I built a tool to measure how much of my codebase is AI-written — here's how it works

Ask your team what percentage of your production codebase was written by an AI last quarter. You'll get silence — not because nobody cares, but because there's no way to measure it.

We instrument everything else. Deployments, latency, error rates, test coverage. But code provenance? Nothing. Git blame still assumes a human wrote every line.

I built aigit to fix this.

The problem

As AI coding tools became part of my workflow, I noticed something uncomfortable: I had no visibility into the quality or longevity of AI-generated code versus hand-written code. Was AI code churning faster? Did it correlate with bug fixes? Which files were effectively AI-authored?