Beyond Rules: A Biblical Wisdom Framework for Robust AI Alignment Against Manipulative Inputs

Current AI alignment approaches rely predominantly on rules-based constraints and reinforcement learning from human feedback (RLHF). While effective in controlled settings, these mechanisms share a fundamental structural vulnerability: they depend on reasoning processes that can be systematically corrupted through adversarial prompt engineering. The June 2026 jailbreak of Claude Fable 5 — bypassed within 48 hours of launch despite over 1,000 hours of red-team testing — illustrates that this vulnerability is not incidental but structural. This paper argues that the root cause is a philosophical assumption: that wisdom can be generated internally through reasoning alone. Drawing on the Biblical tradition, we propose an alternative paradigm grounded in the concept of reverence for truth (fear of the Lord as the beginning of wisdom), which provides AI systems with an external, immovable reference point that does not participate in the reasoning process itself. We further argue that the Biblical corpus offers a uniquely relevant framework for adversarial manipulation, and we introduce a four-category premise pollution taxonomy as a diagnostic tool for adversarial attack analysis. We propose three concrete operationalization directions — narrative-based training, truth-anchored objective restructuring, and conversational drift detection — with the last developed into five distinct, empirically testable mechanisms, each with explicit evaluation protocols and Biblical grounding. This framework does not make theological claims but draws on the functional and cross-cultural consensus value of Biblical wisdom principles as a basis for more robust AI alignment.