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Agentic Orchestration Pattern

A sophisticated pattern where multiple AI agents work together in a coordinated manner, each with specialized capabilities and tools. Agents can communicate, delegate tasks, and combine their outputs to solve complex multi-step problems that require different types of reasoning or access to various systems.

When to Use

Use this pattern for complex workflows that require multiple specialized skills, when tasks need to be broken down into subtasks handled by different agents, or when you need agents that can use tools, make decisions, and adapt their approach based on intermediate results. Ideal for business process automation, complex research tasks, and multi-domain problem solving.

Architecture Drawing

The architecture depicts a central orchestrator managing multiple specialized agents, each with access to specific tools and services, with a shared memory system for context and coordination.

Components: - User Interface (100, 50) - Orchestrator Agent (300, 100) - Planning Agent (150, 200) - Research Agent (300, 200) - Analysis Agent (450, 200) - Action Agent (600, 200) - Shared Memory Store (300, 300) - Tool Registry (500, 100) - External APIs (650, 100)

Edges: - User Interface → Orchestrator Agent: "Task Request" - Orchestrator Agent → Planning Agent: "Decompose Task" - Orchestrator Agent → Research Agent: "Gather Information" - Orchestrator Agent → Analysis Agent: "Process Data" - Orchestrator Agent → Action Agent: "Execute Actions" - All Agents → Shared Memory Store: "State Updates" - Shared Memory Store → All Agents: "Context Retrieval" - Action Agent → External APIs: "Tool Execution" - Tool Registry → Action Agent: "Available Tools"

MCP Integration Pattern, Multi-Agent Collaboration Pattern, Tool-Augmented LLM Pattern

References

  1. AutoGPT: An Autonomous GPT-4 Experiment - 2023 - GitHub - Open-source implementation demonstrating autonomous agent capabilities and task decomposition
  2. ReAct: Synergizing Reasoning and Acting in Language Models - 2022 - arXiv - Framework for combining reasoning and acting in language models through structured prompting
  3. Multi-Agent Programming with ChatGPT - 2023 - arXiv - Exploration of multi-agent systems using large language models for collaborative problem solving