It is an old pattern, see for instance: https://www.versobooks.com/products/688-breaking-things-at-w...
I've seen perfectly legit looking code generated by chatgpt, except that the value of the constants were wrong.
When you have to verify every single little thing, it's easier to just do it. And certainly doesn't take any less skill.
I wonder if this is a natural development of economic optimization.
Computability theory taught us that it is in general easier to verify that an answer is correct (P) than to come up with the answer in the first place (NP).
Verification becomes more productive than sythesis only when the probability of generated content being correct is significantly high. So I suppose, as AI gets more accurate, verification will become more productive.
I'm in a peculiar position with Bing AI. My work provided me an enterprise account, so I can use it for work-related tasks. Often I find myself asking it to write a program for something I don't wanna do myself from scratch, then I just analyze it, see why it doesn't work and fix it. It has got to a point where it's much faster for me to do that, than to read the relevant documentation and figure out how to do it from scratch.
Thus the state of the art was produced by the art.