"Every second your developers wait for AI is a second they're not shipping. Latency isn't just annoying—it's expensive."
Let's talk about money. Specifically, let's talk about the money you're losing every day because your AI infrastructure is slow. This isn't about user experience (though that matters too). This is about hard dollars and the quantifiable ROI of speed.
A developer using an AI coding assistant makes approximately 50 queries per day. If each query takes 2 seconds instead of 100ms, that's 95 extra seconds of waiting per day. Multiply by 250 working days: 6.6 hours per developer per year. At $150/hour fully loaded cost, that's $990 lost per developer annually.
Now multiply by 1,000 developers. The latency tax becomes $990,000 annually. For a 10,000-developer enterprise, it's $9.9 million. And this assumes only 50 queries per day—power users hit 200+. The latency tax scales linearly with headcount and usage.
But the direct time cost understates the impact. Context switching has a cognitive cost. When a developer waits 2 seconds for a response, they lose focus. Research suggests it takes 23 minutes to fully regain deep concentration after an interruption. Even partial focus loss compounds into significant productivity degradation.
Developers who maintain flow state ship 40% more code per hour than those who are frequently interrupted. Sub-100ms latency keeps developers in flow. 2-second latency breaks it. The productivity difference is measurable.
When presenting to leadership, frame latency as a cost center, not a technical detail. Show the math:
The latency tax is real, it's quantifiable, and it's eating your margins. Stop accepting slow AI as inevitable. Demand sub-100ms.