Speaker | AI Mastery Series on Microsoft Foundry

A portfolio entry for my role as a speaker in the 3-day "AI Mastery Series" on Microsoft Foundry, focusing on my technical demonstration of MCP.

AI Mastery Series: Microsoft Foundry

Date: June 27 - 29, 2025 | Format: 3-Day Educational Webinar Series

Executive Summary

As part of a team of three speakers, I contributed to the “AI Mastery Series,” a comprehensive 3-day webinar on Microsoft Foundry. The series was designed to guide freshers and mid-level participants from foundational principles to advanced production deployment, with a strong emphasis on hands-on application. My role was to deliver a key technical demonstration on the Model Context Protocol (MCP), helping the series reach over 1,000 viewers and establish a lasting open-source repository with real-world use cases.

:material-presentation-play: My Demonstration: A Deep Dive into MCP

My specific contribution to the series was to deliver a detailed technical demonstration during the hands-on session. The goal was to bridge the gap between theory and real-world application by deconstructing a complex use case from start to finish, showing attendees how to build practical, powerful AI agents.

  • :material-axis-arrow-lock: Focus: Model Context Protocol (MCP)

    The core of my demo was the Model Context Protocol (MCP). I explained how this framework enables the creation of modular, composable AI agents that can interact with external tools and services in a standardized and scalable way, which is critical for enterprise-grade solutions.

  • :material-code-braces: Live Use Case Implementation

    I presented and built out a practical use case where an AI agent was designed to solve a real-world problem. I walked the audience through the agent’s architecture, the flow of data, and the specific MCP server calls used to execute its complex tasks, providing a clear, step-by-step implementation guide.

  • :material-school-outline: Key Learning Outcomes

    Through my session, attendees gained practical skills and a deeper understanding of how to:

    • Integrate prebuilt MCP servers into their own agents.
    • Structure a complex AI task into smaller, manageable actions.
    • Debug and trace agent behavior in a hands-on environment.

:material-notebook-edit-outline: Comprehensive 3-Day Curriculum

The webinar series offered a complete, end-to-end learning path covering the full lifecycle of AI agent development, from initial concept to final deployment.

???+ abstract “Three-Day Series Agenda”

=== ":material-numeric-1-circle-outline: Session 1: Foundations of AI Agents"
    
	**Focus:** Building a strong theoretical base.
    
	- **Core Concepts:** Covered the fundamental design principles of AI agents.
    - **Platform Introduction:** Introduced the capabilities of the Microsoft Foundry platform.
    - **First Steps:** Guided attendees through creating their first basic AI agents.

=== ":material-numeric-2-circle-outline: Session 2: Hands-on with Microsoft Foundry"
    
	**Focus:** Practical application and real-world problem-solving.
    
	- **Hands-on Labs:** Explored real-world **MCP (Model Context Protocol) use cases** to solve practical problems.
    
	- **Detailed Use Cases:** Each use case in the repository was documented with:
        - **Description:** A clear explanation of the problem the agent solves.
        - **Azure MCP Architecture:** A breakdown of how the solution leverages Azure services.
        - **Workflow & Diagrams:** Visuals illustrating agent interactions and data flow.
        - **Example Actions & Pseudocode:** Concrete examples of how the agent calls MCP actions.

=== ":material-numeric-3-circle-outline: Session 3: Production & Deployment with MCP"
    
	**Focus:** Enterprise readiness and advanced techniques.
    
	- **Advanced MCP:** Covered the integration of prebuilt MCP servers.
    - **Production Best Practices:** Discussed deployment, CI/CD, monitoring, and cost optimization.
    - **Enterprise Strategy:** Focused on preparing agents for large-scale, enterprise environments.

:material-chart-line: Measured Impact & Community Engagement

The series’ collective success is reflected in its strong viewership, active community participation, and the real-world success of its attendees.

  • :material-broadcast: Educational Reach & Engagement

    • Sustained Viewership: Achieved 1,000+ total views across the 3-day series.
    • High Participation: Fostered significant interaction during live Q&A and hands-on labs.
    • Valuable Open-Source Asset: The GitHub repository gained :material-star: 6 stars and :material-source-fork: 1 fork, indicating strong community value.

  • :material-rocket-launch: Developer Enablement & Outcomes

    • Production Deployments: Attendees successfully used the learned concepts to launch enterprise-grade AI applications.
    • Measurable Skill Advancement: Participants reported significantly improved confidence and capabilities in Azure AI.
    • Knowledge Multiplication: Empowered attendees to become mentors and educators within their own organizations.

:material-open-in-new: References & Media

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