When building is cheap, judgement is the product.
I'm a B2B AI and SaaS product leader. For ten years I've turned operational complexity into products that scale. My edge is the decisions: what to build, what to cut, what to kill, and how we'll know it worked. This site, and the agent on it, are the proof.
That's the idea this site is built on — read the essayFive moves I make on every bet — each one grounded in a real case below, not a slide.
Choose. What is worth building. Read the market, run a dynamic SWOT, size with RICE, ask why this world does not exist yet.
Monica AI: The First RAG Product in My Category
What it actually takes to ship AI into a workflow customers already trust.
AI-Native Service Desk: Recovering $25K per Technician per Year
We shipped it fast, technicians wouldn't trust it, and the rebuild is the real story.
The Strategic Pivot: From Cost-Play to a Growth Platform ($0 → Multi-Million ARR)
I studied the market from the outside in, found a gap nobody had filled, and built (and sold) the platform into it.
Smart Tracker: A Real Innovation That Failed on Sequencing
The feature was right. The order I shipped it in was wrong, and the data that proved it became the year's best brand asset.
When Building Is Cheap, Judgement Is the Product
AI made building and ideating almost free. The bottleneck moved to deciding what to build, what to strip, and what to kill. That is the job now, and it runs as five moves.
AI Pricing Is Product Strategy
Why I bake AI into the unit that grows when the customer wins, instead of metering it.
How I Scope a 0→1 Bet
A new product bet isn't a leap of faith. It's a sequence of cheap questions asked in the right order.
The System of Record Wins the Agent Era
When building an agent gets trivial, the platform that owns the data and the workflow owns the ecosystem. So I bet on the marketplace.
How I Built This Site's Agent and Tuned It With Evals
A walkthrough of the agent on this site: how it stays grounded, the failure I found and fixed, and the evaluations and analytics that keep it honest.
The Operating System Behind a Strategy
I'm obsessed with strategic synergy: getting every function to run the same bet, from the value proposition down to the metrics.
Contracts 2.0: The Profitability Wedge
I went looking for it in person, found a units problem nobody had solved, and turned it into the most accurate profitability engine in the category.
When Build and Buy Both Failed
Buying didn't clear the bar. Building wasn't viable. So I designed a third path: a partnership engineered to feel built-in.
Investor-Facing Product Lead
I've been the product voice in the room across every round from Seed to Series C. Investors aren't buying features. They're buying a thesis, and evidence it's already coming true.
Disagree and Commit: Holding the Vision
How I hold a product bet through real pressure, and how I disagree with founders without it turning into a standoff.
The market scan and platform thesis for our next major bet at SuperOps: an AI-native, autonomous IT-operations platform for the mid-market. Mostly outside-in research, competitive positioning, and a discovery program designed to kill the idea cheaply before we commit engineering to it.
What it actually takes to make AI deliver value instead of just demo well: building it inside the workflow, with eval loops that keep it honest and measurable. That's the thread behind the AI-native service-desk work I do, and it runs out into how AI is rewriting the economics of software and what strategy and innovation look like in markets AI is reshaping.
Short essays on AI product strategy. Lately: why AI pricing is a product decision rather than a packaging one, and how I scope a zero-to-one bet.
Let's talk.
Whether you're hiring, building, or just curious about the work.