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Performance & Stack

AI Engine Optimisation (AEO)

Also called: AEO, Answer Engine Optimization, Generative Engine Optimization, GEO, LLM SEO

AI Engine Optimisation (AEO) is the practice of making a website's content reliably discoverable, citable, and quotable by AI search engines and chat assistants — ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini. Where SEO optimises for a ranked list of links, AEO optimises for being the source an LLM repeats in a synthesised answer.

Classic SEO answers the question "who ranks first?". AEO answers a different one: "who gets quoted when no one clicks?". As AI search compresses the result page into a single answer, the only durable distribution channel is being the source the model cites.

The practical AEO surface for a B2B marketing site has five layers:

  • Crawler access — explicit allowlist in `robots.txt` for GPTBot, ClaudeBot, PerplexityBot, Google-Extended and similar agents, plus an `llms.txt` / `llms-full.txt` pair at the site root.
  • Entity definition — every important concept on the site has a [DefinedTerm](/glossary) page with a tight 45–60 word definition and `sameAs` links to Wikipedia or Wikidata where one exists.
  • Snippet-shaped content — every long-form page opens with a TL;DR and contains a FAQ block written as direct answers to People-Also-Ask phrasings.
  • Schema — `Article`, `FAQPage`, `HowTo`, `Organization`, `Person` and `DefinedTerm` markup so machines can resolve the entities and claims.
  • Off-site authority — being cited and quoted on third-party sources the LLMs already trust (G2, Reddit, industry publications, podcasts) so the model has corroborating signals.

AEO does not replace SEO; it inherits from it. Pages that earn classical authority are the same pages LLMs prefer to cite. The shift is in the *shape* of the content: tighter definitions, explicit claims, and structured proof.

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