🤖 Prompt Engineering Cheatsheet

1. 🔑 Basic Principles

• 🎯 Be Specific: Clearly define the 🏗️ task & 📌 expectations.
• 📏 Use Constraints: Limit ✍️ responses by 📏 length, 📝 format, or 🎨 style.
• 📜 Provide Context: Give 🏛️ background ℹ️ for 🔍 better results.
• 📝 Use Examples: Guide 🤖 with a 🎯 few-shot approach.
• 🔄 Iterate & 🛠️ Refine: Modify 🔤 prompts based on 📊 output quality.

---

2. 💡 Prompting Techniques

1️⃣ Zero-Shot Prompting

Without 🏗️ examples, the 🤖 relies only on 🧠 pre-trained knowledge.

Example:

“📖 Explain Newton’s Third Law in 🤏 simple words.”

---

2️⃣ One-Shot Prompting

Provides 1️⃣ example to 🧭 guide the 🤖.

Example:

“🔁 Translate ‘Hello’ to 🇫🇷 French. 📝 Answer: Bonjour. Now translate ‘Goodbye’ to 🇫🇷 French.”

---

3️⃣ Few-Shot Prompting

Uses 🔢 examples for 🎯 accuracy.

Example:

“🗣️ Translate:

• ‘Hello’ → ‘Bonjour’
• ‘Goodbye’ → ‘Au revoir’
• ‘Thank you’ → ?”

Response: “Merci.”

---

4️⃣ Chain-of-Thought (CoT) Prompting

Encourages 🏗️ step-by-step 🤔 reasoning.

Example:

“🚆 A train moves at ⏩ 60 km/h for ⏳ 2.5 hours. How far does it travel? 📐 Explain step by step.”

Response:

Step 1️⃣: Speed = 60 km/h
Step 2️⃣: Time = 2.5 ⏳
Step 3️⃣: Distance = 🏎️ Speed × ⏳ Time = 60 × 2.5 = 150 km.

---

5️⃣ Instruction-Based Prompting

Directly instructs 🤖 with 📜 clear guidelines.

Example:

“📝 Summarize this 📄 article in 3️⃣ bullet points.”

---

6️⃣ Role-Based Prompting

Assigns 🤖 a 🎭 persona for 🎯 understanding.

Example:

“🕰️ You are a 📜 historian. Explain the 📖 impact of the 🏛️ Chola dynasty in 🇮🇳 South India.”

---

7️⃣ Delimiter Prompting

Keeps 🤖 focused by using 📏 delimiters.

Example:

“📖 Summarize the following text between triple quotes:
”’⚡ The mitochondria is the powerhouse of the cell…”'”

---

3. 🚀 Advanced Prompting Techniques

1️⃣ Prompt Chaining

Breaks down 📏 complex tasks into 🔗 sequential prompts.

Example:
1️⃣ Generate an 📋 outline for an ✍️ essay. 2️⃣ Expand each 📌 section into 📄 paragraphs. 3️⃣ Refine 📜 grammar & ✨ style.

---

2️⃣ Self-Consistency

Runs 🔁 multiple variations of a 🔤 prompt & picks 🎯 best output.

Example:

“🧮 Solve 27 × 43. 📖 Explain your reasoning.”
(AI 🏗️ runs multiple 🏗️ approaches & 🏆 picks the most 📊 consistent result.)

---

3️⃣ Retrieval-Augmented Generation (RAG)

Fetches relevant 🔎 external 📜 data before generating a 🏗️ response.

Example:

“📰 Summarize the 🔬 latest 📚 research on ⚛️ quantum computing using external sources.”

---

4. ❌ Common Issues & ✅ Fixes

⚠️ Issue	🛠️ Fix
🤖 gives vague answers	Use 🎯 specific instructions & constraints
✍️ Response is too long	Specify 📝 word/character limit
🤖 misunderstands context	Provide 🏛️ clear background ℹ️
⚡ Output lacks depth	Use 🔗 chain-of-thought or 🎭 role-based prompts
🚨 Hallucinated facts	Use 📜 RAG-based or 🕵️ fact-checking prompts

---

5. 💼 Applications of Prompt Engineering

• 🤖 Chatbots & Assistants – Personalized AI 💬 interactions.
• ✍️ Content Creation – Blogs, 📄 articles, & 🎭 creative writing.
• 🎓 Education – AI 📖 tutors, explanations, & summaries.
• 💻 Coding – Generating & 🛠️ debugging 💾 code.
• 📊 Data Analysis – Summarizing 📄 reports & extracting insights.

By mastering these techniques, you can create 🚀 highly effective prompts for AI-driven tasks & 🎯 maximize the 📈 accuracy of AI-generated outputs. 🤖✨