AI has completely revolutionised coding. Interestingly, the ability to generate software code was an unexpected “side-effect” of developing large language models (LLMs). Like any other AI application, errors still occur at this stage, so it’s essential for software developers to have a solid understanding of programming languages and coding techniques in order to fix, adapt, and test the code generated by AI. Nevertheless, the productivity boost AI provides is undeniable.
If you’re new to a programming language, unfamiliar with a specific library, or simply trying to write a piece of code without reinventing the wheel, you would traditionally turn to online forums and code-sharing platforms. This process typically involves sifting through multiple websites, entering search criteria, reading various results, downloading and testing code snippets. Often, you’d need to adapt the code to your needs, and even then, it might not fully solve your problem. Asking for help in forums could result in delayed responses, or worse, no reply at all.
That’s where AI chatbots come into play. With AI, you can specify your tech stack, programming language, and even the operating system you’re working on. In return, the AI chatbot quickly generates fully written, ready-to-use code in just seconds. What’s more, it often provides an explanation of the different sections of the code without you even asking. Not only do you get the code, but you also learn how it works. If you need to adapt or modify something, simply ask again, and within seconds, a new version of the code is generated. You can even request multiple variations if you’re looking for a more elegant or efficient solution.
A task that once took several hours or spanned over days can now be completed in an hour. It’s like having an expert colleague who specialises in the language or technology you’re working with – one who is endlessly patient and available. It’s game-changing.
However, it’s not without its flaws. Like other generative AI applications, errors can creep in. The generated code might contain bugs or miss certain functionalities you requested. In a way, this makes the AI experience feel more “human” – your AI expert might occasionally make mistakes or overlook something. Fortunately, it’s not a big issue. Thanks to the chat format, previous interactions are remembered, and you never need to start from scratch. You can even revisit conversations from days before or run multiple parallel chats for different tasks or projects.
The Future of Software Development with AI:
How will this impact the future of software development? There are concerns, especially regarding new languages and technologies. AI LLMs are trained on massive datasets that include decades’ worth of online content: textbooks, code samples, code libraries, online forums, open-source repositories, and more. But what happens if people stop sharing knowledge? After all, developers share their expertise to help fellow programmers. Will they continue to do so, knowing that chatbots might outnumber human readers? Additionally, how will AI’s knowledge be updated as new technologies emerge? Could there be a future where code is AI-generated, but no human fully understands how it works?
There are also important questions around best practices. Will AI-generated software follow the principles of data integrity, code reusability, and security?
Even with these potential challenges and uncertainties, there’s no doubt that AI has become an indispensable tool for boosting productivity in software development.
