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Foundations of Multi-Agent Systems

From Single Agents to Systems

Core Coordination Patterns

🎮 Crossword: Multi-Agent Terminology

Designing a Lead Intake Workflow

Mapping the Agent Roles

Defining Handoffs and Context

Building and Safeguarding the System

Connecting the Workflow

Human-in-the-Loop and Guardrails

Monitoring and Scaling

Quiz

Quiz: Multi-Agent Foundations

Quiz: Coordination Patterns

Quiz: Workflow Design

Quiz: Implementation Basics

Quiz: Safety and Monitoring

Course Feedback

Course Survey

Architecting Multi-Agent Systems for Coordinated AI Workflows is a practical, end-to-end course that teaches you how to design, connect, and safeguard AI agents to work together as a reliable, production-ready system. If you’ve moved beyond single chatbots and task bots—and now need orchestrated agents that research, route, collaborate, and execute with traceability—this course is your blueprint. You’ll start by grounding your understanding in the fundamentals of multi-agent systems and the coordination patterns that underpin them: chaining, routing, and collaboration. Then you’ll apply these patterns to a real business scenario: a lead intake workflow that moves prospects from capture to CRM with automated research and outreach. Along the way, you’ll define agent roles, map handoffs, share context, and create data flows that minimize loss and maximize consistency. You’ll also implement human-in-the-loop checkpoints and guardrails to reduce hallucinations, contain risk, and ensure compliance. Finally, you’ll instrument your system with health metrics, spot agent loops, and scale with confidence. Packed with quizzes and hands-on design exercises, this course equips product managers, solutions architects, and technical operators to ship dependable, auditable AI automations that deliver measurable business value.

Architecting Multi-Agent Systems for Coordinated AI Workflows

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            <p>Modern business automation is evolving beyond the capabilities of isolated, single-purpose AI agents. While a single agent can summarize a document or draft an email, complex enterprise workflows require a more sophisticated architecture where multiple specialized agents work in concert. This course explores the transition from single-agent setups to robust multi-agent systems (MAS), detailing how to leverage coordination patterns such as chaining, routing, and collaboration. By distributing responsibilities across a network of agents, organizations can overcome the inherent limitations of individual models, achieving higher levels of accuracy, efficiency, and scalability in their automated processes.</p>

<p>Throughout this curriculum, the focus shifts from theoretical foundations to the practical design of a comprehensive lead intake workflow. Participants will learn to define specific agent roles—including Intake, Research, Outreach, and CRM agents—and manage the critical handoffs and shared context that prevent information loss. Beyond initial construction, the course emphasizes the necessity of safeguarding these systems through "Human-in-the-Loop" (HITL) checkpoints and rigorous guardrails to prevent errors or hallucinations. By mastering the monitoring and scaling of these coordinated workflows, architects can ensure their AI ecosystems remain reliable and adaptable as business needs grow.</p>
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