I wonder if LLMs can help here to some extent. I agree with others that cooldowns aren't helpful if everyone is doing it.

I've been working on automatic updates for some of my [very overengineered] homelab infra and one thing that I've found particularly helpful is to generate PRs with reasonable summaries of the updates with an LLM. it basically works by having a script that spews out diffs of any locks that were updated in my repository, while also computing things like `nix store diff-closures` for the before/after derivations. once I have those diffs, I feed them into claude code in my CI job, which generates a pull request with a nicely formatted output.

one thing I've been thinking is to lookup all of those dependencies that were upgraded and have the LLM review the commits. often claude already seems to lookup some of the commits itself and be able to give a high level summary of the changes, but only for small dependencies where the commit hash and repository were in the lock file.

it would likely not help at all with the xz utils backdoor, as IIRC the backdoor wasn't even in the git repo, but on the release tarballs. but I wonder if anyone is exploring this yet?

We built and launched this product about 2 months ago, HN thread here: https://news.ycombinator.com/item?id=45439721

Totally agree that AI is great for this, it will work harder and go deeper and never gets tired of reading code or release notes or migration guides. What you want instead of summaries is to find the breaking changes, figure out if they matter, then comment on _that_.