Written by Michelle Visagie, with AI assistance
There is a noticeable shift happening in software development, and it is happening faster than many businesses may realise. Artificial Intelligence can now generate code, create applications, troubleshoot problems and assist with many of the tasks that have traditionally required significant developer time. For someone looking to turn an idea into an application, the barrier to entry has never been lower.
That is exciting. It also raises some interesting questions about where software development is heading.
We are already seeing people use AI to build applications for their businesses without necessarily having a background in software development. In some cases, the results are surprisingly good. An idea can be turned into a working prototype in a fraction of the time it might previously have taken, and AI can make software development accessible to people who would never have considered building an application themselves.
However, there is an important difference between creating something that works and creating something that is properly engineered.
An application may function exactly as expected when it is first launched, but that does not necessarily tell us anything about the quality of the underlying architecture. How is the data being handled? Are appropriate security measures in place? What happens when the application has ten users instead of one hundred, or ten thousand? Are the dependencies being managed correctly? Can another developer understand and maintain the code six months from now? What happens when something fails?
These are the kinds of considerations that can be easy to overlook when the focus is simply on getting an application built quickly.
This does not mean that AI is producing poor software, nor does it diminish what AI can achieve. In fact, our own developers are already using AI as part of their development process. The difference is that they bring years of experience and technical understanding to the output. AI can help generate code, suggest solutions and accelerate repetitive tasks, but the developer still needs to assess whether what has been produced is appropriate for the particular environment, secure, scalable, maintainable and accurate.
That human involvement is unlikely to disappear. If anything, it may become more important as AI becomes more capable.
Developers are now competing with AI, and using it to compete
There is an interesting tension emerging for developers. AI can produce code considerably faster than a human can write it manually, which means developers need to find new ways of working if they are going to remain competitive on speed and productivity.
The answer is not to try to type code faster than AI. It is to use AI to remove some of the more repetitive and time-consuming aspects of development, while allowing developers to spend more of their time on the areas where their experience has the greatest value.
AI can generate a starting point. It can help write repetitive functions, explain unfamiliar code, suggest approaches to a problem, assist with testing and identify potential issues. A developer can then review that output, adapt it to the application, test it against real-world requirements and make the architectural and security decisions that AI cannot necessarily make in isolation.
The developer's role therefore starts to move from being primarily about writing every line of code to being much more about directing, evaluating and engineering the solution as a whole.
That shift is significant.
The importance of architecture and experience
As AI makes it easier to produce software, understanding how that software fits together becomes increasingly valuable.
A developer needs to consider far more than whether a particular piece of code works. They need to understand how different components interact, where information should be stored, how users should be authenticated, what permissions are required, how the system will scale and what happens when something goes wrong.
They also need to think beyond the initial launch. Software is rarely a finished product. It needs to be maintained, updated, secured and adapted as the business changes. A solution that works beautifully today but becomes difficult or expensive to maintain later may not have been a successful solution at all.
This is where experience matters.
AI can give you an enormous amount of output very quickly, but someone still needs to know what questions to ask of that output.
So, what happens next?
It is tempting to frame this as a choice between developers and AI, but that is probably not where we are heading. The more likely future is one where developers who know how to work effectively with AI will have a significant advantage over those who do not.
The same amount of development work may be completed in considerably less time, allowing businesses to explore ideas more quickly and developers to concentrate on more complex problems. That is a positive development, provided speed does not become the only measure of success.
For businesses, this also means becoming more discerning about how software is built. The fact that an AI tool can produce an application does not necessarily mean that the application is ready to become part of your business infrastructure.
There is still a need for people who understand the business problem, can translate it into an appropriate technical solution, understand the risks involved and take responsibility for what is ultimately delivered.
AI is changing how software is developed, and there is no reason to resist that change. Developers should absolutely be using these tools to become faster and more productive. At the same time, we should recognise that software engineering has never been solely about writing code.
It is about understanding problems, designing solutions, making informed technical decisions and creating systems that can continue to work long after the initial build.
AI can accelerate the process considerably.
But the experience, judgement and human oversight behind the solution still matter.
