Actually, all good engineering principles which reduce cognitive load for humans work for AI as well.

This is what's so funny about this. In some alternative universe I hope that LLMs never get any better. Because they force so much of good things.

They are the single closest thing we've ever had to objective evaluation on if an engineering practice is better or worse. Simply because just about every single engineering practice that I see that makes coding agents work well also makes humans work well.

And so many of these circular debates and other best practices (TDD, static typing, keeping todo lists, working in smaller pieces, testing independently before testing together, clearly defined codebase practices, ...) have all been settled in my mind.

The most controversial take, and the one I dislike but may reluctantly have to agree with is "Is it better for a business to use a popular language less suited for the task than a less popular language more suited for it." While obviously it's a sliding scale, coding agents clearly weight in on one side of this debate... as little as I like seeing it.

This is the big secret. Keep code modular, small, single purpose, encapsulated, and it works great with vibe coding. I want to write a protocol/meta language similar to the markdown docs that Claude et al create that is per module, and defines behavior, so you actually program and compose modules with well defined interfaces in natural language. I'm surprised someone hasn't done it already.