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建立時間： 2026-06-19 來源： https://x.com/heynavtoor/status/2067194761446920264
Summary
Repackages Stanford OVAL Lab’s STORM method (NAACL 2024, multi-perspective question-asking for article synthesis) as a 4-prompt workflow runnable directly inside Claude with no tooling: simulate 5 expert perspectives, map contradictions between them, synthesize into a briefing, then peer-review the briefing’s own confidence and bias. Claims this compresses a 40-60 hour human research process into ~5 minutes.
將 Stanford OVAL Lab 的 STORM 方法（NAACL 2024，多視角提問式文章合成）重新包裝為可直接在 Claude 內執行、無需額外工具的 4 步提示詞流程：模擬 5 個專家視角、找出視角間的矛盾、整合為簡報，最後對簡報自身的信心程度與偏誤進行同行評審。文章宣稱此流程可將 40-60 小時的人工研究壓縮至約 5 分鐘。
Key Points
- STORM’s published result: multi-perspective-generated articles were 25% more organized and 10% broader in coverage than single-pass research articles (NAACL 2024, Stanford OVAL Lab).
- Prompt 1 simulates 5 fixed personas (practitioner, academic, skeptic, economist, historian) each giving a position, supporting evidence, and a unique claim no other perspective would surface.
- Prompt 2 explicitly maps contradictions between perspectives, identifies universal agreement (likely true), and surfaces topics none of the perspectives addressed (the field’s blind spot).
- Prompt 4 (peer review) addresses STORM’s own documented weakness — source bias and fact misassociation — by having the model score confidence per finding, name its weakest claim, and check whether one perspective was overrepresented.
- The persona set (practitioner/academic/skeptic/economist/historian) is fixed and domain-agnostic; the article suggests applying it before writing, before business decisions, before interviews, before investing, before negotiation, before presentations.
Insights
This is essentially a from-scratch reimplementation of an evaluator-optimizer / multi-agent debate pattern using personas-in-a-single-context rather than literal separate model calls — it gets some of STORM’s benefit (catching blind spots via diverse framing) without the retrieval/multi-perspective question generation that does the real grounding work in the original paper, so claims should be read as “good structured-thinking prompt” rather than “reproduces STORM’s retrieval-grounded fact quality.” Worth testing directly for /research-vault style synthesis work, especially Prompt 2 (contradiction map) and Prompt 4 (self peer-review), which are the two steps most other “AI research prompt” content skips.
Connections
Raw Excerpt
If all 5 perspectives agree, it is probably true. If nobody addressed a topic, you just found the gap in the entire field.