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New 'Memoryfields' proposal reimagines AI agent memory as a plain file format

A developer critiques current AI agent memory systems, arguing most are either locked to a specific vendor's harness, overly complex (requiring vector databases, graph databases and extra LLM calls), or overly abstracted into disconnected fact lists. As an alternative, they propose 'Memoryfields', a much simpler approach that stores agent memory as a straightforward file format rather than a complicated database architecture.