For seventy years, origin-of-life research has primarily pursued a bottom-up strategy: starting with stochastic chemistry in the expectation that a digital code will eventually emerge. To date, no self-organizing communication system satisfying the Shannon boundary has been experimentally produced from non-living chemicals. This paper argues that the search direction requires a fundamental inversion. Asking 'which chemical reaction produces a code?' may be conceptually akin to asking 'which raindrop causes a river.' The river is governed by gravity and topology, not by any individual raindrop. We propose that the emergence of the genetic code is driven by macroscopic thermodynamic laws rather than isolated chemical reactions. Drawing on Wheeler's 'It from Bit' thesis, Noble's Principle of Biological Relativity, Kauffman's autocatalytic set theory, and Prigogine's dissipative structure framework, we establish an Information-First paradigm. Within this framework, non-equilibrium physical laws constrain chemical systems into discrete coding structures, preceding the spontaneous generation of the codes themselves. This approach is distinct from intelligent design; the 'information' discussed herein refers exclusively to physical information in the sense of Landauer and Wheeler quantifiable, thermodynamically constrained, and experimentally measurable. We identify the six fundamental thermodynamic barriers to spontaneous code emergence and provide a physics-grounded resolution for each. Furthermore, we introduce a comprehensive theoretical and computational architecture for an encoder, message, and decoder system capable of yielding 64 discrete digital states. Supported by seven deterministic computational simulations, we demonstrate that this physical selection autonomously achieves 88% of the theoretical Shannon channel capacity. By integrating an innovative detection methodology adapted from nuclear non-destructive examination (NDE), this paper provides a predictive, mathematically falsifiable framework to resolve the Shannon-Turing bottleneck of abiogenesis.
Taekyung Lee (Thu,) studied this question.