A draft can link to the right announcement and still tell readers that an experimental feature is on by default. The citation looks reassuring precisely because the destination is legitimate. Opening the page is only the beginning of checking the sentence.
Treat the claim and its supporting passage as the unit of factual review. A working link is not a completed check, and a long bibliography cannot compensate for a detail that changed on its way into the article.
Make the writer bring the support
Ask for the proposed claim, its source URL and the exact supporting passage together. Keep this working record beside the draft rather than sending the editor on a second research assignment.
The distinction matters when pricing, release conditions or statistics carry the argument. Finding a relevant page and finding support for the actual sentence are different tasks. If the support is missing, the draft is not ready for an editor merely because it reads smoothly.
For a statistic, follow the citation back to the original study where possible. Record the source date and the context in which the figure applies. A recent article repeating an older number does not make the underlying measurement recent.
The editor still needs to open the source. A pasted passage is a convenient place to begin, not evidence that the passage exists or that its surrounding text agrees with the draft.
Compare the condition, not just the figure
Read around the cited passage. Does the result apply to an estimate, a beta feature, a particular region or a limited group? Is the claim about a measured outcome or a proposed capability?
A number can survive a rewrite while its meaning does not. Removing an estimate qualifier or turning an optional feature into a default changes the promise the reader receives. Matching the digits cannot settle those questions.
Keep the same discipline when revising. Adding an approximation word to an unsupported figure does not give it a source. Find support for the narrower claim if it matters; otherwise remove it. A confident sentence should not survive merely because somebody has already spent time polishing it.
A small team should reduce the hunt, not disguise the gaps
The strongest objection is time. A small blog cannot give every line the same attention as a contested product claim. Numbers, dates, names, quotations and statements about products or competitors deserve early attention because the detail can change a reader's decision.
Use that priority to order the work, not to certify whatever remains unchecked. A spot check establishes what happened to the sampled claims. It does not verify the others. If the review budget cannot cover the factual load, fewer claims are a better compromise than a reassuring link beside each one.
Starting from an interview, a recorded talk or earlier work can shorten the search for support. It also makes the additions easier to identify. But an owned recording does not make every remembered fact current, and a model's addition should not inherit the authority of the original speaker.
No fixed number of minutes establishes that this review is complete. The useful endpoint is knowing which claims have support and which were removed or still need work.
Let automation prepare the comparison
A second AI pass can challenge the wording and identify places to inspect. A script can help check whether a proposed quotation appears on a page. Both can make the human comparison easier.
Neither result establishes that the source supports the article's interpretation. A literal match can omit the qualification immediately before it. Another confident model response is still not the source text.
Keep a human responsible for the final claim-to-source decision. Ask tools to bring the relevant material into view, then judge the relationship rather than accepting the tool's approval as another citation.
The short fields are still publication
Google's guidance on generative AI content calls for manual factual review before publishing, including titles, meta descriptions, structured data and image alt text. It also recognizes useful AI-assisted research and structure. This is not a ban on the tool or a promise of rankings after review.
Writing those fields before generating the body can limit what the model fills in. Giving them a separate final pass catches a different problem: whether the finished page still says what those fields promise. Choose the order that fits the work, but do not let either approach exempt the fields from review.
Then read for the reader. A fully supported article can still avoid the question, bury the answer or connect its sentences badly. Factual approval and editorial usefulness are separate judgments. Finish both before publishing; the reader needs a reason to trust the argument, not merely somewhere else to click.