Launching the AI Assistant under a tight three-month timeline required overcoming both moving product targets and complex user mental models. With the underlying AI code and UI continuously shifting prior to code freeze, maintaining prompt accuracy was a constant hurdle. Enterprise designers also faced a steep workflow adjustment: understanding that the AI Assistant was designed to kickstart prototypes rather than deliver finished, fully functional files, requiring fine-tuning to complete. On the business side, failing to bridge this learning gap threatened low feature adoption and increased enterprise churn risk.

To manage these constraints and align internal stakeholders, the project relied on a centralized storyboard framework for cross-functional content and developed engineering-to-sales readiness reports to clearly map confirmed capabilities, upcoming features, and off-limit topics.