TL;DR I built a multi-agent AI orchestration system and let AI generate an ebook from real tests, Git commits, and CLI-generated docs. Free, practical, and very in the trenches . What it is AI Team Orchestrator an AI-generated captain s log of the build: architecture, failures, fixes, and lessons learned. Why it s different Not theory. It s compiled from the actual dev exhaust (tests/commits/docs), so the narrative mirrors the real workflow. Who it s for Builders shipping with agents, founders validating AI ops, and devs curious about orchestration beyond toy demos. Link books.danielepelleri.com Ask (feedback welcome!) 1. Which chapter needs the most depth (architecture, evals, guardrails, ops)? 2. Would a starter repo + checklists be more useful than more chapters? 3. What s missing to apply this in a real startup stack? Self-promo, yes but I m genuinely looking for critique and use-cases. Happy to share the raw prompts/pipeline if helpful.