What changes when intelligence becomes infrastructure. Interface layers, compute economics, the new shape of software, organisational reconfiguration around inference.
Intelligence is becoming a utility input, and the consequences worth tracking are structural rather than capability-level. Once inference cost falls by orders of magnitude, the question stops being what a model can do and becomes what gets rebuilt on the assumption that reasoning is cheap and abundant.
That reorganisation runs deeper than product features. It changes the unit economics of software — marginal cost returns to compute after two decades of sitting near zero. It changes the shape of interfaces, as the visible form retreats and the abstraction rises. And it changes the structure of the organisations deploying it: headcount that existed to move information between systems is the first thing re-examined.
The failure modes are structural too. Systems that demonstrate strong capability on a bounded task stay brittle when run continuously, and the gap between demo reliability and deployment reliability is where most enterprise AI budgets are currently disappearing.
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