Reading across books with Claude Code (pieterma.es)

A recent exploration using Claude Code has revealed innovative ways to leverage large language models (LLMs) for deeper reading experiences rather than mere summarization. By connecting excerpts from a curated library of 100 non-fiction books, Claude identified thematic trails that link concepts such as deception in startups to the social dynamics of mass movements. This method allows users to explore literature through an intelligent interface, navigating complex ideas across diverse topics with ease. The significance of this advancement lies in its potential to enhance the research process and scholarly engagement, revealing connections that may not be immediately apparent. Key technical details include the indexing of book passages into a hierarchical topic tree, facilitating efficient searches while accommodating over 100,000 extracted topics. Claude generates insights by proposing novel trails and refining them through iterative exploration, demonstrating the LLM's capacity to function as a creative collaborator. This methodology not only streamlined the task of uncovering relevant content but also widened the exploration spectrum, shifting the focus from sheer output to qualitative novelty in understanding intricate ideas within the literature.