I had 4 old laptops collecting dust and was frustrated paying for AI coding tools. So I built Ralph Loops — a system that coordinates multiple AI agents to work on code overnight while I sleep.

  How it works:
  - Write tasks in markdown, commit to Git
  - Run `start-night.sh` before bed
  - Agents (old laptops on Tailscale) claim tasks, run Claude/Gemini CLI, push results
  - Manager agent reviews work, auto-creates fix tasks for failures
  - Morning: run `morning-review.sh` to see what happened

  What's actually working:
  - 95% overnight execution success rate
  - Git-based coordination (no central server)
  - Automatic retry/fix cycle for failed tasks
  - Heartbeat monitoring so I know agent status

  What's NOT magic:
  - You still write the task specs
  - AI makes mistakes — the manager catches ~70% automatically
  - Complex features need multiple task iterations
  - This is a "batch processing" model, not real-time pair programming

  Cost: ~$15/month electricity vs $500/month for Devin. Trade-off is you need the hardware and patience to set it up.

  Code is MIT licensed. Happy to answer questions about the architecture or failure modes (there were many).