How engines work
Reranking
Reranking is a second pass that reorders retrieved documents by how well they actually answer the question, before the model writes from them. It decides which of the candidates becomes a citation.
In more detail
Pages that answer the question directly and early tend to survive reranking, which is a practical argument for putting the answer at the top of a page rather than after the context.
Guides that cover this
Related terms
Vector search
Vector search finds documents by comparing embeddings rather than matching keywords, retrieving passages whose meaning is close to the question. It is the retrieval method behind most answer engines.
Retrieval-augmented generation
Retrieval-augmented generation is when a model searches for relevant documents and writes its answer from what it finds, rather than from training alone. It is why a page published this week can appear in an answer today.
Answer-first content
Answer-first content states the answer in the opening lines, before context or background. It suits AI answers because engines lift self-contained passages, and a passage that answers the question outright is the easiest to take.
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