LLM retrieval-augmented QA
Design a retrieval-augmented LLM system that answers questions over a company's 10M-document knowledge base for 50k employees, with a 3s p95 end-to-end budget, answers grounded in (and citing) source documents, freshness within minutes of a document changing, and strict access control so users only see content they're authorized for. Cover ingestion/indexing, the retrieval + generation path, how you enforce permissions and freshness, and how you evaluate answer quality.
What a strong answer looks like
Clarify scale and constraints first. Propose a clean component breakdown, then go deep on the hard parts (data model, bottlenecks, consistency, failure modes) and name the trade-offs you are making.
Clarify6:00 left
Estimate6:00 planned
Design18:30 planned
Deep dive14:30 planned
Failure10:00 planned
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.