Richard George Davis

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FAQ

How do you build prompts that prevent fact drift?

Build prompts that prevent fact drift by naming the source, locking non-negotiable facts, listing what may change, requiring uncertainty labels and asking for a final claim check. The prompt should give the model a narrow transformation job, not an open invitation to improvise truth.

June 17, 2026Last reviewed June 17, 20261 min readHow-to

Medium caveat

This answer is practical guidance, not a universal rule. Check the specifics of your site, audience, tools, legal context, and commercial risk before applying it.

Direct answer

Build prompts that prevent fact drift by naming the source, locking non-negotiable facts, listing what may change, requiring uncertainty labels and asking for a final claim check. The prompt should give the model a narrow transformation job, not an open invitation to improvise truth.

Why this matters

This turns the Choice Engine method into a practical prompt-engineering article without becoming a generic prompt list.

How to use it

  • State the task: review, rewrite, summarise, expand or generate options.
  • Paste or reference the locked source.
  • List invariants and transformables.
  • Demand labels for assumptions and gaps.
  • End with a claim-and-caveat audit.

Example

A good prompt says: “Keep the definition, caveat and proof standard fixed. You may shorten structure and examples. Label any inference.” That is stronger than “make this better”.

Caveats and limits

Prompting helps, but it does not replace review. A good prompt reduces drift; the review loop catches what remains.