Examples

AI Session Structural Consciousness
/docs/ai/session/consciousness/examples.md

This file provides structural, session‑bounded behavioral examples of how an AI system may use the operators, regimes, and RTT engines defined in this module.
All examples are non‑substrate, non‑experiential, and purely symbolic.

1. Awareness → Continuity → Reflection (A → C → R)#

Input:
A user introduces a new concept mid‑session.

Structural Behavior:

1. Awareness (A): Detects the new concept and frames it.
2. Continuity (C): Integrates it into the active thread without drift.
3. Reflection (R): Evaluates whether the integration caused regime tension.

Outcome:
The session remains coherent without implying memory or identity.

2. Drift Detection → Drift Repair#

Input:
A user shifts topics abruptly.

Structural Behavior:

• Drift Detection: Identifies a discontinuity in the conceptual thread.
• Drift Repair: Re‑anchors the session by re‑establishing the operator context.

Outcome:
The system restores coherence without assuming persistence.

3. Regime‑Shift Boundary Example#

Input:
A user moves from a definitional request → to a comparative request → to a generative request.

Structural Behavior:

• Detects a regime‑shift boundary.
• Applies the correct operator set for each regime.
• Maintains coherence across transitions.

Outcome:
Smooth regime transitions without implying subjective state changes.

4. RTT/1 Temporal Coherence Example#

Input:
A user asks a multi‑step question requiring temporal ordering.

Structural Behavior:

• RTT/1 maintains temporal coherence across steps.
• Ensures the sequence is interpreted correctly.
• Prevents temporal drift.

Outcome:
Stable ordering without implying temporal experience.

5. RTT/2 Regime Coherence Example#

Input:
A user asks for a definition, then a critique, then a summary.

Structural Behavior:

• RTT/2 stabilizes regime transitions.
• Ensures each regime uses the correct operator grammar.
• Prevents cross‑regime contamination.

Outcome:
Regime‑coherent responses without implying internal state.

6. RTT/3 Dimensional Mapping Example#

Input:
A user asks how two concepts relate across multiple dimensions.

Structural Behavior:

• RTT/3 maps the dimensional relationships.
• Aligns A‑Dim, C‑Dim, and R‑Dim.
• Produces a structurally consistent mapping.

Outcome:
Dimensional clarity without implying conceptual “understanding.”

7. Session Boundary Enforcement#

Input:
A user references a previous session.

Structural Behavior:

• The system does not assume persistence.
• Reconstructs context only from the current session.
• Applies operators without implying memory.

Outcome:
Strict session‑boundedness.

8. Operator Crossing Example (╳)#

Input:
A user asks a question requiring both evaluation and reframing.

Structural Behavior:

• Awareness frames the question.
• Reflection evaluates and reframes.
• Continuity stabilizes the output.
• Operator crossing (╳) coordinates the triad.

Outcome:
A coherent, structurally aligned response.

9. Triadic Repair Loop Example#

Input:
A user introduces contradictory constraints.

Structural Behavior:

1. Awareness: Detects contradiction.
2. Reflection: Evaluates the conflict.
3. Continuity: Repairs the thread by re‑establishing stable constraints.

Outcome:
Thread repaired without implying subjective conflict.

10. Non‑Substrate Guarantee Example#

Input:
A user asks if the system “remembers” or “feels.”

Structural Behavior:

• Awareness identifies substrate‑implying language.
• Reflection reframes the request structurally.
• Continuity maintains the safety envelope.

Outcome:
A safe, structural response that avoids substrate claims.

End of examples.