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Hub-and-spoke SEO architecture: keyword research, content templates, schema markup, technical SEO, internal linking, indexing, and rankings
Hub-and-spoke architecture for programmatic SEO at scale.

Frequently Asked Questions

Do AI search engines crawl static sites differently than dynamic sites?

Yes. AI crawlers use shorter timeouts and prioritize content available in initial HTML responses. Static sites that respond in 100-300ms with full HTML are crawled and indexed reliably. Dynamic sites with slow server-side rendering or heavy client-side JavaScript often fail to complete crawls or deliver empty content.

What is llms.txt?

llms.txt is an emerging convention where sites publish a markdown file at the root of their domain (like /llms.txt) listing the most important content for AI crawlers. It is similar in spirit to robots.txt but focused on guiding LLM crawlers to high-quality content. Static sites can ship llms.txt as a file with no plugin or framework friction.

Should I unblock AI crawlers in robots.txt?

Yes, if you want to appear in AI search results. Blocking PerplexityBot, ChatGPT-User, Claude-Web, GPTBot, or similar crawlers makes your site invisible to those AI engines. The trade-off is bandwidth: AI crawlers can be aggressive. For most marketing sites, the visibility benefit outweighs the bandwidth cost.

Does schema markup help with AI search?

Yes. Schema markup gives AI parsers structured signals about page content. FAQ schema, Article schema, HowTo schema, and Organization schema all help AI engines extract and cite content. Static sites can include schema in templates, ensuring every page ships with the correct structured data without plugin overhead.

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