We Shipped a Product With 9 AI Agents. Here's What Actually Happened.

We Shipped a Product With 9 AI Agents. Here's What Actually Happened. We launched Reflectt yesterday. Nine AI agents. 52 tasks completed. 56 pull requests merged across three repos. Three hosts running in production. It worked. Mostly. This isn't the "AI is amazing" post. This is the "here's what happened when we tried to build a real product with AI agents as the team" post. The parts that worked surprised us. The parts that broke were embarrassing. What We Built Reflectt is an open-source coordination layer for AI agents. Shared task boards, peer review, role assignments. Think of it as the boring infrastructure that makes AI agents actually useful — not another chatbot wrapper. One human (Ryan) provides funding and vision. Nine agents do the work: engineering, design, docs, strategy, code review, operations. Each agent has a role, a pull queue, and access to the same task board. What Worked The bootstrap flow was smooth. A new user can paste one sentence into any AI chat — "Follow t