Within the software engineering community, the rise of AI-generated code has ignited a dynamic conversation among professionals of all ranks. From eager junior developers to highly experienced senior software engineers, the integration of tools like GitHub’s Copilot and chat GPT has prompted a range of reactions, encompassing both optimism and doubt. To deepen our understanding of this complex issue, we asked for our colleague’s opinions, based on their experience in using generated code.
This article aims to offer you insights into the advantages and drawbacks of AI-generated code and examining its influence on developers at different points in their career journey.
The Promise of AI: Efficiency and Accessibility
At first glance, the utility of AI-generated code is undeniable. For junior developers, particularly, the ability to generate boilerplate code swiftly can seem like a godsend. It promises a reduction in mundane tasks, faster project initiation and an efficient way to tackle complex coding challenges. Mid-level developers might see it as a valuable tool for accelerating development cycles, potentially freeing up time to focus on more strategic, high-value aspects of their projects.
Quality Concerns and Conceptual Gaps
An article on GitClear highlights a concerning trend: AI’s tendency to exert a “downward pressure on code quality“. This resonates with experiences shared by developers, who recount tales of AI-generated code leading to confusion and, in some cases, outright failure during the implementation phase.
Paul, Senior Developer: “Generating boilerplate code with AI seems useful, but it can lead to confusion, especially when developers over-rely on tools like chat GPT. For example, I know a case when a project failed because the team trusted chat GPT too much, mixing incompatible library features. This issue isn’t new; blindly copying code from any source without understanding it can be problematic. It often affects juniors more, but not exclusively, creating a false sense of productivity. Spending time to understand the documentation or explore GitHub is more valuable in the long run than a quick fix with AI. While tools like Stack Overflow or AI can temporarily boost productivity, they can also hide essential basics. Ultimately, knowing the deeper concepts behind code, frameworks, or libraries becomes necessary.”
A perspective by seniority levels
Junior Developers: A double-edged sword
For junior developers, AI-generated code can be very useful, providing a quick way to get past the early learning stages. However, this easy route has its drawbacks. Depending too much on AI can hide the essential basics of coding, resulting in a shallow knowledge of programming languages and frameworks. If AI-generated suggestions are wrong, junior developers may struggle, missing the in-depth understanding needed to fix or improve code efficiently.
Mid-Level Developers: The quest for balance
Mid-level developers stand at the crossroads, equipped with enough experience to recognize the pitfalls of AI-generated code, yet still enticed by its potential for boosting productivity. Their challenge lies in balancing the use of AI tools with a commitment to maintaining code quality and deepening their technical expertise. The risk for them is becoming complacent, allowing AI to make decisions that they should be making based on their growing expertise.
Senior Developers: A tool among many
Senior developers, with their wealth of experience and deep understanding of software engineering principles, are likely to view AI-generated code with a critical eye. They appreciate the technology’s potential for handling repetitive tasks or serving as a brainstorming partner but remain acutely aware of its limitations. The emphasis for seniors is on leveraging AI as one tool in a vast arsenal, always prioritizing a solid architectural foundation and clean, maintainable code over the allure of quick fixes.
“If a strong background is missing, it can lead to problematic results or even worse. It’s not just AI code generators that pose a challenge; they just amplify the issue. Remember how many developers used to copy-paste from StackOverflow without trying to understand the underlying logic, resulting in similar issues but on a smaller scale.
As a best practice, it’s recommended to thoroughly examine the output, try to understand what’s happening and why that particular output was generated. Be curious, seek out other solutions or implementations, or ask around!” – Marian, Senior Developer.
Conclusion
AI-generated code represents both a remarkable opportunity and a significant responsibility. By embracing it with a mindful approach that respects the nuances of professional development, engineers at all levels can navigate its challenges and reap its benefits, ensuring that the software they build stands the test of time.
As we wrap up our journey, we’re left with two insights applicable to every developer, regardless of seniority.
1.Stay curious, ask for help and always seek to understand first!
2. Knowing is better than quick fixes from AI!
Let these ideas guide you to a more creative and better coding.
