I Ran a Daily AI News Digest for a Month. Here's What Stopped Being News.
After thirty days of summarizing the sector, the launches blurred and the governance stories started mattering more. The signal moved.
I committed to a one-paragraph AI news digest every day for a month, pulling from a handful of sources each morning. By week two the model launches had blurred into one list; by week four the items I actually saved were about agents, regulation, and incidents, not new benchmarks.
The shift was the point. A 'new model beats the old one by a point' stopped feeling like news because it happened constantly. A 'lab got subpoenaed' or 'agent wiped 100 accounts' didn't blur, because consequences don't average out the way specs do.
My digest got shorter on launches and longer on fallout. That's a better read of the field than any leaderboard: the interesting question moved from 'what can it do' to 'what happens when it does it without asking.' The month taught me to weight incidents over announcements.
If you consume AI news, try the exercise. Forcing one paragraph a day exposes which stories are noise by morning. The ones still worth writing about at 8am are the ones the industry is actually living through.