Beginner LevelAI, LLMs, Embeddings & MCP
What are Zero-Shot, Few-Shot, and Chain-of-Thought (CoT) Prompt Engineering techniques?
❓ Interview Prompt: Compare Zero-Shot, Few-Shot, and Chain-of-Thought prompting strategies for improving task accuracy.
Prompt engineering shapes model input text to produce higher-quality, structured LLM completions:
1. Zero-Shot Prompting:
Asking the model to perform a task without providing any demonstration examples.
•
Example:
"Classify sentiment: 'I love this product!' ->"2. Few-Shot Prompting:
Providing 1 to 5 input-output demonstration examples inside the prompt before asking the target question. Guides output format and style.
3. Chain-of-Thought (CoT) Prompting:
Instructing the model to "think step-by-step" before producing its final answer. Significantly improves mathematical, logical, and coding accuracy.
Code Implementation Example
typescript
// Chain-of-Thought (CoT) Prompt Template
const cotPrompt = "Q: Roger has 5 tennis balls. He buys 2 more cans of tennis balls. Each can has 3 balls. How many tennis balls does he have now?\n" +
"A: Roger started with 5 balls. 2 cans of 3 balls each is 6 balls. 5 + 6 = 11. The answer is 11.\n\n" +
"Q: The cafeteria had 23 apples. If they used 20 to make lunch and bought 6 more, how many apples do they have?\n" +
"A: Let's think step by step.";💡Few-shot Chain-of-Thought prompt example encouraging step-by-step reasoning.
🎯 Interview Key Takeaway
Few-shot prompts provide format examples; Chain-of-Thought instructs step-by-step reasoning for complex problem solving.
#Prompt Engineering#Few-Shot#Chain-of-Thought#Beginner
Back to all AI, LLMs, Embeddings & MCP Questions→