I've spent most of the past two weeks trying to get my AI to stop writing so goddamned much code. It's great that I can, say, completely switch between two databases, but I wish the AIs would develop a concept of energy spend or something and spend maybe a moment checking whether something is already implemented in the code base before blasting out 2000 new lines defining a new database access layer, and also rewriting random code it shouldn't be touching for some task hundreds of lines at a time just because it can. I don't care how easy it is to write some tests that sort of kind of cover it hopefully maybe... no new code is as tested as the stuff that has been doing it in the field for years already.
Just because it has the power doesn't mean it should be used.
I'm not asking for everything to be some sort of beautiful code whose concision would lead Knuth to tears. I'm just asking that you not slather dozens of existing functions with three new parameters and dozens of lines of code each that basically do nothing, to cover a use case that I accidentally vaguely alluded to, if you read my prompt a certain way, but isn't really what I was interested in.
Totally agree but I suspect that our desires are in contrast with ai companies profits
Right. There IS a way to convince ai to write less code.. but it obviously spends 10x tokens, whether it’s LLMs as judge and automated review or just write 10 solutions and keep 1. Partly ai companies like it this way but partly it’s unintentional consequences that happen to work in their favor.
Training for good taste in architecture actually causes premature optimization at high effort allowance, but at the same time, it is combined with an inability to even recognize / exploit that later if it should ever become actually useful. Dial the effort down, and it skips the reasonable abstraction and nothing is dry, factoring is insane.
Goldilocks for simple stuff barely works with frontier models after they are out of their comfort zone for topic or line limits.. you kind of just have to decide whether it’s worth it anyway. In practice.. constant supervision for high quality code, or such high quality system design that the code quality is less of a down side.