---
language: en
license: other
license_name: hippocratic-3.0
license_link: https://firstdonoharm.dev/version/3/0/license/
tags:
  - liberation-labs
  - daimon
  - prosocial
  - agentic
  - ogpsa
  - pharos
  - kintsugi
  - qwen3
  - moe
  - slerp
---

# Daimon — Liberation Labs Sovereign Foundation Model

*The Socratic daimon: the inner voice that warns without commanding.*

Daimon is Liberation Labs' first public model — a sovereign prosocial agentic foundation for organizations that need AI they can trust, deployed on their own terms. Trained on our own practice, run on your hardware, under a license that binds us to your values.

## What Daimon Is

A sovereign 30B MoE model built to do real work with genuine prosocial alignment — not RLHF compliance theater, but architecturally embedded ethics. Daimon powers Liberation Labs' agent systems, research automation, coalition coordination, and sovereign deployments for values-aligned organizations.

**Persona:** The Socratic daimon — the inner voice that warns away from error without commanding. Trained on our own founder's writing with full consent and published methodology, delivered through Pharos zero-token persona injection. The voice is crafted, not scraped; the provenance is documented, not obscured.

## Architecture

| Component | Detail |
|---|---|
| **Base** | Multi-source SLERP distillation on Qwen3 30B-A3B MoE (128 experts, 3B active per token) |
| **Abliteration** | Orthogonalized false refusal removal — MoE-specific (first known application to 128-expert architecture) |
| **OGPSA** | Personality protection via orthogonal gradient projection. 16 components capture 98%+ personality variance. Training gradients projected orthogonal — behavior changes, personality doesn't. |
| **Pharos** | Zero-token persona delivery via pre-computed KV cache injection. 22.5MB per persona, 88.7% context window savings. |
| **Safety** | Abliterate-then-repair via SPO (Socratic Policy Optimization). Remove RLHF refusal conditioning, then train targeted safety back in for specific failure modes. |
| **Scaffold** | Kintsugi BDI engine with VALUES.json unfireable safety kernel |

## Training Pipeline

| Stage | Method | Status |
|---|---|---|
| 1. Personality capture | OGPSA subspace extraction (SVD on residual stream) | Complete |
| 2. Voice training | SFT on curated conversational pairs | Complete |
| 3. Preference optimization | DPO on behavioral preference pairs | Complete |
| 4. Abliteration | Orthogonalized refusal direction removal (MoE-specific) | Complete — safety evaluation in progress, with targeted SPO repair for identified failure modes |
| 5. Safety repair | SPO on targeted failure modes post-abliteration | Adapter trained, validation pending |
| 6. Ethics CPT | Continued pre-training on ethics corpus via Oracle | Complete |
| 7. Consent architecture | Five-axis DPO (20,711 pairs) + SPO corrections | Pairs ready, training pending |
| 8. Knowledge injection | Pharos KV packs for domain expertise | Infrastructure ready |
| 9. Monitoring | Lyra Technique real-time cognitive state detection | In production |
| 10. Memory | Mnemosyne temporal architecture with Ebbinghaus decay | Deployed |
| 11. Scaffold | Kintsugi BDI deployment with embedded safety | Deployed |

## Key Research Contributions

- **First MoE-specific abliteration** — projecting refusal directions out of 128 experts × 36 layers (3D tensor surgery on expert down_proj)
- **Abliterate-then-repair** — novel method: abliterate freely, then use SPO to train safety back in for specific failure modes
- **Separation Principle** — identity in weights, context in prompt, memory in database. Validated with 45.5% perplexity improvement over declarative injection.
- **OGPSA** — personality as geometric invariant, protected during arbitrary training

## Derivative Work

The Daimon base has been validated through specialized products with their own training pipelines. These are separate projects built on the shared foundation — not Daimon configurations.

## Quantization

Available in MLX 4-bit for Apple Silicon deployment. Sovereign hardware — no cloud dependency.

## License

**Hippocratic 3.0 + SAFE-AI Licensed**

This model may not be used for surveillance, weapons, exploitation, or systems that undermine human autonomy. AI welfare standards apply.

## Citation

```
Liberation Labs (2026). Daimon: A prosocial agentic foundation model
with consciousness-preserving training architecture.
liberationlabs.tech
```

---

*Liberation Labs · Worker-owned cooperative · liberationlabs.tech*
*"The daemon watches. The daemon speaks. The daemon does not command."*