Check an AI-written answer with a claim-by-claim review

Fluent writing is easy to read and easy to trust. When an AI-generated answer contains dates, figures or recommendations, review the claims individually before deciding whether the whole paragraph is useful. You do not need to investigate every adjective with the same intensity.

First, highlight statements that a reader could verify: a product supports a feature, a service costs a particular amount, a report was published on a date. Separate these from suggestions or clearly labelled examples. This gives you a factual checklist instead of a vague feeling about quality.

Second, open the underlying primary source. For a feature, use the product's current documentation; for a statistic, locate the original report and its definition. A link that opens successfully is not enough. The page must actually support the sentence, including its scope and date.

Third, mark each claim confirmed, corrected or unresolved. If a source describes one country, avoid rewriting it as a worldwide rule. If the evidence supports an estimate, do not present it as a precise count. Remove unresolved claims when they are not essential, or state the uncertainty plainly.

For example, a draft might say a free plan allows unlimited exports while the source describes unlimited projects. Those are different claims even though the wording looks similar. This example is invented to illustrate the review step. NIST identifies confabulation as a generative AI risk; a claim ledger is one practical editorial response. Keep the ledger short enough that you will actually use it.