Hi seanpmcn,

Great job troubleshooting that! It is very common for the UI steps in training documentation to occasionally lag behind the platform's rapid evolution, and you navigated that perfectly by exploring the "Create pipeline asset" workflow.

Your experience with the language syntax error is a perfect example of how declarative pipelines (like DLT/SDP) require strict environment settings compared to interactive notebooks. When a pipeline is configured for SQL, the engine expects pure SQL execution, and the inclusion of %sql magic commands (which are meant for interactive Python/notebook shells) will naturally trigger an error.

Architect’s Pro-Tip: When moving from interactive development (using %sql or %python cells) to declarative production (pipelines), I always recommend cleaning up the code into pure language-specific files or standard notebooks. It not only avoids these execution errors but also makes your code much more compatible with Databricks Asset Bundles (DABs) for CI/CD later on.

It’s great that you shared the solution—this will definitely save the next person.