How agents can delegate better

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In any organizational behavior class, students will learn that effective delegation is among the most important skills for a seasoned leader. Getting meaningful work done involves careful coordination, starting with a subdivision of projects into manageable tasks, mapped onto the skills of the team, and assigned to the right people. At Google Cloud, we’re learning a similar lesson when it comes to building and deploying AI agents in enterprise workflows. These workflows are best approached by multi-agent systems that can break apart and execute complex tasks. To do so, AI agents need to become good delegators.  To learn how, we turned to research from Google DeepMind. In their recent study titled Intelligent AI Delegation, they prove how delegation itself involves intelligence: adaptive negotiations, aligning on formal contracts, and security guardrails.  This work opens up new opportunities for customers building AI agents that can communicate, share tasks, and coordinate towards set objectives. Today, we’ll share four principles that emerged from that work, and how you might apply them to your own workflows.  Principle 1: Verify delegated work  According to Nenad Tomasev, Research Scientist at Google DeepMind, “If we are to permit AI to delegate tasks, we want it to do more than arbitrarily assign work. Agents should intelligently break down work into tasks that can be reliably verified. In our research, we call this ‘contract-first decomposition’”  Like human delegation, this takes thoughtful deliberation. With people, this might mean a leader understanding their team’s …

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