Multi-Agent Systems
The Power of the Swarm

Stop trying to make one model do everything. Learn how to orchestrate specialized agents to solve complex problems together.

Why build a team?

Just as you wouldn't hire one person to be CEO, Engineer, and Marketer, AI works better when roles are specialized.

Specialization

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Expertise

Assigning specific roles (e.g., "Python Coder", "Legal Analyst") creates narrower context windows and fewer hallucinations.

Collaboration

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Handoffs

Agents pass tasks to each other. A "Researcher" finds facts, passes them to a "Writer" to draft, who passes to an "Editor" to refine.

Manager Agent

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The Orchestrator

A central agent that breaks down user requests and delegates sub-tasks to the correct worker agents.

Dialogue

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Iterative Refinement

Agents can "chat" with each other to critique and improve work before showing it to the human.

Interactive: Hierarchical Team

See how a Manager Agent delegates a task to create a blog post about "SpaceX".

Manager
Researcher
Writer
Editor
Click the Manager to start the workflow...

Orchestration View

Follow the delegation process. The Manager receives a goal and breaks it down for the workers.

Team Architectures

The Assembly Line

One agent finishes, passes output to the next.

Input
Agent A
Agent B
Output

Best for: Clearly defined workflows like "Research -> Write -> Translate".

Knowledge Check

Test your Orchestration skills.

1. Why use multiple agents instead of one big prompt?

2. In a Hierarchical architecture, what is the role of the Manager?

3. Which pattern describes agents passing work in a straight line?