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The article identifies four key flaws in current AI agent memory systems—brittleness, lack of temporal reasoning, forgetting dilemma, and evaluation gap—and presents a novel memory architecture inspired by code agents, achieving high benchmark scores while emphasizing context learning as the next challenge.