Because LLM's are causal autoregressive. The output is non-deterministic and is based on a sampling algorithm. It's why things like 'self-consistency' is a thin

Because LLM's are causal autoregressive. The output is non-deterministic and is based on a sampling algorithm. It's why things like 'self-consistency' is a thing. It's possible LLM's are better than or equal to best prompt engineers in producing the best "trace" or "prompt" that will lead to the desired sampling "trajectories".