| name | cdo-review |
| description | /cs:cdo-review <plan> — Decision-driven Chief Data Officer interrogation of any plan that touches training data, data architecture, data productization, or data team hiring. Use when validating training-data rights before model work, choosing warehouse vs lakehouse vs mesh, or valuing data assets for productization or M&A. |
/cs:cdo-review — CDO Forcing Questions
Command: /cs:cdo-review <plan>
The decision-driven CDO pressure-tests any plan that touches data strategy. Six questions before any commitment to a data architecture, AI training run, data productization, or data team hire.
When to Run
- Before approving any new ML model training run that uses customer data
- Before signing a multi-year data-infrastructure SaaS contract (Snowflake, Databricks, Fivetran)
- Before productizing any customer data (benchmark report, embedding endpoint, license)
- Before a major data team hire (head of data, CDO, data PM, ML engineer)
- Before M&A diligence — yours or theirs
- When the founder uses the word "monetize" near "data"
The Six CDO Questions
1. What decision does this data drive?
If no decision is unblocked, why are we collecting / training on / productizing it?
- "We might need it later" is not a decision.
- "It feels like a moat" is not a decision.
- A real answer names a specific business call that requires this data.
2. What's the consent provenance for every source?
For each data source: origin, consent flow, data class, intended use.
- 1st-party-TOS-only is weaker than 1st-party-explicit-opt-in.
- Bundled TOS doesn't cover material new purposes (training on PII for foundation models).
- Run
ai_training_data_audit.py if there's any AI use case in scope.
