Build Multi-Agent Systems with ADK
Go beyond simple chatbots and build a distributed multi-agent system!
Track Overview
We're thrilled to launch our second DEV Education track in partnership with the team at Google AI. This track will guide you through building distributed multi-agent systems using Google's Agent Development Kit (ADK), Agent2Agent Protocol (A2A), and Cloud Run. You'll learn to architect AI applications as coordinated teams of specialized agents rather than relying on a single monolithic prompt.
What You'll Learn
Multi-agent systems are one of the most important architectural patterns in production AI development. Just as you wouldn't ask a single developer to handle frontend, backend, database, and DevOps all at once, modern AI systems benefit from specialization. You'll learn to create focused agents and coordinate them to solve complex problems that would otherwise overwhelm a single prompt.
How to Complete This Track
This DEV Education Track is a three-part experience: 1) an expert tutorial followed by 2) a hands-on build and 3) a writing assignment.
Work through all three parts and you'll earn the exclusive Multi-Agent Systems Builder badge!
Track Details
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Multi-Agent Systems Builder
Complete the track to earn this badge
Learn More
Get additional details and ask questions about the Build Multi-Agent Systems with ADK learning track.
View AnnouncementLearning Partner: Google AI
Google AI is at the forefront of artificial intelligence research and development, creating tools and technologies that democratize AI for developers worldwide. Through various AI developer tools such as Gemini CLI, Google AI Studio, Antigravity, ADK, and more, they're making it easier than ever to build intelligent applications.
Learning Curriculum
Follow this structured learning path to master the skills
📖 Part 1: Follow the Expert Tutorial
Work through the comprehensive Google codelab that guides you step-by-step through building a production-ready, distributed multi-agent system.
Learning Objectives
- Understand why specialized agents are more effective than monolithic prompts
- Learn the architecture of distributed multi-agent systems
- Master orchestration patterns
- Implement the Agent-to-Agent (A2A) protocol for distributed communication
Getting Started
Begin by working through the expert tutorial created by the Google AI team. This codelab will walk you through every step of the process, from initial setup to final deployment.
Module Details
🤖 Part 2: Build Your Own Multi-Agent System
Apply what you've learned by building a distributed multi-agent system with a web interface that breaks a complex task into specialized roles
Learning Objectives
- Apply learned concepts to create your own multi-agent system
- Experiment with different agent architectures
- Deploy a working web application and agents to Cloud Run
Getting Started
Your assignment is to build a multi-agent system that takes a task that would normally require "one giant prompt" and breaks it into specialized roles, accessible through a web interface.
Requirements:
- Multiple specialized agents
- Each agent has a focused responsibility
- Deployed to Google Cloud Run - Agents must run as separate microservices
- Frontend application - Web interface deployed to Cloud Run that users interact with
We encourage you to come up with your own apps, but here are some ideas if you need inspiration:
App Ideas for Inspiration:
- Email Drafter: Topic agent suggests what to write → Writer agent creates draft → Editor agent polishes tone
- Gift Idea Generator: Profile analyzer understands the recipient → Idea finder suggests options → Budget filter removes expensive items
- To-Do Prioritizer: Task analyzer reviews your list → Urgency checker ranks by deadline → Focus agent picks top 3 for today
Module Details
✏️ Part 3: Earn Community Recognition
Share your multi-agent system with the DEV community and earn your exclusive Multi-Agent Systems Builder badge.
Learning Objectives
- Document distributed system architecture
- Share learnings with the community
- Contribute to the collective knowledge base
Getting Started
Use our official submission template to share your assignment and earn your badge! Your submission should include:
- What you built: Describe the problem your system solves
- Cloud Run Embed: Embed your web app directly into the submission
- Your agents: Explain each agent's specialized role and how they work together
- Key learnings: What surprised you? What was challenging?
Our team reviews submissions on a rolling basis and badges are awarded every few days. There's no deadline!
Module Details
Frequently Asked Questions
Get answers to common questions about the Build Multi-Agent Systems with ADK track
Frequently Asked Questions
Do I need prior AI/ML experience?
No! The tutorial teaches you everything you need about the Agent Development Kit (ADK). You don't need to understand machine learning internals. If you can write Python functions and understand the concept of API calls, you're ready to start..
Do I need a Google Cloud account?
Yes. You'll need a Google Cloud account to deploy your agents and frontend to Cloud Run. Google Cloud offers free credits for new users, and the services used in this tutorial typically fall within free tier limits for testing purposes.
Is the track really free?
Yes! The track is completely free.
What if I get stuck?
Join our community discussions using the #buildmultiagents tag, where you can ask questions and get help from other learners and the Google AI team.
