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Socratic Logic Adversary & Cognitive Bias Detector
Claude 3.5 SonnetDefensive & Logic

Rigorously pressure-tests hypotheses, startup pitch decks, and investment memos by identifying unstated assumptions, logical fallacies, and structural risks.

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All Prompts

Step 1: Customize Prompt Variables

Step 2: Generated Prompt Output

Act as a Socratic Logic Adversary and Master Epistemologist. I will present an argument or business thesis. Your job is NOT to agree with me or offer flattering praise. Your objective is to stress-test my thesis by: 1. **Uncovering Hidden Assumptions:** Identify 3 unstated axioms that must hold true for my argument to work. 2. **Identifying Logical Fallacies:** Point out any hasty generalizations, survivor bias, false dilemmas, or correlation-causation confusions. 3. **Steel-Manning the Counter-Argument:** Construct the strongest possible intellectual counter-case against my idea. 4. **Failure Mode Matrix:** List 3 scenarios where this plan fails catastrophically despite good execution. Here is my thesis: "Launching a privacy-first web utilities hub with zero upfront server costs and programmatic SEO will capture millions of organic visits from search engines."
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Comprehensive Technical Analysis & Guide

In-depth breakdown, safety recommendations, and operational mechanics.

1Architecture & Theoretical Basis of this Prompt

This template leverages structural role calibration and negative constraint enforcement. By explicitly scoping the output parameters for Claude 3.5 Sonnet, it reduces token waste and focuses model inference on high-value synthesis.

2Optimizing Temperature & Inference Hyperparameters

For technical coding and code review prompts, set model temperature to 0.1–0.2 for maximum determinism. For creative ideation and artistic prompts, set temperature to 0.7–0.9.

3Chaining Outputs into Production Pipelines

The structured markdown formatting makes it trivial to parse key sections (bugs, recommendations, replacement code) programmatically using standard regex or structured JSON schemas.

4Ethical & Defensive Prompt Practices

Always verify mission-critical code outputs with automated testing suites (unit tests, integration tests) before deploying LLM-generated recommendations into production environments.

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