clarify-first

To resolve ambiguity in software requirements, you must employ targeted questioning to define scope, data models, and API contracts before any implementation begins. This prevents wasted development effort and avoids misinterpretations that lead to costly rework.

Gathering requirements for high-risk operations with undefined scope requires asking precise, numbered questions to resolve uncertainty. This ensures adherence to artifact-first principles by preventing premature coding and establishing clear API contracts.

The best way to define API contracts and data models from unclear requests is through targeted questioning that identifies missing specifics. Asking precise questions about metrics and functional aspects ensures scope definition before development starts.

You need to clarify scope for an ambiguous user update request when the request lacks clear parameters regarding UI, data fields, or performance. Detecting this ambiguity early prevents misinterpretations and ensures accurate data models are defined.

Yes, this approach works for preventing premature coding in artifact-first workflows by managing ambiguous requests through targeted questioning. It enforces scope definition and data model agreement before any implementation logic is written.