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Boost Your Business Central Development: GitHub Copilot Tips & Prompt Strategies

 In today's fast-paced software development environment, automation and AI have become indispensable tools for improving productivity. One of the most groundbreaking innovations in this area is GitHub Copilot, an AI-powered assistant that can help developers write code faster and more efficiently. For Business Central developers, leveraging GitHub Copilot can be a game-changer, making complex AL programming tasks easier, more intuitive, and less time-consuming. In this article, we’ll explore how GitHub Copilot can boost your Business Central development process and provide use cases along with effective prompt strategies.

What is GitHub Copilot?

GitHub Copilot is an AI-powered tool developed by GitHub in collaboration with OpenAI. It acts as a virtual pair programmer by suggesting entire code snippets, functions, and even documentation, all based on the context of the code you are writing. The tool is built on OpenAI’s Codex language model, which has been trained on a vast range of code from public repositories.

Why Use GitHub Copilot in Business Central Development?

Business Central developers work with AL programming, which involves customizing and extending Dynamics 365 Business Central applications. This environment is rich with various objects like tables, pages, reports, and queries, all of which require a deep understanding of the platform’s intricacies.

GitHub Copilot helps streamline the development process by:

  1. Speeding up development: Copilot can generate code faster than writing it manually, saving developers significant time on repetitive tasks.
  2. Improving code quality: The AI suggests solutions based on best practices, helping to ensure that the code adheres to industry standards.
  3. Enhancing learning: Copilot can assist novice developers by showing them how to write code and use various AL language features.

How GitHub Copilot Works with AL Programming in Business Central

1. Code Completion

GitHub Copilot suggests complete code snippets as you type. For instance, if you’re defining a table extension in AL, GitHub Copilot might suggest a complete set of field definitions based on what you’ve written so far.

Use Case:

You’re working on a Customer Table Extension and want to add a custom field for storing customer preferences. As you begin typing the table extension code, Copilot can suggest the entire code block for adding the new field.

2. Auto-Generated Functions and Methods

GitHub Copilot can generate entire functions or methods based on the context you provide. It recognizes patterns in the AL code and can offer helpful suggestions for functions, events, or even triggers.

Use Case:

Suppose you need to create a function that updates customer records. Instead of manually typing out all the boilerplate code, Copilot can suggest a well-structured function based on your code’s context.

3. Documentation and Comments

Writing clear documentation for AL code is essential, but it can be time-consuming. GitHub Copilot helps by suggesting documentation comments, especially for public methods and complex code.

Use Case:

When working on a function, GitHub Copilot can generate comments explaining the purpose of the method and how it works, making your code more readable and maintainable.

4. Error Handling Suggestions

Business Central developers often need to add error handling to their AL code. GitHub Copilot can help by suggesting the correct structure for try-catch blocks, enabling developers to handle errors effectively.

Use Case:

When you're writing code that interacts with external data sources (e.g., web services or APIs), Copilot can suggest appropriate error handling strategies to ensure that your application runs smoothly in production.

GitHub Copilot Prompt Strategies for Business Central Development

Effective use of GitHub Copilot relies on crafting clear and concise prompts. Here are some strategies for utilizing Copilot effectively in Business Central development:

1. Be Specific with Object Types

When working with tables, pages, reports, or queries, ensure that your prompt specifies the object type you are working on. For instance, when extending a page, indicate whether it's a card page, list page, or factbox.

Example Prompt:

"Generate a page extension for a list page to add a field displaying the customer’s preferred delivery method."

2. Use Comments to Guide Copilot

If you have a specific outcome in mind, start with a comment to guide GitHub Copilot. Comments can help narrow down the AI’s suggestions to meet your requirements.

Example Prompt:

// Generate a function that returns the total sales for a given customer
procedure GetTotalSales(CustomerID: Code[20]): Decimal

3. Iterate with Smaller Prompts

Instead of asking for a large block of code, break your request into smaller, manageable chunks. This will help GitHub Copilot generate more focused suggestions, which you can then assemble into a full solution.

Example Prompt:

  1. First, ask for a function to get the customer data:

procedure GetCustomerData(CustomerID: Code[20])
  1. Then, follow up with a request for error handling:

// Add error handling to the GetCustomerData function

4. Combine Copilot with AL Documentation

GitHub Copilot can help improve your code by suggesting relevant documentation for AL code. When starting a new object or function, prompt Copilot to include documentation for better readability and future reference.

Example Prompt:


// Generate a table extension with fields for the customer’s email and phone number

5. Refactor Code with Copilot Suggestions

If you have existing code that could be optimized or refactored, you can ask GitHub Copilot to help you clean up or improve specific parts of your code. Copilot can suggest improvements based on best practices, improving code efficiency and maintainability.

Example Prompt:

// Refactor the UpdateCustomerPreferences function to improve efficiency

Conclusion

GitHub Copilot offers significant benefits for Business Central developers by reducing development time, enhancing code quality, and supporting learning. With its powerful AI-driven suggestions, Copilot assists developers with everything from writing code and generating functions to adding documentation and improving error handling. By crafting clear, targeted prompts, you can make the most of GitHub Copilot and streamline your Business Central development workflow.

Final Thoughts

To maximize the effectiveness of GitHub Copilot in your Business Central development, continue experimenting with different prompt strategies, refine your understanding of AL programming, and leverage Copilot's suggestions as a valuable tool in your development toolkit. As AI technology continues to evolve, tools like GitHub Copilot will become even more integrated into development processes, making coding faster, easier, and more efficient.



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