Reference · Page 4
Glossary, cheatsheets, and canonical definitions for GEO/AEO terminology.
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Grounding vs Fact-Checking: What's the Difference in AI Content Workflows?
Grounding anchors AI answers to trusted sources before generation; fact-checking verifies claims after generation. Learn when each belongs in your AI content workflow.
LLM Citation Anchor Text Patterns: How Generative Engines Phrase Source Mentions
LLM citation anchor text patterns reference cataloging how ChatGPT, Perplexity, Gemini, and Claude phrase source mentions across answer formats and engines.
LLM Context Window Impact on Citation Patterns
Reference on how LLM context window size, position bias, and chunking shape which passages get cited, with rules to make GEO content survive long-context retrieval.
llms.txt Field Reference
Complete field-by-field reference for the llms.txt specification: required H1 and blockquote, optional sections, link list format, and companion files .md and llms-full.txt.
Retrieval-Augmented Generation (RAG) vs Answer Grounding: What's the Difference?
Compare RAG and answer grounding: how they differ in objective, architecture, evaluation, and when to choose each to make AI answers trustworthy.
Robots.txt vs ai.txt vs llms.txt: Practical Comparison
Compare robots.txt, ai.txt, and llms.txt: purpose, AI bot support, risks, and a practical implementation checklist for site owners.
Structured Data Cheatsheet for AI Search (2026)
Copy-ready JSON-LD templates and 2026 status for the schema types that still drive AI search citations: Article, FAQPage, Organization, Product, Review, BreadcrumbList, and more.