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Coercion combines flexible points, semi-automated optimization and expert guided manual code modification for adapting simulations to meet new requirements. Coercion can improve simulation adaptation efficiency by offloading large portions of work to automated search. This paper identifies requirements and related challenges in coercion, presents methods for gaining insight, and describes how to use these insights to make agile strategy decisions during a coercion. We call our optimization method agile optimization, because it allows users to preempt optimization and flexibly interleave alternative optimization methods and manual code modification, as needed. Agile optimization exploits the combined strengths of human insight and process automation to improve efficiency. We describe a prototype system and a case study that together demonstrate the benefits that can accrue from agile optimization.