It's also why I urge junior engineers to not rely on AI so much because even though it makes writing code so much faster, it prevents them from learning the quirks of the codebase and eventually they'll lose the ability to write code on their own.
AI can fix it
I'm not defending or encouraging AI, just saying that argument doesn't work
It's been well documented that LLMs collapse after a certain complexity level.
(To anticipate the usual reaction when I point that out: if you're going to sputter with rage and say that compilers are deterministic while AI isn't, well... save it for a future argument with someone who can be convinced that it matters.)
Human involvement will end after the first phase, once the required test targets exist.
Basically we are going to have to stop micromanaging our toolchains and start telling them what outcomes we want. Call it "vibe coding lol" or whatever, that's how it's going to work. When you write code in a traditional high-level language, you are telling your compiler how to generate the code that actually gets executed by the CPU. But this object code, again, might as well be completely inaccessible as far as most developers are concerned. If the compiler were to achieve the same result in different, unknowable ways each time it runs, that's a horrifying notion to those same developers... but we all might as well get used to it, because soon there will be no other way forward.
Notice that the math guys are already having to deal with similar problems. Mochizuki or somebody drops a thousand-page proof on the community, and experts at the very highest levels have to waste years looking for bugs in it. They can't go on like this and they know it. They will have to give up the quaint idea of understanding something completely in order to prove or refute it, just as programmers and engineers will have to relinquish control over how our own creations work.