We live in a moment of rapid change. Artificial intelligence is no longer the stuff of lab experiments or sci-fi, it’s becoming a tool students (and teachers) use every day, in assignments, research, creativity, and even assessment. As this shift accelerates, one thing has become clear: our greatest advantage is not competing with machines, but doubling down on the human skills needed in an AI driven world.

If your goal is to lead your school toward a future of resilience, relevance, and humanity, then investing in human skills is not optional. In this post, I’ll explore the most critical human skills students, teachers, and school leaders should focus on now, how they complement AI, and practical strategies to embed them into school culture, curriculum, and professional learning.

I covered many of these tools in a free webinar: How To Actually Engage Learners with AI Tools.

At the end of every workshop or talk I give attendees a list of AI resources/tools that I’ve found useful, and that are also being used by teachers and school leaders with upsides beyond “saving time” (which is a nice part of it).

Here are Four MORE AI Tools (You May Not Have Heard About) That Are Helping Teachers Engage right now.

The most engaging learning happens at the edge of comfort. If a task is too easy, students coast in boredom. If it’s too hard, they withdraw in frustration. The sweet spot is where friction sharpens focus. It’s where effort is required, but success still feels possible.

Psychologists call this the “zone of proximal development.” Athletes call it “the edge.” Game designers call it “flow.” Whatever the name, the principle is universal. A challenge can create engagement when it demands just enough effort without crushing your spirit.

You can see this any time you play a video game, or watch students play a game. If a game is too easy, the players become bored and lose interest because there is no sense of growth or achievement. If it's too hard, the repeated failures become frustrating and feel insurmountable, causing players to quit. The 80–85% window is the "sweet spot" that avoids both extremes.

In 1995, science fiction writer Neal Stephenson published The Diamond Age: Or, A Young Lady’s Illustrated Primer.

At the center of the book was something that educators and technologists still obsess over nearly 30 years later: The Primer.

The Primer wasn’t a Kindle. It wasn’t an iPad. It wasn’t even Duolingo with a cuter mascot. It was a living, breathing, adaptive tutor that could tell stories, shift based on a learner’s needs, and guide a child not just in academics, but in life.

Today, the idea feels less like science fiction and more like a roadmap for every edtech startup pitch deck. So let’s talk about why that might be very good, or very bad, for learners.

For years, I thought engagement meant I had to be the entertainer-in-chief of my classroom.

If my students weren’t on the edge of their seats, with wide eyes, and smiling…well, then clearly I was doing something wrong. Right?

So I did what many of us do when we’re young, eager, and maybe just a little desperate. I would put on a show.

I tried so many things. I once taught a lesson in a cape, and no, it wasn’t even a superhero unit. I created elaborate PowerPoints with enough animations to trigger vertigo.

And let’s not even talk about the time I attempted to rap the Preamble to the Constitution. My students are probably still in therapy.

Here’s the thing: all of that got me attention… but not necessarily engagement. They laughed, they clapped, they even told other teachers about it. But did they actually learn? Ehh, not so much. At least not in the way I’d hoped.

Step into any classroom, in any century, and you will find the same invisible battle unfolding: the battle for attention.

The ancient philosopher Socrates, standing in the busy Athenian marketplace, had to cut through the chaos of merchants and politicians to capture the minds of young learners who were eager, while also distracted by the noise of the city. Medieval monks teaching in cold stone cloisters had to fight the monotony of endless recitations and the fatigue of apprentices who rose before dawn. In the early industrial age, teachers stood before rows of children trained to sit in silence, but whose imaginations longed to escape the rigidity of the factory-style classroom.

Every teacher in every age has asked the same unspoken question: How do I make them care?

As my son was getting ready to start Kindergarten, I was a nervous wreck.

Like so many 5-year olds he was a bundle of energy and emotion. Flying high and running low depending on what was happening in any given moment.

He had recently been diagnosed with ADHD and Sensory Processing Disorder, and was doing some PT and OT already through our local service agency.

Yet, that wasn’t what was really getting me all worked up.

You see, I had been working in education for already more than a decade. I’d started out as a middle school and high school teacher but had recently been working as an instructional coach at the Elementary level as well.

Like many of you reading this article, I also saw the K-12 education system up close and personal as a student. Not only my own experience with teachers and the process, but also friends, classmates, and my families own struggles to make sense of their own experience.

After my last article on Relevant Assessments in the AI Age, I received a lot of emails from folks asking what these types of performance tasks might look like in their classroom.

Here are some examples of how relevant, AI-integrated performance tasks might look across K–12. I used ChatGPT and Perplexity to brainstorm ideas, flesh out the assessment focus, and connect to relevant standards. Each task is designed to highlight process, iteration, and authentic application. The goal is for students to use AI as a tool in learning, not a shortcut to avoid the learning.

You’ve probably heard the term performance task before (especially if you are reading this article). If not, you’ve at least seen its cousins: the project, the portfolio, the presentation, or the dreaded poster board.

The performance task was born out of the desire to move beyond rote memorization and regurgitation tests, toward something that would measure deeper levels of learning. Grant Wiggins and Jay McTighe popularized this shift in their work on Understanding by Design, positioning performance tasks as authentic demonstrations of learning where students apply knowledge and skills to real-world problems.

I’ve written extensively about their work, and had McTighe on my podcast to share some of his research and perspective from year’s of shifting towards performance tasks.

The goal was always clear: move away from “telling” and toward “showing.” Students should be able to transfer their learning, not just regurgitate it.

Picture this: a middle schooler writing an essay with the help of an AI-powered tool that suggests sentences. A classroom full of students on learning apps tailored just for them, with algorithms deciding who gets which math problem next. A teacher grading more efficiently thanks to automated assessments. We’re not talking science fiction. This is already happening in schools across the country and around the world.

AI is here, it’s moving fast, and it’s changing the way students learn and teachers teach. At first glance, it might seem like a dream come true to have personalized learning, streamlined workflows, smarter insights into student needs. But as we rush to embrace all these shiny new tools, we need to pause and ask an important question: Are we keeping learning human in a world where machines are doing more and more?

If the answer is going to be yes (and it must be yes) then we need to talk about transparency.

Picture this: A teacher excitedly introduces her class to a new AI-powered writing assistant. Students' eyes light up as they prompt the tool and generate paragraph after paragraph with minimal effort. Within minutes, they've produced essays that would have taken hours to write by hand. The teacher feels proud of embracing innovation, but something gnaws at her as she reviews the work. The writing is polished, yes, but where is the struggle that builds resilience? Where is the messy process of organizing thoughts that develops critical thinking? Where is the learning?

This scenario plays out in classrooms across the country as educators grapple with artificial intelligence's role in education. The question isn't whether AI belongs in our schools (it's already here).

The real question is this: Are we using AI to enhance meaningful learning, or are we letting the tool become the destination instead of the vehicle?

The future belongs to those who can both follow a recipe and invent a new one. Our challenge as educators and parents is to raise students who are grounded in foundational skills but empowered to question, create, and lead. In today’s world, we need learners who can be both cooks and chefs, who know the rules, but also when and how to break them. As I said years ago in our book EMPOWER:

"The problem is that the magic formula doesn’t work anymore, and I’m not sure it ever did... Ultimately we have to ask ourselves... what is the purpose for almost 15,000 hours of instruction and learning time in a school setting from K-12? Do we want to continue producing students who believe their life will be set as a cook? Or who want to live life like as a chef..."

The answer, perhaps, is to help every student become a chef who knows how to cook. To become a creator who understands the fundamentals, but is never afraid to ask, "What if we tried it this way?"