A mathematical model explains the performance decline of AI agents on longer-duration tasks, suggesting an exponentially decreasing success rate characterized by a unique half-life for each agent. This model indicates that task complexity increases with the number of subtasks, where failure in any subtask leads to overall task failure. Further research is needed to explore the model's applicability across different task suites.