The wrong million tokens

The article argues that the real AI budget risk for enterprises is not just token volume, but the lack of a measurable cost-per-task model that ties usage to business value. For CIOs and technology leaders, the strategic implication is that IT must instrument agentic workflows with the same rigor as performance and reliability metrics—tracking token economics, cache hit rates, and context design—so AI spend can be justified to finance and scaled without surprise overruns. The biggest takeaway is that controlling how often models are called is only half the problem; organizations also need to reduce the cost of each pass through better prompt architecture and caching.