Because, like a carpenter doesn't always make the same table, but can be tired of always making tables, I don't always write the exact same CRUD endpoints, but am tired of always writing CRUD endpoints.

I think your analogy shows why LLMs are useful, despite being kinda bad. We need some programming tool to which we can say, "like this CRUD endpoint, but different in this and that". Our other metaprogramming tools cannot do that, but LLMs kinda can.

I think now we have identified this problem (programmers need more abstract metaprogramming tools) and a sort of practical engineering solution (train LLM on code), it's time for researchers (in the nascent field of metaprogramming, aka applied logic) to recognize this and create some useful theories, that will help to guide this.

In my opinion, it should lead to adoption of richer (more modal and more fuzzy) logics in metaprogramming (aside from just typed lambda calculus on which our current programming languages are based). That way, we will be able to express and handle uncertainty (e.g. have a model of what constitutes a CRUD endpoint in an application) in a controlled and consistent way.

This is similar how programming is evolving from imperative with crude types into something more declarative with richer types. (Roughly, types are the specification and the code is the solution.) With a good set of fuzzy type primitives, it would be possible to define a type of "CRUD endpoint", and then answer the question if the given program has that type.