, it did not look great. And

48:32 I think it was like Six months later we launched the marketplace. A vetery and it just like completely took off and then a year later we sold for one hundred and ten million. And I think that period from twenty twelve to twenty seventeen was just like was like I like I had like basically debt.

48:49 Things weren't working. And it's hard. And what's what's the inner monologue? What do you tell yourself Uh the inner monologues like this really sucks, super painful. I think at that point you just gotta go like day for day. You just gotta make it like day. You gotta make uh when things get really bad like that, you gotta build a punch list and you just gotta get through it. Like there's only a way out is through. So you need to build a punch list.

49:07 And you need to get to day to day. You gotta go day to day. You can't go week to week, th two days, can't look at Friday, look at you gotta go every day, every you gotta get to the next day. Pile through it. I was training for this ultra marathon and I hate like really long distance running. And I read this. And he was like, just

49:26 All you gotta do is like pick something like it doesn't matter if it's a hundred feet or half a mile in the distance, even though you have forty nine 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.

49:39 Maybe I have a little bit more and you pick another thing just like only two hundred yards away. You're like, Okay, I'll consider quitting when I get to that. No, it was like great. I think it's exactly how I thought about it. But it was like it's like okay, so then I sold Vetery, and then I was doing Archer and was like, Oh man, it's made a hundred and ten million, we like twelve X to all the adventure guys. And then I was like, We're gonna raise money it'll be f I'll be raised money, it'll be fine and like everybody's like, What are we do what are you doing? For Archer. Yeah, everybody's like, What are you doing? We're not gonna find this. What are you talking about? How do you fight that inner monologue where everyone says you're stupid and wrong and this is silly, just go do software. It's coming from place of conviction.

50:12 Like I I know them, right, because I've been in the I've done the work. I understand it. I'm on the floor. Yeah, but the odds are still against you, right? But that's that's that that's the game. That's when you play this game, it's like you like sign up and like ninety five percent of everybody around you will fail. Like I remember what Veterans we like we 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 fifty companies that were there. Started in Soho.

50:36 Um 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 zero dollars.

50:47 When our c we're a team. Forty eight 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 twenty years now I've been watching around. You're like You see all the tech crun stuff and things on

51:02 X about people raising money all s and just like over time that all just kinda fades away. And it's just really brutal. Um So I had to like I had to like I you know I had to like I bought a house

51:13 And like I had to put all the rest of the money into Archer. And then I had like a stock lock up. So even while I was coming over to figure, like The like the stock was like unlocking. I was funding figure with stock from Archer'cause I had no other cash. Stock was coming down, the stock was just like literally like a

51:30 falling knife when at that point it was just 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, the D even Fund Figure.

51:43 We asked you one of your philosophies that you said Um I believe that doing hard things is easier in many ways than doing easier things. Can you explain? 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.

52:00 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. Do you have like just like you know risk reward trade.

52:10 Yeah, folks that probably want to work on hard things. Probably one like the best overachievers in the world that kinda wanna want to work there. Generally like you know, hard things have this like binary payoff for investments. They were like really want to fund those things'cause it could have like a Hundred X return for the portfolio. And I think there's like a nonlinear curve to scaling here, or we mean diff of of the difficulty here, meaning like I think a lot of the hard things are not like

52:31 Ten or hundred times harder. I think the hard things sometimes are like two or three or four times harder. May 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.

52:45 I think like largely building like quadruped robots, like four legged dog robots versus humanoids, like Probably human rights 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 cu for humanoid like Like those dogs.

52:59 I 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 really at this point like really wants to spend a lot of time on that. So like you do humanoids like okay three times harder, but it's probably like a a million times higher payoff. Probably a million X or billion X. Higher R

53:14 For that. You know what I mean? For investors, for humans that want to work there, get stock and participate in the upside and for everything else. Like wh why would you ever like Wanna work on like like four legged dogs. W what economic value can a 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.

53:33 And it just becomes really difficult. You know, 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 I don't think any of'em will make it long term. You might have some consolidation here and there for aqua hires and stuff, but like

53:47 That's gonna go all the way. Did you talk in so many absolutes, ha has that not gotten you in trouble ever? I don't know, I mean mark my words. Like like you think like I have you guys even used open claw since then? No, I don't know how to. Oh, do you use open claw? I I never I never trusted Open Claw to set it up. I was not a 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

54:15 Is it thing through what you're gonna actually go do? 'Cause you're gonna spend the next ten, fifteen years doing it. And it'll it'll like it'll map the whole course, the probability course. It's like a probability weighted of like or probability of like of like potential outcomes. Well, but you're you're you're p you're talking about a a very particular game. Like

54:33 Like, for example, uh you're as you 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 ten million dollar a year business, that's a massive home run.

54:55 Is it? With like if like if they can do that well and you look back when you're seventy or eighty, would they would you've asked the same person, hey You built a really cool five or ten million dollar business. You did it for thirty years. You didn't do anything else. You didn't try anything else while you're doing it. You just took work on that business. Would you have gone back thirty years ago and try to take a bigger swing. Would you have taken a different swing than Veter? Vetery was like that.

55:15 Veterans my bridge. I stand inside a vetery 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.

55:27 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 we 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

55:44 And I do think. Startups are like I think it is kinda binary. Even guys that can get the ten million dollars There's probably like another ninety percent 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 the guys getting like five or ten million.

55:58 In business. That's hard. Um, especially doing that if we maybe like a little bit of capital or no capital. 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. And uh

56:15 You know, unrelated spaces. So 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 more than most of the listeners. Can you give us Uh anything that you've seen or heard or read about I found a 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.

56:35 And we're just you know, not it's not evenly distributed for all the rest of us yet. I like I like looking at I I like trying to think through this problem of What was the world gonna look like in thirty years? Or is there where everything's headed? I think we have an energy problem.

56:48 Like not an energy consumption, like a generation problem. So how we B I mean both, but like oh ultimately how do we like j generate more energy? Uh as like a species. I think there's like a 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

57:06 Lot of work done correlating this to like So I think There's a lot of work here on like what is the next generation? Is it solar, is it wind, is it nuclear, like and then there's a bunch of different traits 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 there stopping that stuff.

57:25 I think AI is just gonna dominate A lot of stuff in the next ten or twenty years. for all of us here. I think it's gonna be like a hundred we all live through the internet, like I think it's gonna be a hundred times bigger than the internet. It gets me so, so big. It's gonna It's it's gonna AI's gonna eat the whole internet.

57:40 And uh I think it's gonna be a g extremely like large trend both physically and digitally. 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? I mean, we're working on this stuff at Hur Configure. Um

57:58 It's unclear. We're still in this spot where like it's really not clear who's gonna do well here and this stuff. We're in this like foggy area for a lot of these Stuff of which there's no 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

58:19 I mean, I've used like every AI device out there. Having been Super thrilled. Um I don't know if you guys are seeing stuff in the market.

58:28 for these type of things, but like I haven't like, you know, been like, Man, this is like a crazy great product. I like the small stuff. Like I like Whisper Whisper Flow has like pretty meaningfully changed how I communicate. Yeah. Um 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.

58:47 Because you're um You have very high standards. Who or What type of entrepreneur or 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?

59:04 I think I really admire the folks that are like fully dedicated in their craft. You like watch the Michael Jordan documentary, he's just like he's just like I just wanna be like the best in the world at this. I think for like for Startups have the same thing too. And I think first and foremost, like, you know, what I can read at evermess 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.

59:26 Um I've also got the note Jeff Bas was pretty well. He invested in figure and he's been here a lot of times and I think uh I think Justice. 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're

59:41 fairly close and I think Jensen's just an unblamable operator as well. He's very hands on has a very unique way of managing NVIDIA and his organization last thirty years and it's uh I I think he's like he's doing a lot of really good things. What advice did Jeff uh give you that was meaningful? Jeff said when last time he was here, he's like, Listen, you're at a really interesting period'cause like you've figured out how to do this somehow.

1:00:02 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 it's a really interesting point. I'm 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

1:00:22 push is gonna like m make or break it. So I think he's largely right. Like I think we're like We got robots not doing this stuff autonomously with AI models, which is crazy. I think four years ago you've been like I've been like, No way. Like no way you could. 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 was of the 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 dorsal flexion.

1:00:55 And we were just sitting around looking at this knee and that was like the coolest thing. I know. I mean 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 Oh pretty well all the joints go up. You know. It's it's unbel it's unbelievable. And uh

1:01:10 It's crazy it works. And um And w 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 it's um I know. I think those are kinda some like I think really good folks to look up to that really like like love their craft deeply.

1:01:24 Didn't really care. Well Brett? I think it's time for you to get back to work, my friend. Great. Thanks guys. It was good to see you again. Thank you so much, dude. Alright, that's it, that's the pod.

1:01:34 I feel like I can root Well I know. be what I want to I put my law in it like my day's off On the road less travel never looking back 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 Battel and Eric Sue. 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.

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