James Dooley Podcast

·E277

How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov

June 19
8 mins

Episode Description

In this episode, James Dooley is joined by Sergey Lucktinov to break down how query fan-out works inside large language models. They explain how LLMs expand a single search into multiple background queries, why intent matters more than keywords, and how platforms like Google, Gemini, ChatGPT and Perplexity analyse, filter and select sources. The discussion covers fan-out limits, trust signals, listicle inclusion, brand mentions, and how content gets extracted or ignored. This episode is essential for SEOs, marketers and founders who want to understand how LLM search really works and how to optimise content for visibility in AI-driven results.


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