They do have "everything" but that's too much, I think. They need to have direct instruction that is in the context, that is appropriate for the project and codebase at hand. In the whole universe of training data, there's every approach imaginable. What's needed is enough guidance to identify the right approach consistently.

I recognize that crafting a 'perfect' prompt is impossible, but neither is writing the perfect code, or even the 'perfect' code style guide. But it is 100% the kind of problem that can be iteratively improved to a point where it's much better than what you get by one-shotting everything without much consideration of these details.

I myself am maybe 5% sophisticated if 0 is I just discovered LLMs today, and 100 is the most skilled at using AI the world has seen. What I've learned so far is that I have a lot of room to improve.

Which is why I am actually not completely worried about the careers of current software engineers: If you brought in a bunch of non-engineers to prompt Claude to build and maintain an ERP system, or a social networking site, or an ad exchange, or even Shopify clone, I don't see those products being competitive with ones where engineers armed with the same LLMs are building them.