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The Breakthrough For Home Robots with Kyle Vogt, CEO of the Bot Company | Ep. 32
Kyle Vogt argues that AI is making useful home robots possible, and that affordable, specialized machines will reach people before humanoids.
Uncapped · Jack Altman
- Kyle Vogt is CEO of the Bot Company.
The best minutes
- 0:32Language models are changing what robots can understand5 min
- 22:32A 100-person cap can preserve a startup’s output4 min
- 27:19Home robots should start with forgiving tasksPro pick 4 min
Also worth watching
- 8:53Affordable robots can build a data flywheel3 min
- 12:05Humanoids make sense only when their flexibility pays off3 min
- 15:02Home robots need user control over collected data3 min
- 17:54Robotics companies still lack an internet-scale training corpus3 min
- 38:33Revenue during development can reduce reliance on capital markets2 min
Skip the career-motivation discussion, hand and actuator design, home-security applications, and the marathon's planning and logistics.
Full analysis · 6 min read
Real Alpha · Nov 8
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.
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6 sections, the 4 other voices it tests Vogt against, and what it means for you. Every episode we cut gets one.
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Language models remove two old robotics bottlenecks
Vogt's breakthrough story is not that robots suddenly acquired hands. He says language models bring world knowledge, while neural networks learn coordinated movement.
Before, finding a whiteboard could require a mapped room and detectors trained on many examples. Vogt says a robot can now draw on broad learned knowledge to recognize it.
For example, he describes learning movement through teleoperation or simulation, rather than calculating every joint trajectory by hand. That may make more tasks practical to attempt.
Yet recognition and learned motion do not establish safe, repeatable household performance. The episode offers a mechanism for progress, not a measured deployment result.
“you can take all the common sense that's on the internet and inject it into a robot brain.”
Our read
This is a credible explanation of why robotics feels newly open to experimentation. But the technical ingredients are not proof of a dependable home product.
Specialized robots may beat humanoids on cost
Vogt expects many purpose-built machines, rather than one humanoid designed to handle every job. A costly walking body may add little on flat floors, where wheels can move goods.
For homes, he emphasizes low mass and lower cost, partly because a falling robot could hurt someone. Human-shaped designs make more sense, he says, where jobs require ladders or tools made for people.
He also said humanoid advertising can attract investment, while practical uses may be narrower than current pitches. That is his judgment about product economics, not proof that a particular shape will win.
Take a construction site, where ladders and human tools could justify a humanoid. For a flat warehouse floor, the extra limbs may not earn their cost.
“there are very few uses for which the answer is yes.”
Our read
The useful question is not whether humanoids are impressive. It is whether their flexibility earns back their cost and added safety burden in a specific job.
Forgiving jobs make early robot forecasts testable
The headline forecast belongs to Vogt. Asked whether a robot might cook a steak 15 years from now, he gives a much shorter horizon.
His reasoning is that cooking includes pick-and-place and simple manipulation, alongside higher reliability, temperature sensing and food safety. He calls the task doable, but gives no product, test conditions or success rate.
For example, he says picking up children's toys can still delight someone if two of 100 remain on the floor. Take a wine glass, where a narrow grip margin makes failure costlier.
That is a useful deployment ladder. Yet cooking has several steps where mistakes can spoil food or leave cleanup unfinished, making the forecast difficult to evaluate.
Vogt's forecast skips over a success rate, safeguards and what counts as finished. Those are the measures that would distinguish a compelling demonstration from a dependable household product.
Josh Gao of Mecka AI said on Training Data in October 2026 that his team had spent about a year and a half plus trying to solve laundry folding. He expects it solved in the interviewer's term.
So Gao gives a timeline for one constrained task, not evidence that every household chore is near.
“Less than five.”
Our read
Vogt's under-five-year timeline is an opinion, not a demonstrated product milestone. Task-specific reliability and failure tolerance are better tests as capabilities expand.
Affordable deployments could supply missing robot data
Vogt links lower cost to wider adoption, then to more real-world data and a better product. He says The Bot Company has usually favored reducing cost over adding capabilities.
That feedback loop is plausible, not automatic. But more robots mean more observations, not necessarily useful training. Task coverage, failure correction and improvements in later versions matter too.
Josh Gao of Mecka AI said on Training Data in October 2026 that deployment failures and corrections can improve robots. Jason Ma of Dyna Robotics said on Latent Space that month that data quality changes as models improve.
Sergey Levine of Physical Intelligence said robots may eventually generate vast amounts of physical-world data. He said this on Minus One in October 2026.
Ali Ansari of micro1 told the Sabrina Halper Show in October 2026 that the real world has more possible actions. He said its action space exceeds the digital world's.
Still, these views support deployed data's importance while exposing its limits. Home robots encounter varied objects, layouts and preferences, unlike a shared text corpus.
Vogt also says robotics lacks the internet-scale corpus that helped language models. Companies now collect, simulate or infer much of their own robot data.
Josh Gao · Training Data · Oct 20Robot integrators can improve installed bots with data
Jason Ma · Latent Space · Oct 13Robot data quality changes as the model improves
Sergey Levine · Minus One · Oct 22General-purpose robots can bootstrap their own data
Ali Ansari · Sabrina Halper Show · Oct 15Robotics is held back by a much larger data problem
Our read
Vogt's cost-to-data thesis has support as an industry hypothesis, not proof of a self-sustaining loop. Teams should trace which data improves which task and how they know.
Home adoption depends on controls owners can verify
A camera-equipped robot brings a different burden from a factory machine. Vogt says companies should make collected data transparent and let owners control how it is used.
That is a clear principle, but the conversation gives no product setting, retention policy or independent check. And those details matter because a promise is harder to judge than a visible control.
Vogt also says developers have a responsibility to make products safe, even without targeted regulation. For a home product, privacy and safety are part of the experience, not just compliance work.
So buyers and product teams can make the principle testable. Ask what the robot records, where data travels, how long it remains and how owners can stop collection.
“one is transparency”
Our read
The episode identifies trust as a design requirement, not a solved feature. Buyers should be able to verify what is collected, where it goes and how to stop it.
Vogt ties startup survival to shipping and revenue
Vogt says the company is taking its 100-person cap seriously now, while leaving open whether it lasts. The constraint would make every hire carry more weight.
His reason is that growth can bring communication problems, management layers and disconnected incentives. He says a small company may keep the high-output feel of an early startup.
He advises companies to work back from the product to the constraint that limits progress. At Cruise, he said safety, public trust and acceptance were bottlenecks, reviewed against metrics each week.
That logic extends to any company, including home robotics. A capable demonstration does not ship if safety, customer acceptance or operations remain the binding constraint.
On financing, Vogt contrasts Tesla selling before self-driving was complete with Waymo's long development and relatively meager revenue. He says five to ten years without meaningful revenue leaves startups exposed.
Such companies may then depend on acquisition or capital markets. That is his comparison, not a full financial analysis of either company.
Still, founders can ask what customers might pay for while harder capabilities are unfinished. Early revenue can ease funding exposure only if interim work delivers real value.
The episode does not say what that interim product or its economics will be at The Bot Company. And a small headcount alone does not prove speed.
“it means you're entirely dependent on either being acquired or the capital markets”
Our read
The small-team cap and early-revenue case are operating hypotheses, not guarantees of speed or survival. Teams should measure the actual bottleneck and test whether interim work can fund progress without distracting from it.
What it means for you
- Set task thresholds. Choose one household task and define acceptable completion, damage and recovery rates before testing. Vogt's toys and wine-glass examples show why one reliability target will not fit every job.
- Track cost per task. For each prototype, measure cost per useful task, not just machine build cost. Vogt's team has usually favored lower cost over adding capabilities.
- Audit data controls. Ask what the robot records, where that data goes, how long it stays and how owners can stop collection. Those checks turn Vogt's transparency and control principles into requirements.
- Name the bottleneck. Pick one constraint that currently limits progress and review its measure each week. Vogt's Cruise example suggests technical capability alone may not determine readiness.
What to watch
- Whether home-robot demonstrations report task-level success, failure and recovery rates.
- Whether owners can inspect and control data collected inside their homes.
- Whether robotics startups find useful revenue before years of development exhaust their funding.
Send this to product and finance leaders building physical AI.
Watch the minute where Vogt gives the under-five-year cooking forecast
Written by Real Alpha from the episode's transcript and the other moments it links, then checked against the transcript. Quotes are the speaker's exact words.
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Read it with Pro, 7 days free- 0:24Neural 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.
- 5:28Home 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.
- 8:53Affordability 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.
- 12:14Most 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.
- 17:54Robotics 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.
- 20:55Small 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.
- 26:02Start 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.
- 32:26Robot 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.
- 35:06Home 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.
- 38:33Revenue 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.
- 40:49Sell 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.
- 42:35The 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.
Published Nov 12, 2025.
Transcript · 50 min read
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.
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.
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 can take all the common sense that's on the internet and inject it into a robot brain.”
Read the whole transcript
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
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?
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?
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
“Most of the time, the answer is no, I can build a simpler machine that works in this environment”
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?
“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.”
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
“There isn't an entire internet of point clouds or camera images of robots manipulating objects.”
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.
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
“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.”
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
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
“like maybe one nine is fine for that particular task.”
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.
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.
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.
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.
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
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?
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.
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.
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
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
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
“they found a way to sell the product essentially before it was fully complete”
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.
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.
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.
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
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.
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.
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.
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.
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.
Thank you.
