Final week, I discovered myself hunched over my laptop computer at 10 p.m. (hey, that’s late for me!), wrestling with a coding downside. After hours of frustration, I stepped away and made a cup of tea. After I returned, I did what any self-respecting technologist in 2025 would do: I backtracked, reformulated my query, and requested ChatGPT for assist.
I’m continually requested questions like “Ought to my youngsters be taught to code?” and “What expertise do they really want on this AI world?” I’m wondering about this too. I imply, if AI can now write code higher than most people, ought to we nonetheless be educating youngsters to do it? How can we put together them for the longer term, particularly as issues are shifting so shortly?
Maybe counterintuitively, this AI revolution may make a liberal arts schooling extra invaluable. A poetry main learns find out how to specific humanity. A historian learns classes from the previous. A philosophy pupil learns to query assumptions and moral frameworks. These timeless human expertise change into much more essential as AI handles the technical heavy lifting. With these foundational skills to grasp and specific the human situation, what’s potential with creativity turns into boundless.
The Finish of Coding Is the Starting of Drawback-Fixing
As AI begins writing code, we’re coming into what my buddy Tim O’Reilly calls “the tip of programming as we all know it.” We’ve gone from punch playing cards to meeting language to C, Python, and JavaScript—and now we’re simply telling computer systems what to do in plain language. That shift opens the door for extra individuals to form expertise. The long run isn’t about realizing code; it’s about realizing what to construct and why.
Stanford researchers, together with Noah Goodman (who’s each a pc scientist and a psychologist finding out human cognition), just lately printed a fascinating paper inspecting how completely different AI techniques strategy problem-solving.
What makes Goodman’s perspective so invaluable is his twin experience in how minds, each human and synthetic, work. His paper reveals that the pondering patterns that make sure AI techniques extra profitable mirror these of efficient human problem-solvers: Essentially the most profitable techniques confirm their work, backtrack when caught, break huge issues into manageable subgoals, and work backward from desired outcomes.
It’s a profound discovery: The talents that make people efficient problem-solvers will stay invaluable no matter how AI evolves. It made me notice that these cognitive behaviors—not coding syntax—are what we must be nurturing in our youngsters.
5 Important Expertise Children Want (Greater than Coding)
I’m not saying we shouldn’t train youngsters to code. It’s a helpful ability. However these are the 5 true foundations that may serve them no matter how expertise evolves.
1. Loving the journey, not simply the vacation spot
When homework appears inconceivable or a LEGO construction collapses for the fifth time, it’s straightforward for youths to get discouraged. However educating them that setbacks are studying alternatives builds the bounce-back capacity they’ll want in a quickly altering world. The capability to soak up real setbacks and proceed ahead—discovering one thing new even once they don’t attain their preliminary aim—is perhaps the only most necessary ability we will nurture in our children.
Growing a love of studying helps them to see powerful issues as attention-grabbing puzzles slightly than scary roadblocks. This doesn’t simply apply to educational topics. Real curiosity in regards to the world prepares kids to adapt constantly. Essentially the most profitable individuals I do know aren’t those that memorized probably the most information or mastered one particular ability; they’re those who stayed curious and saved going by means of fixed change.
We regularly discuss intrinsic motivation as a prerequisite for studying, however it’s additionally a muscle you construct by means of the training course of. As kids sort out challenges and expertise the satisfaction of overcoming them, they’re not simply fixing issues; they’re growing the motivation to sort out the following one.
2. Being a question-asker, not simply an answer-getter
While you’re a pupil, you’re judged by how nicely you reply questions.…However in life, you’re judged by how good your questions are.—Robert Langer, MIT Professor and Cofounder of Moderna
Anybody can ask AI for solutions. Those that ask considerate questions will get probably the most from it. Good questions stem from understanding what you don’t know, being clear about what you’re actually in search of, and framing them in a manner that results in significant solutions.
One of the crucial highly effective metaskills we may help kids develop is self-awareness about their very own studying model. Some are project-based learners who have to construct one thing to be able to perceive it. Others be taught by means of dialog, writing, visualization, or educating others. When a baby discovers how their mind works greatest, they’ll strategy any new topic by means of the lens that works for them, turning what may need been a wrestle right into a pure course of.
When a baby asks, “Why is the sky blue?,” they’re doing one thing highly effective: noticing patterns, questioning what others take with no consideration, and searching for deeper understanding. Youngsters who be taught to ask good questions will direct the world slightly than be directed by it. They’ll know find out how to break huge issues into solvable items—an strategy that works in any area.
3. Attempting, failing, and attempting in another way
When fixing issues, scientists don’t transfer ahead in a straight line. They make guesses, check them, and infrequently uncover they have been mistaken. Then they use that data to make higher guesses. This try-learn-adjust loop is one thing all profitable problem-solvers use, whether or not they’re fixing code or determining life.
When one thing doesn’t work as anticipated—together with an AI-generated reply—youngsters want to determine what went mistaken after which attempt completely different approaches. This implies getting snug with saying issues like “Let me attempt a unique manner” or “That didn’t work as a result of…”
Whether or not they’re troubleshooting a tool or navigating on a regular basis challenges, this mindset helps them strategy issues with confidence slightly than giving up.
4. Seeing the entire image
The most important challenges we at the moment face, from local weather change to healthcare, require understanding how completely different items join and affect one another. This “big-picture pondering” applies equally to on a regular basis conditions, reminiscent of understanding why a classroom will get noisy or why a household price range doesn’t stability.
This mindset is about recognizing patterns and understanding how altering one factor impacts the whole lot else. It helps us anticipate unintended penalties and create options that truly work.
Once we train youngsters to see connections slightly than remoted information, we put together them to sort out issues that AI alone can’t clear up. They change into administrators slightly than followers, capable of mix human wants with technological potentialities.
5. Strolling in others’ sneakers
In my latest op-ed for the Chicago Tribune, I argued that effectivity and empathy aren’t opposing forces. They want one another. This precept is particularly necessary as we elevate the following era.
Know-how with out human understanding results in options that may look good on paper however overlook the true individuals they’re meant to assist. I’ve seen this firsthand in authorities techniques that course of individuals effectively however fail to acknowledge their dignity and distinctive conditions.
Youngsters who develop deep empathy will create applied sciences that actually serve humanity slightly than simply serving statistics. They’ll ask not solely “Can we construct this?” however “Ought to we construct this, and who will it assist or hurt?” They’ll do not forget that behind each knowledge level is a human story, and that probably the most significant improvements are those who strengthen our connections to at least one one other.
The Actual Future: Amplifying Human Creativity
These 5 expertise converge in what I see as probably the most thrilling side of our AI-augmented future: democratized creation. As extra individuals acquire the flexibility to form expertise, even with out conventional coding expertise, we’ll see an explosion of native, purpose-driven options.
As I just lately wrote, I helped put collectively ai/teenagers, the primary world AI convention for and by teenagers. I needed to be taught from the primary AI-native era, which intuitively understands expertise’s potential in methods many adults don’t.
Think about a world the place younger individuals not solely use expertise however actively form it to unravel issues of their communities, designing accessibility instruments for buddies with disabilities, creating platforms that join native sources with those that want them, or constructing academic experiences tailor-made to completely different studying types.
This future isn’t about AI changing human creativity; it’s about amplifying it, making it potential for extra individuals to carry their distinctive views and options to life.
Let’s Construct This Future Collectively!
The great thing about this strategy—specializing in resilience, questioning, adaptation, techniques pondering, and empathy—is that it really works no matter how expertise evolves. Essentially the most technologically superior future nonetheless wants individuals who can embrace challenges, ask significant questions, be taught constantly, see connections, and perceive one another.
In some ways, we’re returning to the best of a classical schooling for the AI age. These expertise kind a contemporary trivium—not grammar, logic, and rhetoric however maybe curiosity, creativity, and compassion—foundational skills that unlock all different studying and doing.
Let’s work on this as a neighborhood! I’m crowdsourcing concepts, actions, and approaches that assist develop these important expertise. What different expertise do you assume we should always concentrate on? I’m wanting to be taught with all of you.