How Do You Know What Fan Out Queries Were Searched? James...

What this episode covers

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.Where to Listen to This EpisodeHow Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov is available across all major podcast platforms. Choose your preferred platform below.Listen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on TransistorListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on Pocket CastsListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on Amazon MusicListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on SpotifyListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on PodverseListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on Pod.linkListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on CastroListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on CastboxListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on Podcast AddictListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on DeezerListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on Listen NotesListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on Podcast GuruListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on PodchaserListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on StenoListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on MetacastListen to How Do You Know What Fan Out Queries Were Searched? James Dooley Interviews Sergey Lucktinov on Entity Home

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Frequently Asked Questions

How long is this episode of James Dooley Podcast?

This episode is 8 minutes long.

When was this James Dooley Podcast episode published?

This episode was published on June 19, 2026.

What is this episode about?

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...

Is there a transcript available for this episode?

Yes, a full transcript is available for this episode. You can read the complete transcript on the episode page.

Can I download this James Dooley Podcast episode?

Yes, you can download this episode by clicking the download button on the episode player, or subscribe to the podcast in your preferred podcast app for automatic downloads.