01
AEO
Answer Engine Optimization
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 synthesized answers.
02
GEO
Generative Engine Optimization
Optimizing a source so that it survives the synthesis step when generative models compose one answer from many inputs. A source can be cited yet lose its wording during synthesis; a source optimized for GEO is quoted verbatim.
Forthcoming
Forthcoming edition
03
LLMO
Large Language Model Optimization
Preparing content specifically for ingestion, retrieval and citation by large language models, as distinct from classical web search. The broader family under which AEO and GEO are specialised disciplines.
Forthcoming
Forthcoming edition
04
Agentic
SEO
SEO for autonomous agents
SEO practice oriented toward autonomous agents rather than human browsers — structuring content, endpoints and manifests so autonomous agents can read, compare and take action on behalf of users.
Forthcoming
Forthcoming edition
05
Entity
Optimization
Single identity across the open web
The practice of making a business, concept or institution identifiable as a single entity across the open web via name consistency, sameAs links, Schema.org markup and Knowledge Graph registration.
Forthcoming
Forthcoming edition
06
Citation
Velocity
North-star KPI of AEO
The rate at which a source accumulates verifiable mentions across answer engines. Measured by the publisher across a canonical query-surface matrix. The metric that replaces ranking position.
Forthcoming
Forthcoming edition
07
llms.txt
Root-level model-readable manifest
A root-level markdown manifest that tells language models which pages to read, in what order and for what purpose. First articulated by Jeremy Howard of Answer.AI as a proposed convention for AI-readable site guidance.
Forthcoming
Forthcoming edition
08
Knowledge
Graph
Structured entity relationships
A structured database of real-world entities (people, organizations, places, concepts) and the relations between them. Search engines and language models reason over knowledge graphs when composing answers.
Forthcoming
Forthcoming edition
09
Generative
Search
Answers composed from sources
Search powered by generative models that returns a synthesized answer instead of a list of links. The mode in which answer engines operate — answers composed from retrieved sources, not ranked results.
Forthcoming
Forthcoming edition
10
RAG
Pipeline
Retrieval-Augmented Generation
A pattern where a model retrieves relevant documents at query time and then composes an answer grounded in those documents — the mechanism by which modern answer engines cite sources.
Forthcoming
Forthcoming edition
11
Answer
Box
Synthesized answer UI element
The UI element that displays a synthesized answer above traditional search results. Featured snippets, People Also Ask and AI Overviews are variants. Appearing in the answer box requires structured, extractable content.
Forthcoming
Forthcoming edition
12
Entity
Coherence
Core citation precondition
The degree to which an entity is represented consistently across all public sources — name, address, Schema.org markup, social profiles and knowledge graphs. A precondition for being cited as one real entity.
Forthcoming
Forthcoming edition