[Case 02]
Helping users plan their day by working with their energy, not against it
Productivity & Wellness
EnergyFlow+
Wellness & Task Management Platform
[Project Overview]
EnergyFlow+ is a wellness-centered task management app that helps users plan their day based on real-time and predicted energy levels. By integrating wearable device data with self-reported insights, the app delivers personalized task suggestions, restorative activity prompts, and clear energy-trend visualizations that support sustainable productivity and ongoing self-understanding.
[Problem Statement]
Many people living with chronic illness, neurodivergence, or mental health challenges experience fluctuating energy, decision fatigue, and overwhelm that make traditional task apps less usable. These tools rely on long lists, deadlines, and consistent capacity, leaving users without guidance on what they can realistically do or when they should do it.
[Industry]
Productivity & Wellness
[My Role]
UX/UI Designer, AI Designer
[Platforms]
Mobile
[Timeline]
Aug 2025 - Dec 2025
[Deliverables]
High Fidelity Prototype
Design System
UX Case Study Report
[Persona]
Lara
HR Manager
“I want a system that helps me work with my energy instead of feeling like I’m constantly falling behind.”
Age: 30
Location: New York City
Tech Proficiency: Moderate
Gender: Female
[Goal]
Reduce stress levels throughout the day while still getting things done
Know when to take a step back and recover versus pushing through fatigue
Build sustainable routines that prevent burnout and recover when it happens
[Frustrations]
Feels overwhelmed when energy is low but tasks remain
Has difficulty prioritizing tasks when mental and physical energy don’t align
Feels pressure to stay productive even when her energy is low
[Process]
[01] User Research
Conducted exploratory, AI-moderated user interviews with Whyzer to understand how people with chronic illness, neurodivergence, and mental health challenges manage fluctuating energy, burnout, and task overwhelm
Performed competitive analysis across productivity and wellness tools (Todoist, Oura, Visible, Sunsama) to identify gaps between energy tracking and task planning
Developed personas using synthesized research themes to capture decision fatigue, emotional needs, and expectations for non-judgmental support
[02] Insights
Users struggle with decision fatigue on low-energy days and need gentle guidance on what to do and when, rather than being faced with long task lists
Existing tools organize tasks but don’t adjust to changing physical and mental capacity, leaving users overwhelmed and burned out
Users value supportive, emotionally validating guidance and are sensitive to intrusive notifications or prescriptive tones
[03 Design Solution]
Designed an energy-based task recommendation system that suggests tasks based on real-time and predicted energy levels
Introduced task breakdown tools, adaptive prioritization, and a restorative “dopamine menu” to support recovery and sustainable productivity
Created calm dashboards with energy snapshots, trend visualizations, and optional guidance to reduce cognitive load
[04] Testing & Iteration
Used ChatGPT and Whyzer AI-assisted data synthesis to quickly surface patterns and validate early concepts, followed by manual review to refine insights
Iterated from paper sketches to low-fidelity and high-fidelity wireframes, refining information architecture and interaction flows
Adjusted tone, notifications, and recommendations to remain supportive and non-intrusive based on research feedback
[Outcome]
Transformed task planning into an energy-aware experience that helps users work with their capacity, not against it
Reduced overwhelm by combining energy insights, adaptive task suggestions, and restorative support
Delivered a wellness-centered MVP that supports sustainable productivity and emotional well-being.
[Key Learnings]
Energy Comes Before Productivity
Users need tools that adapt to capacity, not demand consistency.
Support Must Feel Gentle
Non-judgmental guidance builds trust and long-term engagement.
AI Is a Partner, Not the Decider
AI accelerated exploration, but human judgment ensured usability.