All terms
The 2026 vocabulary of Generative Engine Optimization, with live per-term citation status across ChatGPT, Perplexity, Claude, and Copilot.
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Schema cluster (3)
foundational
Article Schema
Article schema (schema.org/Article) is the JSON-LD type for marking up news articles, blog posts, and long-form editorial content. It exposes authorship, publication date, and topical-scope metadata that AI engines and search engines can parse, though no major engine has publicly confirmed how heavily these fields weight in citation or ranking decisions.
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BreadcrumbList Schema
BreadcrumbList (schema.org/BreadcrumbList) is the JSON-LD type that declares a page's position in the site hierarchy. It powers Google's breadcrumb rich result in the SERP and can provide machine-readable site-hierarchy context where systems parse structured data.
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JSON-LD
JSON-LD (JavaScript Object Notation for Linked Data) is the W3C-standard syntax for embedding schema.org structured data into web pages. It is the most commonly recommended format for publishing structured data and is widely parsed by AI search engines and Google Search for entity, definition, and FAQ markup.
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Search foundations (4)
foundational
AI Overview
AI Overview is Google's generative search feature that produces AI-synthesized answers at the top of results, citing multiple sources. It is the 2024 rename and rollout of Search Generative Experience (SGE).
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Featured snippets
Featured snippets are the boxed answers Google displays at the top of search results for question-form queries. They are the SERP feature AEO grew up around, increasingly subsumed by AI Overview in 2024–2026.
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Search Generative Experience (SGE)
Search Generative Experience (SGE) was Google's labs-stage AI search feature launched in May 2023, the precursor to AI Overview. Renamed and graduated to AI Overview at Google I/O in May 2024.
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Topic clusters
Topic clusters are a content architecture pattern: one pillar page covers a topic broadly, multiple spoke pages drill into sub-topics, all interlinked. Originated as classic SEO methodology; increasingly adapted for AI-search topic coverage, entity clarity, and retrieval-friendly content organization.
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Umbrella terms (4)
foundational
AI Search Optimization
AI Search Optimization (AIO) is the umbrella term for optimizing content visibility across all AI-driven search surfaces: generative engines, answer engines, and emerging agentic browse experiences.
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Answer Engine Optimization
Answer Engine Optimization (AEO) is the practice of structuring content to be selected as the direct answer in AI-driven and traditional answer engines: featured snippets, voice assistants, and chat-based search.
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Generative Engine Optimization
Generative Engine Optimization (GEO) is the practice of structuring web content so that generative AI search engines like ChatGPT, Perplexity, Claude, and Google's AI Overview cite it as a primary source.
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LLM Optimization (LLMO)
LLM Optimization (LLMO) is the practice of making content easier for LLM-based systems to retrieve, parse, summarize, and attribute accurately when answering user prompts. It covers runtime retrieval influence (clearer, more actionable for publishers) and training-data influence (indirect, mostly unobservable, debated).
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