A new method, ReSAIL, is introduced to mitigate performance collapse in iterative agent self-distillation. ReSAIL selects interaction steps where privileged information most strongly changes the teacher's predictions and balances distillation losses across trajectories. This results in substantial gains in final-cycle success rates for AI agents over three cycles.