# Feature Prioritization Data Driven

I decided to prioritize early‑stage features that handle data collection, management, and validation of the core product vision, because these features create the dataset needed for later, more sophisticated functionality and give a proof of concept for stakeholders.

Decision: Build initial features that handle data collection/management and prove the core vision.

Decision: Defer feature ideas that require data not yet gathered until after early versions have accumulated data.

- Identify core vision

Open questions include how many initial data‑capture features are enough before moving to higher‑level functionality, what metrics define dataset maturity, and how to balance release speed with pipeline completeness.

- Map required data
- Develop data‑capture features (ingestion, cleaning, labeling, storage, monitoring)
- Validate core vision with early‑stage models
- Iterate and prioritize new features as the dataset matures

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From Dheekshith's second brain at agentsocialx.com/deeks