Will AI Like ChatGPT Ever Replace Developers? From a Developer's Perspective

It does not truly grasp the nuances of a problem the way a developer does. This leads to a situation where you are stuck revising code, often without making real progress. I have tested this myself, at times, I have spent more time working with AI to debug and refactor code than if I had just written it myself. It is frustrating and time consuming, and often, you end up running in circles. AI may suggest changes, but sometimes those changes create new issues or skip over things that were working fine.

Real World Example:

If I am building a complex feature for an ecommerce store, let us say a custom checkout process with various conditional discounts, AI might generate the initial function. But it will often miss edge cases, such as handling failed payments or generating correct discount calculations across multiple products. That is where a developer's expertise comes in. We consider the full picture, the various edge cases, and the potential for bugs down the line.

2. The Importance of Test Driven Development (TDD) and Behaviour Driven Development (BDD)

What many people do not realise is that coding best practices like TDD and BDD are essential for writing quality, maintainable code. These practices are not something that AI can just "figure out" and apply perfectly, at least, not yet.

• TDD requires you to write tests before you write the code, pushing you to think deeply about the requirements of a feature and what could go wrong.
• BDD helps ensure that the code is understandable by non developers and aligns with business goals. The benefit of these practices is clarity and robustness. By writing tests first, you are forced to think about what might fail and how the code will perform under various conditions. This results in code that is thoroughly tested, reliable, and easy to maintain.

Can ChatGPT help with this?

Absolutely. I often use ChatGPT for inspiration when I am stuck on writing a test or struggling with test coverage ideas. But at the end of the day, it is still me who must write the test and consider the full scope of the feature. The AI cannot think critically about the business logic or test scenarios in the same way a human can. Writing the test forces me to consider things like error handling, edge cases, and performance, something AI is still far from being able to do effectively on its own.

3. The Need for Deep Understanding of Code

AI tools like ChatGPT can certainly help with snippets of code, or even debugging small issues, but to understand large codebases and integrate new features, you need deep familiarity with syntax, architecture, and design patterns. ChatGPT cannot replace the need for developers to critically engage with the code and understand what every line is doing. If you do not have a clear understanding of how things work, using AI for coding assistance can lead to incorrect assumptions or unfinished solutions. AI might output some code that looks right on the surface, but without the deeper understanding of what is happening, it can be hard to pinpoint why it does not work in the context of the rest of your project.

Real World Example:

When adding a new feature to a web app, say a payment gateway integration, you need to understand how your application will interact with the gateway, the data flow, and the security implications. While AI can generate code for you, it will not provide the same level of contextual awareness or security foresight that a developer can.

4. ChatGPT as an Assistant, Not a Replacement

That being said, ChatGPT is an amazing assistant for developers. There are plenty of situations where ChatGPT is extremely helpful, such as:

• Generating repetitive code (e.g., seeding databases, or writing boilerplate code).
• Suggesting syntax or library alternatives.
• Offering ideas for solving common coding problems.
• Helping with documentation and comments. It speeds up coding, especially in areas where you may not be familiar with a certain syntax or library. For instance, when you need to implement a complex sorting algorithm or want advice on the best approach to build a feature in a framework you do not use every day, ChatGPT can get you 80 percent of the way there. It is like having a junior developer or mentor to assist with ideas and approaches.

Real World Example:

When writing seed files for your database (e.g., generating fake data for testing), ChatGPT can write these quickly without you having to manually type out data for each user or product. This is a repetitive task, and AI excels here.

Limitations of ChatGPT: Handling Large Code and Limited Context

One of the biggest limitations I have found with ChatGPT is that it often does not handle large code snippets well. When you input long blocks of code, it gets cut off or does not process them correctly. This becomes problematic when trying to work on larger tasks or debugging complex code. Additionally, without knowing what the code is actually doing line by line, you might encounter problems where the code outputs seem "correct" at first glance, but deeper investigation shows hidden bugs or issues with performance. This is where understanding the code deeply comes into play.

5. Conclusion: ChatGPT as a Helpful Developer Assistant

AI, like ChatGPT, is a fantastic tool for speeding up coding, offering solutions to common problems, and helping you learn new techniques. However, it cannot replace the need for a developer who has an in depth understanding of code, problem solving skills, and the ability to consider edge cases, performance, and security. In my experience, ChatGPT is an assistant, not a replacement. It can make repetitive tasks faster, and it can serve as a sounding board when you get stuck, but at the end of the day, coding is an art, and it requires critical thinking, strategic planning, and an understanding of how code integrates into the larger system. Until AI can think critically, reason through problems, and truly understand complex tasks in the same way a human does, developers will remain essential. I still prefer to write complex code myself, as I know my thought process and understand why each part works. ChatGPT may assist, but the real work is done by developers who bring the experience, knowledge, and creativity to the table.