CFrame (Common Frame)

Title

CFrame AI Experience Platform

Subtitle

Designing structured, AI-assisted workflows for capturing and interpreting human input.

Overview

CFrame is an AI-driven experience platform focused on transforming subjective human input into structured, actionable insight.

I led product design from concept through prototype, defining how users capture, structure, and interact with data in a way that supports real decision-making rather than just collection.

Problem

Most systems struggle to capture and interpret human experience in a consistent way. Feedback is often unstructured, difficult to compare, and disconnected from actual decision-making.

Key challenges included:

Inconsistent and fragmented data capture
Lack of clarity in how input is interpreted
Limited ability to turn qualitative experience into usable outputs
Need for a scalable system that could evolve over time
My Role
Led product design strategy from early concept through working prototypes
Defined UX architecture and core interaction patterns
Designed structured workflows for capturing and organizing input
Established scalable design system patterns
Collaborated with engineering on AI-assisted functionality
Owned design decisions across multiple workstreams
Approach
Product & UX Strategy
Defined a structured system for capturing and interpreting input
Aligned user needs with product goals and long-term scalability
Focused on building a system, not just a feature set
UX & Interaction Design
Designed workflows that guide users through structured input
Simplified complex concepts into clear interaction models
Built consistent UI patterns to support repeatable use
Design Decisions
Prioritized structure over flexibility to reduce ambiguity
Designed AI interactions to support users rather than overwhelm them
Focused on clarity and consistency across workflows
Built patterns that could scale across different use cases
AI-Assisted Workflow
Developed structured prompting approaches for AI-assisted interaction
Used scoped generation to explore workflow and UI variations
Validated outputs against system rules and UX constraints
Ensured consistency between design, logic, and user interaction
Used AI to accelerate iteration while maintaining control over outcomes
Execution
Delivered end-to-end product workflows and prototypes
Iterated designs through feedback and testing
Defined system-level UX patterns for long-term scalability
Maintained consistency across components and interactions
Outcomes
Established a structured foundation for capturing and interpreting experience data
Improved clarity in complex input-driven workflows
Accelerated iteration cycles through AI-assisted design
Created a scalable product direction for future development