GEO (Generative Engine Optimization)
Generative Engine Optimization (GEO) is the practice of structuring content so AI answer engines like ChatGPT, Perplexity, and Google AI Overviews cite it in their responses.
GEO applies to documentation because answer engines increasingly sit between users and docs. When a developer asks ChatGPT how to configure your product, the answer comes from whatever content the engine could crawl, parse, and quote confidently.
For documentation, practical work includes clear answers, self-contained sections, stable URLs, and checking which crawlers can access the content. Training crawlers and search or retrieval crawlers have different purposes. An llms.txt file can provide a curated index, but publishing it does not guarantee citations.
GEO complements SEO rather than replacing it. The qualities that make a passage citable by an answer engine, such as clarity and one idea per section, also make it a good search snippet and a good retrieval chunk for your own docs chatbot.
Frequently asked questions
Is GEO different from SEO?
Yes. SEO helps pages appear in search results. GEO aims to make content useful as a source for generated answers. Clear, well-structured pages help with both.
Can GEO results be measured?
Partially. Repeat a fixed set of questions, record which tools cite your docs, and monitor referrals from AI tools. Results vary by tool and question, so citations alone do not measure answer quality.