A quick reference for the terms that come up across these guides and across the AI search world. Definitions are kept short and plain. Where a term is used loosely in the industry, this says so, because pretending these are all settled would be its own kind of jargon.
The big three (and their cousins)
SEO (Search Engine Optimization) is the long-standing practice of earning visibility in a ranked list of search results, the model where users click through to a site.
AEO (Answer Engine Optimization) is optimizing your content so AI answer engines understand, trust, and cite you inside their written answers. It is a practitioner term with no single canonical definition. See what is AEO.
GEO (Generative Engine Optimization) is the same idea, focused on generative AI responses. It is the one term with an academic origin, coined in a 2023 research paper. In practice, AEO and GEO are used almost interchangeably; do not over-invest in the distinction.
Answer engine is a tool that returns a direct, synthesized answer with citations instead of a list of links. Perplexity describes itself as one; ChatGPT search and Google’s AI surfaces behave like ones.
AI Overviews / AI Mode (Google) are Google’s AI search surfaces. AI Overviews are the AI summaries shown above traditional results (launched in the US in May 2024). AI Mode is a more conversational version for complex, multi-part questions.
How the engines work
LLM (large language model) is the kind of AI model, trained on huge amounts of text, that understands and generates language. It is what powers every answer engine.
RAG (retrieval-augmented generation) is the retrieve-then-answer pattern: the system fetches relevant pages first, then writes an answer grounded in them, usually with citations. Named in a 2020 paper. See how AI engines work.
Grounding means tying an AI’s answer to retrieved, verifiable sources rather than its memory alone, to keep it accurate and citable.
Hallucination is when an AI states something false but confident. Grounding and citations are the main ways engines reduce it (and let you check it).
Token / tokenisation : a token is the small chunk of text a model processes (roughly four characters, or about three-quarters of a word). Tokenisation is splitting text into those units.
Context window is the maximum amount of text, measured in tokens, a model can consider at once. It is shared across the question, the retrieved pages, and the answer, which is why concise, well-structured content helps.
Embeddings / semantic search : an embedding turns text into a list of numbers (a vector) that captures its meaning, so systems can match content by meaning rather than exact keywords.
Query fan-out is Google’s term for breaking one question into multiple related sub-queries, running them at once, and combining the results. The high-level mechanism is Google’s; the finer detail is partly industry interpretation.
Understanding and trust
Knowledge graph is a structured map of real-world entities (people, places, organizations) and how they relate, the “things, not strings” idea Google introduced in 2012.
Entity is a distinct, recognized “thing” an engine can identify and connect to other things, the unit of meaning behind your brand.
Structured data / schema.org is machine-readable markup that labels what your content means. Schema.org is the shared vocabulary; JSON-LD is the recommended format. See JSON-LD structured data.
E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trust, the criteria Google’s human quality raters use to judge content. Important: it is not a direct ranking factor and there is no “E-E-A-T score.” See authority and proof.
sameAs is the structured-data property that links your site to your authoritative profiles (LinkedIn, Crunchbase, Wikidata) so engines can confirm your identity.
Crawling and discovery
Crawler / user agent : a crawler is automated software that fetches web pages; its user agent is the name it identifies itself with (like GPTBot or OAI-SearchBot), which you can allow or block. See AI crawler access.
llms.txt is a proposed Markdown file at your site root that gives AI models a curated map of your key pages. It is an emerging convention, not an adopted standard, and no major AI engine has confirmed it uses one. See llms.txt.
Visibility and measurement
Citation vs mention : a mention names your brand in an answer; a citation links to or attributes your page as a source. Tools count them differently.
Share of voice is how often you appear in AI answers relative to competitors, for a defined set of prompts. The concept is borrowed from traditional marketing; each tool computes it its own way.
Zero-click search is a search answered right on the results page, with no click through to a website. AI answers are accelerating it. See measuring your AI visibility.