Developer’s guide to multi-agent patterns in ADK- Google Developers Blog

If you’ve ever tried to build a single AI agent that does everything, you already know how this story ends. It starts confident. Then it gets messy. Rules blur, edge cases pile up, and debugging feels like pulling on one loose thread only to unravel the whole sweater.

That tension is exactly what the Google Developers Blog explores in **“Developer’s guide to multi-agent patterns in ADK”**, a thoughtful walkthrough of how *teams of agents* outperform lone, overworked ones. The full article lives here, and it’s worth bookmarking if you build serious AI systems: https://developers.googleblog.com/developers-guide-to-multi-agent-patterns-in-adk/.

Rather than treating an AI agent like a magical all-knowing brain, the post reframes it as something more familiar… a software system. One with roles, boundaries, and clear responsibilities. The article introduces **eight multi-agent design patterns** using Google’s Agent Development Kit (ADK), each pattern solving a different real-world problem.

There’s the *Sequential Pipeline*, which feels like an assembly line you can actually debug. Parser hands off to Extractor, Extractor hands off to Summarizer. Clean. Predictable. Then there’s the *Dispatcher pattern*, where a coordinator routes tasks to specialists, much like customer support sending you to billing instead of tech support (we’ve all been there).

Speed gets its own moment too. With *Parallel agents*, multiple specialists work at the same time, then a synthesizer pulls everything together. Think code reviews where security, style, and performance checks run simultaneously instead of waiting in line.

What stands out is how practical this guide feels. It doesn’t pretend agents are perfect. It openly designs for critique loops, refinement cycles, and even *human-in-the-loop* approvals when stakes are high. That balance between automation and control feels… honest.

The takeaway is optimistic. As agent systems grow more capable, the future isn’t one giant brain. It’s *well-coordinated teams*. Smaller, smarter, and easier to trust. And honestly, that sounds a lot like how good software has always been built.