pm-product-discovery

You can summarize interview transcripts into structured, evidence-graded product insights by processing raw text through the framework to extract pain points, opportunities, and assumptions automatically.

Testing product assumptions from user research involves analyzing interview transcripts to extract hypotheses and then using the framework to design targeted experiments with clear evidence-quality signals.

Coordinating product discovery across multiple teams requires a structured framework that standardizes interview analysis, assumption validation, and experiment design to ensure consistent, evidence-graded outputs.

Yes, local overrides take precedence over upstream configurations, enabling customization of the product discovery workflow to fit specific team needs without modifying the core framework.

No, this product discovery skill operates independently without external dependencies, allowing you to analyze transcripts and design experiments directly within your local environment.

Designing experiments to validate product ideas involves processing structured insights from interview transcripts to formulate testable hypotheses and generate clear evidence-quality signals for your findings.