Make the page eligible for search
Keep it indexable, avoid accidental noindex or nosnippet settings, and make sure robots.txt, CDN rules, and WAF rules allow the bots you want.
Generative Engine Optimization
Generative Engine Optimization, or GEO, is the practice of making a page easy for AI search systems and assistants to discover, understand, quote, and cite accurately. In practice, that means strong SEO fundamentals, clearer entities, answer-first content, and an explicit policy for AI crawlers.
Author: Piotr ZientaraLast updated: May 18, 2026Canonical: https://www.alfaumi.pro/generative-engine-optimization
What changed
GEO is less about inventing new markup and more about serving modern retrieval systems: AI Overviews, AI Mode, ChatGPT Search, Claude Search, and Perplexity. In May 2026 Google expanded inline links and citations inside AI answers, raising the value of being a cited source.
What did not change
High-quality technical SEO still matters. Google explicitly says there are no extra AI-only requirements to appear in its AI search features.
What to do now
Build pages around real intents, keep important content in HTML, and separate search bot access from model-training access where platforms support it.
Current checklist
Answer the query in the first 150 words
Lead with a direct, definition-style answer in the opening lines. AI retrieval pipelines weight the first ~150 tokens heavily during summarization, so a buried answer is easy to miss.
Back claims with citations and concrete data
Include named sources, statistics, dates, and first-party numbers inline at the claim. Pages with verifiable, cross-checkable facts are cited noticeably more often than vague brand copy.
Keep time-sensitive pages fresh
Citation priority decays fast: most pages cited in AI answers are under 30 days old. Revisit comparisons, pricing, and how-to content on a regular cycle and show a real update date.
Expose facts in crawlable text
Products, policies, pricing, comparisons, and explanations should be visible in the rendered HTML, not only inside client-side widgets or PDFs.
Use schema that reflects the page
Add Organization, SoftwareApplication, Article, FAQPage, BreadcrumbList, or other relevant schema only when the user can see matching content on the page.
Show who is responsible
Include authors, organization details, and dates so the page has stronger trust and provenance signals.
Create pages for real intents
Exact-match pages such as product comparisons, definition pages, pricing pages, and policy pages are easier for search systems and answer engines to retrieve and cite.
Separate discovery from training
Where platforms support it, allow search bots and user fetchers separately from training crawlers so you can maximize visibility without making a larger data-sharing decision by accident.
Build visibility across multiple AI engines
ChatGPT Search, Google AI Mode, Perplexity, and Copilot each retrieve differently. Brands cited across several engines see far higher overall citation rates than single-engine presence.
Treat llms.txt as optional, not foundational
llms.txt is cheap to publish and useful for IDE agents and MCP tooling, but 2026 data shows the major AI search crawlers largely ignore it. Do not let it displace good HTML, internal links, or schema.
A practical robots.txt stance
A useful default for many product sites is to allow search bots and user-directed fetchers while blocking training bots where those controls are separate. That keeps the site discoverable without treating training access as the default.
User-agent: *
Allow: /
Disallow: /api/
User-agent: OAI-SearchBot
Allow: /
Disallow: /api/
User-agent: ChatGPT-User
Allow: /
Disallow: /api/
User-agent: Claude-SearchBot
Allow: /
Disallow: /api/
User-agent: Claude-User
Allow: /
Disallow: /api/
User-agent: PerplexityBot
Allow: /
Disallow: /api/
User-agent: GPTBot
Disallow: /
User-agent: ClaudeBot
Disallow: /Google is the main exception to this clean split: Google-Extended controls Gemini training and grounding separately from Google Search, so that decision deserves an explicit policy choice.
Where llms.txt fits
llms.txt is a helper file for inference-time agents and developer tooling. It is not required for Google AI features, and 2026 adoption studies show the major AI search crawlers rarely fetch it — so it should not replace good HTML pages, internal linking, or structured data. Its real value today is for IDE agents and MCP tooling that read a curated shortlist of your most important pages.
AlfaUMi now publishes both /llms.txt and /llms-full.txt so agents can get either a short or expanded view of the product.
References
Google AI Features and Your Website
Google says there are no extra AI-only requirements for AI Overviews or AI Mode.
Google crawler reference
Google documents Google-Extended as a separate control for Gemini training and grounding.
OpenAI crawler controls
OpenAI separates OAI-SearchBot, ChatGPT-User, and GPTBot.
Anthropic crawler controls
Anthropic separates Claude-SearchBot, Claude-User, and ClaudeBot.
Perplexity crawler docs
Perplexity recommends allowing PerplexityBot and, where relevant, its published IPs.
llms.txt proposal
An inference-time standard for an AI-readable site overview. Useful for IDE agents, but 2026 adoption data shows AI search crawlers rarely fetch it.
Google AI Overviews & AI Mode links update
May 2026: Google expanded inline links, hover previews, creator attribution, and article suggestions inside AI answers.
FAQ
Is GEO different from SEO?
Yes, but it builds on SEO. SEO gets pages discovered and indexed. GEO makes the same pages easier for AI systems to extract, summarize, and cite correctly.
Does schema guarantee AI citations?
No. Schema helps machines understand page structure and entities, but citations still depend on the relevance, clarity, originality, and usefulness of the visible content.
Should I publish llms.txt?
It is low-effort and helps IDE agents and MCP tooling, so it is fine to publish. But adoption studies in 2026 show the major AI search crawlers rarely fetch it, so it should never replace strong HTML pages, internal linking, or structured data.
Can I block training bots and still show up in AI search?
Often yes. OpenAI, Anthropic, and Perplexity all document separate controls for search or user-requested fetches versus model-training crawlers.
How fresh does my content need to be for AI search?
Fresher than most teams expect. For time-sensitive topics, citations decay within weeks and the majority of pages cited in AI answers are under a month old. Keep comparisons, pricing, and how-to pages on a regular update cycle and surface a genuine update date.
What content gets cited most often?
Pages that answer a narrow question in the first 150 words, include concrete data and named citations, use consistent entity names, stay recently updated, and make supporting details easy to verify are cited most often.
Did Google change anything for AI search in 2026?
In May 2026 Google expanded links inside AI Overviews and AI Mode with inline citations, desktop hover previews, creator attribution, and end-of-answer article suggestions, and published an official AI optimization guide. Its core position is unchanged: standard SEO best practices cover AI features, with no AI-only requirements.
Audit your site against the checklist
AlfaUMi turns these GEO requirements into a concrete report covering structured data, crawlability, AI bot policy, content clarity, and action items for your codebase.