I co-founded LemonStand and sold it to Mailchimp, where I went on to lead commerce. I later spent five years as CEO of Orbit, part of publicly traded Tiny. Today I’m building AI products and exploring what to take on next.
I co-founded LemonStand and built it with our team into an e-commerce platform serving hundreds of web design and development agencies, with GMV in the low hundreds of millions. Mailchimp acquired the company, and our shareholders made a good return on their investment.
LemonStand in detailI led commerce at Mailchimp, where we built a team of around 60. That work eventually evolved into Mailchimp Stores, which launched to millions of users.
Mailchimp in detailFor five years as CEO of Orbit, I ran a portfolio of Shopify apps with full P&L responsibility. We grew Wholesale Hub at double-digit rates year over year and built a new app in a new category, quickly winning leading outdoor brands as customers.
Orbit in detailAI coaching for trail and ultra runners.
I built Ontrack from idea to working beta. It connects training plans with Strava activity and gives runners a way to check in when life changes their training.
The planner follows coaching rules in code, so I can inspect how a plan was put together. AI supports the coaching conversation.
Week 14 of 24
Peak
89%
Avg complianceBlack Bear 50K · 10 weeks to go
AI made building cheap. It didn’t change what makes products win.
AI made producing work cheap: code, copy, prototypes, analysis. What’s scarce is knowing what’s good, which bet to take, and what to cut. I own every decision I put in front of a team, including anything an agent helped produce. I have to understand it well enough to question the reasoning and say “this is wrong,” with a why.
The reliable path begins with a real, painful problem, not a clever solution hunting for one. The market is a choice worth making on purpose: who exactly, and why them. For a startup it’s existential. In an existing company the market is usually already set, so the discipline moves to which problems you solve inside it. Retention is still the truest read on whether the problem was real.
Use the product yourself, then watch customers use it on their own: they’ll struggle with things you’ve learned to work around. Support conversations explain what’s behind the numbers. Complaints mean they care enough to complain; silence is the red flag.
Every bet has one assumption everything else rests on. Name it, say what result would change the plan, and get the smallest possible test in front of customers. A forty-page PRD can still leave that assumption untested.
Every feature is a long-term relationship: you maintain it, support it, and end up defending it. A product needs a clear reason for the right customer to choose it. That guides what makes the cut and which details are worth another day on. Pick a few things and get them very right.
For non-deterministic AI products, the eval is the spec: concrete examples of great and broken, a way to surface the failures that matter, and proof that a change actually helped. For deterministic work, plain acceptance criteria will do. Either way, check the results against what customers actually experience. The score is not the goal.
A great product with no distribution or broken economics is a hobby, not a business. How customers find you should shape what you build, so choose the route early. Products that spread by word of mouth need instant value and a reason to invite. Products sold through a sales team look completely different. Price, cost to serve, and the path to the customer have to work by design. AI made serving every user expensive, so growth has to compound through retention.
The best products come from small teams iterating fast, close to the customer. Give the team the business context, including what the work has to earn, so they can decide without waiting for me. I stay in the details with them. Judge the work by outcomes: do customers keep using it, and does the math work?
Let’s talk about what you’re building.
I want to work on something I believe in and take responsibility for making it succeed. I’m especially interested in AI products. If you need someone who can help shape the direction and build with you, I’d like to talk, even if there isn’t a defined role yet.
South Okanagan, BC · Pacific Time