Hackathon Finalist · 1st Place (Education Track)
PrepTalk
An AI-powered interview prep platform that analyzes résumés, generates role- and company-aware questions, and simulates realistic interview practice with structured feedback.
Personalized Questions
Generated interview questions using résumé content, role, and company context.
Mock Interview Flow
Created a guided prep and interview experience with realistic structure and feedback.
Accessible Prep Tool
Designed to reduce barriers for students who lack mentors or formal mock interview practice.
Overview
What the project does
PrepTalk is an interview preparation platform built to help users practice more effectively with personalized, structured support. Instead of relying on generic question banks or scattered resources, the product brings résumé analysis, company context, tailored interview questions, and mock interview feedback into one flow.
The goal was to create an experience that felt practical and immediately useful — especially for students and early-career candidates preparing for interviews without easy access to mentors, coaching, or realistic practice environments.
Problem
Why interview prep feels fragmented
Interview preparation is often spread across disconnected tools and resources. Candidates may search for likely questions, read company pages, revise résumés, and practice answers separately — but still lack feedback that feels personalized or realistic.
- Practice is often generic instead of tailored to the user’s background
- Company research and interview prep usually happen in separate places
- Most students do not have access to realistic mock interviews or useful feedback
- Technical and behavioral preparation are rarely integrated into one flow
The opportunity was not just generating questions with AI — it was designing a single product that made interview prep feel more personal, realistic, and actionable.
Solution
Designing an end-to-end prep experience
PrepTalk was designed as a guided system rather than a single-screen tool. The experience moves users from setup into preparation and then into interview simulation, helping them feel more prepared at each step.
- Upload résumé and enter target role or company
- Generate tailored interview questions
- Review company-aware prep context
- Run behavioral or technical mock interview flows
- Receive structured feedback and improvement guidance
My Role
What I contributed
My work focused on UX design and front-end development. I helped shape the interview-prep flow, organize the experience into clearer stages, and build the interface so users could move from setup to practice in a way that felt intuitive and usable.
UX Design
Structured the flow into setup, prep, and interview stages to reduce confusion and support progression.
Front-End
Worked on the interface and interaction patterns that supported guided prep, question display, and user flow.
Product Thinking
Focused on how personalization, realism, and feedback could work together as one cohesive experience.
UX Decisions
How the experience was structured
One of the biggest design priorities was keeping the product from feeling overwhelming. Interview prep already carries stress, so the interface needed to feel clear, guided, and focused rather than overloaded with too many choices at once.
Step-Based Flow
Separated setup, prep, and interview stages to create a clearer mental model for users.
Personalization First
Used résumé, role, and company input as the basis for a more relevant prep experience.
Panelized Feedback
Organized outputs into readable sections so users could quickly understand next steps.
Behavioral + Technical Support
Designed the product to support multiple interview types instead of a one-size-fits-all flow.
Confidence Through Structure
Made the experience feel more approachable by reducing ambiguity and clarifying progression.
Usability Under Time Pressure
Prioritized clean layout and direct actions for a fast-paced hackathon build that still felt polished.
Technical Implementation
How it was built
Frontend
React, TypeScript, and Vite for a responsive interface and structured client-side flow.
Backend
FastAPI used to support AI-powered interview generation and feedback workflows.
AI Layer
OpenAI-powered prompts were used to generate tailored interview questions and responses.
Technical Round
Monaco Editor supported coding-focused interview practice in the product experience.
A key part of development was making the AI outputs feel usable inside the interface, not just technically functional. That meant thinking carefully about prompt structure, result formatting, and how users would actually move through the prep process.
- Prompt structure for consistent question generation
- Front-end state and flow between prep stages
- Readable display of tailored questions and feedback
- Technical interview support through editor-based interaction
Outcome
Recognition and impact
PrepTalk was recognized as a finalist and received 1st Place in the Education Track. The project stood out because it paired a practical problem with a clear end-to-end solution: helping people prepare for interviews in a more equitable, personalized, and realistic way.
- Finalist recognition at the hackathon
- 1st Place in the Education Track
- Combined UX, AI, and front-end execution in one product
- Addressed a real accessibility and opportunity gap in interview preparation
Takeaways
What this project taught me
PrepTalk reinforced how valuable it is to design AI-powered products around usability and trust. The strongest part of the project was not just the AI generation itself, but how that intelligence was shaped into a product flow that felt practical, supportive, and easy to use.
- Designing AI experiences that feel clear and useful
- Structuring guided flows for higher-stress tasks
- Building front-end systems around dynamic generated content
- Balancing speed of implementation with usability in a hackathon setting