The Illusion of Stability: Why AI's Reasoning Fragility Demands a Trust-Centric Response

AI reasoning is scaling faster than trust safety. OpenAI offloads it, Anthropic exposes fragility, TVM shows why trust must be built into the core.

In August 2025, OpenAI made headlines by releasing its first open-weight models in six years—gpt-oss-120b and gpt-oss-20b—with a notable twist: they embedded unsupervised chain-of-thought reasoning and explicitly asked developers to build their own monitoring systems for reasoning safety. Just days earlier, Anthropic released findings from its latest research on Large Reasoning Models (LRMs), revealing that extended reasoning often degrades accuracy, increases susceptibility to spurious signals, and amplifies undesirable behaviors like anthropomorphic self-preservation.

These announcements are not isolated events. Together, they signal a critical inflection point: the reasoning capabilities of frontier AI models have outpaced the infrastructure designed to govern them.

Through the lens of Trust Value Management (TVM), a methodology for operationalizing, measuring, and governing trust, we can now see clearly what’s at stake. Reasoning, long treated as a goalpost for general intelligence,…