• Identify opportunities emerging from new technologies, AI, data, platform capabilities, or infrastructure shifts • Translate weak signals and technical possibilities into clear product hypotheses • Explore ideas before there is a clear buyer, category, or demand signal • Maintain an exploration backlog with risks, assumptions, and learning goals • Frame experiments around the single riskiest assumption • Define explicit kill criteria before building anything • Execute scrappy prototypes, MVPs, and pilots with minimal scope • Synthesize results into opinionated recommendations: Scale / Iterate / Kill • Clearly communicate what was tested, what was learned, and what remains unknown • Maintain a visible Lab portfolio: what's being explored, why, and what the signals say