Depth Over Breadth in Learning | Generated by AI
Absolutely! That’s a really insightful parallel. Working deeply on a few challenging, well-designed projects will teach you far more than churning through dozens of simple ones.
When you dive deep into a complex codebase, you encounter real architectural decisions, performance considerations, edge cases, and design patterns that you’d never see in tutorial-level projects. You learn how to debug tricky issues, refactor messy code, handle technical debt, and work within constraints. You also get to see how different parts of a system interact over time.
Plus, those deeper projects often force you to really understand the underlying concepts rather than just copying patterns. You might spend days wrestling with a single problem, but by the end you truly get it in a way that superficial exposure never provides.
The “few deep projects” approach also mirrors how professional development actually works - you’re rarely building everything from scratch. You’re usually diving into existing systems, understanding how they work, and making meaningful improvements.
It’s like the difference between reading 50 book summaries versus really studying 5 books thoroughly. The surface approach gives you breadth but misses the depth where real learning happens.
Have you noticed this in your own coding experience? Are there particular projects that taught you way more than you expected because you stuck with them through the complexity?