As large language models (LLMs) like GPT-4 become integral to applications ranging from customer support to research and code generation, developers often face a crucial challenge: troubleshooting GPT-4 output quality. Unlike traditional software, GPT-4 doesn’t throw runtime errors — instead it could provide irrelevant output, hallucinated facts, or misunderstood instructions. https://covolunteers.com/members/quincewealth6/activity/1288187/