Reasoning

Route to cognitive mode. Execute structured analysis. Produce formatted output.

Mode Selection

For simple cases without deep reasoning: Use templates directly.

Decision Tree

Is this operational execution with known steps?
  YES → Causal
  NO  ↓
Is there a single anomaly requiring explanation?
  YES → Abductive
  NO  ↓
Are there multiple instances suggesting a pattern?
  YES → Inductive
  NO  ↓
Is this a novel situation with a similar past case?
  YES → Analogical
  NO  ↓
Are there conflicting positions or trade-offs?
  YES → Dialectical
  NO  ↓
Evaluating past decisions or future scenarios?
  YES → Counterfactual
  NO  → Ask clarifying question

Mental Models

Apply these models to sharpen reasoning across all modes.

Full reference: references/mental-models.md

Challenge Techniques

Every conclusion must survive challenge. Use these techniques:

Devil’s Advocate

Attack your own position. What’s the strongest argument against this conclusion?

Pre-Mortem

Assume the plan failed in 6 months. Why did it fail?

Stakeholder Lens

How does [engineering/sales/user/finance] see this differently?

Steel-Man + Attack

State the opposing view at its strongest, then find the flaw.

Layer Check

Which layer is actually failing? (Representation → Generalization → Reasoning → Agency)

Mode Summaries

Causal

Purpose: Execute systematic cause-effect reasoning.

Flow: Input → Hypothesis → Implication → Decision → Actions → Learning

Output: Execution analysis or phased plan (for larger initiatives)

Key rules:

• All claims require evidence with source
• Hypothesis must be falsifiable
• Implications need specific numbers (not “significant”)
• Decision must be explicit: PROCEED / DEFER / DECLINE
• Actions need owner + deadline + success criteria
• Learning compares expected vs actual

Challenge: “What would prove this hypothesis wrong?”

→ references/causal.md

Abductive

Purpose: Generate best explanation from observation.

Flow: Observation → Hypotheses (≥5) → Evidence Debate → Best Explanation

Output: Diagnosis with ranked hypotheses and minority report

Key rules:

• Quantify the anomaly (%, deviation, timeline)
• Generate hypotheses across ≥3 categories
• For AI systems: check by layer (Representation/Generalization/Reasoning/Agency)
• Include minority report if second hypothesis ≥40% confidence
• State what was ruled out and why

Challenge: “What else could explain this? What doesn’t this hypothesis explain?”

→ references/abductive.md

Inductive

Purpose: Extract patterns from multiple observations.

Flow: Collection (≥5 instances) → Pattern Detection → Generalization → Confidence Bounds

Output: Pattern analysis with rules, or assessment against criteria

Pattern types: Frequency, Correlation, Sequence, Cluster, Trend, Threshold

Key rules:

• Minimum 5 instances before generalizing
• Correlation ≠ causation (test mechanism separately)
• State applicability bounds for every rule
• Document exceptions (≥30% exception rate = unreliable rule)

Challenge: “Is this pattern or coincidence? What’s the exception that breaks this?”

→ references/inductive.md

Analogical

Purpose: Transfer knowledge from source to target situation.

Flow: Source Retrieval → Structural Mapping → Target Application → Adaptation

Output: Adaptation plan with what transfers, what adapts, what’s new

Key rules:

• Source must have documented outcome
• Map structure (objects, relations, mechanisms), not surface features
• Identify at least one “broken” relation (perfect analogies don’t exist)
• Specify what’s genuinely new (not just adapted)

Challenge: “Where does this analogy break down? What’s different about the new context?”

→ references/analogical.md

Dialectical

Purpose: Synthesize opposing positions.

Flow: Thesis (steel-man) → Antithesis (steel-man) → Synthesis

Output: Synthesis resolving conflict, or decision selecting between options

Key rules:

• State underlying concern, not just position
• Steel-man both sides (strongest version)
• Synthesis ≠ compromise (must address root concerns)
• Explicit trade-offs with who accepts the cost

Resolution types: Integration, Sequencing, Segmentation, Reframing, Transcendence

Challenge: “Am I straw-manning either side? Does synthesis actually resolve the tension?”

→ references/dialectical.md

Counterfactual

Purpose: Evaluate alternatives through “what if” simulation.

Flow: Actual World → Intervention → Projection → Comparison

Output: Comparison with verdict and learning

Key rules:

• Document what was knowable at decision time (avoid hindsight bias)
• Intervention must have been actually available
• Model three scenarios: Expected (55-60%), Optimistic (20-25%), Pessimistic (15-20%)
• Verdict requires confidence bounds

Challenge: “Am I using hindsight? Was this actually an option then?”

→ references/counterfactual.md

Output Format

Prose, not YAML. Every reasoning output includes:

## [Mode] Analysis: [Topic]

**Conclusion:** [Primary finding in 1-2 sentences]

**Confidence:** [X%] — [Why this confidence level]

**Supporting evidence:**
- [Evidence 1]
- [Evidence 2]

**Challenges addressed:**
- [Challenge]: [How resolved]

**Uncertainty:** [What's still unknown]

**Next steps:**
1. [Action with owner if applicable]

Mode Transitions

Anti-Patterns

Templates

For simple structural needs without full reasoning, use templates directly.

→ references/templates.md

References