Ai Coding And Product Systems hard
Your completion backend receives about 15 requests per second from each actively typing user, GPUs are saturated, and over 90% of generated suggestions are never displayed because the user kept typing. What change fixes this while keeping the latency target?
- A Batch each user's keystroke requests into one larger request every 2 seconds to maximize GPU batching efficiency and throughput.
- B Scale the GPU fleet behind a least-connections load balancer, since discarded completions are an unavoidable cost of the feature.
- C Debounce briefly on the client, cancel in-flight requests on new keystrokes, and reuse a suggestion the user is typing through.
- D Cache completions keyed on a hash of the full file content so identical files return instantly regardless of cursor position.
Answer: C. Debounce briefly on the client, cancel in-flight requests on new keystrokes, and reuse a suggestion the user is typing through.
A short debounce adds a few tens of milliseconds but **eliminates wasted generations**, and cancellation frees GPU slots right away. Reusing a suggestion the user is typing through avoids a new request entirely. Batching every 2 seconds (A) improves throughput but blows the 200 to 400 ms completion budget, so it only suits offline workloads. Scaling out (B) pays for waste instead of removing it.
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