Hi there, it’s Jill!

Since becoming a mother, my sense of time has stretched forward.

In the small pockets of calm between feeds and naps, I find myself wondering about the world my child will grow into. Will the knowledge I’ve accumulated still matter in twenty years? Will schools look anything like they do today? And perhaps most personally: as a parent, how do I continue growing alongside my child in a world that seems to advance faster every year?

This post is my attempt to think through those questions, drawing from what I’ve observed, what I’ve read, and what feels increasingly plausible.

Let’s dive in.

Years ago, I read an interview with Elon Musk, where he described building a school for his children that didn’t group students by age. Instead, students were organized around skills, interests, and projects. Younger and older children can collaborate on problems they genuinely cared about.

At the time, I didn’t fully grasp the idea.

Like many millennials, I grew up inside a very structured system: students sorted by birth year, progress measured through standardized tests, and university admission determined largely by exam scores. Age was treated as a proxy for ability, readiness, and comprehension.

But over the past year, Musk’s vision has begun to feel reasonable.

I’ve repeatedly come across stories of university students, and even middle schoolers using AI tools to build applications that once required years of professional engineering experience. When knowledge becomes instantly accessible, and when AI can patiently explain concepts at any depth, the traditional assumptions about “what a student should be able to learn at a certain age” start to weaken.

I still firmly believe in learning fundamentals before advancing further. Depth matters. Foundations matter. But when learners have access to a well-structured framework, one that AI can dynamically adapt to their pace and gaps, age becomes a much less meaningful constraint.

Of course, this would require a fundamental redesign of schooling. Project-based learning would likely move from the margins to the center. Classrooms would become more heterogeneous, with students bringing very different backgrounds, speeds, and strengths to the same work.

Which raises an important question:
How does teaching change when everyone in the room is learning differently?

In an AI-enabled future, the role of human teachers is unlikely to disappear, but it will evolve.

What remains constant is the teacher’s ability to structure knowledge, frame ideas, and guide understanding. What changes is how students iterate on that understanding.

Imagine this: after a teacher introduces a new concept, each student has access to an AI assistant that can answer questions in real time, re-explain ideas using different analogies, and adjust explanations based on what the student already knows.

This addresses one of the most persistent challenges in education: a single teacher cannot realistically tailor instruction to 30 students simultaneously, each with different learning styles and levels of readiness. AI can step in as a personalized learning companion—available 24/7, endlessly patient and adaptive by design.

This also raises another practical question:
Does a class still need to be 45 minutes long?

Perhaps not.

A future classroom might look more like:

This structure could increase learning efficiency while freeing teachers to focus on higher-leverage work: designing projects, asking better questions, and supporting students intellectually and socially.

Recently, I learned that Stanford released a full series of courses on Large Language Models online, and it’s free.

What once required admission to an elite institution is now accessible to anyone with an internet connection.

If knowledge is everywhere, does it still matter where you study?

My answer is still: yes, absolutely.

The greatest value of a strong university education has never been the lectures alone.
It’s the people you grow alongside.

In a world where AI can help you learn almost anything, human relationships become even more valuable:

AI can accelerate learning. But it cannot replace trust, shared struggle, or long-term relationships.

NVIDIA CEO Jensen Huang once said that people who are genuinely talented, intellectually curious, hardworking, and act with integrity will succeed, without exception.

I agree. And if I had to distill it further, I’d highlight three traits:

Curiosity
The ability to ask better questions and genuinely want to understand how the world works.

High agency
The willingness to take responsibility for one’s learning, to seek answers, experiment, and adapt when the rules change.

Integrity
Using knowledge and tools to create real value, not shortcuts.

The students who thrive won’t necessarily be the ones who know the most today, but the ones who can learn continuously, apply knowledge thoughtfully, and stay grounded in purpose.

Becoming a parent has changed how I think about the future.

I no longer ask only, “How do I stay relevant?”
I also ask, “How do I grow alongside my child in a world that keeps accelerating?”

AI will continue to reshape how we learn. For students, and for all of us, the most important skill may not be mastering any single tool.

It may be learning how to learn, again and again.

— Jill

Founder of Anchor Growth Newsletter

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