Every few thousand years, humanity figures out a completely new way to learn.

This has nothing to do with a better textbook. It’s not about a new teaching method. Not an updated curriculum framework. It is something more fundamental than any of those.

It’s a shift in the basic infrastructure of how knowledge moves from one human mind to another. A change so deep that it rewrites what learning is, who gets access to it, and what it costs to transmit everything a civilization knows to the generation that will carry it forward.

We are living through the third of these shifts right now (I know, it sounds extreme, but stay with me).

Life 3.0: Being Human in the Age of Artificial Intelligence by Max Tegmark introduces a framework for understanding the evolution of life and the transformative, potentially existential impact of artificial intelligence.

Published all the way back in 2017 before ChatGPT hit the streets, this best-selling book explores how AI could lead to a future where life can design both its own software and hardware.

Tegmark categorizes life into three stages based on its ability to evolve and upgrade: 

• Life 1.0 (Biological): Life where both hardware (body) and software (behaviors/skills) are evolved, not designed. Examples include bacteria.

• Life 2.0 (Cultural): Life whose hardware is evolved, but whose software is largely designed by the life itself. Humans are Life 2.0 because we learn skills, languages, and behaviors during our lifetimes.

• Life 3.0 (Technological): A future form of life that can design not only its software but also its hardware, breaking free from the constraints of biological evolution. This stage does not currently exist but could be created through AI.

There's a fantasy at the heart of modern education (as well as corporate training programs) that if we get the curriculum just right, and the slides polished, the learning objectives crisp enough, learning will seamlessly follow. If you think we can engineer understanding the way we engineer a bridge, or a building, or any physical product…

We can't.

Learning is not a delivery mechanism. It is not something that happens to a person when the right content is transmitted at the right time. It is something that happens inside a person, in ways that are fundamentally beyond any designer's direct control. The best we can do (and it turns out this is quite a lot) is create the conditions in which learning becomes possible, even likely. But we should be humble about the distinction.

For those of you who want to jump right in, I’ve built out a case-study application/website that give you 10 ways to use AI with a purpose for K-12 Data Analysis: https://k12data.replit.app/

We created this site during my recent “AI-Ready School Leaders Certification Program” Cohort using Claude Code and Replit.

In the video below I break down the beginning steps for creating this K-12 Data Analysis Dashboard. One of the areas that we explored in our Cohort was how much time, money, and resources we can save by making custom AI tools. This was just one of those ways that resonated with the Cohort and I wanted to share with all of you.

In an article I wrote a few years ago I shared 10 AI-Resistant Practices for the Classroom. These were simple ways to design learning experiences that prioritize human thinking, discussion, and creation.

But AI-resistant learning isn’t just a reaction to ChatGPT or generative AI.
It’s actually rooted in decades of research about how people learn best.

When you look closely at the science of learning (constructivism, cognitive psychology, and social learning theory) you realize something that most effective learning experiences were already AI-resistant.

They emphasize critical thinking, discussions, experimentation, reflection, and human interaction.

Every teacher has had the moment. You're twelve minutes into a lesson you spent two hours planning, and you can feel the room slipping. Eyes glazing. The same three hands going up. Bodies turning sideways. You have two choices.

You can push through and hope it clicks, or read what's happening and adjust. I spent so many years just pushing through. Mostly because no one taught me what adjusting actually looks like in the moment.

As coaches, we never have that problem. Every coach at every level has a halftime. A built-in pause to look at what's actually happening versus what they planned, and recalibrate.

Teachers don't get a halftime, but we can build one. And the research says it might be the most important skill we’re not developing.

I’ve been coaching HS/MS and Youth athletic teams since 2006. 20 years.

Almost every weekend you’ll find me on a lacrosse field, football field, or basketball court coaching my kids and their teammates.

I love coaching. It’s challenging. It’s rewarding. And it is demanding.

Early on in my coaching career, one of my good friends Steve Mogg (who I taught English with and coached football with) made a comment that still resonates with me today: “Great teaching is like coaching. And great coaches have to teach.”

If you ever been a teacher and a coach, that will make sense immediately. For anyone who hasn’t, let me break it down for you here.

Maybe you’ve heard about Claude. Maybe you are using it.

Or, like millions of others, you haven’t heard of it and it is just another “AI tool” out there that is just like ChatGPT.

In any case, I think it is beneficial for educators who want to use Claude to help their work, and their student’s learning, to have some practical ways to get started.

I recently met with my AI-Ready School Leadership Cohort, and we spent some time discussing the potential of Claude for their work.

In this article I want to break down how to get started with Claude, where you can use it with a purpose, and why I love this as my “everyday AI tool” (and I’m someone who uses them all, or at least tries the majority of tools out there).

Over 7 years ago I first posed this question in a Youtube Video you can watch below. I had recently lost my brother to cancer, and was wrestling with all the ways he impacted my life and changed my mindset on learning and leading. This was pre-pandemic, pre-AI, and so much has changed since then…

Yet, the message has never been more important.

This week an article went extremely viral (millions and millions of views), titled, “Something Big Is Happening”.

Yes, some folks are saying it is an extremist alarm about AI, and others are questioning if it is content marketing disguised as a thought-piece.

But, hidden in this article was a quote that made me think about the difference between Cooks and Chefs, and what we are doing in schools.

The AI debate in schools usually sounds like this:

• “Should we ban AI?”

• “Should we teach kids how to use AI?”

• “Is AI cheating?”

All fine questions.
But they miss the most important one:

Should this task be AI-resistant… or AI-compatible?

Because the truth is complicated. Some learning gets better with AI. Some learning gets worse with AI. And some learning should politely tell AI to wait in the hallway :)

Let’s make this easier (and more fun). First, a brief overview on the reasons for AI-Resistant and AI-Compatible.

Yea, this AI THING is not slowing down any time soon. And YES this means we have to be ever-vigilant when working with AI, when leading in this moment, and thinking about how it will impact our current generation of students.

This is why I’m so passionate about AI-Fluency. And why I released my new AI-Ready School Leadership Certification Program with Maven.

AI-Literacy is a moving target (and a bad target for schools right now). All the things I just listed above happened this week and will impact learning in thousands of ways.

Here’s my issue, and an argument for you as a school leader:

• AI-literacy is an overloaded, still-fuzzy buzzword that risks distracting us from the real literacy crisis (reading, writing, critical comprehension).

• AI-fluency is a better target. Students and educators who can actually work with AI in authentic tasks, grounded in strong foundational literacy.

In a recent essay that's resonating across Silicon Valley, Dion Lim reframes the AI moment not as a bubble but as a wildfire force that doesn't just destroy but fundamentally reshapes ecosystems. His metaphor is simple and powerful: "Wildfires don't just destroy; they're essential to ecosystem health. They clear the dense underbrush that chokes out new growth, return nutrients to the soil, and create the conditions for the next generation of forest to thrive."

Dion founded NextLesson (as well as other companies before it), and I was able to work with him and his team for a few years. I learned a lot from Dion, but especially love his ability to bridge the gap between industries and people.

For K-12 school leaders, Dion’s metaphor isn't just cute, it's prophetic.