> I used to joke about prompt engineering. But by jiminy it is a thing now.

This is the downside of living in a world of tweets, hot takes and content generation for the sake of views. Prompt engineering was always important, because GIGO has always been a ground truth in any ML project.

This is also why I encourage all my colleagues and friends to try these tools out from time to time. New capabilities become aparent only when you try them out. What didn't work 6mo ago has a very good chance of working today. But you need a "feel" for what works and what doesn't.

I also value much more examples, blogs, gists that show a positive instead of a negative. Yes, they can't count the r's in strawberry, but I don't need that! I don't need the models to do simple arithmetic wrong. I need them to follow tasks, improve workflows and help me.

Prompt engineering was always about getting the "google-fu" of 10-15 years ago rolling, and then keeping up with what's changed, what works and what doesn't.