Paving the Way for AI Agents in Retail: Exclusive Interview with Factory CEO Matan Grinberg

McKinsey TechnologyPaving the road for AI agents: Interview withFactory CEO Matan Factory CEO and cofounder Matan Grinberg discusses why scaling AI insoftware engineering depends less on flashy demos and more on changesto the operating model and how teams work. In April 2023,Matan Grinberg left a PhD program in theoretical physics to found Factory, whichbuilds software development agents called Droids for enterprise environments. In aconversation with McKinsey Senior Partner Martin Harrysson, he reflected on what it takes tomove from AI pilots to scaled adoption, how agent-native development changes engineers’ daily This interview has been edited for length and clarity. Martin Harrysson:You started your career in theoretical physics. How did that lead to founding Matan Grinberg:I spent about a decade as a theoretical physicist, working on quantum fieldtheory, general relativity, and string theory. It was while I was at UC Berkeley for my PhD that Irealized physics was not what I wanted to do for the rest of my life. I started taking AI courses and became interested in what was then called program synthesis,now called code generation. The idea that AI systems—built in code—could actually write code After about a year and a half exploring that, it became clear to me that the best way to pursue itwasn’t through academia but by starting a company. I cold-emailed a former physicist who isnow at Sequoia [a venture capital firm in Silicon Valley]. We went on a long walk, and he Martin Harrysson:Many enterprises have experimented with AI in software development, butnot all have seen a step change in impact. What differentiates those that are scaling? Matan Grinberg:Since day one, our mission has been to bring autonomy to softwareengineering. We build software development agents—which we call Droids—designedspecifically for enterprises. But they’re not just for vibe coding or building a website from That’s where enterprises actually get stuck and where a lot of potential is locked up. We like to use an analogy: Software development agents are like Ferraris. But if you drop aFerrari into San Francisco in 1850 with dirt roads and horses, it’s not going to perform well. Youmight crash it into a ditch and conclude that cars don’t work. Before organizations can really In practice, that means documentation, test coverage, CI/CD [continuous integration andcontinuous delivery], observability, linters, integrations with internal tools, and access to the kindof tacit knowledge human engineers rely on. If those things aren’t in place, agents struggle.If Martin Harrysson:What convinces organizations to make that investment in paving the roads? Matan Grinberg:In every organization, there are AI enthusiasts—the people who are willing totake a bet on their reputation and have their team try this out. They’ll go and pave a small stretch If you’re working with the right people, they know which engineers to bring over and say, “Lookat this.” And especially when the work involves something like a legacy migration where no onewants to spend more time than necessary, engineers are very open to something that makes the Once that small area shows real results, others in the organization are much more willing to pavemore roads and try it themselves. But it typically starts with a few people who are willing to go Martin Harrysson:You’ve described paving the roads as an enterprise challenge. How have youapproached it at Factory, and what has changed in how your engineers work? Matan Grinberg:The enemy of AI agents is tacit knowledge—things discussed but not writtendown. If I know something that an AI agent doesn’t, I have to remember to tell it. That creates Internally, we record every meeting. Our Droids generate notes and store them in a repository. Ifa prompt from an engineer is incomplete, a Droid can look at how Factory typically makes We also have Droids that automatically start working on tickets the moment they’re created. If acustomer reports a bug, a Droid tries to reproduce it, fix it, and test the fix in a virtual The mindset shift is that the new directive isn’t to write a line of code. It’s to delegate to anagent. Before a meeting or before going to bed, engineers think about what they can offload.You can ask an agent to try five different approaches overnight, and then you can review the Martin Harrysson:If the focus in the product development life cycle shifts from writing code todelegating work to agents, traditional role boundaries begin to blur. How does that change Matan Grinberg:I think it clarifies ownership. Before, someone could say, “I don’t write code, so that’s not my fault.” Now code is more of atool across roles. In our sales organization, for example, people ship code for automations The distinction shifts away from who produces which input and toward outcomes. Who owns thecustomer outcome? Who owns a feature’s adoption? If something goes wrong, who is That focus on scope and ownership