How to Structure a Site for Both Google and AI Search

Every few months, SEO gets another acronym. GEO. AEO. LLMO.

The names keep changing, but the fundamentals rarely do.

Many businesses are looking for a shortcut that makes ChatGPT, Google AI Overviews, Gemini, Claude, or Perplexity mention their website more often. In reality, these systems reward something far less exciting: websites that are easier to understand.

A lot of noise exists right now around AI search. Everyone is testing, sharing screenshots, and publishing theories. The only way to know what works for your business is to implement changes, measure the results, and repeat what actually moves the needle.

The four engines don’t work the same way

Treating “AI search” as one target is the first mistake. Each engine retrieves and prioritizes information differently.

• ChatGPT uses its own search index and frequently references well-established community sources such as Wikipedia and Reddit.
• Gemini and Google AI Overviews rely on Google’s search index while also surfacing content from products like YouTube and other trusted sources within Google’s ecosystem.
• Claude searches through Brave Search and often favors well-structured, long-form content from identifiable authors and publishers.
• Perplexity combines its own retrieval system with citations from authoritative publications, research papers, documentation, and data-rich content.

The exact weighting changes over time. The takeaway doesn’t: there is no single “AI algorithm” to optimize for.

Build a site that is easy for any search or retrieval system to understand instead of chasing the behavior of one platform.

One practical example is Reddit. If questions from your industry repeatedly appear there, they become an excellent content roadmap. Instead of guessing what customers want to know, answer the questions they are already asking.

Schema and FAQs remove ambiguity

Structured data helps search systems understand what they’re reading. Organization schema identifies your business, and article schema identifies your content. Product, FAQ, Review, Breadcrumb, and other schema types explain how different pieces of your site relate to each other.

Schema doesn’t make weak content trustworthy. It simply removes ambiguity.

FAQ sections follow the same principle.

Don’t write generic questions like “Why choose us?” or “What services do you offer?” Answer the questions that stop customers from buying. Use the questions people ask in sales calls, support tickets, Reddit discussions, community forums, and product reviews. Those questions already represent real search intent.

Internal linking creates context

Internal links do far more than help visitors navigate your website. They explain how your pages relate to one another.

• A comparison page should naturally link to the products being compared.
• A buying guide should lead users toward relevant categories or services.
• Documentation should connect to implementation guides.
• Case studies should reinforce the services that delivered those results.

Publishing great content without connecting it properly forces search systems to guess how your expertise is organized. The clearer those relationships become, the easier it is for both traditional search and AI-driven retrieval systems to understand your website.

llms.txt, briefly

I covered this in detail in a previous issue LLM.txt File Is Spreading Across the Web, including why adoption sits under 10 percent and why the major crawlers rarely request it.

If creating an llms.txt file takes ten minutes, ship it. Just don’t expect it to solve structural problems: it won’t replace schema, fix poor internal linking, or make weak content more relevant. Think of it as a supporting document, not a strategy.

Crawl budget looks different by site type

Robots.txt and crawl budget are not one-size-fits-all rules. A few examples:

• Ecommerce customer review pages. Pagination, sorting options, and filters can generate thousands of near-identical URLs. Decide which versions deserve crawling and block or canonicalize the rest, so search engines spend time on your real product pages instead of duplicate variations.
• SaaS comparison pages. “X vs Y” pages directly match commercial search intent. If those pages are buried several clicks deep or accidentally set to noindex, you’re hiding exactly the content buyers and AI search systems look for.
• Bot-specific rules still matter. Training crawlers and citation crawlers are different bots. Decide intentionally which ones can access your content instead of blocking everything by default.

Implement it, don’t just read about it

The conversation around GEO and AEO will continue to evolve. Waiting for a perfect playbook means waiting forever. Start with something measurable:

• Improve your schema.
• Rewrite your FAQs around real customer questions.
• Audit your internal linking.
• Review your robots.txt rules.

Strengthen the pages that generate revenue before publishing another generic blog post.

Further reading

• Five Answer Engines in 2026 (Everything-PR): https://everything-pr.com/the-five-answer-engines-2026-chatgpt-claude-gemini-perplexity-google-ai-overviews-compared
• Complete Guide to AI Search Engines (GEOScore): https://geoscoreai.com/blog/ai-search-engines-guide
• Which Search Engine Does AI Use (Hitit Medya): https://www.hititmedya.com/blog/which-search-engine-does-ai-use