Large Language Models, as impressive as they are, can still make mistakes. The impact of these mistakes often depends on the nature of the input prompt, the criticality of the scenario, and the action that the LLM output drives. In a consumer-grade use case, slips may be tolerable, but in an enterprise setting, the error […]