This explains one of the biggest misconceptions around AI-assisted development right now: people think faster code generation automatically means faster software engineering. But the real bottleneck was never typing code — it was understanding systems, constraints, tradeoffs, scaling behavior, and long-term maintainability. The “vibe fixing” part especially feels real. A lot of teams are accidentally replacing deliberate engineering with endless prompt-repair cycles that only look productive on the surface. Feels like the companies that survive this shift won’t necessarily be the ones generating the most code, but the ones building the strongest review, architecture, and decision-making processes around AI-assisted workflows.