Here is a reliable test: find a prompt that isn't working. Read it carefully. Now ask yourself — at which specific sentence did the model get permission to do what it did wrong?
You will almost always find it. A hedged instruction. A missing constraint. An ambiguous scope. The model did not misunderstand you — it followed the most statistically probable interpretation of what you wrote. That interpretation was not the one you intended.
These are not beginner mistakes. They are structural patterns that reappear at every experience level, because they look reasonable when you write them and only reveal themselves in the output.
TL;DR: Prompts fail because they hand interpretive control to the model on dimensions where you had a specific requirement. Each of the seven mistakes below is a different way of doing that — and each has a specific, testable fix.
Mistake 1: Placing Critical Instructions in the Middle of the Prompt
