Why understanding code matters in the AI era

Today I ran into this Linkedin post from Wouter Denayer, former regional IBM CTO, that underlines the importance of knowing how your code works when coding.

Then I realized that Aragorn Meulendijks reposted Wouter’s content, making a case that no one will need to learn coding as this activity will be reduced to a commodity.

Personally, I believe that this way of thinking can make humanity stall. In fact, you could apply this idea to many field: “Don’t need to learn that, AI will do it/know it for you”…

We’ll never go very far if that’s the path we’re going to take.

Taking back Aragorn’s analogy between coding and electricity, here’s my take against the notion that coding is becoming a commodity like electricity, where understanding its intricacies is unnecessary:

1. False Equivalence: Comparing coding to electricity usage is misleading. While most people don’t need to understand electricity to use it, the same cannot be said for software development. Code isn’t a static infrastructure; it’s a constantly evolving, problem-solving tool.
2. Innovation Requires Understanding: The argument that “no one cares” about how electricity works ignores the critical role of electrical engineers and researchers who continually innovate and improve our electrical systems. Similarly, without developers who deeply understand code, we cannot push the boundaries of what’s possible in software.
3. Complexity of Software Systems: Unlike electrical systems, which have standardized over time, software systems are diverse and often bespoke. Understanding code is crucial for maintaining, debugging, and optimizing these complex systems.
4. Security Concerns: In an age of increasing cyber threats, understanding code is vital for creating secure systems. Relying solely on AI-generated code without comprehension is a recipe for vulnerabilities.
5. Adaptability and Problem-Solving: Knowing how to code and understanding its principles allows developers to adapt to new languages, frameworks, and paradigms. This adaptability is crucial in the fast-paced tech industry.
6. AI is a Tool, Not a Replacement: AI coding assistants are powerful tools, but they’re not infallible. Understanding code allows developers to critically evaluate AI-generated solutions and make necessary adjustments.
7. Continuous Learning: The tech industry thrives on continuous learning. Reducing coding to a commodity undermines this principle and can lead to stagnation in the field.
8. Building Better Products: Contrary to the claim, understanding the intricacies of code is exactly what allows us to build “constantly better and more-value-adding products.” Deep knowledge enables innovation and optimization.
9. Ethical Considerations: As AI and software increasingly impact society, we need developers who understand the ethical implications of their code. This requires a deep understanding of how code works and its potential consequences.
10. Problem Domain Knowledge: Effective software development requires not just coding skills but also an understanding of the problem domain. This holistic knowledge is crucial for creating truly valuable solutions.

Moreover, understanding code deeply doesn’t just prevent stagnation; it actively propels innovation forward. When developers truly grasp the intricacies of programming, they can think outside the box, combining concepts in novel ways to create groundbreaking solutions. This deep knowledge allows them to see possibilities that might be missed by those relying solely on AI-generated code or surface-level understanding. From developing more efficient algorithms to architecting entirely new systems, the creative potential unlocked by a thorough understanding of code is limitless. It’s this kind of innovation that pushes the boundaries of technology, solving complex problems and opening up new frontiers in fields like artificial intelligence, quantum computing, and beyond. By fostering a culture of in-depth coding knowledge, we’re not just maintaining the status quo — we’re actively shaping the future of technology and human progress.

In conclusion, while AI tools can enhance productivity, they should complement, not replace, a deep understanding of code. The future of technology depends on developers who can think critically, solve complex problems, and innovate — skills that come from truly understanding the code they write.

Check https://www.linkedin.com/in/alexandrelarose/ for more insight on CS, software development & continuous learning 😊