Fwiw, that's not what the parent was talking about.
You're trying to middle road it. He was talking about actually treating it as a black box, so just give the model your expectations and goals it needs to meet, not tell it a rough solution for it to apply in detail.
The expectation/goal approach in a ai edited project works better then the middle road since opus5.5 ime. Depending on your project structure, it may not be viable however without large refactorings
Expectations and goals can be technically nonsensical. Agents have gotten really good, but they can’t magically solve intractable problems. If you’re out of your technical depth it can be easy to set unrealistic expectations without realizing it
For me it's really hard to find a balance with LLMs. Even trying one to add .NET IR codegen to my compiler that already had a working C++, JS, and C# backend for it to use as a reference. It just kept doing really odd stuff and when we got to generics it had done such a bad job with the prior work it struggled to collect the information it needed from .NET to do generic calls correctly, and mid session decided to just make everything reflection based with no notice to me. It had a doc of the AST with notes on what the nodes mean and how different constructs are represented, it's a pretty typical ML family language. Plus a working C# backend to reference.
Other times it will one shot things near perfectly that I was expecting to just use as a reference. Demo pages for work I've done its so fast and gets good enough right out the door
Every time I've tried to use it to write something small in my compiler? :"( pain. It's the perfect intersection of looks good and covers 90% of cases fine but explodes far away because some subtle invariant is wrong. I can't always think of the invariants up front without writing the code myself