Exploration—through action, inquiry, or search—is how cognitive actors expand what they know. Inquiry is a self-correcting process where problematic situations are resolved through experimentation. In computational learning, the explore-exploit tradeoff formalizes this: agents must balance gathering new information against acting on current knowledge. The memex was imagined as an extension of human memory because retrieval is inseparable from thought; augmenting human intellect requires tools that help us navigate and synthesize knowledge. As AI systems move toward open-ended learning, exploration becomes the mechanism for generating novel training experiences and discovering not just answers but new questions entirely. The ability to explore—to formulate questions, test hypotheses, and navigate information spaces—is the sovereign act of cognitive agency.