Why, despite the rise of AI, there still is, and will always be, a need for human coders
The ability to understand code is of more value than being able to produce code.
AI tools undoubtedly accelerate code generation, but human oversight remains crucial for several reasons. Developers are needed to craft precise prompts aligned with project requirements, interpret the generated code and ensure its correct implementation. They must also intervene when issues arise, such as debugging inaccuracies or refining flawed logic. Therefore, despite AI’s advancements, a practical coding education and a strong understanding of programming remain essential for securing employment in the field.
The limitations of AI
While AI has the ability to streamline processes and improve efficiency, it falls short when it comes to replicating essential human qualities such as collaboration, adaptability and the ability to navigate workplace dynamics. What may come as a surprise is that these soft skills are often regarded as more valuable than technical coding expertise by many companies looking for developers. Understanding the value that companies place on these skills, online learning platforms like Zaio have deliberately incorporated training on soft skills into their formal curriculum to better prepare individuals for the realities of the workplace. As an added long term bonus, this will also be an essential part of differentiating a developer’s utility from that of AI coding tools.
Beyond interpersonal skills, there are numerous complexities in tech projects that require human judgement and critical thinking to deliver code that can become a holistic solution, rather than just a part of a function . Factors such as budget constraints, project phases and shifting requirements within the context of diverse stakeholders and interconnected expectations and realities, all play a significant role in software development and must be carefully considered when writing and implementing code. Unlike human developers, AI lacks the ability to fully comprehend these nuanced aspects, making it an insufficient substitute for human expertise in the field.
How AI is changing the way we conduct interviews
The latest hiring trends report by OfferZen highlights that a shift towards more human-centered skill assessments is already underway – at the same time that AI-coding is accelerating. Instead of relying on quick, automated online tests to evaluate task-execution, companies are placing greater emphasis on comprehensive evaluations. The report notes that “AI is changing the way developers’ technical skills are assessed” and that “the number of companies using online coding challenges to assess developers has fallen by 21.6% over the past 12 months.”
With generative AI producing code more and more efficiently, online skills-evaluations are simply no longer a feasible method for assessing potential employees. Employers find it increasingly difficult to identify whether candidates actually understand the work they deliver or whether they simply copied it over from an AI tool. Because of this, many companies now prefer to assess problem-solving skills and evaluation techniques through face-to-face technical interviews instead of online assessments. AI-coding has rapidly evolved, but so has the recruitment of human-coders, all while hiring hasn’t stopped.
Practical, yet theory-backed skills
It’s long been the case that traditional Computer Science graduates tend to face a lot of challenges when entering the tech industry, particularly in startup environments where employees are expected to hit the ground running. This is because typical university graduates often struggle to apply their vast theoretical knowledge in a setting where practical execution generally takes priority. This is why alternative ways of learning, such as through accredited online bootcamps and practical courses can be a lot more effective in preparing prospective coders for the tech job market, and still lay a strong theoretical foundation for understanding that AI can’t get a competitive edge over.
One online learning platform that has particularly excelled in bridging the gap between theoretical knowledge and practical application, is Zaio. Just looking at data from this last month alone, the company has managed to successfully place close to 100 graduates from their programme into paid tech roles, despite them not having had any prior technical experience.
The demand for human coders remains strong and aspiring developers should not be discouraged by the rise of AI. Instead, they should embrace it as a tool to enhance efficiency and accelerate their growth. However, as the industry evolves, the ability to apply coding knowledge to dynamic real-world projects will be more crucial than ever. To stay competitive, developers must prioritise gaining hands-on experience alongside their theoretical education for a deep understanding of how software solutions have to address human needs.