Equation 4 · Ten Failure Modes That Define Production RAG
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Suppose retrieval succeeds outright — the correct passage is in the top- k , correctly chunked, sitting in the prompt. The system can still fail for a reason that has nothing to do with what was retrieved. Liu and colleagues varied the position of the one relevant document inside a long input and found performance highest when it sat at the very beginning or the very end, and markedly worse when it had to be used from the middle, a pattern that held even in models built specifically for long contexts [ 4 ] . This is a usage failure layered on top of a successful retrieval: the evidence is present in the context window, and the generator simply does not draw on it as reliably from the middle…
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Suppose retrieval succeeds outright — the correct passage is in the top- k , correctly chunked, sitting in the prompt. The system can still fail for a reason that has nothing to do with what was retrieved. Liu and colleagues varied the position of the one relevant document inside a long input and found performance highest when it sat at the very beginning or the very end, and markedly worse when it had to be used from the middle, a pattern that held even in models built specifically for long contexts [ 4 ] . This is a usage failure layered on top of a successful retrieval: the evidence is present in the context window, and the generator simply does not draw on it as reliably from the middle of a long list as from its edges. A retrieval pipeline that ranks strictly by descending relevance places its second- and third-best passages exactly where they are least likely to be used, which is the opposite of what the ranking was meant to accomplish.
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