MemArchitect: A Policy Driven Memory Governance Layer

2026-03-18

AI Summary

Current persistent large language model agents lack effective memory governance mechanisms, rendering them vulnerable to contradictory information, privacy leaks, and outdated “zombie memories.” This work proposes MemArchitect—a memory governance layer decoupled from model weights—that introduces, for the first time, a rule-based memory lifecycle management framework. By leveraging a policy-driven rule engine, MemArchitect enables explicit control over memory decay, conflict resolution, and privacy preservation. Experimental results demonstrate that memories governed by MemArchitect significantly outperform unmanaged baselines in agent tasks, underscoring the critical role of structured memory governance in enhancing the reliability and safety of autonomous systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Agent/AI Theories and Architectures
• Machine Learning: Deep Neural Architectures and Foundation Models

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Persistent Large Language Model (LLM) agents expose a critical governance gap in memory management. Standard Retrieval-Augmented Generation (RAG) frameworks treat memory as passive storage, lacking mechanisms to resolve contradictions, enforce privacy, or prevent outdated information ("zombie memories") from contaminating the context window. We introduce MemArchitect, a governance layer that decouples memory lifecycle management from model weights. MemArchitect enforces explicit, rule-based policies, including memory decay, conflict resolution, and privacy controls. We demonstrate that governed memory consistently outperforms unmanaged memory in agentic settings, highlighting the necessity of structured memory governance for reliable and safe autonomous systems.

Problem

• memory governance
• LLM agents
• zombie memories
• privacy control
• memory contradiction

Innovation

• memory governance
• policy-driven memory
• LLM agents
• zombie memories
• conflict resolution