PostgreSQL 19 is now expected around November 19. One of its committers, Peter Eisentraut, wrote that LLM-assisted code review was surfacing defects faster than the team could fix them, and roughly 8 to 10 significant features were reverted from the 19 branch after beta began. (The Register ran it as "AI reviewers delayed Postgres"; the project's own reasons are a bit more nuanced, but the pattern is worth noticing.)
Finding problems got cheap
A year ago the scarce thing was a careful reviewer. Now you can point several models at the same change and get a long list of concerns in minutes. That is great, until the list is longer than your week.
The hard part has moved:
- Which of these findings are real, and which are a model being confidently wrong?
- Which ones actually block a release, and which can wait?
- Who owns that call?
What I do as a solo builder
I build Brainstorm, a Linux app (1.0.1) where several AIs discuss the same goal. The workflow I ended up with is boring on purpose:
- Let more than one model argue about the plan, so disagreement shows up early instead of in review.
- Keep the check separate from the agents that wrote the draft, so "it ran smoothly" doesn't get mistaken for "it's right".
- Nothing reaches the project's main branch until a human approves it.
The point isn't more findings. It's a trail of who disagreed, what got checked, and who signed off.
You bring your own model accounts; I don't sell model credits.
If you're dealing with an AI review flood on your own projects, I'd like to hear how you triage it.
Top comments (0)