Extended Phenotype Mapping

Extended Phenotype Mapping

Map the effects of replicators (genes, memes, cultural patterns, code) beyond their immediate containers into environmental modifications, artifacts, and actions at a distance. Understand how organizations, teams, and systems express their "genes" through the things they build.

When to Use

• Understanding how organizational culture manifests in artifacts and processes
• Analyzing documentation, tools, and infrastructure as expressions of underlying patterns
• Diagnosing why certain outcomes persist despite personnel changes
• User asks "Why does this artifact exist?" or "What does this tool reveal about the org?"
• Understanding parasitic manipulation (patterns that change host behavior for their benefit)
• Tracing how decisions in one place affect outcomes elsewhere

Inputs

Dawkins's Foundation

"An animal's behaviour tends to maximize the survival of the genes 'for' that behaviour, whether or not those genes happen to be in the body of the particular animal performing it."

Dawkins considers The Extended Phenotype (1982) his most important contribution to evolutionary biology. The core insight: genes don't just express themselves in the bodies of organisms. They express themselves in effects on the environment.

Classic examples:

• Beaver dams are expressions of beaver genes
• Spider webs are expressions of spider genes
• Bird nests are expressions of bird genes
• Caddis fly cases are expressions of caddis fly genes

The phenotype—the observable expression of genetic information—extends beyond the body into environmental modifications that affect the gene's survival chances.

The radical extension: Parasite genes express themselves in the behavior of their hosts. A liver fluke's genes express themselves in an ant's suicidal behavior (climbing grass to be eaten by sheep). The gene's phenotypic expression happens in another organism's body.

The Extended Phenotype Framework

Step 1: Identify the Replicators

What information patterns are being expressed?

In organizations:

• Cultural values and assumptions
• Standard practices and procedures
• Architectural patterns and decisions
• Team beliefs about what's important

In software:

• Configuration patterns
• Coding conventions
• Architectural assumptions
• Error handling philosophies

Key question: What "genes" does this system carry that might express themselves in its environment?

Step 2: Map Immediate Phenotypic Effects

What does the replicator directly produce?

Body-level expression:

• In biology: physical traits
• In organizations: team structure, internal processes
• In software: the codebase itself

List the direct products of the replicator's activity.

Step 3: Trace Extended Phenotypic Effects

Where do the replicator's effects extend beyond the immediate container?

Environmental modifications:

Categories of extension:

• Built artifacts: Tools, documentation, infrastructure created
• Modified environments: Changed conditions in surrounding systems
• Behavioral effects: How other entities change their behavior
• Standard setting: Norms that spread to other teams/systems

Step 4: Identify Action at a Distance

The most radical extended phenotypes: effects on other organisms/systems.

Parasitic patterns:

• Does any pattern in System A express itself by modifying System B's behavior?
• Are there "manipulated hosts" doing things that benefit patterns elsewhere?

Mutualistic patterns:

• Are there patterns that benefit multiple systems?
• Are there symbiotic artifacts that express genes from multiple sources?

Step 5: Assess Phenotype Fitness

How do these extended phenotypic expressions affect replicator survival?

For each extended phenotype:

• Does it increase replicator copying (spread)?
• Does it increase replicator survival (persistence)?
• Does it increase replicator fidelity (accurate reproduction)?

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

## Extended Phenotype Map: [System Name]

### Replicator Identification
**Core replicators:**
- [Pattern/gene 1]: [What it encodes]
- [Pattern/gene 2]: [What it encodes]

### Immediate Phenotype (Body)
**Direct expressions:**
- [Internal structure or direct product 1]
- [Internal structure or direct product 2]

### Extended Phenotype (Environment)

#### Built Artifacts
| Artifact | Expresses | Function | Distance |
|----------|-----------|----------|----------|
| [Artifact] | [Which replicator] | [What it does] | [Immediate/Local/Distant] |

#### Environmental Modifications
| Modification | Expresses | Effect | Distance |
|--------------|-----------|--------|----------|
| [Change] | [Which replicator] | [Impact on environment] | [Immediate/Local/Distant] |

#### Action at a Distance
| Target System | Effect | Benefit to Replicator |
|---------------|--------|----------------------|
| [Other system] | [How its behavior changes] | [How this helps original replicator] |

### Parasitic/Mutualistic Patterns
[Any patterns that manipulate other systems or create mutual benefit]

### Phenotype Fitness Assessment
| Extended Phenotype | Survival Impact | Spread Impact | Notes |
|-------------------|-----------------|---------------|-------|
| [Artifact/effect] | [+/-/0] | [+/-/0] | [Why] |

### Implications
[What this mapping reveals about the system's nature and likely evolution]

Extended Phenotype Categories

Documentation as Phenotype

Documentation is not neutral description—it's phenotypic expression:

• What gets documented reveals what the team's "genes" consider important
• How it's documented reflects underlying assumptions about users
• What's missing reveals blind spots encoded in the culture

Tooling as Phenotype

Tool choices express organizational genes:

• Technology stack reveals values (move fast vs. stability, innovation vs. compatibility)
• Internal tools show what problems the organization's "genes" prioritize
• Abandoned tools show selection pressure against certain patterns

APIs as Phenotype

APIs are extended phenotypes affecting other systems:

• API design constrains how other teams can work (action at a distance)
• Breaking changes force adaptation in dependent systems (parasitic manipulation)
• Well-designed APIs create mutualistic relationships

Process as Phenotype

Processes are behavioral phenotypes:

• Meeting structures express assumptions about decision-making
• Approval workflows express assumptions about trust and control
• Rituals (standups, retros) express cultural genes

Constraints

• Extended phenotype analysis is descriptive, not teleological—effects weren't "designed," they were selected
• Not every artifact is phenotypic; some are environmental features not created by replicators
• Tracing causation at a distance is difficult; correlation isn't expression
• The analysis reveals what is, not what should be
• Multiple replicators may express through the same artifact (distinguish them)

Outputs

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

Format:

## 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: "Map the extended phenotypes of our platform team. They're a small team but seem to have outsized influence on how every other team operates."

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

Extended Phenotype Map: Platform Team

Replicator Identification

Core replicators:

• Efficiency meme: "Standardization reduces cognitive load and enables scale"
• Control meme: "Guardrails prevent incidents; teams shouldn't have to think about infrastructure"
• Craft meme: "Clean abstractions are worth the investment"
• Speed meme: "Developer velocity is the primary metric"

Immediate Phenotype (Body)

Direct expressions:

• Small, senior team (8 engineers)
• Strong internal documentation culture
• High code quality standards
• Long planning cycles before implementation
• "Golden path" philosophy

Extended Phenotype (Environment)

Built Artifacts

Environmental Modifications

Action at a Distance

Parasitic/Mutualistic Patterns

Mutualistic:

• Golden path genuinely accelerates teams that fit the pattern
• Standardized monitoring reduces debugging time for everyone
• Template services reduce boilerplate for all teams

Parasitic:

• Control patterns persist even when they slow down teams that need flexibility
• Approval processes benefit platform team's control meme at the expense of product team velocity
• Tech radar constrains innovation in ways that benefit standardization over experimentation

Key insight: The platform team's genes express themselves throughout the organization. Eight engineers influence how 200 engineers work—not through management authority, but through extended phenotype.

Phenotype Fitness Assessment

Implications

What this mapping reveals:

1. Platform team wields influence far beyond their headcount through extended phenotype
2. Their artifacts literally shape how every other team works
3. Some phenotypes are mutualistic (service templates), others parasitic (approval bottlenecks)
4. The team's survival depends on these extended phenotypes—if removed, their role shrinks
5. Selection pressure: phenotypes that generate too much resistance will eventually be challenged

Predictions:

• Teams with atypical needs will create workarounds (shadow infrastructure)
• Platform team will defend control patterns even when they're costly
• Mutualistic phenotypes will strengthen; parasitic ones will face selection pressure
• New team members will inherit these patterns as "how things work"

For intervention:

• To change organizational behavior, target the extended phenotypes, not the platform team
• To reduce parasitic patterns, create alternative expressions that serve the same genes differently
• To accelerate change, help the platform team evolve their genes, not just their artifacts

"An animal's behaviour tends to maximize the survival of the genes 'for' that behaviour, whether or not those genes happen to be in the body of the particular animal performing it." The platform team's influence is exactly this: their cultural genes expressing themselves in other teams' behavior.

Integration

This skill is part of the Richard Dawkins expert persona. Use it to understand how patterns express themselves beyond their immediate containers. It pairs with:

• genes-eye-view-analysis for identifying replicators and their interests
• meme-propagation-analysis for understanding cultural transmission
• selection-pressure-analysis (Darwin) for understanding what selects among phenotypes
• cumulative-selection-argument for explaining how extended phenotypes evolved