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 Duration 14 hours

Course Outline

Introduction to LLM Agents and AutoGen Studio

  • Concepts of multi-agent systems
  • Overview of AutoGen and AutoGen Studio
  • Familiarity with the visual design interface

Planning Agent-Based Workflows

  • Identifying business use cases for agent collaboration
  • Aligning user goals with agent interactions
  • Designing task flows and triggers

Creating and Configuring Agents

  • Defining agent roles and behaviors
  • Crafting effective prompts and objectives
  • Utilizing predefined versus custom agent templates

Managing Multi-Agent Communication

  • Designing message passing and coordination mechanisms
  • Controlling agent turn-taking and logical paths
  • Establishing agent groups and dependencies

Error Handling and Response Management

  • Addressing missing inputs and fallback procedures
  • Logging and analyzing conversation flows
  • Refining logic based on agent feedback

No-Code Deployment and Testing

  • Executing workflows within AutoGen Studio
  • Debugging using visual execution history
  • Optimizing workflows based on test outcomes

Real-World Use Cases and Best Practices

  • Internal workflow automation (e.g., summarization, approvals)
  • Developing product prototypes with AI logic
  • Strategies for scalable and reusable agent design

Summary and Next Steps

Requirements

  • Familiarity with AI or automation concepts
  • Proficiency with visual tools and process modeling
  • No prior coding experience necessary

Audience

  • Product managers
  • Business analysts
  • Innovation teams and non-developers

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