Getting Started with Prompt Engineering

Published: August 18, 2025

Prompt engineering is the art and science of crafting inputs that elicit desired outputs from large language models. This post covers fundamental techniques and best practices.

Core Principles

1. Clarity and Specificity

python

Bad prompt

"Write code"

Good prompt

"Write a Python function that takes a list of integers and returns the median value, handling edge cases for empty lists."

2. Context and Examples

Providing context dramatically improves output quality:

markdown You are a technical documentation writer. Given this API endpoint, write clear documentation:

GET /users/{id} Returns user information by ID.

3. Iterative Refinement

Prompt engineering is iterative. Start broad, then refine:

1. Initial prompt: "Explain machine learning"
2. Refined: "Explain supervised learning algorithms for classification"
3. Specific: "Compare SVM and Random Forest for text classification tasks"

Advanced Techniques

Chain-of-Thought Prompting

markdown Solve this step by step: What is 15% of 240?

Step 1: Convert percentage to decimal Step 2: Multiply by the base number Step 3: State the final answer

Few-Shot Learning

python

Examples of function documentation:

def add(a, b): """Add two numbers and return the result.""" return a + b

def multiply(a, b): """Multiply two numbers and return the product."""
return a * b

Now document this function:

def factorial(n): if n <= 1: return 1 return n * factorial(n - 1)

Best Practices

1. Be specific about format: Specify JSON, markdown, code language
2. Set constraints: Word limits, style requirements, technical level
3. Use delimiters: Triple quotes, XML tags, or other clear boundaries
4. Test variations: Try different phrasings for the same request

Common Pitfalls

• Ambiguous pronouns: "It", "this", "that" without clear referents
• Assumed knowledge: Not providing necessary context
• Multiple requests: Combining unrelated tasks in one prompt

Conclusion

Effective prompt engineering requires practice and iteration. Start with these fundamentals and adapt based on your specific use cases and model behavior.

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Next: Advanced Prompt Patterns