Hello ChatGPT, RIP software developer?

George Lynch, Head of Technology Advisory at NashTech shares his thoughts on what generative AI mean for software developers. This article first appeared on ComputerWeekly.com. This year has seen a remarkable explosion of interest in Generative AI. Go back just six months, and most people had never heard of it. Now, it seems as though everyone – from tech professionals to students – is using it and experimenting, in particular, with the ‘poster child’ ChatGPT. This has also generated increasing discussion of whether AI and Gen AI spell the end for human roles, including in software development. Does ChatGPT and its Gen AI cousins (such as Bard, Copilot and Bing Chat) mean the demise of the software developer – given that Gen AI can already generate code snippets? It occurred to me that a good first step in considering this question was… to ask ChatGPT. As always, it gave an instant, eloquent answer, and the thrust of its response was ‘no’. ChatGPT and similar language models, it wrote, “are unlikely to replace software engineers entirely”. This is because software engineering “involves much more than just natural language processing” and requires a range of skills such as problem-solving and collaboration that are “beyond the scope” of Gen AI. However, it did also say that Gen AI “can automate certain aspects of software development” and “augment the capabilities of software engineers.” Clearly, then, it’s not a case of ‘RIP software developer’ – or at least, not yet. But at the same time, there is no doubt that the advent of Gen AI will bring about significant changes and disruptions. Field of opportunities It’s helpful to divide the impacts into opportunities and risks. So, I’ll start firstly with the many positives. Gen AI will significantly speed up certain aspects of the software development process. It can already manage some of the lower-level tasks, such as entry-level code writing, code snippets, testing and documentation. It can also write excellent comments in code – something software developers tend to be less enthusiastic about doing. And that’s just as at today. These capabilities could (almost certainly, will) rapidly improve and increase going forward. What catapulted ChatGPT into the mainstream was its ability to leverage modern advances in computing power that allow Large Language Models (that underpin ChatGPT) to be trained in a relatively short period of time. The potential for Gen AI to leverage advances in quantum computing could open up even more opportunities for developers. Who knows what agile will look like when Gen AI really develops? Imagine sprint cycles of not two weeks but two days or even two hours! The speed and productivity could be beyond our wildest dreams. The challenge will be handling all the code generated, curating it and managing it. In short, there is massive potential to do things faster, potentially more cheaply, and to spend more of the human time involved on the higher-end, value-adding aspects. These could all be huge positives in terms of productivity and client delivery. I don’t think there’s any question that senior developers and engineers will always be needed – they are where art meets science, they have the experience and the know-how and the creativity/problem-solving ability to bring it all together. The role of the programmer and indeed business analyst will still be to elicit requirements from clients that can then be converted into prompts for GenAI to generate, test and document code snippets. These will still need to be woven into the fabric of the overall solution. It’s also worth remembering that to get the most from Gen AI, you need well-constructed prompts. In a way prompting Gen AI is a protocol all of its own, akin to pseudo-code. Gen AI at the moment does not remove the need for thinking about how a software solution needs to be structured, which for the most part is the biggest value a software developer brings. A range of risks We must be honest and say that Gen AI does represent a threat to junior roles and entry level tasks. However, in a way this is no different to the new frameworks and automation tools that keep appearing in the market. It’s a factor the IT industry is already used to living with. It may be more pronounced with Gen AI, however, as clients may expect software firms and consultants to reduce the size of their (human) teams due to the fact that they can use Gen AI – either that or get jobs done faster (or both).An inflection point may therefore be coming. But tech has always been resilient and adaptable. It always reinvents itself. I have no doubt that new jobs and roles will be needed to support Gen AI (prompt engineers for example) that many junior team members can fill. Gen AI will be a disruptor, but I am confident that the industry will embrace Gen AI as it has other advances in computing science. Whilst the industry will not only survive but thrive, the level of disruption Gen AI has caused and will continue to