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new develop agents module
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.github/agents/learn-module-writer.agent.md

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.github/agents/learn-writer.agent.md

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---
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description: Creates a learn unit based on the provided requirementsm by orchestrating multiple subagents.
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description: Creates a learn unit based on the provided requirements by orchestrating multiple subagents.
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model: Claude Sonnet 4.5 (copilot)
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tools:
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['edit', 'search', 'runTasks', 'microsoft_docs_mcp/*', 'fetch', 'github.vscode-pull-request-github/issue_fetch', 'todos', 'shell', 'synthesia/crt-video', 'synthesia/get-video']
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### YamlMime:LearningPath
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uid: learn.wwl.develop-ai-agents-azure
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hidden: true
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metadata:
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title: Develop AI Agents on Azure
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description: Learn how to develop AI agents on Azure using the Microsoft Foundry Agent Service and Microsoft Agent Framework. AI-3026
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ms.date: 02/12/2026
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author: wwlpublish
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ms.author: berryivor
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ms.topic: learning-path
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ms.collection: wwl-ai-copilot
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title: Develop AI agents on Azure
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prerequisites: |
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Before starting this module, you should be familiar with fundamental AI concepts and services in Azure. Consider completing the [Get started with artificial intelligence](/training/paths/get-started-with-artificial-intelligence-on-azure) learning path first.
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summary: |
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Generative Artificial Intelligence (AI) is becoming more functional and accessible, and AI agents are a key component of this evolution. This learning path will help you understand the AI agents, including when to use them and how to build them, using Microsoft Foundry Agent Service and Microsoft Agent Framework. By the end of this learning path, you will have the skills needed to develop AI agents on Azure.
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iconUrl: /training/achievements/generic-badge.svg
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levels:
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- intermediate
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roles:
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- ai-engineer
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products:
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- ai-services
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- azure-ai-foundry
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- azure-ai-foundry-agent-service
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- azure-ai-foundry-sdk
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subjects:
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- artificial-intelligence
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- machine-learning
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- natural-language-processing
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modules:
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- learn.wwl.develop-ai-agents-azure-vs-code
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- learn.wwl.build-agent-with-custom-tools
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- learn.wwl.connect-agent-to-mcp-tools
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- learn.wwl.introduction-foundry-iq
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- learn.wwl.build-agent-workflows-microsoft-foundry
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- learn.wwl.develop-multi-agent-azure-ai-foundry
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- learn.wwl.develop-ai-agent-with-semantic-kernel
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- learn.wwl.orchestrate-sk-multi-agent-solution
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- learn.wwl.discover-agents-with-a2a
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trophy:
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uid: learn.wwl.develop-ai-agents-azure.trophy
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### YamlMime:ModuleUnit
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uid: learn.wwl.develop-ai-agents-azure-vs-code.introduction
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title: Introduction
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metadata:
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title: Introduction
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description: Introduction to developing AI agents with Microsoft Foundry and Visual Studio Code.
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ms.date: 02/12/2026
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author: ivorb
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ms.author: berryivor
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ms.topic: unit
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ai-usage: ai-generated
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durationInMinutes: 3
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content: |
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[!include[](includes/1-introduction.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.develop-ai-agents-azure-vs-code.knowledge-check
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title: Knowledge check
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metadata:
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title: Knowledge Check
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description: Check your knowledge of AI agent development with Microsoft Foundry.
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ms.date: 02/12/2026
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author: ivorb
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ms.author: berryivor
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ms.topic: unit
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ai-usage: ai-generated
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durationInMinutes: 3
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quiz:
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title: Check your knowledge
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questions:
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- content: What is the primary benefit of using Microsoft Foundry Agent Service compared to building agents with standard APIs?
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choices:
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- content: It provides access to more powerful AI models
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isCorrect: false
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explanation: Incorrect. Microsoft Foundry Agent Service uses the same models available through standard APIs.
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- content: It requires no Azure subscription
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isCorrect: false
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explanation: Incorrect. You need an Azure subscription to use Microsoft Foundry Agent Service.
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- content: It handles tool calling, state management, and infrastructure automatically
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isCorrect: true
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explanation: Correct. Microsoft Foundry Agent Service manages the complexity of tool calling, conversation state, and infrastructure, reducing development effort.
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- content: It only works with the Azure portal
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isCorrect: false
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explanation: Incorrect. Microsoft Foundry Agent Service works with both the Azure portal and Visual Studio Code extension.
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- content: How does Microsoft Foundry Agent Service handle conversation state?
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choices:
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- content: By requiring developers to manually manage conversation history
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isCorrect: false
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explanation: Incorrect. The service handles conversation state automatically.
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- content: Through external database connections
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isCorrect: false
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explanation: Incorrect. The service manages state internally without requiring external databases.
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- content: Through the Responses API which automatically manages conversation context
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isCorrect: true
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explanation: Correct. The Responses API handles conversation context automatically, removing the need for manual state management.
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- content: Using local file storage on the client device
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isCorrect: false
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explanation: Incorrect. Conversation state is managed by the service, not stored locally on client devices.
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- content: Which of the following is NOT a recommended security practice for AI agents?
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choices:
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- content: Using role-based access controls
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isCorrect: false
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explanation: Incorrect. This is a recommended security practice.
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- content: Implementing prompt filtering and validation
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isCorrect: false
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explanation: Incorrect. This is a recommended security practice to prevent injection attacks.
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- content: Maintaining comprehensive logging and traceability
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isCorrect: false
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explanation: Incorrect. This is a recommended security practice for auditability.
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- content: Allowing agents unrestricted access to all enterprise data
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isCorrect: true
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explanation: Correct. This is NOT recommended. Agents should follow least privilege principles with restricted access based on their specific needs.
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- content: What happens when an agent determines it needs a tool to respond to a user request?
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choices:
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- content: The agent asks the user for permission to use the tool
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isCorrect: false
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explanation: Incorrect. Agents don't request permission; they automatically use configured tools.
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- content: The agent stops processing and waits for developer input
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isCorrect: false
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explanation: Incorrect. Agents handle tool invocation automatically without developer intervention.
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- content: The agent automatically invokes the tool, processes results, and incorporates them into its response
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isCorrect: true
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explanation: Correct. Microsoft Foundry Agent Service handles the complete tool-calling lifecycle automatically.
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- content: The agent sends the request to a separate processing queue
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isCorrect: false
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explanation: Incorrect. Tool execution happens synchronously as part of the response generation process.
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### YamlMime:ModuleUnit
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uid: learn.wwl.develop-ai-agents-azure-vs-code.summary
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title: Summary
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metadata:
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title: Summary
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description: Summary of key concepts and next steps for AI agent development.
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ms.date: 02/12/2026
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author: ivorb
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ms.author: berryivor
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ms.topic: unit
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ai-usage: ai-generated
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durationInMinutes: 2
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content: |
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[!include[](includes/11-summary.md)]
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### YamlMime:ModuleUnit
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uid: learn.wwl.develop-ai-agents-azure-vs-code.understand-ai-agents-foundry
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title: Understand AI agents and Microsoft Foundry Agent Service
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metadata:
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title: Understand AI Agents and Microsoft Foundry Agent Service
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description: Learn about AI agents, their capabilities, use cases, and the features of Microsoft Foundry Agent Service.
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ms.date: 02/12/2026
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author: ivorb
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ms.author: berryivor
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ms.topic: unit
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ai-usage: ai-generated
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durationInMinutes: 8
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content: |
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[!include[](includes/2-understand-ai-agents-foundry.md)]

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