The agent system design coverage in this one is the right frame to watch - the architectural choices being made now for how agents coordinate, escalate, and terminate are going to look obvious in retrospect but feel ambiguous in the moment.
The math breakthrough piece is worth tracking separately. AI proving new theorems isn't a benchmark story - it's a shift in what AI is actually doing versus what we thought it was doing. The line between 'applying known patterns' and 'discovering new ones' is moving in a way that's hard to describe without sounding hyperbolic.
Privacy-wise: default settings being unfavorable isn't a new story but the scale changes the nature of the problem. It's not 'users need to opt out' - it's 'most data exhaust is now AI training data by default.'
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