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To validate product assumptions, you can use low-effort experiments like prototypes, A/B tests, spikes, and fake-door methods to gather structured metrics and success criteria without heavy engineering.

Lightweight validation methods for existing products include designing prototypes, running A/B tests, executing technical spikes, and deploying fake-door tests to prioritize ideas and maximize learning with minimal effort.

Yes, you can use fake-door tests and A/B testing for product feature validation. These methods help specify input requirements and output structured experiment definitions to measure user interest accurately.

Designing experiments to validate assumptions requires specifying your product idea and its assumptions. This process outputs structured experiment definitions with assumptions, designs, metrics, and success criteria to guide discovery.

The best way to prioritize experiments and select metrics is to evaluate each assumption against low-effort methods like prototypes and spikes, ensuring you maximize learning and inform execution plans efficiently.