As a programmer, most of my knowledge did not come from classrooms or formal courses. Of course, the basics come from books, tutorials, and lectures. But the real learning moments? They mostly came from mistakes.
Why Mistakes Are the Best Teachers
A mistake is concrete. You write code, run the program, and bam — a crash, an error message, or behavior that doesn’t match your expectations. In that moment, you are forced to figure out:
- What went wrong?
- Why did this happen?
- How do I fix it?
That process digs deeper than any course. You read documentation you’d normally skip, experiment with alternatives, and develop a stronger understanding of the technology.
Examples from Practice
- Memory leaks in C++: Spending hours debugging a missing
deletemade me far more aware of memory management than any theory lesson. - Misusing APIs: The frustration of failed requests forced me to truly understand how protocols and headers work.
- Git mistakes: A bad merge that wrecked a branch taught me more about version control than any workshop could.
Every mistake was painful in the moment, but valuable in the long run.
The Difference with Education
Education is often linear and controlled. You follow a syllabus, get examples, and learn “the right way.” But in practice, situations are messy. Bugs aren’t always logical, documentation is unclear, and systems behave unexpectedly. It’s in that gray area where you become creative and learn to think independently.
AI as an Intern
Today, there’s a new factor: AI as a programming assistant. For me, AI feels like a good intern. It can quickly suggest ideas, generate snippets of code, and offer alternative approaches. But as with any intern, it’s my experience and knowledge that determine whether the result is correct, safe, and relevant. AI speeds up my work, but I always act as the editor. Without that final review, mistakes, inaccuracies, or inefficient solutions would slip through.
Conclusion
Mistakes are not obstacles, but building blocks. They force you to dig deeper, give you practical experience, and build resilience. For me, the most important skills I use daily weren’t learned in a course, but by making mistakes — and overcoming them step by step. And now that AI has become my “digital intern,” I learn even faster. But the final decision and the quality always come from my own knowledge and experience.