Remember when we thought knowing five programming languages made us cool? Well, plot twist - now clear writing in English might be just as important as your ability to write a perfect for-loop, in ANY programming language. 🤷‍♂️
The rise of AI has changed how we build software. Multiple AI tools are now available to help us write code, faster with just simple text prompts. The better the prompt, the better the code. Creating software is no longer a solo activity. 🤖
AI is changing how we build software, but not exactly how we imagined.
Having an AI in your codebase is like having an enthusiastic junior developer who can type at lightning speed but needs someone to point them in the right direction.
Sure, they’ll write code faster than you can say “Hello World,” but they’ll also introduce bugs that'll make you question your life choices.
The shift brings new priorities for developers. System design, architecture planning, and clear communication are becoming essential skills. And here’s the funny part - the better you explain what you want, the better code you get.
It’s like teaching a very literal-minded intern who takes “make it pop” as an instruction to add explosion animations everywhere.
But there’s a catch with rapid prototyping through AI. Getting that first version out feels great - until real users start poking around.
Suddenly you’re dealing with weird edge cases that crash your app because someone tried to input their 47-character middle name, or performance issues because the AI didn’t consider what happens when 10,000 users hit the server at once.
Here’s the real kicker: letting AI write all your code without understanding how it works is like learning to drive by sitting in the passenger seat. You might get where you’re going, but good luck when something goes wrong. You miss out on:
- Building debugging skills (beyond asking “AI, why is it broken?”)
- Learning fundamental patterns (instead of copy-pasting solutions)
- Understanding architectural decisions (beyond “the AI said this was better”)
- Maintaining and improving code (without calling AI for help every time)
The result? You become dependent on AI to fix problems instead of developing your own expertise. It’s like having a calculator but never learning how to do math - fine until your battery dies.
Check out this tweet:
You cannot rely on AI to write complete code for you. You need to understand the code it generates. I can actually relate this to my own experience. I have used AI to write code for my projects. But I always end up spending more time debugging than writing code. But then I realized that I am not using it correctly.
The key is finding the right balance.
Use AI as a helpful tool, not a crutch. Write clear requirements, understand the code it generates, and most importantly, keep learning the fundamentals. Because at the end of the day, someone needs to know why the code works - and that someone should probably be YOU.
P.S: I am already using AI heavily in all of my projects. It has helped me write code faster and more efficiently. Because of AI I can now write code in any language, for any platform. But I am also a firm believer in the importance of fundamental knowledge.
