Reducing token consumption during runtime is only a small part of the cost optimization process in AI systems. For developers and product managers, identifying the hidden costs inherent in agentic loops is a serious challenge that goes beyond simple savings in instantaneous token usage.
In fact, precise management of these expenditures in complex agentic cycles requires a deeper look at how models interact and the prevention of unnecessary repetitions in automated processes to ensure the economic efficiency of the project.