What Should an Agent Forget? Separating What Is Stored from What Is Used

Researchers have proposed a framework to help persistent language agents distinguish between the information they archive and the evidence they actively use for specific tasks. This approach addresses the risk of outdated data corrupting current responses while ensuring historical context remains accessible for past inquiries. By compartmentalizing memory, developers can better manage how agents retrieve relevant facts without relying on obsolete information.