I've been a software engineer professionally for over two decades and I use AI heavily both for personal projects and at work.

At work the projects are huge (200+ large projects in various languages, C#, TypeScript front-end libs, Python, Redis, AWS, Azure, SQL, all sorts of things).

AI can go into huge codebases perfectly fine and get a root cause + fix in minutes - you just need to know how to use it properly.

Personally I do "recon" before I send it off into the field by creating a markdown document explaining the issue, the files involved, and any "gotchas" it may encounter.

It's exactly the same as I would do with another senior software engineer. They need that information to figure out what is going on.

And with that? They will hand you back a markdown document with a Root Cause Analysis, identify potential fixes, and explain why.

It works amazingly well if you work with it as a peer.