The LLM is basically a runtime that needs optimized input bc the output is compute bottlenecked. Input quality scales with domain knowledge, specificity and therefore human time input. You can absolutely navigate an LLMs attention piecemeal around a spec until you build an optimized input.
https://www.dbreunig.com/2025/06/10/let-the-model-write-the-... is an example.
You can see the hands on results in this hugging face branch I was messing around in:
here is where I tell the LLM to generate prompts for me based on research so far
https://github.com/AlexChesser/transformers/blob/personal/vi...
here is the prompts that produced:
https://github.com/AlexChesser/transformers/tree/personal/vi...
and here is the result of those prompts:
https://github.com/AlexChesser/transformers/tree/personal/vi.... (also look at the diagram folders etc..)