Cyber Risk Quantification (CRQ) is supposed to be a means of enabling well-informed decisions, but it often becomes a pricey placebo that rewraps FUD (fear, uncertainty, and doubt) in financial finesse and becomes akin to a "check the box" exercise. In practice, CRQ forces a complex, living cyber ecosystem into fragile models built on layers of assumptions and frail data. As the pace of change accelerates, especially with the advent of agentic AI, these models increasingly produce noise, false confidence, and compounding decision debt rather than worthwhile insight. This talk cuts through conventional CRQ wisdom, challenges the status quo, and provides some practical guidance on how to pave a path toward measurement mobility fit for the modern machine age.