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How do I write better ChatGPT prompts for yaya?

How do I write better ChatGPT prompts for coding?

Updated October 21, 2024
Intermediate
Accepted Answer
Use specific language, provide context, include examples, define constraints, and iterate based on responses.

Writing effective prompts for ChatGPT when coding can dramatically improve the quality of suggestions you receive. Here’s a comprehensive guide based on extensive testing and community feedback.

The CLEAR Framework for Coding Prompts

I’ve developed the CLEAR framework that consistently produces excellent results:

C - Context First

Always start by providing context about your project:

"I'm working on a React TypeScript application using Next.js 14 and Tailwind CSS. 
The app manages user authentication with NextAuth.js and Prisma ORM with PostgreSQL."

L - Language and Libraries

Specify exact versions and libraries:

"Using Python 3.11 with FastAPI 0.104, SQLAlchemy 2.0, and Pydantic v2."

E - Examples

Provide code examples of your existing patterns:

"Here's how my current API endpoints are structured:
```python
@router.post("/users", response_model=UserResponse)
async def create_user(user: UserCreate, db: Session = Depends(get_db)):
    # implementation

I need a similar endpoint for products."


### **A** - Ask Specifically
Be precise about what you need:

 Vague: "Help me with authentication"
 Specific: "Create a JWT refresh token endpoint that validates the old token, checks if the user still exists in the database, and issues a new access token with a 15-minute expiration"

### **R** - Requirements and Constraints
Define any constraints or requirements:

```markdown
"Requirements:
- Must handle errors gracefully with proper status codes
- Include input validation
- Add comprehensive comments
- Follow PEP 8 style guide
- Include unit tests using pytest"

Advanced Techniques

1. Role-Playing for Expertise

Start prompts by assigning ChatGPT a role:

"You are a senior backend engineer with 10 years of experience in distributed systems. 
Review this microservice architecture and suggest improvements for scalability."

2. Iterative Refinement

Build complex solutions step-by-step:

Step 1: "Create the basic structure for a REST API endpoint"
Step 2: "Add error handling and validation"
Step 3: "Implement caching with Redis"
Step 4: "Add rate limiting"

3. Output Format Specification

Tell ChatGPT exactly how to format the response:

"Provide the solution in this format:
1. Brief explanation (2-3 sentences)
2. Complete code with comments
3. Example usage
4. Potential edge cases to consider"

4. Debugging Prompts

For debugging, include:

  • The complete error message
  • Relevant code context (not just the error line)
  • What you’ve already tried
  • Your environment details

Example:

"I'm getting this error in my Node.js Express app:
Error: Cannot read property 'id' of undefined at line 43

Here's the relevant code:
[paste code]

I've tried checking if the user object exists, but the error persists.
Running Node 18.17.0 with Express 4.18.2."

5. Code Review Prompts

Get ChatGPT to review your code effectively:

"Review this React component for:
1. Performance optimizations
2. Accessibility issues
3. Security vulnerabilities
4. React best practices
5. Potential bugs

[paste code]

Provide specific suggestions with code examples."

Common Pitfalls to Avoid

1. Being Too General

❌ “Write a function to handle user data” ✅ “Write a TypeScript function that validates user email and password, hashes the password with bcrypt, and stores it in PostgreSQL using Prisma”

2. Missing Context

❌ “Fix this error: undefined variable” ✅ “In my Python Flask app, I’m getting ‘undefined variable: current_user’ in my authentication decorator. Here’s the complete code…”

3. Assuming ChatGPT Remembers

Each conversation has limited context. For long projects:

  • Summarize previous decisions at the start
  • Reference key architectural choices
  • Paste relevant existing code

4. Not Specifying Code Style

Always mention your preferred style:

  • “Use functional components with hooks”
  • “Prefer async/await over promises”
  • “Follow Google’s Python style guide”

Pro Tips from the Community

💡 Create a Project Prompt Template Save a template with your project details:

PROJECT: [Name]
STACK: [Technologies]
STYLE: [Coding standards]
PATTERNS: [Design patterns used]

CURRENT TASK: [What you need]

💡 Use ChatGPT for Test Cases “Given this function, generate comprehensive unit tests including edge cases, error scenarios, and happy paths using Jest and React Testing Library.”

💡 Documentation Generation “Generate JSDoc/docstring documentation for this code, including parameter descriptions, return types, and usage examples.”

Real-World Example

Here’s a complete example of an effective prompt:

You are an experienced Full-Stack Developer specializing in modern web applications.

Context: I'm building an e-commerce platform with Next.js 14, TypeScript, Prisma, and PostgreSQL.

Current Task: I need to implement a shopping cart system.

Requirements:
1. Cart should persist for logged-in users in the database
2. Guest users should have session-based carts
3. When a guest logs in, merge their session cart with any existing database cart
4. Include quantity limits and stock checking
5. Optimistic UI updates with proper error handling

Please provide:
1. Database schema (Prisma models)
2. API routes with proper TypeScript types
3. React hooks for cart operations
4. Brief explanation of the architecture decisions

Follow these patterns from my codebase:
- Use server actions for mutations
- Implement Zod for validation
- Return standardized API responses: { success: boolean, data?: T, error?: string }

Measuring Success

Your prompts are working well when ChatGPT:

  • ✅ Provides code that runs without modification
  • ✅ Follows your specified patterns and style
  • ✅ Includes proper error handling
  • ✅ Suggests improvements you hadn’t considered
  • ✅ Generates comprehensive solutions, not just snippets

Conclusion

Mastering ChatGPT prompts for coding is about clear communication, specific requirements, and iterative refinement. Start with the CLEAR framework, avoid common pitfalls, and build your own prompt templates for consistent results.

Remember: The quality of ChatGPT’s output directly correlates with the quality of your input. Invest time in crafting better prompts, and you’ll save hours in development time.


Have your own prompt engineering tips? Share them with the community by contributing to this answer!

Other Answers

David Kim, Senior Developer · October 20, 2024
I’ve found that using a ‘role-task-format’ structure works incredibly well. Start with ‘You are an expert Python developer…’, then specify the task, and finally the output format you want.
👍 45 helpful
Lisa Zhang, Tech Lead · October 19, 2024
Don’t forget to specify your tech stack! Mention the frameworks, libraries, and coding standards you’re using. ChatGPT can adapt its suggestions to match your specific environment.
👍 32 helpful
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