Cheaper Tokens & Bigger Bills: Industry Challenges
The price of a token keeps falling. The bill for running AI agents keeps rising. The two facts are connected: cheaper intelligence makes more workflows viable, and agents consume far more than a chat ever did. Every step of an agent loads history, calls tools, reads long results, retries and revises, and much of what it sends to the model has been sent before.
Two of our earlier articles frame the problem. Beyond Copilot [1] showed that consumption climbs with the level of autonomy, and that context engineering is both the primary quality strategy and the primary cost strategy. When AI Becomes More Affordable, Measuring Value Gets Harder [2] argued that tokens are the wrong unit for executives and that the right one is the business outcome. This article asks the next practical question: what is being done about context and output, and what options does a technology leader have?
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