Agents that remember

Building persistent memory for AI agents requires moving beyond isolated, ephemeral sessions toward integrated architectures. Cloud Managed Agents address this by implementing memory stores—persistent, file-system-like resources that enable agents to read and write information across multiple interactions. To prevent these stores from becoming disorganized or unbounded, the "Dreaming" feature utilizes an asynchronous, multi-agent harness to perform batch processing, fact-checking, and deduplication. This process creates an optimized index, ensuring that future agents can retrieve relevant context efficiently. By layering sessions, memory stores, and dreaming, developers can maintain manageable, up-to-date knowledge bases that significantly enhance agent performance and utility in real-world workflows. This approach transforms memory from a simple data dump into an evolving, structured resource that scales with the complexity of the tasks being performed.