RaptorCI – Catch risky code changes and weak tests before they ship

Hello! With more and more AI coding agents popping up and companies expecting higher output have you noticed more issues in production or other bottlenecks?

I’m a principal engineer at a leading cybersecurity company and we have a very lean engineering team and the expectations have shifted to us using AI to increase productivity instead of hiring. The result has been production becoming the most unstable it has ever been and bottlenecks around testing and releasing as we don’t have the resources to cope.

I spent a few weeks of thinking of ways that AI could help our full SDLC and one thing resonated with me. While ai code review tools are pretty awesome and have great results they’re moment in time reviewers looking more along coding practices than answering a major question of mine:

“What could break if we merge this code?”

I’ve decided to launch an early version of my devtool called RaptorCI. It’s super early stage but working on it pretty consistently at the minute to grow the idea and help small and medium sized engineering teams like ours.

Right now it analyses pull requests to surface: - Risky changes (auth, env vars, missing tests) - Explains why they matter - Gives you the steps to validate and fix any issues

It’s already running on a few repos and it’s super cheap at the minute while I validate the idea and would really appreciate any testing and feedback especially constructive!

Thank you!