Abstraction can be done well, or terribly, and there seem to be both objective and subjective dimensions to it.

For example, the program runs 20,000x times slower, or you need to go thru 12 layers of indirection to find a boolean. (Not making up either of those examples, sadly.)

So I don't think it makes sense to be for or against abstraction. It depends on the context, and on the execution.

That said, my point earlier was, it's silly to me that people are designing abstractions specifically "for AI" when AI can happily work on minified outputs, raw weights, etc. (It builds up its own abstractions in the transformer layers.)

There's probably a difference in efficiency, but we might be surprised, and I haven't seen anyone measure that.

So considering the LLM can happily ingest the entire codebase, in abstraction-free form, and operate productively on that level, then the value of abstractions, as far as I can tell, is for the humans alone — so that we can continue understand what is going on. Otherwise we might as well accept defeat and let the AI do its business in assembly.