Formant's Advanced Industrial Robot Management System - Jeff Linnell

What was it that you got exposed for the first time to hardware? You mentioned using Kukan Fanos robots. These are industrial robots that are used to pick up plays or weld or do all this stuff. Can I imagine you use that for animation? When was it that you're like, "Okay, we got to make the jump of quality and go and automate some of the animation." I watched, I grew up with the original Star Wars. I remembered that there used to be a lot of documentaries on this. There was a most patrol rig that was used to shoot a lot of the principal photography for Star Wars. But specifically, the scene where Skywalker is blowing up the dust art, is going through the trench. That was all computer controlled camera work. That was done on a system. It was actually done in Marin, which is about half an hour from here. Those were bespoke machines that were a million dollar robots, essentially, with cameras on them. It was about 2008, the economy had crashed in America. I was shopping on eBay and I realized I buy these industrial welding robots for pennies on the dollar. That mean $10,000. These were systems that should have been $80,000, $90,000. Let's get one. I bought one off of eBay. It showed up on Giant Truck. We had to figure out if it was useful for anything. The thesis was, "Why can't I use a welding robot?" I've seen videos of these things that are incredibly fast, incredibly precise. Why don't we put a camera on that and see if we can do the same thing. 25 years ago, there was an experience of being acquired by Google. All those who have lived this, by the way, I really wanted to know all of the bad sides of it. If you have any, because it's been a while ago, it's been very quick. Google was a customer of mine. We should have videos for that. So we were known inside of Google as people that have this kind of crazy technology, these robots. We were also just doing traditional design work for them. And traditional kind of 360 advertising for Ant-Tradd phones that were coming out. At that point, we did a lot of churnina then. So they knew us. Where are you spending most of your time right now? Very fast. Spending most of my time today in front of a Zoom station, talking to my remote company, we're all remote. So I spent my entire day sitting in a chair staring at a rectangle, speaking to you and being through an artificial interface. What is your advice for a young founder that it's building something hard? Because building is something in an industry that's hard to crack, it's building a solution that it's hard to make. And it's building a team that's hard to put together for mentioned duties. It's a very nice. I mean, a lot of people give up pretty early. And I think that maybe the message here is like tenacity matters. That's the weird wire. And so I heard an anecdote, you know, ten percent of venture-back companies succeed. And investor-folding wants, you know, it's true or not. I've adopted it and it aligns with my thesis, so I'm sticking with it. But the investor told me, Jeff, the reality is, it's not that ten percent of the companies are on to something brilliant or have product market fit or there's some existential problem with the company. The majority of companies that fail are because the pound moves on and this. Hey everyone and welcome to BitBuilders, where we sit down with the greatest minds building and exploring robotics in construction and space. Before we get started though, if you're a startup founder or operator, responsible for innovation in your company or you want a deeper, more insightful look into technology in AEC, you won't want to miss our newsletter. From deep dives into particular technologies such as AI, robotics, design, software and so on. Hot takes from investors betting big in AEC technology and advice on building tech companies including the stories and takeaways of the most successful AEC technology founders. Head over to www.bricks-by-t-e-s.com and sign up today to get this exclusive material straight to your inbox. And now for the episode. Hi Jeff, welcome to BitBuilders. Great to be here. Let me do something. What I do usually is ask the guests to introduce themselves. And then we probably unpack everything you say. Start on the first part of the podcast so you pick your wording and we'll go on the right page. Yeah, I haven't introduced myself for a minute. So let's see where this goes. Jeff, I'm out of San Francisco. I'm the CEO and founder of Format. And let's see. I've been in arts and technology my whole career. And I started out in New York City doing. I had a design company and animation company. Did a lot of television broadcast design work of people like MTV and Viacom. Back in the day. Then ended up doing special effects. Ended up in kind of dot com 1 0 building internet sites and websites when that was a thing. And so all sorts of stuff in New York and spend a little bit of time in Europe somehow ended up here in San Francisco with very, very long time ago and got more involved in technology. I had a company called botan dolly that became known for very technical photography and cinematography. And so we ended up kind of evolving into a company that used large industrial robots things like fanics and coupes that are traditionally applied to our manufacturing. And so we put George Clooney's on them and set her Bullocks on them cameras lights and we were film film Hollywood movies. So very kind of strange path to get there, but ended up doing things like that. We were then acquired by Google and ended up inside a Google running various aspects of the robotics group. And ended up in in product and had a product exposure to the entire robotics portfolio, which them at that time was extremely broad. We were acquired about a week after before I don't call Boston dynamics. So I saw that whole movie and you obviously have no following them for a while. Very close to them. And eventually I left and I started for it as well as a design agency at that time. And let's see, that was about six, seven years ago at this point. So still at it, but working in robotics, I would say 25 years at this point, I am not trained as a roboticist and trained as an engineer went to art school and ended up just kind of always with any more technical and here we are. But I think as a result of that, I have kind of a worth that I don't know point of view on the market. I have a very different view on interfaces for software because it's used them at various industries outside of robotics. And so, yeah, I don't know. I think that's kind of my story. I love it. I think the I've seen again only one time this. Like interaction design to robotics bridge. And it was the founder of Arduino that we got on the podcast on the last show. And you know, just like you, that's where you started. And very curious. How do you know, how does one go and three, two thousand and get into the industry for a special effects for the kind of like design, percent of photography. What's that industry like? We've never talked about that from the builders. I guess you got to give us a little bit of an intro. What did you do there? Oh, well, yeah, I know. Now it's so so long ago. And it's actually it's the I think, you know, I've kind of astounded by it is just the radical change recently. And that everybody that I have worked with my, you know, in that part of my career. And you know, our sort of, I always thought there would be the last to be replaced by a technology or you know, the creatives. and AI has just absolutely changed the playing field there. And it would take us months, if not half a year to accomplish you can do in a day. And so there's been radical transformation there. But for me, I think, how did I get into it? I went to school, studied art, study video art, which was a thing, you know, we have back in the day and ended up having access to some really sophisticated computers at the university. And so, you know, I kind of dove into three animation software. And it was pretty fascinating by that. And I ended up in New York. I think, oh man, how did this happen? I don't know, one day, I had a well, I ended up at this company called our Greenberg Associates, RGA, they were sort of the industrial lighting magic of the East Coast. And I ended up working out TV commercials right out of school. That job lasted for about a year. And I think I had a certain amount of air against it at that point. Maybe I still did. And I asked for an inordinate raise. And I was suggested that maybe I should go look elsewhere. So I did and ended up doing some work on some film effects for a Woody Allen film of all the things. You don't think of that as highly sure effects, but ended up painting wires out of the air. The Goldie Hunt was flying. Yeah, well, she was dancing and did that for three or four months. Met some people working on that project. It was a woman that was from Japan happened to know about some colleagues who have heard in Japan that were trying to start a television channel, which was essentially, it's called Mando 21. It was kind of the MTV equivalent in Japan. They wanted to have some animation done at the beginning of the movie. And she said, hey, Jeff, these people want to come over. Do you think it'd be interesting? So I sort of spun up a company that weekend ran to the space that I was sure that I could get out of it if I needed to and meet a couple of buddies, made a makeshift office and retained a few of these exactly as we put together a whole pitch. And then Lexi, you know, I had an animation studio in New York when I was about 21. And slightly terrified, you know, there wasn't the career trajectory I was going to take, but stuck with it and just kind of kept evolving it into different things. I think that's kind of been the, maybe the arc of my career is, you know, try something, it ends up sticking or you pivot a little bit, you stick with it and it turns into a, mixing you know, it turns into a company. So, you know, that one turned into a maybe a 50 person shop ended up selling it and moving on to the next thing. So, so yeah. When was it that you got exposed for the first time to hardware, you know, you mentioned using coolcon, fanux robots, these are industrial robots that are used to like pick and place or weld or do all this stuff. And I imagine I can imagine I use that for animation, but when was it you're like, okay, we got to make the jump of quality and go and automate some of the animation, explain me that. - Gump, I figured. - Yeah, so, you know, I watched, I was, I know, I grew up with the original Star Wars. And I remembered that, you know, there used to be a lot of documentaries on this. There was a most control rig that was used to shoot the, a lot of the principle of photography for Star Wars, but specifically the scene where Luke Skywalker is blowing up the dust already, is going through the trench and that was all computer controlled camera work. And that was done on a system, was actually done in Marin, which is about half an hour from here. Those were bespoke machines that were million dollar, you know, robots essentially with cameras on them. And it was about 2008, the economy had crashed in America. And I was shopping on eBay, and I realized you could buy these industrial welding robots for pennies on the dollar, you know, that being like $10,000. But these were systems that should have been $80,000, $90,000. And said, oh, let's get one. And so I bought one off of eBay and showed up on a giant truck. And then we had to kind of figure out if it was useful for anything. But, you know, the thesis was, well, why can I use a-- Hey, listeners, I want to take a quick break to remind you about the Brickson Bytes newsletter. If you're interested in learning about the technology, shaping the future of construction, you won't want to miss the valuable insights we share each week. To get this exclusive content delivered straight to your inbox, head over to www.bricks-by-t-e-s.com and sign up today. Link is in the show notes. Back to the show. The welding robot, I've seen these videos of these things that are incredibly fast, they're incredibly precise. Why don't we put a camera on that and see if we can do the same thing that these guys did, you know, 25 years ago. Star Wars at that point. And, you know, I don't know, three or four days later, I think we're going to look at each other like, holy, you know, exploitive, this thing's incredible. We're onto something here. And so we bought two more. And then we had a robotics company, all of a sudden. So that's kind of how we got into the large hardware. I would say that prior to that, I took a couple of years off in my career and I ended up spending a whole lot of time playing with remote control airplanes. And that led to once you get bored with remote control airplanes, you get into remote control helicopters because the stakes are so much higher. They're more expensive when they fail, they fail tragically. And so I got into remote control helicopters. And then I'm looking at these helicopters. And they've got all these beautiful CNC parts, you know, the cuter of an American troll like milled little things and these complex mechanisms. So I was looking at them. I'm like, you know, I should figure out how to make these things. So I bought a small CNC and I had it in my garage so I could make parts because, you know, why spend $200 on a part if you can make it yourself. And by the way, the answer to that is, you can make it by yourself. It's going to take you three weeks. And so you can slide, you know, far more than the cost of those bits, but you learn along the way. And so now I learned how to do CNC machining. I learned how to program those. Really is a hobby. And this is something that's kind of a key kind of, you know, finds some of them interested in turn into business. But I took that CNC machine, which is moving, you know, kind of micron level increments in with a drill on it. I said, why can't I put a camera on this? And then, you know, computer control that camera. So I move it a little bit, shoot, move it a little bit, shoot, essentially doing stop motion. And I build a little robot that we call Maxine. And it was a little CNC with a SLR camera on it. In a turn, that'd be really, really good at shooting products, things like cell phones for commercials or shot a lot of food with it. But it essentially could do that. What they were doing in Star Wars with this little CNC machine and an SLR. So people found out about it. And then I was shooting seven days away with this system. A company came out of that when it turned out that these large robots were available on the secondary market. I saw them and went, like, let's upgrade this thing and go there. So it was kind of interesting. So I went from a CNC that could fit on a desktop to a 3,000 pound welding robot. I didn't want in one move. And that, you know, simulate, could lift 200 kilograms and, you know, really dangerous, actually. But quite a big, big delta there. So, yeah, that's kind of the journey into robotics. And yeah, 2008 was when that happened. We shot a couple commercials with the robots. And then we ended up Warner Brothers saw an article about our studio at that point in Wired Magazine and called us to see if we could help out with this movie they were making called Gravity. And so we did a little test and kind of the rest is this history that decided that was the only way they could film them. The interesting part for me is that it just realized there was a better way to Star Wars was older, but that couldn't have been done out of a hobby. And then at that point, 2008, that's what you turn into a reality. I think they probably now look at what foreign does and I can see some of the inspiration and the sense of like, hey, do we understand the coordinate motion to coordinate things? But, you know, we'll get to that. But before that, I really wanted to ask you, so you started off that I had an animator or, you know, work an animation. and then you understood, hey, it can be the best at shooting with precise control notion and that at some point, you've got an acquisition on her. Yeah, go. What's that experienced by? The worst experience of being acquired by Google like others who live this. In by the way, I really want to know also the bad sides of it. If you have any because though it's been a while ago, but in general, you started from owning the business. Now you were owning the problem at Google, right? I don't need to miss any. How all of that turns if it to? Yeah, that's a interesting question. I think, you know, I'll be, be very, I will be cautious to some extent here. I think it's, um, how did that happen? That happened very quick. We would shoot videos for them. And so we were, we were known inside of Google as people that had this kind of crazy technology, these robots, um, but we're also just doing traditional design work for them and traditional kind of 360 advertising, brand, television commercials and some specialized in photography, really for the Android phones that were coming out at that point. We did a lot of shooting of them. So they knew us. And, you know, let's see, we sort of, it all happened very quick. We were about to take a strategic investment from, um, uh, one of one of the companies that I really appreciate the most, um, auto desk and, uh, auto desk had a research lab that did a bunch of robotics work. Uh, I've used, um, they know, on a desk is known mostly for on a CAD and now fusion 360 and that's like that. And a lot of tools in the, in the construction world, um, in the architecture world, but I always knew them as the, the makers of Maya, which is a 3D animation software that was used to do, and certainly, like Jurassic Park and everything since then, uh, the instrument market share, but I've used their software for years and, uh, we were actually controlling our robots. One of our, our big innovation. So as we hooked up our robots to Maya, so that as an animator, I could work with a robot set of me in a program. Like if you watch welding robots over the last 30 years, they, they move like welding robots and they're very quick, very precise. And they, they move at lines because it's more efficient. Um, one of the things I can animate or for two reasons, one, you can do more beautiful motion. Um, if you, if you put them on a path instead of, instead of directly into coordinates. Um, and secondly, you can get, you know, the job of an animator is to get a lot done in as little amount of times possible, especially if there's a Hollywood actor city there, front of you that seem to be paid, uh, $1,000,000 an hour. So, um, so it was a quicker way to get something done with robots and, uh, and a more beautiful way. So anyways, we would take Maya software and we're applying to robots. And so that was kind of the giant hack that we did. And, um, you know, I'm kind of digressing a little bit about, about that, but it's part of the journey. And so we were looking at a investment, um, from Autodesk, which, um, I, like I said, I love that company. And, uh, just as we were about to close a strategic investment, um, I ran into a college at Google and, uh, he said to me, you know, hey, you know, let's, let's have a conversation about how we can work closer together, which, you know, it was sort of coded, I guess, and I sort of, I was going on here and I said, well, okay, yeah, you know, you should know that we're just about to close this, this investment. Um, he says, okay, we're over tomorrow. And so he came to, uh, the studio in the next day and then a day after that, um, very page was there, uh, founder of Google and, um, you know, these robots asking all sorts of interesting questions about them. Uh, and then we were very, very quickly and do diligence. So we sort of, uh, wasn't a very traditional merger and acquisition situation. It was very spontaneous, uh, very, very quick. We, we shut down the other conversations and, and we were kind of, um, you know, then in, uh, in, in, indigents and, and many things happen, which was, you know, a, for, for founders out there when large companies go, go into this motion, you should be aware, uh, that you don't know this the first time you do it. Intelligence is an entire process and, uh, quite, quite, uh, time consuming, uh, it takes a lot of your resources and by the end of it, you're not quite sure when you've been through, but, uh, it's, it's interesting to say the least. So, so yeah, that's kind of, uh, went down. And so you jumped on, on board. So not only the company was acquired, you went on to work at Google, X or neutral factory, whatever the, or was that, I don't know what the nomination was at the time. I'm very, I've been totally familiar with Project Moon, which is one of the projects that was there. I met it called the CTO of, of that project, Silicon, the, the insane, insane technologist, uh, and a lot of the people around that project for something completely different. What I do know about that group is the group that sometimes projects work, sometimes they don't work, but it just group a lot of the most insane talent in one specific vertical. And it just tried to do something that hasn't been done before. So what is it out there? Were you doing at a Google, um, how did you like that experience? Yeah, it's tough for me because, um, you know, a couple of reasons. So I'm, I'm a, I'm a startup guy. So I've had, um, by the time that I had gotten to Google, I didn't really kind of get into the myriad offshoots of my companies and things like that. But I'd already had about 10 companies, um, by the time that we were acquired, um, in, in, in various things that I was doing. And so I loved the early stage. I like the zero to one. I like the, the, the first five employees are like the, the phase shift that happens when you get about 30 people and you spend half of your time walking around the block, trying to, trying to convince people that, that, you know, something's not as terrible as they think it is or, or, or that you're not as crazy as you, because they think you are. And so, you know, all of the, the kind of interpersonal connections that happen in a small company and all of the, um, the amplitudes that are, they're, you know, I think I've very much started to love. And I think, so for me to go from, from what we were about a hundred people when we were acquired and then to end up at a company that is 50,000 people at the, the time, which is far smaller than it is now, um, was traumatic shock. And so I was excited about it. And I didn't really know what I was signing up for, um, at that point, when you're, when you're, when you end up in that sort of a situation, you know, it's the complete opposite of the found room and how to where at a 50 person company, I can make a very quick decision and I can, um, execute that decision through the organization because I have the ultimate authority to do so. And I signed the check. Um, that is obviously not the case of a large, probably traded company. And so you spend a tremendous amount of your time, um, building consensus and, and convincing people that your, your ideas are valid and, and playing the, the, um, I don't want to say the game, but, but, you know, managing the ecosystem versus, um, thinking and doing. And I'm very much a, I think, and I do, and I learn while I'm doing it. And that doesn't, that doesn't work at large companies. There are exceptions to that, um, where you have to really protect your environment from the, you know, the bureaucracy to do so. Um, so, you know, that was kind of my experience was getting less done than I would have liked, uh, for, for a long time. Um, I think you can do it, but you have to be a certain type of person. And, and it's very much the way I think you can succeed in that environment as a, as an executive on a lot of the, the people that do progress companies, um, like that, our people are coming through acquisitions that have strong opinions and, and, and don't tolerate the organization getting in their way. And I didn't have that perspective. When we were acquired, um, there were, uh, eight other companies acquired at the same time. So you can imagine that, uh, in the Ravonics space. And so there was a bit of mayhem. There was a lot of organizations being integrated, um, and a lot of egos, um, to contend with when you, when you got eight CEOs, um, uh, at the table. And so, um, I sort of, and if I look back at it, I think I attempted to play a role with moderator and looking across the aisle and, you know, consensus building and things like that. And I think it, it, potentially, uh, you know, inhibited me from being as effective as I could have done. So, you know, it didn't, it didn't work out because I, I miss, you know, the, the, the drug of the startup, um, uh, but also, you know, I don't think I was particularly, um, you know, I guess the, the classic line is, you know, you know, do it and beg for forgiveness later. I didn't have that mentality. And I think that's what you need to have inside of a large organization, uh, to be, to be impactful. And so, uh, to some extent, I regret, you know, not having sharper elbows or, or, or being more strong in my convictions will be there because you have a tremendous opportunity because of the, you know, the war chest. Uh, so if you're, if you're on to something, you can actually do it. But you've got to be very loud about it, I think. Lower force, longer lever is opposed to the opposite. I get to, I get to think I get the concept. Yeah. Yeah. And so interestingly, I'd off, I think, And I think you were bound to end up somewhere again or you had been about 10 times this you mentioned So what was the next story of form and Those ones start what you guys even do What do we do well time we do not yeah what we do we kind of we do what we start out to do So we connect humans and robots And what does that mean? You know, it's kind of what I've always done sort of If I look at that what we did even in the film industry we were essentially connecting a director photography Machine that they have no business using and you do that through software and so you know now I look at what do we do It's not a completely different scale and completely different industry But we allow human beings to manage robots that are under their command And so you know people think about human like robots So robot armies or whatever drums we don't do that kind of thing We certainly work with with every type of robot that's out there But but we're working with industry and we're working with businesses that have you know between 10 50 to 20,000 robots that are under their command they don't look like You know see three P.O. They look like force grubbers and farming equipment and robots that are vacuuming streets robots that are standing drive So you name it we're working with Somebody and just about every industry that is using automation and so we allow you to monitor those robots that are out there in the field or On the campus or in the warehouse Get all their data signals in store all that information Allow humans to Be alerted when there's an event that they need to take care of or there's something that they need to manage So we're an interface between humans and and robots so that people can can have effective automation You know one of the things that I know that people necessarily realize if you're not in the industry is that there's not a Robot out there that's doing a job that's of any consequence that isn't being washed by human Because these things fail. It's not because people don't want full autonomy Of course everybody does However, there might be a safety reason or more often than not. It's the the reality that things happen There's there's ambiguity in the world And there's situations that need to be navigated so Just about every robot is phoning home in some regard To report an issue or to to have resolution by a human So Followed autonomy is great, but polytonomy in the real word is almost asymptotic So what we're What forment does if I ex-friend or send it correctly is you're bridging to that asymptote By allowing humans to control Do you do that control for yourself? How do customers Interact with you right? So at the beginning when you when you were signing the first ones was your pitch? What can what can you do for them? Well, I don't know that was so long ago We're six years into this six and a half years into this now. I don't remember the original pitch Uh, you know, I think at the beginning it's it's actually you're more listening than pitching Um, and so you're trying to understand the customers problem you have an intuition about what they need um You know, and I had had a lot of experience from google We looked at just about every application the robot could be applied to and realized that you know so many of them are like at the 95% Mark they you know they almost work and so I was like huh. What if we could bridge that gap with the human So you know, we started talking to a robotic startups that we're having challenges when they started to go from the laboratory out into the field You know, they were sending engineers out with every robot and and this doesn't scale We so we said hey, what's what's build a spill some infrastructure that allows it You to easily get signals off so that you can make proper decisions and you can do it remotely uh, and uh And so on and so forth. So you know, I think we we kind of we knew the problem space a little bit Then we knew that you know, wouldn't it be nice if you could tell without walking up to a robot was going on to it Um, and you know, you get a you get a empathic yes on that um Wouldn't it be nice if you can lower your ratio of engineers to to robots to to maintain them and you get a yes But then there's a lot of things that you don't understand uh that your customers inform you about so you know How do you want to review your data? How do you want to re-inform the data set? I have a human smart it up what are you using for labeling all these sorts of things and And you kind of You know build on the the the the core Technology that you have and the product that you have so it's kind of a two-way street getting um, I think now we're we're Recognized as that the industry leader. I think we are The you know in a position to inform The industry on best practices because we have what we have brought exposure to all these people doing all these different things And so we see the bend diagram of the overlap and you know How do you want to deal with with our learning? How do you want to deal with data management? How do you want to deal with Operation of the robot and and what are you talking about analysts? We have pretty strong position on that now um, you know We're obviously on on enterprise engagement specifically We're continually being asked to adopt or adapt, but it's usually kind of adapting to some of these infrastructure needs or their Security require amounts or things like that. So it's still an evolution. We're we're not what we're never going to stop revolving But I think we're far more uh Solid in and in our knowledge and and um and Oftentimes we're informing uh the customer Um at this point and so the What I'm curious about and I think something that we double click on very often a bit builders Our business models and how do business models basically interlock with the market dynamics the market needs um and To me Thinking about this What I see is is a market that needs an outcome. It's basically the operation Um, but I also need some tools Basically handle themselves the customers some of the failures some of the data gathering Uh some of the detail operation. So how did you construct a business model? How did that evolve? I'm sure that evolved together with the company uh and yeah, you know, what's what's their thesis and Yeah, so if you know it's like I don't um It's organic and I think it has to be right you know, this is an early market still robotics has been around for 40 years, but uh in in artist and and you know very seriously in the last 20 Um, but that's that's still the adoption rates are are relatively low outside of um traditional manufacturing Uh, and so it's a bit it's a bit greenfield and people don't know you know, you know what what the right model is yet It's also not a um hyper scale like the server business or something like that or um, you know So there's not a a uh There's not a tried and true answer um at this point so I think you need to um You know continually adjusting it based on what we see out there um, but you can think of us as a um sass company Um, and so it's subscription based Uh, and so you pay you pay monthly and then you pay um by end point Um, you know, there are other people that are looking at um per seat licenses Um, isn't seem intuitive to us to do it that way um, it's also you know a fact that there aren't a tremendous amount of operators At robotics companies are relatively small groups of people um, so it seems um, you know clearer to tie the the business model to the so the high value asset which is the machine out there doing the work and so Um, so you have where we're you know based on how many Uh, robots you have deployed and then there's um breaks for you know bucket sizes Uh, so that's that's the model it's traditional sass um and uh So far so good What is the What is the biggest point of friction or customer that wants to adopt a solution like for months Uh, what is it that they have to do uh, what is it that you guys are helping them doing to implement faster integrate faster Yeah, it's actually you know, I thought when we started this um That we would have a tremendous amount of friction and that all these systems are are different so When we when we you know, it's like well and i think investors are always asking this question of us and I You know, I want to say it ironically. I want it. It's surprisingly we realized kind of very quickly that that wasn't the issue um Just going to be a Linux computer somewhere in the chain and uh, and it's going to likely be connected to the internet So you've kind of got a place that you can install an agent. So you know, generally that's something like a jetson or something from a video running on the robot It's got Linux and you can You've got the opportunity to install a piece of software that is essentially um doing some buffering on the robot and and then Transmitting that data and allowing command control from real situation. So there's a hardware, bridge essentially that is common to 95% of the robots out there. And then there's also, I would say, 60, 65% of our customers use Ross or Ross too, which is the robotic operating system. There's a messaging protocol that is common. So there's enough commonality that wasn't the problem early on, it was built versus buy everybody had kind of a home roof solution that they were doing. They had been around before, before we were there. Um, I think where the industry has matured, it's like, you're not going to go build data dog. It exists. Uh, so you're picking up, I think we're at that point now where you don't need to, to build on this infrastructure. You don't need to manage to see you want to pick it up from somebody. Um, so, you know, I think, but originally you're, you're talking to deep tech companies inherently, right? These robotics companies are full of engineers. They don't want to, uh, they forgot to buy software. Why buy it when you can spend all day running it? I think. And so, you know, that was the originally in the friction, but I would suggest that we've, we've kind of overcome that at this point, the, the amount of money you would spend to build data infrastructure and get it right and understand, you know, sort of best practices in terms of the, the usability of those interfaces and what's actually needed. Um, you're going to spend way, way, way more than you are picking up, um, something. And I actually think it's sort of when I consider what the value proposition is these days, it's, it's very much from, from the end user standpoint, it is, you know, how, how many operators to how many robots do you need? So it's that ratio that is kind of the Holy Grail, or it's time to deployment out there in the field, or, um, or something like this. And so those are the business arguments, but I think about the, the value of the company, you know, we have all sorts of technologies that I'm very proud of that we've, we've built a dismiss the technologies that we have there, they're all replaceable. Anybody can configure any of it out. It's the domain knowledge that we have. It's, it's been there. It's working with, you know, all these companies and all these verticals, understanding the problems. There's a place. And so, you know, I think that's kind of the, the strongest argument that we have is like, we understand how you want to work with these machines. We know the requirements. We know field engineer wants. We know what CTO wants. We know what the, um, the analyst wants. Um, and we provide the tooling for that. And also maybe to, to back to your, your question around kind of friction, a lot of our customers actually are getting to a point where they don't have, you know, some of the people who work with make robots, a lot of the people we work with, and especially as we continue to go up market and we work bigger, bigger companies, they don't make robots. They buy robots from other vendors and they want to integrate them all in one space and have them all be nice or have all the data is, uh, you know, correlated. And so we make it really, really, really simple to bring on a new robot. And so what used to take, uh, you know, a month of integration work now is the day or two. And you've got another OEMs robot, you know, on your platform. So you can check your vendors. You can, uh, you can, you're not bound to anybody else's to any vendor software. And so as opposed to friction, people see us as like, wait, we're going to, we know the strategically, we don't want to be tight any main fashion. We have to have that flexibility. So we need a neutral platform. And so they see us as a way to easily work with many types of robots from, from, from many people. So it's actually becoming, it's kind of an anti anti friction argument, I suppose, you know, that simply get a robot up in, yeah, days, it's not like minutes yet, but we're get there. It's interesting because the people that have never worked in robotics, not they're touched, a microcontroller or anything like that, don't fully grasp the idea that basically to may robot or the computer that runs the robot, right? Uh, do something need to code in a specific language, resume that, that, that, uh, a command in a specific, with a specific language through a specific channel, set, et cetera. If you can actually level the plane field and make the fleet harder agnostic, you can actually extract a lot more data, a lot more insight, a lot more coordination can spin out of that. And that's how you make robotic fleets. When you look at like the initial, um, in a, the initial days of robotics, you had companies that the purchase different robots from different manufacturers and literally add a team per each robot to figure out each robot should work. And then the team at the talk to each other, others and hey, when you pass this back this way and the other robot grips it, we don't know really to understand what the other robot has done. But to have a, you know, you need to have like all sorts of external checks to link that, that's what the infrastructure is like. So the, the data I have in analogy, you were actually not a desk before the author of construction. And I'm talking not about Maya, but the rest of their offering, uh, the, the platform of construction software that exists today on the desktops of architects, engineers, it's completely fragmented. And we have, you know, there's especially one company that's called speckle, but there's a bunch of them that are building the infrastructure to make that data readable and ratable in an 80 or month in and out, uh, with different software vendors. That's actually the same concept is like you speaking different languages with different people in your team, you culminating this and then it just becomes completely different to work with. Uh, and so I'm curious to understand. Where do you see Foreman's algae going? Because today what you have, you have a market, it's extremely hungry for more and more robots who were mentioning Jetson. There's many more development platforms that are coming out. Um, Arduino Pro, all the new and video shiny stuff. Uh, there's a lot of interesting things. I even worked and played with Lego mind store when I was in high school in the US, which I'm sure you know. So there's all sorts of controllers out there, et cetera. So the market is growing. Where is the data infrastructure? Quite the word. Yeah, that's good. Good question. I mean, I think we're in the right, right spot. Uh, you know, it's going to companies like like Foreman. So it's, it's very much going away from OEMs. There's a, um, people are very concerned about where their, their data is going and they're seen as the, as a very high value, you know, asset. So we help as long as collect all that information and, and leverage it. So I don't know beyond, you know, what we're doing where it goes in the future. I think it, I think the obvious answer is it's centralized in, in, in the cloud. We have multiple employment strategies. So you can do everything from on-prem to public cloud. Um, and so that's, that's kind of a customer's requirement. We will do different appointments. So beyond that, there's not really another, there's not really another solution. I don't know what would happen. It's beyond being co-aided in, in one place. But I think what, um, you know, what's happening is people are starting to gather the information from multiple systems. They're starting to normalize it so they can get reporting that is intelligible. Um, and, and you can compare a contrast performance to different types of systems, but you can also coordinate between them, you know, for example, some of the things that you're, you're talking about where, you know, one robot needs to deal with another robot and two robots meet in an aisle at a Walmart. Like, what do you do? Uh, that's like, like, like, to some extent, they solve problem and then, and, but who are actually, you'd be surprised how unsolved that is and that the, the intercommunication protocols are not standardized yet. There's a couple, um, standards out there, but there's, they're, they're, immature and then not, they're not widely adopted. Um, so they'll be standardization, things like that. Um, but, you know, maybe, maybe more interesting is, um, we're going to kind of skip over a lot of that. And so, uh, now that you met all the, the data in a spot and you can contextualize that data and you could tell a system, like ours, you know, why do I care about this? What is a mission? What is a, uh, route? What is a air, which ones matter? Which ones don't? If you could start to feed that information into metadata, essentially, that you're, you're collecting then an intelligent agent can help you do your coordination. And so where the world has been has been things like slang, which is a navigation technology or, you know, for afic management, how to two robots, navigator, who gets priority in a delivery system, which I think that that is going to very quickly not be the conversation. That's the domain of roboticists. And that's the thinking of roboticists, but now with artificial intelligence and the gas agents, you can reason over large data sets that are contextualized. And you can make intelligent choices where you can recommend to a human being, you know, here is a course of action that we'd recommend. You agree or not. And so you're going to start to see that. And so, um, I think a lot of the traditional, uh, working robotics, where, you know, get the data and then engineer a solution, uh, based on rule, goals is going to go away and what's going to become far more interesting and important is that you catalog and contextualize the data in a way that says, "Here's my intent. Here's what the robot is trying to do. Here's where it's succeeding. Here's where it's failing. Help me out." Because I've got 20,000 of these things and I need to know what do I do. And so you're going to start to have a layer of artificial intelligence on top of this that is making a superset of recommendations to human beings. So I think that's where it's going and it's not going there in 10 years. It's going there now. And so the fundamental of that is collect all the data, make sure you're connected to the machines, make sure that connection is secure, make sure it's both proof and make sure you're gathering highly contextualized information. So what you're saying is let data create an ontology context and code intent and then let the user act on that intent. Yep. You got correct. That's where it's going. I'm very close. Oh. I'm spending most of my time sitting in front of the Zoom station, talking to my remote company. We're all remote. So I spent my entire day sitting unfortunately in a chair staring at a rectangle speaking to human beings through an artificial interface. But beyond that, I don't think that was the question. I spend, let's see, that's a great question. I don't know. I'm a builder. And so I don't want to answer the question because I don't want to hear myself say the answer but I probably spend 25% of my time on innovation currently, which I am extremely excited about. And then the delta is with between fundraising because it's my primary responsibility as a CEO of a venture back company. And then management and of what we're building and customer relations. So I'm not doing, I do get involved on large counts on the sales side. I really it's important for me that I continue to be abreast of what the actual problems are. So spend much time with customers. But then working on the company, trying to transform it all the time and then a tremendous amount of time on fundraising. And that's kind of a, it's new. This is actually, we've had a lot of companies and this is the first venture back company I've had. So I have not had that experience, but I have now, and you know, six and a half, seven years into this. So very familiar with what it means to fundraise. But it's difficult because it's is an antithetical to build it. And so you want to spend your day creating and solving problems with any of your, you know, this is the reality of fundraising that is the responsibility to see. Yeah. There's a huge, you know, one of all of our of conversations that we might have on like the difference between building a business in traditional way, building a business with capital that you can burn. And also what it means basically, well, what you can achieve with one, what you can't achieve with the other. But then on one side, but then on the other side, where does the leaders, the leadership spend time and our investors interest always align with the build this interest. That's really not a trivial thing to understand. From important. Yeah. And it's actually the thing that, you know, I don't know, it's sort of, I'm not like I said, I, you know, I, I learned by doing and I'm, I, I would dreamily different point of view on this than I did, you know, when I started the company and so I think you were not on one of the way and you, and everything you just mentioned, you, those are, they're real concerns and, and there's materiality to all of it. And I think that, you know, or to that is making sure that your, your investors and your interests are mine. That's how you win. And you can, you can leverage them. Otherwise, you have a problem with unfortunate and we have a tremendous group of investors. I, I don't do up, checkery, well as adult supervision. I think that's why I'm not at a large company, but I do have obviously a board. The board continues to get larger and larger, but I actually love my board and, and they're, they're on our team and that's not always the case. And I think it goes really south, and that's, and that's not the case. It's been important for you to have, not only in the line, but like, I hope you've had the, the experience of having an investor in your board that's actually truly helping with issues, issues of hand, stuff that's, you know, such a stuff that it was burning that was really pressing that, you know, the bad experience within the past or, or simply have been able to help. Did you get that? Obviously you have to say yes, because you're a virtual back company, but yes, of course, but, you know, truly that's, you know, any thoughts? Yeah, you know, I think there's, you need to filter, right? There's a lot of opinions. And so I think we're unique to some extent in that we work in robotics, not a lot of people do. And so there's not a outside of the industrial players, there's not a tremendous amount of industry expertise that you're going to find on a board. And you know, we do have some, some folks certainly that are very experienced in the manufacturing space, VMW, for example, as an investor in the company. And so obviously they've got a ton of robotics experience. It's just not necessarily, you know, most of our robots are fielded, but they're not welding cars. And so that, you know, they can't bring that specific knowledge to us and the other investors, you know, they work in, they're portfolios are generally right on robotics. There's not a whole lot of investors that lean in hard to robotics in the portfolio. So I'm not sure that the tremendous amount of building knowledge to gardener from investors, it's more understanding the financial markets from my perspective and understanding the investment, temperature, sentiment and, you know, what the disposition of that market is. I've been incredibly informative to me. And so, you know, I think all the time, you know, of how to position the company based on, you know, the needs of thought, one of those needs is fuel, which is, which is, you know, so that's been super, the worst and super informative in that regard. I want to move towards the end. I promise to you, short and crispy conversation, but I, you know, I'd go on for hours, but the one thing that I ask you before my usual final question is, what do you guys, I know it's a broad question, but I'm sure you have a, you have a framework. Who are you looking for when you build a team for format? I'm sure that's another piece of the puzzle that, you know, 100% of your time, it's somewhere in there. You said you were remote, are you remote worldwide? Do you only hire an EUS? And also, what do you guys think it's key when being an employee of format? What do you think differentiates your team from rest? Yeah, you know, so we are worldwide, but we are, the line share is US based team members. And I think we're in by 30 states or something last night, I, I, I, I, exactly we have, we have, we have employees in Europe, we have employees in Japan. And so we're kind of everywhere. We've got a whole team in Armenia as well. So, you know, there are some examples of strategic reasons to do this. Obviously, there's, there's cost basis is consideration. But also, you know, one of our bigger concerns is DevOps and, and up time and making sure that we've got coverage 24 hours a day, where people are, are depending on, on the platform. So that, you know, dictates a certain geography. But you know, for me personally, I've always had companies that have thrived when I have, a lot of big delta's and skill sets. And so, you know, at, at Botanol, he prior to, for a month prior to my Google experience, you know, we would hire engineers, but they would be sitting next to architects, which arguably are in jams, but then they'd be sitting next to a storyboard artist, sitting next to a line producer, sitting next to a writer. And you put those people in the room and you sprinkle enough technology around and magic happens. And so, I really, really like interdisciplinary teams. This company, due to its hardcore engineering and very cloud-based technology has, is been, let's say, 70%, software engineers, and the differences there are front-end, back-end, or full stack, or DevOps, QA, things like this. And so it's been pretty traditional. I think, you know, I get asked a lot about how to build a team. There's, we've been fortunate in that we've we've had really just a grapefruit forever. And I think there's, I have this philosophy that if you start with a few good people, it sort of spreads out that way. You just, you inherently, people that get through are passing some kind of a bar that is not necessarily articulable, but it's something that the bad eggs don't get through, or the people that don't agree with the company culture just kind of get, it's not a fit for you or for them. So we have a tremendous a group of human beings that are that are dedicated and that we care about and care about each other. And that's been my experience and my career the whole time. And it's super important to me. I mean, we've all got a choice. We don't all have a choice, but I'm fortunate enough to have a choice. And I think the people that work for me are fortunate enough to have a choice of where they work. And so if you spend all your time, you know, a lot of your time at your job, make sure something you enjoy and make sure it's with people you enjoy. And I think there's just, I don't want to get too philosophical. So we're going to do something where it's like, you know, build it, they will converse something like that about it where the people attract like minded people. So there's not a science to it. It's just more of us of them than I think inherently have. So it's been my experience. As we move forward, I am actually starting to think about this way to bit right now because work is transforming rad and companies are going to transform radically and we're transforming radically. And so I think what's most important right now is that you're malleable. The understand the way to tools, those tools are all AI powered and that your problem solved. And so that's a little bit of a cliche thing to say. But I think it's like, anyone, you need to do a domain expert to some extent in this industry or have some expertise, but you need to be a little bit of a polymath that you have. Part of your brain is you're a great communicator. Part of your brain is you're a great engineer. But a great engineer doesn't mean somebody that writes go or writes, hythonomy, a zener, C++. It means somebody that solves problems from a programmatic standpoint. And so you've got to be great at that. So my, the interview questions are all going to change. It's not going to be a coding test. It's like, here's a problem. How would you go about unpacking that solving? Like that is so relevant right now. And you've also, you've got to be able to maybe bleed into another department because you know, you can't with the tooling that's out there now, especially in the developed world with what we're seeing in AI, you've got to be able to think a little bit like a product manager if you're an engineer and product managers need to think a little bit like an engineer because they can actually write code. And so these lines we're getting very blurry. And so when I step back, what does that mean? It means you've got to be able to solve problems and be able to articulate those problems to something that you're likely chatting. So this is this is new thinking. This will be, you know, somebody here's this podcast in six months. It's going to sound like a. You You You You You You You You You You You You You You You You You not going to be. in 2026 the same person and 285 same person. I love that you're taking that on of course you are given the you are the forefront. And to that question that it's unrelated but still related to an extent. What is your advice which I wanna, by the way I wanna close with? 'Cause building in an industry that's hard to crack, it's building a solution that it's hard to make and it's building a team that it's hard to put together for mentioned to reasons. - That's a nice. - Yeah, so I had this conversation with Guy in New York that I worked with when I was 22 or so. And maybe for a short, my first company and I met this guy and I hooked up with him. He wanted some career rise or something a couple years ago. And he said this thing that I actually, we're really appreciated and was flattering. So of course I appreciated it. But he said Jeff, you always pick something really hard and you don't stop. And so I thought about that. And I think there's a truth to it. I mean a lot of people give up pretty early and I think that so maybe the message here is like tenacity matters. That's the way you're wired. And so I heard in the anecdote, 10% of venture-backed companies succeed. And investor-folding ones, I don't know, this is true or not. But I kind of did it. And I've adopted it and it aligns with my thesis. So I'm sticking with it. But the investor told me, he says, Jeff, the reality is, it's not that 10% of the companies are onto something brilliant or don't have product market fit or there's some existential problem with company. The majority of companies that fail are because the town of Muzan does something else. And so I thought about that a little bit. And I think there might be some truth to that. So I think that what I'd suggest is, commitment matters, tenacity matters. I think you've got to also fear needs to go away. You need to take the shot if you're thinking about it. Just do it. You're going to learn, you're going to grow from it. It's not that big of a deal to try something. You'll succeed or you'll fail, but at the end you're going to be more whipped on the other side of that failure. So I highly encourage people that are inclined to start a company to do it. Actually, don't over think it, just get in there. You don't know what you not know, just go do it. But when you pick that thing, understand what you're walking into. It's not going to be what you think it is. It's not going to be easy. You just think it is. It's not going to have the, you know, likely we won't have the j-curve that you anticipate happening. You know, one and a half years in, you might have to wait three. You might have to wait 10, who knows. But make sure something you care about enough that you're willing to stick it out because it's going to be challenging. It's going to be awesome. But think about, you know, there's something that I could do for five years. There's something I could do for 10 years. There's a really good chance that that's going to happen. And if the answer is yes, and you're committed to it, and you don't stop, you're probably going to succeed at it. That's my wish. I'm going with that anyways. Awesome. I think it's fit. Good luck as I answer the question. Yep. Thank you so much for taking the time to jump on the pillars with me. I hope we can do it part too soon. I'll be watching closely just as much as I did before. You'll work. And what you guys are doing at Foreman, I think is an example for the industry. I think it's a testament to the industry that's moving forward. I think in a lot of fields, when they start maturing, you start finding those common threads across the field that will basically throw into huge value captures. At the same time, they will signal that the industry is ready. So keep up with that amazing good work. I'll be watching for the sidelines. And very, you know, very happy to chat and eat. I am for a part two. Yeah, we'd love to. It's really been a pleasure. And that'd be all that. Awesome. Have a good one. [MUSIC PLAYING] [AUDIO OUT] [AUDIO OUT] [AUDIO OUT] [AUDIO OUT] [AUDIO OUT] [AUDIO OUT] [BLANK_AUDIO] [BLANK_AUDIO] [BLANK_AUDIO] [BLANK_AUDIO] [BLANK_AUDIO] [BLANK_AUDIO]