Planet AI included a Towards Data Science case study about an AI routing layer that cut inference spending by more than half, only for customer satisfaction to decline months later.
The lesson is practical: routing cheaper models to save money can silently degrade product quality if teams only track cost and latency. In AI products, the cheapest acceptable path is only acceptable if the user experience remains intact.
The post argues for detection methods that catch quality loss quickly, which is becoming a key discipline as teams mix multiple models behind one product.