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Duration 14 hours
Course Outline
Foundations of LLM Agents and AutoGen Studio
- Defining multi-agent systems
- Introduction to AutoGen and AutoGen Studio
- Exploring the visual design interface
Planning Agent-Centric Workflows
- Identifying business scenarios for agent collaboration
- Aligning user goals with agent interactions
- Structuring task flows and triggers
Developing and Configuring Agents
- Assigning roles and behaviors to agents
- Crafting effective prompts and objectives
- Selecting between predefined and custom agent templates
Orchestrating Multi-Agent Communication
- Designing message passing and coordination mechanisms
- Regulating agent turn-taking and logical 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
Deployment and Testing Without Code
- Executing workflows within AutoGen Studio
- Debugging via visual execution history
- Iterating on workflows based on test outcomes
Real-World Applications and Best Practices
- Automating internal processes (e.g., summarization, approvals)
- Prototyping products with AI logic
- Strategies for scalable and reusable agent design
Recap and Future Directions
Requirements
- Basic knowledge of AI or automation principles
- Familiarity with visual tools and process modeling
- No previous coding experience is necessary
Target Audience
- Product managers
- Business analysts
- Innovation teams and non-technical users
Testimonials (1)
I liked that he constantly provided examples but also offered time for individual work on what he presented.
