Long-Context Processing

Long-context processing deals with feeding an AI model large amounts of text, such as entire codebases, long documents, or extended conversation histories, in a way that keeps the model accurate. Even when a model's context window is technically large enough, performance can degrade as the amount of content grows, a problem often called context rot. Techniques to manage this include chunking content, retrieving only the most relevant sections, and summarizing older material instead of passing it in full.