Last night, driving back from Thompson Rivers University in the dark, I could feel the road settling me down and winding my thinking up. I’d just finished guest-speaking in a class alongside my colleague and friend, Rob Capello, and I left with that rare feeling you get when you learn something new in public — the kind that makes you want to get home, put a log on the cabin fire, and try the thing immediately.
A huge thank-you to Adina Gray for the invitation and for trusting us with her students while she was away. And a shout-out to Yana, her teaching assistant, who kept the room flowing. Adina is doing terrific work at TRU in AI education — not just using tools, but teaching students how to think with them. Rob brings a different lens: he runs a marketing agency that has reinvented itself in the face of AI, and he builds decks like most people send emails — constantly and at speed.
That pairing — education and industry — set the tone for everything that followed.
The “Gamma” Moment I Didn’t See Coming
I’ve spent a lot of hours in PowerPoint. I’ve dabbled in Canva. I’m comfortable there. Then Rob opened Gamma.
Watching him generate a clean, modern, coherent deck in minutes was one of those “Okay, I need to rethink my defaults” moments. It wasn’t magic — Rob still customized, still made choices — but the frame appeared instantly. Structure, flow, typography, spacing: handled. He could focus on the message.
On the drive back from TRU to the cabin, all I could think was, I can’t wait to run my own decks through this and see what happens. Not because slides should be flashy — they shouldn’t — but because when the scaffolding is fast and good, we get more time for the ideas.
When the AI World Was Small
If you were in the AI trenches a couple of years ago, you probably knew most of the same tools I did. The list was short. Conversations felt like a shared map: we were all standing in roughly the same clearing, pointing at the same landmarks.
That time is over.
Today, the AI world is less a clearing and more a forest — with trails branching in every direction. Education is sprinting down one path. Marketing and creative production have carved another. Operations, sales, legal, finance — each is becoming its own trail system with specialized tools, norms, and best practices.
It’s not that any of us know less. It’s that AI’s surface area has exploded, and competence now comes with a high degree of context. The right tool depends on the job, the team, the workflow, the brand, the risk tolerance, the values. And that means if we stay in our own lanes, we’ll miss what’s happening just one turn over.
Students Are the Early Sensors
Two years ago, I sat in on a TRU class where students were pitching. Roughly 90% used Canva. That made sense: Canva lowered the barrier, made things look “good enough,” and removed a lot of friction.
This week, when Rob mentioned Gamma in Adina’s class, we wondered how many had even heard of it.
A lot had. Some were already using it.
That’s not a scientific survey. But it’s a clue. When a tool drastically reduces the time between idea → presentable, students spread it by word of mouth. No campaign required. Adoption happens in the cracks between classes, on group chats, in late-night “you gotta try this” messages. It’s the natural diffusion of something genuinely useful.
And in a way, that’s the lesson: when a tool creates compounding time savings, the adoption curve steepens — and the rest of us need to decide whether to keep pace or stick with familiar habits.
Specialization Isn’t a Luxury — It’s the Shape of the Work Now
Early in tech, you could say “I work in tech” and it meant something. Then the map fragmented: data, web, security, mobile, cloud, ML. Today, AI is fragmenting the same way. I’m seeing people choose lanes and go deep:
Education & pedagogy (Adina’s lane): How do we teach critical thinking with AI? What’s the right balance between assistance and autonomy? How do we coach citation, consent, and disclosure?
Marketing & creative ops (Rob’s lane): How do we ship more, faster, without losing voice? Where does automation end and brand judgment begin?
Consulting & avatar creation (my lane): How do we design practical workflows for real teams, integrate avatars and voice into communication, reduce friction, and make AI feel like a colleague rather than a gimmick?
Each lane has its own stack of tools. Each stack changes monthly. None of us can hold the whole state of the art in our heads.
Which is why collaboration isn’t just nice — it’s necessary.
The Real Value of Cross-Pollination
There’s a specific kind of learning that only happens when you watch someone in their element. Seeing Rob build in Gamma wasn’t a feature tour. It was a live demo of why speed matters in an agency context: decks are currency, iteration is constant, and clarity beats cleverness.
Likewise, being in Adina’s classroom isn’t just about content — it’s about seeing how students ask questions, where they stall, and how quickly they connect dots between tools and outcomes. Education is where future norms are being set.
When these worlds cross — education, industry, consulting — we borrow each other’s best practices and discard our worst habits. We also discover blind spots we didn’t know we had.
A small example: I’m used to thinking in terms of workflows and operational reliability. Adina thinks deeply about cognitive load and learning scaffolds. Rob thinks in the cadence of campaigns and client expectations. Put those lenses together and you get a better product than any one lane produces on its own.
A Note on Tools vs. Taste
Tools can give us a frame; they can’t give us taste. Gamma made a lot possible in a short time, but Rob’s taste still shaped the output. Adina’s judgment still filters what is responsible in a classroom. My taste still governs whether a slide is cluttered or clear.
AI can finish our sentences; it can’t finish our thinking.
If anything, the faster tools get, the more we need to slow down just enough to ask: What am I trying to say? and What does my audience actually need? That’s where expertise lives. That’s what students are really learning when they watch us work: not the button you clicked, but the decision you made.
What I’m Changing After This Class
I’m trialing Gamma for my next deck. Not because it’s trendy, but because it buys me time back to think about message and flow.
I’m scheduling more cross-lane coffees. If you’re in the Central Interior and working in AI — education, marketing, product, ops — let’s compare notes.
I’m building a short “show-and-tell” habit. One demo, five minutes, at the start of team sessions: “Here’s a thing that saved me an hour this week.” If it sticks, it stays.
I’m documenting defaults. The stack changes, but principles don’t. I’m writing down the 6–8 decisions that make a deck or workflow feel like “me,” so tools serve taste, not the other way around.
A Simple Collaboration Pattern Any Team Can Try
Monthly Roundtable (60 min):
Three people, three domains. Each brings a 5-minute demo.
10 minutes of Q&A after each demo.
Close with “What will we try this month?”Shared “Tool Notes” Doc:
One page per tool.
Keep only: what it’s great for, what it’s not for, settings that matter, pitfalls, sample prompts/templates.
If the page gets long, you’ve made it a manual. Compress it back to the essentials.The “Borrow a Brain” Rule:
Before committing to a new tool or workflow, ask one colleague in another lane to sanity-check.
You’ll spot blind spots you can’t see from inside your lane.Ethics Check (Fast but Real):
Consent: Are we using data appropriately and with permission?
Disclosure: Will the audience understand where/when AI was used?
Bias: Did we sanity-check outputs against obvious skews?
Impact: Who benefits, who could be harmed? What’s our mitigation?
The Classroom as a Mirror
One of the privileges of guest-speaking is that you get to see your own assumptions reflected back at you. Students are honest in a way professionals sometimes aren’t. They move faster, share freely, and — when a tool is genuinely useful — they don’t wait for permission.
That’s good pressure for the rest of us. It forces us to keep our workflows honest: Are we clinging to habit or choosing on purpose? Are we optimizing for speed or clarity? Are we using tools to look polished or to communicate better?
When I saw how many already knew Gamma, it wasn’t a “kids these days” moment. It was a reminder that learning is not a department — it’s a posture. If you’re curious and you’re willing to share, you get better together.
A Public Thank-You
Adina, thank you for the invitation and for the work you’re doing to prepare students for a future where AI is just normal. Rob, thanks for the Gamma walk-through and for showing how to balance speed with taste in the real world. Yana, thanks for anchoring the room.
And to the students: I learned from you too.
The Drive Home
There’s something about a night drive that makes ideas settle into their right size. The road from campus to the cabin is familiar, but the thoughts were new. I don’t think of myself as a “presentation person.” I think of myself as someone who tries to communicate clearly and build helpful things with people I respect. If a tool lets me do those things with more focus and less friction, I’m in.
I’ve said for a while that I work with AI, not on AI. I treat it like a colleague — one that’s fast, occasionally overeager, and always improving. Nights like this are a reminder that my best days in this space don’t happen alone. They show up when education, industry, and community intersect — when someone opens a tool I’ve never tried and says, “Watch.”
AI is getting bigger. None of us can keep up alone. But together — in classrooms, in agencies, in coffee shops, and yes, in cabins — we can keep learning at the pace that matters: the pace of the problems we’re trying to solve for real people.
If you’re in the Central Interior and working in or around AI — education, marketing, ops, product — consider this a standing invite: let’s make the “show-and-tell” a habit. I’ll bring my first Gamma draft.