Back to practice Practice this problem
AI for FrontendIntermediate50 minutes
RAG-Powered Smart FAQ
Design a retrieval-augmented FAQ experience with chunking, relevance evaluation, and grounded answer generation.
LLM-friendly summary
An AI-for-frontend design exercise about retrieval-augmented generation, chunking, relevance, and citation-aware answer UX.
Scenario
Support teams need a smart FAQ experience that can answer product questions from a knowledge base without hallucinating.
What you need to design
- 1Choose a client-side or server-side RAG architecture.
- 2Explain chunking, retrieval, and grounding.
- 3Design the answer UI and trust signals.
- 4Measure quality with useful evaluation criteria.
- 5Handle stale knowledge and failure modes.
Concepts
RAGEmbeddingsChunkingGrounded Generation
Skills
AI Feature DesignSearch RelevanceTrustworthy UX
What good solutions are evaluated on
- - RAG system design and retrieval flow
- - Evaluation and debugging strategy
- - UX patterns for uncertainty and citations
- - Trade-offs between latency, quality, and cost
Ready to practice this yourself?
Open the interactive AlgoReason workspace to sketch the architecture, write notes, and submit for AI evaluation.