6 Core Patterns of AI Agent Orchestration ! Not all AI agents work the same way. The magic lies in how they are orchestrated. If you're building advanced agent workflows or AI copilots, understanding these orchestration patterns is essential. Here's a breakdown of the six most powerful structures: 1. Chaining Each agent passes its output to the next. Ideal for linear, multi-step tasks like research → drafting → proofreading. 2. Parallel Multiple agents run at once. Speeds up processing—great for generating reports, analysis, or summaries from different sources in real time. 3. Routing A central agent assigns tasks to specialist agents based on type—just like a smart triage system. 4. Iteration Repeats the same task until a condition is satisfied. Perfect for planning loops, optimizations, or multi-round reasoning. 5. Looping If the output isn’t right, the agent re-queries or re-generates. Ideal for Q&A bots, assistants, or agents refining search results. 6. Hierarchy Supervisor agents assign and review work. Used in multi-role agents like coding copilots, where engineers and retrievers collaborate under oversight. Save this framework before building your next AI Agent. [Explore More In The Post] I help companies go from clunky operations to lean, high-output systems with AI agents, automations, and chatbots. Want 20+ hours back per week? Or 5–6 figures in added pipeline? That’s what we deliver—in 30 days. 👉 Book before my calendar closes: https://lnkd.in/dU3iSs7u Be honest—are you using AI to save time, or still stuck in busywork? | 34 comments on LinkedIn