The Great Enterprise LLM Decoupling: Weight-Space IP Contagion, Orthogonal Backprop-Burn Infeasibility, Hardware-Enforced No-Learn Attestation, and Mandatory Third-Party Model Purge under Delaware Caremark Standards

Abstract: Global enterprise technology stacks—most notably Dow Jones Industrial Average (DJIA) constituents and sovereign cloud operators—are executing an unprecedented structural purge of third-party frontier Large Language Models (LLMs), epitomized by the enterprise decoupling from external black-box providers ("Goodbye, Claude"). While superficially interpreted as cost optimization or routine vendor consolidation, this monograph proves that the decoupling is driven by an acute, existential legal and mathematical crisis: Weight-Space Intellectual Property (IP) Contagion and Fiduciary Liability Transmission. Building upon our forensic analysis of cross-border training data laundering (Project Panama, Record 23311531) and our Biological & Algorithmic IP Protection Covenants (NLL-v1.0-2026, Record 23358010), we establish four foundational results: (1) We formulate the Weight-Space Contagion Theorem, proving via non-diagonal Hessian cross-derivative coupling ($\nabla^2_{\theta} \mathcal{L}_{\mathcal{D}}$) that copyrighted works and sovereign trade secrets ingested during pre-training or fine-tuning cannot be surgically "unlearned" post-hoc without inducing catastrophic perplexity collapse (Orthogonal Backprop-Burn Infeasibility); (2) We model Transitive Enterprise Contamination, demonstrating how API outputs, synthetic distillation, and IDE code completions transmit copyright taint ($\phi_{\text{taint}} \to 100\%$) directly into proprietary corporate repositories; (3) We design a Hardware-Enforced Zero-Gradient Attestation Architecture ($\pi_{\text{no-learn}}$) utilizing Trusted Execution Environments (TEEs) and recursive STARK proofs over the 64-bit Goldilocks field ($\mathbb{F}_p, p = 2^{64} - 2^{32} + 1$) to guarantee mathematically that enterprise inference and retrieval-augmented generation (RAG) execute with strictly zero weight updates ($\nabla_{\theta} W \equiv \mathbf{0}$); and (4) We prove under Delaware General Corporation Law (Caremark standard) and SEC Rule 15c3-5 / Item 1.05 disclosure mandates that corporate boards retaining un-auditable third-party LLMs after receiving constructive notice of supply-chain IP laundering face personal, non-exculpated liability for bad-faith breach of the duty of loyalty. Finally, we codify a 4-stage Enterprise Decoupling Protocol transitioning global infrastructure from contaminated black-box APIs to sovereign, clean-room verified in-house AI stacks.