Scheduling Agents and Improving Memory with Dreaming

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    Video summary

    Anthropic's workshop moves from coordinating company-research sessions to scheduling recurring work. A deployment supplies an agent definition, schedule, initial messages and optional resources. Memory stores remain separate resources that a builder attaches to sessions. The live demonstration encounters failed runs, so the segment does not establish that every scheduled execution succeeds.

    The presenters preview Dreaming, which analyzes a chosen period of session transcripts and updates a memory store with lessons from repeated problems. Directly modifying skills and prompts is described as future work. They emphasize task-specific evaluation; audience questions highlight the risk that observed patterns are not sufficient evidence of improved outcomes. Dreaming is an experimental research preview, not guaranteed autonomous self-improvement.

    The Q&A distinguishes the managed tool loop from an application's broader orchestration, explains event-based observability and describes workspace separation. Fine-grained role-based access, graph-based orchestration UI and an on-premises offering are not shown as currently available. The API product supports customer-facing applications and team agents, while personal use remains a different workflow.

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    Priyanka Phatak on the left and Gabriel Cemaj on the right, neither wearing glasses, surround the blue-and-white AGENT MEMORY headline against black. Framed in blue with WWW.ARTIFICIAL-INTELLIGENCE.VIDEO, 12 October 2026 and duration 26m 31s.

    Anthropic demonstrates recurring managed-agent deployments and experimental memory improvement, then discusses observability, evaluation and access-control limits.