Max Headroom 
Last week, I found myself hunched over my laptop at 10 p.m. (hey, that’s late for me!), wrestling with a coding problem. After hours of frustration, I stepped away and made a cup of tea. When I returned, I did what any self-respecting technologist in 2025 would do: I backtracked, reformulated my question, and asked ChatGPT for help.
I’m constantly asked questions like “Should my kids learn to code?” and “What skills do they actually need in this AI world?” I wonder about this too. I mean, if AI can now write code better than most humans, should we still be teaching kids to do it? How do we prepare them for the future, especially as things are moving so quickly?
Perhaps counterintuitively, this AI revolution might make a liberal arts education more valuable. A poetry major learns how to express humanity. A historian learns lessons from the past. A philosophy student learns to question assumptions and ethical frameworks. These timeless human skills become even more crucial as AI handles the technical heavy lifting. With these foundational abilities to understand and express the human condition, what’s possible with creativity becomes boundless.
The End of Coding Is the Beginning of Problem-Solving
As AI starts writing code, we’re entering what my friend Tim O’Reilly calls “the end of programming as we know it.” We’ve gone from punch cards to assembly language to C, Python, and JavaScript—and now we’re just telling computers what to do in plain language. That shift opens the door for more people to shape technology. The future isn’t about knowing code; it’s about knowing what to build and why.
Stanford researchers, including Noah Goodman (who’s both a computer scientist and a psychologist studying human cognition), recently published a fascinating paper examining how different AI systems approach problem-solving.
What makes Goodman’s perspective so valuable is his dual expertise in how minds, both human and artificial, work. His paper shows that the thinking patterns that make certain AI systems more successful mirror those of effective human problem-solvers: The most successful systems verify their work, backtrack when stuck, break big problems into manageable subgoals, and work backward from desired outcomes.
It’s a profound discovery: The skills that make humans effective problem-solvers will remain valuable regardless of how AI evolves. It made me realize that these cognitive behaviors—not coding syntax—are what we should be nurturing in our children.
Five Essential Skills Kids Need (More than Coding)
I’m not saying we shouldn’t teach kids to code. It’s a useful skill. But these are the five true foundations that will serve them regardless of how technology evolves.
1. Loving the journey, not just the destination
When homework seems impossible or a LEGO structure collapses for the fifth time, it’s easy for kids to get discouraged. But teaching them that setbacks are learning opportunities builds the bounce-back ability they’ll need in a rapidly changing world. The capacity to absorb genuine setbacks and continue forward—discovering something new even when they don’t reach their initial goal—might be the single most important skill we can nurture in our kids.
Developing a love of learning helps them to see tough problems as interesting puzzles rather than scary roadblocks. This doesn’t just apply to academic subjects. Genuine curiosity about the world prepares children to adapt continuously. The most successful people I know aren’t those who memorized the most facts or mastered one specific skill; they’re the ones who stayed curious and kept going through constant change.
We often talk about intrinsic motivation as a prerequisite for learning, but it’s also a muscle you build through the learning process. As children tackle challenges and experience the satisfaction of overcoming them, they’re not just solving problems; they’re developing the motivation to tackle the next one.
2. Being a question-asker, not just an answer-getter
When you’re a student, you’re judged by how well you answer questions.…But in life, you’re judged by how good your questions are.—Robert Langer, MIT Professor and Cofounder of Moderna
Anyone can ask AI for answers. Those who ask thoughtful questions will get the most from it. Good questions stem from understanding what you don’t know, being clear about what you’re really looking for, and framing them in a way that leads to meaningful answers.
One of the most powerful metaskills we can help children develop is self-awareness about their own learning style. Some are project-based learners who need to build something in order to understand it. Others learn through conversation, writing, visualization, or teaching others. When a child discovers how their brain works best, they can approach any new subject through the lens that works for them, turning what might have been a struggle into a natural process.
When a child asks, “Why is the sky blue?,” they’re doing something powerful: noticing patterns, questioning what others take for granted, and seeking deeper understanding. Children who learn to ask good questions will direct the world rather than be directed by it. They’ll know how to break big problems into solvable pieces—an approach that works in any field.
3. Trying, failing, and trying differently
When solving problems, scientists don’t move forward in a straight line. They make guesses, test them, and often discover they were wrong. Then they use that information to make better guesses. This try-learn-adjust loop is something all successful problem-solvers use, whether they’re fixing code or figuring out life.
When something doesn’t work as expected—including an AI-generated answer—kids need to figure out what went wrong and then try different approaches. This means getting comfortable with saying things like “Let me try a different way” or “That didn’t work because…”
Whether they’re troubleshooting a device or navigating everyday challenges, this mindset helps them approach problems with confidence rather than giving up.
4. Seeing the whole picture
The biggest challenges we currently face, from climate change to healthcare, require understanding how different pieces connect and influence each other. This “big-picture thinking” applies equally to everyday situations, such as understanding why a classroom gets noisy or why a family budget doesn’t balance.
This mindset is about spotting patterns and understanding how changing one thing affects everything else. It helps us anticipate unintended consequences and create solutions that actually work.
When we teach kids to see connections rather than isolated facts, we prepare them to tackle problems that AI alone can’t solve. They become directors rather than followers, able to combine human needs with technological possibilities.
5. Walking in others’ shoes
In my recent op-ed for the Chicago Tribune, I argued that efficiency and empathy aren’t opposing forces. They need each other. This principle is especially important as we raise the next generation.
Technology without human understanding leads to solutions that might look good on paper but forget the real people they’re meant to help. I’ve seen this firsthand in government systems that process people efficiently but fail to recognize their dignity and unique situations.
Children who develop deep empathy will create technologies that truly serve humanity rather than just serving statistics. They’ll ask not only “Can we build this?” but “Should we build this, and who will it help or harm?” They’ll remember that behind every data point is a human story, and that the most meaningful innovations are those that strengthen our connections to one another.
The Real Future: Amplifying Human Creativity
These five skills converge in what I see as the most exciting aspect of our AI-augmented future: democratized creation. As more people gain the ability to shape technology, even without traditional coding skills, we’ll see an explosion of local, purpose-driven solutions.
As I recently wrote, I helped put together ai/teens, the first global AI conference for and by teens. I wanted to learn from the first AI-native generation, which intuitively understands technology’s potential in ways many adults don’t.
Imagine a world where young people not only use technology but actively shape it to solve problems in their communities, designing accessibility tools for friends with disabilities, creating platforms that connect local resources with those who need them, or building educational experiences tailored to different learning styles.
This future isn’t about AI replacing human creativity; it’s about amplifying it, making it possible for more people to bring their unique perspectives and solutions to life.
Let’s Build This Future Together!
The beauty of this approach—focusing on resilience, questioning, adaptation, systems thinking, and empathy—is that it works regardless of how technology evolves. The most technologically advanced future still needs people who can embrace challenges, ask meaningful questions, learn continuously, see connections, and understand each other.
In many ways, we’re returning to the ideal of a classical education for the AI age. These skills form a modern trivium—not grammar, logic, and rhetoric but perhaps curiosity, creativity, and compassion—foundational abilities that unlock all other learning and doing.
Let’s work on this as a community! I’m crowdsourcing ideas, activities, and approaches that help develop these essential skills. What other skills do you think we should focus on? I’m eager to learn with all of you.
Artificial Intelligence, Research
Radar
