There's a moment almost everyone hits in their first week using AI for code. You type something like "help me with this error," the AI gives you a generic answer that applies to roughly everything except your actual problem, and you close the tab convinced this whole AI thing is overhyped.
Here's what no one tells you in that moment: the AI didn't fail. The prompt did.
That same model, thirty seconds later, with a structured question, would have given you exactly what you needed. The difference between those two questions isn't advanced technical knowledge — it's structure. And structure can be learned.
Why the same model gives such different answers
A quick callback to Module 1: the AI doesn't "think" in the human sense. It predicts tokens. That means if you give it little context, it fills the gaps with the most probable continuation — and for a vague question, the most probable answer is a vague one. If you want to dig into the mechanics behind that, the hallucinations tutorial covers exactly how this plays out.
