diff --git a/azure/documentdb/quickstart-agent-go.md b/azure/documentdb/quickstart-agent-go.md
index d66066a4c9..b3cccda5e2 100644
--- a/azure/documentdb/quickstart-agent-go.md
+++ b/azure/documentdb/quickstart-agent-go.md
@@ -38,6 +38,9 @@ You can use the Azure Developer CLI to create the required Azure resources by ru
     - Add your client IP address to the cluster's firewall rules. For more information, see [Grant access from your IP address](/azure/documentdb/how-to-configure-firewall#grant-access-from-your-ip-address).
   - For passwordless authentication, Role Based Access Control (RBAC) enabled
 
+> [!NOTE]
+> The infrastructure deploys Azure OpenAI with the **Standard** SKU (not GlobalStandard). You can customize the SKU and model parameters using `azd env set` before deployment. See the sample's README for available parameters.
+
 ### Development tools
 
 - [Go](https://golang.org/dl/) 1.22 or later
@@ -120,6 +123,9 @@ AZURE_DOCUMENTDB_COLLECTION=hotel_data
 AZURE_DOCUMENTDB_INDEX_NAME=vectorIndex
 ```
 
+> [!TIP]
+> Unlike some databases, DocumentDB allows you to create and drop vector indexes at any time after container creation. You don't need to define the vector indexing policy at container creation time.
+
 ## Project structure
 
 The project follows the standard Go project layout. Your directory structure should look like the following structure:
diff --git a/azure/documentdb/quickstart-agent-nodejs.md b/azure/documentdb/quickstart-agent-nodejs.md
index 8b3fbba1d5..3d25d51ba0 100644
--- a/azure/documentdb/quickstart-agent-nodejs.md
+++ b/azure/documentdb/quickstart-agent-nodejs.md
@@ -87,6 +87,15 @@ Use the Azure Developer CLI (`azd`) to provision the required Azure OpenAI and D
 
 > [!TIP]
 > Run `azd env get-values` at any time to view the current environment values.
+>
+> To export these values to a `.env` file, run:
+>
+> ```bash
+> azd env get-values > .env
+> ```
+
+> [!NOTE]
+> The infrastructure deploys Azure OpenAI with the **Standard** SKU (not GlobalStandard). You can customize the SKU and model parameters using `azd env set` before deployment. See the sample's README for available parameters.
 
 ## Configure environment variables
 
@@ -186,6 +195,9 @@ VECTOR_INDEX_ALGORITHM=vector-ivf
 EMBEDDING_DIMENSIONS=1536
 ```
 
+> [!TIP]
+> Unlike some databases, DocumentDB allows you to create and drop vector indexes at any time after container creation. You don't need to define the vector indexing policy at container creation time.
+
 ## Project structure
 
 The project follows a standard Node.js/TypeScript project layout. Your directory structure should look like the following structure:
diff --git a/azure/documentdb/quickstart-dotnet-vector-search.md b/azure/documentdb/quickstart-dotnet-vector-search.md
index b9e217935f..d780a6803c 100644
--- a/azure/documentdb/quickstart-dotnet-vector-search.md
+++ b/azure/documentdb/quickstart-dotnet-vector-search.md
@@ -28,6 +28,9 @@ The app uses a sample hotel dataset in a JSON file with pre-calculated vectors f
 
 [!INCLUDE[Prerequisites - Vector Search Quickstart](includes/prerequisite-quickstart-vector-search-model.md)]
 
+> [!NOTE]
+> The infrastructure deploys Azure OpenAI with the **Standard** SKU (not GlobalStandard). You can customize the SKU and model parameters using `azd env set` before deployment. See the sample's README for available parameters.
+
 - [.NET 8.0 SDK](https://dotnet.microsoft.com/download/dotnet/8.0) or later
 
     - [C# extension for Visual Studio Code](https://marketplace.visualstudio.com/items?itemName=ms-dotnettools.csharp)
diff --git a/azure/documentdb/quickstart-go-vector-search.md b/azure/documentdb/quickstart-go-vector-search.md
index 70d20e0064..30cd19df97 100644
--- a/azure/documentdb/quickstart-go-vector-search.md
+++ b/azure/documentdb/quickstart-go-vector-search.md
@@ -23,6 +23,9 @@ Find the [sample code](https://github.com/Azure-Samples/documentdb-samples/tree/
 
 [!INCLUDE[Prerequisites - Vector Search Quickstart](includes/prerequisite-quickstart-vector-search-model.md)]
 
+> [!NOTE]
+> The infrastructure deploys Azure OpenAI with the **Standard** SKU (not GlobalStandard). You can customize the SKU and model parameters using `azd env set` before deployment. See the sample's README for available parameters.
+
 - [Go](https://golang.org/dl/) version 1.24 or later
 
 ## Create data file with vectors
@@ -171,6 +174,9 @@ vector-search-quickstart
 
 ----
 
+> [!TIP]
+> Unlike some databases, DocumentDB allows you to create and drop vector indexes at any time after container creation. You don't need to define the vector indexing policy at container creation time.
+
 ## Create code for vector search
 
 ### [DiskANN](#tab/tab-diskann)
diff --git a/azure/documentdb/quickstart-java-vector-search.md b/azure/documentdb/quickstart-java-vector-search.md
index 33bcb767c5..dda35c76f0 100644
--- a/azure/documentdb/quickstart-java-vector-search.md
+++ b/azure/documentdb/quickstart-java-vector-search.md
@@ -27,6 +27,9 @@ The app uses a sample hotel dataset in a JSON file with pre-calculated vectors f
 
 [!INCLUDE[Prerequisites - Vector Search Quickstart](includes/prerequisite-quickstart-vector-search-model.md)]
 
+> [!NOTE]
+> The infrastructure deploys Azure OpenAI with the **Standard** SKU (not GlobalStandard). You can customize the SKU and model parameters using `azd env set` before deployment. See the sample's README for available parameters.
+
 - [Java 21](/java/openjdk/download) or later
 
 - [Maven 3.6](https://maven.apache.org/download.cgi) or later
diff --git a/azure/documentdb/quickstart-nodejs-vector-search.md b/azure/documentdb/quickstart-nodejs-vector-search.md
index 95a8e08ff3..5de2f82f56 100644
--- a/azure/documentdb/quickstart-nodejs-vector-search.md
+++ b/azure/documentdb/quickstart-nodejs-vector-search.md
@@ -28,6 +28,9 @@ Find the [sample code](https://github.com/Azure-Samples/documentdb-samples/tree/
 
 [!INCLUDE[Prerequisites - Vector Search Quickstart](includes/prerequisite-quickstart-vector-search-model.md)]
 
+> [!NOTE]
+> The infrastructure deploys Azure OpenAI with the **Standard** SKU (not GlobalStandard). You can customize the SKU and model parameters using `azd env set` before deployment. See the sample's README for available parameters.
+
 - [Node.js LTS](https://nodejs.org/download/)
 
 - [TypeScript](https://www.typescriptlang.org/download): Install TypeScript globally:
@@ -180,6 +183,9 @@ touch src/utils.ts
 
 ----
 
+> [!TIP]
+> Unlike some databases, DocumentDB allows you to create and drop vector indexes at any time after container creation. You don't need to define the vector indexing policy at container creation time.
+
 ## Create code for vector search
 
 ### [DiskANN](#tab/tab-diskann)
diff --git a/azure/documentdb/quickstart-python-vector-search.md b/azure/documentdb/quickstart-python-vector-search.md
index d97e213d0d..3eb4410a3d 100644
--- a/azure/documentdb/quickstart-python-vector-search.md
+++ b/azure/documentdb/quickstart-python-vector-search.md
@@ -29,6 +29,9 @@ Find the [sample code](https://github.com/Azure-Samples/documentdb-samples/tree/
 
 [!INCLUDE[Prerequisites - Vector Search Quickstart](includes/prerequisite-quickstart-vector-search-model.md)]
 
+> [!NOTE]
+> The infrastructure deploys Azure OpenAI with the **Standard** SKU (not GlobalStandard). You can customize the SKU and model parameters using `azd env set` before deployment. See the sample's README for available parameters.
+
 - [Python](https://www.python.org/downloads/) 3.9 or greater
 
 ## Create data file with vectors
@@ -156,6 +159,9 @@ touch src/utils.py
 
 ----
 
+> [!TIP]
+> Unlike some databases, DocumentDB allows you to create and drop vector indexes at any time after container creation. You don't need to define the vector indexing policy at container creation time.
+
 ## Create code for vector search