Recently, Mr. Nvidia made waves at the World Economic Forum by suggesting that we shouldn’t teach kids how to code. Naturally, this sparked outrage. But before jumping to conclusions, let’s take a step back—because people might have misunderstood what he was really saying.
The Evolution of Computing: Layers Change, Fundamentals Don’t
Computers are built on layers—hardware, operating systems, programming languages. Over the decades, we’ve moved from:
Assembly → BASIC → C++ → Python → AI-assisted coding
Yet, beneath all these layers, the core principles of computing have remained the same
- Logic gates
- Memory management
- Data pipelines
No matter how high-level coding gets, these principles are timeless. What does change is how we apply them.
Today, we’re witnessing a fundamental shift in computing—from serial processing (one task at a time) to parallel processing (many tasks simultaneously). And AI is just one major application of this shift.
AI’s Strengths and Limits
Take ChatGPT as an example. It can write in multiple languages and generate responses across countless topics—but has it replaced great writers or expert programmers? No.
That’s because AI isn’t thinking—it’s predicting.
Ask an AI, “How are you feeling?” It might reply, “I’m feeling great!” But the reality? It doesn’t actually feel anything.It’s just predicting the most likely response based on millions of past conversations.
AI operates on patterns, not understanding.
Let’s put it another way. Think about a tree. How do you define a tree? You might say it has branches, leaves, a trunk, roots, flowers—these elements make up a tree in your mind.
But for AI, it doesn’t actually “see” a tree. It just compares an image against thousands of others and guesses based on shape and color. That’s why AI sometimes makes bizarre mistakes—it’s performing high-speed pattern matching, but it’s not applying true logic.
Coding Will End, But Software Engineering Won’t
The days of manually typing out every line of code are fading. AI tools can now:
- Generate full scripts from plain English
- Automate debugging
- Build basic apps in minutes
But here’s the catch—writing code ≠ engineering.
The Future of Software Engineering
Being a Software Engineer isn’t about syntax—it’s about solving problems. As computers shift toward parallel processing, engineers will need to:
- Design complex, scalable systems
- Optimize workloads across multiple processors
- Handle real-world applications like self-driving cars, weather simulations, and factory automation
Basic coding will become as common as using a spreadsheet. But just like knowing Excel doesn’t make you a financial analyst, writing AI-assisted code won’t make you a software engineer.
Conclusion
Will coding as we know it end? Yes.
But software engineering? That’s only becoming more important.
The future isn’t about typing code—it’s about understanding systems, optimizing AI, and engineering solutions.
And that’s why real engineers will always be in demand.
Let us know what you think in the comments!!
