AI has changed the way we write software.
Today, you can describe a feature in a few sentences and get working code in seconds. You can ask AI to fix an error, explain an unfamiliar function, write tests, or even build an entire small application.
But there is one thing I think developers should be careful about:
Writing code is not the same as solving a problem.
The Problem With “Just Ask AI”
Imagine your application is slow.
You ask an AI:
“My API is slow. Optimize this code.”
It might suggest better queries, caching, asynchronous operations, or a completely different implementation.
The code may even look impressive.
But what if the real problem isn't the code?
Maybe:
- The database has a missing index.
- An external API is taking 3 seconds to respond.
- The application is making unnecessary requests.
- A poorly designed feature is causing excessive traffic.
- The server doesn't have enough resources.
- The system was never designed for the current number of users.
AI can improve the code you show it. But it doesn't automatically understand the entire system behind that code.
This Is Where Developers Still Matter
A good developer doesn't simply ask:
“How do I fix this error?”
They ask:
“Why did this error happen?”
That difference is important.
AI can give you ten possible solutions.
Your job is to determine:
- What is actually happening?
- What caused it?
- Which solution fits the architecture?
- What could break if we apply it?
- How can we verify that the solution really works?
That's engineering.
AI Should Make Us Better, Not Lazier
I don't think developers should avoid AI.
Quite the opposite.
Use it.
Use it to:
- Explore unfamiliar technologies
- Generate boilerplate
- Explain complicated code
- Create test cases
- Find potential bugs
- Compare different approaches
- Learn faster
- Automate repetitive work
But don't outsource your thinking.
Before accepting an AI-generated solution, ask yourself:
“Do I understand why this works?”
If the answer is no, that's probably the next thing you should learn.
The Developer Skill That Is Becoming More Valuable
As AI becomes better at generating code, I believe problem-solving and system understanding will become even more important.
Knowing syntax is useful.
Knowing frameworks is useful.
Knowing how to use AI is useful.
But understanding users, requirements, architecture, trade-offs, performance, security, and business problems is much harder to automate.
The future developer might not be the person who writes the most code.
It may be the person who can look at a messy problem and say:
“Here is what is actually happening, here is why, and here is the simplest solution.”
A Question for Developers
When you use AI for coding, what do you usually use it for?
A) Writing code faster
B) Debugging
C) Learning new technologies
D) Generating complete features
E) Almost everything
And more importantly:
Do you think AI is making developers better problem solvers—or making us depend on it too much?
I'd love to hear your experience.
Sumita
Web Developer
