ask-questions-if-underspecified

To clarify ambiguous requirements, prompt users with essential clarifying questions targeting objective, scope, constraints, environment, and safety before any work begins. This must-have-questions-first approach locks down acceptance criteria, confirms key assumptions, and reduces rework caused by misinterpretation.

Preventing AI assistant misinterpretation of underspecified requests requires prompting for essential details before acting. Acknowledging must-have questions first and waiting until key assumptions are confirmed ensures alignment and reduces misinterpretation across multiple plausible interpretations.

You need to ask clarifying questions for software requirements discovery whenever a request has multiple plausible interpretations across objectives, scope, constraints, environment, or safety. Engaging with targeted questions before starting a complex feature ensures alignment and minimizes rework.

Yes, this clarifying questions approach works for complex feature scope and safety constraints by identifying those exact dimensions during discovery. It applies a lightweight, must-have questions first methodology to minimize user effort while maximizing correctness before proceeding.

An AI assistant proceeds without confirming key assumptions because it lacks a mechanism to pause and ask clarifying questions. Applying a discovery prompt to acknowledge must-have questions first ensures it does not proceed until key assumptions are confirmed or defaults are accepted.