Robin
Robin is a smart job search assistant that helps users stay organized, motivated, and efficient during the job hunt. It centralizes applications, automates resume and cover letter creation, and uses AI to recommend job matches, follow-ups, and skill-building resources — all while maintaining a simple, intuitive interface.
Context
This project was developed as part of the Introduction to User Experience Design course. As my first UX project at the graduate level, it laid the foundation for applying human-centered design principles in real-world problem solving.
Tools Used
Figma, Miro, Canva, Google forms & Excel
My Responsibilities
- Conducted contextual inquiry and user interviews
- Designed surveys and analyzed insights
- Synthesized feedback into user needs and priorities
- Created Low-Fidelity mockups and functional prototypes
- Contributed to feature ideation, Information Architecture, and prototype testing

Survey and User Interviews Summary
- 70% of users track job applications, but only 40% use dedicated tools — many rely on email inboxes or manual spreadsheets
- Repetitive tasks like re-entering resume data frustrate users
- 70% reuse the same resume multiple times, showing a need for smart resume tailoring
- Lack of personalized guidance, inefficient tracking, no centralized platform
Participant Comments:
- “There's no value in tracking each application manually — I only do it once I get an interview.”
- “I reuse the same resume for efficiency, but I'd like help tailoring it if it didn't take so long.”
- “It's frustrating having to re-enter job history every time — let AI do that.”
Ideation
Persona 1
Samantha is a 27-year-old social media marketing manager living in Brooklyn with her fiancé and cat. She commutes an hour each way to her job in Manhattan and is currently balancing work with wedding planning. Samantha values personal time and is seeking a remote job with a higher salary, a clear 6 PM work cutoff, and a more efficient way to manage job applications to improve her work-life balance.

Journey Map

Design Process

Sprint Design Process

Each of us drew a sprint design of the app that we imagined.

Then we divided us into 2 groups and imagined the app like this

Our final Sprint design where we combined all the best ideas into one
Wireframes




Usability Testing Insights
Quantitative Feedback
- Calendar & resume tools were considered helpful by all testers
- AI features received high praise, especially for content generation
- Users wanted more AI functionality across other screens
Qualitative Feedback
Loved the AI-assisted resume builder and template gallery
Users wanted to click calendar dates directly, not rely on small icons
Suggestions included:
- Personalized job suggestions based on background/skills
- Personality/skill assessments for self-evaluation
- Integration with skill-building resources and resume optimization tips
- Clearer labeling (e.g., LinkedIn URL field)
Key Learnings
- Users want centralized control, not scattered tools
- AI works best when it reduces repetition (resume auto-fill, follow-up prompts)
- Clear navigation and consistent UI feedback enhance trust and usability
- People prefer flexible interaction modes — from automation to manual tweaking
- Job seekers feel empowered by skill-building tools, not just job listings