END-TO-END UX — DISCOVERY → FLOWS → HI-FI → PROTOTYPES → HANDOFF
A calm system that helps people stick to routines
Research-led UX for planning, edge states, and handoff-ready specs—built for fast iteration and clarity
ROLE
UX Designer
EXPERTISE
UX · Prototyping · Design Systems
YEAR
2024
LifeSync is an adaptive routine + habit system designed to help users stay consistent when real life changes—unexpected tasks, low-energy days, missed routines, and shifting priorities. I translated user + business needs into clarity-first flows and scalable UI patterns, focusing on reducing decision fatigue and helping users recover fast after slip-ups.
The work covers end-to-end UX—problem framing, flows + IA, hi-fi screens, interactive prototypes, and handoff-ready specs (states, variants, and edge cases) so engineering implementation stays smooth and consistent.
Timeline
5 weeks — Discovery → flows/IA → hi-fi → prototype → handoff. Shipped 22 screens, 28 components, edge states + dev-ready specs for smooth implementation.
Background
Most habit apps assume stable days and reward perfect streaks—when life gets messy, users face guilt + complexity, leading to drop-offs. Users don’t need “more reminders”; they need a system that adapts—reduces cognitive load, supports recovery after misses, and turns long-term goals into realistic daily actions.
LifeSync focuses on fast iteration + clarity: designing mechanisms that help users choose the next best step, stay motivated without pressure, and maintain progress even when routines break.
End-to-end UX: discovery → flows → hi-fi → prototype → handoff—built to reduce cognitive load, improve follow-through, and keep decisions trustworthy.
Research & Insights
Ran quick interviews + pulse surveys to find why routines break (overplanning, guilt loops, notification fatigue, unclear priorities). Synthesized into 2 core JTBD, mapped friction points, and defined success metrics: time-to-plan ↓, follow-through ↑, perceived control ↑
Design & Prototyping
Mapped core flows: onboarding → goal setup → routine generation → daily check-in → reschedule/recovery. Started with low-fi, then shipped hi-fi UI with clear hierarchy, accessible type, and reusable components. Prototyped key interactions: adaptive suggestions, one-tap reschedule, and minimum-effort mode for low-energy days.
System & Handoff
Built a scalable UI system: tokens + components + variants + edge states (empty/loading/error/recovery). Delivered handoff-ready specs (interaction notes, redlines, states) so implementation stays fast, consistent, and easy to extend.
LifeSync is designed for real life—adaptive plans, clear priorities, and graceful recovery—so users keep moving even on imperfect days.
Adaptive Scheduling
Clarity & Hierarchy
Recovery & Reschedule
Adaptive Scheduling
Generates flexible routines from goals, available time, and real constraints—then auto-adjusts when the day shifts (low energy, surprise tasks, missed blocks) so the plan stays realistic.
Clarity & Hierarchy
A “Today” view that surfaces 1–3 priorities with a clear next action. Reduces decision fatigue with progressive disclosure, so users always know what to do now.
Recovery & Reschedule
Slip-ups don’t reset momentum. Users can one-tap reschedule, switch to Minimum-Effort Mode, and continue with a smaller win—keeping consistency alive instead of breaking the streak.
Outcomes from LifeSync’s end-to-end UX work—focused on clarity, follow-through, and recovery.
Reduced planning friction
Introduced a clarity-first “Next Best Action” and limited daily focus to 1–3 priorities, helping users decide faster and start sooner. Impact → Faster task selection, fewer what now? moments, higher perceived control.
Improved consistency through recovery
Designed one-tap reschedule, minimum-effort mode, and non-punitive streak logic so missed days don’t feel like a reset. Impact → Higher return-to-routine behavior and stronger real-world adherence signals.
Scalable foundation for shipping
Built a reusable component system and state-driven flows (empty,loading,error,recovery) to keep experiences consistent as features expand. Impact → Cleaner handoff, faster iteration loops, easier future expansion.
Learning
Consistency isn’t motivation—it’s friction management + graceful recovery.