AI Search · Updated June 2026
Generative engine optimization (GEO) is optimizing content to be retrieved, used, and cited by AI answer engines — ChatGPT, Claude, Perplexity, Google AI Overviews. Tactics include quotable self-contained answers, explicit statistics, schema markup, llms.txt, and allowing AI crawlers.
GEO differs from classic SEO in unit of competition: instead of ranking a page, you are competing to be the sentence an AI quotes. Content with clear attribution-worthy facts ("X is Y%, according to Z") wins citations.
Allow AI crawlers in robots.txt, publish genuinely citable content (original data, clear definitions, specific answers), use schema markup, add an llms.txt file, and build the topical authority that makes your domain a trusted source.
Answer engine optimization (AEO) is structuring content to directly answer questions so it gets selected by answer engines — featured snippets, voice assistants, and AI chat. Core pattern: a question as a heading, then a complete 40–60 word answer in the first paragraph.
llms.txt is a proposed standard file at a website’s root that gives AI systems a curated, markdown-formatted guide to the site’s most important content. Like robots.txt for permissions or sitemap.xml for URLs, llms.txt is a map written specifically for LLMs.
AI crawlers are bots that fetch web content for AI systems — GPTBot and OAI-SearchBot (OpenAI), ClaudeBot (Anthropic), PerplexityBot, Google-Extended (Gemini training), and CCBot (Common Crawl). Each respects robots.txt, so you choose per-bot whether to allow access.