AI tools are delivering real productivity gains in software engineering, faster features, less boilerplate, but speed has never been free. This essay explores how acceleration can quietly erode review depth, increase technical debt, thin system understanding, and limit skill formation through reduced exposure to hard problems. Drawing from observations and recent research (e.g., Daniotti et al. in Science), it argues for conscious trade-offs rather than defaulting to more output.