How to build production-grade LLM evaluation pipelines

A developer shares how their team replaced manual 'vibe checks' with automated evaluation, catching 92% of hallucinations before deployment. The pipeline uses domain-specific judges, CI/CD integration, and golden datasets to detect regressions. It blocks merges that degrade quality, preventing incidents like the one that exposed 500+ users to hallucinated responses.