Credibility comes from traceable claims, honest examples and clear authorship. Use AI for assistance, not to manufacture experience or testimonials.
Authenticity is not a list of words to remove. A casual tone can still conceal an invented statistic, while formal writing can be careful and trustworthy.
Separate experience, examples and evidence
If you describe a personal test, record what you actually did and what you observed. Do not ask a model to invent a customer, conversation or failure story and publish it as your experience. Label a constructed scenario as an example.
An honest example
Instead of “our customers saved hours,” write “in this example, a pasted draft contains four blank lines between paragraphs.” The second statement is inspectable without pretending to have measured a business outcome.
Keep a claim ledger
For each important factual sentence, record its source, relevant passage and limitations. A model-generated citation is a research lead, not verification. Open the original source and check whether it supports the exact claim.
If a source is unavailable, narrow the wording or remove the claim. Do not convert an estimate into a precise percentage because precision sounds authoritative.
Explain responsibility
Identify the person or team responsible for publication and provide a correction route. Where it helps readers understand the work, describe how AI assisted the process and what was checked. Google's guidance on generative AI content emphasizes accuracy, quality and relevance; using AI does not exempt metadata or image descriptions from review.
Edit without staging imperfection
Choose wording that your audience can understand. Do not insert mistakes, fake emotion or arbitrary contractions to appear human. Preserve terms that matter to the subject even if a detector dislikes them.
Before publication, use local formatting cleanup only for copied markup or spacing. It does not verify the article or establish who wrote it. See the cleaning methodology for that boundary.