The author argues that coding agents should be priced based on the number of failed attempts rather than token consumption. They contend that tokens measure text volume, not the actual work or progress an agent makes. Pricing by iterations, which represent the developer's time spent reviewing and correcting agent outputs, offers a more accurate reflection of an agent's cost and effectiveness. The article proposes a method to log agent actions and calculate iterations per successful task to provide a more honest cost metric. AI
IMPACT Suggests a shift in how AI coding tools are evaluated and budgeted, focusing on developer time and iteration cost over token usage.
RANK_REASON Opinion piece arguing for a new pricing model for AI coding agents.
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