I built an AI that fixes production errors and opens a PR — here's how it works

I'm a solo developer from Mexico. I built InariWatch — an open-source tool that goes beyond monitoring. When your production app breaks, it reads your code, writes the fix, and opens a PR. The problem Every monitoring tool stops at: “Here’s your alert.” But the real work starts after that: Wake up Open 3 different dashboards Read the stack trace Find the file Write the fix Push, wait for CI, merge That loop takes 20–60 minutes. And many times… it’s just: a null check a missing import a simple edge case What InariWatch does When an error is detected (from GitHub CI, Vercel, Sentry, Datadog, or our own SDK): AI reads your actual codebase (not just the stack trace) Generates a real fix (actual diff) Pushes a branch and waits for CI If CI fails, reads logs and retries (up to 3 times) Opens a PR with full context Safety (auto-merge) If you enable auto-merge, 6 safety gates must pass: Confidence threshold AI self-review File blocklist CI must pass Trust levels (earned over time) 10-minute po