AI SEO course glossary

This AI SEO course glossary defines 23 terms used in AI SEO courses and in the documentation of the search and AI systems they teach. Where a term has an origin or an official definition, the entry cites it; where courses use a term loosely, the entry says so. For the subject as a whole, see AI SEO course.

AI SEO · Generative engine · Generative engine optimization (GEO) · Answer engine optimization (AEO) · LLM optimization (LLMO) · AI Overviews · Search Generative Experience (SGE) · AI Mode · ChatGPT search · Query fan-out · Retrieval-augmented generation (RAG) · Citation · Brand mention · Share of voice, share of answer · Prompt tracking · Entity · Knowledge Graph · E-E-A-T · AI crawler · llms.txt · Structured data · Parasite SEO · Gray hat, black hat

What do AI SEO course terms mean?

The 23 entries below define the vocabulary of AI SEO courses, from GEO, AEO and LLMO to query fan-out, retrieval-augmented generation, AI Overviews, E-E-A-T and llms.txt. Each cites the origin or the official definition of the term where one exists, and notes where courses use a term loosely.^[1]

AI SEO

Search engine optimization aimed at answers generated by AI systems as well as, or instead of, ranked lists of links. Used loosely: it can also mean using AI tools to do conventional SEO work, and course titles use it in both senses.

Generative engine

A search or answer system that writes a response with a large language model from sources it retrieves, rather than returning only a list of links. The term was used in the paper that formalized GEO.^[1]

Generative engine optimization (GEO)

Improving the visibility of content in the responses of generative engines. The term was formalized in a paper first posted to arXiv on 16 November 2023, whose authors reported gains of up to 40% in visibility with effects that varied by domain.^[1][1]

Answer engine optimization (AEO)

Optimizing content so that systems which answer questions directly, including AI assistants and search features, extract and cite it. HubSpot uses the term for the certifications that replaced its SEO certification in June 2026.^[2]

LLM optimization (LLMO)

Optimizing for how large language models describe, recommend or cite a brand or page. Often used interchangeably with GEO; the Learning AI Search roadmap lists GEO, AEO and LLMO together.^[3]

AI Overviews

Google's generated summaries shown above search results, rolled out to everyone in the United States from 14 May 2024 after testing as the Search Generative Experience.^[4][5]

Search Generative Experience (SGE)

Google's experiment with generative AI in Search, announced on 10 May 2023 and offered through Search Labs; the predecessor of AI Overviews.^[5]

AI Mode

A conversational search mode Google introduced as a Search Labs experiment on 5 March 2025, drawing on the web as well as sources such as the Knowledge Graph and shopping data.^[6][6]

ChatGPT search

OpenAI's search feature, introduced on 31 October 2024, which answers questions with links to web sources.^[7]

Query fan-out

The technique of issuing multiple related searches across subtopics and data sources to build one answer. Google describes AI Mode and AI Overviews as using it, which is why AI SEO courses teach coverage of related questions rather than a single keyword.^[6][8]

Retrieval-augmented generation (RAG)

An architecture that combines a language model with a retrieval step over an external document index, described in a paper first posted in May 2020. Most answer engines work this way, which is why being retrievable is a precondition for being cited.^[9]

Citation

A source shown or linked by an AI answer as support for what it says. Counting citations is one of the measures AI SEO courses teach.^[10]

Brand mention

The naming of a brand, product or person in an AI answer, with or without a link. Courses teach earning mentions on the sites AI systems draw on.^[10]

Share of voice, share of answer

The proportion of answers to a defined set of prompts that cite or mention a brand, compared with competitors. Semrush's course describes measuring AI visibility and share of voice against competitors.^[11]

Prompt tracking

Running a fixed set of prompts through AI systems on a schedule and recording which sources are cited or mentioned; the AI search counterpart of rank tracking.^[11]

Entity

A distinct, identifiable thing, such as a person, organization, product or concept, as represented in a search engine's knowledge base. Entity SEO aims to make a brand's identity and relationships unambiguous to machines.^[6]

Knowledge Graph

Google's knowledge base of entities and their relationships. Google names it among the sources AI Mode draws on.^[6]

E-E-A-T

Experience, expertise, authoritativeness and trustworthiness: the concept in Google's quality rater guidelines to which Experience was added in December 2022. Commonly taught in AI SEO courses as a basis for being chosen as a source.^[12]

AI crawler

A bot that fetches web pages for an AI company, whether for search answers or for model training. OpenAI documents separate user agents, OAI-SearchBot for search and GPTBot for training, which a site can allow or block independently in robots.txt.^[13]

llms.txt

A proposed file at the root of a website that gives language models a concise markdown guide to its content, published by Jeremy Howard on 3 September 2024. It is a proposal, not a standard adopted by search engines.^[14]

Structured data

Machine-readable markup, usually schema.org vocabulary in JSON-LD, that describes a page's content. Several AI SEO courses teach it under technical GEO.^[15]

Parasite SEO

Publishing content on a high-authority third-party site to rank or be cited on the strength of that site's reputation. Some paid communities teach it; AI SEO Rainmakers ships a parasite SEO page builder among its tools.^[16]

Gray hat, black hat

Techniques that fall outside a search engine's published guidelines, to a lesser or greater degree. Charles Floate describes white, gray and black hat as risk settings rather than moral categories.^[17]

Are GEO, AEO and LLMO the same thing?

They overlap but are not identical. GEO refers to visibility in generated responses, AEO to extraction and citation by answer systems, and LLMO to how language models describe a brand. Of the 27 programs in this site's dataset, 15 name GEO and 11 name AEO on their public pages.^[10]

GEO, AEO and LLMO overlap and are often used as synonyms, but the sources that coined or adopted them use them for slightly different things: GEO for visibility in generated responses, AEO for extraction and citation by answer systems, and LLMO for how language models describe a brand.^[1][2] Of the 27 programs in this site's dataset, 15 name GEO and 11 name AEO on their public pages.^[10] The history of AI SEO courses gives the dates at which the underlying systems appeared.