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Replit CEO Amjad Masad describes AI agents running a self-driving company
Replit CEO Amjad Masad said at TechCrunch Disrupt that AI agents now handle much of the company's routine work, a model he called the self-driving company. He said agents are changing what people work on rather than taking jobs.
Key points
- Masad said AI agents now handle much of Replit's routine work.
- A Replit agent triages support tickets using GitHub issues, the codebase and Linear.
- Masad said agents change what people work on rather than taking jobs.
What happened: Replit CEO and co-founder Amjad Masad spoke at TechCrunch Disrupt in San Francisco on Thursday, TechCrunch reported. He described what he called a self-driving company, where AI agents handle much of the routine work and people are valued for their judgment and taste.
The details: Masad said Replit's own operations changed over the past year, particularly after AI agents became more reliable earlier in 2026. "Our company entirely changed how we operate," he said. In one workflow, an agent first triages customer support tickets by reviewing GitHub issues, the codebase and Linear tickets. When a support person submits a patch, deploying another agent takes a single click. "You need human judgment; you need taste," Masad said.
Who it affects: Masad said agents are changing what people work on rather than taking jobs. "We're spending a lot more time figuring out what to work on," he said, pointing to more whiteboarding and architecture discussions. He said his conversations with other businesses focus on how AI can make people more productive and happier, since agents make work less boring and more creative.
What to watch: Businesses are adopting Replit's AI coding tools to build and launch their own software, according to TechCrunch. Masad also said, "There's a positive vision of the world that Silicon Valley is not really putting out." Replit has not disclosed metrics on how its agent workflows affected output or headcount.
Our take
Replit's support workflow is a concrete example of how teams can chain agents across ticketing, code and deployment while keeping humans on judgment calls.