The section "Forget the Theory of Computation, AI will Soon Replace Programmers" feels as if it's missing a practical slant that explains this trend. I think approaching it from a purely theoretical perspective misses the relationship between real software and real problems.

First: most practical problems are computable, and most practical programs do not run forever. Even if an agent had to run a program to termination, it could still use the feedback gathered from running it to make modifications.

Second: an agent with a sufficiently good intermediate representation _which is computable_ doesn't need to actually execute a program to model its behavior. Humans do this all the time--we can read code and understand its approximate function as a means to edit it. I don't want to claim that LLMs have a concept of "understanding," but they definitely build an intermediate representation which, when combined with external input (e.g. having to kill a program, because it exceeded a timeout), can be used to modify the program.

Now with all of that said: I don't feel confident about whether or not AI is actually serious risk to programmers, I just don't feel as if this argument is sufficiently compelling.