Filesystem-Based Memory for LLM Agents: Organization, Evolution, and Sustainability

Deployed large language model (LLM) agents increasingly keep their long-term memory as a filesystem: a directory tree of markdown files that the agent itself reads, writes, and reorganizes through generic file tools. Yet research has largely passed over this medium: prior systems design bespoke memory representations and study retrieval over them, leaving the default's two working assumptions untested: that an agent can keep a growing memory organized as memories accumulate, conflict, and go stale, and that this organization pays. We present, to our knowledge, the first systematic exploration of filesystem-based memory for LLM agents. We formalize the setting as three roles around one memory filesystem: a management agent integrates and organizes incoming content, a search agent answers queries with cited sources, and an execution agent supplies task trajectories that are distilled into skills, unifying declarative memory and skills in the same filesystem. Across long-conversation benchmarks and embodied tasks, we vary the memory variant, the stream's scale, the harness, and the backbones of the management and search agents, tracking answer quality, cost, and the health of the memory as it grows. Organization reliably buys search economy, but not always answer quality: reorganized memories more than halve per-query search cost on the two PersonaMem tiers, where the memorized content is largest, while no memory organization leads answer quality everywhere. As a memory grows it stays useful and its structure holds, but its fit to the content erodes in the well-organized memories that keep adding files. Capability matters in the agent that reads on conversation and, as a step at the top tier, in the agent that writes in the embodied setting, and two other model families also show no universally best organization while changing its form and its benefits. The harness alone reshapes the memory as strongly as the model. The study turns the filesystem default from an assumption into a design space for agent memory.