Agent Memory as a File Format

Memoryfields propose a simpler file-based approach to agent memory using markdown files with optional vector indexing, rather than treating memory as a complex multi-stage process. Existing agent memory systems fail because they are either vendor-locked platforms, overly complicated with multiple databases, or strip context from information through graph-based abstraction. The author argues memory should be represented as portable data files rather than pipelines, allowing AI agents to start with relevant contextual information instead of blank slates.