AI can dramatically speed up individual tasks like research synthesis, prototyping, and code generation, but that doesn't automatically make the entire product development process faster. Often the work doesn't disappear—it shifts into review, verification, refactoring, or downstream teams, creating hidden costs that can erode the initial gains. The real question isn't whether AI increases local productivity, but whether it improves the whole system's ability to turn ideas into reliable products without accumulating technical debt, instability, or rework.