What happens when an AI architect performs 10 reviews of their architecture?

They become 10x better. I launched arch-review today — an open-source architecture review assistant with 4 specialized agents running in parallel. But the feature I'm most proud of isn't the speed. It's the memory. The evolution cycle: After each squad review, each agent logs a lesson: 🔐 Security Agent: "Always check for rate limiting on the API Gateway before checking internal authentication" 🛡️ Reliability Agent: "PostgreSQL shared between 2+ services = disguised SPOF" 📡 Observability Agent: "Local logs in EC2 without ship = first symptom of a system lacking an observability culture" These lessons are injected into each agent's prompt in the next review. Over time, the squad calibrates to your tech stack, your failure modes, and your business context. Evolution levels of each agent: 🌱 Fresh (0 revisions) — standard prompts 🟢 Growing (1-2) — begins to recognize your patterns 🔵 Experienced (3-7) — calibrated to your stack 🟣 Expert (8+) — highly customized The Evolution Dashboard