Why Programmers Won't Be Replaced, But Will Evolve.

Doing a project after a while, I realized how insanely fast large language models (LLMs) are improving. Sure, we hear about their capabilities and achievements, but you will be shocked when you actually use them for work. This experience got me thinking: what is the future of programmers? We often hear that AI will replace them, but the truth is more complex. In my view, it is both true and false. Prior to transformers, coding a project was all about searching and reading documentation. You had an idea but did not know the right tools. The main difference between senior and junior programmers was their ability to search for similar problems and adapt solutions. AI has changed this dramatically. Now, you describe your task, and the AI codes it for you, using the necessary libraries and tools without you even needing to know them. Will AI replace programmers? Not exactly. I see it more like a student and an advisor. The advisor, who deeply understands the field, provides the vision; the student (LLM) implements it. Similarly, you describe your goals and your LLM handles the implementation. Creativity and the ability to give clear, feasible instructions will define success. Those who can adapt when results aren’t perfect will thrive. Today, it is less about learning libraries and more about understanding the theory. You must supervise your LLM like a good advisor, with deep knowledge of your goals. However, theory alone is not enough. Coding skills will still be crucial. LLMs have limited knowledge; they often do not know about libraries released in the past two years and may hallucinate when asked to use them. Plus, as frameworks evolve, older methods may raise errors. LLMs aren't perfect. Unlike human students, they won’t warn you when they're unsure. They sound confident even when wrong. Thus, analyzing and debugging AI outputs will be an invaluable skill. While you won't need to code everything from scratch, you will likely face more errors, making debugging essential. Finally, breaking tasks into subsystems is critical, especially for larger projects. Systematic thinking—generalizing problems, organizing work, and structuring tasks—will be more important than ever. In conclusion, while AI and LLMs are transforming the programming landscape, they won't replace programmers. Instead, they are reshaping the role—emphasizing creativity, clear communication, and systematic thinking. The future will belong to those who can leverage AI effectively, debug errors, and apply deep theoretical knowledge to guide the process. Adaptation, rather than replacement, is the key to thriving in this new era of programming.