Helix is HackerEarth’s AI interview coach that helps candidates practice mock interviews with realistic prompts, technical & soft skill evaluation, and targeted feedback. The goal was to sharpen usability, streamline the flow of mock practice, and amplify clarity around performance metrics. I focused on elevating the experience through cleaner visuals, clearer structure, and more intuitive feedback mechanisms. Below are four key pillars of the redesign that deliver on those goals.
Simplifying choice & progress — users can select mock type (system design, resume screener, language/framework), view clear instructions, and move seamlessly from voice/video mode to feedback. Every step is designed to reduce uncertainty and help users focus on practicing.
Post-interview insights are more detailed and more usable: strengths, improvement areas, job-readiness score, plus technical & soft-skills breakdowns. Feedback is structured to motivate learning and support concrete improvement.
Tracks tailored for different roles (frontend, backend, full-stack, product, data science) ensure relevance. Questions and mock scenarios adapt to what users “really” need to prepare for, making practice more efficient.
Voice or video modes simulate real interviews; interface design supports clear audio/visual cues, smooth transitions, and accessible layouts. Goal: make users feel confident, regardless of their device or setting.
