It seems ( only seems, because I have not gotten around to test it in any systematic way ) that some variables like context and what the model knows about you may actually influence quality ( or lack thereof ) of the response.
What is better is to build a good set of rules and stick to one and then refine those rules over time as you get more experience using the tool or if the tool evolves and digress from the results you expect.
But, unless you are on a local model you control, you literally can't. Otherwise, good rules will work only as long as the next update allows. I will admit that makes me consider some other options, but those probably shouldn't be 'set and iterate' each time something changes.