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Design a real-time collaborative coding assistant: stream completions under 200ms for 10k concurrent users

A Copilot/Cursor-style assistant lives or dies on the latency budget. The strong answer spends every millisecond of a 200ms end-to-end budget on purpose, separates the inline-ghost-text path from the chat path, and shows why prefix caching and speculative decoding are the only ways to hit it at 10k concurrent users.

Updated Sep 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.

A Copilot/Cursor-style assistant lives or dies on the latency budget. The strong answer spends every millisecond of a 200ms end-to-end budget on purpose, separates the inline-ghost-text path from the chat path, and shows why prefix caching and speculative decoding are the only ways to hit it at 10k concurrent users.

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FEDITOR'S NOTE

The screen is whether the candidate budgets latency explicitly instead of hand-waving. The 200ms number forces a split: inline completions are a different system from chat, with a small fast model, aggressive debouncing, and prefix caching, while chat tolerates seconds. Watch for the candidate who routes every keystroke to a frontier model and never mentions cancellation, which would melt the GPU fleet and miss the budget by 10x.

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