The Five Ways AI Agents Burn Your Token Budget

A practitioner’s confession, with the log files to back it up.

Pull up July 10 in my logs: 52 agent sessions across six projects. 7.3 million tokens of output. 117 million tokens read fresh into context, 1.4 billion if you count cache hits.

That’s one day. A heavy one, but not the record.

I’m not confessing the total. The total is what a small AI engineering team costs to run, and that’s exactly what my setup is: leads, builders, researchers, critics, some working while I sleep. The confession is in the line items. Because when I go through those 52 sessions, they split cleanly into two piles: tokens I’d spend again tomorrow, and tokens I still regret.

Here’s the distinction almost every token-cost conversation misses. People count tokens the way dieters count calories, as if fewer is automatically better. But my healthiest engineering days are often my heaviest. What separates...

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