Filesystem-based memory is a common yet understudied approach for LLM agents, where memory is stored as a directory of markdown files. This method allows agents to manage memory through generic file operations, but its scalability and organizational efficiency remain unverified. Current research focuses on custom memory systems rather than analyzing the default filesystem model. Key assumptions about memory growth and reorganization require further empirical validation.