I was the lead designer on this project, taking initiative to define the AI coach experience. I defined the brand, user experience, and design direction from inception of the AI native product. This project introduced me to advocating for user experience among AI strategy and complex systems. As a main designer, I defined key design patterns/templates and collaborated closely with developers to bring them to life in a functional platform.

I also built and maintained the eval system across different AI features. Partnered with engineers to improve AI quality through experiments, prompt engineering and rapid code tweaks.

The prioritization logic was also shaped through close collaboration with engineering.

Rather than surfacing every possible insight, we aligned on a system that highlights only the strongest few signals. This helped coaches make faster decisions while also keeping inference costs and processing demands under control.

I also prototyped directly with real model outputs and worked with engineering to understand where the pipeline was confident, vague, or inconsistent. That feedback loop helped me design the surfacing, ordering, and review states around how the system actually behaved. As a result, the experience stayed fast when the signal was strong, while uncertain cases still felt clear, reviewable, and gracefully handled.

As an AI-native designer, we're using to pair code, agents, and design tools into pretty simple workflows. With AI-agents (Claude Code, Storybook and Replit), we are able to ship the designe in a much faster speed and stakeholders can validate the feature look and feel without spending time tweaking the details.