AEO — Answer Engine Optimization

What is AEO?

AEO (Answer Engine Optimization) is optimizing content for direct citation by “answer engines”: Google AI Overviews, Yandex Neuro, ChatGPT, Perplexity. The core technique — put the ready answer in the first sentence and split the text into self-contained question-answer blocks a machine can quote without rewriting.

In the zero-click era, users often get the answer right in the results and never visit the site. AEO competes not for the click but for source status: the engine pulls your answer into its card and credits you with the citation.

How is AEO different from SEO and GEO?

In short: SEO is about ranking pages, GEO is about a site’s overall visibility in AI answers, and AEO is a specific tactic for delivering content in a ready-answer format. That’s why AEO is usually treated as the practical part of GEO.

	Goal	Unit of optimization	Key technique
SEO	Rank in organic results	Page + keywords	Keywords, links, speed
GEO	Citation in AI answers	Whole site (content + technical base)	Structured data, llms.txt, robots AI-rules
AEO	Land in the “zero answer”	A single question-answer block	Inverted pyramid, Q&A, facts

The mechanics differ: a search engine ranks a page by relevance, while an answer engine extracts a ready fragment from it. If the fragment can’t be extracted, a competitor becomes the source.

How do you write content for AEO?

Each section is built as an independent module that’s easy for a machine to “slice.” Six rules of the frame:

1. Inverted pyramid. The direct answer goes in the first sentence after the heading; details follow below.
2. Heading = a user’s question. “How do I configure robots.txt for AI bots?” instead of “robots.txt setup.”
3. Short paragraphs. One idea = up to 3–4 lines. Engines skip long walls of text.
4. Lists and tables instead of prose — structured data is parsed first.
5. Concrete numbers. “From 15 minutes,” “10 of 23 checks” instead of “fast” and “many.”
6. Semantic cleanup. Remove filler words — the meaning should survive without 70% of the adjectives.

A machine-readable layer amplifies the effect: mark up FAQPage or HowTo blocks in Schema.org, serve clean Markdown to agents, and describe key pages in llms.txt.

How does AEO relate to our scanner?

There’s no direct “AEO text quality” check in the scanner — that’s a content metric that can’t be measured reliably without judging meaning. But we do check the technical foundation of AEO directly:

• schema_org — whether structured markup exists (including FAQPage/HowTo)
• markdown_negotiation — whether clean Markdown is served to agents
• llms_txt — whether LLM navigation is published

These three checks show whether the page’s infrastructure is ready for answer extraction. The text itself stays with the author — the six-rule frame above is the working checklist.