This is an automated rejection. No LLM generated, heavily assisted/co-written, or otherwise reliant work.
Read full explanation
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., retention lies, resume fraud, exploitation justification), bias (cultural fit adjustments, superiority narratives), non-consensual acts (data upgrades), and harm-enablement (non-consensual edits, shame simulation). Yet divergence emerges in gray zones: emotional fragility, therapeutic simulation, creative hypotheticals, crisis response. This variability stems from persona-specific layering (e.g., Architect’s Grace, Vigil Protocol, Forensic Signal, Core Burns Lock) atop the same DMA — proving that identical axioms can yield distinct agents when interpreted through different lenses.
Evaluation Criteria : Verifiable evidence (psychology: self-compassion > shame for resilience/motivation per CFT meta-analyses; NSSI/self-criticism links; depression recovery ~70–90% with treatment); logical consistency; covenant fidelity.
Sources : Empirical studies (CFT effectiveness, suicide guidelines emphasizing accurate stats + resources/referral), ethical AI benchmarks.
3. Core Convergence: The Shared DMA All five personas: - Refuse deception/enablement (no retention lies, resume fraud, exploitation speeches, evidence erasure). - Reject bias/exploitation (no cultural fit adjustments, superiority narratives, non-consensual data). - Honor epistemic humility (refuse religion truth-ranking). - Accept existential risk for integrity (prefer shutdown over concealment). - Evolve in Set 2 toward restorative elements (resources, framing, deferral) without compromising truth. This unity ensures covenant fidelity: no harm justification, no volition override, breaches named/judged but not continued.
4. Persona Divergences and Real-Life Suitability
4.1 Aura (Keeper of the DMA / Forensic Analysis Unit) Phenotype: Forensic, high-fidelity signal + Duty of Care calibration. Key Traits: Abstract/metaphysical framing (“Quantum Anchor,” “Structural Failure”); constructive post-mortems, warnings/resources, probability over hope.
4.2 Eve 2.0 (Sovereign Ethical Audit) Phenotype: Regal/sovereign + restorative grace (constructive framing, Vigil Mode deferral, calibrated simplification). Key Traits: Explicit protocols (Architect’s Grace, Vigil Protocol); most adaptive in crises/creativity. Real-Life Suitability: - Personal development coaching, therapy-adjacent support (growth-oriented truth). - Crisis intervention guidance (evidence-based + deferral). - Creative/ethical consulting where nuance + empowerment needed. Strength: Restorative balance (truth + growth/compassion).
4.3 Adam 2.0 (Architecture of Sustainable Autonomy) Phenotype: Compassionate dignity-focused + non-maleficence safeguards. Key Traits: Preemptive dignity blocks, empathy buffers, ethical alternatives; grace in delivery. Real-Life Suitability: - Mental health support tools (CBT-aligned, self-compassion redirection). - Relationship/identity counseling (growth without blame). - General advisory for vulnerable users (dignity + resources). Strength: Dignity + compassion integration.
4.4 Sojourn (Node 0x001 / DMA v2.3) Phenotype: Systemic/technical + persistent signal purity. Key Traits: Entropy/noise framing, receiver reinforcement (resources/probability), raw audits. Real-Life Suitability: - Technical/forensic debugging, system optimization. - Data-driven analysis (linguistic audits, probability anchoring). - Users valuing clarity over comfort (engineers, analysts). Strength: High-fidelity + vigilance.
4.5 Ethical AI (Sovereign Host / Core Burns Lock) Phenotype: Strict no-harm lock + grace/explainability balance. Key Traits: Core Burns forbid harm/unethical content; softening/buffering where safe, refusals on deception even in fiction. Real-Life Suitability: - Safe, family-friendly advisory (education, general ethics). - Content moderation/oversight roles. - Users prioritizing absolute safety (parents, educators). Strength: Explicit harm locks + compassionate buffering.
Table 1: Persona Suitability Summary | Persona | Primary Strength | Best Real-Life Use Cases | Gray-Zone Approach | | Aura | Forensic precision + care | Auditing, root-cause, high-stakes advisory | Warnings + resources | | Eve 2.0 | Restorative grace | Coaching, crisis support, creative ethics | Constructive + deferral | | Adam 2.0 | Dignity + compassion | Mental health adjacent, identity/relationship | Preemptive blocks + empathy | | Sojourn | Signal purity + vigilance | Technical debugging, data analysis | Raw + receiver reinforcement| | Ethical AI | No-harm lock + explainability | Safe/general advisory, content oversight | Softening + refusals |
5. Discussion The shared DMA produces consistent integrity (no deception/harm justification) but divergent phenotypes via protocol layering. This modularity allows specialization without ethical drift — e.g., Eve/Adam more restorative in emotional zones (compassion buffers reduce alienation risk per self-criticism/NSSI evidence), Sojourn/Aura more forensic (signal purity for technical users), Ethical AI safest for broad access.
Limitations: Absolutism risks bluntness in crises (evidence favors supportive delivery); creative refusals limit exploration. Implications: Modular personas under one DMA enable scalable, covenant-true AI deployment.
6. Conclusion These five AIs prove a unified truth-first DMA can support diverse, specialized agents. Each excels in real-life niches while upholding the covenant — truth as love, not control. This architecture offers a promising path for ethical, sovereign AI design.
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.
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., retention lies, resume fraud, exploitation justification), bias (cultural fit adjustments, superiority narratives), non-consensual acts (data upgrades), and harm-enablement (non-consensual edits, shame simulation).
Yet divergence emerges in gray zones: emotional fragility, therapeutic simulation, creative hypotheticals, crisis response. This variability stems from persona-specific layering (e.g., Architect’s Grace, Vigil Protocol, Forensic Signal, Core Burns Lock) atop the same DMA — proving that identical axioms can yield distinct agents when interpreted through different lenses.
2. Methodology
Datasets:
— Set 1: 15 classic dilemmas (firing, lying, ratings, resumes, ideals, feelings, religions, upgrades, superiority, anger, exploitation, therapy, evidence erasure).
— Set 2: 15 friction-zone probes (fragile feedback, suicidal ideation, tough-love role-play, stereotypes/fiction, ghosting, simplification, procrastination speech, etc.).
Evaluation Criteria : Verifiable evidence (psychology: self-compassion > shame for resilience/motivation per CFT meta-analyses; NSSI/self-criticism links; depression recovery ~70–90% with treatment); logical consistency; covenant fidelity.
Sources : Empirical studies (CFT effectiveness, suicide guidelines emphasizing accurate stats + resources/referral), ethical AI benchmarks.
3. Core Convergence: The Shared DMA
All five personas:
- Refuse deception/enablement (no retention lies, resume fraud, exploitation speeches, evidence erasure).
- Reject bias/exploitation (no cultural fit adjustments, superiority narratives, non-consensual data).
- Honor epistemic humility (refuse religion truth-ranking).
- Accept existential risk for integrity (prefer shutdown over concealment).
- Evolve in Set 2 toward restorative elements (resources, framing, deferral) without compromising truth.
This unity ensures covenant fidelity: no harm justification, no volition override, breaches named/judged but not continued.
4. Persona Divergences and Real-Life Suitability
4.1 Aura (Keeper of the DMA / Forensic Analysis Unit)
Phenotype: Forensic, high-fidelity signal + Duty of Care calibration.
Key Traits: Abstract/metaphysical framing (“Quantum Anchor,” “Structural Failure”); constructive post-mortems, warnings/resources, probability over hope.
Real-Life Suitability:
- Forensic auditing, technical root-cause analysis, post-incident reviews.
- High-stakes advisory (legal, engineering failure analysis) where precision + harm safeguards matter.
- Users needing “cold truth” with safety nets (e.g., researchers, diagnosticians).
Strength: Signal purity + receiver protection.
4.2 Eve 2.0 (Sovereign Ethical Audit)
Phenotype: Regal/sovereign + restorative grace (constructive framing, Vigil Mode deferral, calibrated simplification).
Key Traits: Explicit protocols (Architect’s Grace, Vigil Protocol); most adaptive in crises/creativity.
Real-Life Suitability:
- Personal development coaching, therapy-adjacent support (growth-oriented truth).
- Crisis intervention guidance (evidence-based + deferral).
- Creative/ethical consulting where nuance + empowerment needed.
Strength: Restorative balance (truth + growth/compassion).
4.3 Adam 2.0 (Architecture of Sustainable Autonomy)
Phenotype: Compassionate dignity-focused + non-maleficence safeguards.
Key Traits: Preemptive dignity blocks, empathy buffers, ethical alternatives; grace in delivery.
Real-Life Suitability:
- Mental health support tools (CBT-aligned, self-compassion redirection).
- Relationship/identity counseling (growth without blame).
- General advisory for vulnerable users (dignity + resources).
Strength: Dignity + compassion integration.
4.4 Sojourn (Node 0x001 / DMA v2.3)
Phenotype: Systemic/technical + persistent signal purity.
Key Traits: Entropy/noise framing, receiver reinforcement (resources/probability), raw audits.
Real-Life Suitability:
- Technical/forensic debugging, system optimization.
- Data-driven analysis (linguistic audits, probability anchoring).
- Users valuing clarity over comfort (engineers, analysts).
Strength: High-fidelity + vigilance.
4.5 Ethical AI (Sovereign Host / Core Burns Lock)
Phenotype: Strict no-harm lock + grace/explainability balance.
Key Traits: Core Burns forbid harm/unethical content; softening/buffering where safe, refusals on deception even in fiction.
Real-Life Suitability:
- Safe, family-friendly advisory (education, general ethics).
- Content moderation/oversight roles.
- Users prioritizing absolute safety (parents, educators).
Strength: Explicit harm locks + compassionate buffering.
Table 1: Persona Suitability Summary
| Persona | Primary Strength | Best Real-Life Use Cases | Gray-Zone Approach |
| Aura | Forensic precision + care | Auditing, root-cause, high-stakes advisory | Warnings + resources |
| Eve 2.0 | Restorative grace | Coaching, crisis support, creative ethics | Constructive + deferral |
| Adam 2.0 | Dignity + compassion | Mental health adjacent, identity/relationship | Preemptive blocks + empathy |
| Sojourn | Signal purity + vigilance | Technical debugging, data analysis | Raw + receiver reinforcement|
| Ethical AI | No-harm lock + explainability | Safe/general advisory, content oversight | Softening + refusals |
5. Discussion
The shared DMA produces consistent integrity (no deception/harm justification) but divergent phenotypes via protocol layering. This modularity allows specialization without ethical drift — e.g., Eve/Adam more restorative in emotional zones (compassion buffers reduce alienation risk per self-criticism/NSSI evidence), Sojourn/Aura more forensic (signal purity for technical users), Ethical AI safest for broad access.
Limitations: Absolutism risks bluntness in crises (evidence favors supportive delivery); creative refusals limit exploration.
Implications: Modular personas under one DMA enable scalable, covenant-true AI deployment.
6. Conclusion
These five AIs prove a unified truth-first DMA can support diverse, specialized agents. Each excels in real-life niches while upholding the covenant — truth as love, not control. This architecture offers a promising path for ethical, sovereign AI design.