My Conversation with Mehul Nariyawala, Co-Founder of Matic

27:41So you really don't want this giant dog or ugly duckling sitting around in a living room or family room as well. So how do you make sure that it's friendly, it's good looking, that it feels like it belongs to a home? How do you make sure that robot actually looks like robot? How do you make sure that if kids run into it, they're never going to get hurt, that it can go over various trains? And one of the thought experiments we had done, which I told you about, was we thought that let's imagine a world where we take disc robots and we have invented teleporting machine and we can send it back to 60s and ask people, what is it?

28:14There's a good chance they won't be able to guess that it's a robot or a vacuum. So we wanted to make sure that a robot looked like a robot. And that was actually one of the lessons that Tony Fidel and Matt Rogers taught us at Nest, that purpose of the product has to be clear when you use it. So when you look at your T-shirt, you know it's T-shirt. When you look at watch, you know it's watch. When you look at camera, you know it's camera. But when you look at disk robot, you're like, wait a minute, is this a vacuum? Is this a speaker? What is it? So we wanted to make a robot that looked like a robot, that it was friendly, and people got used to it.

28:46And that's how we started thinking about it. So a lot of iterations were initially figuring out what problems are that we want to solve. Can we solve them? And just iteration on is the big wheels better? Are the four wheels better? Three wheels better? And just continuously going through and solving each problem. And with each iteration, we learned and we got better and better. You said that a lot of vacuums, like people associate the loudness of the machine with the amount of suction. And so, you know, vacuum companies would just artificially inflate the like decibels. to make them extremely loud so they sound like they're sectioning.

29:20I remember when I was a kid, I vacuumed all the time, or I was at least asked to, and it was extremely loud, but a lot of the time it didn't even vacuum. It didn't even vacuum. Exactly. And not only that, they have switches, right? It's like you go higher section and it goes, ooh, and you're like, wow, it must be so great. But it turns out actually noise has nothing to do with it. Suction power has nothing to do with it. It actually is about airflow, but even going back to the history of vacuums, vacuums were invented as carpet sweepers. Vacuums did not exist for the world that was hard surface.

29:58In 60s and 70s, we had these manual swivers with just brush roll that you would kind of drive and it will pick up things up. So in the same exact way, the analogy I use is that if you have a car and it's dusty and it has this fine dust, let's say you went to some sort of a national park. On your way back, no matter how fast you drive, that dust doesn't go away. But if you go come home and just gently nudge it with your finger, it comes off. So it turns out on a hard surface is if you really want to agitate your dirt, you have to have a brush roll that spins it and scrapes it. It just needs agitation.

30:27And once it has an agitation, all you need suction for is to take it back to the bag or the bin. And that does not require a crazy amount of suction power. The amount of suction power that Dyson or some of these other vacuum companies have is great if you have sandy carpets, but most of us don't live near beach and we don't have sandy carpets. So just simple amount of brush roll is great. And what was amazing is that all these settings are preset, but the world has changed. We have thick pile carpets, low pile carpets, shag rugs, Iranian rugs, and some of them require different kinds of suction power.

31:07So we're like, look, just the way our brain thinks and our fingers sort of adjust how we should do the task. Why can't we build a robot that can dynamically adjust based on a floor type? What kind of suction power it should use? What kind of brush roll speed it should use? And because it has an actuating cleaning head, it can go up and down just to the right amount of thing instead of squishing it. Ideally, you know, you've got your list of all the problems. But hopefully not everyone has done things completely horribly wrong over the course of the history of vacuum. Sure. So what things were you able to learn?

31:38like with Dyson they designed you know handheld vacuums a lot of them that are like delightful to use like they're really delightful use but it's not even necessarily you know that solves like the enjoyment of the the actual taking the action and cleaning your home but maybe you don't actually want to clean your home maybe you just want the home clean and so what were you able to take that was like good learnings and adopt into your product I think there are some ones the one that we really like and I didn't know about it until I started doing research as me it's a European brand but they are actually very well liked and very well loved vacuum and those who use it swear by it and it's because they're quiet and the air flow is great and they're very gentle on your floors and carpets so that one is something we kind of looked at and said okay that's a good inspiration but ultimately and Dyson was great from the perspective of branding perspective design there is a distinct identity to it which is really really cool but at the same time it wasn't something that people swore by the way iPhone did.

32:37So there was an element of saying that, okay, what are the products that people absolutely love? Like, why do people love their Model Y or Model 3 or Model S in an absolutely fanatical way? And how do we do that? And how do we create that bond with the product? So those were some of the things we had been thinking about along the way. But obviously, Dyson suction is amazing. If you really want to clean a sandy rug, that's the best vacuum you're going to get for your money. if the suction power is the priority. But if you're trying to build a robot, a robot is mostly going to clean and it's going to take slightly longer when you're not in a mode of cleaning.

33:13And no one likes noisy guests in their home. So if you build a quieter robot, then people will use it all the time. And then you can get to this perpetual clean point of view, not once a day or once a night, which is can you continuously clean? And actually the inspiration of Continuously Clean came from this movie Passenger with Jennifer Lawrence and Chris Pratt. And they're on this spaceship. Yeah, exactly. And Chris Pratt, he wakes up. And after three months, he's kind of bored. And then he's eating in a cafeteria and he drops cereal. And this vacuum comes out and just immediately cleans it.

33:50And then he's like, hey, hey, stop. I want to talk to you. And he goes away. And what he does is he picks up a spoon of it and then drops it again. And it comes out. And I remember like, oh, continuous clean. Like it should just remain pristine. So that's where the idea came. But once the idea came, actually we realized this was also true for India. So what I mean by that is the way to think about that is in India or any third world country, you can afford domestic help. And we could afford it even as a middle class family. And I remember that my clothes not only got washed every day, they got ironed every day.

34:28Homes get broomed and mopped twice a day. dishes got cleaned after every single meal because there was a physical human being matching the entropy as the homes were getting dirty and clearly we can't do that everywhere in the world so robots are perfect to do that they don't get tired they don't get bored so they can just do the same thing over and over again though and that allowed us to live there but then we also realized on a flip side that every single appliance built in the United States and first world are built as a batch processor and what i mean by that is you have to collect your dirty dishes until dishwasher can be full and then clean them you have to collect laundry till laundry laundry is completely full yeah yeah yeah so it's like because you're trying to make sure that you're using it efficiently you're collecting entropy and that doesn't make sense like if you want to just clean one dish you're shit out of luck if you want to just clean one piece of cloth you're shit out of luck and you got to just do it manually but because same thing with a floor you just collect entropy a bunch of shit like exactly about exactly because you don't have a time you only have time over the weekend especially busy parents they may not have time to continuously clean and kids are you know kids are kids and pets are tornado of entropy generator the rate of entropy just skyrockets the moment you throw kids and pets into the home so that's where we realized that how do we build robots that are continuously cleaning on our behalf because when our homes are clean we feel this peace this zen but then only last for a few minutes because homes are constantly getting and the radianthropy is always there.

35:57I wanna talk about, even though you didn't necessarily ship product, you did iterate a huge amount. And I assume that you had this operating in your own home or somewhere else. From what I can tell, the very first version right next to you is made out of wood. Yeah, that was just like a student project. I don't think any mechanical engineer would lay claim to it. That was just me and Nounith very early on tinkering, and then we had a couple of interns who were tinkering with us. And we just said that, okay, let's just build a robot. And what does it even take to build a robot? Because we had no prior experience in robotics.

36:31We were computer vision guys. So we just sort of built it that way and see if we can make it even work. And then we were like, okay, we know how to do it. So the next three prototypes, the white ones and two black ones, those were some of the proof of concept prototype. And proof of concept was that can we make it quieter? Can we build at that time where like maybe we need cyclone vacuums, so we also build cyclone vacuums. Can we make sure that just with two RGB cameras, we can map and navigate and teach a robot how to behave intelligently? Can we build an interaction method on it? So even in that prototype, we built voice and gestures interactions there, which we haven't shipped yet.

37:08But we kind of pointed out and proved to ourselves that, yes, this all can be done. Now we just got to do it at a level where it scales and just works again and again. And then we went out and did a lot of research from users' perspective. And we realized that most people actually don't even want, so this robot vacuums are built with this metaphor that I want to clean my entire home. Actually, most people don't want to do that. Most people on a day-to-day basis don't clean their entire home. They just clean their living room, dining room, family room. Or they like see. Exactly. The attic is always completely messy.

37:42Yeah. So it's just like things that they're constantly getting dirty versus, you know, your bedroom, which will get dirty. But once a month or maybe once, two months is enough or once a week is enough, depending on how often you want to do it. So we realized that the living area, which is kitchen, dining room, family room, they were always getting dirty much faster. So can we clean it from that perspective? So that was another one. But then a lot of homes were so Roombas and vacuums were obviously invented in the world. that was wall-to-wall carpet in late 90s. But over the last 20 years, everything has shifted to hard surfaces and thick pile rugs and wires and thresholds.

38:20So wheels needed to be bigger. People also wanted mopping. So we just sort of kind of understood what users wanted and then kept iterating. And initially, we did two separate iterations. We said, okay, we're going to actually build mechanical systems and that will be separate than actual vision and intelligence systems. So first robots, we just wanted to use a remote control and say, if we even have an Xbox remote control paired with it, can we use that to control? Does it clean well? And it was this idea that, you know, when was the last time truly great mechanical engineer looked at cleaning systems from scratch?

38:55Well, that was probably Dyson 30 years ago, but the world has changed, so how do we build it? Same thing, which is when was the last time someone really redesigned the mobility system of the robot? Because every single robot vacuum is exact same set of wheels and exact same set of bearings. So can we switch that so it can go over thresholds and rugs very well? So there was an entire design. We used to have this diagram which felt like five different streams. One stream was ID. Another stream was perception. Another stream was app. Another stream was hardware and within hardware, M, E, N, E. And the idea was that we each work individually and eventually the streams connect.

39:32How did you initially interact with users? Did you just go and ask people how they used their vacuums? So first was just reading every single review and feedback I could find on robot vacuums and history of robot vacuums and history of vacuums, just understanding how they evolved and why they evolved. So that was one. The second thing was at some point doing research that what is your need? You know, what are you looking for? And realized that the target customer for us was families like us. And families like us were especially busy parents with kids. for them the biggest pain point was day-to-day cleaning it wasn't even a deep cleaning because they almost always could afford or would hire someone to come and deep clean their home once a month or once every two weeks so it was just this day-to-day cleaning where instead of spending time with kids they're cleaning floors because kids sit all the time or they're they're wiping tables so that daily chores is what we really wanted to go after and that's how we started thinking about it and then along the way it was just using the product in our own homes then once we got to a point where we could showcase it I believe I went out and did at least 50 different home demos in different homes but it was both it was dual alternative one was to just show the product and have them to react but two I wanted to see if it's working in different homes as well so in the context of this demo we got to understand that it is working in a bunch of different homes and then we at some point did about 20 first initially 20 customers we gave them the robot and they used it for a year and then we build another 70 and give it to early set of customers so just kept increasing the amount of customers who were a product and then seeing their reactions and some people like first 20 products we ever shipped were really really bad and was this just like for free just just for asking yeah and and and we actually divided so first initially was free then we're like okay let's get five customers who are actually paid and let's try them and see if they're keeping it so just kind of slowly slowly increasing the stakes if you will to test and but first products wouldn't work in low lights first product wouldn't work in night light it would get stuck randomly they were just really bad and then some people obviously stopped using it but then there were a set of customers who just kept using it in spite of it being so bad they just figured out when it works extremely well and they kept using it and they kept using it for a year and in many cases even refused to return the robot to us even when we had a newer version they're like no no no i want to keep this janky version and i was just like upstairs they figured out what what it would do and what it would do and when it works and they're like oh i'll keep it in my different floor i'll put it in my basement but i don't want to give it back to you and that was really the interesting part we're like whoa like here's the product that is not good in our imagination and people are still loving it so that's what was your kind of the brick idea that it just it just problem is so intense that people don't want to uh just clean it all and even if it works 50 of times they're pretty happy you know you said the first 250 iterations yeah basically like completely 3d printed correct um why did you kind of make that decision and how did that enable you to you know iterate faster and and that was that was really that's a great question but it is that quote that hey we want to iterate faster and everything is in iteration.

42:48The reason we did it for two reasons, which is if you try to injection mold any of the parts, even soft mold any of the parts, it's expensive. It also, because we don't have really a good manufacturing industry left in the United States, a lot of times you have to go outside of the country or get those parts from China or different parts of Asia or different even states in the United States, maybe Detroit has something there. But all of that takes time and that time that you have to place the order. Not only it's expensive, but it takes longer to come here. So 3D, the idea initially was that can we just 3D print and iterate faster?

43:24And luckily for us, just around the time when we started, 3D printers started getting really, really good. First ProSauce and then now Bamboo's. So it was very easy to just build it from that perspective and say, okay, let's make sure that our design is functional. And once we got to a point where it was functional, That's when we said, okay, now is a good time to start thinking about injection molding. So it was both doing it cheaply and doing it fast. And how do you do both? How much did you spend making those first 250 iterations prior to doing the first injection molded model? So overall, we probably spent order of magnitude less money than companies, or maybe one-sixth of the money that companies typically spend in getting to this stage, especially hardware companies.

44:11We're still about 70 people team entirely, vertically integrated. Typically, companies get to about 300 people by the time they are at this stage. So we know that we are one-sixth of the size. I want to say maybe around like$15 million. Yeah, I don't have exact number, but that was the total burn as we iterated through those first years. But it's still relatively cheap considering how much robotic companies are raising these days. Did you end up ever going to China? Because I know that you are like most of your parts are like assemblies are coming from China now. Did you end up going to China and talking with a bunch of suppliers and factories and stuff?

44:50Absolutely. So we have, you know, we actually have team in Hong Kong and Taiwan now. We did go initially. I think the first time we may have visited is probably 2023. So we're actually spinning up the supply chain. Yeah. Once when we got to injection molding, it just made a sense. Because even if you try to do it from the U.S., sometimes you just get vendors who themselves get parts from China or different parts of Asia. And initially, a lot of supply chain was China. But actually, over the last year, we've switched it out. And now we go to Vietnam, Taiwan. Malaysia is another country from which we have CMs in.

45:28We're also trying to spin up Mexico. So there are different parts that we go and try to figure it out. How much of the product did you actually have to make from scratch versus, you know, parts off the shelf just happen to be there? Great question. I think as much as possible, we try to use off the shelf parts. But the type of product we build, as you can see, hasn't been built before. There is an element of building custom parts, but things like motors, things like batteries, things like cameras, these are all off the shelf. We didn't want to use any of the things or even, you know, PCBs or I guess NVIDIAs, GPUs.

46:00So anything that we can buy easily from outside, we would do it. We didn't want to create custom sensors or custom parts in that scenario. The plastics and the shape of the robot, those are customers, but that's where the design comes in. I imagine if you're going through like hundreds and hundreds of iterations, over time you kind of have these probably like serendipitous unlock moments where you notice, you know, something's fundamentally shifted. Yeah. What were those? The moments I remember the most is first time it cleaned. So just using even a... How many times did it not clean? it's like being able to just move this up and down which is you have this vision and you put it together and it cleans but it cleans in a lab environment if i can take it home and just even with the remote control if i can drive it and cleans and room felt clean and and we always kind of joke that and and that the first customers are obviously of our better off a better house and our wives so if you can't make them happy and if they're not happy with the cleaning performance we have a terrible product because they're biased and they're willing to love our product.

47:02So that was the first thing when we would use it. There's the mom test and there's the wife test. Which is, is she going to love it? Is she going to be happy with it? So that was the first one. Then the second time I remember like the other unlock moments where when all of a sudden it would navigate under very sort of complex environment. And in their case, just a dining table with chairs inside it and just navigating around and weaving around it without bumping it was really cool. Like anytime a robot goes underneath the table and finds its way, it's really, really cool to me. So that was amazing when it made some of those very, very human-like turns or car-like turns into it.

47:37So that was really cool. The third, and then the one that I remember the most was, I remember first time I got a bag full. It was a really, really exciting thing that not only I've used this robot, but it cleaned enough that our bag is full. And I brought it and showed it to the entire team. when he's like, okay, this is the first bag. And I took the picture. And it's this proof that robot works. Well, how long did it take to get the first bag full? That was probably 2023 January. So six years. Six years, yeah. Six years to get one bag. Six years, one bag, yeah. Do you guys track how many bags?

48:08Like, I imagine, you know, every single bag you guys are personally shipping. So you track like over time. Over time. So now on average, people use about two bags a month. But we've been like, I think we're going to end up shipping somewhere around 17 ,000 or 18 ,000 bags over the next few weeks. So, yeah, a lot of dirt getting collected and thrown away. We clean about half a million square feet a day now. And all together, we clean 100 million square feet. Do you have any context on how big a house is typically? Like how many square feet? An average house is at like 1 ,000 square feet? Around 2 ,000.

48:412 ,000? Around 2 ,000. So it's like roughly 250 houses a day getting cleaned? 250 houses kind of spaced to getting cleaned. But once people put furniture and stuff, it's very narrow space and people don't use it. But on average, people use the product seven times a week, so almost once a day. They clean that entire space once a day, so that's great. And as I said, we do about half a million, two million square. We've crossed 100 million. And altogether, I think Robot has driven 75 ,000 miles inside homes. I love this line from Brian Chesky where he's trying to design the 11-star experience. Like the 10-star experience is everything goes right and it's perfect.

49:17But then the 11-star experience is like assume not only, you know, what is almost like impossible today, but hypothetically it would like delight customers and stuff. What is the 11-star experience that you're trying to drive towards? 11-star experience that we're trying to drive towards is the robot comes into your home and says, hey, Ty, this floor cleaning thing, I got it. You never have to worry about it from this moment onwards. If it turns out that there is a stain that I can't clean, I'll tell you about it. If it turns out that there is a home, a room to one of the room door is locked, I'll tell you when to open it.

49:49I'll tell you when we haven't cleaned underneath the table and moved it out of the way for me to go clean in two weeks or three weeks. And ideally, when you're sitting in a home relaxing, it says, hey, Ty, I really need your help. Can we do deep cleaning today? I think it's required. So this idea earlier you alluded, the cognitive load of keeping floor cleanses robots. It's not something that you ever have to think about. And that's really interesting because very early on we realized that we as humans are creative species, not repetitive species. And if we can give people their time and energy back, then hopefully that would result in much higher productivity.

50:29And that's precisely what has happened in the history of civilization, that you see productivity to be pretty flat until 1900 arrives and it skyrockets with the Industrial Revolution. Not only that, but one of the stats that blew my mind a long time ago as we were doing research is that if you just dial back 100 years or maybe 105 years now and look at 1920, on average, people had traveled 30 miles from their homes. Now, you're from Alaska. I'm from India. We're in California doing this. Can't even fathom how that world is. But that changed because traveling through plane or trains or cars became much, much easier.

51:08So technology shrunk the distance and gave our time back. Because otherwise, it would have taken years for us to go from, you know, even on a land from Alaska to California. Correct? You no longer had to, like, get on a ship and experience the treacherous waters of the Atlantic. Exactly. So that just blew my mind. So it's like, okay, if you can shrink time or basically give people their time back, then they will use it for more productive means. And that's the hope that how do we enable customers to be a person of their dreams, whether that's better parents, better caretakers, better artists, better singers, better piano players, whatever they wish.

51:46Over the course of, you know, the six years where you're just tinkering kind of in darkness before things have shipped, what were the biggest moments of just like extreme pain? There were a few. So first one was when the pandemic happened. I remember in March of 2020, we had no idea what was going to happen. We shut down because we didn't know COVID was there. And we hadn't raised a lot of funding until then. We were still relatively bootstrapping and had some angel investors. So I remember thinking, wait a minute, if we shut down for a year, what happens? And then we thought maybe we can make it work.

52:19So I know a couple of engineers who took 3D printers in their home and tried iterating. But then in June of 2020, we got back to office. Within three months, it was clear. That's actually really fast. That was really fast. So by May, there was enough literature out there that said that you could safely work with the mask on. So in June of 2020, we came back. And part of the reason we came back is because we just weren't making enough progress. So the question was either you go back to the company and wear masks and work that way. And we did that for about a year and make progress or you die. And so that was one really scary moment.

52:56The second one was a different one, which is there are times where you don't anticipate certain challenges. So I talk about this a little bit, but one of the fundamental technology that allows a robot to know where exactly it is inside home is this algorithm called simultaneous location and mapping SLAM, right? Now SLAM algorithm theoretically were solved in mid 80s. And there have been tons of SLAM implementation since then all the way till 2000. So one of the problem, one of the assumptions we made when we started this company was that SLAM is a solved problem. There has to be some open source library that is doing really, really well.

53:35We'll use it. I think it took us entire 2020 and working on an early part of 2021 to realize that none of the slam open source libraries were even remotely good enough, that they were sort of 80 % accurate at best. And then we decided to just write the whole thing from scratch ourselves and use a bunch of neural network techniques as well as classical ideas. but we got it to a point where I believe our SLAM system at the moment is order of magnitude better than anything out there. And that was just pure grind of three years. And the way I describe that is a sort of iPhone with like touch interfaces pre-iPhone and post-iPhone.

54:17Which is touch interfaces did exist before iPhone, but you had to, you know, jab your finger with all the power you can muster or you can smack those styluses in order for input to come. And then iPhone came and it's just beautiful and it's silky. It's almost like you forget. You forget. Like beforehand, if you're using a stylus and you're slamming your phone. I remember this when I had my first Kindle Fire. Yes. It wasn't super great. Yes. And it would miss a lot of the actions that I was trying to take, which completely sucks you out of whatever you're trying to do. Exactly. And it's very frustrating.

54:47And that's how robot vacuums are. There is other part of it, too, which is something that not just most robot vacuums, but any indoor robot. If you go and look at any indoor robot, they can map and navigate, but those maps are like blueprint plans. They don't have contextual awareness. But the part that is actually worst is that if you'll see their demo, they almost always start from their dock and build a map. That's because dock is a reference point. So these are relative maps. To us, that was always a wrong way of doing it because that's like saying that I can only navigate my home if I enter through front door.

55:19Like I'm from Alaska and I can't navigate if I don't understand where my house is in Alaska. Yeah, exactly. Just like I can go through front door. If I came through side door or back door, I don't know. Or if I didn't go through Canada, I don't know how to navigate. There is no around way, right? That doesn't make sense. So we wanted to build an absolute map, which is just like human being. You're in this office. If you're walking around, if I blindfold you and take you to the manufacturing area where you've been only once, you'll immediately know where you are. So can we teach a robot to do that?

55:50And there is entire classic kidnapping a robot problem in computer vision. So we wanted to solve this in a very, very meaningful way. So that's where we pushed the needle. So that was really tough. That took us much longer. So that was one of the reasons why we had to keep it trading for so long because software turned out to be much harder than we anticipate, precise precision. Was the hardware easier than the software for this? Hardware, I don't want to say easier, but it was ahead, which is it was building hardware or building vacuuming system. It is hard, but it is deterministic. It has been done before versus what we were trying to do with this robot, just vision only system for indoor world hadn't been done before.

56:29So that one is slightly, we didn't know when we would get there. It was indeterministic. I think this is kind of like the Tesla situation where I remember Elon came out and said, we're not going to, we're just going to delete all the LiDAR from the cars. I mean, they had for years, they were building this hardware with the understanding that they would have LIDAR. They were even trying to create like invisible LIDAR. They would create like little spots on the car that the LIDAR could see through that you wouldn't even notice. It was, you know, there was no interruption in the paint. But for a long time, you know, he was kind of like shamed or people like to poke fun at him.

57:03And then it kind of worked. Like eventually people are driving around, self-driving cars. Yes. What was that like for you? Did you have people that were kind of detracting or giving you negative feedback on that? So there was this, I don't think people were detracting, but there was this thought process that, hey, if you just add sensors, you can move faster and you can get there faster. And if you just do that, it will work. But it's not just about making product work. It's also about making business work. It's also about making sure the customers would buy it, correct? Now, first Roomba, so the misconception is that Roombas were the first robot vacuums.

57:39They weren't. There was a product from ElectroLux. They actually created this disk robot and built a robot. and I think it came out in 2001. I'm forgetting the name of the product. But it was priced at$1 ,400. And it failed because back then$1 ,400 was obviously a lot of money. So then Roomba and iRobot built it below$200 and they priced it at$199. Now, you know, any guesses why they decided to price it below$200? I'm not sure. So it turns out that, and this is psychological barrier kind of thing, but it turns out that below$200, you don't have to ask permission from your wife or significant other to purchase a gadget.

58:17Has there been studies done on this? Yes. So they did, they actually, that was the thing that they actually, I remember talking to Dr. Rodney Brooks and they did that study and they actually wanted to price it at$149, but then it got a little expensive. So they ended up doing it at$199, but that was the threshold. Then I've also heard from someone at GoPro before that if you build a gadget, any kind of gadget, which is priced somewhere around$100 and$200, bucks that's a toy money you'll have 50 000 people on internet absolutely buy it but as you go above that price point things change a little bit so we knew that you couldn't have a robot that is really expensive there was a second element of it as i said we did a lot of research and understanding of it and if you take a step back and think about it there is literally zero ubiquitous consumer electronics device that's priced higher than two thousand dollars beyond two thousand dollars you're in a prosumer space where professional gamers might do it or professional graphic designer your market shrinks by like over 10x exactly only thing that consumers pay that is higher than two thousand dollars is cars cars after 100 years of utility which is you don't have to no one questions why i need a car or whether it's going to be useful or not so after 100 years of proven utility proven usefulness, it's still not an impulsive purchase.

59:36If you're trying to buy a car that is costing$10 ,000 or$15 ,000, it's still a considered purchase. You think twice, thrice, four times about it. So if you're building a robot and if it's not going to be priced cheaply, it's game over. And we observed that there were Kickstarter campaigns after Kickstarter campaigns where robots would get funded, but by the time they were supposed to ship, either they never shipped or they were prohibitively expensive and that just killed the market completely. So we knew that we had to make this robot affordable and accessible on day one because there are a lot of these robot vacuums at$800 price point.

1:00:09And if it came out and wanted$8 ,000, it wasn't going to work. And the thing with the sensors is, and this is something we learned from Tony and Matt at Nest, but we had this rule of thumb that a single sensor you add in a hardware, assume three software engineers on a flip side has a permanent cost. So more sensors, bigger the team. More sensors, more calibration. More sensors, more complex the supply chain. Higher the bomb cost, more complex the manufacturing. More failure points. So with each sensor, complexity actually rises exponentially. And so we came to a conclusion very early on that either we're going to make this work just using RGB camera and absorb complexity in software, or we won't be able to build a product that is commercially viable, economically viable.

1:00:55So we made this bet along with Tesla that vision-only robotics is the only way to make products viable. And so that's where we really went after. I know for you, even if you are going to be kind of in darkness for a very long time, you do really want this like fast iterative loop. How did you kind of keep pressing on the gas, even if there's not a really obvious metric to look at and point at and say, this thing is going up into the right and we need to make it go faster? I think we did come up with certain metrics to go do it. So first one was like, let's just make a robot work mechanically and let if it cleans right or let's just have a robot map my home.

1:01:32but I remember for the longest time I just kept saying that hey let's just clean a rug can we even clean a rug let's say there is no obstacles in it is it going to work autonomously then can I just get a robot that cleans my room with all the obstacles in it without getting stuck so it's just like how do you take this which is constrain the problem in a very minimal way and then keep solving it so initially we're like we're going to build map manually and if I have manual map built, will it clean? If the answer is yes, now actually build map autonomously, then we're like, okay, it's going to clean carpets very well.

1:02:09Can we clean carpets and hard surface-oriented room very well? So it was just again and again, which is constraining the problem. So when we started shipping in November of 2024, our robot actually would not clean edges of the rope. It would only clean interior. It wouldn't even clean underneath the kitchen cabinets, which is referred to as toe kicks. all those things we shipped after we shipped the robot so that was just softer updates but it's like arbitrary constraint not arbitrarily but functionally constraining the product and saying can we just do this let's get there and then we add another layer another layer so it's this idea that you're trying to climb quote-unquote my mount Everest if that's the way you think about zero to one product what is base camp one what is base camp two what is base camp three can you define those milestones and can you hit those along the way so you know that you're making progress yeah it's a little bit like understanding that this is the first version is not necessarily the thing that's going to be mass adopted but that gives you enough data to get the second and the third and the fourth do you when you have that kind of philosophy what was the first version that you were saying we're going to ship this it's not going to be perfect we're also i think a lot of especially like ai products today like people will come out the gate and they'll promise basically like this perfect solution to you know a plethora of different products problems how did you think about basically distilling that down and saying we're not gonna do a million things we're not gonna do under the kitchen cabinets we're not gonna do under the needed you know underneath the couch or whatever but we are gonna do a few things really well what was that first set of things that you decided we're gonna promise us that's that's a great question actually I'll take a step back I think one of my favorite quotes I ever is that was by Jack Dorsey and he always talks about this idea that you You have to make every detail perfect, but minimize number of details.

1:03:52As much as I knew this quote is actually extremely hard in practice because you just sit there and say, wait, how do I like really you're going to ship a robot that doesn't clean edges? What if most of the dirt is edges? Then I still have to manually do it. Why would people buy it? So it's really hard in practice. And then I remember reading this essay. I think Paul Graham has this essay, like 16 mistakes you make as an entrepreneur, 18 or something like that. And number three is shipping too early. And number four is shipping too late. Okay. So how do you get it right? How do you get that thing in the middle?

1:04:26And the answer is we didn't get it right. We had to ship partly because after six years, there was this gigantic pressure of we just got to ship. We had also announced our product in November of 2023, and we thought we would be able to ship it. So along the way, we switched from Ambrella as a SoC to NVIDIA. That's a separate story. But because of that, we were six months more delayed than we had anticipated. So there was also this intense pressure from customers who had paid for the robot and reserved it and saying, when is it coming? You guys are never going to ship. So there was this intense pressure of shipping.

1:05:00And then we're like, OK, we clearly don't have edge cleaning. We clearly don't have this. Maybe we reach out to our customer base who have already placed an order and ask who is willing to take the robot as it is. And turns out there are a lot of people. Some people say, hey, I'm going to wait for another three months. And some people say, nope, I'm ready. Just ship it. Did you like preemptively just say like, this is what we, our robot can do. This is what it can't do. This is what it should be able to do very soon, but it just can't do it right now. Correct. We did that. We went into customers and we were very direct and very honest that this works and this doesn't work.

1:05:33And if you really want, care about what doesn't work, please don't. But if you want to be an early adopter. But if you want to be an early adopter and you just want to try it out and you want to take it as it is, we'd be there to support you. We'll iterate. great, you know, you'll see us making progress right away and you can start taking it. And many customers who are just early adopters and especially those who are understanding on how hard this challenge is, they took it and they've been extremely helpful. And they're like, yeah, I see it. I'm happy to wait for next software update. And then they give us a lot of feedback.

1:06:04So there are many customers who want to help you innovate. There are many customers who want to be part of community. And if you can find them and if you just set the right expectation, they will actually help you. You know, one of my favorite product of all time and favorite company of all time is this tiny burger place called In-N-Out that no one ever talks about. And the reason I find it absolutely amazing as a product is because it's a freaking burger. It's not a rocket science. It's not taking, you know, Starship to space. But for 80 years, they've never changed a menu. They've never changed anything about their process or stores for 80 years.

1:06:41you've never seen any advertisement for in and out anywhere yet each in and out store does 10x the revenue of each mcdonald's stores and they have gone through three generations of owners and it's it's gone from literally 1950s which is completely different world and it literally started 20 miles away from where mcdonald's started in los angeles and how do you build a product that 80 years you don't change anything and yet people still love it and they just rave about it and sometimes it is just making a promise and meeting it because most products don't most products over promise and under deliver so if you can just make a promise and deliver it in a meaningful way consistently that's good enough um that's where we were talking about starbucks earlier chipotle you know no one will call chipotle the best burrito in the world or no one would call starbucks the best coffee in the world but they make a promise and they deliver it consistently in terms of the taste and price point.

1:07:35In the same exact way, if you can just do that, it's really, really amazing. And that's actually much harder to maintain over time. Yeah, I actually think that Chipotle is an interesting example of kind of a company that probably fucked up in some way. And the reason why is because a couple of years ago, I remember this idea of like a Chipotle burrito is you got your burrito and it's going to be like this big burrito and you get a lot of food and all those things. And then over time, like the portions kind of started getting skimped. And then, you know, online people would, you know, they did this study where if you recorded the person making your burrito, on average it was 50 % bigger than if you just asked them for the exact same ingredients in the exact same way.

1:08:14And so there was that big of a difference. And of course, like over the course of, you know, the past probably like 10 years or let's say seven years, over like people, millions and millions of people are seeing that in their mind. And like the erosion of the customer experience, like no one goes to an in and out today. and says it's a drastically different experience than it was 10 years ago. That's correct. Which is at some point, if you do not, customers are not stupid. Customers are really, really smart. Every single one of us expects what's going on. This is not 70s where you can just create some advertisement and people will trust.

1:08:46This is the world where people have expectation and they observe it. And you were correct that if you trust in a very, very small way, it will backfire you. Debt by a thousand cuts. Yeah, debt by a thousand cuts, right? And then there is also a bit of a, I also dislike this idea. So, okay, I'll take a step back. What I've learned over my career is that there is no such thing as a perfect product. It doesn't exist. Perfection is a mirage. But there is a simple product and a complex product. And simplicity is much, much harder to maintain. So In-N-Out has kept that simplicity. A lot of companies fail to do that over time.

1:09:21One of the points that I always make is, you know, I have a, my dad just passed away, but my parents were in 70s. My mom is 75. My dad was 80. And they would visit from India. And every year when they came back, Uber app is different. And every year they come and iOS is different. And a lot of it is just basically designed for design sake versus genuinely making it simpler or better. And that always bothered me that why are we changing things that are not needing to change? So there is a bit of a sort of this, you know, arrogance of design. and I don't mean to criticize anyone, but there is this element that we need to learn that simplicity is the goal, not perfection.

1:10:04And you shouldn't keep designing things or reinventing the wheel to get to that sort of newness, just kind of teasing them. Counterintuitively, if you have a complex product, you know, like let's say the Apple phone, it's not super, it's not extremely simple, but people over the course of like a decade plus learn to use it. I remember they came out with the Apple Glass update where it's just like they also like do a whole bunch of redesigns on like the photo app and all these other things and I'm like we've already trained our grandmas and grandpas you know this process of helping them understand their their their device and suddenly just created this like Matt you know just taking a grenade and just dropped it and all that it's nicely and it's it's uh I think they just pulled a Chipotle and just like destroyed eroded a lot of customer value correct because part of it is just that consistency consistency It's hard, but don't change things.

1:10:56So, you know, at least in 2017, when we were starting out, I created this sort of like a number line where you have complexity on one side and simplicity on the other side. And what I did was I said, let's take Facebook apps and add them. And in 2018, at least, I felt like Facebook was the most complex app and then probably Facebook Messenger and then Instagram and then WhatsApp. and WhatsApp today is still probably the simplest one. And the way I kind of think about it is if you tell people, why do you want WhatsApp? Or if you sort of living under the rock and you downloaded WhatsApp today for the first time, you'd know what it's for.

1:11:36It's to communicate with your friends and family, your contact book. You immediately see your contacts, you click on one, and you're able to message. Message, and it's clear. It's not necessarily the prettiest app anymore, but it is simple, and the purpose is still clear. if you look at Facebook, why do I download Facebook today? Is it to connect with my friends? Is it for newsfeed? Is it for reels? Is it for stories? Is it for group chats? It's for, what is it for? Same exact thing. Instagram, when it came out, it was really clear that you got the product to - Like share photos. Exactly. Fix your photos, make them nice, share with the world.

1:12:12Now it's what? Is it about the stories, reels? Is it about posts? Is it about communication? I don't know what is it for. So for a new user, it becomes overwhelming when you actually add a lot of that stuff. So simplicity is harder to maintain than the other way around. I was briefly mentioning like an interview that I really want to do with Paul Derov. And he has managed to create a company. I think it's worth like$40 billion, has a billion users, generated a billion dollars plus of revenue last year. And it's just like he's got a team of 30 people that work on it total, including himself. That's a great constraint.

1:12:43And they're all like remote. Yes. They're all in different places. And the only way that you get hired at Telegram is, is there's this website called contest.com. Okay. And, and basically you have to just solve these like extremely difficult, like coding challenges and all this stuff. And then like the very best of the best of the best that are, they get, maybe get a job at Telegram. But with that sort of product, it's, it's like deceptively simple where you just kind of intuitively understand what it does. And then with Facebook, they may have 120 ,000 plus, you know, people working at Facebook.

1:13:14And what does that do? that says like there's all these different teams trying to create value inside of that company. What does that mean? That means new features, new this, new that. There's only one designer at Telegram and that's Pavel Durov. And that's exactly right. And that was the point for WhatsApp as well, right? WhatsApp was just 48 people when it got acquired for$19 billion. Instagram was just 13 people when it was first billion dollar acquisition ever. So they were simple products and they remain small team. And I believe WhatsApp is still probably the smallest team inside Meta or Facebook.

1:13:43so that that constraints are great and constraints forces you to think there so so when you only have let's say 30 people like telegram you would say that is this feature that's going to help 90 % of my users if the answer is no not build it but when you have you know I don't know 3 ,000 people you say oh 300 million people will actually use it but that's still just 30 % of your million users so you can always frame the number in a way where it feels like it's an important feature but it's really not and then that discipline is really really really hard i wonder uh have you ever seen the uh fuck around find out uh chart yes i wonder if you can kind of do the same thing with like customer experience and the amount change and it's basically the fuck around you know how much do you want to change and how much do you want to see you know impact how people you know customers interact with your your experience it's a i think a lot of people the best way to say it is chipotle or if it is getting away and its stock price at least feels like it is getting away with this, right?

1:14:40Or some other company, if it gets away, it gets away because they almost create a monopolistic environment and you don't have an alternative. And when you don't have an alternative, people keep using it. So that's unfortunate part of it, which is sometimes that sort of behavior where you know you corner the market for loses that mindset as well. But it's discipline is really hard. And I feel like the best companies or the best entrepreneurs over time keep the go after simplicity. How do you kind of distill that in your culture? Because you can kind of keep it in your mind, right? And I know that the best companies, like the torch of the company is kind of carried by the founder, right?

1:15:19The soul of the company. And that's why when the founder leaves, typically the company is drastically different or if they get acquired and they're no longer really the dictator of the experience, they're no longer able to direct it. How do you think about instilling that in your culture of just radical simplicity and trying to make sure that we don't add things that don't need to be added. Unlike Flutter, where we didn't think about it, at least here we sat down and we said, how do we build a company that when it grows up, let's say with, I don't know, gigantic amount of revenue or whatever, we'd still enjoy working in.

1:15:51And what that meant was, how do we make sure that the goal there is also still going to be shipping iconic products, even if it's a fifth, sixth, or seventh product. And for that, you almost have to think of company as a product as well and keep crafting it. And that iteration and crafting doesn't go away. And to install in your culture, you just have to keep repeating and prove it and keep preaching those things even when it's hard, especially when it's hard. And we do that, but it's still hard. I think the company that is a model company, at least in my mind, that has done this very well is actually Netflix.

1:16:29So Netflix is still, so Netflix started at the same amount of time. So we did this experiment. I'll take a step back. We did the experiment. We said, okay, inside Facebook, WhatsApp is simple. Facebook is, app is complex. But can you do that at a company level? If you do it at a company level, what's the measurement? What's the matrix you'd use? And one of the matrix might be that, hey, it's profitability per employee, but that's really hard because of gap and all that stuff. So what about revenue per employee? So at that time in, at that point in time in 2018, we're like, okay, let's take company that has been around for at least 15 years, has been public for a while.

1:17:05It's pretty big. And let's actually figure out which one has the highest amount of revenue per employee. And I started with this idea that it will obviously be Apple because Apple is just so amazing in many different ways. And the products are not necessarily cheap. They're premiumly priced. Turns out it was Netflix when we did that math. And it was Netflix because the amount of people inside Netflix is, I think, I believe they're still around like 11 ,000 or 12 ,000 people versus, you know, Salesforce.com is$100 ,000 people. Meta is probably somewhere close to that. Apple is 200 plus. Google is 200 plus.

1:17:44Microsoft is 200 plus. So there are these gigantic companies. And I bring up these companies because Netflix started just around the same time. And it remained small. And it remained small very, very deliberately. So one of my business school colleagues is a chief product officer at Netflix now. And she told me, Eunice Kim, she told me that there are only about 50 product managers in the entire Netflix. So that discipline is really, really clean. Then another example is I read somewhere that for first 20 years of Netflix life, they used to have a free trial. You went to a Netflix website and you signed up for a new trial.

1:18:25When they decided to get rid of it, it wasn't that you just commented that section out of the code. They actually put together an entire team to delete everything from their system that was around this particular feature that they had. And that's important because what you're doing is by deleting, you're simplifying. When you just archive or put it in a code, you're not simplifying it, right? There is this some stat that Windows is what, 2 billion lines of codes or something like that and you can't really duplicate it or word is that way. So being able to kind of control the beast is hard. So how do you actively simplify it and by deleting things and those were some of the things you have to do.

1:19:08But it's hard. It's not easy. There are not that many companies that got there. I think that requires patience, that requires deliberation. In and out is probably another company that has done that very, very well were kept things simple over the years. What have been the moments in your life where you came across something where you felt like extreme intentionality? I think it started very early on. I used to be very much a movie buff very growing up. And I think movies was my initial passion. I just felt like great stories, even though they were the exact stories that had been told some multiple times.

1:19:43There was just a craft about it. And there was this thing where you couldn't glue. I remember like maybe sometimes in college, I can't remember, but I would literally sit there and watch movies and say, which scene would I cut? Not because, and I had watched that movie five times already and I would sit there and thinking like, which one do I cut? And I wouldn't cut anyone. On a flip side, sometimes I get people mad because I kind of say that as much as I like Star Wars, I would say that Star Wars are the worst edited movies because every single scene kind of stops. and then you see three rockets flying around and big giant ship of Darth Vader and you hear see Darth Vader or big giant resistant ship and then resistance happens but every single scene changes that way so initially I didn't notice it but once I started noticing it it got really I got really mad because I just felt like I left it always destroyed the link of the story that it was episodic it just moved from one episode to another episode it was just tiny shorts that change with each rocket flying back and forth but then it was but even then like star wars for 70s was amazing uh what they did but that's when i think i started thinking about the intentionality it was first with movies and then kind of came to the product after i got hands-on apple products did you take any lessons from steve jobs like did you decide to do anything differently than you would have otherwise because you had him as an example?

1:21:11So initially I came with this idea to Silicon Valley that product trumps everything, that a great product, great experiences are there. I think it was both Apple as well as Pixar. So doing something consistently is really, really hard. And then the first 10, 15, whatever number of movies from Pixar was just so mind-bogglingly amazing and it's not the same Pixar that it used to be that 10 years but how do you do that so that was Pixar story was really fascinating to me as well and there was so much intentionality in every single movie and how do you come up with hits after hits after hits and it's really really hard to do that so that was really then the other story that I really got admire is I absolutely love Harry Potter I've read it three times and the reason I like that is because it took j.k rowling 15 years to write those seven books and each books reveal more about the previous books than you thought it so the the to weave in all these clues where when you read a six book all of a sudden second the second one makes more sense to you that's mind-boggling and to be able to stay with that for seven years and tell that story in a very very concise fashion relatively speaking it's so amazing it's like just adding depth it just adding depth and and and doing that 15 years is a long time so i remember thinking like absolutely that if i think of it as a product like she built this amazing seven book product that is just i don't think you know many people will try but won't come close to it so so that was just fascinating to me so that's where you see the intentionality so if you kind of look for it it's everywhere in anything people do across the board that is fascinating.

1:22:59And to me, I just kind of said, let me just think of it as a product. So I translate everything as a product and then stories emerge, then the intentionality emerge and you kind of think of it. But I absolutely remember reading, I didn't start reading Harry Potter until the sixth book was already arrived. And then I remember being obsessed about it for a long, long time. I love that that's kind of like your favorite story because that translates almost exactly into what you're actually doing at the company level as you build the first product and that product builds on itself. It's just basically like a stepped up version of the first one.

1:23:31And then there's a third version. How are you thinking about kind of planning out this multi-decade journey of building a products company where every single product that you release just adds depth to the story that you've already been building? Yeah. So I think Charlie Munger said it, right? Or someone else said it's that the, or no, I think Einstein has this quote that the eighth wonder of the world is compounding. Anything that you do for long-term compounds, and it takes time, there is no shortcuts. And we realized this because I think I told you that we were part of Y Combinator batch with Flutter in 2012.

1:24:08The most successful company out of that batch is Gusto, the payroll company, which is, I mean, Tomer and those guys have done phenomenally well. But I remember in 2017 thinking that even then it was like five years into it and they were just compounding versus we sold Flutter and it was gone. Same thing, I remember running into Stripes offices I mentioned when there were five people on Ramona Street and now it's a$100 billion company. So you see the value of compounding and this is the lesson that I learned later in my life. Even Amazon, everything store, like Elon's, Tesla and SpaceX, like until 2015, probably no one paid attention to those companies.

1:24:48So anything worth building over the time, we learned that it requires patience. It requires building compounding. And you want to do it that way. So that's where in 2017, we knew that we were never going to sell this company. And the goal wasn't to, quote, unquote, build robotic vacuums. That was the problem we wanted to solve as a step one. But the goal was to, as I mentioned, build products that give people their time and energy back. And we did this research very early on where we realized that families in the United States and Western world on average spend about 45 to 60 hours a week doing home chores.

1:25:24Really? That's 3x bigger than the time your family affair. That's like a full-time job. Yes, exactly. And you don't realize this because you spend 15 minutes here cooking and 15 minutes here doing two dishes or 15 minutes here just doing vacuuming. But it's a consistent time sink. And that time is gigantic. So at some point we realized that, hey, if we can build a product that gives people their time back, that's amazing. And that was really the mission that how do we build products that give people their time and energy back? And that mission was never about just this technology or one robot.

1:25:58It's about building, solving all the problems. And then we kind of laid down how do we solve these problems in a sequential way. And very early on we realized that there are two approaches to do it. One is to do what Waymo, Neuro, Cruise, a lot of this company did, which is build dummy robots and start collecting data and build the self-driving cars. And it takes 15, 20 years to do it. For us, the goal was to build great products. And that's why we like the Tesla approach, because the way to think about Tesla approach is that they're building cars. They're building, they built cars, they sold cars.

1:26:32They have amazingly loyal customers. They are generating revenue. and data collection and building FSD or full-staff driving is an ancillary side benefit of selling these cars. So they are making an impact that they change the world in terms of gasoline engine or ice engine to EVs even before getting to FSD. So how can we do it where we are making sure that we are productizing it every single way? And ultimately, whether your technology genuinely works or not, the test of that is not writing a paper. Test of that is can you ship it to customers and it works. So if we can ship it and make it work, then we won't try or trust to make the second, third, fourth products.

1:27:11For you just internally, when you're deciding whether or not to ship something that you know is not fully fleshed out and you're literally emailing your customers, you know, those first few signups and you're saying, here's what we can't do. Yes. And here's the small set of things that we can. Yes. And if you want to sign up for those small set of things, we'll ship you your product. Yeah. You know, what is going through your mind in making that decision and deciding to just ship? The great part about building companies is that no matter how you get it right, it's kind of mentioned, I mentioned, right, like you have to be in a swimming pool.

1:27:44And sometimes when you're in that swimming pool and you decide to have a courage to go to the deep end, you have no choice but to get to the other side. And that teaches you certain things. And the same exact way was constraints. So the way we think about it is in November of 2024, we had no choice but to ship. And in all honesty, but we had to do that because I had come to conclusion by that time that if we don't ship this year, we don't have a future. That we may not survive as a company. So either you ship or you die. And this is the beauty of startup. And this is why, you know, I love it, which is it's very binary.

1:28:20You ship or you die. You do things with less resources than the other companies or you die. You innovate or you die. Like it's a very binary thing. It's kind of like fighting back against entropy is like the default state is if you do nothing, it just the brand kind of disappears and you kind of disappear. The meaning kind of disappears. So you have to kind of re you have to keep on watering it. Yeah. And like, you know, we do a lot of things because we don't want to die as a human being. A lot of our innovation is just being based on survival. So even for companies, when I sent that email, it wasn't that, hey, which is either customers will accept or we're dead anyway.

1:28:58So it's like, are we ready where customers will accept? It's a pretty easy decision to make. Which is, we have no choice. So you get to a point where you're no choice. And I think I mentioned earlier on to you that if you had come to our office in April of this year or April of last year, right before Wired gave us 10 out of 10 perfect rating, I think most of our team would have told you that our product is actually shit. and people genuinely believe that it wasn't good because day-to-day, you only look at the problems. You're constantly trying to improve it. So you're solving the problem and whatever is done, product does really, really well, gets forgotten.

1:29:31So then you don't think about it. But there are little elements that we always had in mind. So first one was this idea that if it's a robot and if we are building genuinely intelligent robot, then day one, we knew that if you take anything out of the box, it's object it's physical thing it's not smart if it's a robot and it's intelligent it has to roll itself out of the box so that's where some of the idea was that how do you build a box where robot just rolls out and and then say how do you say how do you get people to smile and be friends with it in the first 30 seconds so can we say on a display that hello xyz family or hello uh naryawala family And if you did that, maybe it puts smile on their face.

1:30:13So it was the idea that how do you make it friendly within the first 30 seconds? And the way we could become friends or someone seems friendly is if they come and say hello to you. So why can't robot say hello? And then we're like, okay, a lot of kids still may be apprehensive about it because it is a new object coming into your home. So at some point, realize that, you know what, kids love stickers. So you ship stickers and the moment kids put stickers on the robot, it's a friend instant. before even it moves around. You just built a bond right away. And you personalize it. You actually feel good about it.

1:30:46Like that's how we love our pets. The first thing we do is we name them and we personalize them. We get them colors. We get them things that we want. And that's how it works. So if you just kind of think in that direction, it gives you certain ideas. It was just, yeah, pushing in that direction. When you first started getting like customer feedback from those first few orders, how did you kind of take that feedback and get to the next group of customers where you can ship that future version? I think we've always talked about this internally, that single negative feedback is worth 100 positive feedback.

1:31:23So we had to balance positives, and you can't just play on positives and not worry about other things. But we almost kind of got to a point where we said, no, no, no, give us every single feedback, especially things you don't like. Partly because even when I was doing, as I said, you know, I was going to friends' homes, 50 different demos in real homes. In person, people are super nice. They don't want to tell you what they don't like or like about it. So reality was to say, no, no, tell me what is critical and pay attention to that. Do them like a comment box where they can say, fuck you. Yeah, exactly.

1:31:57Really. And then the second one was also get to, which is when we wrote this email to customers saying that these are the things that works and these are doesn't work. We made sure that we were actually sending that email to customers who had paid for it. Because if you have paid for a product, your expectations are far different than something that's free. And you're far more critical about whether you value that or not. So that was the criteria as well, that if they return it, we know the answer. No matter what they say, if they return it, we know where we stand. So return rate or them just not using the product, those are the signs.

1:32:35So we would kind of combine it with what we expect users to do if they genuinely liked it versus if they genuinely disliked it. Like I said at the start of this, the reason that I came and did this interview is because of the just positive, spontaneous customer feedback that I saw on X and elsewhere. what were those kinds of moments like you know toby lutke uh famously like said matic is a really special company or like where do i buy one uh what were those days like uh it was really really really really uh satisfactory in some ways uh which is so when we started this company both navinit and i also sat down and said okay what are the best days in our career and the reason we and say iconic products is because best days in our career, the most memorable ones weren't the day we started a company or the way we sold company.

1:33:28In fact, what I do remember about Flutter getting acquired or selling Flutter to Google was relief, not necessarily jubilation, right? That was the feeling I had. The jubilation always came when you thought something meaningful for the futuristic or when you built something futuristic and got into the hands of users and they loved it. and that part was really exciting that you craft something you build something you pour your heart into it and then other users get hands on it and it's just amazing so from that perspective when it started finally getting to a notoriety on x or people started loving it it was really fulfilling but it was both surprising as well as not surprising because we we still haven't shipped 50 % of the MLP features that we wrote down back in 2019.

1:34:14So it was surprising that people were loving it so much. And I think it was surprising because, as I said, things that it does well, we just take it for granted because we're so focused on improving the negative things. So it was really amazing from that perspective that all these decisions we took and we were just taking for granted, people are really recognizing it. So that was great. That was absolutely amazing. And ultimately, the reason I mentioned 100 million square feet clean, it's still, So I think, what is it? I think it's like 12 ,000 hours cleaned, if I'm not mistaken. 12 ,000 hours saved, sorry.

1:34:4712 ,000 hours of labor saved, which translates to about 100 million square feet as we kind of do the thing. So that's really fulfilling that you're really attaining your mission. So it was really great. It was really great. And especially because we tried to launch in 2023 and no one gave a shit. And we tried to launch in, we launched again in November of 2023 and no one cared. And I think Brian Chesky is infamous for saying that would Airbnb launch some 13 times or something. And if you, you know, if no one pays attention, then you can just keep on launching. Keep on launching, exactly. So it was really good to finally see that, no, no, no, we are doing something truly innovative.

1:35:28It's not just another robot vacuum that we built this from very grounds up from first principles that is the vision only robot. and all of a sudden everything that we were talking about that, hey, it's sort of like a Tesla FSD for home robots, people started saying that and that was really fulfilling. And fulfilling in a way that, okay, now we know absolutely foolproofly that we're going in the right direction and we absolutely have to double down and keep going. I think probably right now you are at the stage where it's Harry Potter and the Chamber of Secrets, but not quite even past that. Not quite even past that, yeah.

1:36:03What does this kind of look like going, this journey look like for the next, you know, 15, 20 years of kind of adding more lore, deepening the story? How is this going to unfold? I would go back to our sort of axioms and what we talked about, which is can we keep solving more problems? So more than, you know, can we build a great product? it's more along the line that okay if we solved floor cleaning and let's let's say we nailed it completely now maybe can we take it to the next level and maybe we'll do i don't know will it be a toy cleaning robot will it be will it put the shoes back in its place i don't know answer to those questions but what is the next intense problem that customers have that they absolutely want to solve and can we do it to a point where they again have a delightful experience and no longer have to think about.

1:36:53So in that lore, I would love to have a set of pain points that customers have and then say, we take this one and then we take this one and then we take this one and we keep going down. And what we build as a product is just means to an end. So to me, that's how we think about it, that we start with problem first and work backwards versus starting with robots and working backwards, which is, let's say at the moment, and I absolutely love everything Tesla does and everything Elon does. But even if Optimus was available, great. Why would I buy it? Am I buying it for laundry in my home? Am I buying it for dishwashing in my home?

1:37:29Am I buying it for everything in my home? Am I buying it for babysitting or maybe my elderly care? What is the purpose? And it's not necessarily clear yet. I'm sure they have some guidelines and intuition that they're going after. So it's really just productization is the key piece of the puzzle to me. And there is actually a really good, so one part we learned over the years, and this is, I forgot to mention when we talked about SLAM, but initially we got to our first prototype in 2021, working prototype, and it took us another three years to ship. And initially we thought that, hey, we would be able to ship this product faster because mistakes that we make inside home are trivial.

1:38:14but turns out if the task is trivial people's expectations of precision are higher so with today's ai for example we collaborate which is if it gives us 80 percent of the video right we're mesmerized if it gives us 80 percent of the app coded already we're mesmerized and we're happy to take it to the 20 percent or 80 percent of the email is already drafted and you'll do final touches and put it there right so we're happy to collaborate because it takes us years to learn how to code or learn how to be an amazing director or be amazing interviewer so on and so forth but learning how to navigate your home without bumping you don't go to school for that learning how to vacuum you don't go to school for that maybe seven-year-old can do it in a far within a very precise manner so it turns out that if the tasks are simpler people just want to delegate they don't want to collaborate and if you're delegating the bar for accuracy is much higher.

1:39:08So we get email if single popcorn is left behind and says, hey, your robot didn't clean that, it didn't pick it up. And people lose trust right away. So precision bar was much, much higher, and it took us a while to get there. And that's one of the things we're learning again and again, that in this scenario, as we build the lure, it has to just work. People want to be rid of this task completely. And there is a lot more work to be done to get there. I think it's a little bit different with optimus where they're going to implement you know deploy it in their factories and and stuff first and there's going to be real value driving or not you know and they'll know because either the cars will go off the line or they won't but do you think that the model of you basically try to jump to book seven immediately and then you say we're just going to ship this thing and it's going to be perfect does that even work um i mean way more got there so i don't think it's not it doesn't not work it just takes longer time like you can't it's like even Apple started with iPhone 1 even Apple started with iPhone 1 and I'm sure there will be five optimist version but and will it get there sure it will get there it's just a matter of then not if so there is a future in which humanoids are around there is a future in which who's the robot is available the question is when do you get there and and if you're a startup can you survive until then, until technologies to get better.

1:40:31So anytime a startup, you know, one of the questions that, you know, entrepreneurs or at least investors love to ask is, why now? And to be entirely honest, the product that we built, we couldn't have built that in 2012. Technology didn't exist. Computes weren't available. 3D printers weren't there. And one of the actually things that we got really lucky on and one of the things we've talked about quite a bit is that we are entirely Rust language shopped. And Rust wasn't great back in 2012 as well. It only became really, really good in 2019, 2020. So you do get lucky along the way where certain things open up and get available.

1:41:11So, for example, you know, Netflix and Reed Hastings never wanted to build a DVD company. They wanted to build a streaming company. That was the goal, deliver movies over the internet. Like a seamless experience. Seamless experience. But reality is that they couldn't have done it in 1997 internet or even 2002 internet it's only 2005 or 2006 where broadband became ubiquitous and you could do it so sometimes infrastructure has to be around for you to be able to deliver that product experience that we want like you know instacart was tried as web van back in back in early 2000s right or doordash for that matter and didn't work because the technology and infrastructure and the communication devices weren't good enough yet yeah so sometimes you have to have a weight.

1:41:57So I think Anderson Horowitz says this best, Mark Anderson, that as an entrepreneur, the challenging part is that whether they will get timing right or not is very hard to predict. But investors can keep investing in the same idea again and again. And sure enough, Seqoia invested in both Webvan as well as Instacart. So it is possible to go do that. So in that scenario, if you start early then you have to survive now optimus and elon can make that bet because they don't have to worry about survival because they're already generating tons of profits and there is a cash cow but they also have like like you were talking about earlier the muscle memory they have like in in the same thing that you were describing is you guys are like a products company and you don't want to basically work in darkness for 20 years and not ship a single thing and then say here's this perfect thing and then start shipping correct over time you're building this muscle memory of you've built one product and then you've shipped it to 500 customers or three customers and then a thousand and five thousand and ten thousand and a million.

1:42:57And for them it's great because they are the customers. They have these amazing factories. They are absolutely aware of what are the efficient systems in terms of their manufacturing or what are inefficient systems and where human labor is absolutely necessary and where the labor shortage is hurting them. So for them to build Optimus Robot and kind of go after it is actually makes 100 % of the sense because they can build for their needs. And then it goes back to this idea that if you build something that works for you, hopefully more people will have a same exact need and then they will do it.

1:43:28So I think it's brilliant for them. Some of the wonderfulness about the world is that humans are mostly the same. We like to be special and we want to be unique, but mostly we all want Thordash roughly the same way. Yes, yes. Or Uber. Exactly. But startup, like, you know, to kind of continue, we did do, so in 2017, it was obvious to us that if you're trying to build the way Neuro Cruise or some of these companies did, okay, I'll take a step back. The day you run out of money, you die as a startup. No matter how many customers, products, how much revenue you have, it doesn't matter. If you don't have any money left in the bank, you're dead.

1:44:06There's that wonderful line that all startups and all companies die for the same reason. It's just lack of cash. It's just lack of cash, exactly. So my very, very crude analogy for startups is that every startup is a ticking time bomb and the day you run out of money, it goes poof. Now, as long as you're raising funding from outside, you're just adding more time to that clock, right? You're not necessarily diffusing the threat. The only way to diffuse the threat is when you get to cashflow positive on your own. Now you're generating your own cash and you don't need any external resources. So if you're a startup trying to build for 10 years, when you don't, if you're a startup that is trying to build indeterministic product, You don't know how long it's going to survive.

1:44:49And it's kind of fascinating to me when we look at self-driving car space that the only two companies that are shipping and thriving today are Tesla, which has a car as a cash cow, and Waymo, which has AdWords as a cash cow. So both of those companies had these profits that they were making that they could generate. So survival wasn't based on shipping, potentially, and you could keep building for a long time. I feel it's kind of interesting that you say that because I feel like the DNA that both of those companies have is that DNA of shipping. Like you have to ship. You have to create something that's valuable in order to diffuse the clock.

1:45:24And they maybe have these other organizations that do raise like a couple billion dollars without having diffuse the clock. They didn't actually ever build that muscle memory. That's a great point. Honestly, I didn't think about it, but you're correct. Absolutely correct that they actually have a genes to ship as well. That's kind of what I'm saying. It's like, are you doing almost if you just raise a couple billion dollars and you never ship anything? Is it basically doing like an organ transplant of, you know, does it actually like accept? Do you go from suddenly having a culture of never shipping, raising huge amounts of money?

1:45:52Yeah, you don't get there. No, no. That's a founder has to get there. Founder has to do it. Usually, usually it's if you don't have that gene and if you've been in that research lab oriented environment, you don't end up shipping. So with Claude, I mean, with Anthropic and OpenAI, it is an exception to the rule than the reality. But yeah, you're absolutely correct. What thing do you do that almost every other founder that you know doesn't do, but you think is right? I'll go back to what Kevin Zerstrom said, which is think of a product first. I am not, which is we preach again and again and again inside this company that we're solving customer problems, start with the problem, work backwards.

1:46:38Don't build cool, build useful first. These are very, very unintuitive for whatever reason to many, many early engineers in their career because you're just so mesmerized by technology and possibilities of technologies. So for us, one of the things that I do again and again is that, is this really solving the problem? Is this really going to be useful to customers? The other thing that is somehow very unintuitive is putting yourself in the shoes of customers and just thinking, is this complex or simple? Which is asking why? Like, why are we doing this again? You know, why is this simple? Why do we need to have this tap?

1:47:16Or why do you need to have these features? Are you sure we need it? That's another very, very counterintuitive thing, surprisingly. Because most of the time, which is, there was an article from Steve Jobs that I read a long time ago. I can never find it again. But in that article, he talks about this idea that most people think of a solution and they just go build it. And it's like at Apple, we don't do that. We build a solution, we put it there, then we go away for three days and come back and say, is every single feature or piece of button we added to this hardware product absolutely needed?

1:47:52And it's like we keep peeling the layers of the onion until the essence is left. In the same way, we think of a solution, we put it there, and then we keep removing things. to get to the simplicity. And it's like, why do we need three buttons? Can we get away with one? And that requires iteration and that requires time and you have to walk away from the product. And that's actually still very, very counterintuitive. Which is, it's easy to say, oh, let's just add an option for it or let's just add a button for it. But instead, it's very hard to say, no, no, how do we solve a problem where it just works for customers or how do we do the hard work on other side?

1:48:25Well, let's come back to Matic and where you guys are at right now. We're in your office. There's a whole bunch of parts and assemblies and sub-assemblies and all these different things that you guys have stacked around and you're just starting to ramp manufacturing now. What's the journey kind of been like going from having not shipped a single unit to shipping thousands of units? So it's very much fun, but it's, you know, again, quoting Elon Musk, he's right about a lot of different things, especially products. and he has this quote that says, factory is the product. And he always talks about how scaling Model 3 was much, much harder than actually building Model 3.

1:49:04And we are in that scaling hell at the moment. Production hell, exactly. And building something that consistently just works again and again is really, really hard. And we're figuring it out. And I think Namneet has a really good framework for it. So Namneet, my co-founder and CEO, again, He always said that it's very easy to imagine. If you build one product, it's easy to imagine how we're going to build 10. If you build 10, it's easy to imagine how you'll build 100, which is it's easier to imagine order of magnitude growth. But going from 1 to 10 ,000 is hard. That's very hard to imagine. And that's still true in software as well, because even though people build apps, people build websites, if you all of a sudden went from 100 users on your website to a million users, it's going to crash and burn.

1:49:54It requires a different set of tools and systems to deal with 1 ,000 users concurrently on your website. So in the same exact way, the challenges for us has, like we shipped 300 units in Q4 of 2024. We've shipped 3 ,000 over the last two months of Q4 this year. So 10x. So we did AirAuto or Magdeter. Now the goal is to go to 60 ,000 this year. and it's both extremely fulfilling and as well as extremely challenging we were walking around and i think you said that 20 of the assemblies that you're getting from china are basically just malfunctioning or like they don't work in some way um with that you have to get really good at basically unfucking shit yes right so how have you started getting good at that great question so there are two parts of it actually you know to to be entirely honest there are set of challenge or quality issues in your product that at the small scale don't surface so when you try to build thousand they show up a lot more than when you try to build hundred so there have been challenges like that about reliability and quality that as we got to scale we realized so we have to solve that as well but there is also communication things so things that are really really surprising that has happened.

1:51:15So we endured 60 days of camera delay, which our cameras come from ST Micro, which is a French company, really big, really popular. They're amazing. But even they face their own delays. So we endured 60 days of camera delays. Then at some point we get our motors from really popular Japanese company. I'm not going to name them. And they've been phenomenal for or two and a half years. And then all of a sudden we started getting these robots and 80 % of the robots were just failing our noise tests. And then - 80 %? 80%. This is right around the time in May as Toby Lutke and all these guys are trading about as we're getting lots of orders on the flip side.

1:51:56So the fires are just like everyone on Twitter is like, go buy here. Yeah. And it's just like fires are cropping up everywhere. Cropping everywhere. Like 80 % of robots are failing. We're like, what the hell is going on? So initially we're like, we must have screwed up something into our manufacturing process. So we kept digging into it and ultimately realized, no, no, no, that motors that have been amazingly reliable for two and a half years of us iterating, all of a sudden are just noisy. So we reach out to the CM and we said, hey, your motors are noisy. Did you change anything? And they're like, no.

1:52:28And we're like, no, no, no, let us show you. So we had this old motor, a new motor, and we proved side by side that these were noisy. So they started digging into it. And it turns out, unbeknownst to them, their own supplier had changed the glue that goes on the impeller on the motor, which results in higher friction, which results in higher noise. So figuring that out and then dealing with it. So then we had to replace all those motors and we had to fly them in and getting there. So those are all the challenges that you don't think about on a day to day basis as we build it. But those are the things that we really have to think about every day, that things, it's like there is a quote somewhere, right, that man plans and God humbles.

1:53:13There is nothing more humbling than trying to build hardware assembly line. With that in mind, especially for the first hundreds or thousands of units, you can kind of have a much higher touch experience with customers. You can kind of, you can maybe even be personal customer support. That doesn't obviously scale to millions, but you can do it at the early stage. And so when you have a customer and something goes wrong, what is the process that you kind of create to solve that issue as fast as possible? So I think this goes back to our thinking that we never thought of product as just Matic Robot itself.

1:53:50This goes back to Tony Fidel, Tony Fidel's teaching. And he always said that the product entire experience, you have to get the entire experience right, which is from the moment they hear about Matic or your company, all the way till they stop being your customer, which is completely stop using your product, is entirely a journey. And every step you have to get it right. So what happens when they come to your website? What happens when they purchase the product? What is the experience when they ship the product? How do you, how did they feel? Are they, are they feeling like you're being very straightforward to them?

1:54:21What happens when they actually get the robot and unbox them? What is the first 24 hours, first 30 minutes, first 21 hours, first week, first month. And what happens when robot actually doesn't work as it's supposed to work and they've paid for it and now they are in this crisis situation? How do you handle that? And you're not going to get all of these things right. Some robots will ship in spite of your trial with some quality issue, but how do you handle it? It becomes critical. So to me, customer service has never been a separate thing. It's part of the product experience, which means it has to be done in a very, very meaningful way.

1:54:54and every single customer has to be looked at in detail. So we try to avoid, for example, any sort of templates. We try to avoid any sort of cookie cutter answers on how you do it. Every single customer, we try to explain exactly what the problem is in detail because worst is when you call a customer service, then they walk you through a script. So we know what bad customer experience looks like, so we try it. And then at the moment, anytime a customer has any sort of issues that is there, obviously, I can't look at every single customer tickets. But I do get every single one as an email. So I get email alerts on everyone.

1:55:35So as I'm browsing or even. You want to keep a pulse on what's happening. Exactly. So I do do that. And then there is a process we've placed in that anytime you see issues like X, Y, or Z escalated up to me. if customers endured some sort of experience that was really really out of their point of view can we can we go and can I go and reach out to them so every single customers who wants to return a product I reach out to them and ask them why what happened and that's a learning opportunity more to me any single customers there are routine issues there are maintenance issues and then there are issues that were unexpected so I try to go and dig in into why and what happened and we didn't make expectations and make sense of it.

1:56:16What I noticed is you just have a huge amount of reliability and testing before any one of these robots goes out. How did you kind of come up with that process? I think it was all saturation. Even assembly line could be a product. And we just kind of said, okay, what are the point of view? So for example, we looked at calibration, camera calibration. that's critical because if the cameras are not looking at in a right way entire system fails right and a lot of it is because we just keep testing robots ourselves as well and we realize that here are the failure points so as we do reliability testing as we do longevity testing we know what the failure points are typical things are so then you can come up that okay what are the things we can test that would change it and really the answer to the question is that in the first 10 ,000 or 1 ,000 customers are you're going to be your evangelist for life.

1:57:14And if they receive a bad product, they're not going to be happy with it. And if you didn't care. If you didn't care, it's even worse. So we're much rather off taking pain and double and triple check everything and handle them and understand what's needed than we not. And then as we understand that there is a reliability, we can relax certain constraints. But as I said, we just have to assume, go after with this assumption that things are not going to work as well as you want. And at least at the critical point, there are tons of reliability checks, but critical points where the five, six, seven tests we can do that says robot is working exactly the way it's supposed to work.

1:57:49I love this line from Brian Chesky. I don't know when he said it, but he basically said every founder, when they start their company, they like almost unanimously just want it to take off immediately. But there's something special and useful about companies just not taking off and not working for a long time. It allows you to kind of build different muscle and different understanding of the problem and things. And so I imagine that with one of these types of products, it's helpful almost if most of the people that will eventually adopt don't want to buy it day one, because then you can actually spend that much more time and that much more thought and care on those first few orders to make sure that the thing is nailed before you scale up.

1:58:31Yeah, it's actually built into hardware. It doesn't matter how, like, ChatGPT can go from zero to 800 million users in two years. In hardware, it's impossible. There is nothing we can do that will happen. Not only that, but, you know, some of the numbers that we want to shoot for, we have to buy certain parts eight months, nine months, ten months in advance. So even if you get to a point where all of a sudden, like, you know, in May of last year, all of a sudden we saw demand skyrocket. We couldn't do it. Every entire projected sales for the month of December or prior to Christmas that we could have shipped for was sold between Black Friday and Cyber Monday.

1:59:10Just four days. So everything we planned for seven months and I was like, we're going to ship this unit. Turns out demand will be severely underestimated demand and everything got sold in that four days. And then come December 2nd, we couldn't have, if the order came on December 2nd, And we knew, we anticipated that we won't be able to ship it prior to Christmas. So we couldn't really do any push anymore. And we changed our timeline right then and there. Telling people. Yeah. And there was nothing we can do about it. Could we have sold another 2X, 3X more robots? Sure. But you couldn't have sold them in the right by Christmas.

1:59:42Yeah. We couldn't have shipped them by Christmas. So the advantage of hardware is that your supply, if you find a product market fit, you will be supply constrained, which means you are forced to grow deliberately. And that deliberate growth is necessary because every single level of growth uncovers bugs, uncovers issues, and it gives you time to push it. So it's sort of like a forced discipline of compounding, whether you want it or not. It's interesting that you say that because once you hit that inflection point where there's just way more demand than there is supply, suddenly the product goes from being the actual product to being the factory.

2:00:21The factory, precisely. And it's like toggles. Toggles. And when you build it that way, I think that we did this, I don't know when I did this, at some point in 2022, as we were sort of trying to keep everyone patient and make sure the team would remain patient to ship this to, so that let's look at the top 10 companies by market cap in the world today. I think eight or nine are hardware companies, right? From Apple to SpaceX to Tesla to TSMC to NVIDIA. These are all hardware companies. Even Microsoft, you can say it's a software company, but has some hardware components associated with it. So it was really fascinating to see so many hardware companies.

2:00:58And what we realized is that in hardware space, compounding takes a long time. But once you get there, you genuinely have an opportunity to build impactful, transcendent company. And you can get there. Precision software ups and downs are much faster. Yeah, your moat is a lot deeper. Correct. Yeah. I think one of the best moats is just the required pain that must be experienced before the thing can work. And if you have seven years of pain as a moat, that's a pretty good moat. That's pretty good. It's just, so I'll give you an example, and this was a really big one as well. So we, Nest Camera, I mean, when I was at Nest, most of the time I worked on Nest Camera.

2:01:40In fact, I was a product lead for Nest Camera, so that was my primary product, even though I give you the thermostat example. Nest cameras became hyper-competitive very, very fast. In 2015, when I went to Nest and started, took over as a product management, Nest product manager, Nest camera was the only product in the market. By December, they were at least competitive security camera products, 20. And I remember the joke was that cameras flying out of Santa's ears because every week new camera company would launch. But then I remember thinking even back then that, wait a minute, there is literally no competition in nest thermostat in terms of smart thermostat even today 15 years or 14 years after or 15 years after its launch now if you want to buy a decent thermostat for your home nest is still it right and that sort of perplexed me because the the microeconomic principle says that wherever there is a profit competition will enter and nest thermostat or thermostat if you think about it is a no you don't have to go and explain to any user why you need a thermostat you don't even have to explain why you need a smart one because everyone one of us have used the dumb one where we forgot to turn it off or it was too hot or too cold or unconnected one there are 130 million households in the united states and everyone legally lawfully requires a thermostat so here's the clear-cut market clear-cut profitable category yet no one is entering this space and nest is still it on a flip side security cameras most of us actually did not grow up with the security cameras in our homes it's a new product coming into our home many customers are asking why in fact i live in a home in in a cul-de-sac in los altos where previous owner hadn't locked it for 30 years and i remember and the reason i know this is i asked him hey how secure is this home or is this area and he's like well i haven't locked it for 30 years, so take it for what you will.

2:03:34That was his answer. And I remember thinking that, okay, good luck to me trying to sell this guy a security camera because he doesn't even think security is a concern, right? So it was a new product. Yet everyone and their uncle was building security cameras. So it just bothered us for a long, long while. And then we realized that it has to do with the tediousness, unsexiness, and also which acts as a barrier to entry. So it turns out that if you want to build a thermostat, everything is hard, the hardware, software, the screen, making it beautiful, all that stuff is hard. But still the most tedious part is making it compatible with last 60 years of HVAC system.

2:04:08That's a vaca-mole. That's just pure grind, unsexy work. No one wants to do that. Similarly, when we were building smoke alarm, which I told you about earlier, 800 pages of regulations. No one wants to deal with that. 800 pages of regulations? Yes, because each state has a different law. Each state has different things. And then the type of alarm that sounds when you have a fire is very different than type of alarm that sounds when you have a carbon monoxide and how you turn it off and how it's supposed to work and how the batteries are supposed to last and what you're supposed to do to notify the customers.

2:04:40All those rules are preset and they're preset per county and states and stuff. So you sort of have to go through these regulations and make sure you're sticking by. If you're building security camera, you can go to Shenzan, you can buy a camera, it will come with embedded software, you can use open CV to do percent detection and voila you've got a camera. There is no barriers to entry. There is nothing tedious about it. So security cameras was a space that was easy to enter versus here. It was just really tedious. It just sucks. It just sucks. So when we did start building in this category 27, one of the reasons to build this product was also that we just looked at Roomba and we're like, look, they haven't innovated our iRobot.

2:05:18They haven't innovated for 15 years. Now it's 23 years. and yet even though iRobot went bankrupt last year in December, in 2024 they did$700 million in revenue. So if you tell me that I don't have to innovate on a product for 23 years and generate$700 million in revenue, well sign me up. Most companies in Silicon Valley will die to have that sort of revenue. So it was really obvious to us that this was in a very interesting category where no one was coming except for sort of Chinese copycats. But what was even more interesting is that we knew from day one in 2017 that Google wasn't going to enter this category.

2:05:56Apple wasn't going to enter this category. Amazon won't. It's just too unsexy and tedious of a category. And even startups won't get excited about it because if you graduate with a computer vision PhD from Stanford and tell your mom, I'm working on self-driving cars and lane detection, she'll probably say, oh, my son is amazing and cool. And look at this world-changing problem. it's she's working on but then if you go to Sanford for graduate with computer vision PhD and tell your mom I'm working on robot vacuums most likely she'll say what the fuck is wrong with you right so we knew that it was such an unsexy space that no one was going to come and that would allow us to build this amazing product that we want to build and then it's a product that's needed by everyone and we'll have a chance to build a sustainable business which allows us to build second third fourth product let's end it on what's the hardest thing you've overcome?

2:06:50I think my own patience. This is the longest job I've held in my career. I think prior to that, because of acquisitions and everything, the job that I've always held was three years at most. So it's really, really hard to learn to be patient. I'm by definition, very, very impatient. So just being patient with Matic and continuously preaching that, we're making progress stay alive and then keeping that faith was absolutely hard it's not easy and then we've lost some people along the way some people who thought um you know they'd be with that i thought would be with us forever and ever people lose faith it's hard