Engineering

Prompting Tips 💡

Best practices and general tips for designing effective prompts. Learn how to iterate, be specific, and structure your instructions for better LLM performance.

Driptanil DattaSoftware Developer

Mar 20266 min read

Designing Effective Prompts

Prompt engineering is an iterative process. It requires experimentation and refinement to get optimal resultsrequires experimentation and refinement to get optimal results. Here are the core principles to keep in mind when designing your prompts.

1. Start Simple

Begin with a basic prompt and gradually add more elements and context as you aim for better results. If you have a complex task, try to break it down into simpler subtasks and build up step-by-step.

2. The Instruction

Use clear commands to tell the model exactly what you want it to do (e.g., "Write", "Classify", "Summarize", "Translate").

Example:

### Instruction ###
Translate the text below to Spanish:
 
Text: "hello!"

3. Specificity

Be highly descriptive and detailed about the desired outcome or stylehighly descriptive and detailed about the desired outcome or style. This is especially important when you need a specific format (like JSON or a comma-separated list).

Example of specific extraction:

Extract the name of places in the following text. 
Desired format: Place: <comma_separated_list_of_places>
 
Input: [Insert Text Here]

4. Avoid Impreciseness

Direct communicationDirect communication is more effective. Instead of saying "keep it short", specify exactly how long or for what audience the output should be.

5. Focus on "What to Do"

Instead of telling the model what not to do, focus on what it should do. This leads to more predictable and reliable responses.