I often think “what will ‘maintainable’ code look like in the future?” given this kind of thing. Much of ‘good coding’ is about optimising the codebase for workability for a human intellect with human working memory.

Though having said that, from the studies I’ve come across it seems like LLMs tend to generate more verbose code but perform better over the long-term when the code is maintained and not allowed to sprawl all over the place.

I’m mainly using AI for tools development and in that context I often wonder if I’ve just developed a career-long habit of over-abstracting. Like, the tools work without all the fuss I might have put in at the beginning and you just iterate and evolve as you go.

Is this assuming or studying human maintenance?

I’ll dig up the references but I believe they were studying what happened to LLM performance as the complexity and verbosity of the code went up (ie- just letting the LLM rip without doing explicit code cleanup and simplifying).