Betting on Execution, Not Hype
About a decade ago, I had a drink with a friend who managed one of the largest funds in Canada. I asked him point-blank: “What’s your edge? With all the noise out there, how do you decide where to place your bets?”
He didn’t hesitate. In so many words, he said:
The only difference between me and a retail investor is that if I want to talk to the CEO, I just pick up the phone. I can have lunch with the people running the company. I invest in people I trust to deliver results.
That answer has been echoing in my head ever since.
We’re living through an AI gold rush. Every week, a new startup promises to “redefine the future,” and most of them are doing some version of the same thing. Ideas are cheap. The winners will be the ones who execute relentlessly—those who can take a generic concept and turn it into a market-dominating business.
A couple years ago, I invested in Wakewater, co-founded by Dan Bartek and Cam McDonald. On paper, the products aren’t revolutionary—flavoured caffeinated sparkling water. Now, they’ve moved into electrolytes and have other things cooking.
But I didn’t invest in the product. When I heard that Dan would be moving full-time to Wakewater as soon as the sale of Ace was complete, I invested in Dan and his ability to execute.
Here’s why:
Before Wakewater, he co-founded Iconic Brewing, which merged with Ace Beverage Group and was ultimately acquired by Corby Spirit and Wine.
Iconic didn’t win because vodka sodas or beers were groundbreaking. They won because they out-executed everyone else.
If my memory serves me, at the time of acquisition, they had around 30 SKUs and a system for launching new products faster and more efficiently than their competitors.
Speed and operational discipline—not a unique recipe—made them a market leader.
This is the essence of early-stage investing: products can be copied, but systems and people who can execute at speed create real defensibility.
What does this means for AI Investing?
I see the same pattern playing out in AI today. Most startups are built on similar foundations: large language models, off-the-shelf APIs, and an application layer. Their initial “big idea” rarely matters as much as:
Founder-Market Fit – Does the founder deeply understand the problem they’re solving?
Execution Velocity – Are they shipping fast, iterating, and learning from customers?
Team Attractiveness – Can they pull in talent and partners to move faster than competitors?
Path to Defensibility – Can they build a moat, whether it’s proprietary data, distribution, or operational excellence?
Industry Knowledge - Every industry has its nuances. The leadership team needs to know how to navigate it.
The AI companies that win won’t necessarily have the flashiest pitch deck. They’ll have founders who outwork, out-learn, and out-execute the competition—just like Dan did in beverages.