Today, I came across a post on LinkedIn discussing Stack Overflow being put up for sale and the sharp decline in question–answer content produced since 2022.



I believe this is a topic that has been growing in many people’s minds for quite some time and deserves a deeper discussion. With the rapid advancement of modern artificial intelligence, I wanted to approach this subject from a new perspective. How we produce solutions in software development, and whether the tools we currently rely on are still sufficient, remains an open debate.

In this article, I want to explore the direction we are heading with the data we currently have, how the evolution of artificial intelligence will shape our approach to problem solving in the software industry, and where this transformation might ultimately lead us.



How Far Can Ready-Made Datasets Take Us?

Today’s artificial intelligence systems process and utilize the large datasets we already possess. However, unlike the early days of AI, this does not mean that thirty years’ worth of new data is added to these systems every single year. That phase was largely a one-time phenomenon—and it has already passed.

From now on, the data incorporated each year will mostly consist of whatever new content is produced during that period. In fact, statistics show that AI itself has increased the volume of content being generated. The real question, however, is this: Is this increase about quality, or merely quantity?


Yes, we fed massive knowledge bases like Stack Overflow directly into AI systems. The results were, as expected, quite impressive. But this raises a simple yet powerful question:

A father (human) raised his son (robot). But can the son produce a child of his own without ever experiencing life?

Artificial intelligence is excellent at organizing, summarizing, and restructuring existing information. But can it truly create a new solution?



This idea feels so clear to me that I could even place it as a slogan in the header of my website :)

Artificial intelligence organizes knowledge perfectly, but it does not generate the problem itself.

We handed over everything we had accumulated over years to AI so it could structure and process it for us. So what happens next?



The Software Industry and the Reality of Problem Solving

At the center of all this is a software industry that continuously generates new problems. New business models, new requirements, and increasingly complex systems ensure that software-related challenges never remain static.

This leads to an unavoidable question:

Will this situation become challenging for those of us working in the software industry in the future?

Because while trying to delegate solution creation entirely to artificial intelligence, we often overlook a critical distinction:

  • Experience-driven, context-aware solutions

  • Or logic-based, probabilistic solutions produced by artificial intelligence

AI is extremely strong in the second category. But the first—intuition, context, and real-world experience—still firmly belongs to humans.



Is a New Role Emerging?

There are two major question marks still waiting to be resolved. My personal view is this:

I believe a new role, a new type of leadership, will emerge to answer these questions. And this role will fundamentally reshape our traditional definition of a software developer.


Perhaps in the near future, this role will be known as:

Senior Problem Engineer

A role that does not move away from writing code, but instead is deeply familiar with code structures and the software ecosystem as a whole. This technical foundation enables a deep understanding of problems, allowing them to be clearly defined, properly scoped, and questioned in the right way.


With this level of expertise, the individual does not simply accept AI-generated solutions at face value, but interprets them, evaluates their consistency, and turns them into accurate and reliable outcomes.


Don’t you think the software world is moving precisely in this direction?