A writer experimented with using LLMs to generate personalized book recommendations by having detailed conversations about literary preferences, rather than relying on search history alone. The approach showed promising results and led to a prototype app that stores user preference profiles locally and uses conversational analysis to build evolving recommendation models, potentially offering privacy benefits over traditional recommendation systems.