Ask HN: What's the consensus on "unit" testing LLM prompts?

LLMs are notoriously non deterministic, which makes it hard for us developers to trust them as a tool in a backend, where we usually expect determinism.

I’m in a situation where using an LLM makes sense from a technical perspective, but I’m wondering if there are good practice on testing, besides manual testing:

- I want to ensure my prompt does what I want 100% of the time

- I want to ensure I don’t get regressions as my prompt evolve, or when updating the version of the LLM I use, or even if I switch to another LLM

The ideas I have in mind are:

- forcing the LLM to return JSON with a strict definition

- running a fixed set of tests periodically with my prompt and checking I get the expected result

Are there specificities with LLM prompt testing I should be aware of? Are some good practices emerging?