These past couple of days I’ve been reading a bunch of “address profiling” reports. The labels, the clustering, and the fund-flow diagrams all look pretty good, but I’ve always had reservations in my gut. To put it plainly: the same pool of funds gets broken up into dozens of shell addresses and then routed around in circles, and the clustering feels like in street photography—forcing job labels on random pedestrians. Sometimes it’s scary-accurate, and sometimes it’s just a pure misclassification.

Especially now, with Layer 2s trading jabs with each other over TPS/fees/subsidies, the on-chain traffic suddenly changes. A lot of what people call “smart money migration” is actually just grabbing subsidies and lining up across cross-chain bridges. The tags haven’t even been updated yet, yet they’re already trying to set the narrative… I trust data, but only raw data: who comes first and who comes last in the queue, how the same amount of money moves, and traces of failures or withdrawals. I also use intuition—mainly to remind myself: don’t treat models like people. That’s it for now.