Holding LLMs to the standards of human contextual understanding without communicating sufficient context can be dispensed with, as fantasy.
Using LLMs you quickly learn how much can be inferred from existing, which is dynamic and particular to each model today. There will always be a gap in how much instruction is needed due to mismatches of existing versus intent. Current state, you don't need much to get a lot out that can be verified prior to merge.
LLMs + Harnesses are incredibly effective, as evidenced by the literal millions of people who are paying quite a lot to use them, who speak glowingly of them and would 'never go back'.
Whatever 'shape they take' - they are obviously useful - ergo - 'you're doing something wrong' if you can't make use of them for most tasks.
Mileage varies, there are downsides, but it's the same with anything.