Fact checking requires tracing important claims to evidence rather than asking the same model to reassure itself.
A practical strategy starts with the decision the work must support. Before adding output, define what a useful result would allow the reader, customer, or team to do. That choice determines which inputs deserve attention and which activities can wait.
Choose the work that matters
- Extract factual claims from the draft.
- Check suitable primary evidence.
- Correct, qualify, or remove unsupported statements.
Read the material from the intended reader’s starting point. Familiarity can hide missing definitions, unexplained assumptions, and jumps in reasoning. A useful edit should make the task easier to understand while preserving the details that make the explanation trustworthy.
An illustrative application
An article about a software workflow could verify current capabilities against documentation and an actual test of the described process.
Treat this as a hypothetical planning example, not a reported customer result. The useful exercise is to identify the necessary evidence, the decision being supported, and the person responsible for checking the work. Substitute actual business facts before applying it.
Five weak points to design around
AI cites sources that do not exist. Generated reference details were accepted without verification. Open each reference and confirm its title, author, and relevant passage.
A real source is cited for a claim it never makes. Topical relevance is mistaken for evidentiary support. Match each important assertion to the actual supporting passage.
Old facts survive a rewrite with a new date. The update changes prose but does not recheck volatile details. Identify time-sensitive claims and verify them before publication.
Statistics lose their denominator and context. A striking percentage is copied without its definition. Restore the population, period, method, and comparison needed to interpret it.
The model is asked to verify its own unsupported draft. Repetition is treated as independent confirmation. Use external evidence and human review for consequential factual claims.
Define success before expanding
Track unsupported claims found before publication and recurring categories of factual error.
Begin with a bounded piece of work and write down what would count as an acceptable result. If the initial attempt fails, identify the specific weak point before increasing volume. A useful strategy gives the team a reason to continue, revise, or stop—not merely another publishing target.