Answer engine
An answer engine is an AI system that responds to a user's question with a synthesized answer instead of a list of links: ChatGPT, Gemini, Claude, Grok, Perplexity, Copilot and Google's AI Overviews are the main examples.
Glossary
The AEO vocabulary, defined so it can be cited.
Every term has a short, quotable definition and a longer explanation with examples and sources. New terms are added continuously as the discipline evolves.
Core concepts
Answer Engine Optimization (AEO)
Answer Engine Optimization (AEO) is the practice of improving how AI systems such as ChatGPT, Gemini, Claude, Grok and Perplexity understand, cite and recommend a company when users ask questions, by improving the evidence those systems retrieve and trust.
Generative Engine Optimization (GEO)
Generative Engine Optimization (GEO) is the discipline of improving how a brand is represented inside answers produced by generative search engines and AI assistants, focusing on the sources, claims and entities those systems synthesize.
Knowledge graph
A knowledge graph is a structured representation of entities, facts and relationships, often with sources or context, that helps AI systems reason about what things are and how they connect.
LLM Optimization (LLMO)
LLM Optimization (LLMO) is the work of improving how large language models represent a brand: the facts they associate with it, the contexts where they mention it and the sources they cite about it, both from trained knowledge and from retrieval.
Measurement and metrics
Citation rate
Citation rate is the percentage of sampled AI answers that cite a brand's own domain as a source. It measures whether the brand's website has become evidence that answer engines retrieve and trust, beyond simply being mentioned.
Mention rate
Mention rate is the percentage of sampled AI answers in which a brand is named at all, regardless of sentiment or position. It is the baseline visibility metric for answer engines, computed from repeated runs of a prompt portfolio.
Prompt portfolio
A prompt portfolio is a fixed, structured set of questions that real buyers ask AI engines, run repeatedly across engines and over time to measure a brand's visibility statistically instead of from isolated screenshots.
Recommendation rate
Recommendation rate is the percentage of sampled AI answers in which the engine actively advises choosing or shortlisting a brand, not merely naming it. It is the metric closest to commercial impact in AI visibility measurement.
Strategy and operations
Entity disambiguation
Entity disambiguation is the work of helping search and AI systems identify exactly which company, person, product or organization a name refers to.
Source graph
A source graph maps which sources support which claims about an entity, so AEO teams can see whether important facts are primary, corroborated, conflicting or weak.
White-label AEO
White-label AEO is a partnership model where a specialized provider performs Answer Engine Optimization work — audits, optimization and reporting — that a client-facing agency sells and presents under its own brand, keeping the client relationship entirely with the agency.
Engines and platforms
Google AI Overviews
AI Overviews are Google Search's AI-generated summaries shown above classic results, composed from multiple retrieved sources with links. Together with AI Mode, they are Google's main answer-engine surface and a key target for AEO work.
Technical foundations
llms.txt
llms.txt is a proposed convention: a Markdown file at a website's root that gives large language models a curated, machine-friendly summary of the site, its key pages and its canonical facts, complementing robots.txt and sitemaps.
Provenance
Provenance is the trace of where a fact came from: who published it, when, in which document or URL, and with what authority over the claim.