The engine behind the answer: our updated audit of how AI models handle Iran in Persian

Earlier this year we published on how AI models source and frame Persian-language answers about Iran. Here's how our understanding of the testing infrastructure has evolved since then.

tbd/con update #4: last call, four days left to pitch

woohoo!

Re:noted #2: We know who we’re competing against. So what do we do about it?

Initial survey results show newsroom mindsets are shifting toward service, but reliance on generic value claims still holds us back.

Re:filtered #31: What counts now

Reach is rented. Outcomes are yours. Revisiting lifetime civic value.

tbd/con update #4: meet the review crew

Keep the pitches coming.

Re:noted #1: A Service Desk newsletter + challenge for you

Restarting our Field Notes newsletter.

Habit ≠ loyalty

A retention curve can't distinguish between them. The difference only shows when something breaks.

Re:filtered #30: Foraging after the funnel

A great tit, a screaming hairy armadillo and a reader chasing a rabbit hole all obey the same rule. A fifty-year-old idea from ecology, as AI reroutes how people find things.

AIdas in action: how five models handle Iran's hardest (and some biased) questions

The same questions, asked six ways in Persian and English, scored for whose side each answer takes and where the models find their sources.