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

Short summary

A detailed guide to building production-grade LLM evaluation pipelines, motivated by a real incident where a RAG assistant hallucinated responses to 500+ users. It covers judge ensembles (faithfulness, instruction following, JSON schema, safety, domain expert), golden dataset management, and CI/CD integration with code examples. The pipeline reportedly catches 92% of hallucinations pre-deployment.

• •Automated judge ensemble catches 92% of hallucinations before deployment
• •Covers faithfulness, instruction following, JSON schema, safety, and domain-specific judges
• •Includes Python code for evaluation harness, LLM judges, and CI/CD integration

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