Agentic Memory Systems — From Chaotic Context to Learned Control Your agent just failed a customer support escalation because it couldn't remember that this same user had already explained their billing issue twice in previous sessions. The context window filled up with tool calls and intermediate reasoning, and the critical historical context got evicted. This isn't a rare edge case—it's the default failure mode for any agent that runs longer than a single conversation turn. The 2024-era solutions of naive RAG retrieval and sliding window compression treat memory as passive storage, but production agents need something fundamentally different: the ability to decide what to remember. The research wave from early 2026 has crystallized around a compelling answer.…