9.1Two Evaluation Problems, One Skill Set

By mid-2026, QA job postings routinely list LLM eval design as a core competency, alongside RAG metrics and frameworks like Ragas, TruLens, and OpenAI Evals. This is not a fad -- it reflects two evaluation problems that now land on the QA engineer's desk:

1. Evaluating the tests AI wrote for you. If AI generates half your suite, "how good is the suite?" needs a quantitative answer, not a gut feeling.
2. Evaluating the AI inside your product. When the feature under test is itself an LLM (a chatbot, a summarizer, a RAG-backed search), classical pass/fail assertions stop working -- and someone has to design the evaluation harness.

Both problems share the same discipline: define quality metrics, build a measurement harness, set thresholds, and track trends. That is test engineering. You already do this -- you are just pointing it at new targets.