A plain-English glossary of the 45 terms that define how blogs get found, quoted, and cited in the AI search era. Each entry leads with a one-sentence definition you can quote, followed by why it matters for your blog. Use the search box to jump to any term.
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AI Overviews
AI Overviews are the AI-generated answer boxes Google places at the top of many search results, summarizing information and citing a handful of source pages. Being cited in an AI Overview can lift clicks even when your blue link sits lower, which is why structuring content for extraction now matters as much as ranking.
AI Mode
AI Mode is Google’s dedicated conversational search experience, where a full chat-style assistant answers queries and follow-ups instead of returning a classic list of links. It leans heavily on the same source-selection signals as AI Overviews, so optimizing for one tends to help the other.
Answer engine
An answer engine is any system that responds to a query with a direct synthesized answer rather than a list of links, including AI Overviews, ChatGPT, Perplexity, and voice assistants. Answer engines are the audience GEO and AEO are written for.
Generative engine
A generative engine is an answer engine powered by a large language model that composes original text on the fly, such as ChatGPT, Gemini, Claude, or Perplexity. The term is the root of GEO, generative engine optimization.
Perplexity
Perplexity is an AI answer engine that responds to questions with a written summary plus numbered citations to the web pages it drew from. Its visible, link-rich citations make it one of the clearest places to measure whether your content is being used.
ChatGPT Search
ChatGPT Search is the web-browsing mode of ChatGPT that retrieves live pages and cites them inside its answers, rather than relying only on training data. It has become a major referral source as hundreds of millions of users ask it research questions.
SGE (Search Generative Experience)
SGE was Google’s original 2023 to 2024 name for its generative search answers, later rebranded and rolled out as AI Overviews. You will still see SGE in older guides, but the current term is AI Overviews.
SEO
Search engine optimization is the practice of structuring a site and its content to rank highly in traditional search results. SEO remains the foundation of AI visibility, because most AI engines still pull their sources from the conventional top-ranking pages.
Generative Engine Optimization GEO
GEO is the practice of structuring content so AI answer engines cite, quote, or recommend you inside the answers they generate, rather than just ranking a link. Where SEO wins the click, GEO wins a place in the synthesized answer itself.
Answer Engine Optimization AEO
AEO is the practice of optimizing content to be surfaced by answer engines, including AI Overviews, AI chatbots, and voice assistants. In practice AEO and GEO are used interchangeably; there is no settled distinction between them as of 2026.
LLM Optimization LLMO
LLMO, large language model optimization, is another name for optimizing content to be retrieved and cited by language-model-based search. It overlaps almost entirely with GEO and AEO.
AI SEO AIO
AI SEO, sometimes called AIO or artificial intelligence optimization, is the umbrella term for adapting classic SEO so a page performs in both traditional and AI-driven search. It signals that the two disciplines are converging rather than competing.
Large Language Model LLM
A large language model is an AI system trained on vast amounts of text to predict and generate human-like language, and it is the engine behind ChatGPT, Gemini, Claude, and similar tools. Understanding that LLMs predict likely text explains why clear, well-structured writing is easier for them to reuse.
Retrieval-Augmented Generation RAG
RAG is the technique where an AI engine first retrieves relevant documents from the live web or a database, then generates its answer grounded in that retrieved text. Almost every cited AI answer uses RAG, which is exactly why on-page structure decides whether your page is the document that gets retrieved.
Grounding
Grounding is the practice of tying an AI model’s answer to specific retrieved sources so its claims can be traced and cited, reducing invented information. A grounded answer is one that links back to pages like yours.
Embedding
An embedding is a numerical representation of a piece of text that captures its meaning, letting AI systems measure how closely two passages relate. Embeddings are how an engine decides your paragraph is relevant to a query even when the exact words differ.
Vector search
Vector search retrieves content by comparing the embeddings, or meaning, of a query and candidate passages, rather than matching exact keywords. It rewards content that covers a topic clearly and completely over content stuffed with repeated phrases.
Semantic search
Semantic search interprets the intent and meaning behind a query instead of matching literal keywords, returning results that answer what the user actually meant. Writing for the question behind the keyword is the core of optimizing for it.
Hallucination
A hallucination is when an AI model states something false or invented as if it were fact, often because it lacked a reliable grounded source. Clear, well-sourced, schema-marked pages reduce the chance an engine guesses wrong about your topic or brand.
Knowledge graph
A knowledge graph is a structured database of entities, such as people, brands, and places, and the relationships between them, that search and AI systems use to understand the world. Getting your brand recognized as a distinct entity helps AI engines attribute information to you correctly.
Entity
An entity is any distinct, identifiable thing, such as a person, company, product, or concept, that search systems track in their knowledge graph. Consistent naming and clear about and author pages strengthen your blog’s entity, which improves how confidently AI engines cite it.
Citation
A citation is when an AI answer references or links to your page as a source for part of its response. Citations are the core currency of GEO, the AI-era equivalent of a top ranking.
Citation rate
Citation rate is the share of relevant AI answers in your topic that cite your site, measured across a set of tracked queries. It is the clearest single metric for how visible your blog is inside AI search.
AI visibility (share of voice)
AI visibility, or share of voice, measures how often your brand appears or is cited in AI answers compared with competitors for the same set of prompts. It reframes the old ranking report around answers instead of links.
Brand mention
A brand mention is any reference to your name in an AI answer, whether or not it includes a clickable link. Unlinked mentions still build the entity associations that make future citations more likely.
Query fan-out
Query fan-out is the process where an AI engine breaks one question into several related sub-queries, searches each, and synthesizes the results into a single answer. It means a page can be pulled in for sub-questions you never explicitly targeted, rewarding broad, thorough coverage.
Zero-click search
A zero-click search is one where the user gets their answer directly on the results page or in an AI reply and never visits a website. The rise of zero-click results is the central reason blogs now optimize to be cited, not just clicked.
Schema markup
Schema markup is structured code added to a page that labels its content, such as an FAQ, article, or author, in a format machines can read directly. It is one of the largest single levers for AI citation because it hands engines a clean, unambiguous copy of your content.
Structured data
Structured data is any information on a page organized in a defined, machine-readable format, most commonly implemented through schema markup. The more of your key facts are structured, the easier they are for an engine to extract and trust.
JSON-LD
JSON-LD is the recommended code format for adding schema markup, placed in a script tag so it describes the page without changing how it looks. It is the practical way most blogs implement structured data for AI and search.
FAQ schema
FAQ schema is structured data that marks up a list of questions and answers so engines can lift them directly into AI answers and rich results. It pairs naturally with question-style subheads to create quotable answer pairs.
llms.txt
llms.txt is a proposed plain-text file in a site’s root that offers AI crawlers a curated, Markdown map of its most important content. As of 2026 adoption is minimal and no major AI crawler has confirmed using it, so treat it as low-cost experiment rather than a proven tactic.
robots.txt
robots.txt is a long-standing file in a site’s root that tells crawlers, including AI bots, which areas of the site they may or may not access. It is where you allow or block specific AI crawlers like GPTBot or Google-Extended.
GPTBot
GPTBot is OpenAI’s web crawler, which gathers content used to train models and to power ChatGPT’s browsing and citations. Allowing it in robots.txt is what lets ChatGPT discover and cite your pages.
Google-Extended
Google-Extended is the crawler control that decides whether your content can be used for Google’s generative AI features, such as Gemini and AI Overviews training. Blocking it can quietly remove you from AI answers, so most publishers leave it allowed.
AI crawlers (ClaudeBot, PerplexityBot)
AI crawlers are the named bots that AI companies use to fetch web pages, including ClaudeBot from Anthropic and PerplexityBot from Perplexity. Your server logs and robots.txt are where you confirm which ones are visiting and allowed.
Crawlability
Crawlability is how easily bots can reach and read your pages, governed by site structure, internal links, load speed, and robots rules. If an AI crawler cannot fetch a page, it can never cite it, making crawlability the prerequisite for everything else.
Answer-first structure
Answer-first structure means leading each section with a direct, concise answer before any background, so the key takeaway sits where engines and readers look first. It is the single easiest writing change to make a page more quotable by AI.
Chunking
Chunking is breaking content into self-contained passages that each make sense on their own, so an engine can lift one without surrounding context. Well-chunked posts give AI more clean, extractable units to cite.
Passage
A passage is a short, coherent block of text, often a paragraph, that an AI engine can retrieve and quote independently of the rest of the page. Optimizing at the passage level, not just the page level, is central to GEO.
E-E-A-T
E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness, the quality signals Google and AI systems use to judge whether a source is reliable. Named, credentialed authors and first-hand testing raise the trust an engine assigns your pages.
Topical authority
Topical authority is the depth and breadth of trustworthy coverage a site has on a subject, built through interlinked content that covers a topic comprehensively. AI engines disproportionately cite sites they recognize as authorities on the specific topic of the query.
Content freshness
Content freshness is how recently a page was published or meaningfully updated, shown by visible dates and current information. Recently updated content is cited far more often, making freshness a strong tiebreaker in AI answers.
Quotability
Quotability is how easily a single sentence or stat from your page can be lifted into an AI answer without editing or extra context. Specific numbers, clear definitions, and self-contained sentences all raise quotability.
Prompt
A prompt is the question or instruction a user types into an AI engine, the AI-era equivalent of a search query. Studying the prompts your audience actually asks is the new keyword research.
Put these terms to work
See how your own posts score on the signals these terms describe with our AI Citation Grader, then read the playbook on optimizing for AI Overviews.
Definitions reflect current usage as of 2026, informed by Wikipedia, Search Engine Land, and Semrush. Terminology in this field is evolving and terms are often used interchangeably.