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What is Constraints?

Also called: negative instructions · rules

Constraints are the explicit rules in a prompt — length limits, banned words, required elements, things never to do — that stop the model drifting toward generic output.

Models default to safe, average output: medium length, hedged claims, familiar clichés. Constraints override the defaults. "Under 120 words", "no hype words", "mention the order number", "never promise a refund date" — each one removes a way the answer could go wrong.

Too few constraints and the output drifts; too many and it becomes brittle or contradictory. Five well-chosen rules usually beat fifteen.

Example
Rules: max 60 words · no exclamation marks · keep "Chairside" capitalised · do not mention competitors · end with one question.
How to use it well
  1. Write one rule per line; the model treats lists as checklists.
  2. Prefer positive rules; keep "never" for real risks.
  3. Test a constraint by removing it — if nothing changes, cut it.
Go deeper
Constraint Calibration (course)Negative Instructions (free course)
Related terms
Output formatGuardrailsPromptAll terms →

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