Personalizing LLMs: How Your ChatGPT & Gemini Differ

What this episode covers

James Dooley speaks with Benjamin Tannenbaum from AISO about the personalisation of large language models and why identical prompts in ChatGPT, Gemini and other AI search systems can produce different answers. Benjamin Tannenbaum explains the difference between true personalisation and simple probabilistic variability, showing how response volatility often comes from token selection rather than user history. The conversation breaks down location signals, memory settings, login state, and how query fan out becomes weighted by personal attributes. They also explore why personalisation can reduce randomness by narrowing candidate sets, how share of voice replaces fixed rankings in AI visibility tracking, and why optimising for LLMs increases probability rather than guaranteeing deterministic results.Where to Listen to This EpisodePersonalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum is available across all major podcast platforms. Choose your preferred platform below.Listen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on TransistorListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on Pocket CastsListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on Amazon MusicListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on SpotifyListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on PodverseListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on Pod.linkListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on CastroListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on CastboxListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on Podcast AddictListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on DeezerListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on Listen NotesListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on Podcast GuruListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on PodchaserListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on StenoListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on MetacastListen to Personalizing LLMs: How Your ChatGPT & Gemini Differ | James Dooley x Benjamin Tannenbaum on Entity Home

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Frequently Asked Questions

How long is this episode of James Dooley Podcast?

This episode is 15 minutes long.

When was this James Dooley Podcast episode published?

This episode was published on June 19, 2026.

What is this episode about?

James Dooley speaks with Benjamin Tannenbaum from AISO about the personalisation of large language models and why identical prompts in ChatGPT, Gemini and other AI search systems can produce different answers. Benjamin Tannenbaum explains the...

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.

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