resolving odd build error

Author: Orin-Thomas

learn-pr/advocates/intro-ai-agent-service-security-controls/1-understand-azure-ai-agent-service.yml

@@ -4,7 +4,7 @@ title: Understand the Azure AI Agent Service
 metadata:
   title: Understand the Azure AI Agent Service
   description: Learn about the Azure AI Agent Service.
-  ms.date: 03/20/2025
+  ms.date: 03/21/2025
   author: Orin-Thomas
   ms.author: orthomas
   ms.topic: unit

learn-pr/advocates/intro-ai-agent-service-security-controls/2-secure-azure-ai-agent-service.yml

@@ -4,7 +4,7 @@ title: Securing the Azure AI Agent Service
 metadata:
   title: Securing the Azure AI Agent Service
   description: Understand the security controls that can be applied to the Azure AI Agent Service.
-  ms.date: 03/20/2025
+  ms.date: 03/21/2025
   author: Orin-Thomas
   ms.author: orthomas
   ms.topic: unit

learn-pr/advocates/intro-ai-agent-service-security-controls/3-azure-ai-agent-service-role-based-access-control.yml

@@ -4,7 +4,7 @@ title: Azure AI Agent Service Role Based Access Control
 metadata:
   title: Azure AI Agent Service Role Based Access Control
   description: Learn to configure role-based access control for the Azure AI Agent Service.
-  ms.date: 03/20/2025
+  ms.date: 03/21/2025
   author: Orin-Thomas
   ms.author: orthomas
   ms.topic: unit

learn-pr/advocates/intro-ai-agent-service-security-controls/4-agent-service-and-network-access.yml

@@ -4,7 +4,7 @@ title: Agent Service and Network Access
 metadata:
   title: Agent Service and Network Access
   description: Learn to configure network access for the Azure AI Agent Service.
-  ms.date: 03/20/2025
+  ms.date: 03/21/2025
   author: Orin-Thomas
   ms.author: orthomas
   ms.topic: unit

learn-pr/advocates/intro-ai-agent-service-security-controls/5-knowledge-check.yml

@@ -3,8 +3,8 @@ uid: learn.introduction-ai-agent-service-security-controls.knowledge-check
 title: Knowledge Check
 metadata:
   title: Knowledge Check
-  description: TBD
-  ms.date: 03/20/2025
+  description: Check your knowledge of the Azure AI Agent Service security controls.
+  ms.date: 03/21/2025
   author: Orin-Thomas
   ms.author: orthomas
   ms.topic: unit

learn-pr/advocates/intro-ai-agent-service-security-controls/6-summary.yml

@@ -3,8 +3,8 @@ uid: learn.introduction-ai-agent-service-security-controls.summary
 title: Summary
 metadata:
   title: Summary
-  description: TBD
-  ms.date: 03/20/2025
+  description: Module summary
+  ms.date: 03/21/2025
   author: Orin-Thomas
   ms.author: orthomas
   ms.topic: unit

learn-pr/advocates/intro-ai-agent-service-security-controls/includes/1-understand-azure-ai-agent-service.md

@@ -1,4 +1,4 @@
-Azure AI Agent Service is a fully managed service designed to empower developers to securely build, deploy, and scale high-quality, and extensible AI agents without needing to manage the underlying compute and storage resources. Tasks that can take hundreds of lines of code to support client side function calling may now be achieved with just a few lines of code with Azure AI Agent Service.
+Azure AI Agent Service is a fully managed service designed to empower developers to securely build, deploy, and scale high-quality, and extensible AI agents without needing to manage the underlying compute and storage resources. Tasks that can take hundreds of lines of code to support client side function calling can now be achieved with just a few lines of code with Azure AI Agent Service.
 
 An AI Agent acts as a "smart" microservice that can be used to answer questions (Retrieval Augmented Generation), perform actions, or completely automate workflows. AI agents achieve this by combining the power of generative AI models to understand information resources with tools that allow that model to access and interact with real-world data sources.
 

learn-pr/advocates/intro-ai-agent-service-security-controls/includes/2-secure-azure-ai-agent-service.md

@@ -8,4 +8,4 @@ You can apply security controls through the Azure AI Foundry interface or by app
 - Network access
 - Monitoring alerts, metrics and logs
 
-At the Azure AI project level, you can configure role based access control, monitoring alerts, metrics, and logs, but can't configure network access restrictions. In most scenarios you configure security controls related to Azure AI Agents Service agents at the hub level. When you need to have different sets of security controls, you host Azure AI Agent Service agents in different Azure AI hubs.
+At the Azure AI project level, you can configure role based access control, monitoring alerts, metrics, and logs, but can't configure network access restrictions. In the majority of scenarios, you configure security controls related to Azure AI Agents Service agents at the hub level. When you need to have different sets of security controls, you host Azure AI Agent Service agents in different Azure AI hubs.

learn-pr/advocates/intro-ai-agent-service-security-controls/includes/3-azure-ai-agent-service-role-based-access-control.md

@@ -11,7 +11,7 @@ The Azure AI Foundry hub has built-in roles that are available by default.
 | **Azure AI Inference Deployment Operator** | Perform all actions required to create a resource deployment within a resource group. |
 | **Reader** | Read only access to the hub. This role is automatically assigned to all project members within the hub. |
 
-Hubs have the system-assigned managed identity assigned to the Azure AI Administrator role. This role is more narrowly scoped to the minimum permissions needed for the managed identity to perform its tasks. This system-assigned managed identity is inherited at the project level. Depending on how an Azure AI Agent is configured, it will either use the system-assigned managed identity when accessing data sources or performing actions such as running code, running a custom function or an Azure function.  
+Hubs have the system-assigned managed identity assigned to the Azure AI Administrator role. This role is more narrowly scoped to the minimum permissions needed for the managed identity to perform its tasks. This system-assigned managed identity is inherited at the project level. Depending on how an Azure AI Agent is configured, the process will use the system-assigned managed identity when accessing data sources or performing actions such as running code, running a custom function or an Azure function with the user's identity.  
 
 When a user is granted access to a project (for example, through the Azure AI Foundry portal permission management), two more roles are automatically assigned to the user. The first role is Reader on the hub. The second role is the Inference Deployment Operator role, which allows the user to create deployments on the resource group that the project is in.
 

learn-pr/advocates/intro-ai-agent-service-security-controls/includes/4-agent-service-network-access.md

@@ -1,4 +1,4 @@
-Network access for an Azure AI Agent associated with an Azure Foundry project is configured at the Hub level. You can only configure network settings for a hub in the Azure portal and can't configure network settings in Azure Foundry.
+You configure network access for an Azure AI Agent associated with an Azure Foundry project at the Hub level. You can only configure network settings for a hub in the Azure portal and can't configure network settings in Azure Foundry.
 
 You have the following options when configuring network access: