Sub-50ms or Bust: Why Inference Latency Is the New Uptime
A 200ms response is a broken product for a trading desk. This is how we engineered our way to 48ms P50 — and why every millisecond was a deliberate architectural choice.
Latency used to be a model benchmark problem. In production agents, latency is product uptime.
A trading desk cannot wait 200ms for a classification. A support workflow cannot stall while a user watches a spinner. Every millisecond is an architectural decision.
Where latency actually hides
Most teams measure model time and stop. Real latency includes retrieval, tool calls, policy checks, queueing, serialization, and post-processing.
The stack that moved the P50
We reduced P50 latency to 48ms by combining warm pools, KV cache reuse, speculative decoding on predictable paths, and edge routing close to the caller.
Latency is a reliability metric
When latency drifts, workflows fail silently. Users retry. Costs spike. Policies time out. Treat latency like uptime and instrument the full run, not just the model call.
Marcus Thorn
Head of Infrastructure, AIRMY. Writes about production-grade agent infrastructure, governance, and platform operations.
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