Last month, an Ask HN thread titled 'Anyone else disillusioned with AI experts in their team?' surfaced a pattern that's been quietly damaging production systems: engineering teams are shipping LLM applications without any systematic way to measure whether they actually work. The original poster described an internal AI workshop where senior developers couldn't articulate how language models function or what constitutes acceptable output quality. The thread exploded with similar stories—teams deploying RAG systems, code assistants, and customer-facing chatbots without evaluation frameworks, only to discover in production that hallucination rates, tonality mismatches, or logical errors were breaking user trust. One commenter noted his company had shipped three LLM features to production before anyone asked: 'How do we know this is correct?' The silence was damaging.