Our platform offered content and assessments—but nothing in between. There was no low-stakes, low-pressure space for students to practice applying what they’d learned. And most AI tools available at the time were focused on grading or tutoring, not interaction. We wanted to create something different.

I designed the structure and content logic of an AI-driven practice tool, focusing on how students would engage, recover, and grow in realistic roleplay scenarios. My goal was to support learning through trial and feedback, not performance or grading.

I led the experience strategy for how AI would behave during roleplay: when it would stay in character, when it would pivot to coaching, and how tone, recovery, and feedback would be handled. I collaborated on interface design and worked closely with product and content teams to define branching logic, feedback pacing, and scenario complexity. I also explored options for short versus extended practice arcs, and began mapping what a verbal/audio-first version of the tool could become.

We created a prototype that let learners practice skills in realistic, flexible ways—with space to reflect, retry, and grow. It offered an alternative to quiz-based learning and showed how AI could support confidence-building and agency. The next phase focused on expanding access through an audio-first experience designed for learners who prefer verbal interaction or struggle with text-heavy environments.