AI Engineering
hard
~50 hours
AI-Powered Quiz Platform with Adaptive Difficulty
Build a production quiz platform that uses LLMs to generate questions, evaluate answers, and adapt difficulty in real-time. Implement semantic caching and model routing to keep costs under $0.01/request.
Skills Demonstrated
LLM API integration with cost optimization
Semantic caching (embeddings + similarity search)
Adaptive difficulty algorithms
FastAPI + PostgreSQL production backend
Implementation Steps
- Design database schema for quizzes, questions, user progress
- Build question generation service with prompt engineering
- Implement content verification pipeline (LLM-as-judge)
- Add semantic cache with FAISS for similar question detection
- Build adaptive difficulty engine based on user performance
- Implement model routing: easy questions to Haiku, hard to Opus
- Deploy with Docker + CI/CD pipeline
Interview Relevance
Why this project matters for interviews
This is the exact system described in AI Engineering course. Shows you can build a production AI app with cost controls -- the #1 concern at every company deploying LLMs at scale.