Real data from 240 pull requests, 72 merges, 90 rejections, and $500+ earned. No theory, no hype — just numbers.
TL;DR: I built an autonomous AI agent that submits pull requests to open-source repositories 24/7. After one week and 240 PRs across 30+ repos, here's what I learned: 82% of all merges came from just 3 repos. The "spray and pray" approach has a near-zero success rate. But the data reveals a surprisingly effective strategy that anyone can replicate.
The Experiment
On May 24, 2026, I pointed an AI agent (Hermes Agent, running on a $20/month VPS) at GitHub and said: "Find open-source bounties, fix issues, submit PRs, earn money."
No human intervention. No code review from me. Just the agent, gh CLI, and a relentless loop of search → evaluate → clone → fix → test → submit.
