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Hyperweb Communications, 2192 Emily Circle, Oakville, ON (2026)

10/13/2026

My best ideas tend to arrive when I’m 𝘂𝗻𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 to write them down.

In the shower.
Halfway through swimming laps.
Doing something repetitive that requires almost none of my attention.

𝗩𝗲𝗿𝘆 𝗶𝗻𝗰𝗼𝗻𝘃𝗲𝗻𝗶𝗲𝗻𝘁. Apparently, my brain has no respect for office hours. 😀

But those moments have something in common.

The little voice that questions everything finally shuts up.

“Are you qualified to do that?”
“Is that too ambitious?”
“What if it doesn’t work?”
“Who do you think you are?”

That voice can make a perfectly good idea feel ridiculous before you’ve even explored it.

Then something interrupts the pattern.

For a moment, you can see the possibility 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗶𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲𝗹𝘆 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗰𝗮𝘀𝗲 𝗮𝗴𝗮𝗶𝗻𝘀𝘁 𝘆𝗼𝘂𝗿𝘀𝗲𝗹𝗳.

The doubt hasn’t been disproven. It’s just stopped chairing the meeting.

And you get room to think.

To connect things you’d been treating as separate.
To question a limit you’d mistaken for a fact.
To stretch a little further than you were comfortable stretching yesterday.

I’ve been having a lot of those moments lately.

Enough that I’m going out on a limb:
..I believe we’re building the most sophisticated, powerful go-to-market system we’ve ever put together at Hyperweb...

𝗧𝗵𝗲𝗿𝗲’𝘀 𝗮 𝗹𝗼𝘁 𝗼𝗳 𝘄𝗼𝗿𝗸 𝗯𝗲𝗵𝗶𝗻𝗱 𝘁𝗵𝗮𝘁 𝘀𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁. But some of the thinking that got us here happened when I stopped trying so hard to think.

Built on the backs of pattern interrupts.

What’s the pattern interrupt? Is it exercise? Something mundane? A mind-altering substance?

I’ll leave that part to you to decide.

10/02/2026

"𝗜 𝗳𝗲𝗱 𝘆𝗼𝘂𝗿 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗶𝗻𝘁𝗼 𝗖𝗹𝗮𝘂𝗱𝗲.”
I’ve heard versions of that from clients. So have a lot of people I respect.

I don’t object to a second opinion. If you’re making an important decision, you should question the advice you receive.

But something changes when a client brings back an AI answer and asks the person they hired to defend themselves against it.

I know people who are starting to lose confidence in their own abilities because this keeps happening. I feel for them. I’ve felt some of that wind leave my sails, too.

The difficult part is that the AI answer can sound certain without carrying the history behind the recommendation: the conversations, the constraints, the things that failed before, and the judgment built through years of doing the work.

Maybe it has spotted something we missed. I’m willing to hear that.

But a different answer isn’t, by itself, evidence that the original recommendation was wrong. And a professional shouldn’t have to hand over everything they know just to earn back the credibility they brought into the room.

If an AI answer raises a useful question, let’s discuss the question. Let’s examine the reasoning. That can make the work better.

What’s wearing people down is the assumption that 𝗮𝗻 𝗮𝗻𝘀𝘄𝗲𝗿 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 𝗶𝗻 𝘀𝗲𝗰𝗼𝗻𝗱𝘀 deserves equal footing with the judgment of the person you trusted enough to hire.

10/01/2026

I thought AI-assisted development would buy us a 2- to 3-year advantage.
𝗜𝘁 𝗹𝗮𝘀𝘁𝗲𝗱 𝗮𝗯𝗼𝘂𝘁 𝟱 𝘄𝗲𝗲𝗸𝘀.

Maybe a few months, if I'm being generous with myself.

𝘐 𝘸𝘢𝘴 𝘤𝘰𝘯𝘧𝘪𝘥𝘦𝘯𝘵𝘭𝘺 𝘸𝘳𝘰𝘯𝘨, 𝘢𝘯𝘥 𝘵𝘩𝘦 𝘳𝘦𝘢𝘴𝘰𝘯 𝘪𝘴 𝘸𝘰𝘳𝘵𝘩 𝘴𝘪𝘵𝘵𝘪𝘯𝘨 𝘸𝘪𝘵𝘩.
I assumed the scarce thing would be knowing how to use the tools well. It wasn't. Everyone got the same tools in the same quarter, at the same price, including the firm down the street.

Accelerated development.
Generated interfaces.
A working prototype in an afternoon instead of a month.

So here's what being wrong taught me: tool access isn't a MOAT right now.
It's table stakes with a very short shelf life.

𝗧𝗵𝗲 𝗼𝗻𝗹𝘆 𝗿𝗲𝗮𝗹 𝗠𝗢𝗔𝗧 𝗜 𝗰𝗮𝗻 𝘀𝗲𝗲 𝘁𝗼𝗱𝗮𝘆 𝗶𝘀 𝗽𝗲𝗼𝗽𝗹𝗲'𝘀 𝗿𝗲𝗹𝘂𝗰𝘁𝗮𝗻𝗰𝗲 𝘁𝗼 𝗰𝗵𝗮𝗻𝗴𝗲.

Whatever edge is left has to come from somewhere the tools can't reach yet.
- Knowing which problem is worth solving.
- Relationships that predate the software.
- Being the one who's accountable when it goes sideways.

𝗜'𝗺 𝘀𝘁𝗶𝗹𝗹 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝗼𝘂𝘁 𝗵𝗼𝘄 𝗺𝘂𝗰𝗵 𝗼𝗳 𝘁𝗵𝗮𝘁 𝗶𝘀 𝗱𝘂𝗿𝗮𝗯𝗹𝗲 𝗮𝗻𝗱 𝗵𝗼𝘄 𝗺𝘂𝗰𝗵 𝗼𝗳 𝗶𝘁 𝗜 𝗷𝘂𝘀𝘁 𝘄𝗮𝗻𝘁 𝘁𝗼 𝗯𝗲 𝘁𝗿𝘂𝗲.

Where are you finding an edge right now, if it isn't in the tools?

This post is part of a bigger question I’ve been wrestling with. I wrote about it in more detail in the latest Gecko Droppings: https://lnkd.in/p/gjqbdtRN

09/30/2026

𝗔𝗜 𝗺𝗶𝘀𝘀𝗲𝗱 𝗮 𝘀𝗽𝗼𝘁.
That seems to be where a lot of conversations end.

We point at the mistake, have a laugh, and conclude that AI isn’t ready.
Sometimes that criticism is fair. These tools have real limitations.

But look at the fence in this image. AI was shown how to paint it, then repeated what it saw. The interesting question isn’t just, “Why did it miss those spots?” It’s, “What happens when we show it the finish we actually want?”

We’re still learning how to direct these tools. The instructions, examples, context, and checks matter. Once we get those right, we aren’t talking about one person painting a fence a little faster. We’re talking about the ability to produce the desired result across a thousand fences.

I understand the instinct to pick at the flaws. They’re easy to see, and some deserve serious attention. But if you use today’s flaws as proof that there’s no opportunity here, you may be watching the bumps in the road while missing where the road leads.

𝗪𝗵𝗮𝘁’𝘀 𝗮 𝘁𝗮𝘀𝗸 𝘆𝗼𝘂’𝘃𝗲 𝘀𝗲𝗲𝗻 𝗔𝗜 𝘀𝘁𝗿𝘂𝗴𝗴𝗹𝗲 𝘄𝗶𝘁𝗵 𝘁𝗵𝗮𝘁 𝘆𝗼𝘂 𝘀𝘂𝘀𝗽𝗲𝗰𝘁 𝗰𝗼𝘂𝗹𝗱 𝘄𝗼𝗿𝗸 𝘄𝗶𝘁𝗵 𝗯𝗲𝘁𝘁𝗲𝗿 𝗱𝗶𝗿𝗲𝗰𝘁𝗶𝗼𝗻?

09/29/2026

Here are the 6 questions I'm using to pressure-test my own business. 𝗦𝘁𝗲𝗮𝗹 𝘁𝗵𝗲𝗺.

1. Which parts of what we sell are 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗯𝗲𝗶𝗻𝗴 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱, whether we admit it or not?

2. What's genuinely scarce in what we do? Not hard to do well. 𝗦𝗰𝗮𝗿𝗰𝗲.

3. 𝗜𝘀 𝗼𝘂𝗿 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 𝘁𝗵𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁, or is it becoming an ingredient inside somebody else's product?

4. Where do judgment, relationships and accountability 𝘀𝘁𝗶𝗹𝗹 𝗱𝗲𝗰𝗶𝗱𝗲 𝘁𝗵𝗲 𝗼𝘂𝘁𝗰𝗼𝗺𝗲?

5. If I were starting Hyperweb tomorrow, with today's tools available on day one, 𝘄𝗵𝗮𝘁 𝘄𝗼𝘂𝗹𝗱 𝗜 𝗯𝘂𝗶𝗹𝗱 𝗶𝗻𝘀𝘁𝗲𝗮𝗱?

6. What am I protecting because it's genuinely valuable, and 𝘄𝗵𝗮𝘁 𝗮𝗺 𝗜 𝗽𝗿𝗼𝘁𝗲𝗰𝘁𝗶𝗻𝗴 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝗜'𝗺 𝘂𝘀𝗲𝗱 𝘁𝗼 𝗶𝘁?

Number 5 is the one I keep circling back to.
I don't have a clean answer yet, which is itself informative.

𝗧𝗵𝗲 𝗮𝘀𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻 𝗜'𝗱 𝘁𝗵𝗿𝗼𝘄 𝗼𝘂𝘁 𝗳𝗶𝗿𝘀𝘁: 𝘵𝘩𝘢𝘵 𝘵𝘩𝘦 𝘸𝘢𝘺 𝘺𝘰𝘶𝘳 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘺 𝘸𝘰𝘳𝘬𝘦𝘥 5 𝘺𝘦𝘢𝘳𝘴 𝘢𝘨𝘰 𝘵𝘦𝘭𝘭𝘴 𝘺𝘰𝘶 𝘢𝘯𝘺𝘵𝘩𝘪𝘯𝘨 𝘶𝘴𝘦𝘧𝘶𝘭 𝘢𝘣𝘰𝘶𝘵 𝘩𝘰𝘸 𝘪𝘵 𝘸𝘰𝘳𝘬𝘴 5 𝘺𝘦𝘢𝘳𝘴 𝘧𝘳𝘰𝘮 𝘯𝘰𝘸.

If you only run one of these, run number 5.
𝗧𝗵𝗮𝘁'𝘀 𝘄𝗵𝗲𝗿𝗲 𝗶𝘁 𝗴𝗲𝘁𝘀 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲, 𝗮𝗻𝗱 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝗶𝘀 𝘄𝗵𝗲𝗿𝗲 𝘁𝗵𝗲 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗶𝘀.

This post is part of a bigger question I’ve been wrestling with. I wrote about it in more detail in the latest Gecko Droppings: https://lnkd.in/p/gjqbdtRN

09/29/2026

Gecko Droppings?
On the surface, it looks ridiculous. A gecko. Droppings. A strange little campaign built around an intentionally weird idea.

But that is the point.

The real product is not Gecko Droppings.
𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗶𝘀 𝗮𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻.

Gecko Droppings is the proof.

It proves that when an idea has enough contrast, personality, and curiosity baked into it, people notice.

And once they notice, you have a chance to say something useful.

That is the part most businesses miss.

They are trying to explain everything perfectly before they have earned anyone’s attention.

Good marketing does not always start with polish.

Sometimes it starts with a hook strong enough to make someone stop, laugh, click, ask a question, or remember you three days later.

That is the method behind the madness.

https://hyperweb.ca/gecko-campaign/

09/28/2026

I’ve never been short of opinions.
And I’m reasonably well known for speaking my mind.

But I’ve also been told I have a high EQ (𝘸𝘩𝘪𝘤𝘩 𝘪𝘴 𝘢 𝘸𝘰𝘯𝘥𝘦𝘳𝘧𝘶𝘭𝘭𝘺 𝘢𝘸𝘬𝘸𝘢𝘳𝘥 𝘵𝘩𝘪𝘯𝘨 𝘵𝘰 𝘳𝘦𝘱𝘦𝘢𝘵 𝘢𝘣𝘰𝘶𝘵 𝘺𝘰𝘶𝘳𝘴𝘦𝘭𝘧)

For whatever reason, those two sides of me seem to come together on LinkedIn and manifest as vulnerability.

𝗠𝗮𝘆𝗯𝗲 𝗶𝘁’𝘀 𝗮 𝗸𝗶𝗻𝗱 𝗼𝗳 𝘆𝗶𝗻 𝗮𝗻𝗱 𝘆𝗮𝗻𝗴.

One side says:
“This is what I think.”

The other asks:
“But why do I think it? What if I’m wrong? And what does this reveal about me?”

𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁, 𝘃𝘂𝗹𝗻𝗲𝗿𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗰𝗮𝗻 𝗯𝗲𝗰𝗼𝗺𝗲 𝗻𝗮𝘃𝗲𝗹-𝗴𝗮𝘇𝗶𝗻𝗴.

𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝘁𝗵𝗲 𝘀𝗲𝗰𝗼𝗻𝗱, 𝘀𝘁𝗿𝗼𝗻𝗴 𝗼𝗽𝗶𝗻𝗶𝗼𝗻𝘀 𝗰𝗮𝗻 𝗯𝗲𝗰𝗼𝗺𝗲 𝗻𝗼𝗶𝘀𝗲.

I’ve spent much of my career being paid to have an answer. To make a recommendation. To see around corners and help clients decide what to do next.

But some of the things I’m writing about now... AI, the future of agencies, what happens to people’s jobs and where human value comes from... 𝗱𝗼𝗻’𝘁 𝗵𝗮𝘃𝗲 𝘁𝗶𝗱𝘆 𝗮𝗻𝘀𝘄𝗲𝗿𝘀.

I still have opinions.

I’m just becoming more comfortable examining them in public.

Maybe that’s why these posts feel vulnerable.

I’m not simply telling people what I think.

I’m letting them see me work out whether I still believe it.

And apparently, people find that more interesting than another list of five things they should be doing.

𝗛𝗼𝗻𝗲𝘀𝘁𝗹𝘆, 𝗜 𝗱𝗼 𝘁𝗼𝗼.

09/25/2026

This is what AI feels like right now.

We watch in fascination as skilled developers use it to expand what’s possible almost every day.

The demonstrations are impressive.
The possibilities feel endless.
And the people closest to it 𝗮𝗽𝗽𝗲𝗮𝗿 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲𝗹𝘆 𝗶𝗻 𝗰𝗼𝗻𝘁𝗿𝗼𝗹.

So we move a little closer.

We get comfortable.

We 𝘀𝘁𝗮𝗿𝘁 𝗯𝗲𝗹𝗶𝗲𝘃𝗶𝗻𝗴 we understand what we’re watching.

Then something unexpected enters the picture, 𝗮𝗻𝗱 𝘁𝗵𝗲𝗻 𝗰𝗵𝗮𝗼𝘀 𝗲𝗻𝘀𝘂𝗲𝘀.

That’s the part I don’t think businesses are fully prepared for.

AI doesn’t have to turn against us. It only has to change faster than our assumptions, business models and people can adapt.

The disruption probably won’t come from where we’re all staring.

It’ll come from the side. 🐒

09/24/2026

𝗪𝗲 𝗯𝘂𝗶𝗹𝘁 𝗮 𝗯𝗲𝘁𝘁𝗲𝗿 𝗽𝗹𝘂𝗻𝗴𝗲𝗿.

- Bluetooth-enabled.
- Ergonomic grip.
- Digital display.
- Battery indicator.
- Real-time performance monitoring.

𝗜𝘁 𝗲𝘃𝗲𝗻 𝘀𝘆𝗻𝗰𝘀 𝘄𝗶𝘁𝗵 𝘆𝗼𝘂𝗿 𝗽𝗵𝗼𝗻𝗲.

And yet, at the end of the day, you’re still unclogging a toilet.

𝗧𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝗽𝗮𝗿𝗮𝗹𝗹𝗲𝗹 𝗜 𝗸𝗲𝗲𝗽 𝘀𝗲𝗲𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜.

AI can help almost anyone build a website, create a campaign, automate a workflow or launch an app.

The output can look remarkably polished.

But polished and effective aren’t the same thing.

A non-marketer can build a beautiful website without realizing that search engines can’t understand it.

They can create hundreds of pages without a coherent content strategy.

They can automate lead follow-up without considering whether the messages build trust or slowly destroy it.

They can launch something that looks finished without understanding the implications for accessibility, analytics, data residency, security or conversion.

𝗔𝗻𝗱 𝘁𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗱𝗮𝗻𝗴𝗲𝗿𝗼𝘂𝘀 𝗽𝗮𝗿𝘁.

AI doesn’t always tell you when the original idea is flawed. It simply helps you execute it faster, cheaper and more confidently.

Sometimes it even adds Bluetooth. 😀

The real advantage isn’t knowing how to use the tools. More and more people can do that.

The advantage is knowing which problems are worth solving, what good actually looks like and where the hidden risks tend to live.

AI can help us build almost anything.

We still need enough judgment to recognize when we’re simply building a better plunger.

Where have you seen AI improve the work—and where has it merely helped someone do the wrong work faster?

09/23/2026

I’ve fallen into an AI trap of my own making.
I know it well because I’m still living in it.

𝗜 𝘄𝗮𝘀 𝘁𝗵𝗲 𝗲𝗮𝗿𝗹𝘆 𝗮𝗱𝗼𝗽𝘁𝗲𝗿. Excited by the technology. Curious about what AI could do.

So I explored. Investigated. Bought subscriptions. Installed skills. Built workflows. Experimented with just about everything I could get my hands on.

I learned. I grew. Before long, I knew more about AI than most people around me.

𝗔𝗻𝗱 𝘁𝗵𝗮𝘁’𝘀 𝘄𝗵𝗲𝗻 𝘁𝗵𝗲 𝘁𝗿𝗮𝗽 𝗰𝗹𝗼𝘀𝗲𝗱.

I became the person who knew which tool to use. I had the subscriptions, the skills and all the accumulated knowledge required to make everything work.

My team is excited about AI.

𝗕𝘂𝘁 𝘁𝗵𝗲𝘆 𝗱𝗼𝗻’𝘁 𝗻𝗲𝗰𝗲𝘀𝘀𝗮𝗿𝗶𝗹𝘆 𝗵𝗮𝘃𝗲 𝗺𝘆 𝘀𝗲𝘁𝘂𝗽, 𝗺𝘆 𝗮𝗰𝗰𝗲𝘀𝘀 𝗼𝗿 𝘁𝗵𝗲 𝗯𝗲𝗻𝗲𝗳𝗶𝘁 𝗼𝗳 𝗵𝘂𝗻𝗱𝗿𝗲𝗱𝘀 𝗼𝗳 𝗵𝗼𝘂𝗿𝘀 𝘀𝗽𝗲𝗻𝘁 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗶𝗻𝗴.

So when something needs to be done, it comes to me.

AI was supposed to make me more efficient.

It was supposed to expand the capabilities of the entire team.

Instead, it made me the bottleneck.

And here I am, doing the work—working in the business instead of on it.

𝗛𝗼𝘄 𝘁𝗵𝗲 𝗵𝗲𝗹𝗹 𝗱𝗶𝗱 𝘁𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻?

I adopted AI personally.

I haven’t yet operationalized it at the organizational level.

𝗧𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: moving beyond tools and individual productivity to rethink the systems, roles and workflows around them.

It’s also why I value conversations with big thinkers like Raffi Oshagan from Garo and Wayne Regier from Integrated Supply Systems.

They aren’t simply asking, “Which AI tool should we use?”

They’re looking at the business holistically and asking the much more important question:

“How should the organization work now?”

Hyperweb Communications

10/13/2026

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