But it's not that. We're not talking about training narrowly intelligent ML systems for specific problems. You're right, that's a distinct skill. We're talking about a ML system that can write code based on some higher-than-now level of human input. What that level will/could be is what we're arguing about. Whether it has to be done by some kind of programmer-like person or whether it can be a more generic user/product-owner/product manager. I.e. someone who understands the problem domain but doesn't know too much about the solution domain/technology.

Those ML/AI systems will also have to be built, coded and trained but that's a job for a very small set of people compared to the total number of end users (and the total number of developers on the market today). And, as the ML/AI field stands, it always seem to turn out that specialized algorithms that do what the ML layer cannot do, get pretty quickly eliminated by the ML layer. So most solutions always gets closer and closer to end-to-end.