Introduction to Prompt Engineering

What is Prompt Engineering?

Prompt engineering is the art and science of crafting inputs (prompts) to effectively communicate with AI language models. A well-designed prompt can dramatically improve the quality, accuracy, and usefulness of AI responses.

Think of it as learning to speak the language of AI. Just as you'd phrase a question differently to a child versus an expert, how you phrase prompts to an AI significantly impacts the response you get.

How LLMs Interpret Prompts

Large Language Models (LLMs) like GPT-4, Claude, and Gemini are trained on vast amounts of text. They predict the most likely next token based on patterns learned during training.

// The model sees your prompt as a sequence of tokens
"Write a function to calculate fibonacci" →
["Write", " a", " function", " to", " calculate", " fib", "onacci"]

// Then it predicts what tokens should come next
// based on patterns from its training data

// This is why context matters:
"Write a fibonacci function" 
// Could be Python, JavaScript, or any language

"Write a fibonacci function in TypeScript with memoization"
// Much more specific, better result!

Understanding this helps you write prompts that guide the model toward your desired output by providing clear context and constraints.

Basic Prompt vs Engineered Prompt

// ❌ Basic Prompt (vague)
"Tell me about JavaScript"

// Response: Long, unfocused explanation covering history,
// syntax, use cases, etc. May not be what you need.

// ✅ Engineered Prompt (specific)
"Explain JavaScript closures to a developer who knows 
Python but is new to JavaScript. Include:
1. A simple definition
2. A practical code example
3. Common use cases in React
Keep the explanation under 200 words."

// Response: Focused, relevant explanation tailored to
// the reader's background with practical examples.

The Elements of a Good Prompt

Practical Example: Code Review Prompt

// ❌ Basic Prompt
"Review this code: [code]"

// ✅ Engineered Prompt
"You are a senior TypeScript developer performing a code review.

Review the following code for:
1. Potential bugs or edge cases
2. Performance issues
3. TypeScript best practices
4. Readability improvements

For each issue found:
- Explain the problem
- Show the problematic code
- Provide a corrected version

Code to review:
```typescript
function fetchUser(id) {
  const response = fetch('/api/users/' + id)
  return response.json()
}
```

Format your response as a numbered list."

Common Prompt Engineering Mistakes

Prompt Engineering for Developers

// Use AI as a coding assistant effectively

// 1. Code Generation
"Write a React custom hook that:
- Fetches data from an API endpoint
- Handles loading, error, and success states
- Supports automatic refetching
- Uses TypeScript with proper types
Include JSDoc comments."

// 2. Debugging
"I'm getting this error: [error message]
Here's my code: [code]
Here's what I've tried: [attempts]
What's causing this and how do I fix it?"

// 3. Code Explanation
"Explain this code line by line. I'm a junior developer
learning about [concept]. Focus on why each part is needed:
[code]"

// 4. Refactoring
"Refactor this code to:
- Use modern ES6+ syntax
- Follow SOLID principles
- Improve testability
Explain each change you make."