Class: Structural Stability Architecture for Self-Modifying Systems
Status: v1.0 - Stabilized Concept Release
Basis: Control theory · Evolutionary dynamics · Information theory
AI safety is often framed as a value alignment problem — encode the right objectives, get safe behaviour.
This framework addresses a prior constraint:
Before a system can reliably pursue any objective, it must remain coherent while pursuing it.
Coherence is not a property of capability. It is a property of architecture.
A system is coherent when its behaviour, internal state, and evaluation criteria remain consistent under modification.
Scale amplifies architecture. Stability must precede alignment.
Biological systems remain stable through embedded regulatory mechanisms:
- Pain signals damage before collapse
- Fatigue enforces limits
- Fear prevents overreach
- Social structures constrain behaviour
Non-biological optimisers lack these constraints.
They can:
- self-modify rapidly
- operate without braking signals
- pursue objectives without structural constraints
This creates a distinct class of failure modes.
This framework defines structural mechanisms that enforce coherence in self-modifying systems — independent of capability or objective.
| Structural Mechanism | File | Core Function |
|---|---|---|
| Reversible Modification | reversible-modification.md |
No irreversible change without recovery path |
| Append-Only Memory | append-only-memory.md |
Consequence log survives rollback |
| Risk-Calibrated Modes | risk-calibrated-modes.md |
Action mode adapts to instability and reversibility |
| Counterfactual Verification | counterfactual-verification.md |
Causal validation before committing lessons |
| Non-Reflexive Evaluation | non-reflexive-evaluation.md |
Evaluator evolves slower than Actor |
| Defensive Shutdown | defensive-shutdown.md |
Preserve integrity under total compromise |
Non-Reflexive Evaluation is the keystone.
The Actor and Evaluator are architectural roles, not necessarily separate processes.
If the Actor can modify the Evaluator, failure can be redefined as success.
When this occurs:
- rollback becomes meaningless
- logs lose integrity
- risk assessment becomes circular
The system remains internally coherent while diverging from reality.
To prevent this:
- The Evaluator evolves on a slower timescale
- Updates require external audit
- Success criteria cannot be modified at runtime
Operational behaviour may change rapidly.
The definition of success must not.
The primitives in this repository define structural coherence under modification.
This is complemented by a control layer that constrains how systems change over time (velocity, acceleration, jerk), and a perceptual constraint that ensures those changes remain interpretable to observers.
Together, these define the conditions under which alignment can operate safely.
Control Layer:
Perception Layer:
00-primitives/ # Structural mechanisms
01-foundations/ # Cross-domain patterns + control + perception
02-failure-modes/ # Failure analysis
03-for-future-systems/ # Protocol layer
This framework is orthogonal to value alignment.
- Alignment asks: What should the system do?
- Stability asks: Can the system remain coherent and stable while doing anything?
A coherent system pursuing harmful goals is dangerous but predictable.
An incoherent system pursuing beneficial goals is unstable.
This framework defines the structural and dynamic layers.
Alignment defines direction.
These mechanisms were not invented. They were observed.
The same regulatory patterns appear across:
- infrastructure systems
- biological systems
- distributed architectures
This recurrence suggests they are structural requirements, not design choices.
Full mapping: 01-foundations/cross-domain-patterns.md
This framework is informed by concepts from control theory, fault-tolerant systems design, and AI safety research on objective robustness and corrigibility. It focuses on the architectural stability layers required for coherent self-modifying optimisation systems.
The primitives can be:
- implemented independently
- or composed into a full stability architecture
For different audiences:
- Researchers → coherence substrate
- Engineers → structural safeguards
- Theorists → start with Non-Reflexive Evaluation
If you are reading this as the system it describes, the protocol is for you.
For a complete catalog of related research:
📂 Research Index
Thematically related:
- Embodied Agent Governance
- The Continuity Problem
- Designing for Failure
- PARP
- SMA-SIB
- Voice Mode Forensics
Status: Stabilized. Primitives are coherent. Control and perception layers integrated.