The Changing Face of Software Development

For many years, the core of becoming a skilled software developer was rooted in deep knowledge of mathematics, algorithms, and logical thinking. These foundational elements weren’t just supplementary—they were the essence of problem-solving in programming. The ability to understand complex equations, work through algorithms, and apply theoretical knowledge to practical challenges was what separated the good from the great in the tech world.

However, the landscape shifted dramatically with the rise of the IT boom. Technology became not only a booming industry but also a cultural phenomenon. It was no longer just for the mathematically inclined or the naturally logical thinkers; it was now a career path that anyone could pursue, especially with the promise of lucrative salaries and fast career growth. This shift gave birth to the mantra, “You don’t need mathematics nor deep fundamental knowledge to become an IT professional.” And for many, this was liberating—offering a fast track to success without the heavy mental load of traditional computer science education.

As companies raced to meet the overwhelming demand for software developers, the focus moved from foundational theory to practical, hands-on skills. More developers entered the workforce, but many did so without the deep foundational grounding that had once been a hallmark of the profession. Instead, they learned languages, frameworks, and tools—skills that allowed them to build software, but often without a clear understanding of the inner workings beneath the surface.

Fast forward to today, and we’re witnessing the rise of AI as a tool that’s reshaping the way software is built. Increasing number of new developers— with little to no experience in actual software development—are turning to AI to do much of the heavy lifting. In fact, when asked about their process, many of these newcomers proudly say, "I develop software with AI." This statement often comes from individuals who have little more than a basic understanding of tech languages, or even none at all. They’ve been introduced to the world of programming, but instead of learning the depth, they directly turn to AI to handle much of the work for them.

While AI undoubtedly accelerates development and opens up new possibilities, this shift raises important questions: What happens to the developer’s ability to problem-solve when the complex math and algorithms are abstracted away by AI tools? How does the reliance on AI impact a developer’s capacity for deep, creative thinking in the face of technical challenges?

In the short term, the immediate result of this equation— "IT knowledge - Fundamentals + Using AI" —will likely lead to faster software delivery, an explosion of creative applications, and an increase in the number of people entering the tech field. However, in the long term, we may see an erosion of deeper problem-solving abilities, as young developers become more reliant on AI to fill in the gaps where fundamental knowledge once thrived. The risk? We could face a generation of developers who struggle when AI tools are unavailable or ineffective in complex, novel situations.

To maintain balance, it’s crucial to encourage the next generation of developers to not only use AI but also understand?why?and?how?it works. At #MNKnowledge, this exact balance is what we are striving to achieve in our consultancy and knowledge-share services.?By blending AI-driven development with a solid foundation in computer science, math, and algorithms, we can ensure that developers are equipped not just to use the tools of tomorrow, but to innovate and build the next generation of tech.