Build low-fidelity proofs to test feasibility, then advance the survivors to medium and high-fidelity prototypes on real production data, in the hands of real users, and decide quickly which ones earn production investment and which get killed. Personally produces working artifacts (data pipelines, ontology and semantic models, notebooks, agent workflows, and functional user interfaces) rather than only specifying them, and is fluent in Python, SQL, or equivalent.