# The Breakthrough For Home Robots with Kyle Vogt, CEO of the Bot Company | Ep. 32 Markdown copy of https://realalpha.app/v/XQoFbvyWEy8/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy. Kyle Vogt argues that AI is making useful home robots possible, and that affordable, specialized machines will reach people before humanoids. - Show: Uncapped - Hosts: [Jack Altman](https://realalpha.app/people/jack-altman/) - Guest: [Kyle Vogt](https://realalpha.app/builders/kyle-vogt/) is CEO of the Bot Company. - Published: Nov 12, 2025 - Length: 46 min ## The best minutes - [0:32](https://realalpha.app/v/XQoFbvyWEy8/?t=32) [Language models are changing what robots can understand](https://realalpha.app/s/language-models-are-changing-what-robots-can-understand/) (5 min) - [22:32](https://realalpha.app/v/XQoFbvyWEy8/?t=1352) [A 100-person cap can preserve a startup’s output](https://realalpha.app/s/a-100-person-cap-can-preserve-a-startups-output/) (4 min) - [27:19](https://realalpha.app/v/XQoFbvyWEy8/?t=1639) [Home robots should start with forgiving tasks](https://realalpha.app/s/home-robots-should-start-with-forgiving-tasks/) (4 min) ## Also worth watching - [8:53](https://realalpha.app/v/XQoFbvyWEy8/?t=533) [Affordable robots can build a data flywheel](https://realalpha.app/s/affordable-robots-can-build-a-data-flywheel/) (3 min) - [12:05](https://realalpha.app/v/XQoFbvyWEy8/?t=725) [Humanoids make sense only when their flexibility pays off](https://realalpha.app/s/humanoids-make-sense-only-when-their-flexibility-pays-off/) (3 min) - [15:02](https://realalpha.app/v/XQoFbvyWEy8/?t=902) [Home robots need user control over collected data](https://realalpha.app/s/home-robots-need-user-control-over-collected-data/) (3 min) - [17:54](https://realalpha.app/v/XQoFbvyWEy8/?t=1074) [Robotics companies still lack an internet-scale training corpus](https://realalpha.app/s/robotics-companies-still-lack-an-internet-scale-training/) (3 min) - [38:33](https://realalpha.app/v/XQoFbvyWEy8/?t=2313) [Revenue during development can reduce reliance on capital markets](https://realalpha.app/s/revenue-during-development-can-reduce-reliance-on-capital/) (2 min) Skip the career-motivation discussion, hand and actuator design, home-security applications, and the marathon's planning and logistics. ## Full analysis: Kyle Vogt says home robots could cook steak in under five years - Kyle Vogt says a home robot could cook steak in under five years. - But the forecast rests on broader bets, and the episode gives no reliability or product-price data. - Watch whether forgiving chores, owner controls and early revenue make deployment repeatable. Its 6 sections, what it means for you and what to watch are on [the page](https://realalpha.app/v/XQoFbvyWEy8/#analysis), free with an account: - [1:48](https://realalpha.app/v/XQoFbvyWEy8/?t=108) Language models remove two old robotics bottlenecks - [13:19](https://realalpha.app/v/XQoFbvyWEy8/?t=799) Specialized robots may beat humanoids on cost - [0:26](https://realalpha.app/v/XQoFbvyWEy8/?t=26) Forgiving jobs make early robot forecasts testable - [11:55](https://realalpha.app/v/XQoFbvyWEy8/?t=715) Affordable deployments could supply missing robot data - [17:16](https://realalpha.app/v/XQoFbvyWEy8/?t=1036) Home adoption depends on controls owners can verify - [40:33](https://realalpha.app/v/XQoFbvyWEy8/?t=2433) Vogt ties startup survival to shipping and revenue ## Summary Kyle Vogt is a serial entrepreneur and engineer who co-founded Twitch and Cruise and served as Cruise's CEO. General Motors acquired Cruise for $1 billion. He is now building the Bot Company, focused on intelligent home automation. Kyle Vogt says advances in language models and neural networks give robots new ways to understand their surroundings and learn movement, opening the door to many specialized machines. He argues that home robots should prioritize affordability, safety, privacy and tasks where users can tolerate occasional mistakes, then expand to more demanding jobs. Vogt expects data from deployed robots to improve the technology and says small, high-output teams should focus on shipping and solving bottlenecks. He also discusses how to fund robotics businesses, when a founder should sell, and his seven-continent marathon challenge. ### Minute by minute - [0:24](https://realalpha.app/v/XQoFbvyWEy8/?t=24) **Neural networks change robotics.** Vogt says robots were historically fragile and depended on carefully mapped environments and hand-engineered perception and motion. He argues that language-model knowledge and neural-network control, trained through teleoperation or simulation, change what robots can do and could enable a wide range of applications. - [5:28](https://realalpha.app/v/XQoFbvyWEy8/?t=328) **Home robots must fit real life.** Vogt says home robots need to navigate, remember where things are, manipulate objects and account for user preferences. He expects the technology to advance faster than people adapt their homes and routines, so builders should help make adoption straightforward while testing and revising their product ideas. - [8:53](https://realalpha.app/v/XQoFbvyWEy8/?t=533) **Affordability can drive adoption.** Vogt chose home robotics because he wants to build something people he knows can use and see users benefit directly, as he did with Twitch. For early products, he favors reducing cost over adding capabilities: lower prices could bring in more users and create a feedback loop as robots generate real-world data. - [12:14](https://realalpha.app/v/XQoFbvyWEy8/?t=734) **Most robots will be specialized.** Vogt says humanoids are impressive but that simpler machines will usually deliver more value for a specific job. He sees fall risks as a concern for humanoids in homes, though ladders and human-designed tools could make them useful on construction sites. He says developers should prioritize safety and give users transparency and control over home data. - [17:54](https://realalpha.app/v/XQoFbvyWEy8/?t=1074) **Robotics needs its own data.** Vogt says robotics shares training approaches with language models, but needs real-world data and ways to connect it with simulation. Unlike language models, robotics has no internet-scale dataset of robots manipulating objects, so companies must gather or infer data. He expects deployed robots to supply most of it as useful machines enter the world. - [20:55](https://realalpha.app/v/XQoFbvyWEy8/?t=1255) **Small teams protect focus.** Vogt says solving hard problems with smart people is what motivates him to start another company. He is taking a 100-person limit seriously because he wants to preserve the high-output, closely aligned feel of a small team. He says a small company should partner on work outside its core strengths. - [26:02](https://realalpha.app/v/XQoFbvyWEy8/?t=1562) **Start with forgiving tasks.** Vogt says companies should identify their main bottlenecks and make progress against clear metrics. For home robots, he weighs technical difficulty against how much failure a customer will tolerate: toys can be left behind, but breaking a wine glass may lose a customer. He expects tasks to progress toward cooking, and says a robot could cook a steak and clean up in less than five years. - [32:26](https://realalpha.app/v/XQoFbvyWEy8/?t=1946) **Robot hands balance trade-offs.** Vogt says a robot's hand is its interface with objects: more joints and sensing can make tasks easier, but add cost, complexity and durability risks. He questions whether human-like hands and arms are the best design and suggests a flexible, tentacle-like form could prove useful. He says new muscle-like actuators may eventually offer quieter operation and more power density than gear motors. - [35:06](https://realalpha.app/v/XQoFbvyWEy8/?t=2106) **Home robots could improve daily life.** Vogt says a home robot could check whether the stove is off or alert its owner to an open door, though he expects monitoring rather than physical intervention. He also wants robots to do more than chores: they could handle small touches that make a home feel more comfortable and give people time back. - [38:33](https://realalpha.app/v/XQoFbvyWEy8/?t=2313) **Revenue can reduce funding risk.** Vogt contrasts Tesla selling a self-driving product before it was complete, which he says generated cash for further research, with Waymo's large investment and more limited revenue relative to it. He hopes home robotics companies can find ways to reach meaningful revenue sooner instead of depending on a corporate benefactor or capital markets. - [40:49](https://realalpha.app/v/XQoFbvyWEy8/?t=2449) **Sell only when the thesis changes.** Vogt says a founder should sell when the original reason for starting the company or the founder's circumstances have changed. He doubts that selling usually lets a founder keep control and advance the mission, and says he wants to retain the ability to build the Bot Company's product while remaining accountable to investors and employees. - [42:35](https://realalpha.app/v/XQoFbvyWEy8/?t=2555) **The marathon challenge took 18 months.** Vogt says he turned to running because progress at Cruise could fluctuate, while training gave him a more direct link between effort and improvement. He spent 18 months planning and training, then ran a marathon on each continent in about three and a half days, beating the world record. ## Transcript Uncapped, hosted by Jack Altman, with Kyle Vogt. Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there. [0:00](https://realalpha.app/v/XQoFbvyWEy8/?t=0) You think it's like cooking a steak at some point? Yeah, why not? If you think about at the end of the day, you have pick and place and simple manipulation. That's what cooking is. They're just like a much higher degree of reliability. And there's other things around food safety and bacteria and other things that come in cooking and temperature sensing and what like that. So it's all doable. It's just like, I would not stop there. So you think at some point it's like, hey, robot, I'm at work right now. There's a steak in the fridge. Please cook it and clean up everything. By the time of like 15 years from now, that's doable. [0:26](https://realalpha.app/v/XQoFbvyWEy8/?t=26) Less than five. Less than five? Yeah. All right. I'm really pumped to be here with Kyle Vogt. Kyle, thanks a ton for making time for this. Thanks for having me. So I want to start with talking about like why robotics seems to be having such a moment. You know, it's obviously been really important for a long time, but in the last few years, it seems like a lot of really good entrepreneurs, a lot of good investors have started to pour a bunch of time, money, resources, and effort into this. And I guess I'm curious just to start with sort of laying a foundation of like, can you put this in some context and like what used to be the case and what has changed that's like making people so energized right now? [0:57](https://realalpha.app/v/XQoFbvyWEy8/?t=57) Yeah, it is. It's like the most excited I've ever seen people in robotics. And, you know, I guess as an engineer, there's something like romantic about building machines to do the stuff that we don't want to do. And that's why I've been doing this for so long. First with, you know, a decade on self-driving cars. But for me, even going back to like teenage years doing BattleBots and then going to MIT to basically build more robots. but you know during that entire spectrum it's also it's always been this niche thing and frankly like robots have never really lived up to their promise there's always something they're always overly fragile like in a factory environment we put them in cages and if things don't line up like within a millimeter the whole thing doesn't work except the battle bots those were good actually battle bots were yeah you made them with like the saws and everything ours had like a hydraulic axe which was which was pretty cool but the calling these robots is a bit of a stretch they're basically glorified rc cars yeah right with a weapon yeah so so with a weapon what's different now is you know for the first time you have robots that are powered by essentially they have all the brains of an llm built into this robot and we're controlling them with neural [1:59](https://realalpha.app/v/XQoFbvyWEy8/?t=119) networks instead of classically engineered algorithms and so the difference was before if you have a robot that's like in a room like this uh even saying like go to the whiteboard is almost like an impossibly hard computer science problem it's like okay i have to build an exact 3D map of the world, have a detector that can figure out what a whiteboard is, train it on millions of examples of what whiteboards look like just to be able to do this. And even then, the failure rate would be high if you put it in a different room and it doesn't have a map. [2:26](https://realalpha.app/v/XQoFbvyWEy8/?t=146) **Kyle Vogt:** But now it's almost like cheating. You can take all the common sense that's on the internet and inject it into a robot brain. And so if you're like, where's the whiteboard? It knows instantly. [2:34](https://realalpha.app/v/XQoFbvyWEy8/?t=154) You open the chat GPT. If you open video, you can show it anything and it knows what it is. Yeah. And so imagine robots before started with zero knowledge of the world, and now like suddenly have this kind of knowledge of the world. Like better than us. Like they can look around the room and see stuff better than we can. Yeah. And then on the motion side, you used to have to have a PhD to compute these complex trajectories. You have like 12 joints on a motor or on a robot. How do you get all 12 joints to move in tight coordination to like move an arm to a place? And this is a very difficult and computationally intensive problem. [3:04](https://realalpha.app/v/XQoFbvyWEy8/?t=184) And now we just kind of jump over that whole thing. And now if you have a way to teleoperate a robot or to put it in a simulation, you can just learn how to move all those joints to mimic the human operator or to accomplish, you know, some reward function or to maximize it. And so you can skip that whole computational challenge. And so those two things together basically mean that everything we thought we knew about robotics or like what kind of businesses were good businesses or bad businesses, all like that slate has been wiped clean. And so I think you're going to see this Cambrian explosion of different robots for different applications that now suddenly just work. Whereas before they were like really struggled to do the most basic things and when you say for different applications is that are you saying it won't be terribly generalized will it be medium generalized like what made you say for different applications or like different environments maybe yeah i mean classically like a lot of robot businesses like try to really get really really narrow the successful ones we're going to focus on this one problem like factory automation for 3pls for putting things in box at the box. [3:59](https://realalpha.app/v/XQoFbvyWEy8/?t=239) and putting them on a conveyor belt, like very specific. And that's just so you could narrow the problem enough to be good at it. Now, I think you're going to see people broaden the horizons a little bit because it's much, much easier to go from, you know, a piece of dumb hardware to something that's performing a useful task. You know, I say multiple applications too, because it's my view that there's going to be a whole bunch of different shapes and sizes of robots, each optimized for different types of work. You know, as opposed to maybe like a humanoid robot, which, you know, is very, very expensive, but in theory can do everything. [4:26](https://realalpha.app/v/XQoFbvyWEy8/?t=266) I think we're probably going to see some of those, But the vast majority of robots will be more special purpose in nature. I feel like there was a moment in AI where the researchers who were sort of closest to the work were like very sure it was going to work before the rest of the world sort of knew. Is there an equivalent thing in robotic? Like have people crossed a similar threshold to like whatever that was, like the pre-Chat GPT moment in robotics where like some people who are at the very front have been working on it for decades are like, this is definitely happening now. Yeah, if you had like secret microphones in like robotics labs across the country right now, you'd just be hearing, holy shit, holy shit, holy shit. It's like constantly happening. And I think finally, like the light bulb moments are happening. And it all like in the early days of this stuff, it all looks very rudimentary and kind of simple. But if you know what you're looking at, you see the signs of life that mean over the next three to five, 10, you know, even less years of development, this will go from an interesting technology in a research organization to like, you know, broad mainstream appeal. And yeah, those signs of life are happening. Those light [5:30](https://realalpha.app/v/XQoFbvyWEy8/?t=330) moments are happening all over the place right now. So what are the components? Like there's obviously, you know, we talked about like, there's like vision, there's like the ability for the robot to do like manipulation the right way for it to have the right sort of dexterity. There's going to be something around like reliability. I don't know about like decision making, if that's its own sort of like, what are the components basically to like this up level? Yeah, you've touched on a bunch of good ones um depends on the type of robot but the ones we're building like robots that operate in your home they need to navigate through a home they need to remember where things are in the home uh they need to interact with and manipulate these objects like you said and um probably have some way of incorporating your user preferences into all of this and so you've got a reasoning component like i see a certain thing in a home plus i know you know the preferences you've told me in the past about how you like things organized or or how you run things in your home and then i'm going to take that and reason about what the next steps i should take as a robot. And then once you have those next steps you're going to take, you know, drive [6:24](https://realalpha.app/v/XQoFbvyWEy8/?t=384) to the oven, put the towel on it, then go over here. Once you have those discrete steps, then you can move to more one of these, you know, end to end models that basically given a simple task can go execute it. My implicit assumption here is that on some timescale, you're like extremely confident this will all work. But like, what are you unsure about in the next, let's say, like five to 10 years? Or like, what will drag? You know, one of the biggest challenges for something like this, it's a brand new product. It's like, how do I use it? Like, how does my life change? And how do I adapt the way I live to best, you know, make use of a robot like this? And that could be, you know, in a home environment, or maybe it's like a manufacturing business that, you know, its entire workflow is organized around people standing in work cells doing a task and handing things on the conveyor belt. Like, how does all this change? And so I think that the technology part will come pretty fast. And I'm pretty confident in that. The part that I think traditionally takes longer is the world has to adapt to basically, now that this new thing exists, How does everything about how I run my business or how I live in my home or how do I operate my hotel or whatever it is need to change or should change to best make use of this? [7:26](https://realalpha.app/v/XQoFbvyWEy8/?t=446) This is like where like AI software is where like it's obviously much better than like what's currently being deployed and used. It like takes time to get from like the tech is good to now it's like implemented everywhere. So you're basically saying it's like the robots will be good enough at some point soon, but then figuring out how to use them in daily life and like where does it actually fit into like a life workflow, that kind of thing. yeah and i think the companies building these technologies have a responsibility to help us figure that out you know they're closest to technology and i think they need to think not just about like what what is technology building do or you know what's the fancy new thing i built in there but like Three steps removed from that. How do businesses actually make use of this? And like, you know, what do they need to know about it? And like, what things do you need to build in so that it's as easy as possible to sort of go on this adoption curve and make it happen? [8:10](https://realalpha.app/v/XQoFbvyWEy8/?t=490) Are you more in a mindset of like, we are Apple and we're going to like, we'll tell you the product kind of and like, this is how it's going to work. And this is what the robot will be. Or is it more of like the YC? Like, let's just get it into some homes and iterate. Like, which mindset do you think you feel closer to? Well, it was a frustrating answer, but a little bit of both. It's one of those things like strong opinions, weakly held. So I think you have to have an opinion. You have to have your taste and your preferences built into the design of a product or it feels bland. Like a product with no opinions is just like, you know, you wouldn't even notice it. So I think you have to start off with strong opinions and then be willing to put those in people's hands and then quickly abandon them if it's not, you know, if it doesn't work the way you want to. I think if you're not stubborn enough, you end up with a just product no one is interested in. And if you're too stubborn, then you end up with a flop in the market once it's out there. And so, you know, I think it's a careful balance. Why did you feel compelled to go for the home? Like you obviously, even with this generalized robot sort of idea, there's a lot of things that you could do that aren't just like [9:08](https://realalpha.app/v/XQoFbvyWEy8/?t=548) pack a box in a warehouse type of thing that's sort of like more dynamic than that. But like you picked home for some reason. Yeah, for some reason. So I just turned 40. This is my third, you know, company that I'm working on. The last two big one. Yeah. I bring this up because like at this point in my career, I kind of know how I want to spend my time and like what's important to me. And, uh, first of all, I want to have a lot of fun and working on home robots that I could use, all my friends can use, like couldn't think of anything more interesting than that, uh, or more fun, especially compared to like robots that are hidden in a factory that no one would ever see. Totally. I also think that, you know, one of the great promises of working on really cool technology is, you know, you certainly get some dopamine hits when you're solving a problem and you make it work, but like 10 times that, or a hundred times more is when you see your hard work go in someone hand someone's hands and they use it for the first time and they come back to you and say oh this is so cool or my life changed because of this i remember you know one of my favorite stories from our examples of this was when we were working on twitch and there was this [10:01](https://realalpha.app/v/XQoFbvyWEy8/?t=601) guy who was like a carpet cleaner in minnesota or something who started streaming on the side and like became had a really popular channel he was making you know he was like the first one of the first streamers to make six figures just playing video games online and he's like this completely changed my life and so like moments like that when you uh build some cool technology but then it actually like moves the needle for someone and they tell you their stories that's that's the really motivating thing for me and you're just not going to get that you know if you don't have millions of people using the product i mean the idea that you could get like a robot in everyone's home is um it's really it's actually totally believable to me like i could see a future which i guess this is what you're building towards if it's the right form factor and price point it does the right set of things it seems very believable and i guess like you probably had some range of considerations where you're like we could make the smallest possible cheapest possible thing all the way up to we could try to make a fifty thousand dollar humanoid and you picked something at some point along that spectrum trying to be somewhere there did you think about [11:01](https://realalpha.app/v/XQoFbvyWEy8/?t=661) it in sort of like a range of like what was technologically possible what future you thought kind of made the most sense like how'd you pick what sort of like complexity and price point to live alone because you're not doing humanoid from day one uh my concern is that there's always going to be an expectation for what the home robot product can deliver and what reality is especially in the early days and that expectation versus reality kind of goes into value how much value you perceive you get from this product there's a scale there's like cost on one hand value on the other we want to do everything possible in our favor to tip the scale towards like value and so that means like being really aggressive on cost um to get the price down and make these affordable that has the dual benefit of on one hand um you know making it so that people are delighted by the product because it's not something they spent as much as a new car on they spent something much much less um and they're pleasantly surprised hopefully and the other is if you get the cost low enough you can sell these to a lot of people because lots of people can afford them and at this day and age data real world data is one of the biggest bottlenecks [12:00](https://realalpha.app/v/XQoFbvyWEy8/?t=720) robotics. And so if you can get lots of robots out there, you're gonna have lots of data much sooner, which then creates this feedback loop where the product gets better, and then it's worth more to people and then more people buy it. There are a lot of trades where you can build a cooler robot or add more capabilities, or you can reduce the cost. And we've almost always been in the reduce the cost kind of thing. Yeah. Do you think that the like, the humanoid vision, which is obviously extremely sci fi and cool? Like, does it make sense? Obviously, you could build a robot a bunch of ways and like one way you could choose to do it is just like shape it like a person but it's a robot you know maybe there's some reason for it but like when you think about like the humanoid question like does it intuitively make sense is something that like ought to exist or is it kind of random first of all when i see the videos of human humanoid robots these days having worked in the field for a long time it is just so cool it's so amazing to see what people are able to come up with these days and how fluid the movement uh looks and you know how dexterous they're getting in terms of the things that they can do. And so I think they're amazing machines, [12:59](https://realalpha.app/v/XQoFbvyWEy8/?t=779) and I think they need to exist in the world. I think the question for me is, if we're talking about putting these robots to work, or like people owning them, the question is like, at the end of the day, is this the most cost effective way to deliver the most value I can, you know, to that customer or to that person? And I think for humanoids, there are very few uses for which [13:19](https://realalpha.app/v/XQoFbvyWEy8/?t=799) **Kyle Vogt:** the answer is yes. Most of the time, the answer is no, I can build a simpler machine that works in this environment if it's a factory thing where the floors are all flat and you're just moving [13:26](https://realalpha.app/v/XQoFbvyWEy8/?t=806) things from one place to another that robot should probably have wheels if you're in a home environment and you know like a humanoid presents all these safety issues like with walking upstairs if it slips on a banana peel and falls it becomes a you know ballistic missile basically going down your stairs these are not good things for that's true actually like a big heavy robot falling down your stairs a huge problem yeah so for the home you probably want to optimize more on like low mass low cost and try to like you know maximize what you can do but you know not not running into some of the challenges of a humanoid. That said, there are some things that would be really hard for a non-humanoid robot to accomplish. If you're on a construction site and you're climbing up and down ladders and using hand tools designed for humans and all these things, I buy that argument that there are some uses where we'll want humanoids. But I think it is currently, I think people advertising humanoids are trying to get hype in the space, get more investment in the space, which we need. But I think the actual practical uses of them, it will be a little bit smaller than what is being portrayed currently. It also could make sense that they don't make [14:17](https://realalpha.app/v/XQoFbvyWEy8/?t=857) the most sense in a home but they live other places like it would be good for example if like a lot of like defense was carried out by machines like because that could in some world you know hopefully that could like save lives for example or like you could imagine it sort of like you know guarding at like you know a stadium or like taking care of like you know big sort of like uh patrol areas and things like that so i could see that because it is like a very mobile thing in the home that example that you just gave you know it slips and it falls on the stairs and it you know, hurts a kid or an animal or something like that. [14:48](https://realalpha.app/v/XQoFbvyWEy8/?t=888) I mean, maybe in the distant future, we can solve these problems. I think just near term, you're less likely to see them in the home first. Along that curve, though, between now and of course, you know, 50 years out, like obviously these things are going to be, I think it's like cars where it gets safer than people, you know, one day, you know, I assume. But on the way up, what's the regulation going to be like for robotics? Like, do you need to be like really involved with the government to like put these robots in a home or is part of what you're doing with the design like to avoid a lot of that stuff? [15:14](https://realalpha.app/v/XQoFbvyWEy8/?t=914) Right now, you know, it's very different than some of the industries I've worked in or defense things or automotive things where they're very, very heavily regulated industries. And for good reason, I think you're going to see a lot of products in the home and it depends on your view. On one hand, we have these little robot vacuums going around today. You could make an argument that this is kind of just a step up from that, but you don't see for consumer products, a whole lot of targeted regulations for individual products. We have, you know, general product liability laws and other things that are generally applicable to everything's from chainsaws to blenders or other things that you might have in your home that carry some risk associated with them. But I think there's an immense responsibility on the developers of these products to try to make them safe and to do everything possible following best practices, regardless of whether or not there's regulation. One thing that we may see more of is looking at how the data is used from these products, the security of these products. I think that's... [16:00](https://realalpha.app/v/XQoFbvyWEy8/?t=960) It's really important. Obviously, like the home is one of the most intimate spaces in your life. You know, there needs to be a great degree of trust and responsibility that goes with the companies who are, you know, have these machines that are likely covered with cameras, you know, running around our homes. And most of us don't even think about today, like when we buy a robot vacuum, where does it come from? Like, who is the company behind it? Are they trustworthy? Are they going to do the right thing in my home? And that's where I'd like to see a lot more scrutiny. So what does that mean you're going to need to do? Because you're right. It's like, you know, I remember, you know, people got comfortable with it at some point, but like the Alexa problem where there's like a microphone in your home like now there's like a microphone and a camera and like whatever else in your home so like what what does that mean you need as like a company to sort of a be you know a trusted brand there like you have to go from day one pretty hard at that I guess yeah yeah you have to have some principles and opinions and be able to talk about it publicly I think but you know all these products are gonna every every new [16:48](https://realalpha.app/v/XQoFbvyWEy8/?t=1008) category of product like this goes through weird snafus in the early days I mean when you mentioned Alexa I was thinking to mind when when those first came out wasn't there something where there's like a tv commercial that came on and said hey alexa something something and then like across the united states like thousands of people bought toilet paper you know and then recently with the meta meta glasses zuckerberg was on stage and he said something and all the people in the audience their device pinged the server at the same time and the demo failed you know so there's going to be these weird moments and things that um that come along in the early days that um but anyways on on the uh on the data side for us we have like two things we care about one is transparency so if if there's data being collected in your home, like what was it? [17:25](https://realalpha.app/v/XQoFbvyWEy8/?t=1045) I want to be able to know what that data was and what's going from the robot to anywhere else. And the second is control. [17:31](https://realalpha.app/v/XQoFbvyWEy8/?t=1051) **Kyle Vogt:** If this product is in your home, you own it, you need to have the on-off switch and be able to control what that data is used for. [17:37](https://realalpha.app/v/XQoFbvyWEy8/?t=1057) And I think if you have those two things and you are principled about those things and hold true to them and basically fulfill your promises and you give the control to the user, I think that's the best sort of starting position for something like this is just establish those principles up front. One last question on robotics and we can go to another topic, AI models behind robotics. How distinct is the concept of like robotics AI versus like other AI? So, I mean, there's a lot of similarities. And I think in a way like LLMs that started off as, you know, like chatbots that exist purely in the text world and robots, which are like physical machines, very multimodal in nature. [18:14](https://realalpha.app/v/XQoFbvyWEy8/?t=1094) You can see these things kind of converging because the latest models are multimodal. They can take in audio, images, other things. in the same way that your robot is expecting that. And so over time, I think they're converging a little bit. And in fact, a lot of the training approaches, pre-training, post-training, those concepts exist in the robotics world. However, there's still a lot of things that are unique to robotics that you would never do if you're working purely on an LLM. And that's a lot, basically like mixing in real-world data, different ways of collecting it, different ways of using simulation and figuring out how to tie that to all the intelligence that's embedded in like a modern LLM. [18:46](https://realalpha.app/v/XQoFbvyWEy8/?t=1126) And then the data is like super important here, obviously. Data is important today. I think this is like a now problem. You know, if you look at LLMs, I think the reason that you can see so many different companies, like 20 different companies all building foundational models and get, you know, within a stone's throw of each other in terms of performance, small teams, large teams, whatever it is, is because essentially they're all starting from the same data set, which is the internet and everything that can be downloaded from it. And, you know, that data kind of determines the quality of the model that you can get. [19:15](https://realalpha.app/v/XQoFbvyWEy8/?t=1155) And there's certainly some alpha on top of that from individual teams. But in the robotics world, [19:19](https://realalpha.app/v/XQoFbvyWEy8/?t=1159) **Kyle Vogt:** there's no corpus of data like the internet that exists. There isn't an entire internet of point clouds or camera images of robots manipulating objects. And so right now we're [19:28](https://realalpha.app/v/XQoFbvyWEy8/?t=1168) in this early days where you've got to either bootstrap that data yourself, you've got to pay people to collect it for you, or you've got to try to interpret or generate robot data from other things like watching YouTube videos and trying to infer from hand motions how a robot should do the same thing. And so we're just kind of in the early, early days of that for robotics. Do you think there should be like a scale AI for robotics data or will it be that a company like yours just generates its own data and gets smarter as a result of that? I don't know. I think they'll probably be both. In fact, I've probably talked to at least a dozen companies who want to be. [20:00](https://realalpha.app/v/XQoFbvyWEy8/?t=1200) the scale AI for robotics. And I think that there's going to be plenty of customers for that in the near term, especially as, you know, as this data void exists. But when that starts to be filled and we start to see useful robots in the world, I do think the majority of data collection will come from robots and less from people getting data. I would also think that for like for your product, for example, any data set that is not your products in the wild is going to be approximating the data and the perfect data set I would imagine would be if you had armies of robots out in homes giving you data. If your technology is sufficiently advanced that you can do transfer learning from other forms of data, other robots, YouTube videos, whatever it is, any source of data, and you can use that to train your robot, that's like an advantage because you don't, you know, then that total size of that data set may be much larger than just the data set that would be collected on your specific robots. However, where we are today, it's much easier to get robots to do amazing things if the data collected came from the exact robot that you're trying to deploy a model on totally yeah and we'll see if that that changes over time yeah it [21:01](https://realalpha.app/v/XQoFbvyWEy8/?t=1261) makes sense so um we alluded to this before but you obviously started twitch you started cruise you're doing it again first of all why uh why are you so motivated to keep doing these hard companies and so like many people after this much success wouldn't go back to the beginning and um you've had two really successful companies which i want to talk about particularly cruise because i think it's related but i guess to get started like what's driving you now to do this again i mean i had you know a very very short-lived existential crisis after cruise is like oh my gosh i'm done with this company this this is like you know practically my identity for a full decade what next i spent some time thinking about that there's you know you could retire you could become a venture capitalist which is the same thing i think i don't know just kidding yeah um and then after after thinking about that for a while i realized like the thing that you know outside of spending time with my family and friends, the thing that brings me the most joy is solving really hard people or really hard problems with really smart people. And so like that is retirement for me. [22:05](https://realalpha.app/v/XQoFbvyWEy8/?t=1325) That's like the most fun, you know, satisfying thing that I could possibly think of to do. And it also ends up being, you can do more of that and do it at a larger scale. If you work with like a big team of people and you do it in the form of a company, as opposed to a hobby or something that you're doing it on your own. And so to me, I think there's no better thing. And maybe at some point I'll run out of energy to go hard like I am right now. But for now, like this is this is great. We have a brilliant team. We're going on this, you know, building this exciting new product in a big market. And that is energizing to me. I want to talk about a couple of the things that you've said about how you want to build this time. One that stuck out to me was that you never want to be more than 100 people. Yeah. And first of all, I actually didn't know. Is that like literal or is that directional? To be to be seen. Yeah. I think right now we're taking it very seriously. So if that is actually your belief, and talk about why, but if that's actually your belief, then you make very different hiring decisions. It's like, well, you know, if I think about the future company having 100 people in it, I can allocate this many people to this [22:59](https://realalpha.app/v/XQoFbvyWEy8/?t=1379) type of role. That means every person in every seat has to be the best in the world at this for the company to be successful. And so you end up, you know, passing on a lot of people that are great people, really talented, but they're not, they're not at that specific level we want for that particular role and i think you know if you're successful in doing that you end up with this there needs to be a name for it but like in the early days of a startup when everyone is like on the same page like maybe just the founders they're all in it 110 they're all usually like brilliant working together they're almost mind melded um and and then you have like insane productivity for some period of time and still you until you get bogged down by the organization growing and adding more functions and you know teams of people and management layers incentives get disconnected, you have communication issues. [23:42](https://realalpha.app/v/XQoFbvyWEy8/?t=1422) And so you get this drift away from this pure force of energy that is in the beginning stage [23:47](https://realalpha.app/v/XQoFbvyWEy8/?t=1427) **Kyle Vogt:** of a company. And so the reason for trying to have a cap on the size of the company is to keep it so that we're always in that pure high output zone. And you can't get that if you have too much of a [23:57](https://realalpha.app/v/XQoFbvyWEy8/?t=1437) range of people in the company. I really think of it more like a pro. sports team like you're not gonna have you know the lakers i think you're gonna have like lebron lebron james and a bunch of high school kids on the team it's like they're all players that are the best in the world so that you know when they work together as a team they can outperform a team that is like a mix of talents like if you have like the lebrons with the high school players like the lebrons are like what are we doing here yeah exactly they want to stay they're gonna they want to go play with the best people in the world against the best people in the world and uh and that's how you get better and grow and you know people who are people who are the best in the world of what they do typically got there because they had this growth mindset that constantly want to get better and you know what better way to do that than to surround yourself with people of different skill sets that are all the best in the world at what they do and sort of absorb from that i think so much of what gets hard is as you start getting into like scaling operations and you get into like that side of things it just gets so hard to keep it really small you know like even [24:47](https://realalpha.app/v/XQoFbvyWEy8/?t=1487) you think about like let's say you only had like 10 non-engineering roles it's like well some someone's got to run finance they probably can't do it alone you've got like you're going to have all these like physical parts you're gonna have to have buildings for things like so how do you think you'll actually try to keep a limit on that like will you partner do you go sort of like work with people outsource do you actually think that like you know maybe with like new ai tooling you could just go way further with people and it's just sort of like a demand deal place yeah it's a good question that's that's part of why i said to be seen like this is a great mental model now and it may not i think it's a great push and by the way i think most of the one of the healthiest changes I feel like I've seen from five years ago is the shift from thinking that like big teams are cool to thinking big teams are lame. Yeah. I mean, things seem to ebb and flow, right? Like I'm taking the extreme position here, but I do think if that has the effect of, you know, causing a small shift in that direction, that's probably net good for the industry and good for these companies. So it'd be a question for us. Do we partner or outsource things? I think, you know, keeping the team small [25:44](https://realalpha.app/v/XQoFbvyWEy8/?t=1544) also forces you to focus on like, what are our core competencies, the things that we need to do uniquely, because we think we can actually do them better than any other company that we could potentially work with and you know for things like a lot of operations or facilities or you know buildings these are things where maybe we have no reason to think we would be the best in the world at this so we should partner and a lot of companies like they have lots of funding they have lots of teams like it's almost like they take on these responsibilities because they can not necessarily because they should I feel like one of the most important things which I think you've obviously shipped in self-driving in a way that like you know very few have but I think in a lot of these um sort of more sci-fi areas it's very easy to not be in like shipping mindset and like i think you did this really well at cruise obviously like opening i was doing this like well before chat gpt and so you basically probably are in a mindset i assume of figuring out like how quickly can we ship and like iterate and like that's got to be the mindset rather than just like hang in a warehouse building the perfect robot forever i think for that it's it's starting the [26:43](https://realalpha.app/v/XQoFbvyWEy8/?t=1603) the thing you want to build and then working back to what is the what is the constraint what are the constraints or bottlenecks that we need to be that we need to make our number one priority because it cannot go faster than you know what that one bottleneck or constraint would dictate and for self-driving that's a combination of safety trust and public acceptance and so you know those are different work streams where basically like unless those are all green you don't have a product it doesn't matter how good the technology is and there are similar things you know for a home robot or really any business and so like you know mapping out what those are and basically making that the company's top priority like it you know crews for example see the metrics were the single thing we talked about every week week over week over week making progress towards those and i think for any company like what you talk about what you may design your metrics around kind of sets the tone for the company and it's got to be aligned with that you know whatever the constraints are what do you think you can do in a home first rely like what do you think will be the first activity that can like really be done well in a home and then like what are the things that you think are close [27:35](https://realalpha.app/v/XQoFbvyWEy8/?t=1655) to maybe follow in the you know next 12 to 24 months or something yeah i mean there are hierarchies I think, of tasks for a home robot. And if you look at, I think, two, like a classic two by two grid, I guess one is maybe the technical complexity of the task, like how hard is it to get a robot to do this successfully? And then the second is like, what is the success rate that is acceptable to a customer of a product like this? And I'll give you an example. If you are You know, in the easy side of things from the technical capability, and also the very forgiving side of things in terms of success rate is probably like picking up your kids toys. So I have, you know, two kids, a one year old and a seven year old, and they're between the two of them are constantly making messes and toys are all over the house, running around picking up toys. And so if you have a product that you can buy, you can go to the store, buy this thing, put it in your house, push a button, turn it on. And then when you're gone for the day, all the toys are magically put away by the time you get home. It's like a mind blowing experience. [28:29](https://realalpha.app/v/XQoFbvyWEy8/?t=1709) And let's say it screws up and like two out of the hundred toys are still on the floor when you get home. That's okay. Doesn't skip a beat. Yeah. So that, so that like, you know, think about nines of reliability for, for engineering, [28:40](https://realalpha.app/v/XQoFbvyWEy8/?t=1720) **Kyle Vogt:** like maybe one nine is fine for that particular task. [28:43](https://realalpha.app/v/XQoFbvyWEy8/?t=1723) There are other things like putting a wine glass in a dishwasher where the technical complexity is a little higher in the, the, um. What's hard about that, by the way, is it like the grabbing or is it? Yeah. So if you think about picking up objects, this microphone, which is going to make a noise when I squish it is, uh, is, is compliance. And so if I'm off a little bit on where I grip it or like how much I squeeze it, I'm not going to shatter this microphone into a million pieces for wine glass. The margin is, is very thin. And so from a dexterity standpoint, it's a little more fragile. Actually, sometimes I think about that's like a good example of a thing where I'm like, it's amazing that people can do certain things like squeeze a wine glass, the right amount or like hit, you know, a ball, you know, with a racket or a golf club with the right angle or something like that, or like catch something that's flying while you're moving. Like it's actually pretty crazy what you can do like mechanically it is and the evolution to how we get there is interesting too because my one-year-old daughter her hands are like open closed there's nothing in between yeah she grabs objects the wine glass is shattered and at some point along [29:39](https://realalpha.app/v/XQoFbvyWEy8/?t=1779) the way we developed much more nuanced skills and abilities but so wine glass is another one the other thing is challenging is if you're putting a wine glass on a rack and you know it's a thin stem or something and you nick uh you like bump into something you might break the stem off right and so not only is it more difficult from a technical standpoint but if you shatter a wine glass in someone's dishwasher they're probably not going to be your customer anymore that's right and so that's like maybe several nines of reliability and so i think that this this sort of spectrum of technical difficulty and uh basically forgivability is going to dictate the types of things you see home robots do first and um and i think we'll work our way up towards you know i think the holy grail of a home robot which is like dishes laundry end to end maybe cooking these things all of them have like all of these little uh it's like a minefield you do one thing wrong and you ruin the whole process like for laundry if you put the red sock in with the whites you know have pink laundry that's like game over right and it's you know so there's things like that for cooking it's the same thing you put too much salt or pepper in there and the [30:37](https://realalpha.app/v/XQoFbvyWEy8/?t=1837) dish is ruined you know so these are things that i think we'll get to and i think it'll happen pretty quick but you know i think you think it's like cooking a steak at some point yeah why not if you think about at the end of the day you've you have pick in place and simple manipulation that's what cooking is yeah they're just like a much higher degree of reliability and there's other things around food safety and bacteria and other things that come in cookie cooking and temperature sensing and what like that so it's all doable it's just like i think at some point it's like hey robot i'm at work right now there's a steak in the fridge please cook it and clean up everything by the time like 15 years from now that's that's doable less than five less than five yeah this stuff is going fast again if you saw if you look at the robots you can buy today day in the world, like the nice robot vacuums, you may not think that. If you see what's happening behind closed doors at the best robotics companies in the world, you might think that. And if you're the leadership of these companies, the technical leadership, and you kind of know where things are going, you absolutely believe that. The hand seems really, as we're talking about this, [31:32](https://realalpha.app/v/XQoFbvyWEy8/?t=1892) I was sort of like stupidly like, I was like, actually a hand's pretty good. Like your fingers are like pliable. You have like a lot of degrees of freedom. You have like multiple grip points. Is the hand the optimal thing? The hand is really important to get right because it is the robot's interface to every object that it interacts with. If you make it too simplistic or not enough sensing capabilities or whatever, then you have to have a much, much smarter brain to figure out how to use this primitive tool to accomplish a complicated task. And so the more The more mechanical complexity or capability that you add to a hand, the more sensing ability. In theory, it would require less, you know, sort of rocket science to figure out how to do a task with that hand. The trade, of course, is the more technology, the more degrees of freedom or motors that you pack into a hand, the more complicated it becomes, which impacts durability and also cost. [32:18](https://realalpha.app/v/XQoFbvyWEy8/?t=1938) And so there's push and pull there to find that sweet spot where you can basically come up with the simplest hand possible to do the tasks you want to do at the lowest cost while also being able to accomplish everything in a fairly straightforward manner. But I think in The Limit, you know, there's a lot of, you know, we think by analogy a lot. And we have two hands and two arms. And so, like a lot of the robots you see today have two hands and two arms. But it is a really interesting thought experiment. Like, what does the ultimate hand-arm thing look like? And I think it was Rodney Brooks who said this the other day. [32:47](https://realalpha.app/v/XQoFbvyWEy8/?t=1967) but i actually do kind of think maybe it ends up being some crazy octopus tentacle looking thing in the future that's like very adaptable and can reach into small spaces interesting well i think that you know the human hand was ended up where we are due to probably some impossible to unravel sequence of evolutional pressures well it's like you start down some path and then you do your best you know evolution does its best given some somewhat random starting point i suppose right yeah so if you could go back like a million years and hit the reset button on human evolution like Maybe something, a new fork would emerge and it would be more tentacle-like or who knows what. [33:18](https://realalpha.app/v/XQoFbvyWEy8/?t=1998) But I am skeptical that the way that human hands and arms evolved is the ultimate. And so the challenge will be like, can we figure out what that is? I have a couple of stupid questions about the robot at home. One is how strong could it be? Like, is a 100-pound robot, like, it must be ridiculously stronger than a person, right? I would think for a 100-pound robot, you could certainly make it maybe stronger in some dimensions. There are some things that like our sort of soft biological muscles are pretty good at. Are stronger than like a physical robot pound for pound kind of thing? Yeah, it's really hard to say. [33:50](https://realalpha.app/v/XQoFbvyWEy8/?t=2030) I think so. I think probably the state-of-the-art Boston Dynamics robot seems like it's on par, if not, you know, more capable than a human. And if not now, I'm sure the next couple of generations will be. So that's kind of interesting. That's surprising that a soft muscle is stronger than like, I don't know why I would think a robot could be dramatically stronger. Yeah, I've been going down the rabbit hole on this a little bit, thinking about like, you know as again our focus on affordability and cost like is a electromagnetic gear motor where you've got a magnets and copper winding and a bunch of gears in a housing is that the most cost-effective durable way to generate motion for a robot and the answer in the short term is probably yes but i think there are some interesting things happening where we're trying to mimic either some of the chemical processes or electrostatic actuators or other things that are similar in how they work to like a human muscle and the benefit there is you can get a higher cycle count more silent operation and potentially more power density like how much strength can you get into a physical volume than what we have today in gear motors and then potentially much much beyond what [34:45](https://realalpha.app/v/XQoFbvyWEy8/?t=2085) humans have in our muscles isn't like hydraulic is pretty strong like a like hydraulic pressure is pretty strong hydraulics can be extremely powerful but they have other trades typically noisy the valves and things are pretty expensive can be harder to control and get you know high fidelity motion and so in terms of power density may be good but you know there are other trades and the reasons you don't see this on a lot of robots that makes sense another question i had that's sort of like probably off spec, but while we're talking, is this going to be something that would have like home security applications as well? [35:14](https://realalpha.app/v/XQoFbvyWEy8/?t=2114) Or does that then take you into weird territory that's just not worth going to? Yeah, I think so. I mean, one of the challenges with a home robot is this kind of general purpose. And so like, you know, what are people going to use this thing for? And I think it's hard if you just have a laundry list of 50 different items that the thing can do and security is one of them. But I do think a lot of people will be out and about and with their home robot at home, be like, oh, I wonder if I forgot to turn off the gas on the stove and send the robot over there to just, you know, tell you or even take it on for yourself. [35:42](https://realalpha.app/v/XQoFbvyWEy8/?t=2142) In the same way, you could be like, hey, robot, like, you know, if you see any person in my home or any doors open, like, let me know. Yeah, if you see me getting burglarized, like, do something. But I don't know if you will think of it as a security robot so much as, like, this is just one of the many responsibilities of my home robot is to keep tabs on my home. Totally. Alerting, probably. Taking action is probably not. I hadn't thought about that side of that. That's not really in our... That makes sense. I'm just thinking because in my head, I'm like, okay, if there's this brilliant, capable robot in the house, my guess is you're going to have a lot of people want it to start doing a ridiculous number of things for them. It would be the arc of time, and then you'll have to choose from that set what goes in. Yeah, I think so. But for sure, I mean, on the security side, I would hope though, rather than having physical deterrence and having having your home robot turn into a security guard with a baton or something. [36:33](https://realalpha.app/v/XQoFbvyWEy8/?t=2193) It's more so that it just becomes unattractive to rob homes or do, you know, break in and enter into a home. Maybe in the same way that, you know, a world full of cars where everyone has like that Tesla sentry mode, there's very little incentive to break into cars. It's not worth the risk. Well, I mean, even like a security system just makes a loud sound and calls the police. I think that's pretty effective. I think it's extremely effective. Yeah. And I think those systems are pretty old and, you know, they're deeply embedded. and but yeah it's like you may figure out how to disable the alarm and sneak into the house but if there's a robot you know rolling around and then the sirens blaring and all that stuff i just think it'll be interesting where if this gets in there my guess is people will start to i could see a future where people expect a ridiculous amount from these things well i mean it's touched on something interesting i've thought about is like when you ask people um or we ask people what would you do with a home robot you know that immediately what comes to mind is like the thing that's most annoying to you today to do in your home and i think that's good we want to help with the annoying [37:28](https://realalpha.app/v/XQoFbvyWEy8/?t=2248) stuff and what comes out like laundry probably yeah laundry dishes picking up after my kids um you know wiping surfaces cleaning like these are the things you would expect and so we're gonna chip away at those things for sure but what i also like to think about is the things that we don't do because we value our time more than that um you know example is if you've ever gone to like a really nice hotel you know the slippers are laid out for you there's a glass of water on the night stand a little chocolate on the pillow all these like little finishes like i don't know i i think that you know robots should not only automate the things that we don't want to do but also like elevate our standard of living to some degree. Yeah. And so I love the idea that if you can afford a really affordable home robot, we're going to give you a lifestyle that, you know, would otherwise be inaccessible to you. Totally. I mean, that's actually a really interesting point that like a lot of the types of things you're talking about don't require any new inputs. It's just about taking care of your home in a certain way that's like beyond what you would normally need. But it's like you've got a bunch of towels that are like sitting in the [38:20](https://realalpha.app/v/XQoFbvyWEy8/?t=2300) laundry room that are clean. But can you like put those by, you know, the shower and like roll them up nicely. Yeah. And maybe don't need all these things, but the point is like, you know, your, your time is more valuable than that. It's very scarce. Like humanity's time, I think is really important, but for a robot that's got 24 hours to sit around in your home and like try to make your life better. What could we come up with for it to do? What, what could it come up with to do for you? That's, that's an interesting question. Wow. I'm curious about reflecting on what you've learned from the way self-driving cars played out and how it might matter here. Maybe one interesting sort of case study is, you know, the Tesla versus Waymo approaches. Do you think in any way that how that played out or any learnings there that poured over to like what could, you know, be impactful in the robotics land? Well, it's hard to say that, you know, very different approaches to getting to market, but it does seem like they're both trying to converge at the same thing, which is, you know, self-driving cars everywhere. I think one thing that was really [39:16](https://realalpha.app/v/XQoFbvyWEy8/?t=2356) **Kyle Vogt:** brilliant about Tesla's approach, they found a way to sell the product essentially before it was fully complete, if we're looking purely at the self-driving side, and generate billions of [39:24](https://realalpha.app/v/XQoFbvyWEy8/?t=2364) dollars of cash flow, which they could use to bolster their core business, but also continue to invest in R&D to make this self-driving product. Waymo, by comparison, has taken almost a couple of decades at this point, maybe not quite that long, and probably tens of billions of dollars of investment. And the revenue relative to that has been fairly meager compared to that total investment over time, which basically means that the only companies in the world who can do this are the ones with that kind of capital on their balance sheet to basically fund this crazy amount of R&D year over year. And I think it's no coincidence that the only companies who succeeded that approach or are on track to succeed in that approach are owned by you know amazon google or um you know like a major car car company and that was even a struggle for a company like general motors and so in the home robot space i hope we don't repeat that i hope it doesn't become the case that the only companies that make it are ones that are basically kept alive through billions or tens of billions of dollars from you know a corporate uh yeah benefactor and instead we can find clever ways to get to market that uh which i guess is why you need to get to market and be [40:28](https://realalpha.app/v/XQoFbvyWEy8/?t=2428) selling something along the way to fund all of this well i think if if your development cycle means you don't get to meaningful revenue for five to ten years after the company has started it means you're entirely dependent on either being acquired or the capital markets you know being pointed in the right direction and you know historically things tend to cycle back and forth in a five to ten year timeline you're getting awfully close to almost guaranteeing that you straddle like a down cycle as well as an up one and that can be a killer for these companies We don't need to talk about sort of cruise and GM too much, but I am curious about sort of, you know, I saw you share on Cheeky Pie about like not wanting to sell. And I'm just curious, like your mindset about the sense of autonomy and how you think about selling a company since you've been through it, you know, a couple of times and everything. [41:14](https://realalpha.app/v/XQoFbvyWEy8/?t=2474) I think, you know, and I said this before, but my conclusion is like, if you are selling a company, it should be because the reason you started the company or the thesis that you had in mind or the thing you wanted to build, something has changed. And maybe like you're no longer interested in it, your life circumstances have changed, whatever. But I think it is a fantasy to believe that you can sell your company, like have your cake and eat it too, like sell your company in order to further the mission and further the mission. I think in theory, this can happen sometimes, but it is so, so rare. And I think more likely than not, you'd be disappointed with that outcome. [41:43](https://realalpha.app/v/XQoFbvyWEy8/?t=2503) And therefore, for me, I can't imagine being in a situation where I would trade the opportunity to build this amazing thing and control it and make sure it happens in the way that I want it to for some kind of partnership or liquidity. So that just doesn't make sense to me. Maybe not for everyone. And maybe that's just because I'm so excited about this thing and bringing this new idea of a home robot into the world that it just wouldn't even cross my mind the thought of handing over the reins to someone else. Yeah, you're at a point now where like this type of company is such a forever project. And like, you're now able to start a company that's like, you know, it's not, it is not some little thing. Like if this works, it's just such an important thing, which also, I guess that probably also drives you to want to sort of hold on to it indefinitely. [42:23](https://realalpha.app/v/XQoFbvyWEy8/?t=2543) Yeah, perhaps. But I think I'm not selfish about it. I feel like I have an obligation to stay true to our investors, the employees, and the mission. So even though I certainly want to hold on to this, I'm not treating it like a pet project. I actually do want to fulfill this broader vision that we all share. Yeah. Maybe as a final thing to touch on, you did this crazy marathon around the world experience. What was that? And why did you do something that seemed so hard? deep in the in the middle of cruise i was i think i was frankly like kind of frustrated that like we were putting in all this energy and sometimes there would just be periods where the metrics wouldn't always go up into the right we'd take a regression and go back and forth and so you know the result wasn't always proportionate to the energy going in and uh for running for me at least that was not the case you put in the time you run you get better yeah and so that's very deterministic and satisfying and so i needed something to balance that i feel like in my life um and as i do i went down a rabbit hole reading about like extreme marathons that you can do. I was like sort of an amateur marathon runner and came across the [43:22](https://realalpha.app/v/XQoFbvyWEy8/?t=2602) world marathon challenge. It's this thing you can sign up for. They take you to each continent, one continent per day, and you run a marathon on each one. And then like the next day you fly to the next continent. I thought that is insane. And then in fine print on the website, it's like the world record is like five days and 10 hours by this, this one guy. And then I got the wheels turning. It's like, well, I wonder what the theoretical engineer brain clicks on. I wonder what the fastest theoretical time you could do is if you, if you optimize the, it's like the traveling salesman, like, yeah, where you land, optimize for customs, in and out and logistics and like really dial it up to 11. And that turned into an 18 month obsession, got stuck in my head and I ended up. [44:00](https://realalpha.app/v/XQoFbvyWEy8/?t=2640) Writing some software to find the shortest route between the seven continents. That's crazy. Spending a... My problem is that I couldn't run a half marathon. That's where I would struggle. This sort of stubbornness and attachment to this idea meant that part of this was I had to train my body physically to be able to do this. Because like you're running a marathon and then you're not resting afterwards. Yeah. So the cycle, for example, is, you know, you start in Cape Town so that you fly to Antarctica. You have to start there because the weather is so... Oh yeah, the Antarctica one, that's tough. [44:25](https://realalpha.app/v/XQoFbvyWEy8/?t=2665) You need like at least a, call it a six hour window of decent weather. and you're like looking at the weather forecast when it clears then you fly in and you land you run the marathon you get out because that can throw off the where in Antarctica do you do this on like the most temperate outer part of Antarctica so it's on the continent but we're not talking like south pole yeah so it's cold but it's not it's not like but it's not snowy I mean it's icy and you can't say it's like barren all ice you land the plane on ice you run on ice you're running on ice on ice it's kind of like crunchy ice like there's a there's like a ski slope groomer that did a course down there uh and it's like a six mile loop or something and so it It was like running on, it was like trail running. [45:01](https://realalpha.app/v/XQoFbvyWEy8/?t=2701) Got it. It's still pretty crazy. That's crazy. Anyways, yeah. So organizing the logistics for the training, training my body and everything, doing it in the end, ended up doing this in about three and a half days, which blew the world record aside. And then after 18 months doing this and finishing it, you know, I got to say like it was, you ever like finish the last item on your to-do list and it's just like a dopamine hit? You're like, oh, that feels so great. That's what it was. It was like relief. It was like, check the box. Now I can, my tormented brain, which wouldn't let this go for 18 months, can finally relax. [45:28](https://realalpha.app/v/XQoFbvyWEy8/?t=2728) Where do you go? Cape Town, Antarctica, South America? Yeah, southern tip of South America, and then to Panama City, and then I think to Madrid, and then Oman. And you're just like, by the last one, are you just crazy fried? Or were you in shape to just not be, you know, so beaten down? I was pretty fried. Pretty fried. Yeah. But it's like, you know, the training I did peaked at doing three marathons within a 24-hour period in three different cities. That was like the stress test for this, if you will. and my coach was like, you know, I was like only three marathons. That's not seven. Like, is that actually the right amount of training? And he said, I promise you when you're doing the really real thing and you have this whole crew of people with you and everything is on the line and the adrenaline going, you're, if you can do three and 24 hours, you can do the rest. And he was right. That's wild. That's like the hardest physical task imaginable. You know, mental toughness is important for startups. And I feel like it, it really helps me quite a bit in that domain. Yeah, totally. All right, Kyle, this was really fun. Thanks for making time for it. [46:21](https://realalpha.app/v/XQoFbvyWEy8/?t=2781) Thank you.