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Elizabeth H. Cottrell's avatar

Terrific article, Denise, and I had to test the prompt on the draft of a book review I plan to publish next week. I was impressed that Claude recognized that a book review does not lend itself to all of your prescriptions when it opened its response by saying: “Quick calibration before the list: this framework is built for how-to and explainer articles, so a couple of the categories land differently on a book review.”

But then it went on and gave me some excellent suggestions and two brilliant ideas for follow-up articles.

Robin Good's avatar

Denise, this is a useful and practical foundation. Clear titles, focused questions, descriptive headings, accessible pages, credible sources and internal links all help AI systems find and understand an article.

All these are classical SEO tactics adapted to AI search and they can definitely help a machine find a page.

Their limitation is only that they give it little reason to trust the author, return to that source and cite it repeatedly.

I think that in order to obtain this, the next step is to make our judgment and verification process visible.

Two simple examples:

Instead of publishing only an answer, present the key claim as a self-contained unit: the claim, the evidence supporting it, the conditions under which it applies, what you checked or rejected, and the date it was last verified.

When an important idea is still emerging, connect the original claim to a small group of sources that support, challenge or refine it. Then explain what that developing idea means for one specific audience and maintain the page as the discussion evolves.

This creates something more valuable than an optimized article. It creates a stable, attributed reference that shows how the author thinks, checks and connects information.

AI visibility helps you get found. But showing how you choose, provenance and consistent verification are new elements that can give your work real citation power.

What do you think?

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