# AI as a Development Tool: Enhancing, Not Replacing

# Tools Define Our Trade

Throughout my career, including experience in construction, I've learned that tools are crucial. Yet, developers often have strong, sometimes puzzling preferences. Why do some developers prefer VS Code for PHP development when PHPStorm provides comprehensive, purpose-built functionality? The answer lies not in the tool itself, but in how we leverage it.

# Reducing Development Arrogance

One unexpected benefit of working with AI tools is reducing my own development arrogance. As a contractor, I've encountered numerous approaches to writing code:

• General framework-specific best practices
• Internet-wide accepted standards
• Internal company style guides (often defended with "that's how we've always done it")
• My own preferred methods

Previously, I might have stubbornly advocated my approach. Now, AI objectively helps evaluate these perspectives. This is especially valuable for greenfield projects or MVPs, where I've learned to treat all code as potential technical debt until it reaches production.

# The Power of Rapid Iteration

AI has revolutionized my workflow, enabling rapid scenario testing. With AI, I can:

• Compare various approaches and their trade-offs
• Analyze package documentation against framework requirements
• Evaluate compatibility across components
• Consider multiple implementation strategies simultaneously

Tasks previously taking a week now take hours. This isn't about cutting corners—it's about exploring more possibilities and making better-informed decisions.

# Ownership and Responsibility

Crucially, when using AI to help write code, the responsibility remains yours. Others will review it as if you wrote every line yourself—because ultimately, you did. AI is simply another tool, akin to linters or static analysis tools.

This emphasizes the importance of:

• Comprehensive testing
• Adequate test coverage
• Genuine validation of functionality
• High code-quality standards

# Beyond Copy-Paste Development

Using AI effectively isn't laziness. Developers misusing AI are often the same individuals who previously copied blindly from Stack Overflow without understanding the code. Although the tool changed, the underlying methodology must remain rigorous and thoughtful.

# Learning Through Application

I've learned more in recent months using AI tools than through years of traditional development. Tackling complex projects—such as replicating legacy applications—deepened my understanding not just of how to code, but why certain methods work better.

Rapidly generating test cases, exploring edge conditions, and evaluating alternative implementations has fostered more thorough and thoughtful development. When replicating legacy systems, AI helps identify potential bugs that might be intentional features, allowing me to document and preserve behaviors while building flexibility for future corrections.

# Conclusion

AI in development isn't about replacing human judgment or creativity. It's about amplifying capabilities, reducing cognitive load, and enabling focus on solving problems effectively. Embracing these tools while maintaining professional standards and responsibilities allows us to create better software faster—without sacrificing quality or understanding.