It can, like all the other tasks, it's not magic and you need to make the job of the agent easier by giving it good instructions, tools, and environments. It's exactly the same thing that makes the life of humans easier too.

This post is a case study that shows one way to do this for a specific task. We found an RCA to a long-standing problem with our dev boxes this week using Ai. I fed Gemini Deep Research a few logs and our tech stack, it came back with an explanation of the underlying interactions, debugging commands, and the most likely fix. It was spot on, GDR is one of the best debugging tools for problems where you don't have full understanding.

If you are curious, and perhaps a PSA, the issue was that Docker and Tailscale were competing on IP table updates, and in rare circumstances (one dev, once every few weeks), Docker DNS would get borked. The fix is to ignore Docker managed interfaces in NetworkManager so Tailscale stops trying to do things with them.

> it's not magic and you need to make the job of the agent easier by giving it good instructions, tools, and environments.

This. We had much better success by letting the agent pull context rather trying to push what we thought was relevant.

Turns out it's exactly like a human: if you push the wrong context, it'll influence them to follow the wrong pattern.

Thanks - that’s the maddening with flakes - is it the thing under test or the thing doing the testing? Hermeticity is a lie we tell ourselves :)