Canonical definitions, comparisons, and implementation guides. Start here to build your GEO foundation.
Canonical definition of Generative Engine Optimization — how content becomes visible in AI-generated answers.
Answer Engine Optimization explained — structuring content so AI systems can extract and cite direct answers.
How generative engine optimization differs from traditional search optimization. Side-by-side with decision criteria.
When to use GEO strategy vs AEO strategy. Understand the difference between visibility and answerability.
Complete specification for the llms.txt standard — tell AI systems what your site contains.
Framework for planning content that earns AI citations. Audit, optimize, and measure AI search visibility.
Implementation specs, file standards, and measurement frameworks. Everything you need to make your content AI-ready.
Every concept has one canonical page. Explore the knowledge graph organized by domain.
Generative Engine Optimization - visibility in AI answers
Answer Engine Optimization - direct answer extraction
Implementation specs - llms.txt, schema, crawl signals
Business frameworks - ROI, planning, measurement
Glossary, cheatsheets, canonical definitions
Evaluations, comparisons, and stack recommendations
Applied examples, implementation stories, and scenario-based evidence
Machine-readable specs and guidance for AI agents and parsers
Every page on geodocs.dev includes AI summary blocks, structured frontmatter, and machine-readable specs. Our content is designed to be cited by AI systems worldwide.
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