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The Precision Prompting Manual: Forcing Superior AI Output through Constraints
Introduction: Beyond Generic Responses
Generic AI answers stem from unconstrained prompts allowing safe, vague paths. To get sharp, specific outputs, apply constraints that invalidate generics, forcing trade-offs, mechanisms, diagnostics, and defensible decisions. This guide covers foundational, tactical, and advanced patterns for practical use.
Foundational Constraints: Forcing Choice and Verifiability
Eliminate "it depends" by compelling clear stances.
Commitment Requirements:** Force a single choice, defense against counters, and opportunity costs.
How: Demand one option, justify vs. alternatives, state losses.
Example (Phone Upgrade): "Recommend one phone model under $800, defend against cheaper options, explain what I sacrifice."
Why: Makes neutrality impossible, yields real decision support.
Trade-Off Constraint: Admit goal conflicts and sacrifices.
How: Prioritize one goal, detail concessions.
Example (Health): "Prioritize muscle gain over enjoyment; list sacrifices like diet restrictions."
Why: Prevents all-benefits pretense, delivers realistic advice.
Failure Modes with Diagnostics: Map failures to symptoms and tests.
How: List distinct modes, unique signs, simple checks.
Example (Car Start): "List failure modes (battery, starter), symptoms (no lights vs. clicking), DIY tests."
Why: Turns lists into actionable troubleshooting.
Tactical Playbook: Deeper Divergence
Alter incentives, tools, structures for insightful paths.
Specific Lens with Incentives:** Use accountable roles for defensible answers.
How: Assign high-stakes persona (e.g., lawyer).
Example (Job Change): "As a career coach facing lawsuits for bad advice, recommend staying or quitting."
Why: Shifts from comfort to scrutiny, narrows claims.
Toolbox Restriction: Limit to one framework for depth.
How: Enforce a single lens, output its elements (e.g., incentives).
Example (Negotiation): "Analyze via game theory: payoffs, signals."
Why: Avoids mushy blends, forces precise translation.
Uncommon Structural Constraints: Mandate real-world formats.
How: Use memo, postmortem; ban bullets.
Example (Quitting Job): "Write as letter from future self, reflecting on decision."
Why: Disrupts defaults, enhances coherence.
Concrete Context Limitations: Add specifics to tailor strategies.
How: Include limits (budget, red lines).
Example (Salary): "Negotiate from $72k; no quitting threats, tight company budget."
Why: Starves ambiguity, yields situational plans.
Advanced Techniques: Restructuring Generation
Manipulate critique, words, reasoning for robust outputs.
Adversarial Prompt Chaining: Internal debate for refinement.
How: Sequence roles: propose, critique, defend.
Example (Purchase): "Propose buying; critique as skeptic; refine."
Why: Exposes assumptions, strengthens ideas.
Probability Inversion: Ban buzzwords for originality.
How: Forbid generics; use lived experiences.
Example (Productivity): "Describe habits without 'optimize' or 'focus'; use friction, anxiety."
Why: Escapes clichés, maps to real life.
Synthetic Context Override: Rule out commons for subtlety.
How: State facts, forbid usual causes.
Example (Breakup): "Not communication or cheating; suggest other causes."
Why: Explores complex dynamics.
Scoring Rules: Gamify for quantified specificity.
How: Penalize generics, reward risks; score and recommend.
Example (Car Buy): "-10 for vagueness, +5 per quantified risk; decide based on score."
Why: Drives data-driven commitments.
Conclusion: Guiding Principle
Redesign prompts to invalidate generics: force choices, mechanisms, diagnostics, penalties for vagueness. Elevate from averages to decision support.
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