This sub isn't for tips on how to prompt ChatGPT

Maybe I'm way off base here but I wanted to share my opinion on what I think is prompt engineering.

Basically, when you type something into a UI like Gemini, Claude, Cursor, ChatGPT, or whatever, there's already some kind of system prompt and a wrapper around your user prompt. Like Anthropic would already tell Claude how to respond to your request. So I'm not convinced that re-using some made some prompt template you came up with is better than crafting a simple prompt on the fly for whatever I'm trying to do, or just simply meta-prompting and starting a new conversation. Literally, just tell the agent to meta-prompt and start a new conversation.

IMO prompt engineering has to have some way of actually measuring results. Like suppose I want to measure how well a prompt solves coding problems. I would need at least a few thousand coding problems to benchmark. To measure and find the best prompt. And it needs to be at a scale that proves statiscal significance across whatever kind of task the prompt is for.

And ultimately, what are you actually trying to achieve? To get more correct answers with fewer tokens? To get better results regardless of token count?

Just to give you a specific example, I want Claude to stop calling everything sophisticated. I'm so sick of that word dude! But I'm not convinced telling Claude not to say sophisticated is a good idea because it's going to distract Claude from the coding task I'm giving it. But me just telling Claude things isn't prompt engineering. It's just prompting!

The engineering comes in when you're trying to actually engineer something.