The original title is "Building Production-Grade LLM Evaluation Pipelines: From Vibes to Metrics"

Short summary

A practical guide to building production-grade LLM evaluation pipelines, motivated by a real incident where a RAG support assistant hallucinated policies to 500+ users. The article covers domain-specific judge ensembles (faithfulness, instruction following, JSON schema, safety, domain expert), golden dataset management, and CI/CD integration to block quality-degrading merges. Code examples show a typed evaluation harness with configurable judges and thresholds.

• •Replaced manual 'looks good' testing with automated judge ensembles catching 92% of hallucinations
• •Five judge types: faithfulness, instruction following, JSON schema, safety, domain expert
• •CI/CD integration blocks merges that degrade quality; golden datasets are versioned and stratified

Generated with AI, which can make mistakes.