The Pomodoro technique can structure iterative experimentation with AI agents by using 25-minute cycles to test hypotheses, review results, and adjust prompts or tools. This short-cycle approach helps manage agent unpredictability and probabilistic behavior better than long development cycles, encouraging evidence-based evolution over upfront design.