Recent content by cameroncreates77

I've found way and useful is usually easier to improve when you write down exactly what changed between runs. Otherwise after a few attempts it becomes hard to remember which tweak actually helped. I would trust a repeatable result more than one impressive run.

When working with Large Language Models, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is evaluation. Define what a good result looks like before changing tools or settings, then test one variable at a...