I'd break programming skills into two key areas in this discussion. The first is logical thinking and understanding technologies. The second is remembering precise syntax and developing muscle memory for writing code efficiently.
It's undeniable that AI-generated code reduces the need to remember syntax or build that muscle memory. For less experienced developers, such habits may never even form. But is this necessarily a bad thing? Given that AI coding assistants can now even run locally, I don't foresee a future where these tools suddenly disappear or become significantly worse. On the contrary, AI's ability to generate code will continue improving month by month, making manual line-by-line coding less relevant.
What matters more is understanding software architecture, logical reasoning, and knowing how to use selected technologies properly. Without this understanding, a developer lacks the ability to guide AI effectively and validate its decisions. We can debate how long it will take until human developers no longer need to worry about code structure, readability, and maintainability. But in my experience, we're not yet at a point where so-called Vibe Coding-where AI-generated outputs are assessed purely based on functionality rather than code quality-works in complex, large-scale projects.
The real risk in AI-assisted development is over-reliance on AI without fully understanding the underlying technology. When encountering unfamiliar concepts, many trust that "if it works, it must be right." Yet, a bigger danger than something not working and not knowing why something is working, but still not knowing why.
Remember, AI isn't just a code generator - it can also be your personal mentor. Whenever AI produces something you don't fully understand, ask it to explain how the solution works and why it follows a particular approach. At the very least, you'll learn something new that will help you guide AI in a more sustainable direction in the future.
