Discovery & Research

    Falling in Love with
    the Problem.

    Continuous discovery beats one-off research, every time.

    De-risking product decisions through weekly customer touchpoints, evidence-based bets, and rapid prototyping.

    From Assumption to Evidence

    Most product failures don't come from bad execution, they come from building the wrong thing. The strongest teams don't guess; they reduce risk before a single line of code is written. That means actively testing four risks: value (will they use it?), usability (can they use it?), feasibility (can we build it?), and viability (does it work for the business?).

    I run discovery as a continuous practice, not a phase. Weekly customer interviews, opportunity solution trees to map the problem space, and rapid prototypes that get in front of users before commitments are made. Every assumption becomes a question; every question becomes a test.

    The result is a product team that ships with conviction. Stakeholders see the evidence behind the roadmap. Engineers know the problem they're solving, not just the feature they're shipping. And users get something that genuinely makes their life easier.

    The Discovery Loop

    01

    Frame the Outcome

    Start with a clear business outcome, not a feature. Define the metric that signals success and the user behavior we expect to change.

    02

    Map Opportunities

    Through interviews, analytics, and session replays, surface the real customer problems behind the desired outcome. Build an opportunity tree to prioritize.

    03

    Prototype & Test

    Generate multiple solutions, prototype the most promising ones, and validate with real users, fast. Kill weak ideas before they become roadmap items.

    04

    Ship & Measure

    Ship in slices. Track the outcome metric, not just the output. Feed learnings straight back into the next discovery cycle.

    How I Work

    Talk to Users Weekly

    Direct customer contact every single week. No proxy, no filter, the team hears the user themselves.

    Opportunity over Solution

    Map the problem space before jumping to solutions. Multiple ideas per opportunity, not one feature per request.

    Test Assumptions Cheap

    Use prototypes, fake doors, and concierge tests to validate before building. The best discovery costs hours, not sprints.

    Quantitative meets Qualitative

    Analytics tells you what; interviews tell you why. Combine both to build conviction in every decision.

    Toolkit

    Tools I Reach For Daily

    User InterviewsOpportunity Solution TreesPRDProductBoardJira Product DiscoveryFigma PrototypesHotjarMicrosoft ClarityGoogle AnalyticsA/B TestingUsability TestingSurvey Research
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