An AI assistant writes: “This coffee cures a headache.” The product brief says only that it is medium-roast coffee from Đắk Lắk. The sentence reads smoothly, but the source does not support its promise.
This is a small example of a review step that belongs in an AI-assisted workflow. A better prompt can improve the draft; it cannot supply missing evidence.
Keep a source beside the draft
Use the approved product sheet, original document or brief. For each factual statement, ask where the evidence comes from. If you cannot point to it, mark the statement as unverified rather than letting fluent wording turn it into a fact.
Separate editing from adding claims
Changing the tone does not require a new promise. “Medium-roast coffee from Đắk Lắk” can be rewritten for clarity without becoming a claim about health or guaranteed results.
Give the reviewer a concrete next action
The next action might be to remove the claim, ask for evidence or flag a missing detail. Saying “make it better” leaves the decision unclear. Saying “remove the unsupported health claim and keep only the source-backed product facts” identifies the problem and the boundary.
Recheck the rewrite
A corrected version can introduce another mistake. Check names, numbers, dates and the call to action again. Record which source you used and why you changed a claim, so a colleague can follow the decision.
Try the exercise
I built an interactive version of this example in my AI Practicum. Try the first task without signing up: compare a coffee draft with the facts, choose a next step and read prepared feedback. This first example does not call a live AI model.
My two AI courses are currently open for free testing: the Practicum has 93 lessons across 13 modules, and AI for marketers has six introductory lessons. A free account saves Practicum progress after lesson one; AI practice responses have usage limits.
Which review decision would you add to this workflow?
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