diff --git a/source/cloud/gcp/vertex-ai.md b/source/cloud/gcp/vertex-ai.md
index c29ce9a9..4382905a 100644
--- a/source/cloud/gcp/vertex-ai.md
+++ b/source/cloud/gcp/vertex-ai.md
@@ -33,6 +33,13 @@ You can find out your current system CUDA Toolkit version by running `ls -ld /us
 
 You can create a new RAPIDS conda environment and register it with `ipykernel` for use in Jupyter Lab. Open a new terminal in Jupyter and run the following commands.
 
+```bash
+# Use a user-writable location for environments and package caches
+$ export MAMBA_ROOT_PREFIX="${HOME}/micromamba"
+```
+
+Setting `MAMBA_ROOT_PREFIX` keeps environments and package caches in a user-writable location.
+
 ```bash
 # Create a new environment
 $ conda create -y -n rapids \
@@ -48,9 +55,11 @@ $ conda activate rapids
 
 ```bash
 # Register the environment with Jupyter
-$ python -m ipykernel install --prefix "${DL_ANACONDA_HOME}/envs/rapids" --name rapids --display-name rapids
+$ python -m ipykernel install --user --name rapids --display-name "rapids"
 ```
 
+Registering the kernel with `--user` installs the kernelspec in the Jupyter user's kernel directory, avoiding permissions errors from writing into the environment prefix.
+
 Then refresh the Jupyter Lab page and open the launcher. You will see a new "rapids" kernel available.
 
 ![Screenshot of the Jupyter Lab launcher showing the RAPIDS kernel](../../images/vertex-ai-launcher.png)