Welcome to the final and most advanced lesson in the AWS Strands course! Here, you'll move beyond single agents and explore powerful patterns for building complex systems where multiple agents collaborate to achieve a goal.

🎯 Learning Objectives

By the end of this lesson, you will be able to:

Design and implement hierarchical agent systems with clear delegation patterns
Build dynamic, self-organizing agent swarms for complex problem-solving
Create structured, predictable workflows using graph-based patterns
Choose the right multi-agent pattern for different use cases
Understand the trade-offs between different multi-agent approaches

🏗️ Multi-Agent Patterns Overview

Strands provides high-level abstractions for orchestrating multi-agent workflows. We'll cover four key patterns, each with distinct advantages:

1. Agent as Tools 🛠️

A hierarchical pattern where a "manager" agent delegates tasks to specialized "worker" agents.

Best for: Clear task decomposition, centralized control
Use cases: Customer service, content creation, research workflows
Advantages: Predictable, easy to debug, clear responsibility boundaries

2. Swarm Intelligence 🐝

A dynamic and decentralized pattern where agents can intelligently hand off tasks to each other.

Best for: Open-ended problems, creative tasks, exploration
Use cases: Software development, research, creative writing
Advantages: Flexible, emergent behavior, self-organizing

3. Graph-Based Workflows 📊

A structured pattern where you define a predictable, directed workflow for your agents.

Best for: Production systems, repeatable processes, compliance
Use cases: Data pipelines, approval workflows, quality assurance
Advantages: Reliable, auditable, parallel execution

4. Workflow Agent 🔄

The most advanced pattern combining stateful workflows with conditional logic.

Best for: Complex business processes, adaptive systems
Use cases: Customer onboarding, dynamic content generation
Advantages: Stateful, conditional, highly flexible

📚 Sub-Lessons

This lesson is divided into the following parts:

Sub-Lesson	Topic	Description	Complexity	Use Case
6.1	Agent as Tools	Build an orchestrator agent that delegates tasks to specialized agents	⭐⭐	Customer service, content creation
6.2	Swarm Intelligence	Create a dynamic group of agents that can hand off tasks to each other	⭐⭐⭐	Software development, research
6.3	Graph-Based Workflows	Define explicit, structured workflows for multi-agent collaboration	⭐⭐⭐	Data pipelines, approval workflows
6.4	Workflow Agent	Build complex, stateful workflows with conditional logic	⭐⭐⭐⭐	Business processes, adaptive systems

🚀 Quick Start

Each sub-lesson includes:

Complete code examples with detailed explanations
Real-world use cases and scenarios
Configuration options and best practices
Troubleshooting guides and common pitfalls

🎓 Prerequisites

Before starting this lesson, make sure you have:

Completed Lesson 5: Human-in-the-Loop
Understanding of basic agent concepts from previous lessons
Familiarity with Python and async programming
Access to a language model API (Nebius, OpenAI, etc.)

🔧 Setup Requirements

Each sub-lesson requires:

Python 3.8+ with uv package manager
Environment variables configured (see individual READMEs)
Required dependencies installed via uv sync

📖 Further Learning

Watch the Video: AWS Strands Course Playlist
Read the Docs: Official Strands Documentation

Previous Lesson	Next Lesson
Lesson 5: Human-in-the-Loop	Sub-Lesson 6.1: Agent as Tools

README.md

Lesson 6: Advanced Multi-Agent Patterns