We synthesize three independent frameworks—the P != NP theorem from operational gradient theory, Threaded Mind’s embodied consciousness model, and thermodynamic energy constraints—to argue that Artificial General Intelligence (AGI) faces fundamental rather than merely engineering limitations. Drawing on the Intrinsic Operational Gradient Theorem (IOGT), we demonstrate that the computational asymmetry between construction and verification is not algorithmic but structural, arising from the non-invertibility of information-processing opera- tions. Threaded Mind theory reveals that human intelligence emerges not from isolated neural computation but from recursive memory dynamics distributed across brain, body, relationships, history, and environmental coupling—a cognitive ecology requiring exponential parallelism to replicate digitally. Finally, we examine thermodynamic bounds: the absence of low-temperature fusion (cold fusion) and the irreducible energy costs of computation impose hardware limits that prevent digital systems from matching biological efficiency. Together, these constraints suggest that human-level AGI may be physically impossible within polynomial resource bounds, with profound implications for technological trajectories, economic assumptions, and the unique status of biological intelligence.