Building better products by asking better questions.
I've spent two decades building, scaling, and occasionally burying software startups. These days I'm VP Product at Property Vista, where we're building property and asset management software around AI, not bolting it onto an existing platform. I'm also a startup advisor to early-stage founders on product strategy and finding product-market fit.
Previously
Before Property Vista, I was CPO at Koru Ventures, an incubator where I led product across AI startups in different verticals, including an AI legal bill review platform we built from scratch. Before that, as SVP at Uberflip, I led product and services through $20M+ ARR and a successful exit. Earlier, I helped build and sell Honeybee, Canada's fastest growing digital health insurance platform, and before that I co-founded Forewards, which won a growth award, then imploded (and taught me more than the others combined).
This site is my public scratchpad. I write about product-market fit, org design, and why most enterprise AI strategies are built to fail.
Writing
All posts →- Stop Demoing. Start Listening Out Loud.
- I've Seen This Movie Before
- Chat Lets Us Rethink Forms and That's a Bigger Deal Than It Sounds
- Nobody Wins Overnight. They Just Wait Long Enough for the World to Catch Up.
- Which SaaS Competitive Advantages Still Hold Up in the AI Era
- When the Product Is Fine and Everything Is Still Broken
If users can ignore the AI, they usually will.
Playbooks
All playbooks →- The Whale Deal Playbook: How to Evaluate a Sales Opportunity Big Enough to Rewrite Your RoadmapA two-gate framework for evaluating sales deals big enough to rewrite your roadmap: fit before size, then economics, build, and dependency risk.
- Signal-First v0: A Founder's Playbook for Building Less and Learning FasterFive constraints for building less and learning faster in the AI era, from taking an AI legal bill review platform from napkin to launch.
- From Roadmap to Results: Building an Outcome-Driven AI Operating SystemReplace your feature roadmap with an outcome-driven AI operating system: 2–3 outcomes, two-week thin slices, clear decision rules, and light governance.
- Ship-to-Learn Playbook: Two-Week Experiments to Find SaaS PMFA two-week experiment rhythm for finding SaaS product-market fit: questions-first problem statements, outcome targets, GTM co-ownership, and decision rules.
Elsewhere
- Pattern Matching Innovation ↗Why the best ideas might not come from customer pain.TPMA
- How AI is Disrupting SaaS ↗How AI is disrupting the SaaS model and creating a new era for enterprise systems.LinkedIn
- Lessons From America's Game ↗What baseball taught me about startups and resilience.Medium
- ProductRPG ↗A little side project that gamifies my answer to "How do I get into product management?"Project
About
I've been a founder, CPO, and operator through venture raises, exits, and implosions. Outside of work I coach youth sports, lift heavy things, and occasionally call BS on "best practices" that haven't aged well.
My operating philosophy is simple:
- Solve the right problem.Most product failures happen before a line of code is written.
- Move faster than the org chart wants you to.Speed is a competitive advantage and a cultural choice.
- Align execution to outcomes, not activity.Ship to learn, not to check boxes.
Advising & contact
If you're an early-stage founder working on product strategy or product-market fit, here's how I work with founders.
I'm always open to smart conversations and good startup problems. Email me or find me on LinkedIn.