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  "text": "New research on scaling agent memory for long-horizon tasks.\n\nOne of the biggest challenges with AI agents is memory.\n\nAs tasks get longer and more complex, agents lose track of what they've learned, what they've tried, and what worked.\n\nThis paper, from Accenture, introduces Memex(RL), a system that gives agents indexed experience memory. Instead of relying on raw context windows, agents build a structured, searchable index of past experiences and retrieve relevant memories as needed.\n\nLong-horizon agent tasks like deep research, multi-step coding, and complex planning all require persistent memory.\n\nMemex(RL) shows how to scale this without blowing up context length.\n\nPaper: https://t.co/TWMF5HC6Qe\n\nLearn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX",
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