note about curated environment names

Author: Blackmist

articles/machine-learning/how-to-manage-environments-v2.md

@@ -8,7 +8,7 @@ ms.topic: how-to
 author: ositanachi
 ms.author: osiotugo
 ms.reviewer: larryfr
-ms.date: 01/03/2024
+ms.date: 04/19/2024
 ms.custom: devx-track-azurecli, devplatv2, devx-track-python
 ---
 
@@ -77,6 +77,9 @@ You can use these curated environments out of the box for training or deployment
 
 You can see the set of available curated environments in the Azure Machine Learning studio UI, or by using the CLI (v2) via `az ml environment list`.
 
+> [!TIP]
+> When working with curated environments in the CLI or SDK, the environment name begins with `AzureML-` followed by the name of the curated environment. When using the Azure Machine Learning studio, they do not have this prefix. The reason for this difference is that the studio UI displays curated and custom environments on separate tabs, so the prefix is not necessary. The CLI and SDK do not have this separation, so the prefix is used to differentiate between curated and custom environments.
+
 ## Create a custom environment
 
 You can define an environment from a Docker image, a Docker build context, and a conda specification with Docker image.