From Strategy to Concepts
Turning AI bets into tangible product experiences
Company
Instructure
Role
Senior Product Designer
Website
instructure.com
Industry
Education
Date
July 2025
The Story
Instructure set an ambitious bet: no teacher should start from scratch. Leadership outlined this vision in a high-level AI strategy deck. My role as the design lead was to translate that abstract strategy into actionable product concepts, wireframes, and prototypes that could guide decision-making and inspire alignment across teams.
The Challenge
Strategy decks are inspirational, but they don’t show what the future looks like in practice. They describe opportunities and risk, but not how a teacher or student would actually experience them. The challenge was to close the gap between vision and product: how to make strategy actionable for design and engineering, how to validate opportunities before investing in development, and how to maintain alignment while exploring multiple directions.
My Role
I led the design process from strategy annotation to prototyping, facilitating workshops for ideation, mapping, and prioritization to align product managers, engineers, and leadership. I introduced AI-assisted design tools like Lovable and AI flows in Figma to accelerate validation. Throughout the process, I helped shape decisions by organizing ideas, prioritizing opportunities, and connecting concepts back to the strategic bet. The resulting design artifacts, including wireframes, prototypes, and annotated frameworks were used in leadership reviews and roadmap discussions.
The Design Process
Annotating the Strategy
I broke down the strategy deck into digestible pieces and added insights from previous teacher research to ground the vision in real needs. I mapped the full assessment cycle, identifying possible issues at each step, and created Jobs to Be Done and How Might We questions to help the team empathize with teachers and frame opportunities effectively.
Concept Generation
I facilitated open ideation sessions with my triad, where every idea, no matter how rough, was encouraged. Afterward, I organized the ideas into themes, connected them back to the strategic bet, and helped prioritize which ones could realistically be tackled within the next year.
Validation with Management
I presented the concepts to product leadership for feedback, then narrowed the scope to the most promising and feasible ideas to move forward into design exploration.
Wireframes & Explorations
Translated validated ideas into low-fidelity wireframes. Shared early explorations in triad reviews for quick validation.
Rapid Prototyping
I introduced Lovable, a rapid prototyping tool, into our process to build end-to-end flows and validate ideas in hours instead of weeks. By combining AI-assisted generation with manual iteration, we were able to test multiple directions quickly and effectively. This marked a significant workflow shift. AI became part of our design process, not just the product vision. The result was faster validation, more iterations, and stronger cross-functional alignment before moving into high-fidelity design. These prototypes were later used in leadership reviews to illustrate what the AI strategy could look like in practice.
The Outcome
The outcome was a set of clear design artifacts that made the AI strategy actionable. The prototypes were used directly in roadmap and investment discussions, helping leadership gain clarity on which AI opportunities to fund first. The team also gained confidence that AI was no longer just a vision, but a tangible product direction.
The Impact
Strategic alignment: Prototypes replaced abstract slides as reference points for triads.
Faster decision-making: Leadership could evaluate trade-offs visually before development.
Workflow innovation: By adopting Lovable and embedding AI into design, we evolved from static decks to living prototypes at a much faster pace.
Cultural shift: Design became the bridge between vision and execution in Instructure’s AI initiatives.