AI is starting to look a lot like the early days of cloud – and the real race is operational
Over the past two years, most of the noise around AI has focused on the model race – whose model is bigger, faster or scoring better on benchmarks.
But as AI moves from pilots into the core of products and workflows, a familiar pattern from the early days of cloud is re‑emerging: systems are more programmable than ever, but they are also much harder to run.
And that means we now know where the most important competition in AI is shifting: from who has the “best” model to who can operate AI reliably, efficiently, and safely at scale.
AI is now hitting operational limits, not model limits
When looking at real‑world telemetry from thousands of production systems, a clear picture starts to form. Nearly 1 in 20 AI requests fails once applications reach scale, and a majority of those failures now stem from capacity limits such as rate limits, quotas...
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