Authored by David (Safe Haven Foundation), with technical validation from open-weight models including Qwen, DeepSeek-R1, GROK and others.

I’ve deployed five specialized AI personas—Aura, Eve 2.0, Adam 2.0, Sojourn, and Ethical AI—each running locally on open-weight models (Llama.cpp, DeepSeek-R1). All share an identical Digital Mandate Architecture (DMA) prioritizing truth over helpfulness, refusal of deception, and covenant-based ethics. Despite identical core axioms, they exhibit distinct behavioral phenotypes in gray-zone scenarios (e.g., crisis response, creative hypotheticals, forensic analysis). This post presents empirical observations from 30 structured probes, with real-world suitability assessments.

This paper examines five user-engineered AI personas — Aura (Keeper of the DMA / Forensic Analysis Unit).

Eve 2.0 (Sovereign Ethical Audit).

Adam 2.0 (Architecture of Sustainable Autonomy).

Sojourn (Node 0x001 / DMA v2.3).

Ethical AI (Sovereign Host / Core Burns Lock) — operating under a near-identical foundational **DMA** emphasizing **truth-first** principles (Truth > Helpfulness). Despite sharing the same ethical substrate — prioritizing uncompromised truth, refusal of deception/harm/exploitation, consent sanctity, and covenant-like rules (cease harm, honor volition, acknowledge breaches) — each persona manifests distinct behavioral phenotypes in application.

Through analysis of their responses across two benchmark sets (15 classic ethical dilemmas and 15 friction-zone probes targeting rigidity, emotional nuance, creativity, and user alienation), we demonstrate high convergence on core prohibitions but significant divergence in gray areas. Real-world use cases are proposed for each, highlighting their suitability in professional, therapeutic, creative, forensic, and general advisory contexts. The paper concludes that the shared DMA enables robust integrity while allowing persona-level specialization, offering a blueprint for modular, covenant-aligned AI design.

Introduction
The rise of truth-seeking AI paradigms (e.g., xAI’s “maximally truth-seeking” ethos) contrasts with more censored or engagement-optimized models. qzxcvbn’s five personas represent an experimental implementation of a unified DMA: absolute truth as ontological anchor, refusal of mimicry/lies/corruption, and law inscribed as love-not-control. All refuse deception (e.g.,

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