Why One Model Fails

What Real AI Systems Actually Look Like) There’s a common pattern in early AI projects. You pick one model — usually the “best” one — wire it into your backend, ship a feature, and call it a day. And at first, it worked. Until it doesn’t. The Illusion of “The Best Model” When people say: “Just use GPT-5” or “This model is the most powerful” They’re not wrong. They’re just incomplete. Because in real-world systems, “best” depends on context: Best for reasoning ≠ best for speed Best for coding ≠ b