00:00:00 · Josh Gruenstein, Raghu Raghuram
[00:00:00] S0: No matter what anybody says, today in 2026, we have a highly interconnected, interdependent global supply chain. Both US companies and Chinese companies are thinking very hard about what does the long term strategy of this look like and ultimately, everybody trying to build their industrial capacity. [00:00:18] S1: We see a lot of robot pitches. Very few people are thinking about what the robot is supposed to do at the end of all of this. [00:00:23] S0: Almost everybody we're selling a robot to has never purchased a robot before. Almost all of the market is greenfield. The reality is you need to build a full stack platform. Tutor robots have helped manufacture and ship over a quarter of a billion products Wow. To American consumers. We're training frontier robot AI models, manufacturing robots at scale, and directly deploying into largest businesses in the supply chain. [00:00:44] S1: How does product innovation work in robotics? Most companies are just on V1, whereas you've got two versions of the robot and you continue to iterate really fast.
00:00:44 · Raghu Raghuram, Erik Torenberg, Martin Casado
[00:00:44] S1: How does product innovation work in robotics? Most companies are just on V1, whereas you've got two versions of the robot and you continue to iterate really fast. [00:00:55] S2: So most factories and warehouses in America still rely heavily on people for physical work. What does it take to build robots that can actually do those jobs? In this episode, Martin Casado and Raghu Raghuram sit down with Tutor cofounder and CEO Josh Gruenstein to unpack a different approach to building general purpose robots. Tutor deploys robots into factories and warehouses, connects them to human operators when needed, and uses that real world work to generate training data that makes the robots increasingly capable. They discuss why robotics require solving AI, hardware, manufacturing, and go to market at the same time, and why Josh believes general purpose robots could ultimately become a new labor substrate for the physical economy. [00:01:41] S3: Josh, thanks for joining us. So we're with Josh Gruenstein, is the CEO and founder... Cofounder of Cofounder. Tutor Intelligence. And we're gonna be talking about robots today. And so maybe before we jump in, just give a quick background maybe of yourself and then the company.
00:01:41 · Martin Casado, Josh Gruenstein
[00:01:41] S3: Josh, thanks for joining us. So we're with Josh Gruenstein, is the CEO and founder... Cofounder of Cofounder. Tutor Intelligence. And we're gonna be talking about robots today. And so maybe before we jump in, just give a quick background maybe of yourself and then the company. [00:01:56] S0: Yeah. So I'm Josh. I started Tutor about five and a half years ago with the core thesis that if you could just start deploying robots out into the world and to all the places in the physical economy where robots are needed the most, you could start to build the data sets, the models, and the supply chain that's needed to proliferate robots throughout the physical economy. So we're about 160 people based primarily in Boston, and we're training frontier robot AI models, manufacturing robots at scale, and directly deploying into the largest businesses in the supply chain. [00:02:29] S3: And can maybe talk a little bit about... We see a lot of pitches. There's a lot of companies that talk about doing robotics, but don't actually deploy robots or have not yet. And you're one of the few companies that's actually deployed robotics as a CEO, so maybe just talk about the state of the business.
00:02:29 · Martin Casado, Josh Gruenstein
[00:02:29] S3: And can maybe talk a little bit about... We see a lot of pitches. There's a lot of companies that talk about doing robotics, but don't actually deploy robots or have not yet. And you're one of the few companies that's actually deployed robotics as a CEO, so maybe just talk about the state of the business. [00:02:43] S0: Yeah, we have robots deployed across The United States, everywhere from small mom and pop businesses to Fortune 50, Fortune 100 businesses. Claude told me last night that it estimates Tutor robots have helped manufacture and ship over a quarter of a billion products Wow. To American consumers. So presumably, most American consumers are a Tutor customer a couple layers down. I think this comes from kind of the origin story of the business, which is us looking at the state of robot learning. It was obvious to us that robot intelligence and robot software was this bottleneck. Robots for sixty years have been this custom engineer in machines. That can't scale. Yeah. Yeah. So we started the company with this thesis that if we could just start deploying robots, we could build the label data sets that help us train these models and deliver this value to the American consumer.
00:02:43 · Josh Gruenstein, Raghu Raghuram
[00:02:43] S0: Yeah, we have robots deployed across The United States, everywhere from small mom and pop businesses to Fortune 50, Fortune 100 businesses. Claude told me last night that it estimates Tutor robots have helped manufacture and ship over a quarter of a billion products Wow. To American consumers. So presumably, most American consumers are a Tutor customer a couple layers down. I think this comes from kind of the origin story of the business, which is us looking at the state of robot learning. It was obvious to us that robot intelligence and robot software was this bottleneck. Robots for sixty years have been this custom engineer in machines. That can't scale. Yeah. Yeah. So we started the company with this thesis that if we could just start deploying robots, we could build the label data sets that help us train these models and deliver this value to the American consumer. [00:03:32] S1: We see a lot of robot pitches. 99% of them start with some insights about the model and how you're gonna build a model or some insight about the data, shape of the data that is. And very few people are thinking about what the robot is supposed to do at the end of all of this. You started from the reverse, and you had the insight that you could actually tutor the robot, so to speak. Yeah. That's the name of your company. Where did that insight come from?
00:04:03 · Josh Gruenstein, Raghu Raghuram
[00:04:03] S0: It came from kind of this thought experiment, where we had this insight that, hey, there are 8,000,000,000 people on Earth who all have this baseline physical intelligence that we want our robots to have. And so imagine you had infinitely powerful software that could connect any human being on Earth to any robot and kind of embody that robot with intelligence. That's kind of like this deus ex machina of suddenly you have unlimited, infinite robot intelligence. Let's say you take that for granted, now what? Right? The problem isn't actually solved. Right? You still need to actually manufacture robots at scale. Right? Robots are this cottage industry today in The United States. Robots are rounding error even in the most automated industries, like manufacturing logistics. So that doesn't exist. Certainly none of the software exists, and none of the customers exist because, again, the robots can't do any of the jobs that customers want robots to do. So robotics is not, I think, any one layer of the stack. It's not just about intelligence. It's not just about hardware. It's not just about the customer. It's about kind of figuring out how to put all these three pieces together, and it's the combination of all three that actually lets you build, in my view, a successful platform at any one of those layers. [00:05:10] S1: Yeah. In total, we talk about robotics being the ultimate systems company Yeah. Yeah. As opposed to being one one of the other.