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AI Query Fanning Framework
The process by which AI search engines expand a single user query into 100+ related queries, search each individually, then aggregate results from 1000+ pages to answer the original question.
How It Works
AI takes user input, creates derivative queries from multiple angles, searches traditional search engines for each variation, scrapes ranking pages, puts content into context window, then synthesizes a response.
Components
User submits initial query
AI expands into 100+ derivative queries
Each query searches Google/Bing individually
AI scrapes content from ranking pages
Content goes into context window
AI synthesizes response from aggregated data
When to Use
When trying to understand how AI search engines work and how to position content to be discovered by them.
When Not to Use
When dealing with simple, direct queries that don't require research or comparison.
Anti-Patterns to Avoid
Example
“User searches 'best funnel building software for mobile' → AI creates 100 related queries like 'mobile-optimized funnel builders 2025', 'funnel software mobile compatibility comparison' → searches each → scrapes 1000 pages → synthesizes answer mentioning top brands found across pages.”