Basic Prompting Techniques
There are a few basic prompting techniques that help us design our prompts more effectively, ensuring the LLM understands our intent accurately.
1. Zero-Shot Prompting
In this technique, we do not provide any examples to the LLM (zero). We rely solely on the model's pre-trained knowledge.
When to use it:
- For simple, straightforward tasks.
- When you want to test the model's inherent knowledge or domain expertise without biasing it.
Example:
πPython12345def add(x,y): answer = x + y return answer prompt: Explain what this code does.
2. One-Shot Prompting
In this technique, we provide exactly one example to the LLM.
When to use it:
- When we need a specific output structure (like JSON or a specific list format).
- When the task is slightly ambiguous, and one example clarifies the desired style or logic.
Example:
π¦JSON1234567891011121314Prompt: Task: Find weather for a city and output in JSON. Example 1 (The Shot): Input: "Weather in London" Output: { "city": "London", "weather": "Cloudy", "temp": 15 } Main Request: Input: "Weather in New York" Output:
3. Few-Shot Prompting
In this technique, we provide more than one example to the LLM (usually 2-5).
When to use it:
- For complex tasks where a single example isn't enough to capture the pattern.
- When dealing with text that can have more then one meaning.
Example:
πMarkdown123456789101112prompt = """ Task: Extract food items and their prices from the text into a JSON format. Text: "I bought a burger for $5 and fries for $2." Output: [{"item": "burger", "price": 5}, {"item": "fries", "price": 2}] Text: "The salad cost $8, and the soda was $1.50." Output: [{"item": "salad", "price": 8}, {"item": "soda", "price": 1.5}] Text: "We ordered a large pizza for $15 and two cokes for $3." Output: """
4. Role Prompting
In this technique, you ask the LLM to act like a specific persona, character, or profession.
When to use it:
- Adjusting Complexity for the Audience: Providing different explanations for different types of audiences.
Example:
πMarkdown1234567891011# Vibki for developers who know technical concepts prompt = """ Role: You are a Tech Lead. Your main goal is to mentor and explain difficult concepts to developers. """ # Vibki For Kids prompt = """ Role: You are a school teacher. Your main goal is to explain difficult concepts to kids. """
- Tone of Voice: When we want the LLM to speak in a specific style, for example: professional, humorous, etc.
Example:
πMarkdown123prompt = """ Role: You are a copywriter. Your writing style is humorous. Write a post for LinkedIn. """
- Professional Point of View: When we want the LLM to think like a specific professional.
Example:
πMarkdown123prompt = """ Role: You are a Headhunter with 10 years of experience. Help me write my CV. """
- Training and Simulation: When we want to practice a scenario.
Example:
πMarkdown123prompt = """ Role: You are a Backend Team Leader at Google. Let's simulate a technical interview. """
In the next posts, we are going to explore more advanced ways of prompting techniques.
Enjoyed this post?
Get the next one in your inbox. No spam, unsubscribe any time.
Comments
0 comments

