In coding, just like in life, exposure matters.
Designers talk about “visual literacy” — the more good design you’ve seen, the better you get at recognizing and creating it. The same applies to code.
Today, many developers generate code with AI.
But here’s the problem for beginners: they often can’t tell what’s good code and what’s just “working for now.” They don’t know what will scale, what will collapse under pressure, or what will haunt them in production at 3 AM.
That’s where exposure to code comes in.
The more examples you read, the more patterns you absorb, the stronger your intuition becomes. Just like machines are trained on massive datasets, humans need their own “dataset” of projects, repos, and codebases.
The difference?
AI predicts patterns.
Humans make decisions.
So it’s not enough to just stare at code. You need to sharpen your exposure toward clean architecture, maintainability, readability, and efficiency. That’s how instincts are built — so you can choose the best path, not just any path.
Because in the end, code exposure is like traveling:
the more places you’ve seen, the better you understand the world.
The more code you’ve seen, the better you understand how to build it. 🌍💻
Just make sure you’ve been exposed to good patterns too — and have seen them working in real life.
Top comments (0)