Episode summary
What iPhone Packaging Reveals About the Robotics Opportunity
The a16z Show
· · 45 min · Hosts: Erik Torenberg · Guests: Josh Gruenstein, Martin Casado, Raghu Raghuram
Summary
Tutor Intelligence argues that robotics is not mainly a model problem, but a systems problem that only works when intelligence, hardware, manufacturing, supply chain, and customer adoption are designed together. The company started from the idea that deploying robots into real jobs would generate the data needed to improve them, rather than trying to solve robotics in the abstract first.
The guest says Tutor has robots deployed across the United States, from small businesses to Fortune 50 and Fortune 100 companies, and claims those robots have helped manufacture and ship over a quarter of a billion products. The business is built around a feedback loop: robots do work, human tutors step in when needed, and the resulting data improves the models. That loop, the guest says, matters more than any single architecture change.
The discussion also emphasizes that most customers are first-time robot buyers, so the pitch centers on economics rather than AI branding. Tutor says it can quote robots at roughly $16 an hour, move from first call to signed contract in 40 to 60 days, and get robots working on site quickly. The company is also verticalizing hardware and building its own robots in Watertown, Massachusetts, including Cassie and Sunny, while betting that more flexible robotic labor could reshape factories, logistics, and eventually broader physical industries.
Key takeaways
- The guest says Tutor’s core advantage is a data flywheel: deploy robots, collect real-world work traces, and use tutors and reinforcement learning to improve capability over time.
- Tutor claims its robots have helped manufacture and ship over a quarter of a billion products and are deployed across the U.S. at small businesses and large enterprises.
- The company says most of its customers are first-time robot buyers, so it wins by selling an economic proposition around roughly $16 an hour rather than by leading with technical jargon.
- Tutor is vertically integrating hardware and manufacturing in Watertown, Massachusetts because, in the guest’s view, robotics requires trade-offs across the full stack, not just software.
- The guest believes spatial reasoning advances in frontier models are accelerating robotics, but that real-world robot data remains the long-term moat.
Notable quotes
“We see a lot of robot pitches. Very few people thinking about what the robot is supposed to do at the end of all of this”
“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”
“we have robots deployed across the United States everywhere from small mom and pop businesses to Fortune50, Fortune 100 businesses”
“we have 100 sunnies operating in Boston in our data factory collecting data for internal use and advancing our research agenda”
“We called them up and we're saying, "Hey, have you ever considered a robot for 16 bucks an hour”
How the episode opens
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.
We see a lot of robot pitches. Very few people thinking about what the robot is supposed to do at the end of all of this. — 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 to American consumers. We're training frontier robot AI models, manufacturing robots at scale and directly deploying into the largest businesses in the supply chain.
How does product innovation work in robotics? Most companies are just on V1 whereas you're got two versions of the robot and you continue to iterate really fast. — So Josh, thanks for uh for joining us. So, uh, we're with Josh Gruinstein, who is the CEO and founder, co-founder of of, um, Tutor Intelligence, and we're going to be talking about robots today. And so, maybe before we jump in, just give a quick background maybe of yourself and then the company.
Yeah. So, I'm Josh. I started tutor about five and a half years ago uh with the core thesis that if you could just start deploying robots out into the world into 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 uh 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.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- robotics systems problem
- ai and hardware
- human tutors training data
- spatial reasoning
- robotic labor for manufacturing
Companies and tickers mentioned
- Tutor Intelligence
Watch the episode
Watch “What iPhone Packaging Reveals About the Robotics Opportunity” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
More from The a16z Show
-
How AI Could Bring Halo and Other Classic Games Back to Life -
Mike Volpi on Why AI Infrastructure Will Outlast the Hype Cycle -
Why HubSpot’s Co-Founder Is Betting Against the SaaSpocalypse -
Inside Salesforce’s Acquisition Strategy for the AI Era -
How AI Is Turning Figma’s Finance Team Into Builders -
The New AI Agents That Shop, Plan, and Gossip
The a16z Show, this episode and its artwork belong to Andreessen Horowitz. Octagon is not affiliated with the show; this page is an independent summary.
