yogsoth-ai Thought Experiment Strategy
Williamson methodology: construct precise, well-specified counterfactual scenarios that isolate individual variables.
Method
- causal-claim-extraction identifies the conclusion and its dependencies
- factor-enumeration identifies contingent vs. essential features
- counterfactual-scenario-construction builds precise thought experiments
- flip-point-detection identifies which scenario variations flip the conclusion
- necessity-evaluation determines if flipped factors are genuinely necessary
- load-bearing-identification distinguishes essential from contingent support
Design Principles
- Scenarios must be internally consistent (no impossible worlds)
- Changes must be minimal and precisely specified
- Background conditions must be held fixed except the target variable
- Conclusions must follow from the scenario, not from intuition pumps
Budget Table
| Parameter | S | M | L |
|---|---|---|---|
| Thought experiments | 3 | 8 | 15 |
| Variables isolated | 3 | 6 | 12 |
| Scenario precision checks | 1 | 3 | 6 |
Orchestration
causal-claim-extraction → factor-enumeration
→ [for each contingent feature]:
counterfactual-scenario-construction (precise scenario)
→ flip-point-detection (does conclusion hold?)
→ necessity-evaluation (is this genuinely necessary?)
→ load-bearing-identification (essential vs contingent)
Subagents
- causal-claim-extraction (dependency identification)
- factor-enumeration (contingent feature detection)
- counterfactual-scenario-construction (scenario design)
- flip-point-detection (conclusion testing)
- necessity-evaluation (necessity judgment)
- load-bearing-identification (classification)
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|---|
| causal-necessity-testing | Tactic: Extract causal claims, evaluate probability of necessity (PN) and sufficiency (PS) for each, classify into necessity-sufficiency quadrants. |
| minimal-change-search | Tactic: Generate candidate changes, detect flip-points where conclusion reverses, measure fragility as distance to nearest flip. |
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| causal-claim-extraction | Extract all causal claims (X causes Y, X leads to Y, X enables Y) from an artifact, producing a structured list of cause-effect pairs. |
| counterfactual-scenario-construction | Construct precise, internally consistent counterfactual scenarios where specified factors are altered, then reason about the resulting conclusion. |
| factor-enumeration | List all key factors, conditions, and assumptions that support or enable the artifact's conclusion. |
| flip-point-detection | Find the minimal change magnitude along a dimension that causes the conclusion to flip from true to false. |
| load-bearing-identification | Identify which factors are "load-bearing walls" — factors whose removal would collapse the conclusion. |
| necessity-evaluation | Evaluate the probability of necessity (PN) for a causal factor — would the conclusion fail if this factor were absent? |