There’s more research on AI search than anyone with a day job can read.

Software follows new research on how AI search finds, ranks and cites sources, as it appears on arXiv and Crossref. Finding a paper doesn’t commit us to writing about it.

A person decides which papers are worth an article. Each one has to answer a question readers have and add something we haven’t already said. A paper that repeats a known finding can update an article we already have, or stay on file without one.

An AI reads the full paper, past the abstract to the last page, and notes its findings, methods and limits, each with the exact words that support it. Software checks every quote against the paper. If the full text isn’t available, or the notes don’t check out, the work stops there.

An AI writes a draft from those notes and our writing rules, in plain English, with a link to the paper. It uses the notes the explanation needs, and the rest stay in our files.

One AI reviewer reads the draft against the paper and asks what readers will come away believing, and whether the paper supports it. If something left out would change that impression, it has to go on the page; a limit kept only in our notes doesn’t count. A second AI reviewer reads only the article, as a reader would, and asks whether it’s worth the time. If a passage could be easier to read without losing anything, it has to be fixed. Required fixes go back to the writer, and both reviewers read the new draft. A draft that still falls short after a few tries is held.

A person reads the finished article and decides whether to publish that exact text, ask for changes or hold it. If the text changes afterwards, it needs a new decision.

Only approved text goes into the site. Once an article is live, software checks the page readers get: its text, its byline and its link to the paper.

A paper can stop at any of these steps, and there’s no quota to fill. When nothing earns a place, nothing is published.