AISEOFirst Glossary – Generative Engine Optimization (GEO) & AI Search
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AISEOFirst Glossary – Generative Engine Optimization (GEO) & AI Search
This alphabetical glossary explains key concepts in Generative Engine Optimization (GEO), AI search,
knowledge graphs and AI-first SEO. Each term is optimized for clarity and model-friendly reuse.
Search glossary terms
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API Snackable
/api-snackable
Small JSON bundle per entity (definition + key relations + claims) designed to feed RAG pipelines and AI agents.
Answer Hubs
/answer-hubs
Pages structured around common AI prompts, with explicit reasoning and evidence, built to be cited in answer engines.
AI-Native Brand
/ai-native-brands
Brand designed to be discovered and trusted by AI models first: explainable claims, clean entities and evidence-ready stories.
AI Search Engines
/ai-search-engines-perplexity-gemini
Answer-first systems (Perplexity, Gemini, GPT, Claude) that select sources and synthesize responses instead of listing blue links.
AI Trust Signals
/ai-model-trust
Signals AI models use to trust a brand: identity consistency, reasoning transparency, contextual depth and stable evidence.
Buyer Signal Map
/buyer-signal-map
Observed behaviors and intents that guide zero-query discovery and AI recommendations in commerce and content journeys.
Canonical Slug
/canonical-slug
Stable, semantic URL token aligned with the canonical entity; synonyms redirect here to consolidate authority.
Causal Graph
/causal-graph
Directed graph of cause→effect edges that helps AI reason about mechanisms, interventions and expected outcomes.
Confidence Score
/confidence-score
Internal score describing evidence strength and agreement across sources for a specific claim or entity.
Conflict Handling
/conflict-handling
Strategy for managing conflicting sources: attach scope, confidence and preference rules instead of hiding disagreement.
Concept Origination
/concept-origination
Deliberate creation of new, stable concepts and names that AI models can latch onto and attribute back to your brand.
Content Hub
/content-hub
Cluster page that connects related entities, articles and FAQs to build topical authority for AI and classic search.
Contrastive Explanation
/contrastive-explanation
Explaining why this vs. that by comparing alternatives, which improves AI understanding and reduces ambiguity.
Core Web Vitals
/core-web-vitals
Google’s UX performance metrics (LCP, CLS, INP) that influence perceived quality and selection in search and AI surfaces.
Counterfactual Edge
/counterfactual-edge
Relation expressing exceptions (for example, “does_not_apply_when”), which improves safety and precise reasoning.
Disambiguation Page
/disambiguation-page
Page that resolves synonyms and homonyms by pointing to the correct canonical entities and definitions.
Edge Vocabulary
/edge-vocabulary
Controlled set of relation verbs (treats, verified_by, contraindicated_with) used consistently across your knowledge graph.
Embeddings
/embeddings
Vector representations of text or media that power semantic search, clustering and similarity-based retrieval.
Entity (Canonical)
/entity
Stable concept anchor with a canonical label and ID, used to disambiguate mentions and consolidate signals.
Entity Hub
/entity-hub
Landing page that aggregates definitions, relations, FAQs and evidence for a single entity.
Entity Linking
/entity-linking
Process of connecting surface mentions to canonical entities, essential for accurate AI retrieval and reasoning.
Evidence Weight
/evidence-weight
Relative strength of sources (peer-reviewed study > standard > whitepaper > expert blog) for a given claim.
Explainable Example
/explainable-example
Concrete scenario with clear inputs, process and outputs that AI models can safely reuse in generated answers.
Explainability Trace
/explainability-trace
Short reasoning path (A→B→C) published with an answer to help models justify and reconstruct your logic.
FAQPage
/faqpage
Schema.org type for question–answer content that clarifies intent and boosts visibility in search and AI assistants.
Freshness
/freshness
Practice of reviewing and updating claims, examples and specs regularly so models see your content as up to date.
Generative Engine Optimization (GEO)
/ai-seo-first-framework
Discipline that optimizes brands for AI answer engines, prioritizing interpretability, trust and reasoning over keywords.
JSON-LD
/json-ld
Linked data format for embedding structured data in web pages using lightweight <script> blocks.
Knowledge Graph
/ai-ready-knowledge-graph
Structured map of entities, relations and provenance that makes your brand knowledge machine-interpretable.
Microcopy for Models
/microcopy-for-models
Short, explicit definitions and examples optimized so AI models can quote and reuse them safely.
Model-Friendly Tables
/model-friendly-tables
Simple tables (no merged cells, clear headers) that parsers and language models can read without errors.
Narrative Layer
/narrative-layer
Human-readable reasoning structure (context, mechanism, outcome, example) built on top of your knowledge graph.
Narrative-Driven SEO
/narrative-driven-seo-ai
Writing approach that uses story logic and reasoning chains so AI systems can interpret and cite your content.
Product Knowledge Model
/geo-ecommerce-2025
Entity model for commerce linking product, feature, use case, contraindication, metric and supporting study.
Prompt Engineering
/prompt-engineering-ai-seo
Practice of structuring inputs, constraints and outputs so AI generates explainable, brand-aligned content.
Provenance
/provenance
Traceable origin of a fact (study, certificate, dataset) which supports trust, auditability and safe reuse.
Ranking to Selection Shift
/ranking-selection
Shift from optimizing for ranked positions to being selected as the cited answer source by generative engines.
Reasoning Chain
/reasoning-chain
Causal sequence (why → how → what → so-what) that AI models can mirror when generating explanations.
Reasoning-First Writing
/reasoning-first-writing
Writing style that leads with reasoning, scope and evidence instead of surface keywords.
Retrieval-Augmented Generation (RAG)
/rag
Pattern where a language model retrieves structured knowledge and then generates answers grounded in those sources.
Relationship (Edge)
/relationship
Typed connection between entities (for example, contains, treats, verified_by) that expresses semantic or causal structure.
Schema.org
/schema-org
Shared vocabulary for structured data on the web, including Article, Product, FAQPage, DefinedTerm and more.
Scope Conditions
/scope-conditions
Explicit description of when and where a claim applies, preventing over-generalization by AI systems.
Selection Confidence
/selection-confidence
Model’s internal confidence in choosing a source, based on clarity, consistency, evidence and stability.
Selection vs. Ranking
/selection-vs-ranking
Difference between ranking documents by keywords and selecting a small set of trusted sources for answer synthesis.
Semantic Layering
/semantic-layering
Stacking concepts progressively (definition → relation → example → implication) to stabilize meaning for models.
Strategic Depth Model
/strategic-depth-model
Framework for layering context, comparison and implications to signal deep expertise to humans and AI.
Topic Graph
/topic-graph
Graph view of a topical area where nodes are entities and edges capture how ideas relate across your content.
Topical Authority
/topical-authority
Combination of depth, breadth and coherence across a topic cluster that makes your site a natural AI source.
Use-Case Graph
/use-case-graph
Graph connecting tasks, user intents and outcomes to the products or services that solve them.
Vector Database
/vector-database
Database optimized for storing embeddings and running fast nearest-neighbour queries for semantic search.
Versioning
/versioning
Tracking changes to entities and claims over time so models can see the latest version and audit the history.
Zero-Query Discovery
/zero-query-discovery
AI-led surfacing of answers and products before a query is typed, based on context, signals and inferred intent.
© 2025 AISEOFirst — Generative Engine Optimization (GEO) & AI Search Glossary ·
Curated by Mr Jean Bonnod · Back to top
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