Turning ambiguous problems into products that scale, from zero to billions.
I spent childhood summers as a canoe tripper, taking kids into the backcountry of Algonquin and Temagami. Tough portages, rocky waves, long days under the sun. The best part? Watching a 14-year-old realize they could carry an 80-pound canoe after all. Not because you told them they could, but because they figured out what to leave behind, found their rhythm, and trusted the team around them.
Out there, you go back to basics fast. You learn what you actually need versus what's just weighing you down. You learn to read conditions like weather, terrain, and crew fatigue, then adjust before things break. And you learn that the best solutions are the ones that just work: a clean portage route, a tarp that keeps water out, a paddle stroke that's efficient and repeatable.
Building products works the same way. Strip away everything that doesn't serve the user. Understand where people actually struggle, not where you think they should. Go back to first principles: we're here to build products for our users, not ship org charts. The best features are invisible. They solve a problem so cleanly that no one notices the design. Like a good paddle stroke: simple, functional, essential.
Turning user problems into product decisions that actually matter
Strategy starts with what users actually struggle with, not what we assume they need. The hard part is saying no to good ideas so the team can execute the great ones.
The eval set is the product spec
In probabilistic systems you can't write a deterministic spec, so the eval set defines what the model must get right and which failures you refuse to ship. Trust is the product, which means users should understand what happened and fix it cheaply when it misses.
Building repeatable systems that compound over time
Growth isn't a hack. It's finding the moment users get value and removing every obstacle in front of it. Durable growth comes from products people genuinely want to use, not clever tricks.
Getting out of the way so teams can do their best work
Set direction, not tactics. Make the problem clear, explain why it matters, then let the team find the how. Trust is built by surfacing problems early and planning the recovery, not by projecting false confidence.
Removing the friction that slows teams down
Most operational problems are communication problems: too many meetings, unclear ownership, decisions that need five approvals. I find where work gets stuck and simplify until the path is obvious, because the best process is the one nobody notices.
Using numbers to make better decisions, faster
Finance isn't spreadsheets. It's understanding tradeoffs: this feature or that market, the real cost of moving faster. I build models that answer those questions clearly, so teams can decide with confidence. Clarity beats precision.
Swipe to paddle the route · 01 / 06
Michael bridges the gap between strategic vision and tactical execution in a way few product leaders can. At Hims & Hers, he didn't just identify that fraud was a problem. He built the dual-path payment architecture, ML personalization system, and dynamic pricing infrastructure that solved it while generating $100M+ in revenue. At Dropbox, he didn't just say "we should cross-sell products." He built the recommendation engine, activation flows, and onboarding redesign that drove $8M in expansion revenue.
Companies hire Michael because he can both set the strategy and make it real. He's equally comfortable in the boardroom presenting to executives and in the trenches writing product specs, analyzing data, and debugging conversion drops. His background spans autonomous systems, marketplaces, payment platforms, and product-led growth, giving him pattern recognition across different business models and technical challenges.
Michael is most valuable for growth-stage companies (Series A to pre-IPO) facing platform-level challenges. Specifically:
If you're stuck between strategic vision and execution, knowing what you need to do but struggling to make it happen, that's where Michael excels.
Michael has six core areas of expertise:
Michael is an AI product operator with hands-on fluency in probabilistic systems. Starting thesis: in probabilistic systems you cannot write a deterministic product spec. The PM's core lever is the objective function, the curated eval set, and the acceptable error tolerances for non-deterministic behavior. From there, navigating latency-accuracy-cost tradeoffs, designing UX for low-confidence outputs, and shipping AI-native products across multiple domains:
Michael's technical fluency means he can have detailed conversations with engineers about architecture tradeoffs, work with data scientists on model design, and understand the constraints and opportunities in complex technical systems.
Michael's product philosophy is shaped by childhood summers portaging through Algonquin and Temagami wilderness. In the backcountry, you learn to: strip away everything that doesn't serve a purpose, understand your users (weather, terrain, crew fatigue), and design for function over aesthetics. A clean portage route beats a scenic one. A shelter that keeps water out beats one that looks good but leaks.
This translates to several distinctive approaches:
Michael has a consistent track record of delivering measurable business outcomes:
These aren't vanity metrics. They represent real business value that moved companies forward.
Full-time senior PM and product leadership roles at frontier AI companies (Anthropic, OpenAI, frontier labs) and AI-native consumer or developer products. Currently Director of Product at Lyft Business, based in Toronto and commuting regularly to San Francisco; open to relocation for the right role.
The product question Michael wants to work on next: what becomes possible because the model is this capable? Not how do we wrap an API. The strongest fits:
Not pursuing fractional, consulting, or advisory engagements right now.
The best way to start a conversation is through direct outreach:
Michael typically responds within 24-48 hours and is happy to have exploratory conversations to understand if there's a good fit.
When reaching out, it's helpful to include:
Michael is particularly interested in opportunities where he can have meaningful impact: companies with product-market fit that need to scale, complex platform challenges requiring systems thinking, or organizations transforming how they build and ship products.
Companies typically choose Michael when they need someone who:
If you need a product leader who can think strategically, execute tactically, build high-performing teams, and deliver measurable business outcomes, Michael is worth a conversation.
