decision-prompt-builder

To prevent rubber-stamping in human-in-the-loop AI workflows, surface 2-3 trade-off questions at key judgment gates before the AI offers any recommendations, forcing human modelers to actively own the decision space.

A decision prompt for AI safety is a mechanism that surfaces minimal, high-impact trade-off questions at judgment gates, ensuring human reasoning guides AI outputs rather than automatically accepting suggested actions.

Generate trade-off questions for problem framing and method choice gates by identifying the single highest-impact judgment required, then producing up to three questions framed as trade-offs for the human modeler to answer.

No, this approach does not require the AI to pre-fill decision artifacts or answer the questions itself, preserving human reasoning by withholding AI suggestions and requiring the downstream system to capture human responses.

Enforce human modeling judgment in prompt design at any gate where modeling judgments are required, such as problem framing, method choice, result verdict, or claim scope, to ensure the human remains in the decision loop.

Yes, you can use this for auditing and traceability by integrating the human answers from the trade-off questions into downstream decision artifacts and logs, ensuring every judgment gate is recorded for review.