I’m curious to hear from the HN community how you tamed this probabilistic non-deterministic genius generate a deterministic and repeatable result 100% percent of the time.
Anyone telling you they have tamed LLMs into producing 100% deterministic answers has either scoped the problem space so narrowly as to border on meaningless (e.g. "Is earth flat?" with a structured output schema of a single JSON boolean value), hasn't done robust statistical validation to actually confirm truly deterministic outputs, or both.
LLMs are fundamentally non-deterministic. Trying to use them to solve deterministic problem spaces is selecting the wrong tool for the job, and expecting them to be 100% reliable is the wrong mindset for working with them.
Right, but do you care about how the sausage was made, or just how it looks and tastes?
You can get Claude Code to fulfill some interface contract with almost certainty. Exactly how it does that will vary between runs.
So to me the more interesting question is, what exactly is it you care about inside the sausage, and how do you verify that it's there in the right amounts?