Constraints are creativity. The clearer the constraints, the more high-quality content AI can produce that matches expectations.
LLMs are trained on massive amounts of data. When you give a vague instruction, it faces a huge search space. When you impose constraints, you are actually trimming that search space.
You are forcing the model to abandon high-probability “mediocre solutions” and dig deeper for low-probability but more requirement-aligned “high-quality solutions.”
That is the core law of prompt engineering.