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How do you evaluate the retrieval component of a RAG system (separately from generation)?

RAG failures are usually retrieval failures, yet most teams only measure the final answer. The signal is scoring retrieval on its own (recall@k, precision@k, MRR/nDCG) to isolate exactly where the system breaks.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

RAG failures are usually retrieval failures, yet most teams only measure the final answer. The signal is scoring retrieval on its own (recall@k, precision@k, MRR/nDCG) to isolate exactly where the system breaks.

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These lessons teach the material this question tests, in order and from the beginning.

Applied AI Engineering·EvaluationSign in14mBuilding a set of examples worth trustingYour evaluation is only as good as the examples in it, and most sets are quietly useless because of how they were assembled. This lesson covers where to get examples, what proportion should be awkward, and the maintenance nobody plans for.
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