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Re-engineer something you own

Convert a notebook transformation into a dbt model and prove parity

  • When a transformation only exists as a notebook someone runs by hand before the numbers go out.
  • When a notebook's cells are the real production logic and nobody can rerun them the same way twice.

Convert a notebook's transformation logic into a version-controlled dbt model and prove its output matches the notebook's last accepted run. Covers the conversion and its parity proof, not the notebook's exploratory or ad hoc analysis steps.

Area
Transformation
Runs on
  • Microsoft Fabric Lakehouse
  • Microsoft Fabric Warehouse
  • MotherDuck
  • DuckDB
Built with
  • dbt
Readiness
SupportedEverything this Recipe composes runs today, without a case that proves this exact shape.

Sample This Recipe has not been materialized in the Cookbook repository yet. Its trigger, description, prompt, agent guidance and acceptance conditions, and the explanation below, are prototype drafts. Its name, job, area and readiness come from the reconciled Cookbook seed snapshot. Readiness is a separate question from this one: it says whether the capability exists, not whether the writing has been reviewed.

Use this Recipe

Use the VibeData Recipe `notebook-transformation-to-dbt` at https://getvibedata.ai/cookbook/notebook-transformation-to-dbt Read the Recipe and execute it in the context of the current Intent.

Recipe id notebook-transformation-to-dbt · Not yet materialized in the Cookbook repository, so the pointer addresses this page.

Verified by

What has to be observably true before this Recipe is finished.

  • the model's output matches the notebook's last accepted run on the agreed comparison slice
  • the transformation logic runs without manual cell-by-cell execution
  • a repeated run of the model produces the same result
  • the notebook is not deleted in the same change that introduces the model
Recipe promptThe task specification the agent reads. Reference only — it is not what you copy.
Deliver: Convert a notebook transformation into a dbt model and prove parity.

Convert a notebook's transformation logic into a version-controlled dbt model and prove its output matches the notebook's last accepted run. Covers the conversion and its parity proof, not the notebook's exploratory or ad hoc analysis steps.

Execute inside the current Intent. Its Domain, repository, platform, environment and attached sources are the context for this work — read them rather than asking for them.

The work is done when:
- the model's output matches the notebook's last accepted run on the agreed comparison slice
- the transformation logic runs without manual cell-by-cell execution
- a repeated run of the model produces the same result
- the notebook is not deleted in the same change that introduces the model

Report the evidence for each condition above with the result. A condition you cannot meet is something to say, not something to work around.
Agent guidanceHow the agent approaches the work, and what it will not do.

Write down the behaviour that has to stay constant before you touch the current form, and get that agreed. Rebuild in an isolated copy, then reconcile old against new at the grain the consumers read. The reconciliation is the deliverable; the diff is not.

Composes

  • dbt model authoring and layering
  • dbt in the project
  • isolated-copy execution and gate verification

Asks first

Semantic decisions the Intent cannot supply. Never context Studio already holds.

  • which Fabric target this work lands on, when the Domain carries both a Lakehouse and a Warehouse

Guardrails

  • Build in an isolated copy. Production is read, never written.
  • Do not edit the object being held constant. Parity that required a change to the original is not parity.

What you need

  • Microsoft Fabric Lakehouse, Microsoft Fabric Warehouse, MotherDuck, or DuckDB.
  • A dbt project you can build, and read access to the models it starts from.
  • dbt in the project, or the intent to add it.

How it goes

  1. Name the thing you own, and what about its behaviour has to stay the same.
  2. Let it read the current form and write down the behaviour it is holding constant.
  3. Review the design before any SQL is written. Grain first.
  4. Let it rebuild in an isolated copy of your estate. Production is untouched throughout.
  5. Reconcile the new form against the old one, row by row.
  6. Read the acceptance conditions. They are the contract; the diff is not.

What you end up with

The deliverable, in your own repository, as transformation work a reviewer who knows the project reads as native to it. Alongside it, the evidence for every one of the acceptance conditions above — which is the part that is still there in three weeks when somebody asks.

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