The intent paradox of AI generated code (opens in new tab)

Wrt to premature optimization, in future, AI will write the most optimized for every general and obscure cases out of the box eking out every last blood of performance from any kind of hardware.

This will usher in the era of "hypermature optimization".

What if instead of static code our programs of the future are written/rewritten on the fly?

Imagine a simple todo application. Instead of a conditional filter on completed items the code itself changes to always and only return completed items upon request, spoken or otherwise.

Future code bases will contain more detailed specifications, design documents, and company guidelines and the code will become more of a byproduct, generated as needed. I already do this more and more with my LLM config files. This has already happened awhile ago with compilers replacing machine code and more recently with open source libraries replacing proprietary code. So, yes, more "intent" based documents, which represent a higher level abstraction of the problem.

This is an interesting perspective and certainly makes sense that the “why” always needs the human. What I think is clear for the moment is that AI coding helpers can’t deliver anything novel by themselves, although through luck they might stumble across new invention by combination of existing human thought. The question for me is, once the majority of AI code has been re-spidered and vectorized, and reused and reused, is there anything novel left?