When you get some abstraction working you concretize it in something deterministic, or sort of “cache” that knowledge bit (aka write me a function, class, library, whatever). In the future, the nondeterministic path now has a deterministic piece to lean on as it explores the problem space. Rinse, repeat, eventually you have a mostly deterministic system now. Leave flexibility in space where you need that nondeterminism.
When you get some abstraction working you concretize it in something deterministic, or sort of “cache” that knowledge bit (aka write me a function, class, library, whatever). In the future, the nondeterministic path now has a deterministic piece to lean on as it explores the problem space. Rinse, repeat, eventually you have a mostly deterministic system now. Leave flexibility in space where you need that nondeterminism.
Rather than telling the LLM "loop through these files", tell it "write a script to loop through these files", then hard-code that script somewhere.
The models will eventually be able to know that they need to do that to get the thing done from natural language
a guess but i think they mean take the orchestration prompt and prompt yet another llm to turn that prompt into code..?