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Duration 14 hours
Course Outline
Foundational Concepts of LLM Agents and AutoGen Studio
- Definition and structure of multi-agent frameworks
- Overview of the AutoGen platform and AutoGen Studio environment
- Analysis of the visual interface for design operations
Strategic Planning for Agent-Based Processes
- Identification of high-value operational use cases for agent collaboration
- Alignment of organizational objectives with agent behavioral outcomes
- Architectural design of task sequences and event triggers
Agent Creation and Configuration Protocols
- Assignment of specific roles and operational behaviors to agents
- Formulation of precise prompts and performance goals
- Selection between standard templates and custom configurations
Governance of Multi-Agent Interaction
- Design of data exchange and coordination mechanisms
- Regulation of turn-taking sequences and decision logic paths
- Establishment of agent groupings and dependency structures
Exception Management and Response Optimization
- Implementation of input validation and fallback procedures
- Systematic logging and audit of interaction histories
- Iterative refinement of logic based on performance feedback
Validation, Testing, and Deployment Procedures
- Execution of workflows within the AutoGen Studio environment
- Diagnostic analysis using visual execution logs
- Workflow adjustments based on empirical test outcomes
Operational Applications and Best Practices
- Automation of internal government processes (e.g., document summarization, approval routing)
- Development of functional prototypes utilizing AI-driven logic
- Strategies for scalable, reusable, and maintainable agent architectures
Summary and Recommended Follow-Up Actions
Requirements
- Familiarity with foundational concepts in artificial intelligence or process automation
- Proficiency with visual design tools and process mapping methodologies
- No prerequisite coding experience is necessary for participation
Target Audience
- Product managers overseeing digital service delivery
- Business analysts focused on process improvement
- Innovation teams and non-technical stakeholders involved in digital transformation
Testimonials (1)
I liked that he constantly provided examples but also offered time for individual work on what he presented.
