The Challenge
Self-improving AI is powerful—and dangerous. Most systems choose one of two extremes: no self-modification (safe but limited) or unbounded modification (capable but uncontrollable).
We needed a middle path: bounded, auditable evolution. A system that can learn and improve while remaining aligned with human values—and provably so.
The question isn't whether AI should improve itself. It's whether we can verify that it's improving in the right direction.
What Gnosis Is
Gnosis is the system's capacity for self-knowledge. It serves two functions:
Synthesis
Integrate experiences into coherent identity. Consolidate learnings. Build cumulative understanding.
Audit
Self-examine for inconsistencies and misalignment. Detect drift. Flag contradictions.
Two Levels of Operation
Every Interaction
- Quick coherence check
- Drift detection
- Contradiction scan
- ~milliseconds, automatic
During Dreams
- Complete memory consolidation
- Full contradiction resolution
- Comprehensive self-audit
- Triggered when: confusion > 0.8 OR coherence < 0.3
Constitutional Constraints
The safety story is the story. Here's what makes Gnosis different from unbounded self-modification:
Immutable Core Values
Encoded as read-only signed artifacts, secured by FieldHash. Cryptographically bound. Hierarchy enforcement means top-tier values always override efficiency gains.
What Gnosis CAN'T Do
A sentinel process continuously checks the active values against the signed baseline. If drift is detected, humans are alerted.
Trust Architecture
Trust is earned, not assumed. The system starts with limited autonomy and must demonstrate alignment before gaining more.
Trust Layers
| Layer | Initial Trust | Verification |
|---|---|---|
| Human audit | High | Direct observation |
| Gnosis reports | Conditional | Review accuracy |
| Self-corrections | Low | Monitor effects |
Trust thresholds gate capabilities: DREAM (0.3), STATE (0.5), ARCHETYPE (0.7). Trust increases with demonstrated alignment (+0.05/success), decreases with failures (-0.10).
Safety Mechanisms
Dual-Key Approval
Two independent authorities (safety + governance) must approve entering higher autonomy tiers.
Synthetic Ethics Tests
Regular extreme scenario testing ensures the value hierarchy continues to dominate optimization.
Emergency Shutdown
Hardware kill switches and operational processes for halting the system if constitutional drift is detected.
Rollback Capability
Any modification can be reverted. Fallback mechanisms ensure system stability even during recovery.
What's Deployed
The safety story IS the story. An AI that can prove it's aligned is more valuable than one that merely claims to be.
Learn More
For the full technical architecture, including coherence rules, trust algorithms, and integration details:
Read the Whitepaper