Sophisticated AI coding assistants have significantly transformed the developer workflow by facilitating rapid code creation and iteration through AI collaboration, shifting essential skills from manual coding to problem formulation and solution evaluation. Despite this evolution, the tech industry's fixation on productivity metrics remains, although these metrics often fail to capture true developer productivity, especially as AI increasingly contributes to code production. Developers face productivity barriers such as technical debt and lack of documentation, which can be mitigated by focusing on enhancing developer experience through automation and streamlined workflows. This anti-metrics approach emphasizes the importance of efficient practices like continuous delivery and monorepos, fostering an environment of clear ownership and collaboration. While metrics can indicate process issues, the real impact on productivity comes from balancing people, practices, and tools, ultimately creating a more supportive and efficient development environment.