Three acronyms, one revolution
Since the emergence of generative AIs that can answer questions directly without redirecting to websites, classical SEO alone is no longer sufficient. Three new disciplines have emerged:
- GEO (Generative Engine Optimization), optimizing to be cited by generative engines (Google AI Overviews, SearchGPT, Perplexity)
- LLMO (Large Language Model Optimization), optimizing your presence in LLM training corpora and responses
- AEO (Answer Engine Optimization), structuring content so answer engines (Perplexity, Bing Copilot, You.com) select it as an authoritative source
GEO, Generative Engine Optimization
Google AI Overviews, SearchGPT, and Perplexity generate synthetic responses from selected sources. GEO aims to be among those sources, and ideally to be named in the generated response.
Confirmed GEO factors in 2026
Editorial authority. AIs favor sources recognized as authoritative: identified authors with verifiable expertise, factual sourced content, citations from reference sources (NRF, Google, Shopify, official institutions).
Content structure. H2/H3 headings as questions, structured lists, comparison tables, and precise definitions facilitate AI extraction. Content dense with well-defined technical terms is more easily synthesized than fluent narrative content.
Freshness. Publication and update dates are read by AIs. Well-dated 2026 content is preferred for recent-topic queries over non-updated 2023 content.
Schema.org structured data. FAQPage, Article, HowTo, and Organization help AIs understand the nature and context of content.
LLMO, Large Language Model Optimization
LLMs (GPT-4o, Gemini 2.0, Claude 3) were trained on massive text corpora. What appeared in those corpora directly influences their responses, including commercial recommendations.
How to optimize for LLMs
Be present on indexed sources. Common Crawl, Wikipedia, GitHub, arXiv, and major sector blogs are over-represented in training corpora. Being cited on these platforms improves your LLM footprint.
Create reference content. LLMs memorize precise definitions, factual lists, and quantified data better. Producing the reference content on a subject, the most complete definition, the most precise comparison table, increases chances of being memorized and cited.
The llms.txt file. An emerging standard involves placing an /llms.txt file at the site root, listing key content in a format optimized for AI reading, the equivalent of robots.txt for training crawlers.
AEO, Answer Engine Optimization
Perplexity, You.com, and Bing Copilot retrieve real-time web sources to generate their responses. AEO aims to be systematically selected and cited by these tools.
Key AEO factors
Direct topical relevance. Answer engines favor pages whose title precisely matches the query. A page titled exactly "What is agentic commerce?" will be selected more often than an article that covers the topic in passing.
Extractable passages. Short, self-contained paragraphs that answer a specific question in 2-3 sentences, comprehensible without the rest of the article.
Citing reliable sources. Citing NRF, Google, Shopify, or academic studies reinforces AEO credibility.
Practical application to agentic commerce
| Discipline | Concrete action | Expected impact |
|---|---|---|
| GEO | H2 headings as questions + FAQPage schema JSON-LD | Appear in Google AI Overviews |
| GEO | Update pages with current dates and sourcing | Be selected as fresh source |
| LLMO | Publish complete maintained /llms.txt | Better indexing by AI crawlers |
| LLMO | Be cited on GitHub awesome-ucp, Wikipedia | Presence in training corpora |
| AEO | Introductions in direct definition format | Citations in Perplexity and Bing Copilot |
| AEO | FAQ with autonomous question/answer pairs | Featured snippets and People Also Ask |
Priority action plan for 2026
- Add publication and update dates to all pages
- Transform each H2 into an explicit question ("How…", "Why…")
- Implement FAQPage schema JSON-LD on key pages
- Publish /llms.txt listing main pages with descriptions
- Create or improve your brand's Wikipedia presence
- Submit your site to AI directories (directory.llmstxt.cloud)
- Structure product pages with schema.org Product + Offer + Review
Further reading
- Structured data for AI agents: schema.org and UCP
- llms.txt for e-commerce
- GEO optimization for e-commerce: practical guide
Update · May 2026
Google states officially that llms.txt is not used by its AI search. llms.txt stays relevant for third-party LLM crawlers (ChatGPT, Perplexity, Claude), not as a Google lever. See our breakdown of Google's GEO guide. Source: Google.