What Answer Engine Optimization and Generative Engine Optimization mean, and how to get your site cited by AI Overviews, ChatGPT, Claude, Perplexity, and Gemini. Search results don’t look the way they did two years ago. Google now opens with AI Overviews, ChatGPT and Claude pull live web results into their answers, Perplexity built an entire product around it, and Gemini sits one tap away inside every Google surface. The page is no longer the destination. The page is a source the model is reading on your behalf. Two acronyms have shown up to describe the work of being visible inside those answers. AEO stands for Answer Engine Optimization, which is the work of being the source an "answer engine" uses when it returns a direct answer instead of a list of links. GEO stands for Generative Engine Optimization, which is the same idea framed around generative AI specifically: appearing inside answers a model writes from scratch using your page as a reference.
Google’s own AI optimization guide treats both as variations of regular SEO. From their perspective, "optimizing for generative AI search is optimizing for the search experience, and thus still SEO." The ranking and quality systems that decide what shows up in a list of blue links are the same systems that decide what shows up inside an AI Overview. Improving for one improves the other. One reason this matters: each AI surface pulls from a different web index, but most of those indexes are downstream of the same crawl, rendering, and quality work. The practical question is what you do to your site. The rest of this post walks through it, with sources for every recommendation. Before any of the content work matters, the page has to be allowed to appear in AI features at all. Google’s guide is explicit: a page is only eligible for AI features if it’s eligible to appear as a regular search snippet (source). That means the URL needs to be indexed, the page needs to be crawlable in robots.txt, snippets need to be allowed (no nosnippet, no max-snippet:0), and the content has to load without requiring the crawler to execute heavy JavaScript first.
Open Google Search Console and run a URL inspection on a page you care about. The "Test live URL" view shows you what Google sees, including the rendered HTML after JavaScript has executed. If the article body is missing from that rendered HTML, fix it before doing anything else. Google’s JavaScript SEO basics covers the patterns that work and the ones that break crawling. Server rendering and static generation are the safest bets. A 200 OK from a spoofed user agent isn’t proof that the real crawler can reach the page. Bot operators block UA spoofing, so the only authoritative check is to verify the request against published IP ranges or reverse-DNS records. Google documents its crawler verification process, and OpenAI, Anthropic, and Perplexity all publish IP ranges in their bot docs. Use the curl test to catch obvious blocks (a 403, 503, or login-page redirect that suggests Cloudflare’s bot-fight rule or a misconfigured WAF), then confirm against the official IP list for the bots that matter to you.
The distinction matters. GPTBot and ClaudeBot are training crawlers, and blocking them does not affect search inclusion. Google-Extended is broader: it controls AI training and grounding inside Gemini Apps and Vertex AI Grounding, but does not affect Google Search ranking or AI Overview eligibility (Google source). The bots that determine whether your page can show up inside an AI answer are the search indexers: Googlebot, Bingbot, OAI-SearchBot, Claude-SearchBot, and PerplexityBot (OpenAI Top Source Media, Anthropic source, Perplexity source). Many sites accidentally block one of those and tank their visibility. To opt out of Google-Extended (Gemini Apps and Vertex AI Grounding), use the robots.txt product token shown earlier. Google does not document Google-Extended as a robots meta tag, only as a robots.txt token (source). The snippet directives above are documented in Google’s meta tags reference. Every layer is a gate. The fancier optimization work only matters once all the gates are open. Generative search rewards specificity.
Models can summarize generic information without quoting anyone, so the pages that get cited are the ones that say something the model can’t synthesize on its own. Google’s guide tells creators to focus on "unique, valuable, people-first content" rather than commodity content that re-states what every other page on the topic already says (source). The deeper version of this advice lives in Google’s helpful content guidance, which goes into how to demonstrate firsthand experience, real expertise, and original perspective. A model can produce the commodity version from training data alone, so it won’t cite the source. There’s nothing in there it couldn’t write itself. The distinctive version has a number (47 broken pages), a specific catch (the function signature subtlety), and a time estimate (3 hours), none of which the model can generate without quoting the Top Source Media. Even one of those details is often enough to flip a page from "training data summary" to "cited reference".