AI answers depend on retrieval. If systems can’t reliably extract your facts, definitions, comparisons, and proof, you will not appear—even if your pages are “good.” This session shows how to make content retrievable: clean entity statements, chunking, intent-aligned headings, answer blocks, evidence patterns, and freshness signals. You’ll also learn a lightweight evaluation method—prompt sets and change control—so teams can iterate with discipline instead of guessing. This session will help ensure attendees will walk away with practical information that can be implemented right away including: A retrieval-readiness checklist for content and templates; Page patterns that increase reuse in AI answers (definitions, decision criteria, comparisons, proof blocks); A repeatable test-and-learn loop (prompt library,logging, versioning, evaluation).