The software development profession is undergoing one of the most profound transformations in its history. AI is reshaping roles, expectations, skills, and daily work.
My Decision to Create This Series of Posts
I chose to create a series of posts to share the many thoughts I have about the transition the software development profession goes through. The main purpose of this series of posts is to explore the central question: how can we help professional software developers adapt to a rapidly changing, AI-driven reality? Rather than offering a fixed framework or a one-size-fits-all answer, this series will unfold gradually across the various dimensions of this question.
Evolving Perspectives on Software Development in the AI Era
Each and every post will examine a specific dimension of the transformation developers are experiencing. Some posts will focus on learning models, others on professional roles, education structures, skills prioritization, and the evolving relationship between humans and AI. This master post serves as an entry point and a continuously updated index. As new posts are published, links will be added here to reflect the evolving conversation. The intent is to create a structured yet flexible map that professionals can revisit over time, using it to reflect, reassess, and adjust their own development paths.
The Posts This Series of Posts Includes
Industry practice, academic teaching, and economic thinking come together in this series exploring how professionals adapt in the AI era. The first posts that are already available in this series are:
The Role of the Teacher (Coming Soon)
Additional posts will follow in the coming weeks, expanding the discussion as the landscape continues to evolve.
Engineering, Education, Business and Economics Convergance
The perspective behind this series is shaped by an uncommon combination of long-term industry practice, business management (especially during the years 2001 and 2007 when my company developed more than 200 games for mobile telephones and distributed them worldwidewide), academic teaching, and formal economic theories. For nearly three decades, I have worked as a professional software development trainer in high-tech companies across multiple technological eras. My journey started with low-level programming and continued with Java to modern frameworks, architectures, and paradigms. In parallel, I have spent over 25 years teaching academic courses in computer science, closely observing how foundational education translates—or fails to translate—into real professional success. What makes this viewpoint distinct is its economic backbone. My academic education in economics and accounting, including advanced studies in pricing theory and years of teaching economics at the Open University, provides a systemic lens for understanding change. Economics is not about money, and when dealing with microeconomics, it is about indifference curves, which set the foundation for nearly everything there is in pricing theory. These same forces are now reshaping software development under the impact of AI. The ideas explored throughout this series are not theoretical speculation. They emerge from building real products, managing development teams, teaching thousands of students, and continuously analyzing how systems evolve when technology disrupts established equilibria.
If software development is being reshaped so fundamentally by AI, is it truly unique, or merely the first domain to undergo such a transformation? Will similar shifts emerge in law, medicine, education, or management? And if the patterns repeat, what can other professions learn from the software developers’ experience before disruption becomes unavoidable?
