Building Production-Grade LLM Evaluation Pipelines: From Vibes to Metrics

A team replaced 'looks good to me' with automated evaluation, catching 92% of hallucinations before deployment. They realized the need for domain-specific judges, speed, regression detection, CI/CD integration, and golden dataset management. To achieve this, they created a pipeline with test cases, LLM under test, judge ensemble, and metrics & regression detection. This approach ensures production-grade LLM evaluation and prevents hallucinations.