Building an LLM Evaluation Framework That Actually Works

Stop Eyeballing Your RAG Outputs. Start Measuring Quality. I shipped a RAG system. It felt fine. Then users started reporting wrong product recommendations, invented prices, and confidently wrong answers to questions the documents couldn't support. I had no numbers. No regression detection. No systematic way to improve. I was flying blind. This is how I built an evaluation stack that catches failures before users do. What "Evaluation" Actually Means Most teams jump straight to asking humans "does this seem good?" That's too slow and too expensive to run on every change. There's a whole layer of automated evaluation that should come first. Level Question Cadence Unit Does this component work correctly? Every commit Integration Does the full pipeline work end-to-end? Every PR Human Do users actually find this helpful? Weekly A/B Is the new version measurably better? Monthly The lower layers are fast and cheap. Build them first, then let human evaluation handle the things automation genui