What Production-Grade RAG Evaluation Should Look Like

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Learn how to evaluate agentic RAG systems using RAGAS, LangSmith, Langfuse, critic scores, retrieval behavior, latency, and cost.
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This article argues that evaluating agentic RAG systems requires far more than a single faithfulness score. It explores a production-focused evaluation stack built around RAGAS component metrics, node-level observability with LangSmith and Langfuse, critic scoring, retrieval-round analysis, latency and cost monitoring, and carefully curated evaluation datasets. The central thesis is that modern RAG systems fail in many ways that end-to-end metrics alone cannot detect.