What is Agentic Coding?

Overview

Agentic coding is a development approach where you work collaboratively with AI-powered assistants (agents) that can understand context, generate code, provide suggestions, and help maintain your codebase. Unlike simple code completion tools, these agents can:

• Understand natural language instructions
• Analyze existing code and context
• Generate complete implementations
• Refactor and improve code
• Explain complex code segments
• Assist with debugging and problem-solving

How It Works

AI coding assistants work by:

1. Understanding Context: The agent analyzes your workspace, open files, and the surrounding code to understand what you’re working on
2. Processing Instructions: You provide instructions in natural language (or through inline comments)
3. Generating Solutions: The agent creates code, documentation, or suggestions based on your needs
4. Iterative Refinement: You review, provide feedback, and the agent adjusts the output

Key Capabilities for AL Development

Code Generation

Generate AL code from natural language descriptions:

• Complete procedures and functions
• Table extensions and page extensions
• API pages and queries
• Event subscribers
• Test code

Code Understanding

Get help understanding existing code:

• Explanations of complex logic
• Documentation of dependencies
• Impact analysis of changes

Code Improvement

Enhance existing code:

• Refactoring for better performance
• Applying AL best practices
• Modernizing legacy code
• Adding error handling

Documentation

Automatically create and maintain:

• XML documentation comments
• README files
• API documentation
• Code comments

Benefits for AL Developers

Faster Development

• Quickly scaffold new objects and extensions
• Implement common patterns without repetitive typing
• Generate boilerplate code instantly

Higher Quality

• Consistent application of best practices
• Fewer common mistakes
• Better code organization

Learning Accelerator

• Learn AL patterns through examples
• Understand Business Central APIs
• Discover best practices in context

Reduced Cognitive Load

• Focus on business logic, not syntax
• Less context switching for documentation lookups
• Automated handling of repetitive tasks

The Human-AI Partnership

It’s important to understand that agentic coding is a collaborative approach:

You Bring:

• Domain Knowledge: Understanding of business requirements and Business Central functionality
• Decision Making: Architectural choices and business logic decisions
• Quality Control: Review and validation of generated code
• Context: Specific requirements, constraints, and organizational standards

The AI Brings:

• Speed: Rapid code generation and transformation
• Consistency: Adherence to patterns and best practices
• Breadth: Knowledge of many AL patterns and APIs
• Assistance: Help with routine tasks and documentation

Common Use Cases

Daily Development

• Creating new tables, pages, and codeunits
• Implementing event subscribers
• Writing test code
• Adding XML documentation

Code Maintenance

• Refactoring existing code
• Adding telemetry to extensions
• Improving error handling
• Updating deprecated APIs

Code Review

• Identifying potential issues
• Suggesting improvements
• Checking adherence to standards
• Finding security concerns

Documentation

• Generating README files
• Creating API documentation
• Writing user guides
• Documenting complex algorithms

Next Steps

Now that you understand what agentic coding is, learn how to:

• Set up your environment for AI assistance
• Write effective prompts to get better results
• Follow best practices for AI-assisted development