Old facts survive a rewrite with a new date. The useful response is a targeted correction with an observable acceptance check. That keeps the repair tied to the problem instead of turning it into an open-ended redesign.
Find the likely cause
The update changes prose but does not recheck volatile details.
Treat this as an explanation to verify against the actual work. Look at the input, the relevant decision, and the final result together. If the evidence does not support this diagnosis, investigate the mismatch before applying a convenient but unrelated fix.
Make the targeted correction
Identify time-sensitive claims and verify them before publication.
Fact checking requires tracing important claims to evidence rather than asking the same model to reassure itself.
Check that the repair worked
Record when decision-critical details were last checked.
Repeat the check on the final version that the reader or customer will encounter. An approved draft, a preview, and a published result can differ; the acceptance decision should concern the version people actually use.
Prevent the next related failure
A separate issue to watch for is this: statistics lose their denominator and context. Restore the population, period, method, and comparison needed to interpret it.
Monitor the useful outcome
Track unsupported claims found before publication and recurring categories of factual error.
Keep a short record of the original symptom, the evidence behind the diagnosis, and the result of the acceptance check. That record makes the solution reusable when the same condition appears again, without assuming that every superficially similar problem has the same cause.