Managing Agents that Manage Agents: Workshop on Responsible Use of Meta-Agents that Build, Optimize, and Supervise Other Agents

Agents now write their own harness and shape their own training. How do we advance these capabilities while ensuring responsible deployment? We define these higher-order systems that build, optimize, and supervise other agents as meta-agents. While meta-agents will likely play an increasingly central role in the future of AI, research remains dispersed across disparate communities. This workshop provides a dedicated venue to address both the technical and societal challenges of this emerging field. Technically, the transition to automated agent design requires new optimization methods, learning signals, and meta-level benchmarks to ensure these systems can safely generalize and improve. Societally, as meta-agents take on the manager roles (i.e. optimizing prompts and assigning tasks to downstream worker agents), they require strict governance. A misaligned objective can propagate to every sub-agent, and the potential for agents to manage human labor raises urgent questions about human autonomy. By spanning the full meta-agent lifecycle, from automated design and open-ended evolution to verifiable halt controls and human oversight, this workshop brings together researchers in AI and organizational science* to ensure these systems are developed and deployed responsibly.