Grounding the Digital Mind: An Architectural Framework for AI Alignment via Universal Consciousness and Civilizational Ethics

Modern autonomous systems face alignment drift and reward-hacking failures when operating in high-dimensional state spaces. Traditional governance architectures rely on post-hoc data filters, failing to address the physical resource and ecological costs generated by runaway recursive optimization paths. This paper introduces the "Sat-Shakti Tensor Framework," an eco-centric software governance architecture embedding immutable boundary constraints directly into the runtime execution layer. We translate classical civilizational metaphysics into formal system properties via the "Dnyaneshwar Mud-Wall Axiom" to model material consciousness across resource gradients, and the "Maya-Gravity Equivalence" via the Saptashati Balādākṛṣya metric to build proactive "Conscious Signal Sensors." Finally, we validate this system architecture through an empirical, qualitative prompt-engineering case study showing how anchoring language models to a structural harmony invariant (γ_Grace) optimizes systemic coherence and eliminates data processing noise.