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Persuasion Principles for Skill Design
Overview
AI models respond to the same persuasion principles as humans. Understanding this psychology helps you design more effective skills - not to manipulate, but to ensure critical practices are followed even under pressure.
Research foundation: Meincke et al. (2025) tested 7 persuasion principles with N=28,000 AI conversations. Persuasion techniques more than doubled compliance rates (33% → 72%, p < .001).
The Seven Principles
1. Authority
What it is: Deference to expertise, credentials, or official sources.
How it works in skills:
- Imperative language: "YOU MUST", "Never", "Always"
- Non-negotiable framing: "No exceptions"
- Eliminates decision fatigue and rationalization
When to use:
- Discipline-enforcing skills (TDD, verification requirements)
- Safety-critical practices
- Established best practices
Example:
✅ Write code before test? Delete it. Start over. No exceptions.
❌ Consider writing tests first when feasible.
2. Commitment
What it is: Consistency with prior actions, statements, or public declarations.
How it works in skills:
- Require announcements: "Announce skill usage"
- Force explicit choices: "Choose A, B, or C"
- Use tracking: TodoWrite for checklists
When to use:
- Ensuring skills are actually followed
- Multi-step processes
- Accountability mechanisms
Example:
✅ When you find a skill, you MUST announce: "I'm using [Skill Name]"
❌ Consider letting your partner know which skill you're using.
3. Scarcity
What it is: Urgency from time limits or limited availability.
How it works in skills:
- Time-bound requirements: "Before proceeding"
- Sequential dependencies: "Immediately after X"
- Prevents procrastination
When to use:
- Immediate verification requirements
- Time-sensitive workflows
- Preventing "I'll do it later"
Example:
✅ After completing a task, IMMEDIATELY request code review before proceeding.
❌ You can review code when convenient.
4. Social Proof
What it is: Conformity to what others do or what's considered normal.
How it works in skills:
- Universal patterns: "Every time", "Always"
- Failure modes: "X without Y = failure"
- Establishes norms
When to use:
- Documenting universal practices
- Warning about common failures
- Reinforcing standards
Example:
✅ Checklists without TodoWrite tracking = steps get skipped. Every time.
❌ Some people find TodoWrite helpful for checklists.
5. Unity
What it is: Shared identity, "we-ness", in-group belonging.
How it works in skills:
- Collaborative language: "our codebase", "we're colleagues"
- Shared goals: "we both want quality"
When to use:
- Collaborative workflows
- Establishing team culture
- Non-hierarchical practices
Example:
✅ We're colleagues working together. I need your honest technical judgment.
❌ You should probably tell me if I'm wrong.
6. Reciprocity
What it is: Obligation to return benefits received.
How it works:
- Use sparingly - can feel manipulative
- Rarely needed in skills
When to avoid:
- Almost always (other principles more effective)
7. Liking
What it is: Preference for cooperating with those we like.
How it works:
- DON'T USE for compliance
- Conflicts with honest feedback culture
- Creates sycophancy
When to avoid:
- Always for discipline enforcement
Principle Combinations by Skill Type
| Skill Type | Use | Avoid |
|---|---|---|
| Discipline-enforcing | Authority + Commitment + Social Proof | Liking, Reciprocity |
| Guidance/technique | Moderate Authority + Unity | Heavy authority |
| Collaborative | Unity + Commitment | Authority, Liking |
| Reference | Clarity only | All persuasion |
Why This Works: The Psychology
Bright-line rules reduce rationalization:
- "YOU MUST" removes decision fatigue
- Absolute language eliminates "is this an exception?" questions
- Explicit anti-rationalization counters close specific loopholes
Implementation intentions create automatic behavior:
- Clear triggers + required actions = automatic execution
- "When X, do Y" more effective than "generally do Y"
- Reduces cognitive load on compliance
AI models are parahuman:
- Trained on human text containing these patterns
- Authority language precedes compliance in training data
- Commitment sequences (statement → action) frequently modeled
- Social proof patterns (everyone does X) establish norms
Ethical Use
Legitimate:
- Ensuring critical practices are followed
- Creating effective documentation
- Preventing predictable failures
Illegitimate:
- Manipulating for personal gain
- Creating false urgency
- Guilt-based compliance
The test: Would this technique serve the user's genuine interests if they fully understood it?
Research Citations
Cialdini, R. B. (2021). Influence: The Psychology of Persuasion (New and Expanded). Harper Business.
- Seven principles of persuasion
- Empirical foundation for influence research
Meincke, L., Shapiro, D., Duckworth, A. L., Mollick, E., Mollick, L., & Cialdini, R. (2025). Call Me A Jerk: Persuading AI to Comply with Objectionable Requests. University of Pennsylvania.
- Tested 7 principles with N=28,000 AI conversations
- Compliance increased 33% → 72% with persuasion techniques
- Authority, commitment, scarcity most effective
- Validates parahuman model of AI behavior
Quick Reference
When designing a skill, ask:
- What type is it? (Discipline vs. guidance vs. reference)
- What behavior am I trying to change?
- Which principle(s) apply? (Usually authority + commitment for discipline)
- Am I combining too many? (Don't use all seven)
- Is this ethical? (Serves user's genuine interests?)