AI-Assisted Software Development

3 days

Welcome to “AI-Assisted Software Development”! This comprehensive course is designed to equip developers with the knowledge and skills needed to effectively leverage AI tools in their software development workflow.

AI coding assistants have revolutionized the way we write, debug, and maintain code. By providing intelligent suggestions, automating routine tasks, and helping with code understanding, these tools can significantly enhance developer productivity. Whether you’re looking to streamline your coding process, improve code quality, or stay ahead in the rapidly evolving field of AI-assisted development, this course will provide you with the practical skills and understanding needed to make the most of these powerful tools.

Throughout this course, you’ll learn everything from fundamental concepts of AI coding assistants to advanced usage patterns and best practices. We’ll cover multiple popular tools, their specific strengths, and how to effectively integrate them into your development workflow while maintaining code quality and security.

By the end of this course, you’ll be able to confidently use various AI coding assistants, understand their capabilities and limitations, and know how to apply them effectively in different development scenarios. You’ll also gain practical experience in using these tools for various tasks while maintaining code quality and security.

Learning Outcomes

Upon completion of this course, participants will be able to:

Understand the fundamentals of AI-assisted software development
Use various AI coding assistants effectively in their development workflow
Write better prompts to get more accurate and useful responses
Implement best practices for AI-assisted development
Maintain code quality and security when using AI tools
Choose the right AI assistant for specific development tasks
Integrate AI tools into existing development processes
Troubleshoot common issues with AI coding assistants

Course Outline

Module 1: Introduction to AI-Assisted Development

Understanding AI coding assistants and their capabilities
Evolution of AI in software development
Types of AI coding assistants
Benefits and potential limitations
Current state of the technology and future trends

Module 2: Understanding Language Models for Coding

How code assistants work with LLMs
Context windows and their importance
Cut-off dates and their impact
Common pitfalls and limitations
Strategies for avoiding hallucinations
Evaluating and choosing models
Practical usage in development

Module 3: Getting Started with AI Coding Tools

Overview of popular AI coding assistants
Setting up your development environment
Basic usage patterns and workflows
Understanding context and prompts
Tool-specific configurations and settings

Module 4: Working with Cursor

Cursor’s unique features and capabilities
Chat and codebase interaction
Code generation and editing
Multi-line editing and smart rewrites
Using images and documentation
Advanced features and shortcuts

Module 5: Writing Effective Prompts

Understanding prompt engineering
Crafting clear and specific requests
Providing proper context
Handling complex requirements
Troubleshooting unclear responses
Best practices for different tools

Module 6: Mastering GitHub Copilot

Understanding Copilot’s capabilities
Setting up and configuring Copilot
Writing effective prompts
Code completion and suggestion features
Handling multiple suggestions
Best practices and common pitfalls

Module 7: Advanced Development with aider

Understanding aider’s architecture
Setting up and configuring aider
Working with multiple files
Git integration and version control
Advanced features and commands
Architect mode and dual models

Module 8: UI Development with v0

Introduction to v0 capabilities
Component generation and modification
Working with different frameworks
Responsive design patterns
Integration with existing projects
Best practices for UI development

Module 9: Navigating the Windsurf IDE

Core design philosophies
Context awareness features
Autocomplete and supercomplete
Integrated chat capabilities
Command palette usage
Codeium flows and cascade
Best practices for Windsurf

Module 10: Code Quality and Security

Maintaining code quality with AI assistance
Security considerations and best practices
Code review strategies
Testing AI-generated code
Handling sensitive information
Compliance and licensing considerations

Module 11: Capstone Project

Design and implement a feature using AI assistance
Apply best practices and security considerations
Utilize multiple AI tools effectively
Document the development process
Present and defend your implementation strategy

Conclusion and Future Directions

Recap of key concepts and best practices
Emerging trends in AI-assisted development
Continuing education and resources
Building an AI-assisted development strategy
Future of AI in software development