Shapeshifter began with a broader question: how can technology make healthcare and personal health resources easier to navigate for people who may not know where to start?
Early concepts focused on helping users discover specialists, understand healthcare resources, and locate appropriate care. Through user interviews and product research, the project identified a recurring problem around personalization: existing health and fitness tools often provided information, but users struggled with generic recommendations, unclear guidance, inconsistent motivation, physical limitations, and advice that did not reflect their circumstances.
The project evolved into a personalized health and fitness platform centered on goal-based guidance. Users could establish their goals and circumstances through an initial questionnaire, receive tailored workout and nutrition recommendations, track progress, and access educational resources intended to explain the reasoning behind recommendations rather than simply prescribe actions.
The application was built with React, Node.js, and Express, with Python handling AI API integration and processing. The project also incorporated user research into the development process, using interviews to identify problems around accessibility, nutrition guidance, workout consistency, injury limitations, motivation, and the need for greater control over automated recommendations.
A central design consideration was avoiding false precision in health guidance. Rather than treating health, caloric intake, or physical activity as universally applicable numbers, the project explored ranges, customization, and educational context while minimizing the collection of unnecessary sensitive health information.
