Inspiration
Choosing a career path shouldn't feel like a high-stakes guessing game. We were inspired to move beyond basic interest surveys and build a platform that truly understands the "shape" of a student's mind before suggesting a path, turning indecision into a structured journey of discovery.
What it does
CareerGenie is a high-fidelity discovery engine designed for the modern undecided student:
- Cognitive Mapping: Instead of simple questions, it uses AI-driven scenarios to analyze how you solve problems and collaborate, mapping your academic DNA across multiple psychological dimensions.
- Actionable Roadmaps: Once a match is made, the platform bridges the gap from theory to reality, providing a focused, week-by-week path toward mastery.
- Seamless Commitment: We built a unique navigation flow that allows for deep exploration before asking for a commitment, protecting user progress every step of the way.
How we built it
We leveraged Next.js 15 for a performance-first architecture and integrated Llama 3.3 to power our interactive scenario engine. The UI is crafted with focused animations using Framer Motion, creating a premium experience that guides user attention. Data persistence and the complex "session-to-profile" migration logic are handled securely through Firebase.
Challenges we overcame
Our biggest challenge was building a user journey that felt both invitation-led and data-secure. We spent significant time perfecting the "Phase Gate" logic—a technical handshake that ensures anonymous discovery data is seamlessly migrated to a permanent profile without a single click of friction for the user.
What we learned
Building CareerGenie taught us that the most effective tools don't just provide answers; they provide a process. By focusing on the cognitive DNA of the user first, we can provide recommendations that feel deeply personal and immediately actionable.
Built With
- next.js
- react
- typescript

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