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Duration 14 hours
Course Outline
Foundations of LLM Agents and AutoGen Studio
- The concept of multi-agent systems
- An overview of AutoGen and AutoGen Studio
- Exploring the visual design interface
Strategy for Agent-Based Workflows
- Identifying business opportunities for agent collaboration
- Aligning user objectives with agent interactions
- Structuring task flows and triggers
Agent Creation and Configuration
- Defining agent roles and behaviors
- Crafting effective prompts and goals
- Utilizing predefined versus custom agent templates
Orchestrating Multi-Agent Communication
- Designing message passing and coordination mechanisms
- Regulating agent turn-taking and logic pathways
- Establishing agent groups and dependencies
Error Handling and Response Optimization
- Managing missing inputs and fallback strategies
- Logging and analyzing conversation flows
- Refining logic based on agent feedback
No-Code Deployment and Validation
- Executing workflows in AutoGen Studio
- Debugging via visual execution history
- Iterating workflows based on test outcomes
Practical Applications and Best Practices
- Internal workflow automation (e.g., summarization, approvals)
- Prototyping products with AI logic
- Strategies for scalable and reusable agent design
Wrap-Up and Future Directions
Requirements
- Familiarity with AI or automation concepts
- Experience with visual tools and process modeling
- No prior coding experience necessary
Target Audience
- Product managers
- Business analysts
- Innovation teams and non-technical stakeholders
Testimonials (1)
I liked that he constantly provided examples but also offered time for individual work on what he presented.
