I built an AI agent that fixes my CI failures at 3am

I do contract development work. The repos I work on have continuous integration that runs tests on every pull request. Sometimes tests fail at inconvenient times.

I used to wake up, check GitHub, read the error, fix it, push, wait for CI to pass, then start my actual day. Now my AI agent does it.

The setup

A cron job runs every 30 minutes and checks all my open PRs. If CI passes, it does nothing. If something fails, it pulls the logs, reads the error, checks out the branch, fixes the code, commits, and pushes. Then it texts me what it fixed.

I wake up to a message like: "PR #14 had a type error in the auth module. Fixed and pushed. CI passing now."

How it works

The agent runs on OpenClaw, an open-source AI agent framework. The CI monitor is a cron job that spawns an isolated sub-agent running Claude Sonnet. The sub-agent has access to the repo via git and the GitHub CLI. It reads the failing run logs, diagnoses the issue, checks out the branch, makes the fix, and pushes. The whole cycle takes about 5 minutes.

Does it actually work?

It doesn't always get it right. Complex architectural issues or flaky tests sometimes need human judgment. But for the 80% of CI failures that are typos, missing imports, type mismatches, or config issues, it handles them faster than I could.

The cost of this specific automation is essentially zero. It only runs when something fails, and each fix costs maybe $0.10 in API tokens. The time it saves me is 15-30 minutes per failure, several times a week.

The bigger picture

This is one example of what we're building at Boland Company. Not just chatbots that answer questions, but agents that take action on your actual systems. If you have repetitive technical workflows that eat your time, we can probably automate them.