GEO, SEO and AEO are three overlapping disciplines for getting found, and in 2026 you need all three because discovery now happens in two places: classic search results and AI answers. SEO (search engine optimization) is the long-standing craft of ranking in Google and Bing. AEO (answer engine optimization) is about being the source an answer engine extracts when it gives a direct answer. GEO (generative engine optimization) is about being cited and recommended inside the synthesised responses of generative assistants like ChatGPT, Perplexity and Claude. They share most of their tactics and differ in what they optimise for. This guide defines each precisely, shows how they relate, and gives you a practical checklist (structured data, llms.txt, answer-first content) you can apply today. Everything here is current as of June 2026 and pairs with the Course 5 SEO and GEO/AEO lesson.
The three terms, defined
It is easy to treat these as buzzwords, so pin down what each one actually means. SEO optimises for ranking in traditional search engine results: the blue links on Google and Bing, driven by relevance, authority and crawlability. AEO optimises for the answer layer: getting your content selected as the source when an engine returns a direct answer, a featured snippet, a voice response or an AI answer box, by making a specific fact, definition or recommendation easy to extract. GEO optimises for generative answers: being chosen and cited when an assistant like ChatGPT or Perplexity synthesises a response from multiple sources. The neat way to hold the difference: SEO ranks pages, AEO supplies the answer, GEO earns the citation. See the glossary entries on GEO and AEO for the standalone definitions.
- SEO: rank in traditional search results (Google, Bing) through relevance, authority and crawlability.
- AEO: be the source extracted for a direct answer (snippets, voice, AI answer boxes).
- GEO: be cited and recommended inside a generative assistant's synthesised response.
- Shorthand: SEO ranks the page, AEO supplies the answer, GEO earns the citation.
How they differ, and why they overlap
The three are not rivals; they are layers of one strategy. SEO establishes baseline visibility, AEO makes your content extractable for direct answers, and GEO positions it as trusted reference material an assistant will cite. The reason you do not have to chase them separately is that they reward the same underlying thing: clear, well-structured, trustworthy content that a machine can read, understand and trust. The differences are in emphasis. SEO still cares a lot about links and ranking signals. AEO cares about answering a specific question cleanly and early on the page. GEO cares about the signals a model uses as a proxy for credibility: clear attribution, quotable statements, statistics and citations. Optimise the shared foundation well and you serve all three at once; then tune the emphasis per channel.
- They are layers of one strategy, not competing tactics; SEO is the base, AEO and GEO build on it.
- All three reward the same thing: clear, structured, trustworthy, machine-readable content.
- Emphasis differs: SEO leans on authority and links, AEO on clean extractable answers, GEO on citability.
- Generative engines treat attribution, quotes, statistics and citations as credibility signals.
Write answer-first content
The biggest single shift for AEO and GEO is structuring content so a machine can lift the answer out cleanly. Lead with the answer: open the page, or a section, by directly answering the question it targets in one or two self-contained sentences, then expand. A heading phrased as the real question ("What is GEO?") followed by an immediate, quotable definition is far more extractable than a paragraph that warms up for three sentences first. Keep claims specific and attributable, because models favour content that reads as credible: cite sources, include real statistics, and use clear, quotable statements. A frequently-asked-questions section is one of the highest-value formats because each question-and-answer pair is a pre-packaged, extractable answer that maps directly onto how people query assistants.
- Answer first: open each section by answering its question in one or two self-contained sentences.
- Phrase headings as the questions people actually ask, then answer immediately below.
- Use a real FAQ section; each Q-and-A pair is a ready-to-extract answer.
- Be specific and attributable: statistics, clear quotable claims and cited sources read as credible.
Add structured data
Structured data is markup (usually JSON-LD using the Schema.org vocabulary) that tells machines exactly what your content is, removing the guesswork. It is foundational for all three disciplines because it lets search and answer engines parse your page reliably rather than inferring its meaning. The high-value types for a content site are FAQPage (mark up your FAQ so each question and answer is machine-readable), Article or BlogPosting (declare author, dates and headline), HowTo (mark up step-by-step guides), BreadcrumbList (express site structure), and Organization or Person (establish who is behind the content, which feeds the credibility signals GEO rewards). Get the markup correct and validate it; broken structured data helps nobody. This campus emits exactly these types on its content pages, which is the practical version of the advice.
- Use JSON-LD with Schema.org types so machines parse your content instead of guessing.
- High-value types: FAQPage, Article/BlogPosting, HowTo, BreadcrumbList, Organization/Person.
- Organization and Person markup establishes who is behind the content, feeding GEO credibility signals.
- Validate your markup; broken structured data is worse than none.
Publish an llms.txt and clean Markdown
llms.txt is a simple proposed standard: a Markdown file at the root of your site (/llms.txt) that gives AI crawlers a clean, curated map of your most important content, free of the navigation, ads and scripts that clutter a normal HTML page. It is an agent-first courtesy that makes your site cheaper and clearer for a model to understand, which is squarely in the GEO and AEO spirit. Pair it with clean, semantic HTML and, where you can, Markdown versions of your pages, so the content a model reads is the content that matters rather than a soup of markup. The same instinct that makes a site good for assistants (clarity, structure, no clutter) makes it good for human readers too. See the glossary entry on llms.txt for the format.
- Publish /llms.txt: a Markdown map of your key content for AI crawlers, without the page clutter.
- Serve clean, semantic HTML and Markdown twins where you can, so models read signal not soup.
- It is an agent-first courtesy that aligns with the agent-first products approach to building.
- See the glossary on llms.txt for the exact format and the llms.txt generator tool when it ships.
Do not abandon classic SEO
In the rush toward AI answers it is easy to forget that the fundamentals still carry most of the weight, and an answer engine often draws on pages that rank well in the first place. So keep doing the SEO basics: clear, compelling title tags and meta descriptions, a sitemap, a clean URL structure, fast pages, and Search Console set up so you can see how you are doing. Authority and trust (E-E-A-T: experience, expertise, authoritativeness, trustworthiness) matter for all three channels, because both Google and the assistants are trying to surface sources they can rely on. The honest framing for 2026 is that GEO and AEO are not a replacement for SEO but an additional layer on top of a solid SEO foundation. Build the foundation, then optimise for the answer and the citation.
- Keep the SEO basics: title tags, meta descriptions, sitemaps, clean URLs, fast pages, Search Console.
- Assistants often cite pages that already rank, so SEO feeds AEO and GEO rather than competing with them.
- E-E-A-T (experience, expertise, authoritativeness, trust) matters across all three channels.
- Treat GEO and AEO as a layer on top of solid SEO, not a replacement for it.
Step by step
Nail the SEO foundation
Write clear title tags and meta descriptions, publish a sitemap, keep URLs clean and pages fast, and set up Search Console. This is the base all three channels build on.
Restructure content answer-first
Open each page and section by answering its target question in one or two self-contained, quotable sentences. Phrase headings as the questions people ask, and add a real FAQ section.
Add and validate structured data
Mark up pages with JSON-LD using Schema.org types: FAQPage, Article or BlogPosting, HowTo, BreadcrumbList and Organization or Person. Validate the markup so it parses correctly.
Publish an llms.txt and clean Markdown
Add a /llms.txt file that maps your most important content for AI crawlers, and serve clean semantic HTML (and Markdown twins where possible) so models read the content, not the clutter.
Strengthen credibility signals
Add author attribution, real statistics, cited sources and clear quotable claims. Generative engines use these as proxies for trust, which is what earns the citation.