Task Decomposition and Orchestration: Build Agent Workflows

Learn to build sophisticated multi-agent systems with orchestration patterns for sequential, parallel, and hierarchical task execution

Task Decomposition and Orchestration

What You'll Build

By the end of this course, you'll create a sophisticated 4+ agent orchestration system that coordinates specialized agents to complete complex tasks through sequential, parallel, and hierarchical execution patterns. This system will demonstrate how proper orchestration enables workflows to complete 5× faster than single-agent approaches while maintaining accuracy and reliability.

Course Value Proposition: Master the art of coordinating multiple AI agents to tackle complex problems through intelligent task decomposition, parallel execution, and hierarchical orchestration strategies that dramatically accelerate workflow completion times.

Prerequisites Required: This is an intermediate course that builds on foundational concepts. You must complete T4.1 Agent Communication Patterns before starting this course. Familiarity with Python, async programming, and basic LLM API usage is essential.

Learning Journey

This course teaches you to design and implement multi-agent orchestration systems through three core competencies. First, understanding orchestration patterns including sequential chains for dependent tasks, parallel execution for independent operations, and hierarchical coordination for complex delegation. Second, building practical multi-agent systems with specialized agent roles, inter-agent communication protocols, and robust error handling mechanisms. Third, implementing coordination strategies that manage task dependencies, optimize execution order, and aggregate results from multiple agents into coherent outputs.

Course Chapters

Why Orchestration Matters

Single agents struggle with complex tasks that require multiple specialized skills, diverse knowledge domains, and coordinated execution strategies. Task decomposition allows breaking large problems into manageable subtasks that specialized agents can handle efficiently. Orchestration patterns enable parallel processing of independent subtasks, reducing total execution time from hours to minutes. Hierarchical coordination provides natural division of labor where coordinator agents delegate to specialist workers, creating scalable systems that maintain coherence while leveraging distributed expertise.

What You'll Master

This course covers three critical orchestration architectures. Sequential orchestration chains agents where each step depends on previous outputs, ideal for linear workflows like research pipelines or content generation processes. Parallel orchestration executes independent tasks simultaneously, dramatically accelerating operations like multi-source data collection or comparative analysis. Hierarchical orchestration implements manager-worker patterns where coordinator agents plan tasks and delegate to specialized executors, enabling complex projects like full-stack development or comprehensive market analysis.

Real-World Impact: Students completing this course report 5-10× faster completion times for complex tasks, 70% reduction in manual coordination overhead, and ability to tackle previously infeasible multi-step automation projects.

Ready to Begin?

Start with the Quick Start chapter to build your first orchestrated workflow in 15 minutes, then progress through the Core Build for comprehensive system development. Domain-specific chapters provide proven templates for economics, software engineering, and business applications.