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From Researcher to Builder: Vibe Coding Tomer Sharon's Method Finder
Summary
Tomer Sharon's question-first framework still matters more now that products can be built faster than ever. Tomer spent his career making user research practical and accessible for product teams who did not have a research background. He passed away in 2025. The Method Finder is a tribute to his work and an attempt to carry it forward: a tool that matches any team's research question to a best-fit method from an 18-method taxonomy, in five prompts or less. In this session, I will show you the tool, explain the framework behind it, and walk through the vibe coding process I used to build it: Replit for development, Claude and NotebookLM for editing. You will leave with access to the tool, the PRD, and a practical understanding of how to apply this workflow to your own R&D practice.
Key Insights
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Tomer Sharon’s main problem was not that product teams ask bad questions, but that they answer them with invalid, biased evidence such as opinions or internal feedback.
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The timing of research within the product development lifecycle is crucial; early-stage research has the greatest impact by reducing risk before decisions lock in.
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Tomer distilled over 400 customer questions into eight core question groups, each mapped to one primary research method plus alternatives.
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Julia Lighty enhanced Tomer’s framework by adding assessment-phase questions and linking methods to product risk categories: feasibility, viability, desirability, and usability.
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The Method Finder uses AI to map plain language user goals to research methods, clarifying ambiguous questions through interactive prompts.
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Research expertise can be transformed into software tools like the Method Finder, making frameworks more accessible and scalable for product teams.
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AI assists in executing research tool development but depends on human expertise for problem definition, decision-making, and user context.
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Usability testing remains the most strategic and impactful method for evaluating live products, with many variants to choose from.
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Researchers are uniquely positioned to build AI-powered tools because of their understanding of human behavior, workflows, and decision processes.
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A question-first approach reduces the barrier for non-researchers to start appropriate user research by focusing on what teams need to learn, not which method to pick.
Notable Quotes
"Nothing beats usability testing."
"Research isn’t about producing reports, it’s about meeting teams where they are so that they can make better decisions."
"Teams ask good questions; the problem was how they were answering them—often with opinions or coworkers, not valid evidence."
"Timing matters because early decisions shape everything that follows—organizational momentum and technical architecture lock in."
"Research is essentially reducing risk—avoiding building the wrong thing in the first place."
"Instead of creating another playbook, what if we could turn research expertise into software so teams can interact with knowledge?"
"AI scales research knowledge, but not judgment. It makes expertise easier to apply but does not replace it."
"If someone doesn’t know their question, the recommendation is an in-depth interview because it’s the easiest and most versatile method."
"Product teams think in questions, not methods—that’s why a question-first framework is powerful and needed."
"Researchers are evolving from just doing research into building tools that scale knowledge and impact."
Or choose a question:
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