Enterprise AI is moving through a familiar cycle. At first, organizations went all in, reaching for the largest and most capable models because the technology was exciting and the bill had not yet arrived. When it did arrive, the response was equally predictable: teams began rationing access, reducing experimentation, and searching for less expensive models. Ali Ghodsi, cofounder and CEO of Databricks, has described the early stage of this cycle as “tokenmaxxing,” where consuming more tokens is…
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Why Token Costs Don’t Tell You Whether Enterprise AI Is Working