Industrialization of IT: The Future of Software Engineering in the AI Era
Software engineering, once considered a creative and strategic discipline, is changing rapidly. With the advent of advanced artificial intelligence models such as Gemini 2.5 Pro, a new era is beginning to take shape – the era of IT industrialization. This shift could fundamentally change the way software is developed and raise questions about the future of human engineers. As AI becomes cheaper, faster, and more efficient, it is worth asking: How much longer will humans remain indispensable in this equation?
Humans vs. Machines: Who Is More Productive?
Let’s break it down with an example. In San Francisco, an entry-level software engineer earns approximately $190,000 per year. After factoring in additional costs such as benefits and taxes, the total cost of an employee rises to $250,000 per year. On the other hand, we have the Gemini 2.5 Pro AI model, which can process enormous amounts of code at a fraction of that cost. For example:
- One request to Gemini, involving 50,000 input tokens and 5,000 output tokens (roughly 5,000 lines of input code and 500 lines of output code), costs just 11 cents.
- If you sent a request every 15 seconds throughout the year, you would spend $237,000 – less than the cost of one junior engineer.
At first glance, AI appears to be a cheaper alternative. But what about productivity? A human engineer has an advantage in creativity, strategic thinking, and the ability to understand the broader context. On the other hand, AI can generate enormous amounts of code, albeit with errors and without deep understanding. Although a human engineer may still win today, the future may not be so clear-cut.
Why Is AI Becoming an Increasingly Stronger Competitor?
Today’s AI models, such as Gemini, are the most expensive and least capable they will ever be. In the coming years, it is expected that:
- Models will become cheaper and more powerful: The costs of running AI are falling exponentially, while its capabilities are growing.
- Optimization of AI’s work: Current models are not fully optimized. With better tools and processes, their efficiency will increase significantly.
- Better infrastructure for AI: Today, AI works in an environment designed for humans – it uses tools such as IDEs, GitHub, and documentation written for human readers. In the future, these tools will be adapted specifically to AI’s needs, increasing its productivity.
Industrialization of Software Development
Imagine a future where, instead of a team of 20 engineers collaborating on software development, you have four people overseeing a factory full of AI models. These models could generate code continuously, 24 hours a day, 7 days a week, without the need for sleep, vacations, or breaks. The cost of such an operation would be half that of a team of humans, but productivity would be astronomically higher. To make this possible, the very foundations of software development would also have to change:
- Code optimized for machines: Instead of code that is readable and understandable to humans, code would be designed so that machines could process it efficiently. This could include greater modularity, parallel processing, and minimizing interdependencies.
- Tools for managing AI: Instead of traditional collaboration tools, systems for monitoring and controlling AI’s work would emerge. Humans would become more like supervisors, overseeing machine performance and resolving potential problems.
Today, the work of a software engineer is considered creative and strategic. But as history shows, the Industrial Revolution never halted its progress because of the romanticization of human labor. Just as steam engines replaced manual labor, AI may replace many aspects of software development. This does not mean that engineers will disappear entirely. Their role, however, will change. Instead of writing code, they will focus on managing and optimizing AI’s work. They will oversee “factories” full of AI models that will generate code on a massive scale.
IT industrialization is not a question of “if,” but “when.” Companies that can manage this transformation will dominate the market. They will be able to produce software faster, more cheaply, and on a larger scale than ever before. And just as steam engines transformed industry, AI will transform software engineering. For engineers, this means that their work will become less about writing code and more about managing machines. And for all of us, it means that the future of software will be cheaper, faster, and perhaps less human.
