How do you verify that an answer's citations actually support its claims (grounding verification)?

An LLM can cite a source that does not say what the answer claims. The signal is checking claim-by-claim entailment against the cited text, not just that a citation marker exists, and knowing what to do when grounding fails.

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

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Applied AI Engineering·RetrievalFree14mHow a working retrieval system goes wrongThe failures that arrive after launch, once real documents and real questions replace your test set. Six of them, each with the signal that identifies it, because the wrong diagnosis here wastes weeks.

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Next in this trackHow do you measure faithfulness (hallucination rate) in a RAG system, and what makes it hard to score?Next in this trackContext precision versus context recall: which do you optimize, and how do they trade off in RAG?Next in this trackHow do you tune the fusion weights between lexical and vector retrieval, RRF k versus a learned alpha?

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