You'd want to have the alteration reference existing guides to the current implementation.

I haven't jumped in headfirst to the "AI revolution", but I have been systematically evaluating the tooling against various use cases.

The approach that tends to have the best result for me combines a collection of `RFI` (request for implementation) markdown documents to describe the work to be done, as well as "guide" documents.

The guide documents need to keep getting updated as the code changes. I do this manually but probably the more enthusiastic AI workflow users would make this an automated part of their AI workflow.

It's important to keep the guides brief. If they get too long they eat context for no good reason. When LLMs write for humans, they tend to be very descriptive. When generating the guide documents, I always add an instruction to tell the LLM to "be succinct and terse", followed by "don't be verbose". This makes the guides into valuable high-density context documents.

The RFIs are then used in a process. For complex problems, I first get the LLM to generate a design doc, then an implementation plan from that design doc, then finally I ask it to implement it while referencing the RFI, design doc, impl doc, and relevant guide docs as context.

If you're altering the spec, you wouldn't ask it to regen from scratch, but use the guide documents to compute the changes needed to implement the alteration.

I'm using claude code primarily.