AI success depends on business outcomes, not usage vanity metrics

Imagine a NASCAR team where leadership decides the winner is the car that burns the most fuel. The crew chief tunes every engine to run rich and wasteful. Drivers ride the gas and the brake at once. The telemetry shows record fuel consumption. The car finishes dead last.

For a stretch this year, wasteful consumption metrics drove AI measurement programs. Companies stood up internal leaderboards ranking employees by how many tokens they burned. A Meta employee built one, crowned the top "token legends," then quietly took it after the numbers leaked externally. By spring the trend had a name: tokenmaxxing.

By the start of summer the inevitable backlash arrived, with companies like Uber acknowledging they’d already spent their entire AI budget for the year in a matter of months.

CTO, ActivTrak.

More recently, the inevitable swing toward using the minimal number of AI tokens (tokenminning) leads to the same problem....

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