There is a partial solution to this problem: use formal methods such as symbolic logic and theorem proving to check the LLM output for correctness. We are launching a semantic validator for LLM-generated SQL code at sql.ai even now. (It checks for things like missing joins.) And others are using logic and math to create LLMs that don't hallucinate or have safety nets for hallucination, such as Symbolica. It is only when the LLM output doesn't have a correct answer that the technical issues become complicated.