It’s a smart move to raise this question before investing lots of time—because with the Databricks VSCode extension, there are indeed specific limitations when it comes to accessing shared workspace folders that weren't originally created by the extension.

Core Limitation: VSCode Extension Folder Access

According to Databricks' own documentation, the VSCode extension only supports workspace folders it creates itself. Existing shared workspace folders or directories—especially those created directly in the Databricks UI or by IT for collaboration—are currently not supported for direct access/editing through the extension. The extension enforces this restriction for compatibility and stability reasons, and there’s no officially documented workaround for "adopting" a pre-existing shared folder into the VSCode workflow.

What Happens If You Try to Bypass?

• Manual artifact modification (trying to mimic what the extension does by copying project scaffolding/artifacts into your shared workspace folder) generally won't work. The extension expects to manage the workspace's metadata and structure itself, which means "hacking" it is likely to result in sync issues or errors.

• This could introduce inconsistency, data loss, or break future extension compatibility.

• The overwhelming consensus in user forums and the official documentation is that, at the moment, you cannot use the extension to collaboratively edit shared workspace folders unless they originate from the extension itself.

Potential Workarounds

While there isn’t a perfect out-of-the-box solution, here are your practical options:

1. Clone/Sync Notebooks Locally

• One approach is to export notebooks from the shared folder via the Databricks UI to your local machine.

• Then, work on them in VSCode with the Databricks extension (in a project folder it creates).

• Later, manually or via script, re-import updated notebooks back into the shared workspace folder in Databricks.

• This isn't seamless but is safe and officially supported.

2. Use Git Repos as a Mediator

• Set up a Git repo (e.g., on GitHub or an internal Git service) to hold your notebook templates and assets.

• Colleagues use VSCode’s Git integration to collaborate on notebooks. Changes can be merged and tracked outside of the Databricks workspace.

• Periodically, push changes to the Databricks workspace—for example, with a scheduled notebook/script, or via direct import.

3. Wait for Feature Support/Submit Feedback

• If collaborative workspace folder access via VSCode is essential, consider submitting feedback to Databricks; the product team is known to prioritize highly requested features.

Summary Table

Final Verdict

You are not wasting your time by exploring, but you are likely to hit an immovable wall trying to force the extension to operate outside its intended scope. The safest productivity boost, in your case, is to use the Git-integrated workflow for now, and to monitor Databricks' roadmap for more collaborative VSCode extension support for shared folders in the future.