I don't think that's true at all. Think of it like setting up conversation constraints to reduce the potential pitfalls for a model. You can vastly improve the capability of just about any LLM I've used by being clear about what you specifically want considered, and what you don't want considered when solving a problem.
It'll take you much farther, by allowing you to incrementally solve your problem in smaller steps while giving the model the proper context required for each step of the problem-solving process, and limiting the things it must consider for each branch of your problem.
It'll take you much farther, by allowing you to incrementally solve your problem in smaller steps while giving the model the proper context required for each step of the problem-solving process, and limiting the things it must consider for each branch of your problem.