I think, there are different niches. AI works extremely well for Web prototyping because a lot of that work is superficial. Back in the 90s we had Delphi where you could make GUI applications with a few clicks as opposed to writing tons of things by hand. The only reason we don't have that for Web is the decentralized nature of it: every framework vendor has their own vision and their own plan for future updates, so a lot of the work is figuring out how to marry the latest version of component X with the specific version of component Y because it is required by component Z. LLMs can do that in a breeze.
But in many other niches (say embedded), the workflow is different. You add a feature, you get weird readings. You start modelling in your head, how the timing would work, doing some combination of tracing and breakpoints to narrow down your hypotheses, then try them out, and figure out what works the best. I can't see the CLI agents do that kind of work. Depends too much on the hunch.
Sort of like autonomous driving: most highway driving is extremely repetitive and easy to automate, so it got automated. But going on a mountain road in heavy rain, while using your judgment to back off when other drivers start doing dangerous stuff, is still purely up to humans.