Mock system design interview at Lyft
A live 45-minute round on a question reported in Lyft interviews, run by an AI interviewer that asks one thing at a time, probes what you say, looks at your whiteboard, and weighs what that round is reported to weigh. It ends with a debrief: a score, what was strong, what was missing.
Design Google Maps
Map tiles, place search, turn-by-turn routing with live traffic, and ETAs for a billion users.
You will not see the requirements, the numbers or the design before you start. That is the point.
What the Lyft round is reported to look like
60 minutes, usually diagrammed in Google Drawings, which candidates suggest practising first. Prompts range from ride-hailing problems such as matching riders to drivers to general ones: chat, a web crawler, a donation or payment flow.
What it weighs
- A systematic structure, from requirements to design
- Covering every stated requirement, not only the interesting one
- A proposed API and database tables, not only boxes and arrows
- A practical design that could be built, and that holds up when a step fails
The common mistake
Preparing only for ride-hailing. Many reported prompts are general problems, and on those the questions still go to covering every requirement and to failures, such as a payment that is lost or recorded with the wrong amount.
From public interview guides and candidate reports, and Lyft’s own interview guidance where it publishes any. Not endorsed by Lyft. The interviewer is an AI running in that style; it is practice, not a prediction.
Start the round
The interviewer’s opening question is free. Answering it is part of Pro. See an example round and its debrief →
The 5 questions this round draws from
Each is reported in Lyft interviews. Pick one to sit, or read its reference design and walk through a strong answer first.
- Design Google MapsMap tiles, place search, turn-by-turn routing with live traffic, and ETAs for a billion users.drawn
- Design UberMatch riders with nearby drivers in seconds, track trips live, and price them, for millions of concurrent users worldwide.
- Design DoorDashTake a food order, get a restaurant to cook it and a courier to arrive just as it is ready, and keep three parties in sync across millions of orders a day.
- Design Apache AirflowSchedule and run twenty thousand data pipelines as dependency graphs, each run tied to a slice of time, so a failed night can be retried or a year backfilled safely.
- Design Nearby FriendsShow each user which friends are within 5 miles, refreshed every 30 s, for 10 M concurrent users, without leaking anyone’s location.
Other companies: Anthropic · Google · Meta · Amazon · OpenAI · Microsoft · Uber · DoorDash