The rise of intelligence in the technology sector has sparked considerable discussion, particularly among software developers. A contentious issue revolves around whether aspiring programmers should use AI tools for coding. The resounding answer is yes.

There is a vital caveat: AI should serve as a learning aid rather than a crutch.

AI driven coding aids such as GitHub Copilot, ChatGPT, and similar platforms provide a shortcut for writing code. These tools can assist in generating code snippets, proposing optimizations, and even furnishing complete blocks of functionality. Understandably, novice programmers may be tempted to rely on these AI resources. Who wouldn't want to expedite their learning process, particularly when confronted with the complexities of programming? Nonetheless, it's crucial to differentiate between utilizing AI for code creation and using it to enhance skills.

For beginners, the primary objective should be laying the groundwork for programming principles and problem-solving abilities. Overreliance on AI for code generation can bypass this learning phase. When new developers utilize AI without grasping the logic or framework of the generated code, they miss out on valuable educational opportunities.

Using AI in education is akin to relying on a calculator for math before mastering addition and subtraction. You may arrive at solutions without understanding the underlying process.

When harnessed effectively, AI can serve as an educational aid. Here's how budding developers can utilize AI to enrich their learning experience;

1. Grasping Code Suggestions:
   Instead of blindly adopting AI generated code, novice developers should delve into the rationale behind these suggestions. Breaking down the code, examining its components, and comprehending how each element contributes to the functionality not only solidifies learning but also aids in identifying potential errors or enhancements.

2. Learning Best Practices:
   AI tools draw from datasets that offer insights into industry best practices. By studying these recommendations, aspiring developers can glean lessons on problem-solving approaches, code structuring techniques, and efficient solution implementation from seasoned professionals' examples. Exposure to top-tier code can significantly expedite the learning curve.

3. Debugging and Optimization:
   AI empowers new developers to troubleshoot and optimize their code effectively. By seeking explanations for errors or optimization suggestions, AI systems, developers can enhance their understanding of improving the performance and reliability of their code. The process of writing, testing and refining code in a manner plays a vital role in acquiring effective programming skills.

4. Experimentation:
   AI also encourages novice developers to explore coding methods. By presenting solutions to a single problem, AI demonstrates that there are often multiple ways to tackle a coding challenge. This adaptability helps deepen comprehension of programming principles and promotes problem solving approaches.

AI should not supplant the learning required by new developers but rather complement it. By utilizing AI as an aid, new developers can enhance their learning curve, grasp best practices, and boost their confidence in coding. The key lies in leveraging AI not as a shortcut to avoid learning but as a valuable companion on the path to becoming proficient and versatile developers.