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- AI agents represent the next generation of intelligent applications. Learn how they can be developed and used on Microsoft Azure.
By the end of this module, you learn to:
- Describe core concepts related to AI agents
- Describe options for agent development
- Create and test an agent in the Microsoft Foundry portal
- Learn how to start using Microsoft Foundry Agent Service.
By the end of this module, you'll be able to:
- Describe the purpose of AI agents
- Explain the key features of Microsoft Foundry Agent Service
- Build an agent using the Foundry Agent Service
- Integrate an agent in the Foundry Agent Service into your own application
- Learn how to build, test, and deploy AI agents using the Microsoft Foundry extension in Visual Studio Code.
By the end of this module, you'll be able to:
- Configure and deploy AI agents using the agent designer
- Add tools and capabilities to extend your agents' functionality
- Test agents using the integrated playground
- Generate sample code to integrate agents into applications
- Learn how to build an agent with custom tools using the Microsoft Foundry Agent Service.
By the end of this module, you'll be able to:
- Describe the benefits of using custom tools with your agent.
- Explore the different options for custom tools.
- Build an agent that integrates custom tools using the Microsoft Foundry Agent Service.
- Break down complex tasks with intelligent collaboration. Learn how to design multi-agent solutions using connected agents.
After completing this module, you'll be able to:
- Describe how connected agents enable modular, collaborative workflows.
- Design a multi-agent solution by defining main agent tools and connected agent roles.
- Build and run a connected agent solution
- Enable dynamic tool access for your Azure AI agents. Learn how to connect MCP-hosted tools and integrate them seamlessly into agent workflows.
After completing this module, you're able to:
- Explain the roles of the MCP server and client in tool discovery and invocation.
- Wrap MCP tools as asynchronous functions and register them with Azure AI agents.
- Build an Azure AI agent that dynamically accesses and calls MCP tools during runtime.
- Learn how to start building agents with Microsoft Agent Framework
By the end of this module, you'll be able to:
- Use Microsoft Agent Framework to connect to a Microsoft Foundry project
- Create Microsoft Foundry Agent Service agents using the Microsoft Agent Framework SDK
- Integrate plugin functions with your AI agent
- Learn how to design multi-agent solutions with the Microsoft Agent Framework SDK
By the end of this module, you'll be able to:
- Build AI agents using the Microsoft Agent Framework SDK
- Understand how and when to use different orchestration patterns
- Develop multi-agent solutions
- Learn how to implement the A2A protocol to enable agent discovery, direct communication, and coordinated task execution across remote agents.
After completing this module, you're able to:
- Understand the A2A protocol and its role in multi-agent orchestration.
- Design discoverable agents for modular, collaborative problem-solving.
- Implement A2A strategies to discover and invoke remote agents.
- Workflows enable you to orchestrate AI agents and other components to create intelligent applications. Learn how to build and manage workflows using Microsoft Foundry.
By the end of this module, you learn to:
- Explain how nodes, variables, and agent outputs control workflow execution
- Route requests using structured outputs and conditional logic
- Loop over multiple inputs with For-Each nodes
- Use human-in-the-loop and escalation patterns for low-confidence items
- Utilize Power Fx expressions to manipulate data and control flow.
- Learn how Foundry IQ transforms how AI agents access and reason over organizational data through its unified knowledge layer and Retrieval Augmented Generation (RAG) capabilities. Build a practical agent that leverages enterprise knowledge through Foundry IQ's agentic retrieval engine.
In this module, you:
- Explain how RAG solves the knowledge problem by connecting agents to real-time information
- Describe how Foundry IQ provides a shared knowledge platform that multiple agents can access
- Configure data sources for knowledge bases including Azure AI Search, Blob Storage, SharePoint, and OneLake
- Configure agent instructions to control retrieval behavior and ensure consistent citations
- Test and monitor agent retrieval to maintain quality in production
