The introduction of AI into many production processes has also changed the role of software professionals.
Today, at any level, it’s hard to imagine not relying on it.
Writing code “by hand” is no longer a virtue. It’s often inefficient and uneconomical.
But this isn’t a sudden disruption: for decades we’ve been writing languages meant for compilers, not for machines directly.
AI takes this one step further.
It moves the abstraction layer higher, bringing interaction with computers closer to human language.
Today, the professional communicates intent and constraints to a model, receives code, which is then compiled and executed.
What doesn’t change are the decisions.
Processes, software architecture, domain modeling, and choices about use cases remain human responsibilities.
It’s not true that anyone can build reliable software just by relying on a chatbot.
Just as an advanced accounting system alone doesn’t guarantee healthy finances.
The difference is always made by decisions: knowing what to build, what to leave out, and which direction to take.
That’s why AI doesn’t reduce the role of the software professional. If anything, it makes it more central.
I see this as a major evolutionary opportunity.
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