Schema validation confirms a workflow is well-formed — every node has the fields it needs, every connection points somewhere real. It says nothing about whether the workflow does the right thing when it actually runs. A perfectly valid workflow can still email the wrong list, or write to the wrong sheet, or run in the wrong order.
Before a generated workflow deploys to a user's live n8n instance, we run it through a sandbox simulation: a dry execution against representative sample data, with every side-effecting step (send email, write row, post message) intercepted rather than actually fired. The simulation traces execution order and the shape of data at each step, so we can catch a workflow that's technically valid but behaviorally wrong before it runs against anything real.
The simulation trace feeds a separate execution-analysis pass that looks for the failure patterns schema validation structurally can't see: a field that will be empty at runtime because an earlier step never populates it, a branch that can never be reached given the trigger conditions, a step order that would send a notification before the record it references has been created.
This is the same "run it, read back what happened, fix what's wrong" loop behind Gydmation's self-healing workflows — just applied before first deployment instead of after a live failure. Catching a behavioral mistake in a sandbox costs nothing. Catching the same mistake after it's already emailed the wrong customer does.
