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Structured prompt framework for multi-domain workflows (reducing cognitive load)

OpenAI Developer Community March 24, 2026
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Really like this framing — especially the distinction between structure and phrasing.

I’ve been using something similar, but more as a small pipeline:

Input → Interpretation → Constraint → Reduction → Output → (Optional Validation)

  • Interpretation clarifies the task before generation.

  • Constraint defines format, scope, and what “done” looks like.

  • Reduction pushes toward the minimum viable useful result instead of maximum completeness.

  • Validation is helpful for higher-stakes cases like math, billing, or compliance.

The part that feels most important in practice is defining done inside the constraint — e.g. usable without editing, fits on one screen, directly actionable.

Your clinic example shows this well: messy input in, multiple usable artifacts out, no reformatting.

That feels less like prompting and more like building a reliable transformation layer.

Curious how you’re handling incomplete or ambiguous inputs — seems like that’s where the interpretation step becomes the main control point.

Discussion in the ATmosphere

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