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用于结构性问题解决的系统动力学提示词

📅 2026-03-15 04:00 God of Prompt 人工智能 3 分鐘 2978 字 評分: 84
提示词工程 系统思维 问题解决 多内拉·梅多斯 LLM 应用
📌 一句话摘要 一个专门的提示词,将多内拉·梅多斯 (Donella Meadows) 的系统动力学方法论应用于 LLM,以识别反馈循环和杠杆点。 📝 详细摘要 这条推文介绍了一个旨在将 LLM 转化为系统动力学分析师的提示词。通过运用多内拉·梅多斯 (Donella Meadows) 的方法论,该提示词帮助用户超越治标不治本的层面,转而绘制底层结构和反馈循环,并识别出那些能以小博大、产生显著效果的最高杠杆干预点。 📊 文章信息 AI 评分:84 来源:God of Prompt(@godofprompt) 作者:God of Prompt 分类:人工智能 语言:英文 阅读时间:2 分钟
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Systems Dynamics Prompt for Structural Problem Solving ======================================================

Systems Dynamics Prompt for Structural Problem Solving ====================================================== ![Image 2: God of Prompt](https://www.bestblogs.dev/en/tweets?sourceId=SOURCE_f58696ab) ### God of Prompt

@godofprompt

Most problem-solving fails because it treats symptoms, not structure.

This prompt turns any LLM into a systems dynamics analyst trained on Donella Meadows' methodology.

It maps feedback loops, diagnoses system traps, and finds the highest-leverage intervention points where small moves create disproportionate change.

Full prompt below 👇

!Image 3: Tweet image

Mar 14, 2026, 8:00 PM View on X

5 Replies

3 Retweets

14 Likes

2,236 Views ![Image 4: God of Prompt](https://www.bestblogs.dev/en/tweets?sourceid=f58696ab) God of Prompt @godofprompt

One Sentence Summary

A specialized prompt that applies Donella Meadows' systems dynamics methodology to LLMs for identifying feedback loops and leverage points.

Summary

The tweet introduces a prompt designed to transform LLMs into systems dynamics analysts. By utilizing the methodology of Donella Meadows, the prompt helps users move beyond treating symptoms to mapping underlying structures, feedback loops, and identifying high-leverage intervention points where small changes can lead to significant results.

AI Score

84

Influence Score 10

Published At Today

Language

English

Tags

Prompt Engineering

Systems Thinking

Problem Solving

Donella Meadows

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Systems Dynamics Prompt for Structural Problem Solving | ... ===============

查看原文 → 發佈: 2026-03-15 04:00:04 收錄: 2026-03-15 06:01:06

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