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

Short summary

A practical guide to building automated LLM evaluation pipelines, motivated by a production incident where a RAG support assistant hallucinated policies to 500+ users. The article covers a judge ensemble architecture (faithfulness, instruction following, JSON schema, safety, domain expert) with code for an evaluation harness, threshold-based pass/fail logic, and CI/CD integration to block merges that degrade quality. Reports catching 92% of hallucinations pre-deployment.

• •Production incident with 500+ users seeing hallucinated responses motivated shift from manual to automated evaluation
• •Judge ensemble covers faithfulness, instruction following, JSON schema validation, safety, and domain-specific accuracy with configurable thresholds
• •Evaluation harness integrates into CI/CD to block quality-degrading merges and detect regressions from prompt changes

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