00:23:50 · Josh Gruenstein
[00:23:50] S0: Yeah. It's an interesting challenge because almost everybody we're selling a robot to has never purchased a robot before. And that kinda comes out of these stats. If The United States is only deploying 38,000 robots a year, if nine out of 10 US factories and warehouses don't have any robots, then almost all of the market is greenfield. And these people understand what this old guard of automation looks like, and they assume a robot doesn't work for them. And so the way we break through that actually isn't by talking about AI, or models, or tutors, or anything like that. We called them up and we're saying, hey, have you ever considered a robot for $16 an hour? And they haven't. That's a new proposition for them. So you can book a meeting, and then you can kind of explain to them this thing that we're doing, and get people interested and involved. And by creating that business model where there is that true incentive alignment between us as the robot vendor and the customer, we're able to run distribution of robots at velocities that, you know, are many orders of magnitude faster than traditional industrial automation industry. We have an average time from that first call to a robot signing contract of forty to sixty days. We have an average time from that signed contract to robots actually in the customer site of about forty days doing work. We stand up robots in production within a day, often within the first couple hours that a robot is on-site. So we're able to move very, very, very quickly because not only is the robot this generally intelligent, generally capable machine that we're not customizing, we're just shipping directly from the factory to the customer, but we're not putting any sort of economic risk on the customer. So we're able to get them on board.
00:25:28 · Raghu Raghuram, Josh Gruenstein, Martin Casado
[00:25:28] S1: And once they deploy it, how do their attitudes about labor versus machines change? [00:25:35] S0: The operations community is really, really fantastic because they see a thing work, it's like, it works. Right? That's it. Right? It's like, yeah, I can see obviously it does the job. I know all the places where this job needs to be done. Let's go put it in all those places. So, we've been able to scale up very, very quickly, both with small businesses and to some of the largest companies in the supply chain from one robot in one site to a dozen plus robots across many sites. [00:26:05] S3: It is interesting though, because a lot of gen AI was like, there's a social element where people get very attached to their models, and it's hard to swap models, and so, listen, you probably have more experience deploying robots than most people alive at this point. Like, are you saying the same thing? Like, they viewed like equipment, or are they starting to be viewed like beings and coworkers? [00:26:27] S0: Yeah. So I saw a very funny tweet, which was, a robot is a robot unless it works, in which case it's a machine. Gotta figure out the attributes. [00:26:37] S3: Is it a Zip Meal? I guess it It's it's pretty real. Is what it is? Like, they just view it as like a piece of equipment once it works?
00:26:37 · Martin Casado, Josh Gruenstein, Raghu Raghuram
[00:26:37] S3: Is it a Zip Meal? I guess it It's it's pretty real. Is what it is? Like, they just view it as like a piece of equipment once it works? [00:26:42] S0: Certainly, at, like, the factory manager level, yes. I think there's still the layer of, interestingly in robotics, your buyer is not your user. Right? Your buyer is the COO or the general manager, and the user is a factory worker, right, who's working with the robot all day long. And there, you actually do need to cultivate the relationship between those workers and the robots because you know, we don't fully automate 100% a factory. We automate some jobs in a factory or warehouse. Do you [00:27:08] S3: have a philosophy on how you even approach this? You try to make them look more like coworkers or less like coworkers? Do you make them talk? How do you view this philosophically? [00:27:17] S0: Yeah. Very, very luckily, there is a whole school of academic research called HRI, human robot interaction. [00:27:23] S3: No idea. [00:27:24] S1: There you go. [00:27:25] S0: Yeah. Lot of people have spent a lot of time thinking about this, including a bunch of people from my academic background, And there are a whole bunch of tricks. So one trick is every robot has a name, and so that lets us actually build relationships with the robots. [00:27:41] S3: Who names [00:27:41] S0: it? Mostly our manufacturing technicians. [00:27:44] S3: Okay, you name it, not the... It's not like a dog is when you get a new dog, can rename it?
00:27:44 · Martin Casado, Josh Gruenstein, Raghu Raghuram
[00:27:44] S3: Okay, you name it, not the... It's not like a dog is when you get a new dog, can rename it? [00:27:48] S0: So, when a customer expands with Tutor, when they do a repeat order, then they're allowed to name the robots. [00:27:54] S3: Okay. Because you're not supposed to rename a boat because [00:27:57] S0: you've got [00:27:57] S3: bad luck, so gotta keep the boat named, but you can rename a dog. [00:28:00] S0: Yeah, so the new robots get to be named, that solves it. And we get customers [00:28:04] S1: Oh, they get the highest ones of ownership now, they've named it. [00:28:07] S0: Exactly, right? And we get really strong signals. We had people name the robots after their kids. Woah. Right? People name the robots after their favorite football player, their favorite pop star. That's good. People get very attached because the robot ultimately helps. It makes their jobs easier. If you're a line worker in the facility, you're not doing back breaking work as much. You're able to be elevated into a higher position, none of these places can hire. And then if you're a factory manager, your job is just a thousand times easier. [00:28:36] S3: What naming scheme do you use [00:28:37] S0: from when you moved We started off doing hurricane naming, and then we kinda So that's not Yeah. [00:28:45] S1: You didn't read the HRI book, rarely. [00:28:47] S0: Well, it's... I don't know. [00:28:48] S1: It's [00:28:49] S3: Well, you're in. Can tell.
00:28:49 · Martin Casado, Josh Gruenstein, Raghu Raghuram
[00:28:49] S3: Well, you're in. Can tell. [00:28:50] S0: The customer doesn't know that Britney is, you know, n mod 26 or whatever equals two. It's it's... But we actually stopped because we kind of went through the hurricane. We went through the alphabet too many times to be able to keep track of it. [00:29:03] S3: Okay. So what are you using now? [00:29:06] S0: I think the technicians just just pick whatever brings them joy. We have a really wonderful and privileged to employ a big staff of people in The United States who are helping to build these robots, and they are also naming them. Awesome. [00:29:18] S1: The other thing that surprised me when we first did the work before investing, most of the time when we talk to robotics companies, they're going after these humongous companies, right? Yeah. The big Fortune 50 type companies that seem to have the budget for lots of experiments, etcetera. Yeah. Whereas, I think a significant majority of your customers are all these local businesses almost. Yeah. And what does that, I mean, there a message in that, or was it a conscious strategy, or?
00:29:52 · Josh Gruenstein
[00:29:52] S0: Yeah, it's a lot of things. One is that's most of the market. The vast majority of US businesses in manufacturing logistics are small businesses or mid market businesses. So if you wanna serve the market, that's what it takes to serve them. We also started this company at a time where we're seeing kind of all of these very academic supply chain oriented robotic startups kind of get started and then not really succeed. And we had the opportunity of being like, okay, what went wrong here? And one of the big things I think that robotics companies get wrong is they're not actually really product companies. They're like, okay, some really big company has a very specific problem. They're willing to write us a shiny piece of paper that says they're gonna expand with it, we're gonna spend two years building a very custom system to solve their problem, we'll deploy it. Chances are it won't work, because anybody who's built products knows that you can't just one and done a product. Doing product requires iteration. Then even if it does work, who's to say that customer still has that problem? So boom, the company's done. I feel like I saw this happen five to 10 times in a row to the point of, my god, if this happened to us, that would just be embarrassing. And so I think working with a diverse range of customers is this beautiful forcing function for building the right shape of product, which to us is a general robot. Right? We don't wanna build a Rube Goldberg machine that works really well for big industrial customer A or B. We wanna build a platform that is generally capable, robot bodies running generally capable robot models, that can immediately get to work. And if you can, you know, sign a contract in two weeks with a mid market customer and have a robot running immediately after that, and that's a totally different type of product and business than your other customers, you know you're being successful.