Anyone who has successfully completed a self-motivated project all on their own knows that the problem definition changes when the knowledge gaps go away. Sometimes even entire classes of solutions become pointless and their value goes from seemingly huge to nothing at all.

If we look into the past it's the difference between wanting to selfishly reconfigure the earth with physics-defying and godlike brute force creating massively worse and life-threatening problems... versus just building the shelter and infrastructure we now consider obvious and far less silly with smarter technology than just brute force and magic.

That's what I think is going to happen to all this pointless scaffolding currently being called "AI". It's a category of software that is completely unnecessary in a world where people are more experienced and better educated.

Of course it is unimpressive when someone does something familiar to you, that is subjective. That same thing could be framed as impressive, to someone else, such as the person who is now able to do the unfamiliar as if it is familiar.

The other bias would be to assume that there aren’t unfamiliar things (you don’t know every tool every made, therefore you may potentially benefit from using AI to help with learning new tools).

Another bias is to assume AI is only good for learning something unfamiliar. There are ways to contain generative coding that scale, in some contexts. Likewise there’s probably use cases even for power users, like organizing messy desktop icons into semantic clusters (automating tedious tasks), summarizing running processes, limiting engagement with brain rot, etc.