Start with a better question.

A problem statement is a design decision. It determines what we measure, which trade-offs we accept and what an eventual result can tell us.

Define the decision.

Before choosing a computational method, ask who will use the result and what they need to decide. A faster answer is of little value when it solves the wrong problem. Record the constraints, identify uncertainty and make the baseline explicit.

Make failure informative.

A good experiment is useful even when the hypothesis does not survive. Reproducible inputs, a clear comparison and carefully chosen metrics turn a negative result into knowledge that the next experiment can build on.

Keep asking.

As a system becomes clearer, the question may change. That is a sign of learning. The discipline is to make those changes visible, rather than silently moving the goalposts.