The next evolution of software developers: from implementation to intent, orchestration, and ownership.
Over the last few months, I've read countless articles debating whether AI will replace software developers. Some predict the end of programming as we know it, while others argue that nothing significant will change.
The real transformation isn't that AI can write code. We already know it can. The interesting question is what happens to our profession when writing code is no longer the hardest part of building software.
When I look back at the history of software engineering, I notice a recurring pattern. Every major innovation has raised the level of abstraction.
We moved from Assembly to high-level languages. We stopped managing memory manually. Frameworks abstracted away repetitive boilerplate. Cloud platforms removed much of the operational complexity that once required dedicated teams.
Every step made developers more productive by allowing them to focus less on implementation and more on solving problems.
AI feels like the next step in that same evolution. Instead of replacing software developers, AI is moving us one level higher in the abstraction stack.
The shift isn't from developers to AI. It's from writing code to defining intent, orchestrating systems, and owning outcomes.
When I started my career, software development revolved around the IDE. A typical day meant creating classes, implementing functions, fixing bugs, and gradually evolving a codebase one commit at a time.
As software systems became larger, something interesting happened. Understanding existing code became just as valuable as writing new code.
Entire consulting projects revolved around taking ownership of legacy applications, understanding how they worked, fixing bugs without introducing regressions, and safely adding new functionality.
Reading code became a highly valuable skill because understanding the system was ultimately more important than producing another hundred lines of PHP or Java.
Every major evolution in software engineering has raised the level of abstraction. AI is simply the next step.
More and more of my time is spent understanding problems before thinking about implementation.
I define requirements, clarify constraints, evaluate trade-offs, design architectures, connect existing platforms, review AI-generated code, and decide where deterministic software is sufficient and where AI reasoning genuinely creates value.
Writing code is still part of my work, but it is no longer necessarily the activity that creates the most value.
This is why I don't believe software developers are disappearing. I believe we're moving to another layer of the stack.
The skills and technical knowledge accumulated over years don't suddenly become irrelevant. Quite the opposite. They allow us to operate at this higher level because we can understand what is happening underneath the abstractions we use.