Why optimizing AI token count alone won't reduce your coding agent costs

A developer analysis on DEV Community argues that measuring AI cost by total token count is misleading, since token type, model choice, and number of retries all affect the true cost of completing a task. A 100,000-token request can cost less than a 20,000-token one depending on how much context is reused versus newly processed. Choosing a cheaper model that requires multiple attempts may ultimately cost more than a pricier model that solves the problem on the first try. The article outlines seven strategies, including protecting reusable context, controlling new inputs, and loading knowledge on demand, all aimed at reducing cost per completed task. The core argument is that the right metric is not tokens spent but the total expenditure needed to reach a correct result.