Site Architecture for AI

How your content is organized affects how large language models interpret, retrieve, and reuse it. Unlike traditional SEO, where internal linking and siloing are about spreading PageRank or boosting crawl efficiency, AI SEO is about semantic clarity. The cleaner and more modular your architecture, the easier it is for LLMs to match your page to a specific query—and reuse your content in answers.

This section outlines how to structure your site for maximum extractability, topical authority, and citation readiness.

One Concept per URL

Why it matters:

• LLMs look for specific answers to specific questions.
• If your page covers too many topics, it’s harder to isolate one clean, quotable paragraph.

Best practices:

• Dedicate each URL to a single concept or sub-topic.

  • ✅ Good: /what-is-debt-to-income-ratio
  • ❌ Bad: /financial-terms-explained

• Match URL slugs to search intent.

  • Use plain, hyphenated, lowercase structure.
  • Avoid dates, IDs, or vague titles (/blog/1234?ref=seo)

Actionable tips:

• Break long guides into sub-pages (or anchor-linked sections if short).
• Add canonical tags for clarity across versions.
• Audit existing URLs: split or prune pages that try to do too much.

Strategic commentary:

Modular content is more likely to be embedded or retrieved by LLMs. One concept per page increases your odds of matching a specific user query, getting cited, and owning that semantic territory in AI-generated answers.

Topical Clusters and Internal Linking

Why it matters:

• LLMs and AI tools use semantic relationships between pages—not just link juice.
• Strong internal connections signal expertise and reinforce context across your site.

How to implement:

• Create topic clusters:

  • A central “pillar” page (e.g., /llm-seo-guide)
  • Supporting pages (e.g., /json-ld-schema, /robots-txt-for-llms, /prompt-testing-methods)

• Internally link downward and sideways:

  • Pillar links to all subtopics
  • Each subtopic links back to the pillar
  • Crosslink subtopics where related

• Use descriptive anchor text:

  • ✅ Good: “Learn how to set up your robots.txt for AI crawlers”
  • ❌ Bad: “Click here”

Actionable steps:

• Build out a visual map of your topical coverage.
• Run a crawl tool like Screaming Frog to analyze link depth and isolation.
• Use rel="canonical" and rel="next/prev" carefully—only for paginated series, not clusters.

Strategic commentary:

AI models favor sites that demonstrate depth within a niche. Topical clustering helps LLMs learn the edges of your expertise and associate your domain with a specific subject area.

Glossary Sections and Summary Hubs

Why it matters:

• AI tools often need quick definitions, descriptions, or terminology lookups.
• A glossary-style section increases your chances of being cited for "What is [term]?" queries.

How to structure:

• Build a dedicated /glossary or /definitions hub.
• One term per URL (e.g., /glossary/llm, /glossary/semantic-seo)

• Use consistent format:

  • Lead with a one-sentence definition
  • Add context, examples, and internal links to deeper resources

Add schema to each page:

{
  "@context": "https://schema.org",
  "@type": "DefinedTerm",
  "name": "LLM SEO",
  "description": "LLM SEO is the practice of optimizing content for visibility and citation in answers generated by large language models like ChatGPT and Claude.",
  "inDefinedTermSet": "https://example.com/glossary"
}

Actionable tips:

• Link glossary entries contextually in other articles.
• Don’t hide the glossary in footers only—make it part of your nav or sidebar.

Strategic commentary:

Glossaries and hubs create strong semantic anchors for LLMs. They help clarify terminology, encourage citation, and build semantic authority across your domain.

Navigation, Breadcrumbs, and Semantic Grouping

Why it matters:

• Clear structure helps crawlers—and language models—understand site hierarchy and topical relationships.
• Breadcrumbs reinforce contextual placement of pages.

Best practices:

• Use breadcrumb schema (BreadcrumbList) and display it on-page.

{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    {
      "@type": "ListItem",
      "position": 1,
      "name": "Home",
      "item": "https://example.com/"
    },
    {
      "@type": "ListItem",
      "position": 2,
      "name": "Glossary",
      "item": "https://example.com/glossary"
    },
    {
      "@type": "ListItem",
      "position": 3,
      "name": "LLM SEO",
      "item": "https://example.com/glossary/llm-seo"
    }
  ]
}

• Organize URLs semantically:

  • Group similar content under parent folders (/tools/, /guides/, /use-cases/)
  • Avoid flat structures with 500+ pages in /blog/

• Build a hierarchy that mirrors your expertise:

  • Top-level: general topics
  • Mid-level: specific use cases, guides
  • Bottom-level: glossary terms, tool descriptions, FAQs

Actionable steps:

• Use a site crawler to audit hierarchy depth
• Flatten deep nesting (>3 levels) unless semantically necessary
• Avoid orphan pages—link all content from nav, sidebars, or hubs

Strategic commentary:

AI doesn’t “see” your menu, but it does follow your internal architecture. Treat your sitemap like a curriculum. Each layer should reinforce your topical identity and make discovery easier—for crawlers and LLMs.

Summary:

Your content doesn’t exist in a vacuum. Site architecture tells the model what you’re about and where to find the answer. By tightening your topical focus and improving internal signals, you increase the likelihood of your content being retrieved, understood, and reused by AI.