term updates

Author: ivorb

learn-pr/wwl-data-ai/develop-ai-agents-azure-vs-code/includes/1-introduction.md

@@ -1,8 +1,8 @@
 Imagine you work for a healthcare organization that needs to automate patient interactions while maintaining high security standards. You need an AI agent that can handle patient inquiries, schedule appointments, and access real-time medical information. Building such a system traditionally requires extensive infrastructure management, significant coding effort, and careful attention to data security. Microsoft Foundry Agent Service offers a solution that simplifies this complexity while maintaining enterprise-grade security.
 
-Microsoft Foundry Agent Service is a fully managed platform that empowers you to build, deploy, and scale AI agents without managing underlying compute and storage resources. Whether you prefer working through the Azure portal or developing directly in Visual Studio Code, you have flexible options for creating intelligent agents that automate workflows and enhance user experiences.
+Microsoft Foundry Agent Service is a fully managed platform that empowers you to build, deploy, and scale AI agents without managing underlying compute and storage resources. Whether you prefer working through the Foundry portal or developing directly in Visual Studio Code, you have flexible options for creating intelligent agents that automate workflows and enhance user experiences.
 
-In this module, you'll learn how to develop AI agents using both the Azure portal and the Microsoft Foundry extension for Visual Studio Code. You'll discover how to configure agents with custom instructions, extend their capabilities with tools, and integrate them into your applications. By the end, you'll be able to choose the right development approach for your scenarios and deploy production-ready AI agents.
+In this module, you'll learn how to develop AI agents using both the Foundry portal and the Microsoft Foundry extension for Visual Studio Code. You'll discover how to configure agents with custom instructions, extend their capabilities with tools, and integrate them into your applications. By the end, you'll be able to choose the right development approach for your scenarios and deploy production-ready AI agents.
 
 ## Learning objectives
 

learn-pr/wwl-data-ai/develop-ai-agents-azure-vs-code/includes/11-summary.md

@@ -1,6 +1,6 @@
-You've learned how to develop AI agents using Microsoft Foundry Agent Service through both the Azure portal and Visual Studio Code. These flexible development approaches enable you to create intelligent automation that handles complex tasks, accesses real-time data, and integrates seamlessly with your applications.
+You've learned how to develop AI agents using Microsoft Foundry Agent Service through both the Foundry portal and Visual Studio Code. These flexible development approaches enable you to create intelligent automation that handles complex tasks, accesses real-time data, and integrates seamlessly with your applications.
 
-Throughout this module, you discovered what AI agents are and why they're valuable for automating workflows and enhancing decision-making. You explored the key features of Microsoft Foundry Agent Service, including automatic tool calling, secure data management, and enterprise-grade security. You learned to build agents using both the visual Azure portal and the developer-focused VS Code extension, understanding when each approach fits best.
+Throughout this module, you discovered what AI agents are and why they're valuable for automating workflows and enhancing decision-making. You explored the key features of Microsoft Foundry Agent Service, including automatic tool calling, secure data management, and enterprise-grade security. You learned to build agents using both the visual Foundry portal and the developer-focused VS Code extension, understanding when each approach fits best.
 
 You configured agents with clear instructions that define their behavior and personality. You extended agent capabilities by adding tools like Code Interpreter, File Search, and Bing Search, transforming simple chat interfaces into sophisticated automation systems. You tested agents using integrated playgrounds, deployed them to production environments, and generated integration code to connect agents with your applications.
 

learn-pr/wwl-data-ai/develop-ai-agents-azure-vs-code/includes/2-understand-ai-agents-foundry.md

@@ -75,7 +75,7 @@ By embedding these practices early in development, you can deploy AI agents safe
 
 Microsoft Foundry Agent Service is a fully managed service designed to empower developers to securely build, deploy, and scale high-quality AI agents without managing underlying compute and storage resources. The service allows you to create agents tailored to your needs through custom instructions and advanced tools.
 
-Previously, creating agent-like experiences required significant coding effort using standard APIs. Microsoft Foundry Agent Service handles the complexity through a streamlined interface, enabling you to build agents via the Azure portal or in your own applications with fewer than 50 lines of code.
+Previously, creating agent-like experiences required significant coding effort using standard APIs. Microsoft Foundry Agent Service handles the complexity through a streamlined interface, enabling you to build agents via the Foundry portal or in your own applications with fewer than 50 lines of code.
 
 ### Key features of Microsoft Foundry Agent Service
 

learn-pr/wwl-data-ai/develop-ai-agents-azure-vs-code/includes/3-explore-development-approaches.md

@@ -1,10 +1,10 @@
 Microsoft Foundry Agent Service provides flexibility in how you develop agents, with options ranging from visual interfaces to code-centric workflows. Understanding the different development approaches helps you choose the right tools for your scenarios and team preferences.
 
-## Azure portal development
+## Foundry portal development
 
-The Azure portal provides a web-based interface for creating and managing AI agents without writing code. This approach is ideal when you want to quickly prototype ideas, collaborate with non-technical stakeholders, or manage agents through a centralized interface.
+The Foundry portal provides a web-based interface for creating and managing AI agents without writing code. This approach is ideal when you want to quickly prototype ideas, collaborate with non-technical stakeholders, or manage agents through a centralized interface.
 
-### When to use the Azure portal
+### When to use the Foundry portal
 
 The portal excels in these scenarios:
 
@@ -14,7 +14,7 @@ The portal excels in these scenarios:
 - **Team collaboration** - Share agent configurations with stakeholders who prefer visual interfaces
 - **Resource oversight** - Monitor token usage, latency, and evaluation outcomes through dashboards
 
-The Azure portal provides immediate access to agent creation without installing additional tools. You simply navigate to your Azure AI project, select the Agents section, and start building.
+The Azure portal provides immediate access to agent creation without installing additional tools. You simply navigate to your Foundry project, select the Agents section, and start building.
 
 ## Visual Studio Code development
 
@@ -48,7 +48,7 @@ The VS Code extension is ideal for:
 - **Code-first development** - Edit YAML configurations directly for precise control
 - **Local development** - Work on agent designs offline before deploying to Azure
 
-The extension installs directly from the Visual Studio Code Marketplace and connects to your existing Azure AI projects.
+The extension installs directly from the Visual Studio Code Marketplace and connects to your existing Foundry projects.
 
 ### Extension installation
 
@@ -73,7 +73,7 @@ Regardless of your chosen approach, agent development follows a consistent patte
 1. **Deploy** the agent to production
 1. **Integrate** the agent into your applications
 
-The Azure portal and VS Code extension both support this workflow, differing primarily in interface style rather than capabilities.
+The Foundry portal and VS Code extension both support this workflow, differing primarily in interface style rather than capabilities.
 
 ## Required Azure resources
 
@@ -97,9 +97,9 @@ These services integrate with your Foundry project as needed, but aren't require
 
 ## Choosing your development approach
 
-Both the Azure portal and Visual Studio Code extension provide complete agent development capabilities. Your choice depends on your workflow preferences, team composition, and integration requirements:
+Both the Foundry portal and Visual Studio Code extension provide complete agent development capabilities. Your choice depends on your workflow preferences, team composition, and integration requirements:
 
-Choose the **Azure portal** when you want visual configuration, centralized management, or quick prototyping without local development setup.
+Choose the **Foundry portal** when you want visual configuration, centralized management, or quick prototyping without local development setup.
 
 Choose **Visual Studio Code** when you prefer developer-centric workflows, need tight integration with application code, or want version-controlled configuration files.
 

learn-pr/wwl-data-ai/develop-ai-agents-azure-vs-code/includes/4-build-agent-azure-portal.md

@@ -1,19 +1,8 @@
-Building your first AI agent in the Azure portal provides an accessible entry point to agent development. The portal's visual interface guides you through configuration without requiring code, making it easy to understand agent concepts while creating functional automation.
+Building your first AI agent in the Foundry portal provides an accessible entry point to agent development. The portal's visual interface guides you through configuration without requiring code, making it easy to understand agent concepts while creating functional automation.
 
-## Prerequisites for agent creation
+## Creating an agent in the Foundry portal
 
-Before creating an agent in the Azure portal, ensure you have:
-
-- An active Azure subscription
-- An Azure AI hub resource
-- An Azure AI project within your hub
-- At least one deployed model (such as GPT-4o or GPT-4)
-
-If you don't have these resources yet, you can create them through the Microsoft Foundry portal at https://ai.azure.com. The portal provides guided workflows for setting up your AI environment.
-
-## Creating an agent in the Azure portal
-
-The Azure portal streamlines agent creation through an intuitive interface:
+The Foundry portal streamlines agent creation through an intuitive interface:
 
 1. **Navigate to Microsoft Foundry** at https://ai.azure.com and sign in with your Azure credentials
 1. **Select your project** from the list of available projects, or create a new one
@@ -22,7 +11,7 @@ The Azure portal streamlines agent creation through an intuitive interface:
 1. **Enter agent details**:
    - **Name**: Provide a descriptive name for your agent
    - **Description**: Add a clear description of the agent's purpose
-   - **Model**: Select a deployed model from the dropdown
+   - **Model**: Select a deployed model from the dropdown, or deploy a new model
 
 The portal creates your agent and opens the configuration interface where you can refine its behavior and capabilities.
 
@@ -79,7 +68,7 @@ You can set maximum token limits for responses, preventing overly long outputs a
 
 ## Testing your agent in the portal
 
-The Azure portal includes an integrated playground for testing your agent before deployment. This testing environment lets you validate instructions, try different scenarios, and refine behavior based on results.
+The Foundry portal includes an integrated playground for testing your agent before deployment. This testing environment lets you validate instructions, try different scenarios, and refine behavior based on results.
 
 To test your agent, select the Playground tab and start a conversation. The playground maintains conversation history during your session, allowing you to test multi-turn interactions and verify the agent maintains context appropriately.
 
@@ -99,4 +88,4 @@ You add these tools through the Tools section in the agent configuration. Tool c
 
 Once you're satisfied with your agent's behavior in testing, you can deploy it for production use. The portal provides clear deployment status indicators and generates the connection information needed to integrate the agent into your applications. After deployment, you can access the agent through the Microsoft Foundry SDK or REST APIs.
 
-Building agents in the Azure portal provides an accessible, visual approach to agent development. The interface guides you through configuration while offering powerful capabilities for creating sophisticated automation.
+Building agents in the Foundry portal provides an accessible, visual approach to agent development. The interface guides you through configuration while offering powerful capabilities for creating sophisticated automation.

learn-pr/wwl-data-ai/develop-ai-agents-azure-vs-code/includes/5-set-up-vs-code.md

@@ -10,7 +10,7 @@ The extension offers several key features that streamline agent development:
 
 **Agent discovery and management** - Browse, create, and manage AI agents within your Microsoft Foundry projects. View all your agents in the Azure Resources explorer without opening a browser.
 
-**Visual agent designer** - Configure agent instructions, tools, and capabilities through an intuitive interface. The designer provides the same power as the Azure portal while keeping you in your development environment.
+**Visual agent designer** - Configure agent instructions, tools, and capabilities through an intuitive interface. The designer provides the same power as the Foundry portal while keeping you in your development environment.
 
 **Integrated testing** - Test agents in real-time using the built-in playground. Verify behavior and iterate on designs without switching contexts or tools.
 

learn-pr/wwl-data-ai/develop-ai-agents-azure-vs-code/includes/8-test-deploy-integrate.md

@@ -6,7 +6,7 @@ Thorough testing ensures your agents behave reliably across diverse scenarios be
 
 ### Testing with integrated playgrounds
 
-Both the Azure portal and Visual Studio Code extension provide playgrounds for interactive testing. These environments simulate real user interactions while providing visibility into agent decision-making.
+Both the Foundry portal and Visual Studio Code extension provide playgrounds for interactive testing. These environments simulate real user interactions while providing visibility into agent decision-making.
 
 **Using the playground effectively:**
 
@@ -68,17 +68,17 @@ When deploying agents, consider conversation management strategies:
 
 **Privacy and retention** - Define retention policies for conversation data. Determine how long message histories should be preserved and when they should be deleted.
 
-You can view and manage conversations through the Azure portal or programmatically through the Responses API, providing visibility into how users interact with your deployed agents.
+You can view and manage conversations through the Foundry portal or programmatically through the Responses API, providing visibility into how users interact with your deployed agents.
 
 ## Deployment approaches
 
 Microsoft Foundry supports multiple deployment approaches to match different operational needs and team workflows.
 
-### Deploying from the Azure portal
+### Deploying from the Foundry portal
 
 Portal deployment provides a visual, guided experience:
 
-1. Navigate to your agent in the Azure portal
+1. Navigate to your agent in the Foundry portal
 1. Verify configuration and test results are satisfactory
 1. Select **Deploy** from the agent's page
 1. Confirm deployment settings