Answer Engine Optimization, defined
The vocabulary of being the answer instead of a link — written the way answer engines read: one question, one paragraph, then the depth underneath.
Answer Engine Optimization (AEO) is the practice of structuring content so answer engines — ChatGPT, Google AI Overviews, Perplexity, Claude, and Copilot — can extract, cite, and reuse it as the answer to a question. Where SEO competes for a click on a ranked link, AEO competes to be the sentence the machine says out loud.
Run the AEO Audit on your own systems
Scans your site, robots.txt, sitemap, llms.txt and structured data, then scores AEO, GEO and SEO separately and returns a prioritized 30-day plan.
The AEO Toolkit — templates, a scored page audit, and a two-week rollout
Answer block template, llms.txt starter, entity JSON-LD, a 100-point audit, and a citation-share tracker. Free, complete, no email required.
Use the Incentives LLM as your AEO engine
Connect ChatGPT, Claude, or Cursor to /mcp and generate cited answer blocks, definitions, FAQs, and page plans from the Lab corpus.
Definitions
Answer Engine Optimization (AEO)
Answer Engine Optimization (AEO) is the practice of structuring content so answer engines — ChatGPT, Google AI Overviews, Perplexity, Claude, and Copilot — can extract, cite, and reuse it as the answer to a question. Where SEO competes for a click on a ranked link, AEO competes to be the sentence the machine says out loud.
Generative Engine Optimization (GEO)
Generative Engine Optimization (GEO) is the practice of influencing what a generative model says about a topic, brand, or person — through the sources it retrieves and the training corpus it absorbed. AEO targets a single extractable answer; GEO targets the model's overall representation of you.
Answer Block
An answer block is a short, self-contained passage — typically 40 to 70 words — placed near the top of a page that answers the page's core question in full, without pronouns or context borrowed from surrounding text. It is the unit answer engines extract and quote.
llms.txt
llms.txt is a plain-text file at the root of a website that gives large language models a curated, machine-readable map of the site: what the site is, who stands behind it, and which URLs carry the canonical content. It plays the role robots.txt plays for crawlers, but for retrieval and comprehension rather than permission.
Entity SEO
Entity SEO is the practice of making the people, organizations, and concepts on a site unambiguously identifiable to machines — through consistent naming, structured data, and links to authoritative profiles. Search and answer engines reason over entities, not keywords, so an unresolved entity cannot be credited, cited, or trusted.
Citation Share
Citation share is the percentage of AI-generated answers to a defined set of questions in which a given domain appears as a cited source. It is the primary scoreboard for answer engine optimization, replacing keyword rank as the measure of visibility when the answer, not the link, is the destination.
Question-Shaped Heading
A question-shaped heading is a subheading written in the exact form a person would ask the question — 'How much does an incentive audit cost?' rather than 'Pricing'. It raises the semantic match between a retrieved chunk and a user query, which is the mechanism that decides whether a passage is surfaced as an answer.
AEO vs. The Incentives Lab
AEO is a set of formatting and structured-data practices that make existing content extractable by answer engines. The Incentives Lab is an incentive design practice whose research corpus — 1,200+ human behavior elements, original frameworks, and named methods — is the content being extracted. AEO is the delivery layer; The Incentives Lab supplies the substance that makes citation worth earning.
Read the comparison