Use case: AI chatbot with retrieval support Tools: Next.js, Python FastAPI, PostgreSQL with pgvector, Vercel AI SDK Difficulty: Intermediate
Why this combo works
- Separates frontend speed from backend orchestration
- Retrieval support makes the stack useful beyond toy demos
- Good balance between flexibility and developer experience
Caveats
- Model costs and latency need active monitoring
- Retrieval quality depends on chunking and evaluation
Use case: Turn an ML or data workflow into a lightweight demo app Tools: Python, Streamlit, Hugging Face, Docker Difficulty: Beginner
Why this combo works
- Very fast path from experiment to shareable interface
- Strong fit for demos, internal tools, and model previews
- Easy for contributors who are more data-focused than frontend-focused
Caveats
- Not ideal for highly custom product UX
- Can become messy if app logic grows too much