In a world where machines are increasingly entering the domain of human creativity, we are on the threshold of a revolution in software development. As in Isaac Asimov's visionary novel I, Robot, where machines gradually take over increasingly complex tasks, so in our reality, tools such as Coursor AI, Devin, GitHub Copilot, and Replit Agent are beginning to transform the programming landscape.
This idea, deeply rooted in our culture, is reminiscent of the biblical concept of the creation of man in the image and likeness of God. Today, standing on the threshold of a revolution in the field of artificial intelligence, especially in the context of coding tools, we are witnessing the realization of these eternal dreams. This both scares us and pushes us to further develop them.
The tools mentioned are not just ordinary programming assistants – they are the first signs of a coming era in which the software development process will undergo a fundamental transformation. Although many programmers are still skeptical about their capabilities, pointing to current limitations and errors, history shows that technological progress often surprises with its pace and scale.
Criticism of AI tools in programming often focuses on their current limitations. Developers point to bugs in the generated code, a lack of understanding of the broader context of the project, or an inability to navigate large code bases. These arguments, while valid today, may not take into account the dynamics of AI technology development.
My thesis is based on the belief that we are witnessing a fundamental transformation in the field of software development. Software development as we know it today will likely disappear in its current form, giving way to new paradigms of work.
Key aspects of this transformation are:
I have observed that many of us in the IT industry, myself included, have been skeptical of the idea that AI could significantly change the nature of programming. Perhaps it was an expression of our ego, or perhaps the egalitarianism so characteristic of the IT community. However, the words of Jensen Huang, CEO of NVIDIA, that machines will soon do our bidding, force us to reflect deeply on the future of our profession.
What caused my approach to change? First of all, the emergence and development of new tools. I decided to approach them with an open mind, testing their capabilities without prejudice. The results were surprising – these tools can already generate simple applications, identify potential errors, analyze the code in terms of standards, quality or even scalability of the solution. It helps significantly in generating mockups or scripts based on the provided documentation of a given library.
My perspective has also been influenced by conversations with people who look further into the future. They have forced me to reflect on the pace of technological progress.
It is worth recalling the revolution in image recognition. In the years 2010-2014 there was a breakthrough thanks to deep learning. ILSVRC competitions on the ImageNet dataset show how the algorithms' performance improved dramatically from 28.2% top-5 error in 2010 to 3.6% error (ResNet) in 2015, surpassing human performance.
This example shows how quickly technology can push boundaries that previously seemed impossible.
Another argument is the current situation on the IT market. After the lean years of 2022-2023 for the IT industry, there was no quick rebound after the pandemic. This may suggest that the industry is on the verge of fundamental changes, and traditional software development models may be giving way to new, AI-based paradigms.
In the face of this technological revolution, roles in the IT industry will undergo significant redefinition.
This transformation does not mean the end of the programming profession and other IT roles, but rather their evolution in a more strategic and creative direction. We must be willing to adapt, constantly learn and develop new skills. The future of programming may be more about skillfully managing and collaborating with AI systems than traditional coding from scratch.
We are at the threshold of an era where the line between human and machine in software development is becoming increasingly blurred. It is an exciting, if somewhat unsettling time. Our task now is not to defend the status quo but to actively shape this new reality, ensuring that the development of AI in programming serves humanity and expands our capabilities, not limits them.
P.S. The text was created using Claude Sonnet 3.5
Image prompt Dalle3: Two people looking behind the window from a small room and a dark room with computers are overseer thousands of robot software developers writing code in a long hall bellow, post apocalyptical vision, wide-angle view,