Feeds:
Posts
Comments

I have been thinking a lot about assistance lately. Who gets it, who does not, and why we suddenly get moralistic about it the moment the assistance comes from AI.

The spark for this post is Nick Potkalitsky’s Substack essay, “In Praise of Assistance.” It is one of those pieces that does not just add to the AI and writing conversation. It reframes it (Thanks to Adam Garry for pointing me towards it).

Nick starts from the now familiar worry about “cognitive offloading,” students delegating the thinking to a tool, and he agrees the concern is real. But then he names what often sits underneath the concern: not just pedagogy, but ideology.

He argues that the cognitive offloading critique rests on “a historical fiction: the autonomous learner.” Because if we are honest, most of us did not learn to write (or think, or revise) alone.

My own invisible advantage

In high school, I had a huge advantage: my dad was an English teacher, and he read every essay before I submitted it. Not just English essays. All of them, across every subject.

He did not write my essays. But he did what good teachers do. He asked questions I had not thought to ask. He pointed out where my logic sagged. He helped me tighten sentences. He coached me toward clarity.

That continued through university. And years later, when I became a newspaper columnist, he was still my first reader. Every column went to him before it went to my editor. He would call with suggestions, and I would decide what to keep and what to let go.

At the time, nobody called this cheating. We called it support. Nick puts it simply: “Students have always learned through assistance. From peers, from teachers, from resources…” 

We rarely worry students are “offloading” onto classmates in a discussion. We celebrate it. But when AI enters the picture, suddenly assistance becomes suspect.

That is the tension.

The question is not “help or no help”

When we talk about AI and writing, the debate often collapses into a binary: real writing (alone, unaided) versus fake writing (assisted, scaffolded).

But that binary does not match how writing actually works. It does not match how learning has actually  ever worked.

The better question is the one Nick keeps pointing us toward: what kind of assistance builds thinking, rather than replacing it?

That is where his essay becomes more than a defense of AI. It is a critique of an unspoken standard that has been unevenly distributed for a long time. The idea that “authentic struggle” is the price of admission to learning.

Nick names the class based reality bluntly: affluent students often have “small seminars, writing conferences, office hours, peer review sessions” while others are in systems where meaningful feedback barely exists. And then comes the sentence: “The outcome depends on whether we recognize assistance for what it is: not a threat to learning, but its precondition.”

What I have been writing toward

In October, I wrote “Modeling AI for Authentic Writing.”  If AI is here (it is), then our job is to model the kind of use that keeps the writer in control. In that post, I tried to move the conversation from “Don’t use AI” to “Show your decisions.”

Because the heart of authentic writing is not whether you had help. It is whether your thinking is present. What did you accept? What did you reject? Why? What did you learn in the revision?

I wrote then: “None of this replaces judgment. I accept or reject every change.”

For years, Tricia Buckley, and before her Sharon Pierce and Deb Podurgiel, have played a similar role here on this blog, reading every post before publication and offering feedback. The byline is still mine because the ideas, voice, and final choices are mine.

That is the point.

Assistance is not the enemy of learning. Abdication is.

What I want to add

There is a system design question underneath that I keep circling back to.

If we accept that all learning has always been assisted, what changes about how we run schools?

A few weeks ago I wrote about the tutoring revolution and found myself wrestling with a similar tension. For years, success in certain courses quietly required something extra: a tutor. Parents traded recommendations, students admitted they needed help, and the whole system ran on an unspoken understanding that school alone was not enough. At least not for everyone.

AI is changing that. But here is the part that worries me: the digital divide is no longer just about device access. It is about knowing how to use the tool well. A student with strong digital literacy might turn ChatGPT into a Socratic tutor. Another might never get past using it as a homework completion machine.

Nick writes about elite students who have always had access to “assistance made flesh.” The risk now is that we create a new version of the same divide. Some students learn to collaborate with AI in ways that deepen their thinking. Others use it to bypass thinking altogether. And if we are not intentional, digital confidence becomes the new proxy for privilege.

The question is not whether students will have AI assistance. They already do. The question is whether we will teach them to use it in ways that build capacity or let the gap widen on its own.

A Culture of Yes stance

A Culture of Yes does not mean saying yes to every tool or every shortcut.

It means saying yes to the conditions that help more people learn well.

So here is where I am landing, at least today.

Writing has always been assisted. The myth of the autonomous writer has always favoured students with the most support. AI can absolutely be used to bypass thinking. But it can also be used to invite thinking, especially where feedback is scarce.

Our job is to design and model practices where assistance makes thinking visible and growth possible.

Nick’s essay refuses the easy frame. It asks us to stop policing help and start building learning communities where help is normal, explicit, teachable, and more equitably available.

That feels like the kind of “yes” worth defending.

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking.

This marks the 11th year of my One Word tradition. Eleven years. When I started this practice back in 2016, I was 42 years old and hungry. Literally, that was my word. Hungry. I wanted to compete, to stay curious, to keep pushing. And here I am, a decade later, still hungry but now asking different questions about what that means.

Before I get to 2026, let me say this about 2025 and “Thrive.” It delivered. In a year where it would have been easy to retreat into cynicism or exhaustion, I chose to flourish instead. I wrote more than I have in years, and it never felt like a chore. I ran every single day. I spent my summer coaching basketball with young athletes who remind me why I do this work. I leaned into AI not as a threat but as an invitation to rethink learning. I found great satisfaction in work and with those I work with.   Thrive was about sustaining momentum and finding joy in that momentum. It worked.

So what comes next?

This word is not about doing more. It is about feeling more, without losing momentum.

My word for 2026 is Alive.

Why Alive?

I turn 53 this year. Regular readers know I feel my age more than ever (I keep bringing it up), and I mean that in both the best and most humbling ways. There are strands of grey in my hair that were not there five years ago. My recovery from long runs takes longer than it used to. I notice things now that I never noticed before: the way my knees feel on cold mornings, the reading glasses I now keep in three different places, the names that take an extra second (or sometimes minute) to retrieve.

And yet.

I am not checking out. My body may be changing, but my commitment to showing up has not. My run streak will cross 2,000 days in 2026. I will keep coaching. I will keep writing. I will keep appearing in classrooms and  conference rooms with intention and energy, even when generating that energy requires more deliberate effort than it used to.

A friend of mine, Anthony, texted me recently. He is not in education; he is a successful entrepreneur. His message was simple: “Call me.” He does that sometimes. When I did, he started right in. “You know what makes us different? No matter what happens today, we show up tomorrow and attack the day. We don’t get stuck in what happened. We just keep moving forward.”

That is what Alive means to me. Not ignoring the hard stuff. Not pretending the grey hair and the sore knees do not exist. But choosing, every single day, to show up and engage anyway.

Alive is my answer to a world that feels increasingly numb. In a time filled with cynics and critics, with doom-scrolling and disengagement, I am choosing to stay fully present. To feel things. To remain curious when it would be easier to become jaded. To stay optimistic when pessimism seems more sophisticated.

Being alive means more than existing. It means showing up with your whole self, not some protected, half version. It means being willing to be changed by what you encounter.

Building on a Decade of Words

When I look back at my words over the past decade, I see a story. Each word was right for its moment, and together they form something larger than any single year.

The early years were about drive: Hungry (2016), Hope (2017), Relevance (2018), Delight (2019).

The middle years were about resilience: Hustle (2020), Optimism (2021), Focus (2022), Coached (2023).

The recent years have been about integration: Accelerate (2024), Thrive (2025).

And now, 2026: Alive.

Alive feels like a synthesis of all of it. You cannot be truly alive without hunger and hope. You cannot be alive without relevance and delight. You cannot be alive without focus and the willingness to be coached. Being alive requires both acceleration and the wisdom to know what thriving actually looks like.

Alive in a Changing World

We are living through one of the most significant shifts in how humans learn and work. AI is not coming; it is here. And I want to be fully alive to what that means, not as a passive observer but as an active participant shaping how we integrate these tools in our schools.

But here is what I keep coming back to:

The more powerful the technology becomes, the more important the human elements are.

Connection. Curiosity. Creativity. Compassion. These are not things AI can replicate. They are the things that make us alive.

In 2026, I want to be alive to both realities. I want to keep exploring what AI can do for learning while never losing sight of what only humans can do for each other. I want to be in classrooms watching teachers and students navigate this new landscape together. I want to ask good questions and resist easy answers. I want to model what it looks like to embrace change without abandoning what matters most.

Alive in Body and Relationship

For me, being alive has always been connected to physical movement. My run streak is not about athletic achievement. It is about presence. Every morning when I lace up my shoes and step outside, I am choosing to be alive to that day. Rain or shine, tired or energized, home or traveling. The streak is a daily declaration: I am here. I am engaged.

In 2026, I will keep running. I will keep coaching basketball. I will keep prioritizing the habits that have carried me this far: 10,000 steps, daily movement, attention to what I put in my body (OK – this last one needs to be better).

But being alive is also about the people around me. My family. My colleagues. The educators I work alongside. Relationships require the same consistency as run streaks. You show up. You do the work. You stay curious about the people next to you, even when you think you know them completely.

Alive and Hopeful

I know the world can feel heavy right now. There is no shortage of reasons to disengage, to protect yourself, to lower your expectations. Cynicism is easy. Hope is harder.

But I keep choosing hope. Not naive hope that ignores reality, but stubborn hope that insists on possibility anyway. Hope that believes education can be better. Hope that trusts young people to rise to challenges we cannot yet imagine. Hope that sees AI as a tool for human flourishing rather than replacement.

Being alive means staying open to wonder. It means maintaining the curiosity that has driven my career and my writing. It means refusing to let age or experience calcify into certainty. The older I get, the more I realize how much I do not know. And that feels like a gift, not a limitation.

All In

So yes, I may be greyer. I may be slower in some ways. But I am all in on 2026.

All in on learning.
All in on family.
All in on health.
All in on this beautiful, complicated, rapidly changing world.

Alive is not a passive state. It is a choice, made daily, sometimes hourly. It is the choice to engage rather than withdraw. To feel rather than numb. To hope rather than despair. To keep saying yes.

That is the Culture of Yes I have been writing about for 16 years now. And it turns out, it has always been about being fully, stubbornly, joyfully alive.

What word will guide your 2026?

And want a second opinion on picking a word,  here is what Daniel Pink said this week about the power of the one word process.  


Previous One Word Posts:

2016: Hungry

2017: Hope

2018: Relevance

2019: Delight

2020: Hustle

2021: Optimism

2022: Focus

2023: Coached

2024: Accelerate

2025: Thrive

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking.

Here we are again. A final post for calendar year 16 on Culture of Yes.

As I close out another year, I find myself in an unexpected place. This was the easiest year of writing in the 16 years I’ve been doing this. Not because the topics were simple or the world less complicated, but because I found myself needing to write. It never felt like a chore. In a year where it would be easy to drown in bad news and uncertainty, I chose optimism. I chose curiosity. I chose to keep saying yes. And if I go back to my word for the year – I chose to thrive.

If you are wondering what you might have missed, here are the previous years Top 3 lists: 2024 (here) 2023 (here) 2022 (here) 2021 (here) 2020 (here) 2019 (here) 2018 (here) 2017 (here) 2016 (here) 2015 (here) 2014 (here) 2013 (here) 2012 (here), 2011 (here) and 2010 (here)

You know the format by now. Grab your beverage of choice and join me as I look back on what made 2025 special.

Top 3 “Culture of Yes” Blog Posts which have generated the most traffic this year:

These three posts represent so much of what I think about in my work. All Means All is at the core of everything we do in West Vancouver. It is not a slogan; it is a commitment. The graduation post has become a fairly regular share, and it forces me to think about what really matters for young people heading out into the world. And the AI post speaks to a tension I keep exploring: how technology might actually help us be more human, not less. I wrote a lot on AI this year, and it was interesting to see the most popular post was one about AI leading to less technology use.

Top 3 Blog Posts That Were My Personal Favourites:

The posts that mean the most to me are often the more personal ones. Writing about Paul Simon let me explore a relationship with music that has spanned more than 40 years. The mentors piece was hard to write but necessary as I am beginning to feel my age in this work. And the Blue Jays post reminded me why I love using sports as a lens to think about learning and life. That was quite the run for the Jays!

Top 3 Shifts in BC Education in 2025:

  • The focus on 0 to 5 and the ongoing integration of childcare and K-12 as one system
  • A renewed emphasis on early literacy and knowing where our young learners are so we can adjust quickly and nimbly
  • A steadiness that allowed the work to get done

I want to dwell on that third one for a moment. There was not a lot of drama in BC education this year. And that is a good thing. When the system is steady, educators can focus on what matters most: the students in front of them. I look at other jurisdictions across North America and they seem constantly distracted from the business of learning. Steadiness does not make headlines, but it makes a difference.

Top 3 Questions I’m Carrying Into 2026:

  • What do we need to stop doing so we can focus on what truly matters?
  • How do we prepare students for an AI-shaped future without losing our humanity?
  • What does leadership look like when certainty is no longer available?

As I wrote in my June post on the power of questions (here), I’m increasingly convinced that progress in education doesn’t come from having better answers, but from asking better questions. These three will quietly shape my thinking, decisions, and conversations as I step into 2026.

Top 3 Things I Was Wrong About:

  • I thought ethical discussions on AI would be more mainstream by now
  • I never thought Canada would come down with Blue Jays fever
  • I did not see my own writing renaissance coming

On AI ethics, I expected 2025 to be the year we would see more public conversation about the big questions. What does this mean for work? For creativity? For what it means to be human? Those conversations are happening, but not at the scale I anticipated. Maybe 2026.

The Blue Jays World Series excitement this year caught me completely off guard. I wrote about it, and it connected with people in ways I did not expect. There is something about baseball that still captures the imagination.

And the writing renaissance? I genuinely did not see it coming. After nearly 500 posts, I thought the well might be running dry. Instead, this year I found more to say than ever. I needed to write. That was a gift.

Top 3 Things I Am Getting Worse At As I Age:

  • Public speaking
  • Seeing stuff
  • Connecting with new staff

This is a new category, and I think an important one. Humility matters.

Public speaking used to feel effortless. Now I feel the rust. I am not as smooth as I was 20 years ago, and I notice it.  I am conscious now that I am not as good as I once was.  My glasses have become a constant companion, though I am still fighting that battle.  Far too often I am using my phone to take a photo of text to enlarge and read.   And connecting with new teachers who are younger than my own children? I can feel my age in those conversations sometimes. It takes more intentionality than it used to. Speaking and connecting are definitely two areas I can work on in 2026.

Top 3 AI Tools for Education (The Migration to the Big Players):

  • ChatGPT
  • Claude
  • Gemini and CoPilot (tied for third)

Last year I wrote about niche AI tools. This year I find myself using fewer specialized tools and relying more on the big players. Co-Pilot, Claude, Gemini, and ChatGPT have become my core toolkit. They are more powerful, more integrated, and constantly improving. The niche tools still have their place, but the migration to the majors has been real for me this year.

Top 3 Presentations That Pushed My Thinking:

  • Speaking to teachers in Beijing
  • Sharing AI thinking with Safe Schools Coordinators
  • Let’s Talk Science

The Beijing presentation stays with me. Their issues are our issues. The questions teachers ask in China about AI, about engagement, about preparing students for an uncertain future are the same questions we wrestle with here. It was a powerful reminder that education’s challenges are global.

Safe Schools Coordinators pushed me to see AI from a different perspective. When you talk about AI with people focused on safety, you think differently about risks and responsibilities.

And my Let’s Talk Science presentation late in the year forced me to take stock of where West Vancouver is right now. Sometimes you need an external audience to clarify your own thinking.

Top 3 Authors Who Pushed My Thinking in 2025:

  • Yong Zhao
  • Peter Diamandis
  • Adam Grant 

Yong Zhao continues to challenge my assumptions about what education could be. I got a look at a new book (here) he has coming out in 2026, and he is pushing again!  Peter Diamandis (here) got me thinking about longevity, which connects to so much of how I approach my own health and habits. And Adam Grant? He pushes my thinking (here) even when I push back. That is what good authors do.

Top 3 AI Connections I Always Recommend:

If you want to follow smart people thinking carefully about AI in education, start with these four. They are generous with their ideas and always worth reading.

Top 3 Blogs I Never Miss (Even After All These Years):

The edu blogosphere is not what it was in 2011 to 2014, but these passionate educators keep writing, and I keep reading. There is something to be said for people who have been at this for years and still find things worth saying. They inspire me to keep going. 

Top 3 Concerts I Saw This Year:

  • Paul Simon (multiple locations)
  • Andy Grammer
  • AC/DC

Paul Simon is not really retired yet, and I am grateful for every chance to see him. I have written about what his music means to me, and those concerts remain a highlight of any year. Andy Grammer brought pure joy. And AC/DC? Sometimes you just need to rock.

Top 3 Travel Moments of the Year:

  • 25th Wedding Anniversary at Niagara Falls
  • Running the 45th Anniversary Terry Fox Run on Confederation Bridge with my two sons
  • The VK Basketball Summer Circuit (Phoenix, LA, Montreal, Las Vegas, Chicago)

Yes, Niagara Falls for a 25th anniversary is a cliché. I do not care. It was great.

The Terry Fox Run from New Brunswick to PEI with 10,000 people on the Confederation Bridge with my sons will stay with me forever. There is something about running alongside your children for a cause that matters that defies easy description.

And the VK Basketball Circuit hit year 10 this summer. Phoenix, LA, Montreal, Las Vegas, Chicago. One more summer left with a playing age daughter. I am not taking it for granted. For the last 10 years I have spent my summers with amazing young athletes and coaches who are some of my very best friends.  It is so much fun!

Top 3 Social Media Follows That Keep Me Focused:

These three help me stay disciplined. Discipline is key. In a world of endless distraction, I need voices that remind me to do the work.

Top 3 Things I Tried To Do More Of This Year:

  • Say no to stuff that was not something I was passionate about
  • Say yes to AI and athletics, two areas where I think I can really add value
  • Be a better mentor and reach out more to colleagues I think I can assist

Saying no is hard for someone who writes a blog called Culture of Yes. But saying no to the wrong things creates space to say yes to the right ones. I need to still cull some things I do from my professional life that are time and energy drags and add little value.   AI and athletics are where I can contribute most right now. And mentorship? I want to be for others what my mentors were for me.

Top 3 Daily Streaks I Still Have Going:

  • Running 5 outdoor km a day (just passed 1,800 days, looking forward to 2,000 on July 9, 2026)
  • 10,000 steps a day (now at 12 years)
  • Daily photo posting to Instagram (January 1st will be 10 years)

The streaks continue. They are about discipline and consistency, qualities I believe are in short supply and more important than ever. The running streak crossing 1,800 days feels significant. 2,000 is on the horizon.

Top 3 Artists for Me According to Spotify This Year:

  • Paul Simon
  • Simon and Garfunkel
  • The Beatles

Not much to see here. For all the things that change in the world, my music tastes are not one of them. I am still my parents’ musical loves.  Spotify gives you an age based on my music – I came in at 73 years old.

Top 3 Photos From This Past Year That Make Me Smile:

With Nick and Zack on the Confederation Bridge

Paul Simon at the Massey Hall in Toronto

Learning alongside K students at West Bay Elementary School

I could easily pick so many others. I love going through my photos from each day to look back on the year. A collection of work, family, and friends. Scrolling through them will always make me smile.

Final Thoughts

As I wrap up my reflections on 2025, I keep coming back to the word that has guided this blog from the beginning: yes.

Yes to curiosity. Yes to optimism. Yes to the belief that education can be better and that the people in it are working hard to make it so.

This year brought me a writing renaissance I did not expect. It reminded me that even after 30 years in education, there is still so much to learn, so much to say, and so much to be excited about.

Early in the new year, I will hit a milestone: 500 posts on Culture of Yes. I did not know when I started this blog that it would become such a constant in my life. But here we are, and I am grateful.

To all of you who have read, shared, and engaged with these posts throughout the year: thank you. Your reflections, challenges, and encouragement fuel my writing and inspire my thinking.

Here is to stepping into 2026 with the same energy, passion, and hope that have carried us through this year. Here is to staying curious as I finish my 30th year in education.

Happy holidays, and see you in the new year.

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking.

For years, there has been a quiet understanding in many high schools that success in certain courses, especially senior math and sciences, required something extra. Not more effort or better attendance, but a tutor. Parents would trade recommendations, students would quietly admit they needed one, and tutoring centres would advertise that “everyone needs help.” In some, especially affluent communities, paid tutors became part of the culture, almost an unspoken prerequisite to keeping up.

That world may be coming to an end.

AI has entered the tutoring business, and it does not take nights or weekends off. For the first time, students have access to personalized, immediate feedback and explanations any time they need it. They can ask follow up questions without embarrassment, get alternative explanations and have complex problems broken into smaller steps. All of this is available for free, or for the price of a phone app. The model that tutoring companies built around scarcity and exclusivity is being replaced by abundance and accessibility.

It is not only about convenience. Tools like ChatGPT, Claude, and Magic School AI can act as math coaches, writing mentors and language partners. They remember the work, adapt to a student’s level, and adjust explanations when the learner gets stuck. The value proposition that human tutors once held, personalization, is becoming a default feature of modern AI systems.

Just last week, one of our Grade 12 students shared how she had been struggling with integration by parts in calculus. Instead of waiting for a weekly tutoring session, she worked through problems with an AI tutor at 11 p.m., asking it to explain the same concept three different ways until it clicked. “It never got frustrated when I asked the same question again,” she said. “And I could be honest about what I did not understand.”

When I first started drafting this piece, I was ready to declare the end of the tutoring era. The evidence seemed clear. The assumption that you need a tutor to survive Pre Calculus is being upended. For many students, the AI sitting quietly on their laptop or phone now fills that role, often better and more patiently than the Saturday morning sessions they once dreaded.

Then I started reading the research. And my thinking got more complicated.

What the Research Actually Shows

The October 2025 edition of AASA’s School Administrator magazine dedicates significant space to the state of tutoring in American schools. AASA is an American based organization, but the questions it raises cross borders easily. The tension between equitable access and quality instruction, the challenge of sustaining initiatives beyond initial funding, the promise and limits of technology in supporting learners: these are Canadian conversations too. The research may come from Texas and Massachusetts, but it speaks directly to what we are wrestling with in British Columbia and across the country.

Liz Cohen, in her article drawing from her book The Future of Tutoring: Lessons from 10,000 School District Tutoring Initiatives, documents an unprecedented expansion. Within a year of the pandemic’s onset, 10,000 U.S. school districts were offering some form of tutoring after years of almost none. By May 2024, 46 percent of public schools reported providing high dosage tutoring, and just 13 percent said they offered no tutoring at all.

Research from the Johns Hopkins Center for Research and Reform in Education, featured in this issue, offers evidence that virtual tutoring with human tutors can produce meaningful results. Grade one students assigned to Air Reading, a structured virtual tutoring program, four times a week for a semester gained nearly 1.6 additional months of learning. Those who attended at least 40 sessions saw even greater progress.

But here is the tension that caught my attention: the research consistently shows that the most effective tutoring models still rely on human tutors. Studies on AI tutoring directly with students remain in early stages, and even the most promising work positions AI as supporting human tutors rather than replacing them

I had to sit with that for a while.

The Hybrid That Works

One case study which helped my framing was learning about the work happening in Ector County ISD in Texas. In partnership with Stanford University, they developed something called Tutor CoPilot. It uses AI not to tutor students directly, but to coach human tutors in real time, suggesting questions to ask, concepts to revisit, hints to offer.

The results are striking: students whose tutors used the AI prompts scored 14 percentage points higher than those whose tutors did not. The AI shifted tutors toward stronger pedagogy, guiding student thinking rather than simply giving away answers. And here is the part that matters most for equity: the greatest benefits went to less experienced tutors. The tool essentially democratized tutoring quality, helping novice tutors perform nearly as well as veterans.

This is not AI replacing humans. This is AI and humans amplifying each other.

What AI Cannot Yet Do

Cohen’s research surfaces something that pure AI cannot yet replicate. The success of tutoring, she argues, is deeply rooted in human relationships. It helps young people feel they matter. It builds motivation through productive struggle in a high support, high standards environment Cohen (This podcast is also a good background on Cohen’s work).

There will still be families who seek human tutors, especially for accountability or emotional connection. Some students need the structure of showing up, the social pressure of not wanting to disappoint someone, or simply the reassurance of a person saying “you’ve got this.” AI has not yet mastered the art of knowing when a student needs a break, a pep talk, or someone to believe in them.

The question is whether it will, and how soon.

The New Digital Divide

For schools, this raises urgent questions. Do we teach students how to use AI tutors effectively? How do we ensure that all students, not only the digitally confident, benefit from these new tools?

The digital divide is no longer just about device access. It is also about knowing how to prompt effectively, when to question an AI response, and how to use these tools for learning rather than answer getting. A student with strong digital literacy might turn ChatGPT into a Socratic tutor. Another might never get past using it as a homework completion machine. If we are not careful, digital confidence becomes the new proxy for privilege, only with different packaging.

There is another issue to face. If every student has a tutor at all hours, what does authentic assessment look like? How do we measure understanding when the line between getting help and getting answers is blurred? This is not a reason to resist change. It is a reason to rethink what we are measuring and why.

What I Got Wrong, and What I Got Right

The shift is cultural as much as it is technological. For years, tutoring companies helped reinforce the idea that school alone was not enough. Now, AI is challenging that notion and putting powerful learning tools directly in the hands of students. I was right about that.

But the real revolution may not be the end of tutoring. It may be its transformation.

This changes the teacher’s role as well. When information delivery and step by step support are available on demand, teachers become something more valuable. They become learning architects who design rich tasks. They become coaches who know when to push and when to support. They become mentors who help students navigate not only content, but the process of learning itself. The human element does not disappear. It becomes more essential, only with a different focus.

We may soon look back on the tutoring era the way we look at encyclopedias and phone books. Useful for their time, but unnecessary once the world changed. Or we may find that the future looks more like Ector County: AI and humans working together, each amplifying what the other does best.

Maybe what we should have wanted all along was not a system where extra help was a luxury, but one where every student has access to the support they need, when they need it, in the form that works best for them. Whether that form is human, AI, or some combination we have not yet imagined.

The question is not whether this change is coming. The question is whether we will shape it with intention, or let it happen to us.

Thanks to Liz Hill and Andrew Holland with whom I had recent conversations that helped inspire this post.

 

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking

There is a shift happening in our schools, and you can feel it.

You see it in the staffroom, in the parking lot, in the subtle ways younger teachers talk about their work. They draw clearer lines between school and home, speaking about boundaries and balance with an ease that still makes some of us older educators pause.

This is not about fault or nostalgia or about who is right and who is wrong. It is about understanding what is changing, what matters most and what might be at risk.

And I will admit it. Sometimes I catch myself thinking, when I started, that is not how it worked. I remember the pride I felt walking to my car after dark, convinced that more hours meant more impact.

But I am not advocating for a return to unhealthy expectations or performative exhaustion. That model burned plenty of people out. What I am wrestling with is simpler. Schools run on human connection, and connection takes time.

The Side Hustle Conversation

Last week, a teacher told me about a small online business they run in the evenings. They spoke with real enthusiasm about the creativity it offers, the extra income and the sense of fulfillment it brings.

My first instinct was to wonder why not channel that energy into coaching a team or running a club.

But then they said something that stayed with me. “This way, I can give my best to my students during the day and still have something that is mine.”

At a recent meeting, a principal named something many of us have quietly noticed. “Culture is built in the building, so if you are racing out at three o’clock, you are not part of it.”

That line lands differently depending on who hears it, but it surfaces an important truth about how culture actually forms.

School culture has always lived in the informal moments. The spontaneous problem solving. The hallway conversations. The shared laughs. The collective exhaustion that somehow turns into shared purpose. When more teachers leave the building right at dismissal, focused on side businesses or evening commitments, what happens to the culture we spent decades building?

And yet, I need to say this clearly.

I know phenomenal early career teachers who are all in. They coach, advise clubs, run events and show up for everything. They remind me that this is not simply generational. It is cultural, contextual and deeply personal.

A Continental Conversation

Across North America, the story feels remarkably consistent.

A superintendent in Ontario tells me it is getting harder to find coaches. A principal in Oregon now hires community members to run the drama program. A colleague in Manitoba describes newer teachers with firm boundaries and veteran teachers carrying more extracurricular load.  This is not a West Vancouver story. It is a profession-wide renegotiation of expectations.

The Apprenticeship Question

Gary Vaynerchuk once said, “If I told you that in fifteen years you would have the perfect life, and all you had to do was work fifteen hours a day for the next ten years, all of you would do it.”

When I think about teaching, it resonates.

Those of us who put in sixty or seventy hour weeks early on were not just completing tasks. We were learning.

Every basketball practice taught me about motivation.
Every extra help study session revealed different dimensions of students.
Every late night planning session became an impromptu masterclass.

And here is where it becomes complicated.

I see early career teachers embracing this model as well. They coach, volunteer and pour themselves into the work. But many of them tell me they feel alone in this approach, swimming against colleagues who view the profession through a different lens.

The Core Question

The question I keep circling back to is this.

If school culture is built in the cracks of the day, what happens when fewer people are in those cracks?

A New Definition of Commitment

These teachers came of age during a different time. COVID did not reshape schooling in the same way it reshaped other sectors, but it reshaped the idea of sustainable work.

Many began their careers when health, boundaries and flexibility were survival strategies. They do not equate hours with impact. They believe good teaching comes from energy and authenticity, not exhaustion.

And boundaries existed twenty years ago as well. The difference now is scale and norm.

Research reinforces this shift. Early career teachers report high stress but also strong boundary setting and wellbeing strategies. Across professions, work life balance has become a top factor when choosing an employer.

Still, I wonder.

When a teacher has a thriving side business, is it smart financial planning or divided attention? When professional development sessions are filled mainly with administrators and not teachers, what does that say about our shared investment in growth.

The Extracurricular Equation

Across districts, extracurricular programs increasingly rely on veteran teachers, administrators and community members. To be fair, many early career teachers are coaching teams, running robotics clubs and leading social justice initiatives. They challenge the stereotype.

But the broader trend is difficult to ignore.

Digital mentoring and global collaboration fill some gaps through Pinterest, TikTok, Instagram and AI tools. A week of differentiated materials can be created in minutes. But learning from the teacher down the hall, seeing how they run a class or recover from mistakes, cannot be replaced by an algorithm. When professional learning becomes screen based and individualized, do we lose the wisdom that has always defined strong schools.

I cannot shake the feeling that something special happens in those after school hours.

Quiet students find their voice on the debate team. Students who struggle academically become leaders on the basketball court. Conversations on the bus ride home from a tournament sometimes matter more than any lesson.

The Community Contract

As a parent of four, I know this from another angle.

My kids grew because other teachers gave their evenings to them. Student council advisers. Coaches. Club sponsors. Teachers who ran practices before sunrise.

One teacher spent every weekend in the gym running basketball practice. My daughter still talks about her years later.

This has always been the unwritten contract of a strong school community.
We support each other’s children.

And that contract has always run on goodwill, extra time and a belief that teaching extends beyond the bell.

As parents, we want our children to be taught well — but we also want them to be known, coached, mentored and challenged. Those moments often happen after 3 pm and we can’t afford to lose them.

The world has changed. We now tell people their time has value, that boundaries are healthy and that self care is not selfish. The tension between those messages and the long standing tradition of teacher volunteerism is real and growing.

The Global Staffroom

Early career teachers build their practice differently. They have always had a global staffroom in their pocket. It is efficient and sparks creativity. But when I see a teacher scrolling TikTok for classroom management tips instead of walking down the hall to ask a colleague, I wonder what context is being lost.

Algorithms cannot know your students. They cannot know your school. They cannot know you.

And yet, many teachers blend both worlds well, learning from colleagues while tapping global resources. The best teachers use technology as an addition, not a replacement.

I watched a new teacher use an AI tool to create differentiated materials for three learning levels, then spend the time she saved having one to one conversations with struggling students. Different method, same heart.

Efficiency is not the enemy. Disconnection is.

Meeting in the Middle

Leadership today means navigating these tensions thoughtfully. It means asking questions like these.

  • How do we honour both the teachers who give their evenings and those who protect them?
  • What structures create sustainability without eroding community?
  • How do we preserve what matters while adapting to what is changing?
  • How do we avoid romanticizing the past while still naming real losses?

We also need to acknowledge the realities many newer teachers face. Housing costs and student debt make side hustles less of a choice and more of a necessity.

The truth is that we probably need both approaches.

Perhaps the healthiest schools will have a mix. Enough builders to sustain the culture. Enough boundaried teachers to model sustainability.

But balance requires intention. It requires honesty about what we value, what we are willing to compensate and what we can no longer expect from goodwill alone.

So here is the forward looking question I cannot shake. If we want to keep the community building work that has always relied on volunteer time, what would it look like to value it differently? To structure it. To support it.

Supporting All Teachers

My inbox tells a story. Workshops on boundaries, resilience and wellbeing. What once felt indulgent now feels essential.

Veteran teachers are setting boundaries too. They are exploring passions outside of school and saying no to committees they once would have led. Perhaps we are all rethinking what a sustainable career looks like.

Maybe this new balance is healthier. Maybe the old model looked noble while quietly burning people out.

A Final Reflection

Every profession undergoes generational renegotiation. Teaching is simply facing its moment now.

After nearly thirty years, I know that some of my most meaningful work happened after hours.

  • The student who finally opened up during an evening study session.
  • The colleague who became a mentor at six o’clock at night.
  • The breakthrough that came not in a meeting but in a tired conversation after the building emptied.

Maybe this new generation will show that clearer boundaries can produce longevity and great teaching. Maybe they will prove that sustainability creates impact. Or maybe we will discover that something essential is lost when fewer people stay for the unscripted moments.

What worries me is not the change itself but our reluctance to name what it might cost.
If we cannot talk honestly about tradeoffs, we cannot choose intentionally what to preserve and what to evolve.

I am trying to stay curious rather than critical.

The question is not whether boundaries are right or wrong. It is whether we are clear eyed about what we gain and what we give up. Because education has always been about more than what happens between the bells. It has always been about what happens between people. And people need time together to become a community.

The profession is changing. The building feels different than it did twenty years ago. Whether that difference strengthens or diminishes what we do remains an open question.

Maybe the next step is simply conversation. A staffroom conversation. A parent conversation. A leadership conversation.

If we want to protect what is best about our schools, we need to talk honestly about what we want to keep, what we can rethink and how we can support the people who make it all possible.

What I know for certain is that great teaching, in whatever shape it takes, still changes lives. And that is the part worth protecting.

 

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking.

Last week, I sat in an education conference listening to a keynote speaker who was absolutely unequivocal about it: students must learn prompt engineering or they will be left behind. The speaker was passionate, convincing even, about how this was the essential skill for the next generation. And as I sat there, I found myself thinking: really? Is this truly the skill we should be racing to embed in every curriculum?

Lately, I keep hearing that prompt engineering, the ability to write clever and precise instructions for AI, is the new super skill every young person needs to master. The idea is that those who can “talk to the machine” will be the ones who thrive in the age of generative AI.

And I get it. For now, it is true. Anyone who spends time with AI knows that the way you ask matters. A well-structured prompt can turn an average response into something remarkable. I have seen entire professional development sessions focused on how to write the perfect prompt.

But I keep wondering if this is really a future skill or simply a transitional one.

We have been here before. About a decade ago, coding was the next great literacy. We were told that all students needed to learn to code or they would be left behind. And while understanding logic, pattern recognition and computational thinking remains valuable, few would now argue that every student must become a programmer. The tools evolved. The interfaces changed. Knowing how to code shifted from a universal requirement to an optional asset.

I suspect the same will happen with prompting. The models are already becoming much more forgiving. Early versions of AI required carefully worded instructions and detailed context. But each new generation of large language models has become better at interpreting vague or natural language. They are now more context aware, more visual and better aligned with human intent. The need for carefully engineered prompts is already beginning to fade.

Even the interfaces are changing. Most people will not type directly into chatbots in the future. They will use AI features inside tools such as Google Docs, Canva or Notion that quietly handle the prompting behind the scenes. The software will translate our natural requests such as “summarize this,” “improve the tone,” or “make it more visual” into optimized prompts automatically. Just as we no longer type code to open a file, we will not need to craft perfect prompts to get great AI output.

There may be a split happening here. For most of us, prompting will become invisible, handled by the interface layer. But specialized roles might still require deep prompt engineering expertise for critical systems or highly creative work where nuance matters. It could mirror how we still have systems programmers even though most people never write a line of code.

Modern AI systems are also being trained on millions of examples of strong instructions and responses. They have learned the meta-skill of interpreting intent. Clear and simple language now produces excellent results.

So if the technical part of prompting is becoming less necessary, what remains essential? The human part. Knowing what to ask. Evaluating whether the answer is right. Recognizing when a response is insightful, biased, or incomplete. The real differentiator will be judgment, not phrasing. The skill will not be in writing prompts but in thinking critically about what those prompts produce.

There is something deeper here too. The enduring skill might be what we could call AI collaboration literacy—the ability to iterate with AI, to recognize when you are not getting what you need, and to adjust your approach, not just your words. It is less about engineering the perfect prompt and more about developing a productive working relationship with these tools.

It reminds me of the evolution from coding to clicking. Early computer users had to memorize complex commands. Now, we all navigate computers intuitively. Prompt engineering feels like today’s command line, a temporary bridge to a more natural future.

So yes, teaching students to think like prompt engineers has value. It helps them be clear, curious and reflective. But perhaps the goal is not to create great prompters. It is to create great thinkers who can:

  • Articulate clear goals and constraints

  • Recognize the difference between excellent and mediocre output

  • Maintain healthy skepticism and verification habits

  • Understand when AI is the right tool versus when another approach works better

  • Iterate and refine their collaboration with AI systems

These capabilities feel more durable regardless of how the interfaces evolve.

Maybe I am wrong. Maybe prompt engineering will become a lasting communication skill. But before we rush to build it into every curriculum, it is worth asking whether we are chasing a moving target, and whether we should focus instead on the deeper cognitive skills that will matter no matter how we end up talking to machines.

As always, I share these ideas not because I have the answers but because I am still thinking them through. I would love to hear how others are thinking about this from where they sit.

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking.


Inspired by the recent Learning Forward BC conversation on human flourishing and AI.

Last week, I spent three hours tweaking a PowerPoint presentation I already had help with. At the same time, I had to decline a visit to an elementary class exploring AI tools. The irony? While I was perfecting slides, they were shaping the very future I was supposed to be leading them toward.

If we are honest, most of us superintendents spend far too much of our energy doing work that does not require the full force of our humanity. We draft versions of the same report again and again for different audiences. We shuffle through data systems, chase signatures, and repackage findings. It is necessary work, but is it what we were called to?

At a recent Learning Forward BC event on The Intersection of Human Flourishing and AI, that question hit home. We were exploring how technology might liberate, not limit, our humanity in education. It made me wonder: What if AI could take over significant portions of our work as leaders? What would we hand over, and what would we fight to keep?

Why This Matters for Leaders

I have written a lot on this blog about how AI is reshaping the work of teachers and students. But we need to look just as critically at our own work as superintendents and senior leaders. If we expect educators to rethink assessment, planning and feedback in an AI-rich world, then we must also examine the way we lead, communicate and make decisions.

The truth is that the same technology that can help a teacher personalize learning or a student write an essay can also help a superintendent analyze data, summarize reports or draft correspondence. AI is not only changing classrooms. It is changing the nature of leadership itself.

And yes, I am sure some superintendents might already be wondering if a chatbot could replace them at board meetings. But since I know my trustees often read this blog, I will not take the chance of testing that particular joke here.

The Question That Changes Everything

The OECD’s (Organisation for Economic Co-operation and Development)  Education for Human Flourishing framework reminds us that our purpose in education is to equip people to lead meaningful and worthwhile lives, oriented toward the future. If that applies to students, it applies to our leadership too.

So whether it is 30 percent, 50 percent, or even 70 percent of what we currently do, the question becomes: What would we hand over to AI, and which tasks would we hold on to because they matter most?

What We Could Let Go Of

AI is already remarkably good at tasks that drain our time but not our meaning:

  • Drafting first versions of reports, memos and letters
  • Crunching and summarizing enrolment or survey data
  • Managing meeting notes, calendars, reminders and task lists
  • Building templates, presentations and standard job postings
  • Drafting policy or procedural documents for refinement

These are automation, not animation. They do not require empathy, judgment, or nuance, only accuracy and speed. That is AI’s strength.

What We Must Protect

What we must protect, deliberately, are the moments of human connection, purpose and complexity:

  • Sitting with a parent whose trust in the system has eroded
  • Listening deeply to a principal wrestling with burnout or vision
  • Reading the room in a board meeting and knowing what not to say
  • Inspiring staff to believe in something greater than their daily tasks
  • Recognizing a student’s spark when they realize someone believes in them

These are leadership moments: irreducible, unautomatable and profoundly essential.

Leading for Human Flourishing

The OECD highlights three human competencies that AI cannot fully replicate: adaptive problem-solving, ethical decision-making and aesthetic perception.

Adaptive problem-solving: When a community crisis hits and there is no playbook, whether a sudden school closure, a traumatic event, or a divided community, we respond with creativity born from experience and intuition.

Ethical decision-making: When budget cuts force impossible choices between programs, when we must balance individual needs against the collective good, when integrity demands the harder path, these moments require moral courage that no algorithm can calculate.

Aesthetic perception: Recognizing when a school’s culture shifts from compliance to inspiration, sensing the exact moment a resistant team begins to trust, and seeing beauty in a struggling student’s small victory. This is what makes leadership an art, not just a science.

AI can mimic these competencies, but it does not feel them. It may calculate empathy, but it cannot experience it or show it. As more of our routine tasks shift to AI, the invitation is clear: we reclaim the human half.

Creating a Culture of Yes

This is where AI becomes an enabler of possibility rather than a threat to purpose. When AI handles the bureaucratic “no” work, the forms, compliance checks and procedural barriers, we create space for the human “yes.”

Yes, I have time to visit your classroom.
Yes, let’s explore that innovative idea.
Yes, I can truly listen.

In a Culture of Yes, AI does not replace us. It liberates us to be more fully present for what matters. Every report AI drafts is a conversation we can have. Every dataset it analyzes is a relationship we can build. Every schedule it optimizes is a moment we can use to connect.

Getting Started

This is not about wholesale transformation tomorrow. It is about small experiments.

What one repetitive task could you delegate to AI this week? What human conversation would that free you to have?

Start simple:

Use AI to draft that routine memo, then spend the saved time walking the halls.

Let AI summarize survey data, then use your energy to discuss what it means with your team.

Have AI create the meeting agenda, then focus fully on reading the human dynamics in the room.

The goal is not efficiency for its own sake, but reclaiming time for what only we can do.

The Real Promise

The promise of AI in leadership is not efficiency, but rediscovery.

It is the chance to release ourselves from the burden of mechanical work and return to the heart of leadership: human connection, meaning and moral purpose.

Imagine walking into your office tomorrow knowing that the reports are drafted, the data analyzed and the calendar managed, all before your first coffee. Now you can spend your morning where it matters most: in classrooms, with people, making meaning.

Because in the end, the future of education will not belong to the most efficient systems. It will belong to the most human leaders, those who use every tool available to protect and amplify what makes us irreplaceably human.

A Question to End With

I wonder if my list looks like yours. What would you hand over to AI, and what would you hold tightly because it feels essentially human? I would be interested to hear how others are thinking about their human half.

 

 

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking

Across Canada, and in many other parts of the world, literacy screening is having a moment.

There is broad agreement that we need to be better at identifying students who may be at risk, and that we need to do this earlier. The push toward more consistent and universal literacy screeners makes a lot of sense: earlier identification leads to earlier intervention, and ultimately, better outcomes for kids.

But here’s the question that’s been nagging me: are we simply going to recycle the same kinds of screeners we have used for the last generation? Or can this be the moment to think differently about what screening could look like in an AI world?

What Screeners Do Well

Traditional screeners help us establish a baseline. They can tell us if a student is meeting expected benchmarks in areas like phonemic awareness, decoding, fluency and comprehension. They provide the data teachers need to take action.

The challenge is that screeners often leave a gap between assessment and action. A teacher receives a score and then has to translate that number into the “what’s next” for the student and their family. It’s useful, but not always immediate, personalized or engaging.

What AI Could Add

This is where I wonder if we are missing an opportunity. AI could allow us to rethink the very design of literacy screeners. Imagine if…

  • Texts were customized for cultural relevance. Instead of one-size-fits-all passages, AI could generate short reading texts tailored to the learner’s context, interests or community. A child on the North Shore might read about the Capilano River, while another in Surrey reads about the Pattullo Bridge reconstruction. For Indigenous learners, this could mean texts that reflect Indigenous ways of knowing and storytelling traditions, developed in partnership with local Nations. The text would still be controlled for vocabulary and difficulty, but it would feel more real and more personal.

  • Feedback was immediate and audience-specific. A student could receive a friendly message highlighting a win (“You read 80 words per minute—your smoothest word was ship”) and a tip for next time. Families could receive a plain-language summary with simple routines for home (“Read together for 10 minutes tonight; circle the words that start with sh”). Teachers could receive a strand-level profile with small-group suggestions, not just a number on a page.

  • Practice was built-in. Instead of waiting for the next lesson, a screener could instantly generate a few targeted practice items based on the patterns the student struggled with, turning assessment into a learning moment instantly.

What This Isn’t

To be clear, this isn’t about replacing teacher expertise or professional judgment. Teachers would still interpret results, make instructional decisions, and build the relationships that matter most.

And this isn’t about creating more data for data’s sake. It’s about making the data we already collect more immediately useful—for students, for families and for teachers.

Safeguards Matter

Of course, any AI use comes with important guardrails. Automated scores would need validation against human judgment, with teachers maintaining override authority. Generated texts would require review for accuracy, bias and cultural safety. Indigenous content, in particular, would need to be co-designed with local Nations and aligned with principles of data sovereignty, ensuring that AI tools serve rather than appropriate Indigenous knowledge.

Quality oversight would need to be built in from day one, with regular audits and continuous monitoring to prevent the kind of drift that could undermine both accuracy and equity.

A Narrow Window

Here’s what makes this moment unique: jurisdictions are investing in new screening initiatives right now. We have a narrow window to influence how these tools are designed. If we don’t explore these possibilities now, we risk locking in approaches that simply digitize yesterday’s thinking.

I am not a literacy expert. But as someone who has watched technology reshape almost every other part of our schools over the last two decades, I see a pattern. The organizations that thrive are the ones that ask not just “how can we do what we’ve always done, but faster?” but “what becomes possible now that wasn’t possible before?”

The Question We Should Be Asking

The push for literacy screening is the right one. The evidence on early identification and intervention is clear. But we also have a unique opportunity to do more than just import the same tools from the past.

What if, instead of only identifying students who need help, our screeners could also immediately provide that help?

What if they could engage families in ways that feel supportive rather than clinical?

What if they could give teachers not just data, but insight?

AI won’t replace the expertise of our teachers or the relationships that matter most. But it might make our tools more immediate, more relevant and more effective for every child.

The question isn’t whether we should innovate. The question is whether we will seize this moment to innovate thoughtfully—or let it pass by.

What new possibilities are you seeing in your corner of education? And how do we make sure we are not just replicating the past with shinier tools?

Thanks to West Vancouver District District Vice-Principal Mary Parackal who really pushed my thinking in creating this post around what might be possible with AI.

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking.

Tomorrow night, as the Blue Jays take the field for their first World Series game in 32 years, I find myself thinking about time, how it moves, how we mark it, and how certain moments seem to hold more than others.

As I write, The Mighty Rio Grande by the band This Will Destroy You plays in the background. It’s the same haunting track often used in baseball highlight reels, the one from Moneyball that rises and swells beneath the most emotional sports moments. Somehow, it feels right.

There’s something about baseball that just hits differently. It’s never just about the game in front of us, but about all the games that came before. 

Maybe it’s the numbers, the endless statistics that let us measure generations and compare legends. Maybe it’s the pace, the slow burn of a game that unfolds in quiet moments between action. Or maybe it’s something deeper. Baseball holds a kind of memory that feels almost sacred.  It is the nostalgia made tangible, a way of reliving who we were through the game we watched and the people we shared it with. 

My first sports memory that really stuck was the 1981 Expos. I can still name their starting nine. I remember racing home at lunch to catch the end of the deciding game, and then the heartbreak as Rick Monday’s home run ended it all. Blue Monday. One of the most memorable days in Canadian baseball history, a unifying disappointment that every fan seemed to feel together.

I remember where I was for that one, just like I remember watching Joe Carter’s home run with my dad twelve years later. You don’t just remember the play; you remember the room, the people, the sound of your own voice shouting in disbelief. Baseball does that. It freezes a moment in time and lets us return to it, even decades later.

We love sports in our house, but none of our kids ever got into baseball. They found it too slow, painfully slow. Instead, they gravitated toward cheer, basketball, and track — sports with constant motion, immediate results, clear finish lines. I loved baseball growing up, but I get it. The game does feel too slow for our short-attention society. We are used to speed, to instant results, constant updates and highlights trimmed down to fifteen seconds. Baseball asks something different. It asks you to wait. To breathe. To notice.

And yet, as an educator, I see them learning the same lessons with my kids, just at a different tempo. The patience of perfecting a cheer routine through countless repetitions. The persistence of basketball practice. The slow accumulation of milliseconds shaved off a track time. The rhythm might be different, but the long game remains.

Monday night, when George Springer launched that three-run homer to send the Blue Jays past Seattle and into the World Series, Rogers Centre (I still just call it Skydome) erupted in a way we hadn’t heard in more than three decades. The excitement is infectious, sweeping through the community and the country. For those of us who grew up on the West Coast, Seattle and Toronto were our two favourite baseball teams. We would catch maybe one Jays game a week, but almost every Mariners game on local TV. Seeing those two cities battle for the pennant, knowing one had to lose, felt bittersweet and beautiful, like revisiting an old part of ourselves. The heartbreak for Seattle fans, the joy for Toronto. Both emotions familiar, both part of the game’s poetry.

Schools are a little like baseball that way. They are built on patience and presence. They reward those who keep showing up, even when the results take time. The best teachers, like the best players, understand that the season is long and the game cannot be rushed. There is a rhythm to learning that can’t be condensed into a clip or captured in a score.

Both baseball and teaching embody a culture of saying yes: yes to the slow moments between breakthroughs, yes to showing up when progress isn’t visible, yes to believing in potential that takes time to manifest. It’s saying yes to the process, not just the outcome.

We talk a lot these days about acceleration, about faster tools, quicker responses, and shorter attention spans. But maybe education, at its heart, is still about the long game. About showing up every day, doing the small things that no one notices, trusting that they will add up to something beautiful over time. About saying yes to patience when everything else demands speed.

When you are twenty and Canada’s team has just won back-to-back championships, you believe it will happen again soon. You can’t imagine that suddenly you’ll be fifty-two, that three decades will have slipped by, that you will have lived an entire life in the space between World Series appearances. The wait itself becomes a teacher. And now, caught up in the excitement that’s gripping the country, you realize how much these moments matter precisely because they are so rare.

As the Blue Jays prepare to face the defending champion Dodgers, I find myself thinking not just about the scoreboard but about that sound, the crack of the bat, the swell of the crowd, the quiet connection between father and son, teacher and student, one generation and the next.

Maybe that’s what baseball and teaching really share. They both remind us that the moments that matter most rarely happen fast. They both ask us to say yes to the waiting, to the watching, to the faithful belief that something magical might happen if we just stay present.

And maybe that’s the real lesson, that in a world obsessed with the next big thing, there’s still magic in the slow game, in the steady, human work of showing up, staying hopeful, and believing that meaning often reveals itself only when we give it time.

Over the next week, a new generation of fans will create their own frozen moments. Somewhere, a parent and child will watch together, and thirty years from now, that child will remember not just the game, but the feeling of being there, present, connected, saying yes to the slow unfolding of something larger than themselves.

Play ball.

 

 

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking.

How I draft, edit, and stay human in the loop

For years I believed my advantage was “writing.” Lately I’ve realized the real edge was not keystrokes, it was ideas, structure, and voice. AI has not erased those. If anything, it has made them more important. Rather than pretend we are still in a pen and paper world, I have been trying to model what authentic writing looks like now.

We do not protect writing by banning the tools everyone already has. We protect writing by showing what thoughtful use looks like, and by being transparent about our process.

What I am hearing, especially in humanities

Last week, a high school English teacher stopped me. “I can tell when something has been AI generated,” he said, “but I cannot tell when they have collaborated with it thoughtfully. And I do not know what to do with that.”

He is not alone. Across our humanities departments, teachers are working on the fly, trying to maintain academic integrity while recognizing that the old gatekeeping moves, ban the tool and police the draft, do not hold when every student has ChatGPT in their pocket. The fear is real. Are we farming out the exact skills we are supposed to be teaching?

I do not think the answer is choosing between integrity and innovation. It is redefining what integrity looks like when the tools have changed.

How I actually write

I still start the old fashioned way, an outline, a thesis, a few proof points, and usually one sentence I think could be the closer. From there, I treat AI like a colleague, not a ghostwriter.

  • Editing help. I ask for a clarity pass, tighten verbs, fix hedging, and check whether my headings are parallel. Here is what I actually typed for this piece: “Revise for clarity and concision. Keep a conversational, hopeful tone similar to my other blog posts. Offer two options for the opening sentence.” I kept one, rejected the other, and moved on.

  • Skeptic check. “What would a fair skeptic say after reading this” It surfaces blind spots before I hit publish.

  • Reports and formatting. For formal documents, I use AI to turn tables into charts, crunch numbers, and reshape dense text into something readable.

  • Speeches. I keep a base grad speech and add school specific stories and names. AI helps blend those elements while keeping the message consistent.

None of this replaces judgment. I accept or reject every change. If a suggestion dulls my voice, it is out. That is the standard. My judgment stays in control. I also disclose what I did, every time. A short note at the end of a post goes a long way with our community and models the behavior we ask of students.

What I encourage for classrooms and staff rooms

The most helpful shift has been moving from “Do not use AI” to “Show your decisions.”

  • Model, then mirror. I demo my messy paragraph, ask AI for a clarity edit, then accept or reject in real time while explaining why. Students should bring their draft, try the same process, and compare choices.

  • Assess the thinking. Rubrics weight claims, evidence, organization, and audience impact, not who placed the comma.

  • Make the process visible. Version histories in Docs or Word, plus brief process notes that list tools used, prompts asked, and choices made, make learning visible and deter abdication of thinking.

  • Cite the workflow. Not to catch people out, but to name steps we can teach.

Guardrails that keep the work honest

  • No blank page outsourcing. Start with your outline, thesis, or key points.

  • Ask precise questions. “Cut 10 percent without losing meaning. Keep my conversational tone.”

  • Verify facts. If AI offers a claim, check it before it lands in public.

  • Always disclose. If a tool shaped meaning or form, say how.

Is this just cheating with better branding

I have never believed collaboration was cheating. When I wrote a newspaper column, my dad, a retired English teacher, was my unofficial copy desk. He proofread, edited, and offered suggestions on every draft. The byline was still mine because the ideas, voice, and final choices were mine.

Tricia Buckley, and before her Sharon Pierce and Deb Podurgiel, all staff in West Vancouver Schools, have read every blog post here before they were published and provided feedback.

AI sits in that same category for me, a helper, not a ghostwriter, and always subject to human judgment. What changed with AI is speed, scale, and availability. I can get feedback at 11 p.m., run ten drafts in twenty minutes, and the tool is always on. What did not change is my judgment, my responsibility for choices and my name on the work.

If the goal is proving you can type unaided, then yes, tools muddy the waters. Our goal in schools is thinking for real audiences. We have always used supports, outlines, spellcheckers, style guides, writing partners, rubrics and colleagues. The standard should be integrity and evidence of learning, not tool abstinence.

Equity

AI is a ramp, not a shortcut.

It helps stuck writers get moving, the student staring at a blank page who needs a sentence to react to, or the English language learner who can articulate ideas verbally but struggles with syntax. AI can generate that first sentence, and suddenly the student has something to revise, reject, or build on. For strong writers, it is a way to go deeper, test alternate structures, get a skeptic to read, or polish a conclusion without losing momentum.

The equity move is not banning tools for everyone. It is teaching how to use them responsibly, and ensuring access to good instruction is not the new dividing line. When we teach tool literacy, we level up. When we ban tools students already have, we make the learning invisible.

Prompts that actually help

  • Clarity pass: “Revise for clarity and concision. Keep a conversational, hopeful tone. Offer two options for the opening sentence.”

  • Skeptic lens: “List the strongest fair minded critiques of this piece and one concrete improvement for each.”

  • Structure check: “Are these headings parallel? Tell me how to fix them without changing the ideas.”

  • Audience flip: “Rewrite the conclusion as guidance to parents in about 120 words.”

  • Report polish: “Turn this table into three plain language insights and a simple chart title. Flag any numbers that look inconsistent.”

What I tell our community

  • We are pro-writing and pro-truth. We will use modern tools and we will say when we did.

  • We value voice. Your voice should be recognizable across drafts and tools.

  • We lead with learning. If a tool helps learning, we will teach it. If it replaces thinking, we will not.

If you want more

Last week I facilitated a Hot Topic discussion, “The Future of Writing in an AI World,” at the Canadian K12 School Leadership Summit on Generative AI

North Star

I can spend my time lamenting that writing once felt like my competitive edge, or I can double down on the edge that still matters, clear thinking, vivid stories and the courage to be transparent about how we work. That is the blended human and AI writing world I want to model for students and staff.

The teacher who stopped me in the hallway was right to be uncertain. We are all figuring this out in real time. I would rather figure it out in the open, and model a messy and honest process, than pretend the tools do not exist.

AI transparency note: I drafted this post myself, then used ChatGPT and Claude for a clarity edit and a skeptic read. I accepted some wording suggestions and rejected others to preserve voice. The image at the top of the post was created through a series of prompts using Claude.

 
 

.