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).
belter•1h ago
What are the most common failure modes?
okokwhatever•1h ago
Basically a cron engine calling an external API. Good enough
HappyVaxman•1h ago
belter•1h ago