In one word, being a developer in 2024 feels “overwhelming.” In a sentence, it’s like running a never-ending race against daily technological advancements, where catching up feels impossible without years of experience. That might sound extreme, but I think it reflects the reality many developers face today.
Web development, in particular, has become one of the most oversaturated fields in the job market. But why? Some argue that everything worth building has already been done countless times. While there’s some truth to that, the root of the problem runs deeper.
The seeds of this oversaturation were planted in the 1990s, when programming began branching out from C-language into higher levels of abstraction. These new languages made complex tasks more accessible, allowing developers with less experience to build applications that would have been unthinkable for their predecessors. Fast forward to today, and we have countless libraries and frameworks—JavaScript alone is notorious for this—that make development faster and easier than ever.
This ease of entry, while a boon for innovation, has also led to saturation. With barriers lowered, more applications are being built, and more developers are entering the field, creating a highly competitive landscape.
The real challenge now is that many new developers skip foundational, lower-level concepts entirely. Instead of understanding what’s happening under the hood, they jump straight into the most modern layers of abstraction—reacting to surface-level advancements without ever mastering the fundamentals. In contrast, developers who take the time to learn these lower-level principles—memory management, algorithmic thinking, and architecture—can apply them to future innovations like AI, blockchain, or cloud computing.
AI is a perfect example of why foundational knowledge matters. At its core, AI relies on lower-level principles such as linear algebra, optimization algorithms, and efficient memory usage. Without a solid understanding of these concepts, it's hard to grasp what’s actually happening behind a neural network, or how to fine-tune models for better performance. Libraries like TensorFlow and PyTorch make it easier to work with AI, but real breakthroughs come from developers who understand how the algorithms work at a fundamental level. By mastering these concepts, you’re not just using AI—you’re advancing it.
Skipping the basics might work for a while, but it creates a dangerous reliance on frameworks and libraries that are popular today. When those tools are inevitably replaced, these developers fall behind, scrambling to catch up with the next big thing. On the other hand, those who invest in understanding the building blocks of technology can adapt more easily to advancements, finding ways to contribute meaningfully to new fields instead of waiting on the sidelines for the next trend to carry them forward.
The path for many developers in 2024 seems obvious: either take the time to understand the lower-level concepts and apply them to modern advancements, or be at the mercy of the next wave of abstraction. Those who choose the former are building a foundation that will last through technological trends, while the latter risk falling behind as the landscape continues to evolve.
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