The Factory Kitchen for AI Agents

If you're putting AI agents to work, you need more than good prompts. You need an environment where agents can pick up context, work independently, learn from previous mistakes, and prove their results. We built one using team chat, isolated threads, shared Markdown files, and automated quality gates. It supported 2,389 agent sessions and more than 1,300 merged pull requests on our connectivity quoting platform. The most important lesson is that the agents don't need to remember everything. The system does. When I wrote about the dark software factory, I used manufacturing as the model: stations on a line, agents doing the work, humans in the control room. Lauren Tan challenges that framing in her talk, “2,000 PRs in a Month.” She prefers a Michelin kitchen to a software factory. Agents may cook the individual components, but you still own the final plate and the kitchen setup: the line cooks, the sous chefs, their equipment, their training. I think she's right. But there's another kitchen that helps explain what happens when you try to make this approach work across an engineering organization. For the past six months, we've been building a connectivity quoting platform for telecom advisors, largely with AI…