Multi-Agent Research System

Throughout this course, we’ve taken a methodical approach, meticulously drawing up blueprints. We’ve defined the core components of agentic systems, from the structured “skeletons” of Pydantic to the strategic patterns that guide their behavior. But blueprints are one thing; witnessing the system in action is another. Now, we’re moving from theory to real-world application. We’re focusing our attention on a real-world, state-of-the-art agentic system: Anthropic’s multi-agent research feature for Claude.

For those unfamiliar with it, Claude is an advanced AI assistant created by Anthropic, a leading AI safety company. What makes this particularly exciting is that Claude represents one of the most sophisticated AI systems in production today, handling millions of conversations and complex tasks. Anthropic’s multi-agent research feature takes this a step further—it’s a cutting-edge system where multiple AI agents collaborate to tackle complex research problems, much like a team of specialists working together on a challenging project.

Our goal here is simple but profound: to see how the patterns we studied are not just theory but the living, breathing heart of one of the world’s most advanced AI systems. We’ll see how they grapple with the same challenges we discussed—planning, delegation, quality control, and cost management. This isn’t just an academic exercise; it’s seeing our architectural principles deployed at a massive scale, handling real-world complexity with millions of users depending on its reliability.

Pay close attention because you’re about to see our blueprints made real in a system that’s pushing the boundaries of what’s possible with AI collaboration.

What’s the underlying pattern used by Anthropic?

When you first look at Anthropic’s research agent, it should feel incredibly familiar. In their official blog post “How we built our multi-agent research system,”https://www.anthropic.com/engineering/built-multi-agent-research-system they describe it as a “multi-agent architecture with an orchestrator-worker pattern.” This is similar to what we built, but now deployed at an industrial scale.

This is what would happen when the system executes a complex user query like: ...