AlgoPilot

Want to land your next software engineering job? AlgoPilot is your AI coding co-pilot—master DSA, ace interviews, and get instant feedback to boost your problem-solving skills and land your next job!

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🚀 Inspiration

As a CS Student, preparing for technical interviews can be overwhelming. Switching between platforms, practicing LeetCode-style problems, and guessing what to improve can be extremely tough. As well as constantly learning and applying new data structures and algorithms can be a lot especially when trying to really learn how to implement them in different ways and how it truly works.

That's why I wanted to build AlgoPilot, an AI-powered co-pilot that not only helps users solve coding problems but also teaches data structures and algorithms step-by-step, gives real-time feedback, and simulates mock interviews with adaptive AI responses so you know where to start and how to go about your dsa journey.

🤖What it does

AlgoPilot is your personal AI interview mentor. It allows users to:

-Practice coding problems in real time with AI feedback on efficiency, readability, and logic and run test cases to improve your skills through our wide selection of problems to choose from for each topic.

-Enter mock interview mode, where the AI asks technical questions based on your selection of topics and difficulty via integrated IDE using Judge0

-Receive instant feedback and grading after submitting coding solution, simulating a real interview experience with feedback being on correctness, clarity, efficiency, time and space complexities, and follow up questions!

-Learn through interactive explanations and tailored improvement suggestions after each session. Ask AlgoPilot to explain concepts and learn through our lessons where we take you through certain problems and how to thoroughly implement the data structure/algorithm.

AlgoPilot was built to help every aspiring developer feel confident walking into their next interview — not just prepared, but ready to thrive.

🛠️How I built it

AlgoPilot is powered by a modern full-stack AI architecture:

Frontend: Built with Next.js, Tailwind CSS, TypeScript, JavaScript, and HTML for a sleek, responsive, and highly optimized user interface.

Backend: Powered by FastAPI (Python) to handle AI request routing, user session management, and real-time feedback processing.

AI Integration: Leveraged the OpenAI API to generate adaptive interview questions, analyze code submissions, and provide detailed feedback on correctness, clarity, and efficiency.

Code Execution Engine: Integrated Judge0 API to create a fully functional IDE within the browser — allowing users to write, run, and test code in real time across multiple programming languages.

Database & Auth: Used Supabase for authentication, persistent user storage, and tracking learning progress.

Deployment: Containerized the app using Docker for consistent development and deployed the frontend seamlessly via Netlify.

⚙️Challenges I ran into

-Managing latency when generating long-form AI feedback and analysis. Took some debugging, but eventually made it through.

-Designing accurate grading prompts for different programming languages.

-Maintaining a clean UI while handling multiple AI states and interactions. I had to keep it user friendly and easy to use so keeping the UI whilst handling all exceptions and callbacks was something that took a bit of work on.

-Balancing conciseness and depth in AI explanations to make them clear and useful to the user. The end feedback should be clear enough on how you should approach the problem next time in an actual interview setting. Going through future improvements and follow up questions is something that every user should be doing which is what I spent time on with AlgoPilot so he can show you just how to do it!

🏆Accomplishments that I'm proud of

-Developed a fully functional AI interview co-pilot with sub-5-second response times in less than 2 days.

-Achieved 90%+ task completion success in user-prompting and AI response activation

-Built a clean, scalable architecture integrating real-time AI grading and mock interviews, as well as practice environments with our integrated IDE and lessons.

-Created a system that actually helps users improve coding confidence and clarity to land those internships!

💡What I learned

-How to design AI systems that balance speed, clarity, and educational value all at the same time.

-The importance of prompt engineering for consistent, context-aware feedback.

-Deepened my understanding of frontend-backend synchronization and AI-driven UX.

-Learned how small tweaks in UI/UX can make complex AI interactions feel natural and user-friendly.

🔮What's next for AlgoPilot

-Personalized learning paths based on user progress and weaknesses.

-Multi-language support (Python, Java, C++, JavaScript).

-Mock interview replays with AI voice feedback and analytics dashboard.

-Behavioral interviews using voice/video + sentiment analysis.

-Long-term: turn AlgoPilot into a developer growth companion, tracking skill progression and offering adaptive goals.

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