Diamond: A Pre-Action Coherence Framework for AI-Assisted Work

This paper introduces Diamond, a lightweight, model-agnostic framework for improving safety and coherence in AI-assisted work. Unlike post-hoc filtering or output moderation, Diamond operates before action by structuring human–AI interaction through reflection, phase discipline, and explicit non-authority. The framework does not replace existing AI safety mechanisms; rather, it complements them by reducing hallucination drift, authority bias, and unsafe escalation at the interaction level. Early stress tests suggest that Diamond reliably stabilizes ambiguous or adversarial prompts without requiring refusal-heavy behavior or model intervention.