Artificial intelligence has reshaped how we design, build, and improve software. AI-powered tools like GitHub Copilot, ChatGPT, and CodeWhisperer assist developers in generating code, debugging, and even suggesting optimizations. These advancements have significantly reduced development time, lowered the barrier for beginners, and improved productivity across teams.

However, the rise of AI-driven coding tools has also led to a concerning shift in judgment among developers. Many now assume these tools can fully replace human effort, handling all tasks without the need to write a single line of code. While AI promises to enhance creativity by allowing developers to focus on problem-solving rather than repetitive tasks, it has also become an indispensable part of daily work. So much so that not using AI feels more unusual than relying on it.

In this short article, I argue that some of AI’s greatest strengths might also be its Achilles’ heel. As software development continues to evolve, developers must go beyond just writing code - they must maintain a deep understanding of the systems they build and think critically about AI-generated solutions. Those who do are using AI as an assistant, not a replacement.

Impact on Future Development and Code Quality

AI’s integration into the development cycle was driven by a clear goal: to accelerate development and deliver more features with the same level of effort. In fact, some believe AI will improve efficiency so drastically that a single developer could accomplish the work of two engineers.

I believe this assumption oversimplifies a developer’s role. If a developer approaches their role as just writing code, they may find themselves struggling to grow in their career. The reason is simple: coding without understanding the product, its priorities, or its strategic goals is ineffective. Developers must assess which features align with business objectives, communicate with stakeholders, and prioritize tasks accordingly. Writing code is merely the final step in a much larger equation.

So far, AI enhancements have been remarkable. They bridged the gap between technical and non-technical stakeholders and have enabled more inclusive software development. Aspiring developers can learn faster with AI-assisted coding, making programming more accessible to a wider audience. For seasoned developers, AI models can help by suggesting best practices, detect vulnerabilities, and ensure consistency in coding standards, leading to more secure and maintainable software.

While AI advancements have been impressive, they also raise concerns. AI has reached its current level of sophistication by learning from human innovation. Whenever developers discover better ways to solve problems, those improvements gradually spread and become widely adopted. However, if AI-generated code replaces human-driven innovation entirely, the focus shifts from writing better code to simply writing code faster. Without continuous human contributions to push for best practices, we risk stagnating AI’s ability to improve software development as a whole.

And here is where I believe we must draw a line. While AI can help us write code faster, we should never lose sight of the critical thinking that coding requires. This isn’t to say we shouldn’t use AI. If it allows us to meet deadlines without overworking ourselves, then it has undoubtedly brought a positive change: better work-life balance. It’s just that overuse could end up having the opposite effect.

My biggest concern lies in the unsupervised use of AI and where it could lead us in the future. After all, AI is not infallible. It can make mistakes. If we blindly accept the output without questioning its quality, we risk introducing more errors and, ultimately, degrade the very system AI learns from. Without careful oversight, we may end up not improving software development but inadvertently making everything worse.

Not everything is bad…

I realize my last section focused more on the negative aspects of AI. However, like most things, AI isn’t inherently bad—it’s all about how we use it. Rather than avoiding it altogether, we should be mindful of overreliance and strive for a balanced approach.

The best aspect I see with AI is how easily we can get answers. Since the model was trained on such a vast set of data, it can answer almost any question you throw at it (at least for Computer Science). My preferred way of using ChatGPT is to ask for examples of concepts I don’t immediately understand.

For instance, when I’ve struggled with complex topics in programming, AI has helped by breaking them down into simple terms and providing real-world examples. Whether it’s understanding functional programming principles, type variance, or concurrency models, seeing the ideas applied in context has made learning much easier.

Another great example is using AI to prepare for or test your knowledge on a specific topic. It’s like having a study partner who never gets tired of quizzing you. Gone are the days of writing questions on flashcards and hoping someone will quiz you - now, AI can generate, ask, and even explain the answers in real time.

These experiences have shaped my perspective on AI. While I once believed it might replace us in the future - and in many ways, it still could - I now see it as a powerful tool for personal and professional growth. AI shouldn’t be used merely to offload daily tasks, but rather to accelerate learning and deepen our understanding of complex topics. Instead of fearing its potential, we should leverage AI to enhance our skills and stay ahead in an ever-evolving field.

Like any skeptic, I believe we must be cautious. However, that doesn’t mean we should ignore the benefits AI has brought or the potential it unlocks. I have no intention of using it to replace my daily tasks. I enjoy what I do and still have plenty of mental space to learn and grow. But if AI can help me understand complex concepts by putting information at my fingertips, then I welcome this new way of learning.

Concluding Thoughts.

All in all, I believe AI must be used with caution. I still don’t trust it to make unsupervised changes without verifying every line it generates. After all, I can’t exactly blame AI if it takes down production (which is rather unfortunate).

That said, I must also acknowledge that AI has fundamentally changed how I work and approach problem-solving. Where I once spent considerable time searching for answers, I now use tools like ChatGPT Search to quickly surface relevant sources. This offloads the complexity of searching, allowing me to focus on understanding the information. Additionally, I’ve found AI particularly useful for generating examples that clarify concepts I don’t immediately grasp, helping me learn faster.

While AI is far from perfect, we are approaching a level of reasoning where its capabilities demand serious discussion - both in terms of safety and its broader impact. Anyone can open a ChatGPT window and ask it anything, but blindly trusting its output is where the real risk lies. Still, I believe that if we remain thoughtful in how we use AI, we can use its power to improve software development and push the industry forward.

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