If AI Can Write Code, Should Kids Still Learn Programming?
5 min
Should Kids Still Learn to Code in the Age of AI?
It is a question we are hearing more and more from parents: If artificial intelligence can already write code, will kids still need to learn computer science?
It is an understandable concern. AI tools are improving quickly, and headlines frequently suggest that programmers may eventually become unnecessary. But according to Jensen Huang, founder and CEO of NVIDIA—the company whose technology powers much of today’s AI—that message is not only misleading. It may be actively discouraging young people from pursuing one of the most important fields of the future.
During a recent appearance on How I Built This with Guy Raz, Huang pushed back against warnings that AI will make software engineers obsolete. He said the alarmist message has gone too far and has scared people away from a profession that remains incredibly important to society. The podcast episode was released May 18, 2026, and includes a broader discussion of why Huang believes the next generation will have more opportunity because of AI, not less.
That perspective matters to us at Coder’s Clubhouse because children who learn computer science are not simply learning how to type lines of code. They are learning how to think, create, troubleshoot and turn ideas into working solutions.
The Radiologist Analogy
One of Huang’s clearest examples comes from healthcare.
AI can now help radiologists analyze medical scans faster and more efficiently. It would be easy to assume that this technology would reduce the need for radiologists. Instead, Huang points out that demand for radiologists has continued to grow.
Why?
Because the purpose of a radiologist’s job is not simply to look at scans. It is to diagnose illness, communicate with patients and other medical professionals, and help people receive the right care. Reading a scan is one task within that much larger responsibility.
When AI helps complete that task more quickly, radiologists can serve more patients, spend more time applying their judgment and expand the impact of their work. Huang has explained that productivity creates additional capacity—and that capacity can create growth rather than eliminate the profession.
The same principle applies to programmers.
A Programmer’s Job Is Not Just to Type Code
The purpose of a programmer’s job is not to manually produce as many lines of syntax as possible. It is to understand a problem and build something that solves it.
That might mean designing an app, protecting a company’s data, creating software for a hospital, programming a robot or developing a tool that has never existed before.
AI can help with parts of that process. It can suggest code, identify errors, explain unfamiliar concepts and accelerate repetitive work. But someone still needs to determine:
What problem should we solve?
What should the program do?
Is the AI-generated answer accurate?
Is the solution safe, useful and fair?
How should the different pieces work together?
What should we try when the first idea does not work?
Those questions require human judgment, creativity and technical understanding.
As Huang has emphasized, the tasks people perform and the ultimate purpose of their jobs are related, but they are not the same. At Carnegie Mellon University’s 2026 commencement, he similarly told graduates that AI automates tasks while elevating workers and creating new possibilities.
Learning to Code Is About More Than Code
At Coder’s Clubhouse, our students certainly learn programming skills. But what they are really practicing goes much deeper.
They learn how to break a complicated idea into smaller steps. They learn to test their work, find mistakes and try again. They experience the frustration of a project not working—and the satisfaction of finally figuring out why.
They also learn that technology is something they can shape, not simply consume.
These skills become more valuable as AI tools improve. A child who understands how technology works will be better prepared to guide AI, evaluate its output and use it to create something meaningful. A child who has never developed those foundational skills may be able to ask an AI tool for an answer, but they will have a much harder time knowing whether that answer is correct or what to do when it fails.
AI may lower some of the barriers to building software. That could allow more people to create more ambitious projects. But greater access to powerful tools makes critical thinking and technical literacy more important—not less.
This is the central point highlighted in the original blog brief: students are developing a problem-solving mindset that becomes more valuable as their tools become more capable.
This May Be One of the Best Times to Learn
Every major technological shift changes the work people do. Calculators changed mathematics. Computers changed nearly every office job. Digital cameras changed photography. None of those tools eliminated the need for people who understood the underlying craft.
They changed what those people were capable of accomplishing.
AI will undoubtedly change programming. Students may spend less time memorizing syntax and more time designing systems, evaluating results, solving larger problems and bringing their ideas to life. That is not the end of computer science. It is the next stage of it.
Huang told Carnegie Mellon graduates that no generation has entered the workforce with more powerful tools or greater opportunities. He described the current moment as the beginning of a new era of science, discovery and industry.
So, should kids still learn to code?
Absolutely.
They should learn to code not because programming will remain exactly the same, but because it will continue to evolve. The young people who understand technology, think computationally and know how to solve problems will be positioned to help shape what comes next.
The company powering much of the AI revolution is not telling students to walk away from computer science. Its founder is warning us about the harm caused when we scare them away from it.
That is a message worth sharing.
Sources: How I Built This with Guy Raz, “NVIDIA: Jensen Huang—From Near Collapse to Becoming the World’s Biggest Company,” released May 18, 2026; NVIDIA’s coverage of Jensen Huang’s 2026 World Economic Forum discussion and Carnegie Mellon University commencement address.
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