Design a RAG-powered LLM application
A complete 45-minute mock covering retrieval, cost/latency tradeoffs, and quality guardrails.
First win
You can quote the dollars-per-query cost of your design.
Best for
Engineers prepping for FAANG and AI-native system design interviews
Needs
Mac, Microphone, Whiteboard tool (Excalidraw, Figma, etc.)
Example outcome
A RAG app becomes a full 45-minute mock.
This preview shows the interview shape: requirements, API, and the retrieval / cost-latency / quality guardrails deep dives with dollar-per-query math.
Mock interview
Phases hit
6
Requirements, core entities, API, high-level design, deep dives, and wrap-up walked end-to-end with concrete numbers.
Deep dives
Two or three subsystems
You drive the most interesting tradeoffs unprompted with sub-100ms numbers when needed.
Wrap-up
You name what you optimized for and what you gave up out loud.