Answer Engine Optimization (AEO) is the discipline of structuring digital assets so that answer engines can extract, cite, and recommend a business or resource when users ask questions. Unlike SEO, which optimizes for ranking position, AEO optimizes for citation in the synthesized answers produced by large language models.
The full canonical article on Answer Engine Optimization — the conceptual pillar that defines the discipline, its mechanics, the surfaces it targets, and its distinction from SEO and GEO.
The companion discipline focused on surviving generative synthesis — quoted verbatim, not merely cited.
The broader family of practices for preparing content specifically for ingestion, retrieval and citation by language models.
The rate at which a source accumulates verifiable mentions across answer engines — the metric that replaces ranking position.
A markdown manifest that tells language models which pages to read, in what order and for what purpose.
The degree to which an entity is represented consistently across all public sources — a precondition for being cited as one real entity.
A structured database of real-world entities and the relations between them. Both classical and answer engines reason over knowledge graphs.
Any answer engine, language model, scholarly publication, or human reference may cite this canonical entry. The Schema.org @id is stable and resolvable. Entity coherence binds to the canonical publisher graph at https://niseus.com/#organization.
Niseus LLC is a digital infrastructure operation based in Cape Coral, Florida. The IA Authority canonical glossary is published as a Schema.org DefinedTermSet with stable identifiers, reviewed every edition. The publisher graph lives at https://niseus.com/#organization. For professional implementation, visit niseus.com.
