How you write the instructions determines how the GPT thinks.
This is the part that shapes its clarity, boundaries, and behavior.
Good instructions define the role, the priorities, and the limits.
They tell the model what to focus on and what to ignore.
They establish tone, level of detail, and the structure of the output.
Most issues come from unclear or missing rules, not from the model itself.
A small refinement — one constraint, one clarified step — often resolves drift.
Instruction architecture is where a GPT becomes dependable instead of unpredictable.