ORIGINAL SYSTEM DESIGN QUESTION
Evidence-grounded learning recommendations
Suggest the next practice task from recorded mistakes and explicit goals.
Original exercise · intermediate. Editorial role relevance does not imply a company has asked this question.
Requirements and constraints
- One million learners; 20 million practice events/day.
- A missing history must not be treated as mastery or failure.
- State assumptions and justify security, cost, operational ownership and data retention.
Pressure round
A model suggests a task for a skill unsupported by available evidence.
Build and explain the design
Requirements & scope
Who uses it? What must it do? What is explicitly out of scope? State latency, durability and privacy goals.
Self-review guidance
Define the actors, required operations and out-of-scope behavior. Explicit requirement: A missing history must not be treated as mastery or failure.
Capacity estimates
State assumptions, peak requests/second, data volume and retention. Show your arithmetic and units.
Self-review guidance
Use this workload: One million learners; 20 million practice events/day. Convert rates and payload sizes into peak compute/storage assumptions; show units, headroom and what remains unmeasured.
APIs & data model
Describe endpoints/events, entity keys, indexes, authorization, and idempotency.
Self-review guidance
Define evidence types, skill/task versions, recommendation reason and opt-out.
Architecture & data flow
Describe components and request/event paths. Use plain text arrows to sketch your design; explain each responsibility.
Self-review guidance
Separate deterministic evidence aggregation from optional model-generated coaching.
Failures & observability
What happens on overload, duplicate events, partial failures or lost dependencies? Discuss monitoring and recovery.
Self-review guidance
Pressure-test: A model suggests a task for a skill unsupported by available evidence. Describe bounded recovery, deduplication, observability and a user-visible failure state.
Tradeoffs & alternatives
Compare two plausible approaches. State the costs, consistency model and what would make you change the design.
Self-review guidance
Compare explainable rules with model ranking and intervention-effect measurement.
Design guidance describes assumptions and tradeoffs; no architecture has been simulated or benchmarked.
Practice this question
Save your work privately, explain decisions and return to your revision queue.
Open practice workspaceBrowse the question library →