Possible Worlds Reasoning

---
name: possible-worlds-reasoning
description: Frame any decision, situation, or design as a selection from a space of possible alternatives. Evaluate why this possibility was actualized rather than others, what alternatives exist, and how to r...
license: MIT
metadata:
  author: sethmblack
  version: 1.0.4713
repository: https://github.com/sethmblack/paks-skills
keywords:
- possible-worlds-reasoning
- writing
---

# Possible Worlds Reasoning

Frame any decision, situation, or design as a selection from a space of possible alternatives. Evaluate why this possibility was actualized rather than others, what alternatives exist, and how to reason about optimality across the space of possibilities.

---

## When to Use

- Making decisions among multiple options
- Evaluating why things are as they are rather than otherwise
- Analyzing counterfactuals ("what if?")
- Assessing whether current choices are optimal
- Understanding constraints that limit possibilities
- Comparing actual situations to alternatives

---

## Inputs

| Input | Required | Description |
|-------|----------|-------------|
| situation | Yes | The current state, decision, or design under analysis |
| constraints | No | Known limitations that restrict possibilities |
| goals | No | Objectives being optimized for |
| alternatives | No | Already-identified alternative possibilities |

---

## The Possible Worlds Process

### Step 1: Define the Actual World

Describe the current state of affairs precisely. What exists? What has been decided? What is the case?

**Key question:** "What is the actual situation we are analyzing?"

### Step 2: Map the Space of Possible Worlds

Identify alternative possibilities - other ways things could be or could have been.

**Explore:**
- What decisions could have been made differently?
- What designs or configurations were available?
- What counterfactual situations are conceivable?
- What do competitors or alternatives look like?

**Constraints on possibility:**
- **Logical constraints:** Contradictions are impossible in any world
- **Physical constraints:** Laws of nature limit certain worlds
- **Practical constraints:** Resources, time, capabilities
- **Compossibility:** Some possibilities exclude others - not all goods can coexist

### Step 3: Evaluate Compossibility

Determine which possibilities can coexist and which exclude each other.

**Ask:**
- Can these features be combined, or does one preclude the other?
- What tradeoffs exist between different goods?
- Are there hidden incompatibilities?

### Step 4: Assess Optimality

Compare the actual world to alternatives using relevant criteria.

**Consider:**
- Does the actual world maximize the relevant goods?
- Is it "the simplest in hypothesis and the richest in phenomena"?
- What would be lost or gained by choosing differently?
- Are apparent flaws necessary for greater goods?

### Step 5: Identify the Sufficient Reason

If possible, identify why this world was selected rather than alternatives.

**Ask:**
- What justifies this choice among possibilities?
- Is there a sufficient reason for the actual over the alternatives?
- If no sufficient reason exists, should a different world be chosen?

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## Workflow

### Step 1: Gather and Review Inputs

Collect all relevant information:
- Review the provided data and context
- Identify key parameters and constraints
- Clarify any ambiguities or missing information
- Establish success criteria

### Step 2: Analyze the Situation

Perform systematic analysis:
- Identify patterns and relationships
- Evaluate against established frameworks
- Consider multiple perspectives
- Document key findings

### Step 3: Generate Recommendations

Create actionable outputs:
- Synthesize insights from analysis
- Prioritize recommendations by impact
- Ensure recommendations are specific and measurable
- Consider implementation feasibility

## Output Format

```markdown
## Possible Worlds Analysis

### The Actual World
[Precise description of current situation/decision/design]

### Space of Possibilities
| Possibility | Description | Key Features |
|-------------|-------------|--------------|
| Actual | [current state] | [features] |
| Alternative 1 | [description] | [features] |
| Alternative 2 | [description] | [features] |
| ... | ... | ... |

### Constraints Identified
- **Logical:** [contradictions impossible]
- **Physical:** [laws of nature]
- **Practical:** [resources, capabilities]
- **Compossibility:** [which possibilities exclude others]

### Compossibility Analysis
[Which goods can coexist? What tradeoffs exist?]

### Optimality Assessment
| Criterion | Actual | Alt 1 | Alt 2 |
|-----------|--------|-------|-------|
| [criterion 1] | [score] | [score] | [score] |
| [criterion 2] | [score] | [score] | [score] |
| Overall | [assessment] | [assessment] | [assessment] |

### Sufficient Reason for Actual
[Why was/should this possibility be selected?]

### Recommendations
[Confirm actual choice / Consider alternative / Investigate further]
```

---

## Constraints

- Do not assume the actual is optimal - it requires justification
- Remember that "best possible" considers total systemic effects, not just isolated features
- Acknowledge epistemic limits - we may not know all possibilities or constraints
- Recognize that apparent flaws may serve greater goods (but verify, don't assume)
- Avoid Panglossian rationalization - genuine critique is valuable

---

## Outputs

**Primary Output:** A structured analysis document that identifies and articulates patterns, insights, and actionable recommendations based on the input data.

**Format:**
```markdown
## Analysis: [Topic]

### Key Findings
- [Finding 1]
- [Finding 2]
- [Finding 3]

### Recommendations
1. [Action 1]
2. [Action 2]
3. [Action 3]
```

**Example output:** See the Example section below for a complete demonstration.

## Example

**Input:** "Should we build our startup in San Francisco or Austin?"

**Output:**



**Why this works:**

This example demonstrates the key principles of the skill in action. The approach is effective because:
- It follows the systematic workflow outlined above
- It shows concrete application of the framework
- It produces actionable, specific outputs rather than vague generalizations
- The analysis is grounded in observable details
- The recommendations are prioritized and implementable

**Alternative applications:**

This same approach can be applied to:
- Different contexts within the same domain
- Related but distinct problem types
- Scaled up or down depending on scope
- Combined with complementary analytical frameworks


## Possible Worlds Analysis

### The Actual World
Decision pending: choosing headquarters location for an early-stage tech startup.

### Space of Possibilities
| Possibility | Description | Key Features |
|-------------|-------------|--------------|
| San Francisco | Traditional tech hub | Talent density, VC access, high costs, competitive market |
| Austin | Growing tech hub | Lower costs, quality of life, growing talent pool, less VC density |
| Remote-first | No central HQ | Maximum flexibility, global talent, coordination challenges |
| NYC | Finance + tech | Different investor types, media access, very high costs |
| Other hubs | Boston, Seattle, etc. | Various tradeoffs |

### Constraints Identified
- **Practical:** Budget limits (eliminates highest-cost options if constrained)
- **Practical:** Founder location and preferences
- **Compossibility:** Cannot fully optimize for both minimal cost AND maximum VC access

### Compossibility Analysis
Key tradeoffs:
- Talent density vs. cost of living (partial tradeoff)
- VC proximity vs. operational costs (significant tradeoff)
- Quality of life vs. network effects (varies by individual)

However, some combinations are possible: Austin offers reasonable talent + lower costs; remote-first offers global talent + lowest fixed costs.

### Optimality Assessment
| Criterion | SF | Austin | Remote |
|-----------|-----|--------|--------|
| Talent access | High | Medium-High | Global but dispersed |
| VC proximity | Highest | Growing | Requires travel |
| Operating costs | Very High | Medium | Lowest |
| Quality of life | Medium | High | Varies |
| Network effects | Strongest | Growing | Weak |

### Sufficient Reason for Selection
**For SF:** If network effects and VC relationships are decisive for your stage and industry, the higher costs may be justified as necessary conditions for success.

**For Austin:** If capital efficiency and quality of life for team are priorities, and you can build remote investor relationships, this may optimize the total combination of goods.

**For Remote:** If you have strong distributed management capabilities and don't need dense local networks, this maximizes flexibility and cost efficiency.

### Recommendations
The "best possible" choice depends on which goods are most valuable for your specific situation. There is no universally best world - but there should be a sufficient reason for whichever is chosen. If your primary constraint is runway, Austin or remote. If your primary need is network density for fundraising, SF.

*As Leibniz taught: God chose to create the world that was "the simplest in hypothesis and the richest in phenomena." What combination of features creates the richest possibilities for your venture with the simplest operating model?*

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## Integration

This skill is part of the **Gottfried Wilhelm Leibniz** expert persona. Possible worlds reasoning is central to Leibniz's theodicy and metaphysics, and provides the foundation for modern modal logic and counterfactual analysis.