The Five Ways AI Agents Burn Your Token Budget

AI agents can burn through token budgets in five costly ways: endless retry loops with no memory of failed attempts, inefficient code searches that read entire files instead of targeted results, using expensive frontier models for simple tasks, re-explaining the same project context every session, and agents adding unrequested features. Fixing these wastes frees up budget for high-value spending like independent review agents, upfront planning, and running parallel attempts simultaneously.