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Most RAG systems fail at retrieval, not at the model. Twelve lessons on chunking for the question, hybrid search for exact strings, re-ranking, making it refuse, and measuring retrieval separately from generation.
Every model comparison you read was written against someone else's task. Twelve lessons on building the evaluation that produces your answer, pricing the choice properly, and making it reversible before the model changes underneath you.
An AI agent is non-deterministic, so 'it worked when I tried it' is not testing. Use n8n's built-in Evaluation feature, a golden test set, and the right scoring metrics to test n8n AI agents and prove a change made it better, not worse.
