Those are completely deterministic systems, of bounded scope. They can be ~completely solved, in the sense that all possible inputs fall within the understood and always correctly handled bounds of the system's specifications.

There's no need for ongoing, consistent human verification at runtime. Any problems with the implementation can wait for a skilled human to do whatever research is necessary to develop the specific system understanding needed to fix it. This is really not a valid comparison.

No, that is a terrible analogy. High level languages are deterministic, fully specified, non-leaky abstractions. You can write C and know for a fact what you are instructing the computer to do. This is not true for LLMs.

>And yet here we are, able to talk to a computer, that writes Pytorch code that orchestrates the complexity below it.

It writes something that that's almost, but not quite entirely unlike Pytorch. You're putting a little too much value on a simulacrum of a programmer.