Inside the dbt Wizard harness: building an agent that thinks in DAGs
Ask an analytics engineer to rename a column and they won't start with the SQL. They'll check what reads it downstream, which tests and dashboards will break, build only what changed, and compare the data before anyone reviews it. The dbt MCP server and agent skills can teach a coding agent those steps, but they can't make sure it follows them every time, builds on what's changed, or shows you the data diff before you review the changes.
We built dbt Wizard around a different idea. Wizard works like an analytics engineer: it thinks in DAGs, tests and fixes its own work, and keeps you in flow, so you review a working change instead of a first draft. None of that comes from the model; it comes from the harness, workflows, and UX we built around it.
Run parallel agents, review data diffs and lineage next to the code, and validate changes against your warehouse. Join the Wizard Desktop waitlist.