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Everyone talks about training the model — the data, the compute, the alignment magic. But what happens after the weights are frozen and millions of users start hammering it with prompts? That's inference, and it's a surprisingly deep rabbit hole of engineering challenges that rarely gets the spotlight it deserves. This week I kick off a new series unpacking the full inference ecosystem — from the moment a model completes training to the moment tokens land in your hands.
