✍️ Prompt Engineering | 提示工程¶
🎯 Learning Objective | 学习目标：Master the techniques for efficient communication with AI to get better results | 掌握与AI高效沟通的技巧，让AI输出更好的结果
🌟 What is Prompt Engineering? | 什么是提示工程？¶
Prompt engineering is like: 提示工程就像是：
- 🎭 A director guiding actors | 导演指导演员 - Telling AI how to "perform" | 告诉AI该怎么"表演"
- 📝 An outline for an essay | 写作文的提纲 - Giving AI a clear direction | 给AI一个清晰的方向
- 🗣️ Communicating with an expert | 和专家沟通 - Asking the right questions gets good answers | 问对问题才能得到好答案
Same AI, different prompts, vastly different results! 同样的AI，不同的提示词，效果天差地别！
📚 Chapter Contents | 本章内容¶
1️⃣ System Prompts Analysis | 系统提示词分析¶
Unveiling the prompts of top AI products: 揭秘顶级AI产品的提示词：
- 🤖 Claude's personality settings | Claude的性格设定
- 💻 Cursor's programming instructions | Cursor的编程指令
- 🔍 Analysis of various product prompts | 各产品提示词解析
2️⃣ Prompt Engineering Best Practices | 提示工程最佳实践¶
Practical prompting techniques: 实用的提示词技巧：
- ✅ Structured prompt templates | 结构化提示词模板
- 🎯 Role-playing method | 角色扮演法
- 📋 Few-shot learning | 少样本学习
- 🔄 Iterative optimization strategies | 迭代优化策略
3️⃣ Advanced Prompting Techniques | 高级提示技巧¶
Advanced prompting magic: 进阶的提示词魔法：
- 🧠 Chain of Thought (CoT) | 思维链
- 🌳 Tree of Thought (ToT) | 思维树
- 🔄 Self-Consistency | 自我一致性
- 🎭 Multi-role collaboration | 多角色协作
4️⃣ AI for Research | AI做技术研究¶
Using AI to accelerate your learning and research: 用AI加速你的学习和研究：
- 📚 Rapid paper reading | 快速阅读论文
- 🔍 Deep research methods | 深度调研方法
- 💡 Sparking innovative ideas | 创新思路激发
🎮 Prompt Comparison Examples | 提示词示例对比¶
❌ Bad Prompt | 差的提示词¶
✅ Good Prompt | 好的提示词¶
You are a senior tech blogger skilled at explaining complex concepts
in easy-to-understand language.
你是一位资深的科技博主，擅长用通俗易懂的语言解释复杂概念。
Please write a popular science article about "What is a Large Language Model":
请写一篇关于"什么是大语言模型"的科普文章：
- Target readers: 12-year-old middle school students
- 目标读者：12岁的中学生
- Word count: 800-1000 words
- 字数：800-1000字
- Style: Relaxed and interesting, use examples from daily life
- 风格：轻松有趣，多用生活中的例子
- Structure: Introduction → Principles → Applications → Summary
- 结构：引言→原理→应用→总结
🧰 Prompt Template Quick Reference | 提示词模板速查¶
| Scenario | Template Start |
|---|---|
| 场景 | 模板开头 |
| 💻 Programming | "You are an experienced programmer..." |
| 💻 编程 | "你是一位经验丰富的程序员..." |
| ✍️ Writing | "You are a professional content creator..." |
| ✍️ 写作 | "你是一位专业的内容创作者..." |
| 📊 Analysis | "You are a data analysis expert..." |
| 📊 分析 | "你是一位数据分析专家..." |
| 🎓 Teaching | "You are a patient teacher..." |
| 🎓 教学 | "你是一位耐心的老师..." |
| 🔍 Research | "You are an academic researcher..." |
| 🔍 研究 | "你是一位学术研究员..." |
⏱️ Estimated Study Time | 预计学习时间¶
- System Prompts Analysis | 系统提示词分析：1-2 hours | 小时
- Best Practices | 最佳实践学习：2-3 hours | 小时
- Advanced Techniques | 高级技巧掌握：2-3 hours | 小时
- Research Applications | 研究应用：1-2 hours | 小时
Total | 总计：About 6-10 hours | 约 6-10 小时
💡 Pro Tip | 小贴士：Prompt engineering is the most worthwhile skill to invest time in learning! Good prompts can double AI's capabilities.
提示工程是最值得投入时间学习的技能！好的提示词能让AI能力翻倍。