I had an agent that worked, and I wanted it sharper. So I did the obvious thing: I added a line telling the model to be careful, think it through, and only answer when it was sure. Every instinct says that should help.
Accuracy dropped. Not by a little. The agent started refusing cases it used to get right, and talking itself out of good answers.
I deleted the line. Accuracy climbed back up, past where it started. The 'be careful' text was not making the model smarter, it was making it hesitant. It read caution as permission to bail.
The lesson I keep relearning: with a strong model, most of your prompt is friction. The skill is not writing the perfect instruction, it is noticing which instruction is quietly hurting you and taking it out. When the output is off, try removing a line before you add one.