Last year my team started using AI coding tools more heavily, and we found ourselves generating tons of code, but spending less time looking at the stuff that's been generated.
We felt like we were losing a bit of grip/understanding of what we were building. Regressions occasionally slipped through. Sometimes changes made it all the way to production only to be reverted later.
We tried several AI code review tools, but most operate at PR time. That felt too late. I wanted review to happen while the implementation was still fresh in the developer's mind at a team level (soft enforcement). I also wanted to emphasize responsibility for keeping prod stable with each individual engineer.
So I built git-lrc.
When you commit, git-lrc opens a review UI with your diff. It summarizes what changed, points out things that deserve a second look, and lets you quickly jump through the important parts of the change.
Over time, git-lrc has grown to check for around 100 common risk patterns across 10 categories, including security, reliability, performance, maintainability, etc.
Note that this is far from a formal review. It's a quick 60 seconds spent looking at your own work before it gets recorded in git.
It also generates a short "summary deck" that highlights the main changes, with special emphasis on potential risks. With git-lrc you can quickly sanity-check what you're about to ship and obtain greater confidence in what's been generated.
In my mind it is less of an AI reviewer and more as a habit for AI-assisted development: a small pause to make sure we understand and stand behind the code we're shipping.
Developers can review the change, vouch for it, or consciously skip the review. Those decisions get recorded in git history, creating a trail of how code was reviewed before it shipped.
It'd be great if you could take a look, give it a try in your projects or teams and let me know what you think.
Happy to take feedback from the HN community and improve it over time!