alt Hacker News> I agree that LLMs are naturally anti abstraction machines.. I'm often trying to find way to reverse that.
I am a bit of an LLM cynic but I am trying to learn it all, and I have to say I have spent most time trying to work out: how do you explain how a brown-field codebase actually works, in such a way that the LLM won't pervert it through misunderstanding.
It does encourage you towards the "conventional" coding standard for any new project, because you want to use a pattern that it will have seen in its training set.
But for example there are differences of opinion in how wordpress plugins (which have a very complex control flow) should be structured. LLMs are incredible at knowing how WP works, actually, but what is difficult is explaining how your methodology for a large plugin is going to work.
It is a battle — but a useful one because it can be used for, er, studying the comparative belief systems of the LLMs.
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They don’t have a useful belief system, one of the rookie mistakes of using LLMs is asking them what you “should” do
The gold standard is code samples. I've got 1000-line convention documents with very simple rules like "Early returns on a single line". Llms sometimes ignore these or misinterpret them in unusual ways.
But if I tell it "read these files that use the same conventions" first, there's no misunderstanding, and the agent also picks up the general "tone" of the code. I have very little to tweak if I've defined the problem well.