How models retrieve & rank
Grounding
Grounding is the practice of anchoring an AI model's answer in specific, verifiable source material rather than its internal memory alone. A grounded answer can be traced back to the documents that informed it, which is what makes citations possible and reduces hallucination.
Why it matters for AEO
Grounding is why crawlable, trustworthy content matters: it is the source pool a model anchors to. Specific, well-attributed claims are easier to ground and therefore easier to cite. Content that cannot be grounded is content the engine cannot safely use in its answer. Publishing specific, verifiable, well-sourced claims gives engines more to anchor to, which is the practical goal of answer-first content.
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