Meta Mental Models

From Biology

From Mathematics/Statistics

From Psychology

Application Method

1. State the decision or problem
2. Select 2-3 relevant models from different disciplines
3. Apply each model to the situation — what does it suggest?
4. Compare conclusions — where do they agree? Where do they disagree?
5. Synthesize — the disagreement reveals the key trade-off to resolve

Output Format

# Multi-Model Analysis: {Decision}

## Models Applied
| Model | Discipline | Insight |
|-------|-----------|---------|
| {model 1} | {field} | {what this model says about the situation} |
| {model 2} | {field} | {what this model says} |
| {model 3} | {field} | {what this model says} |

## Convergence
{Where models agree — high confidence}

## Divergence
{Where models disagree — key trade-off to resolve}

## Synthesis
{Recommended decision based on multi-model analysis}

Gotchas

• Models are simplifications: Every model omits something. The map is not the territory. Use models as lenses, not as truth.
• Model inventory grows over time: Start with 10-15 core models. Add new ones as you encounter new domains. Quality of application matters more than quantity of models.
• Some models conflict by design: Inversion says "avoid failure." Evolution says "failure is how you learn." The conflict is resolved by context: avoid catastrophic failure, embrace recoverable failure.
• Don't force-fit: Not every model applies to every situation. If a model doesn't naturally illuminate the problem, skip it — don't stretch it to fit.

References

• For expanded mental models catalog (50+), see references/mental-models-catalog.md