I agree with your last point - with an added dash of being wary of getting dependent on sophisticated tools that have one vendor. I'm not skeptical of the idea

I agree with your last point - with an added dash of being wary of getting dependent on sophisticated tools that have one vendor. I'm not skeptical of the idea at all, however. I see it as the rough analogy of mathematicians using proof assistants. This is a coding assistant. It's generally true that the vast, vast majority of code one writes is boilerplate or otherwise rote. The core logic and control flow that defines the meaningful bits of any complex program are nested in the middle of tons of error handling, logging, data munging, incidental book-keeping, and other very prosaic tasks. It will not just be handy to have a friendly intelligence assist in these tasks. It doesn't require much "intelligence" (of the sort required for figuring out what the program should do in the first place and how to architect it). Once the technology gets firmed up a bit, the productivity multiplier will be palpable and impossible to ignore. Programmers using these tools will complete tasks faster than ones that don't, and the market will shift. Further extensions of this technology lead to automatic generation of unit tests, automatic refactoring, etc. These all exist as very specialized tools that are explicitly coded, but it's clear to see that adding a bit of ML-driven intuition to them would greatly increase their scope and effectiveness.