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Memory Systems for Long-Running Agents: Episodic to Procedural

A new approach to memory systems for long-running AI agents transitions from episodic to procedural memory, enabling agents to accumulate knowledge and skills over days. This advancement addresses the limitations of flat context windows in single-session chatbots, improving agent performance in extended tasks.

read1 min views32 publishedJun 19, 2026

A single-session chatbot can get away with a flat context window. A long-running agent — one that works across days, accumulates tool… Continue reading on Towards AI »

source & further reading
pub.towardsai.net — original article Why Autonomous SRE Agents Default to Root: The AST Mechanics of Agentic IAM Escalation OpenAI Agents API Sandbox Boundaries: Ship Long-Running Agents Without Shipping Your Secrets The Three Levers That Get AI Architecture Approved
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