What if intelligence lives in the conversation, not the machine?

Intelligence isn't just what happens inside an AI model—it emerges through the back-and-forth between humans and systems over time. This paper reframes how we should evaluate co-creative AI (like drawing tools that adapt to your style) by looking at interaction patterns, coordination, and how participants influence each other, rather than just final outputs or accuracy metrics. Built on decades of work in embodied cognition and human-computer interaction, the framework suggests that measuring adaptive participation and conversational drift matters as much as measuring what the AI produces.