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Effective Prompt Engineering Strategies for AI Coding
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Effective Prompt Engineering Strategies for AI Coding

• 2 min read
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The difference between average and exceptional AI-assisted coding often comes down to how you communicate with the AI. Let’s explore proven strategies.

The Anatomy of an Effective Prompt

A great prompt includes:

  1. Context - What are you building?
  2. Constraints - What are the requirements?
  3. Examples - What does success look like?
  4. Format - How should the output be structured?

Strategy 1: Be Specific About Context

❌ Bad prompt:

Write a function to validate email

✅ Good prompt:

Write a TypeScript function that validates email addresses for a 
user registration form. It should:
- Check for valid email format
- Reject disposable email domains
- Return a validation result object with isValid and errorMessage

Strategy 2: Use Chain-of-Thought

Ask the AI to think through the problem:

Before writing the code, explain:
1. What edge cases should we handle?
2. What's the best algorithm for this problem?
3. What are the tradeoffs of different approaches?

Then implement the solution.

Strategy 3: Iterate Incrementally

Don’t ask for everything at once. Build up:

  1. Start with the core logic
  2. Add error handling
  3. Optimize performance
  4. Add tests

Strategy 4: Provide Examples

Here's an example of the input/output I expect:

Input: { items: [1, 2, 3], multiplier: 2 }
Output: { items: [2, 4, 6], total: 12 }

Now implement a function that does this transformation.

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