A better AI prompt template for work: give it the brief, then check it

The template

A useful workplace prompt explains the task, supplies appropriate context, identifies the allowed sources and defines the expected output. It also makes uncertainty visible. None of this guarantees accuracy; it makes the result easier for a person to judge.

Copy these six lines and replace the instructions with your own:

Task: What should be produced, and why?

Audience: Who will use it, and what do they already know?

Source material: Which supplied information may be used?

Constraints: What must be included, excluded or left undecided?

Output: What structure, length and level of detail will be useful?

Uncertainty: How should missing information and unsupported claims be marked?

Keep the template in plain language. You do not need an elaborate fictional persona to ask for a well-structured first draft.

A worked example

Imagine you need an internal project update. The following is a synthetic exercise, not a client case study:

Draft a 200-word update for a project sponsor. Use only the notes below. Separate completed work, current blockers and decisions needed. Do not invent dates, owners or budget figures. Where the notes do not provide an answer, write “needs confirmation”. Keep the tone direct and neutral. Finish with three questions for the project manager to resolve before this is sent.

Then provide a small set of approved or synthetic notes. Notice that the instruction describes both the output and the boundaries. The result should still be treated as a draft: the model may misunderstand a note, combine unrelated points or fail to follow the instruction.

Review with four questions

First, check fidelity. Can you trace every factual statement back to the supplied material? If an answer cites a source, open it and verify that it supports the claim rather than accepting the citation as proof.

Second, check completeness. Did the draft leave out an important blocker or qualify a decision incorrectly? A fluent summary can be wrong through omission, even when each individual sentence sounds reasonable.

Third, check fitness for the audience. Does the sponsor have enough information to act? Remove confident language that hides uncertainty and background that does not help the decision.

Finally, check the boundary. Does the output contain information that should not be shared with the intended audience? The normal responsibility for review and approval still applies.

Improve the brief before polishing the answer

If the result is weak, diagnose why. Missing context calls for a better brief. Contradictory notes call for a human decision. An invented claim calls for verification and correction. Repeatedly asking for “a more professional version” can polish the wording while leaving the underlying problem intact.

Change one part of the prompt at a time and compare the outputs against the same checklist. Save the version that works with a note about its intended task, the required inputs and the review steps. Do not distribute it as a universal prompt for every department.

Build a small library of complete workflows

A useful team library includes the brief, a safe example, an acceptable output and the checks. Name the owner and review it when the task or tool changes. Retire examples that no longer reflect how the work is done.

Read AI output verification at work for a deeper review approach. The first AI workshop agenda shows how to turn this template into a practice session.

For guided practice, explore prompting and output verification, or talk to Experrt about building examples for your team’s work.