The gap between developers' perceived AI coding speed gains and actual measured productivity is the largest blind spot in engineering AI budgeting. Most ROI calculations rely on misleading sticker prices and self-reported metrics, ignoring usage-based costs and system-level outcomes like longer code review times and higher production incident rates.