Filesystem as Memory: Paper Proposes Agent Architecture Halving Retrieval Costs
BLUECOW009 · x · 2026-08-09
A computer science paper formalizes filesystem-based memory as the long-term storage architecture for autonomous AI agents.
- Core Mechanism: A management agent organizes incoming experiences into hierarchical Markdown files, a search agent retrieves paths with citations, and an execution agent distills trajectories into skills.
- Advantages: Compared to opaque vector stores or flat database logs, this approach turns the local file system into a structured, inspectable memory store, roughly halving retrieval costs on large context stores.
- Key Insight: Tool harnesses reshape memory organization as strongly as swapping the underlying LLM.
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