Everything Is Context: Agentic File System Abstraction for Context Engineering (arxiv.org)

A recent paper introduces a novel file-system abstraction aimed at enhancing context engineering in generative AI (GenAI). As AI systems increasingly rely on external knowledge and human input for reasoning, the need for effective context management has become critical. The proposed architecture, inspired by the Unix principle that "everything is a file," offers a structured and persistent way to handle diverse context artifacts through consistent metadata, access controls, and mounting techniques. This approach intends to overcome the limitations of current practices like prompt engineering and retrieval-augmented generation, which often result in short-lived and untraceable outputs. Implemented within the open-source AIGNE framework, the architecture features components such as a Context Constructor, Loader, and Evaluator, which collectively create a verifiable context-engineering pipeline. This design empowers developers to maintain accountable and collaborative AI systems, ensuring that human operators can serve as curators and verifiers in decision-making processes. Illustrations of this new architecture include an agent equipped with memory and a GitHub assistant, both of which showcase the system’s potential for real-world applications. This innovative approach not only signifies a shift in how AI systems are developed and managed but also lays the groundwork for more reliable and human-centered AI interactions.