chunking strategies

Modern generative AI systems often appear to “read” entire documents instantly, returning precide answers form long PDFs or dense technical manuals. In reality, large language models do not consume documents holistically. Instead, they rely on carefully prepared context that is retrieved and supplied at query time. One  of the most critical and often misunderstood mechanisms behind this process is content chunking. At its core, content chunking determines how raw documents such as PDFs, webpages, or text files are transformed into smaller, meaningful units that can be indexed, embedded, and retrieved efficiently. Understanding how chunking works and how to configure it [...]