In and Out of Model Responses Explained — Whiteboard Friday
Summary
Explain the difference between in-model responses (answers drawn from a model's training data) and out-of-model responses (answers grounded with fresh web retrieval) and why that distinction matters for SEO. Note that influencing in-model outputs requires changing training data and is slow, while out-of-model outputs can be influenced quickly via indexed web pages. Recommend three practical tactics to shape out-of-model answers: barnacle SEO (owning authoritative third-party presences), digital PR to influence external authoritative sites, and keeping your own site updated for rapid indexing. Advise SEOs to classify queries by likely response type when tracking AI visibility and prioritizing efforts.
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