PROOFRUN RESOURCES
Product Discovery in practice
Articles, guides and comparisons to help you frame product questions, evaluate evidence and revisit decisions as new information emerges.
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The evidence-to-decision gap in product teams
Product teams collect feedback, research and data, but that does not guarantee evidence reaches the decisions it should inform.
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The evidence-to-decision gap in product teams
Product teams collect feedback, research and data, but that does not guarantee evidence reaches the decisions it should inform.
Read →A practical boundary for AI in Product Discovery
A practical way to use AI for research and synthesis while keeping evidence quality, product judgment and accountability explicit.
Read →Assumptions vs evidence in Product Discovery
A practical way to separate what a team believes from what the available evidence actually supports before making a product decision.
Read →How AI changes the product decision bottleneck
AI is increasing software delivery throughput. Product teams now need stronger reasoning around evidence, uncertainty and the decisions that guide that execution.
Read →How much evidence is enough for a product decision?
Evidence sufficiency depends on whether the available signals separate hypotheses, reduce important uncertainty and leave the remaining gaps visible.
Read →How to use ChatGPT in Product Discovery
A practical guide to using ChatGPT for Product Discovery while keeping sources, hypotheses, uncertainty and research structure explicit.
Read →How to use GA4 as evidence in Product Discovery
GA4 can show what happened in the product. Product Discovery connects those behavioral signals to questions, hypotheses and other evidence.
Read →How to validate a product hypothesis before building
A practical way to turn an idea into a hypothesis, gather evidence and understand what still needs to be investigated.
Read →Proofrun vs ChatGPT for Product Discovery
A practical comparison of a general-purpose AI research workspace and a structured Product Discovery workflow for evidence and decisions.
Read →Should we build this? A product decision framework
A practical framework for deciding whether a feature request deserves commitment, a smaller experiment, reframing, deferral or further investigation.
Read →What AI-generated PRDs still need from Product Discovery
AI can generate a polished PRD quickly. Product Discovery still has to connect the problem, assumptions and evidence before the document guides execution.
Read →Product Discovery at scale: what changes as your product team grows
More PMs and squads increase product capacity. They also increase the amount of context, evidence and reasoning that needs to travel across the organization.
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