Junior devs and AI: Friends or foes?

In recent years, AI-driven coding assistance tools have been getting increasingly popular. GitHub Copilot, powered by machine learning algorithms and an extensive code repository, offers real-time suggestions and automatic code completion and even generates entire code snippets. This technological advancement is both a blessing and a potential pitfall for junior developers.

At Infobip, we were granted access to the GitHub Copilot AI tool as a way to help boost our productivity. Immediately, I decided to take it for a spin and see how it could assist me in my coding tasks. 

In the beginning, I was genuinely surprised by the sheer power of this tool. It felt as if it could effortlessly complete my code with just a prompt from me – whether it was a simple comment or the start of a function name, Copilot magically finished it.

This was a game-changer, not only for me but for many developers. I was having an incredibly fun time playing around with Copilot, writing code in seconds without even thinking about my implementation. However, as I continued using Copilot, I noticed some limitations affecting my learning and coding skills. 

Although Copilot was undeniably effective in offering solutions, I realized that I wasn’t gaining a complete understanding of how these solutions work. This posed a challenge because a deep understanding of coding principles is essential for any developer’s growth. Furthermore, I realized I wasn’t actively learning from Copilot because I skipped the crucial step of understanding the code.

There are indeed benefits to using AI assistant tools as a Junior Dev:

Productivity Boost: AI assistants automate repetitive coding tasks, allowing young developers to focus on more creative and complex aspects of development, thereby increasing their productivity.

Access to Best Practices: AI assistants often incorporate industry best practices, helping young developers adopt coding standards and conventions early in their careers, which can benefit their professional growth.

Increased Confidence: With AI assistance, new developers can tackle more challenging coding tasks with greater confidence, as they have a reliable resource to guide them.

However, there are concerns regarding the potential drawbacks:
Over-Reliance: An observable risk is the over-dependence on AI tools. Some junior developers may rely on Copilot’s “Tab” key without fully comprehending the code it generates.

Creativity Constraint: Relying too much on AI tools might accidentally stop creativity and fresh ideas in coding. Trying new and special ways to solve problems may not happen as often.

Junior developers need to strike a balance to get the best out of AI tools and keep growing in coding. They should keep practicing and improving their basic coding skills while using AI tools. 

Instead of depending too much on these tools, they should think of them as helpers that make them even better coders – and work on building and maintaining their independent coding skills.