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Design the moderation backbone of a large UGC platform: ~500M pieces of content a day — images, video, and text — must be screened for policy violations (CSAM, nudity, violence, hate, spam) before causing harm. The defining challenge is that you can neither run every model synchronously on upload (it would add seconds of latency and collapse under peak) nor have humans review everything (15K reviewers can touch ~1–2% of the firehose). The right shape is a multi-stage pipeline: a fast synchronous known-bad hash gate that hard-blocks the worst content before publish, an asynchronous ML classifier fan-out over optimistically-published content that takes things down when flagged, and a prioritized human-review queue ranked by severity × reach.
Best after a few full reps. Expect follow-up questions, edge cases, and deeper trade-off discussion.
5 stages
32 min
Grade anytime
Workspace-first, hints visible, stage retry available. The cheap, repeatable loop — build the answer shape before you take it under pressure.
Solve once, compare against the checklist, then come back to the weak stage instead of starting over.
Strict timer, hints hidden, debrief deferred to the end. Use this once you can already structure a clean answer and want to pressure-test pacing and pushback.
Best after one structured rep · timed · focused on pacing and communication.
This is the framing pass. A strong answer quickly defines what the system must do, what quality bar it has to hit, and the numbers that will justify the rest of the design.
What must exist
What good looks like
Numbers to anchor the design
Each stage has a distinct job. Treat them like separate deliverables instead of one giant answer, and the round becomes much easier to navigate.
Define the contract clearly: the endpoints, auth boundary, error semantics, and the one or two decisions that matter most.
What you should produce
Now define the API. How does content enter the pipeline, how is the moderation verdict delivered, and what do reviewers and appeals look like? Be e...
Strong answers cover
Lay out the main components and trace the write path, read path, and any async path cleanly.
What you should walk through
Now draw the system. Walk me through what happens from the moment content is uploaded to the moment a verdict is reached and acted on. Be explicit...
Strong answers cover
Pick the store, show the schema or key model, and explain why that storage choice fits the access pattern.
What you should lock in
Let's get concrete about data.
Strong answers cover
Name the first bottleneck, failure modes, and the trade-offs that keep the system fast and reliable under pressure.
What you should pressure-test
Finally, scale and failure modes.
Strong answers cover
Translate the prompt into concrete requirements, scale, and trade-offs before drawing architecture.
Give APIs in the API stage, data models in the storage stage, and failure modes in scaling. Don't blur them together.
Grade early, compare to the reference reasoning criteria, fix the biggest misses, and re-submit the weak stage instead of starting over.
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