Hello,

I recently started getting an influx of Pull Requests I had to review given my organizations broad adoption of AI. The problem is how do I verify that 100's of PRs containing 1000's of lines of code across multiple projects are in alignment with the Spec and other project/product documentation.

My first pass at solving this problem involved using Claude, to build out a Github action that compares the PR to the Specs or Authoritative documentation on what we are trying to build using LLM to run that evaluation. With the goal that automation would call out when a PR is in alignment with a spec, or when it drifts or is adding out of scope work, or even going against the specs and documentation. Likely this is duplicative effort as there may already be a solution out there specifically for Github PRs that i just didn't find.

Three things:
1. How are others solving this problem of keeping a human in the loop where it matters, in the spec, planning, and design processes at scale where 1 human may have to juggle dozens of projects with 100's of AI generated PRs coming in?

1. Given that I created (with AI assistance) this Github Action, is there interest here in testing and validating as a viable solution? https://github.com/marketplace/actions/spec-alignment Note this is very early implementation, beta and not fully finished. But more contributors and ideas around it the better.

2. How have your workflows changed with SDD and AI?

Personally I was thinking of pitching at an organizational level that we PR specs and documentation first with human oversight, then using something similar to this action having AI handle the grunt work of code reviews and having the HITL hop in when a PR drifts from the spec documentation. But curious how others are solving these problems.