The author spent a year integrating AI into their studio's design process, not for speed, but for a richer outcome. Initial expectations of faster sprints were unrealistic, as the team maintained their five-day sprint cycles. Instead of speed, the AI integration led to a more comprehensive and detailed final product, albeit with new challenges. Skepticism from team members was crucial, acting as an unacknowledged quality control to prevent flawed transformations. The author learned to embrace this skepticism, allowing the work itself to validate the process rather than relying on pitches.The focus shifted from optimizing for raw speed, which can lead to "high-speed mediocrity" or "AI slop," to improving the overall quality and depth of the work. The real value of AI, as discovered, lies in its ability to create a complete, cohesive output rather than just accelerating individual tasks. By building all user states and device variations simultaneously, the studio achieved a much deeper product within the same timeframe. This new approach eliminates the "relay race" of traditional sequential design, where one aspect is completed before the next begins.Furthermore, AI enabled a unified "source of truth" by generating documentation directly from the approved working prototype. This eliminates the old problem of disconnected artifacts like PRDs, wireframes, and Figma files that quickly became outdated. Engineers now build from a continuously synchronized system, ensuring that user stories, flow maps, and error conditions always reflect the current state of the prototype. Any inconsistencies or orphaned elements are automatically surfaced for review, preventing the "Frankenstein problem" of outdated information. This ensures that changes are addressed when they are cheap to fix, leading to a more robust and accurate final product.