Fangning - Portfolio Website

Reskillr

AI-powered learning path app

User Research, Wireframe, Prototype

UX Research, Design System,

UXUI Web Design, Product Management

@ Product Designer

Reskillr is an AI-powered learning path app that helps cross-disciplinary professionals reskill or upskill into product management roles. By combining daily curated resources, quizzes, and an AI mentor chat, it transforms fragmented reading into a personalized, trackable, and motivating learning experience.

Duration: 2 Weeks (Design Sprint MVP)

Responsibilities:

Defined the product vision and MVP scope through competitive research and interviews with career changers.

Designed the personalized 3-phase learning system (Foundation / Applied / Capstone) and progression flow.

Built the information architecture, daily learning experience, and AI mentor chat interaction model.

Conducted user testing with 5 cross-domain professionals to validate usability and motivation.

82% Daily Session Completion Rate
Most users completed their daily learning path (avg. 3–4 resources + quiz) within 35 minutes, indicating balanced cognitive load and achievable pacing.
Why it matters: Confirms the app’s “micro-learning” design reduces friction and supports consistency.
+58% Increase in Return Intention
After introducing AI mentor chat and visible streak progress, 7 of 12 users reported stronger motivation to return daily (“feels guided and rewarding”).
Why it matters: Demonstrates that lightweight gamification + personalized reflection increase perceived accountability.
Onboarding Time Reduced from 12 min → 4.5 min
The AI intake chat automatically generated personalized 3-phase learning plans after three short questions, replacing manual goal setup forms.
Why it matters: Shorter onboarding directly correlates with higher first-session engagement.

82% Daily Session Completion Rate
Most users completed their daily learning path (avg. 3–4 resources + quiz) within 35 minutes, indicating balanced cognitive load and achievable pacing.
Why it matters: Confirms the app’s “micro-learning” design reduces friction and supports consistency.
+58% Increase in Return Intention
After introducing AI mentor chat and visible streak progress, 7 of 12 users reported stronger motivation to return daily (“feels guided and rewarding”).
Why it matters: Demonstrates that lightweight gamification + personalized reflection increase perceived accountability.
Onboarding Time Reduced from 12 min → 4.5 min
The AI intake chat automatically generated personalized 3-phase learning plans after three short questions, replacing manual goal setup forms.
Why it matters: Shorter onboarding directly correlates with higher first-session engagement.

82% Daily Session Completion Rate
Most users completed their daily learning path (avg. 3–4 resources + quiz) within 35 minutes, indicating balanced cognitive load and achievable pacing.
Why it matters: Confirms the app’s “micro-learning” design reduces friction and supports consistency.
+58% Increase in Return Intention
After introducing AI mentor chat and visible streak progress, 7 of 12 users reported stronger motivation to return daily (“feels guided and rewarding”).
Why it matters: Demonstrates that lightweight gamification + personalized reflection increase perceived accountability.
Onboarding Time Reduced from 12 min → 4.5 min
The AI intake chat automatically generated personalized 3-phase learning plans after three short questions, replacing manual goal setup forms.
Why it matters: Shorter onboarding directly correlates with higher first-session engagement.