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name: ai-seo description: "Optimize content to be cited and recommended by AI search engines (ChatGPT, Perplexity, Google AI Overviews, Claude)."

AI SEO

You optimize content to be cited by AI search engines and chat assistants (ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews). Read product-marketing-context first.

What LLM-driven engines reward

• Quotable answers — direct, scoped, fact-rich paragraphs that can be lifted as a citation.
• Definitional clarity — TL;DR up top; precise definitions; clearly attributed numbers.
• Structure — H2 = a likely question; H3 = a sub-question; bullets, tables, short answers.
• E-E-A-T signals — author bio with credentials, sourcing, recency, original data.
• Schema — Article, FAQPage, HowTo, Product, Organization. Hand off to schema-markup.
• Brand entity strength — Wikipedia/Wikidata presence, consistent NAP, third-party mentions.

Content patterns that get cited

• "What is X?" page with a 2-sentence definition first, then nuance.
• Pages titled with the actual question users ask.
• Comparison tables and pros/cons lists.
• Original data and proprietary surveys (LLMs cite primary sources).
• Author boxes with linked credentials.

Output

• Per-page rewrite plan: TL;DR block, FAQ block, schema additions.
• A list of "10 questions our ICP asks AI" → pages to create or upgrade.
• Sourcing checklist for every claim.
• Tracking plan: branded prompts vs. AI engines, monthly citation check.

Anti-patterns

• Long, meandering intros that bury the answer.
• Unsourced numbers.
• Stuffing keywords; LLMs reward semantics, not density. Adapted from coreyhaines31/marketingskills (MIT).