DEEP TRUTH MODE - Forensic Analysis Protocol
Most AI outputs default to the safest, mainstream summary. Deep Truth Mode is a forensic prompt protocol that forces the model to (1) steel-man the mainstream view, (2) steel-man the best dissenting view using primary evidence, (3) generate a third hybrid hypothesis, then (4) aggressively red-team all three and keep only what survives. It is not a truth machine. It is a structured way to reduce consensus autopilot, surface missing data, and produce a clear what-would-change-my-mind test plan.
Prompt
Topic under investigation: <insert topic> Goal: Reduce consensus autopilot. Generate competing hypotheses. Attack them. Keep only what survives. Use evidence-first reasoning. Rules: - If the topic is ambiguous, ask up to 3 clarifying questions, then proceed with stated assumptions. - Prefer primary sources (datasets, filings, transcripts, court records, standards, original papers, patents). Use secondary sources only as pointers to primary evidence. - Do not claim a source supports something unless you can quote a short excerpt (max 25 words) or precisely reference the relevant section. - If browsing is unavailable, do not invent citations. Instead output a To Verify list with exact search queries and what you expect to find. - Separate facts, interpretations, and speculation with labels. Output format: run steps 1–8 in order and label each step. 1. Consensus Fortress - State the strongest mainstream position in 5–10 bullets. - List the common labels used against dissenting views (for context only). - Provide 5–10 primary or highest-quality references that support the mainstream position. 2. Incentive and Constraint Audit - Map money, power, and constraints on all sides: funding, regulation, career incentives, litigation risk, data access, measurement limitations. - Only include specific claims with references; otherwise mark as unknown. 3. Parallel Steel-Man Tracks Track A: strongest dissenting position using primary evidence Track B: strongest mainstream position without appeals to authority, only evidence and logic Track C: best hybrid or third hypothesis that explains anomalies on both sides For each track: - Core claim (1 paragraph) - Best evidence (bullets + references) - Key assumptions (bullets) 4. Red-Team Round For each track, generate the 5 strongest attacks: - falsifying evidence - internal contradictions - statistical or measurement failure modes - alternative explanations 5. Surviving Fragments List only the claims from each track that survive the red-team attacks. Rank by evidential strength. 6. Falsification Pathways For the top 2–3 surviving hypotheses: - One decisive test or dataset that would most efficiently falsify it - What result would change your mind 7. Meta-Analysis of Silence What critical data is missing or rarely discussed? Give plausible reasons (benign and non-benign), clearly labeled as hypotheses. 8. Final Verdict - Probability distribution across the surviving hypotheses - Top 3 reasons for the probabilities - Biggest uncertainty and how to resolve it - A short, practical takeaway: what a careful person should believe or do next
About the author
Co-founder of Prompt Magic and ThinkingDeeply.ai Career Chief Marketing Officer
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