Even as a principal software developer and someone who is skeptical and exhausted with the AI hype, AI IDEs can be useful. The rule I give to my coworkers is: use it where you know what to write but want to save time doing it. Unit tests are great for this. Quick demos and test benches are great. Boilerplate and glue are great for this. There are lots of places where trivial, mind-numbing work can be done quickly and effortlessly with an AI. These are cases where it's actually making life better for the developer, not replacing their expertise.

I've also had luck with it helping with debugging. It has the knowledge of the entire Internet and it can quickly add tracing and run debugging. It has helped me find some nasty interactions that I had no idea were a thing.

AI certainly has some advantages in certain use cases, that's why we have been using AI/ML for decades. The latest wave of models bring even more possibilities. But of course, it also brings a lot of potential for abuse and a lot of hype. I, too, all quite sick of it all and can't wait for the bubble to burst so we can get back to building effective tools instead of making wild claims for investors.

I think you've captured how I feel about it too. If I try to go beyond the scopes you've described, with Cursor in my case and a variety of models, I often end up wasting time unless it's a purely exploratory request.

"This package has been removed, grep for string X and update every reference in the entire codebase" is a great conservative task; easy to review the results, and I basically know what it should be doing and definitely don't want to do it.

"Here's an ambiguous error, what could be the cause?" sometimes comes up with nonsense, but sometimes actually works.