How I Built an AI-Powered Bounty Hunting System That Finds and Solves GitHub Issues Automatically

How I Built an AI-Powered Bounty Hunting System That Finds and Solves GitHub Issues Automatically Open source bounties are real money. Platforms like Algora, Expensify's Help Wanted program, and dozens of smaller bounty boards collectively post hundreds of issues per week with cash rewards attached -- typically $250 to $5,000 per issue. The problem is not supply. The problem is that by the time you manually find an interesting bounty, read the issue, clone the repo, understand the codebase, and write a fix, someone else has already submitted a pull request. So I built a system that automates the entire pipeline: monitoring bounty sources in real time, filtering for issues I can actually solve, analyzing the codebases, and generating candidate fixes. The monitor runs every 10 minutes on a cron job. When it finds something worth pursuing, it pings my phone. When I sit down to work, the solution is often already half-written. This article walks through the architecture, the actual code, t