Why LLM Reasoning Is Breaking AI Infrastructure (And How to Fix It)

If you've tried building anything serious on top of large language models (LLMs) recently, you've probably run into this: "Thinking" is supposed to make models better. In practice, it makes your infrastructure worse. This isn't a model problem—it's an infrastructure and abstraction problem. And it's getting worse as teams scale across multiple AI providers. Let's break down exactly where things go wrong. The Illusion of "Just Turn On Reasoning" At a high level, LLM reasoning sounds straightforwa