--- Summary:
- The paper argues that context engineering—structuring external knowledge, memory, and tools—has surpassed model fine-tuning as the primary challenge for building trustworthy generative AI systems.
- It proposes a Unix-inspired file-system abstraction where “everything is context,” providing a persistent, governed infrastructure for managing heterogeneous AI artefacts through uniform mounting and metadata.
- Implemented within the AIGNE framework, the architecture features a verifiable pipeline consisting of a Context Constructor, Loader, and Evaluator to assemble and validate context under token constraints.
- This approach addresses the fragmentation of current practices like RAG and prompt engineering, which often produce transient artefacts that limit system traceability and long-term accountability.
- The framework redefines the human role as central curators and verifiers, establishing a reusable foundation for accountable AI co-work between humans and autonomous decision-support agents.
- Practical utility is demonstrated through two exemplars: a memory-capable agent and an MCP-based GitHub assistant, proving the architecture’s readiness for industrial and developer environments.
--- Full Article:
[2512.05470] Everything is Context: Agentic File System Abstraction for Context Engineering
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arXiv:2512.05470 (cs)
[Submitted on 5 Dec 2025]
Title:Everything is Context: Agentic File System Abstraction for Context Engineering
Authors:Xiwei Xu, Robert Mao, Quan Bai, Xuewu Gu, Yechao Li, Liming Zhu
View a PDF of the paper titled Everything is Context: Agentic File System Abstraction for Context Engineering, by Xiwei Xu and 5 other authors
Abstract:Generative AI (GenAI) has reshaped software system design by introducing foundation models as pre-trained subsystems that redefine architectures and operations. The emerging challenge is no longer model fine-tuning but context engineering-how systems capture, structure, and govern external knowledge, memory, tools, and human input to enable trustworthy reasoning. Existing practices such as prompt engineering, retrieval-augmented generation (RAG), and tool integration remain fragmented, producing transient artefacts that limit traceability and accountability. This paper proposes a file-system abstraction for context engineering, inspired by the Unix notion that ‘everything is a file’. The abstraction offers a persistent, governed infrastructure for managing heterogeneous context artefacts through uniform mounting, metadata, and access control. Implemented within the open-source AIGNE framework, the architecture realises a verifiable context-engineering pipeline, comprising the Context Constructor, Loader, and Evaluator, that assembles, delivers, and validates context under token constraints. As GenAI becomes an active collaborator in decision support, humans play a central role as curators, verifiers, and co-reasoners. The proposed architecture establishes a reusable foundation for accountable and human-centred AI co-work, demonstrated through two exemplars: an agent with memory and an MCP-based GitHub assistant. The implementation within the AIGNE framework demonstrates how the architecture can be operationalised in developer and industrial settings, supporting verifiable, maintainable, and industry-ready GenAI systems.
Comments:Submitted Subjects:Software Engineering (cs.SE) Cite as:arXiv:2512.05470 [cs.SE] (or arXiv:2512.05470v1 [cs.SE] for this version) https://doi.org/10.48550/arXiv.2512.05470
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From: Xiwei Xu [view email]
[v1] Fri, 5 Dec 2025 06:56:45 UTC (290 KB)
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View a PDF of the paper titled Everything is Context: Agentic File System Abstraction for Context Engineering, by Xiwei Xu and 5 other authors
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