One way it can be useful is when you use it as a more verbal variant of rubber duck debugging. You'll need to state the issue that you're facing, including the context and edge cases. In doing so, the problem will also become more clear to you yourself.

Contrary to a rubber duck, it can then actually suggest some approach vectors, which you can then dismiss or investigate further.

I'm in a similar boat. The challenges I run into at work are often resultant of the weird infrastructure we use in our datacenters and our weird legacy software stacks, so there's no reason to believe AI will have anything in its training set that will help me. People don't realize that AI is only as good as their problem is ubiquitous. If you spend your time working on weird legacy systems, it can't possibly predict all the weird needles you need to thread when developing solutions.

I think it's a sensible position to be in. I tend to use AI in order to build awareness of it's capabilities. I find that sometimes it is useful for brainstorming or "tip of my tongue" searches but as you say the actual coding capabilities are exaggerated.

To me Cognition AI is doing what most other hype-based startups do which is generate good headlines so that VC money can keep pouring in. It is up to us to spot and question things that don't quite make sense... and anything with the words "AI understands X" don't make sense currently ^^

It is a typical Youtube clickbait title but the Youtuber in question doesn't seem to be nefarious, it does what it says on the tin :P I'd say the description covers what the video is about better.