Brett Adcock, CEO of Figure

Brett Adcock is the Founder & CEO of Figure, the $39 billion company tackling one of the most ambitious challenges in technology — building a general-purpose humanoid robot that can do the work of a human, both on the factory floor and inside the home. About 50% of global GDP is human labor. In this episode of Sourcery, we go inside Figure's headquarters for a full tour and sit-down interview on the future of robotics, AI, and jobs. Brett shares why humanoid robots are already working today, how Figure plans to scale from thousands of units this year to 1 million per year, and why he believes this could become the biggest business in the world. Backed by nearly $2B across rounds — including investment from Jeff Bezos, Microsoft, Nvidia, and Amazon — Figure 15x'd its valuation to $39B in just 18 months. We also cover Brett's decision to part ways with OpenAI, the challenges of building physical intelligence, and what it takes to solve one of the hardest problems in engineering. We cover:• Why humanoid robots are finally real• The roadmap to millions of robots• Figure’s production ramp and demand• Why robotics is an intelligence problem• The OpenAI partnership — and breakup• The risks of building physical AI (Capital, Economics, Valuation)• Brett’s vision for general robotics If humanoids work, they will reshape the global economy. Brett Adcock: https://x.com/adcock_brett Molly O’Shea: https://x.com/MollySOShea Sourcery: ⁠https://x.com/sourceryy 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊𝐒 YouTube: https://youtu.be/g1ESjEGG1SM 𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒 • Brex https://brex.com/sourcery—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, & travel. https://brex.com/sourcery • Turing https://turing.com/sourcery—Turing delivers top-tier talent, data, and tools to help AI labs improve model performance—and enables enterprises to turn those models into powerful, production-ready systems. https://turing.com/sourcery•VCX https://fundrise.com/vcx—VCX is the public ticker for private tech, allowing investors of all sizes to invest in venture capital. View The Portfolio athttp://GetVCX.com http://getvcx.com • Deel https://www.deel.com/sourcery—Deel is the global people platform that helps startups hire, manage, pay, and equip anyone, anywhere. Trusted by more than 35,000 fast-growing companies, Deel is the people platform that just works, so teams can scale without the chaos. Visit: https://www.deel.com/sourcery • Public http://public.com/sourcery–Investing platform Public just launched Generated Assets https://public.com/generated-asset, which lets you turn any idea into an investable index with AI. With Generated Assets, you can build, backtest, refine, and invest in any thesis with AI. Gone are the days of one-size-fits-all ETFs. https://public.com/sourcery https://public.com/sourcery • Merge https://merge.dev—The leading provider of customer-facing integrations and agentic tools for frontier LLMs, Fortune 500 organizations, and B2B SaaS companies. Visit https://merge.dev Follow Sourcery for the latest updates! https://www.sourcery.vc/ Disclosure Paid Endorsement. Brokerage services by Open to the Public Investing Inc, member FINRA & SIPC. Advisory services by Public Advisors LLC, SEC-registered adviser. Crypto trading provided by Zero Hash LLC, licensed by the NYSDFS. Generated Assets is an interactive analysis tool by Public Advisors. Output is for informational purposes only and is not an investment recommendation or advice. See disclosures at public.com/disclosures/ga http://public.com/disclosures/ga. Matched funds must remain in your account for at least 5 years. Match rate and other terms are subject to change at any time. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Brett Adcock, Founder & CEO at Figure (01:13) Hot take on Humanoids (04:09) Race to a Million Robots (06:24) Building Figure From Scratch (08:15) Leaving Archer aviation (09:25) Post-IPO move (12:54) Cover, Hark & NASA's IP (16:06) How Figure Outgrew OpenAI (19:18) Founder performance playbook (24:24) Learning from Bezos and Jobs (29:19) Biggest risks to the business (31:26) Building the World's First Physical AGI

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

• 0:00Speaker 00

  The meta problem in robotics is be able to solve a humanoid robot. If you can solve this, it'll build the biggest business in the world by a large factor. A little under half the world's GDP is human labor.

• 0:08Molly O'Shea?

  You recently went viral for comments on your OpenAI partnership with Fingyr. What happened there?

• 0:14Speaker 00

  So, OpenAI led our Series B a couple of years ago. They brought in Satya and Microsoft. It got to a point where our team internally that was designing these models were running circles around OpenAI. We were just way better at this, so I fired them. I self-funded the whole company upfront. No, we got to a million a month of burn in four months. Getting the robots to do the things we showed you today has almost killed me. We had a record production in March, and we're gonna try to 3X that by May. We want to be able to get to a million units a year.

• 0:37Molly O'Shea?

  You've raised nearly $2 billion publicly, stated at $39 billion. Do you see capital as a risk or constraint, or the valuation as a risk?

• 0:48Speaker 00

  We'll just build like enormous of tens of trillions of revenue. We'll build something massive. I mean, what do most companies trade at? Tech companies trade at 10 or 20 times revenue. You're in like $10 trillion or, you know, whatever, $100 billion to $1 trillion in revs. Like, this is gonna be a huge business.

• 1:13Molly O'Shea?

  Brett, welcome to Sorcery.

• 1:15Speaker 00

  Thanks for having me.

• 1:16Molly O'Shea?

  I don't know if this is gonna be part one or part two, but this is a series now.

• 1:20Speaker 00

  Yeah, I agree.

• 1:22Molly O'Shea?

  We did the entire tour, and now we're gonna do a sit-down interview. I figured, uh, we recently went viral for a lot of these hot takes at Hillen Valley. And so I think that would be great if we just start there. So what is your hottest take right now?

• 1:37Speaker 00

  On, in robotics?

• 1:39Molly O'Shea?

  Yeah.

• 1:41Speaker 00

  Hot take.

• 1:44Speaker 00

  I think one thing that we spend a lot of time on is doing things with like fully autonomous and end-to-end. And you asked us a few questions, uh, here when we walked in of like, is this like teleoperated? We're not teleoperating this stuff. I think our hot take for robotics is this, it's like, it's kind of really difficult to see what's really happened in the space without coming on-site and really seeing stuff. So I hope, I, I hope you had a good experience here today, seeing everything we're doing. I think my, and I think the hottest take I have is like We just want humanoid robots to work and like they're working now. It's pretty simple. Like we're seeing robots to do everyday things like we saw it clean up a living room, do commercial work. Like it's just, it's cool to see it. Like it's cool to see that this is going to happen in the next few years.

• 2:30Molly O'Shea?

  This is a very hotly contested space and it's becoming more and more competitive. As it was funny because we did this interview with Skydio and he was talking about, Adam was talking about the drone cycles. There are drone cycles where there's hype cycles and that kind of thing. But humanoid robots are certainly at a different scale and pace than before. So how does this feel with the competition?

• 3:02Speaker 00

  I think like the, listen, our internal goal is like, how do we get these things to do real stuff and get paid for it? And so we think about how to do autonomous useful work. That's our bar. And we need to do that with like AI models really well. And we need to do it on good hardware. It's like, you know, cost effective, we can make a lot of it. We can make a lot of robots. You know, we think we're probably at this point, a few years ahead of everybody globally doing this at this level, which is like, we're kind of early in the humanoid, you know, book. And hopefully the next step is like, how do we get more robots out at scale? And we want to be first to be able to do that. How do we get, you know, hundreds and thousands and tens of thousands of robots in the world

• 3:46Speaker 00

  that run every day? And the space is just early. There's a lot of, we're just like, we're like in the first chapter of humanoids coming into society at scale. And yeah, what we're pumped about here internally is it's working and it's just chapter one. Chapter two is like get more out the door and get them working even like a bigger scale. And at some point, we want to really be able to generalize to do everything a human can.

• 4:09Molly O'Shea?

  How much do you want to produce a year? What's the goal?

• 4:13Speaker 00

  We'll make thousands of robots.

• 4:17Speaker 00

  Over the, like, here, like, basically as fast as we can this year. So we're ramping bot queue, like, lines up as fast as we can. We had a record production in March, and we're gonna try to three X that by May, and we'll build thousands of robots. We basically have, we already have the parts in-house to do this, and we're ramping up production. And then, you know, from there, we want to build tens of thousands and hundreds of thousands. And we are, you know, we want to be able to get to a million units a year. And then we need to commercial progress to also to match that. We have, like, so much commercial demand. It's like, it's hard to, we have, like, just overwhelmingly amount of, we could, I think I could, like, put, you know, so I put so, so many robots into commercial customers today if they were all ready.

• 5:02Speaker 00

  So the big gap is here is, like, getting the robots ready to do at-scale autonomous operations.

• 5:07Molly O'Shea?

  So the bottleneck right now for commercializing them is?

• 5:10Speaker 00

  It's having enough of them and making them run to a level of human performance at scale. Like, what we don't want to do is, like, we don't want to put, like, a thousand robots out to market and have, like, a thousand problems every single, like, hour.

• 5:22Molly O'Shea?

  Yeah.

• 5:22Speaker 00

  Uh, that's like, that's not good for any of us. Uh, so we had a small batch of robots that went out to BMW last year and did work every day. We ran for six months every single day. It was phenomenal. We learned a ton. Uh, we refactored our whole approach to how to commercialize the software and AI systems after that. And that kind of led us to Helix 2, which is our, like, second generation AI model internally, like, we launched a couple of months ago. And, um, uh, now it's like, uh, you know, how do we, like, put these robots into many different customers? That we'll, we'll probably announce a lot of this in the next, like, ninety days and put them out into those groups, uh, at, like, decent scale, like, this year. And assuming that goes well, we'll just keep, we'll just keep compounding that.

• 6:05Speaker 00

  So we, you know, we had robots there last year. That went well. We learned a lot. We'll have, like, a much larger amount of robots going into many different customers this year. And then six of them that goes well, we'll just, we'll keep scaling like crazy.

• 6:17Molly O'Shea?

  Are you worried about Optimus?

• 6:19Speaker 00

  In my mind, this is not a manufacturing problem. This is an intelligence problem.

• 6:24Molly O'Shea?

  You're almost four years old. How did you scale up this fast? What was the process like?

• 6:30Speaker 00

  Um, yeah, I've been building companies for like about 20 years now. Uh, scaled a software company up pretty fast, sold it, scaled Archer up pretty fast, took it public. And so, um, you know, every time, you know, I'm scale, I'm doing, I'm in this phase, I get this, I get to sit back and say, how do, what did I learn from past experiences and how do I do it better? And, um, you know, I figure we took a very differentiated approach to basically vertically design everything. I don't think there's any group in the world that I wouldn't think on the robotic side that makes, designs more parts than we do on the robot. We design the motors, basically every part within there, the rotor state or everything.

• 7:12Speaker 00

  Um, the sensors, the structure, the kinematics, the joints, uh, we like this, you know, the batteries that you saw today, the battery packs, that, that I think has really enabled us to like control our destiny. We get to like build our own supply chain. And, uh, without that, you're like left at the mercy of like some vendor. And then if that has an issue, like, well, how are you going to go solve it? If it's got a code problem, do you understand it? Can you QA it? Can you fix it? Can you patch it?

• 7:38Speaker 00

  So we understand the whole stack from top to bottom. There was enormous lift up front to get the right people here that could do that. And then we've now been iterating through, as you can see behind us, to a point where we like have like decently reliable systems now that run really well.

• 7:52Speaker 00

  But, you know, head on, I self-funded the whole company upfront. We got to, you know, we got to a million a month of burn in four months. It was like a no joke. We had the 40 person team in four or five months. They were like very good. And, um, and then just here, you know, a hundred hours a week, just trying to make it work with the team. And, um, we've, you know, we made a, we've made some mistakes. We've learned a lot. We've done some things well and just recursively getting better.

• 8:15Molly O'Shea?

  Why'd you leave Archer?

• 8:17Speaker 00

  The, the meta problem in robotics is be able to solve a humanoid robot. It's if you can solve this, it'll build the biggest business in the world by like a large factor. Half the world's GD, a little under half the world's GDP is human labor. I wanted to go work on building this, like this holy grail of robotics. Um, and Archer, I, you know, I led design for every aircraft we have there. Uh, and I feel, um,

• 8:43Speaker 00

  I feel like this is now the decade we're going to bring humanoid robots to the masses. It's the probably the most important, maybe one of the most important businesses of our lifetime. And so while I'm like a, you know, uh, yeah, so basically I get to, I get to, I get to spend time, I get to, you know, get to work now on like what I think is probably the, one of the more important areas of my whole career.

• 9:05Speaker 00

  In Archer, I built the, you know, built the whole team up, built like all the, led all engineering design for all the aircraft and led the company through a public offering like. So we were in a good, we're now in a good spot to certify the aircraft and enter like federal airspace. And, uh, and Figure is also in a good spot here to really scale up like physical intelligence of the world.

• 9:25Molly O'Shea?

  I recently had Michelle Delbuono from E16C Perennial, it's Mark and Ben's multifamily office. And we were talking through liquidity events and what you do as a founder for your first liquidity event, um, or second or third. Why did you decide after the IPO to start another company?

• 9:46Speaker 00

  Yeah.

• 9:47Molly O'Shea?

  And fund it?

• 9:48Speaker 00

  Yeah. Um, I've started a few other companies actually since then as well.

• 9:54Speaker 00

  I think the short story is I feel that.

• 9:58Speaker 00

  I've been watching the humanoid space for like a couple of decades. Like these, we've been like seeing humanoids for a long time. They've just been like the wrong, we're on the wrong vector. Like we were building the wrong stuff or we're doing it in a hobbyist grade or, you know, um. The engineering decisions were like, I think were not maybe correct. And I just, I felt there was a need to, uh, advance the space much more rapidly. And I'm doing the same with Hark and Cover. I have a couple of other companies I'm doing where I also feel this similar situation there where I feel like if.

• 10:28Speaker 00

  Left to the, the world to go do it, I'm unclear if like we would head to the right direction. And I think for humanoids, like, you know, the best we had four years ago was like a, you know, Boston Dynamics had a hydraulic humanoid called Atlas. It like dripped oils everywhere, lasted like 20 minutes. It was like very big, very unsafe. You could never put it next to humans. Uh, classical controls methodology there. And it was just like, man, you need to like, it's like a, you know, Boston Dynamics is really a large heritage around research, you know, not commercialization. Or not as much commercialization. So I just felt that there was a need for a group to come in to really like send this thing to the masses. And I felt without my intervention in the space, I don't, I don't know if we would have gotten there.

• 11:10Speaker 00

  Or maybe we will, we'll, we'll find out. But I think Figure has really shown that we've been able to kind of push the timelines left now in this chapter book to get to, to get, to get into the real world. And, um, and like I said, I think it's a significant business.

• 11:24Molly O'Shea?

  Sorcery is brought to you by Brex, the financial stack trusted by more than 30,000 companies, including one in three venture-backed startups in the U.S. Nearly 40% of startups fail because they run out of cash. Brex is literally built to help founders avoid that. Unlike traditional banks that let your money sit idle, chipping away at it with fees, Brex's designs help you spend smarter and move faster. Their all-in-one solution combines checking, treasury, and FDIC protection into one powerful account. You can send and receive money globally at lightning speeds, get 20 times the standard FDIC coverage through their partner banks, and even high yield from day one. With same-day and even same-hour liquidity, access your funds anytime.

• 12:09Molly O'Shea?

  Companies like Scale AI, DoorDash, ServiceTitan, Hims, Anthropic, Flexport, Robinhood, and Plaid. Trust and use Brex. Start today at brex.com/sorcery. That's B-R-E-X dot com slash sorcery. Turing is training the next generation of AI with tasks that require real expertise and real-world judgment. That's why companies like Nvidia, Anthropic, Salesforce, and Gemini partner with Turing. Turing builds realistic reinforcement learning environments and data systems based on real operational traces, the kind of infrastructure Frontier Labs need to train superintelligence. Visit turing.com/sorcery.

• 12:54Molly O'Shea?

  How do you have time to also work on Harken cover?

• 12:56Speaker 00

  The trick is just not sleep.

• 12:59Molly O'Shea?

  Do you have an eight sleep or you just don't sleep?

• 13:02Speaker 00

  You just don't sleep.

• 13:05Speaker 00

  Okay, listen, I like.

• 13:07Molly O'Shea?

  Also, explain what those companies do for people.

• 13:09Speaker 00

  Okay, so. So Cover is basically designing like detection systems for K through 12 schools. So school shootings in the US have gone up 10x last 10 years. And just like this is like actual like a weapon's been fired. And it's it's it's just like basically got fully on hand. My view is that it's a perception problem. We need to see if people have guns, like kids or students have guns on them when they're entering schools. If they do, like it's getting off the students. If they don't, it's those students go in. There's a technology that was designed at NASA Jet Propulsion Lab about a decade ago. That it can detect weapons underneath clothes and in backpacks and bags from like. 10, 20, you know, 5, 10, 20 meters away.

• 13:53Speaker 00

  And they built it for the Iraq Afghanistan war to find like bomb vests and other explosives and stuff on folks. From a standoff distance. So think about this like a. Like a technology similar to like the L3 like scanning systems at an airport, but you can only do that from a few feet away. But if you do that 10x further away, you could just basically scan everybody as they're coming in schools. And it's not just a school thing. You can use it at every public venue in the world. And. It's been all my passion. I've been like following the space in here like this is like a. The the nerdy topic here is called Terahertz Imaging Radar. And that's what we do here at Cover. And so I have a team, most of which are from NASA's Jet Propulsion Lab. So one is I own the IP from NASA's Jet Propulsion Lab. I spun it out two years ago and I'm funding this project.

• 14:36Molly O'Shea?

  Oh.

• 14:37Speaker 00

  Yeah.

• 14:37Molly O'Shea?

  How did you get it?

• 14:38Speaker 00

  I bought it.

• 14:38Molly O'Shea?

  Oh.

• 14:39Speaker 00

  They they'll sell it to you. Yeah. So they sold it to me.

• 14:43Molly O'Shea?

  100% you own it?

• 14:44Speaker 00

  I own it, yeah.

• 14:45Molly O'Shea?

  Okay.

• 14:46Speaker 00

  And then Caltech, which is like, you know, NASA, basically, JPL, has a small, very small minority interest in the business. Yeah. And then a lot of the core team that did that is on my team now at Cover. And it's awesome, like the images we get, it's like, it's like, it's like a hardware and AI problem. It's like a vision problem that you have to solve with AI. And we have prototypes now in, in, like, that are running now. Um, and we will deploy hopefully to our first schools in beta by end of year. And we wanted to deploy, and there's a hundred thirty thousand K through twelve schools. There's like a huge amount we have to manufacture and get out the door. So I've been self-funding that company for two years. Uh, we're making incredible progress. And, uh, I have a team in Pasadena, right next to Jet Propulsion Lab in LA. And they're funding that. So, um, and then I have a separate company called Hark.

• 15:31Speaker 00

  It's an AI lab I started about seven, eight months ago. It's trying to design like really highly personalized and, uh, intelligence. So we're designing next generation AI models and also, um, the next generation of AI devices. Uh, to interact with AI. Like right now, we interact with AI through like twenty year old computers, like phones and MacBooks and stuff like that. And they're just, they're not the ideal, like intermediary and interface to AI. So, um, so we just came out of stealth like two weeks ago. And we have a team of fifty and we're building like, we're building really awesome magical AI models and we're building really magical hardware.

• 16:06Molly O'Shea?

  You recently went viral for comments on your OpenAI partnership with Figure. What happened there?

• 16:14Speaker 00

  Yeah.

• 16:16Speaker 00

  So OpenAI led our, led my series B a couple of years ago. And as a part of that, we did a collaboration agreement to work on like next generation AI models together.

• 16:27Speaker 00

  And, uh, you know, it's great, like something like, uh, got to know the team really well over there. Sam and the rest of the group and, you know, they, they led her around. They brought in Satya and Microsoft, they co-led it. And, um, and then we spent basically a year like collaborating together on like, how do we get AI models to work on a humanoid? Or how do we get like language models to work on a humanoid? And, um, they were very interested in robotics and, uh, we were very interested in like, uh, like understanding, uh, better about how do we get like language? Like, like language models on robots, like what, what, like, what part do they play or do they play a part in robotics? And so we spent a year working with them.

• 17:04Speaker 00

  But ni- nice folks, like, um, you know, I was in the, I was like working with them for, you know, almost every, like every day, every week. And it, it got to a point where we were just like, our team internally that was designing these models were, were running circles around OpenAI. We were just way better at this. And, um,

• 17:23Speaker 00

  We were better about testing on the robots, training the models, like all of it. My team had come from robot learning backgrounds for over a decade. And I think there was also like some interest as OpenAI was watching us getting into robotics. And so I fired him.

• 17:40Molly O'Shea?

  Why did you let them invest in the first place?

• 17:43Speaker 00

  I got to know Sam well and the team. And I thought there could be like a lot of potential strategic interests from both of us. Like of how to develop some of these systems and learn from each other. And it turned out I was kind of wrong on that. Yeah.

• 18:00Molly O'Shea?

  Is that when, or even before that, when you started to become more secure here? Because even coming in, my phone is covered.

• 18:08Speaker 00

  Yeah.

• 18:09Molly O'Shea?

  You know, there's restricted areas. It's very close on IP. Like what is?

• 18:14Speaker 00

  We've always been pretty secure. I think what we're doing is like a very high IP risk. So we really think about carefully about our like engineering CAD and software, like making sure it's like very secure from a, you know, cybersecurity perspective and internal security perspective. And then our office is like really open. You can like see a lot of stuff when you're coming here. Yeah. So we used to have people come in and just like snap photos randomly. Like, whoa, that's like, not okay. Like, I'm like, you know, I like hardware or something in front of the person. And so we like.

• 18:39Molly O'Shea?

  We're in the Bay Area and there's a lot of honeypots and spines.

• 18:43Speaker 00

  One day we're like looking up and we're like, it was in this office. And we look at the corner of the window at the top, there's like a drone sitting there.

• 18:49Molly O'Shea?

  No.

• 18:50Speaker 00

  Looking in the office, like right over here.

• 18:52Molly O'Shea?

  Really?

• 18:52Speaker 00

  Main area. Yeah. We're like, oh my gosh, we've got to like change some things here.

• 18:55Molly O'Shea?

  Did you find out who that was?

• 18:56Speaker 00

  We didn't find out who it was, but we like, we tinted all the, all the glass. Like we have like, we have a really strict security, both physical and digital now. I mean, we're designing some crazy stuff, so we want to protect it at all costs here. But no, we've, we've, we've kind of always been like this. A little, a little paranoid, which always helps.

• 19:15Molly O'Shea?

  Typical founder trait.

• 19:16Speaker 00

  Yeah, exactly.

• 19:18Molly O'Shea?

  Speaking of that, so one of our sponsors is Brex and they're about performance, spending smarter, moving faster. I'm curious from your standpoint, as a leader, how do you maintain your performance? Whether it's like mental or like team leadership wise?

• 19:36Speaker 00

  Yeah. You asked before, like, how do I have time to do all this stuff?

• 19:38Molly O'Shea?

  Yeah.

• 19:40Speaker 00

  You know, I think like I always had like these three pockets of time in my life. I feel like I have like my family. I have like work and I have like, you know, you have like things you do with like friends and people you know. Like whatever annual trip with friends or golf or whatever else it is from college. About like, you know, when I was at Archer, I got to a point where I was like, man, I don't only have time to do all three anymore. So I decided like five years ago to like stop doing like the annual golf trip. And stop doing like this person's in town I haven't seen in 10 years. We need to go out to dinner. I just don't do that anymore. It's been all my time with family or my companies. That's all I do. And it's it's it's kind of nice. It's like the stuff I really care about and I get to kind of go all in on it and do a really good job. So here I'm like, I was at the office last night till like midnight, but like I I come home every night to have dinner with my kids.

• 20:26Speaker 00

  So I'm at home by six and I do dinner and do bedtime and then come back in if I need to or stay home depending on what's going on, but usually it's back to work.

• 20:34Speaker 00

  And just make sure I get the like, make sure I unblock the most pernicious problems of these companies and help help scale.

• 20:41Speaker 00

  So anyway, I think from a time perspective, uh, yeah, I kind of have to be very thoughtful about about what I do. When I'm even in the office now, I had to be really thoughtful about spending my time on. So what I've learned over the time, you you asked when you when you came here is like, do you have like the corner office? Or do you have like a, you're in the, you know?

• 20:59Molly O'Shea?

  The bullpen.

• 20:59Speaker 00

  The bullpen. Man, I have like a, uh, so I, you know, one day after we took the, I took Archer public, I woke up one day. And I was like, I feel like it was in this Groundhog movie where I was like in this conference room with all my C suite and was in there like every day.

• 21:16Speaker 00

  And, you know, usually I'm like on the floor with product engineering, helping to build, build aircraft, designing. I was just like stuck. And I was stuck in like two day a quarter board meetings and analyst callbacks and talking about, you know, my CHRO or GC and all these different things. And I was like, this is just something's wrong here. I mean, it's like elite office over here, like looking down at everybody, like not doing real work on the ground. And, um, you know, I made a decision kind of around that time to like just basically remove everything on my plate, just spend time on like product engineering. So I do a few things like you're like the first person that's actually seen the whole office like this.

• 21:55Molly O'Shea?

  Wow.

• 21:55Speaker 00

  Which is cool. We don't do a lot of these and I love your show. So it's like great to have you here and give a sneak peek to the world on like what we're doing.

• 22:01Molly O'Shea?

  Thank you.

• 22:02Speaker 00

  Yeah. And then the rest of my time is on like, how do I like work on product engineering? How do I advance the humanoid to do better things? Or how do I make cover system out to the world? We need to start testing it and getting feedback. And how do we get hard models and devices out to the world at scale? Like those are the things I think really matter. Matters less about like doing traditional PR and you know, like going to like trade shows and you know, sitting on like these like panels and stuff. None of this matters.

• 22:28Molly O'Shea?

  Yeah.

• 22:29Speaker 00

  It's not real. So, so I try to spend my time in the bullpen and then I try to like maximize my time both when I'm in or out of the office on things that are important.

• 22:38Molly O'Shea?

  V C X by Fundrise, the public ticker for private tech, allowing investors of all sizes to invest in venture capital. View the portfolio at getvcx.com. That's getvcx.com. Some of you may not have heard this yet, but our sponsor Public just launched something called Generated Assets and it brings AI into investing in a way I've honestly never seen before. Here's how it works. You type in an idea like AI-powered supply chain companies with positive free cash flow or defense tech companies growing revenue over 25% year over year. Public's AI then dispatches a swarm of agents that scan every single US stock, evaluates them and instantly builds a custom index around your thesis.

• 23:20Molly O'Shea?

  What really stands out is how clearly it explains why each stock is included. And before you invest, you can even backtest your idea against the S and P 500. So you're making decisions with real context, not just guessing. And beyond Generated Assets, Public lets you invest in stocks, bonds, options, crypto, all in one place. They'll even give you an uncapped 1% match when you transfer your investments over from another platform. If you want to build a portfolio that actually reflects your thesis, visit public.com/sorcery. Paid for by Public Investing. Full disclosures in the description. Enterprise AI runs on Merge, the AI infra platform for integrations, agent tooling and model orchestration. So your team Teams ship product, not plumbing. Mistral, Dropbox, and Drata already trust Merge in production.

• 24:06Molly O'Shea?

  Start building at merge.dev. Founders scale faster on Deal. Set up payroll for any country in minutes. Hire anyone, anywhere. Get visas handled fast and get back to building. Visit deal.com/sorcery. That's D E E L dot com slash sorcery. You mentioned a bit of inspiration on ideas around coming from sci fi. But on the leadership standpoint, like, who are people that you admire or have looked up to that like, help carry you forward and keep you motivated?

• 24:39Speaker 00

  Yeah, I was, I mean, kind of like a generation behind like Steve Jobs and that whole, you know, crew. Like Jeff Bezos, which is a big investor for us at Figured. You know, I get, I get to basically have access to and talk with. And, um, you know, for me, like, I want to play the game like 11 out of 10. I want to go really hard at this. Like, so we're really serious. I'm pretty competitive a person. So if I'm going to do this and like sacrifice my life to do this in my time, I, I, I just want to nail it. I want to win and I want to do, uh, I want to do everything to the most hardcore level possible. And, um, so I think the folks I looked up to of the world are the folks that have done that. Have been successful, but have like really devoted their time to being, um, kind of best athlete in those situations.

• 25:23Speaker 00

  So, uh, yeah, and I'm looking at myself here. Like, how do I make these companies work? There's just nothing worse than like 10, 15, 20 years from now, these things aren't working. Like, well, I, I, like, I missed all my golf trips. You know what I mean? I've missed like time with the family. It's just like, I just missed all the stuff in my life. And I, at this point, I have plenty of money. So it's like, um, I'm doing this because I love it and I better be getting better at it. And, you know, recursively improving. And I think I look up to the folks like that that have done that through their time. If you look at like Steve and Jeff and some of these groups that are kind of a generation above me. They, they've been good at many things in their life across many different areas. And, um, they've also too devoted their life to doing this and have been a good source of inspiration.

• 26:07Speaker 00

  Um, and it's been hard and they've done it over decades. The stuff is like not, the stuff is just happen overnight. I've been, I've been doing like 20 years now doing all this stuff and I feel like I'm just starting.

• 26:18Molly O'Shea?

  What are the biggest risks to the business?

• 26:21Speaker 00

  The humanoid thing is just so hard. Um, I can't like even explain it very well. It's uh, getting the robots to do the things we showed you today. It's been like, it's almost killed me. And we have such an uphill battle to go do that. Same with Archer, we have to fly aircraft every day above cities and make it really safe. And it's like one of the safest transportations you have. So the stuff, the stuff I'm working through is just like, um, like if you look at the odds of, of, of these things, you know, working, they're like super low. And I think that's probably pretty accurate. So, um, I basically have like a, I basically have a funnel of the hardest, most pernicious problems I have to go solve every day.

• 27:07Speaker 00

  And they're like, they're really, really tough. I, um, so like my biggest risk, there's like a list of risk lists, like a very long list of risks. And things that could hurt, like things that could like make us not make it. Um, the figure, the most important thing is to be able to do end to end useful work over a long time horizon. I want to be able to put a robot into a home and be able to do like seven to 10 hours of work successfully without failures. With like to know, with no human intervention and do that every day forever. It's just like a hard problem. Nobody's ever shown that. The robot's very complicated. It's like designed like a turbofan or a rocket. Like an aircraft from scratch.

• 27:51Speaker 00

  It's just like a very difficult thing that we've also designed the entire supply chain from scratch. So it's like, it's got a ton of problems, you know, it doesn't work the first time. We're working those problems out. Like we used to run that robot here, figure, figure one. And man, that robot could like run for like an hour. And it would like fault. We know all the reasons or it'd fall. Or would like, you know, lose power. And, you know, we moved to figure two. I think we probably like, maybe we saw that like once a day. And now figure three, like I think, you know, everywhere here, they're all running all, all day. And we'll see faults, we'll see faults every week. Not on every single robot, we'll see faults. And we have a list of those and we're working those down. Uh, but it's really hard.

• 28:34Speaker 00

  And as we're growing the fleet, the absolute number of faults are rising and we gotta go figure out how to solve those. Cause like you said before, like the amount of states the robot can be in is so high. So you can't really reasonably predict what the robot's gonna like, look like at every single timestamp everywhere in the world. You kinda can for a car. It's like, kinda you can just drive on roads. It's a hard problem too. So like, um. Anyway, I think what I'm trying to say is like, we have like a fun house of problems and it's like never ending problem city for the company. Um, we have to be able to manufacture unprecedented rates. We gotta get humanoid robots to work autonomously without human intervention. Nobody's ever shown that. We have to make it work with like AI policies. The hardware can't fail. It's gonna be really affordable and we gotta make a lot of them. And we gotta get consumers to want them.

• 29:19Molly O'Shea?

  That's a lot. And you've raised nearly $2 billion. I think most recently publicly stated at $39 billion. Do you see capital as a risk or constraint or the valuation as a risker?

• 29:35Speaker 00

  This will build like the biggest business in the world, like half of, like little under half of GDP is human labor in the commercial market. Like they pay wages for humans. We, we do human work. So you're looking at, we will have the ability to ship, if the robots work well, billions of robots in the commercial workforce. Uh, you'll produce, you know, there's like 30 trillion, 40 trillion of wages paid to, like every year to that. To like, to, to, for, to folks that be doing that work. We'll be able to expand that work, automate more, like a lot of it and continue to scale it up. I think like that plus the stuff we're seeing in the home. We'll just build like enormous of tens of trillions of revenue. We'll build something massive.

• 30:19Speaker 00

  I mean, what do most companies trade at? Tech companies trade at 10 or 20 times revenue. You're in like $10 trillion or? You know, whenever a hundred billion dollars to a trillion dollars arrives, like this is gonna be a huge business.

• 30:31Molly O'Shea?

  Do you have plans for the moon or Mars?

• 30:34Speaker 00

  We'd love to send robots into space. Yeah. Let's get them out there.

• 30:41Molly O'Shea?

  Okay.

• 30:41Speaker 00

  I have a gift for you.

• 30:42Molly O'Shea?

  You do?

• 30:43Speaker 00

  I do.

• 30:43Molly O'Shea?

  What is it?

• 30:44Speaker 00

  I have some figure-

• 30:44Molly O'Shea?

  Is it a mini robot?

• 30:45Speaker 00

  I have some figure swag. So-

• 30:48Molly O'Shea?

  Thank you.

• 30:48Speaker 00

  Yeah, some hats, shirts. So you can rep the figure brand here.

• 30:51Molly O'Shea?

  Oh, this is a lot of merch.

• 30:53Speaker 00

  Lot of merch.

• 30:54Molly O'Shea?

  Wow, I'm gonna have to get a new closet.

• 30:58Molly O'Shea?

  This is great. It was funny, I don't think they caught this when we were recording the the tour, but I asked you how you made the logo and you said it was the robot's steps.

• 31:10Speaker 00

  Yeah, basically the robot takes footsteps like this. Even in simulation, they look like little squares. Uh, so you have like a little, uh, like kind of a walk, a walk. And then you also have a kind of an F, abstract F.

• 31:20Molly O'Shea?

  Not really.

• 31:24Speaker 00

  Okay, well, we'll keep the walk.

• 31:25Molly O'Shea?

  Okay. Well, as we wrap up, what are you most looking forward to for this next year?

• 31:33Speaker 00

  For this year, I wanna ship robots at scale out to the world. And the second thing I wanna solve is I wanna solve, there's like, uh, we have like an extreme focus here to solve like what I call general robotics. Like a robot that can do everything a human can. I think like almost like a feeling of like a human in a body suit. You can talk to, can look at you, reason, have visual understanding. And you can drop into any place and like kind of just like look around, reason and understand. Uh, we wanna solve that problem. And that's a, it's a Helix problem for us. And, um, so we have a huge focus to get robots out the door. We have a huge focus to solve general robotics here. I want this to be the first place where we see, uh, CAGI in the physical world. And, uh, we think we have the recipe. And, uh, we think we have like the right, um,

• 32:19Speaker 00

  training processes in place to do this. We, uh, and this will be an important, this year and next will be important to see if we can practice.

• 32:27Molly O'Shea?

  Exciting. Well, thank you so much for the full day here, the entire tour of the whole campus and the thoughtful discussion.

• 32:34Speaker 00

  Thank you. It was great to have you.

• 32:36Molly O'Shea?

  Hey, it's Molly. If you enjoy our interviews, check out our newsletter, sorcery.vc, where we deliver a once a week top deals and tech headlines email and also go deeper on our podcast interviews. Subscribe to Sorcery today. Don't forget to subscribe to the podcast on YouTube, Spotify, Apple, or wherever you listen. Link in description to sign up.