In this episode, James Dooley speaks with Dan Petrovic about the evolution of AI SEO and how large language models are transforming search behaviour. They break down retrieval augmented generation, query fan out, selection rate optimisation and the importance of understanding model psychology. Dan explains how LLMs interpret and trim content, why traditional SEO foundations still underpin AI results, and how brands can test and strengthen their relevance within AI driven search environments. The discussion also covers probabilistic thinking, entropy, and practical ways to influence both grounded responses and long term model perception.Where to Listen to This EpisodeHow AI Models Really Choose Content in Search is available across all major podcast platforms. Choose your preferred platform below.Listen to How AI Models Really Choose Content in Search on TransistorListen to How AI Models Really Choose Content in Search on Pocket CastsListen to How AI Models Really Choose Content in Search on Amazon MusicListen to How AI Models Really Choose Content in Search on AudibleListen to How AI Models Really Choose Content in Search on CastroListen to How AI Models Really Choose Content in Search on CastboxListen to How AI Models Really Choose Content in Search on Podcast AddictListen to How AI Models Really Choose Content in Search on DeezerListen to How AI Models Really Choose Content in Search on RephonicListen to How AI Models Really Choose Content in Search on MetacastListen to How AI Models Really Choose Content in Search on Player FMListen to How AI Models Really Choose Content in Search on SpotifyListen to How AI Models Really Choose Content in Search on Listen NotesListen to How AI Models Really Choose Content in Search on Podcast GuruListen to How AI Models Really Choose Content in Search on PodchaserListen to How AI Models Really Choose Content in Search on Podverse