Sure, concrete example. We do conversational AI for banks, and spend a lot of time on the compliance side. Biggest thing is we don't want the LLM to ever give back an answer that could violate something like ECOA.

So every message that gets generated by the first LLM is then passed to a second series of LLM requests + a distilled version of the legislation. ex: "Does this message imply likelihood of credit approval (True/False)". Then we can score the original LLM response based on that rubric.

All of the compliance checks are very standardized, and have very little reasoning requirements, since they can mostly be distilled into a series of ~20 booleans.