Shared Organizational Memory for Enterprise Coding Agents: System Design and Deployment Snapshot

Abstract:Enterprise coding agents rely on tools and retrieval, yet enterprise knowledge often remains outside public training data and formal documentation: internal DSLs, proprietary platforms, local conventions, recent fixes, and tacit workflows. Existing knowledge interfaces expose stored resources but still depend on agents recognizing and explicitly recording lessons worth reusing, disconnecting capture from the coding workflow and leaving development experience repeatedly rediscovered. We report an ongoing production deployment of a shared organizational memory system that makes capture a platform-level part of coding work: it collects task-adjacent experience with contributor approval, curates it into reusable question-answer memories, gates obvious security and privacy risks, and retrieves memories for future agents. This short paper describes the deployed lifecycle and an operational snapshot. Effects on retrieval and coding tasks remain under evaluation.

Artificial Intelligence (cs.AI)

arXiv:2608.00122 [cs.AI]

(or arXiv:2608.00122v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2608.00122 Focus to learn more arXiv-issued DOI via DataCite

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