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 risks—but not how a teacher or student would actually experience them.
The challenge was to close the gap between vision and product:
• How do we make strategy actionable for design and engineering?
• How do we validate opportunities before investing in development?
• How do we maintain alignment while exploring multiple directions?
My Role
• Led the design process from strategy annotation to prototyping.
• Facilitated workshops (ideation, mapping, prioritization) to align product managers, engineers, and leadership.
• Introduced AI-assisted design tools (Lovable, AI flows in Figma) into our workflow for rapid validation.
• Shaped decisions by organizing ideas, prioritizing opportunities, and tying concepts back to the strategic bet.
• Produced design artifacts (wireframes, prototypes, annotated frameworks) used in leadership reviews and roadmap discussions.
The Design Process
Annotating the Strategy
Broke down the strategy deck into digestible pieces.
Added insights from previous teacher research to ground the vision.
Mapped the full assessment cycle and listed possible issues at each step.
Created Jobs to Be Done and How Might We questions to help the team empathize with teachers.
Concept Generation
Facilitated ideation sessions where we deliberately threw in every idea—no matter how rough.
Organized ideas into themes and tied them back to the strategic bet.
Prioritized which ones could realistically be tackled in the next year.
Validation with Management
Presented concepts to product leadership for feedback.
Narrowed down to the most promising, feasible ideas for design exploration.
Wireframes & Explorations
Translated validated ideas into low-fidelity wireframes.
Designed branching flows to capture teacher decision points (e.g., reviewing AI suggestions, aligning to standards).
Shared early explorations in triad reviews for quick validation.
Rapid Prototyping
Introduced Lovable, a rapid prototyping tool, into our process.
Used it to spin up fast end-to-end flows and validate ideas in hours instead of weeks.
Combined AI-assisted generation with manual iteration, testing multiple directions at speed.
This marked a workflow shift: AI became part of our design process, not just the product vision.
Result: faster validation, more iterations, and stronger cross-functional alignment before moving to high-fidelity design.
Used them in initial leadership reviews to illustrate “what the AI strategy looks like in practice“.
The Outcome
Clear design artifacts that made the AI strategy actionable.
• Prototypes used directly in roadmap and investment discussions.
• Leadership gained clarity on which AI opportunities to fund first.
• The team gained confidence that AI was not 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.