Artificial intelligence is no longer just a supporting tool for software developers; it is fundamentally changing the nature of their work. Traditionally, software development has been centered around technical implementation: developers write, test, and maintain code themselves. In recent years, however, software development has evolved rapidly, requiring developers to adopt entirely new ways of working. In this article, Profium’s software developer Miki Suominen explains how AI is reshaping the structure of his work.
How AI is changing the daily work of developers
“I always start with planning: I think about how the overall solution can be divided into clear, independent components. Only when the components and their interfaces are clearly defined do I let AI agents develop them in parallel,” Suominen explains.
In practice, developers no longer write all the code themselves. Instead, they guide, evaluate, and integrate components produced by AI. The more work that is delegated to agents, the more important it becomes to plan and orchestrate the process effectively.
At the same time, AI is changing where developers focus their attention. As code generation becomes faster, understanding the bigger picture takes center stage: what is being built and why.
“The code itself is often indistinguishable from code written by a human. The difference is that AI is familiar with a vast range of libraries, technologies, and solutions—often ones that would not immediately come to mind. AI provides the options, but choosing the right one still requires expertise,” says Suominen.
This makes AI a powerful tool, but it does not eliminate the need for professional expertise. In fact, defining the right direction becomes even more important, Suominen explains:
“If a developer is heading in the wrong direction, AI-assisted coding only increases the speed at which that happens. The codebase moves away from the intended destination much faster.”
The role of the developer is no longer limited to implementing individual features. Increasingly, it involves correctly understanding the significance of data. At Profium, this means focusing on the design of data models, structures, and rules—not just building traditional application logic.
The growing adoption of AI also affects how expertise is developed. Previously, a significant portion of learning came from writing code manually and solving problems step by step.
“Now that AI tools are becoming commonplace, part of that skill-building phase is disappearing,” Suominen notes.
As a result, responsibility shifts even more to the developer. Expertise can no longer be built solely as a byproduct of day-to-day work; it must be developed consciously and deliberately.
Suominen points out that a developer’s value has never depended on how quickly they can produce code and AI does not change that. Instead, it makes this reality more visible. As generating code becomes increasingly effortless, what remains is what has always mattered most: understanding systems and being able to guide work toward the right outcome.
How Profium is building AI-assisted software development
At Profium, the use of AI is developed through practical experimentation and continuous learning. New tools, such as agent-based programming, are introduced in a controlled manner through sprint-based initiatives, allowing their real value to be assessed.
“We’re exploring what the best way of working with this technology will be going forward,” Suominen explains.
This approach reflects Profium’s broader operating philosophy: technology is not adopted simply because it is trendy, but as part of a larger framework that emphasizes understandable architectures, controlled development, and reliable systems.
“AI is evolving so rapidly that there is no static plan. We are constantly learning how to make better use of it.”
