The knowledge layer for AI search.

What is AEO and why it matters

Answer Engine Optimization (AEO) is the practice of structuring a website so AI systems like ChatGPT, Perplexity, Google AI Overviews, and Gemini can extract, understand, and cite its content. Unlike traditional SEO, which targets ranking positions in search results, AEO targets citation probability inside AI-generated answers. These two goals require overlapping but distinct signals. A site can rank first on Google and still be completely absent from AI answers.

The guides in this knowledge base break down the AEO signal landscape: from crawl access and rendering architecture to structured data implementation, entity disambiguation, and the specific patterns that produce consistent AI citation.

The AI retrieval pipeline

AI citation is not arbitrary. It follows a pipeline: crawler access, content extraction, semantic evaluation, relevance scoring, and citation selection. Each stage can eliminate your site from consideration. A page blocked by robots.txt never enters the pipeline. A page rendered client-side with JavaScript produces no extractable content. A page with no structured data provides no machine-readable signals about its subject matter. A page with ambiguous brand identity gets associated with the wrong entities or none at all.

Understanding how AI search works from crawl to citation is the foundation for every other optimization. The guides here are organized to move you through each stage of that pipeline with actionable specifics, not abstract theory.

Start with these guides

• --What is AEO? Answer Engine Optimization explained
• --Why AI search skips websites: 8 common causes
• --Schema markup for AI search: which types matter
• --Why server-side rendering matters for AI search visibility
• --How to get your site cited by ChatGPT and other AI systems

For context on how these concepts apply to real site audits, see the AudFlo blog, which covers applied examples of each optimization pattern.