Intelligent behavior is typically explained teleologically: agents act to fulfill pre-existing internal goals. This paper challenges that view, proposing instead an inverted cognition model in which actions come first and goals are imposed retroactively. Drawing on cephalopod intelligence and philosophical models—including Dennett’s intentional stance, predictive processing, and cybernetic theories—I argue that intention and purpose can emerge from behavior rather than precede it. Octopuses provide an empirical case of decentralized intelligence that generates purposeful actions without a unified central planner. I develop a philosophical case against strictly goal-driven agency, address objections about randomness and efficacy, and explore implications for artificial general intelligence (AGI). A system that derives goals from its own behavior could be more adaptive, creative, and safe than one rigidly bound to predefined objectives. This framework offers a new perspective on agency, intention, and mind across biological and artificial systems.