• Own the Lab bet portfolio. Size opportunities, set entry/exit criteria, and make decisive scale/iterate/kill calls. • Frame experiments around the single riskiest assumption. Define kill criteria before building. Choose the right fidelity (prototype, spike, wizard-of-oz, no-code, live pilot). Ship fast and protect learning speed. • Synthesize results into opinionated recommendations. Communicate what was tested, learned, and what remains unknown. • When a bet shows strong signal, prepare validated hypotheses, evidence packs, risks, and a proposed scaling model. Transfer ownership fully. • Source and close lighthouse pilots with clear scope, metrics, and off-ramps. Identify enabling partners and join strategic calls to move pilots to business validation. • Build a repeatable Lab Operating System (pipeline reviews, kill reviews, demo days, post-mortems). • Use AI tools to accelerate research, synthesis, and prototyping. Explore AI-enabled product ideas with a realistic lens on cost, data, and accuracy. Publish decision memos and share failed experiments openly.

• Own the Lab bet portfolio. Size opportunities, set entry/exit criteria, and make decisive scale/iterate/kill calls. Maintain a visible exploration backlog. • Frame experiments around the single riskiest assumption. Define kill criteria before building. Choose the right fidelity (prototype, spike, wizard-of-oz, no-code, live pilot). Ship fast and protect learning speed. • Synthesize results into opinionated recommendations. Communicate what was tested, learned, and what remains unknown. Kill zombie initiatives — every experiment ends with a decision. • When a bet shows strong signal, prepare validated hypotheses, evidence packs, risks, and a proposed scaling model. Transfer ownership fully. • Source and close lighthouse pilots with clear scope, metrics, and off-ramps. Identify enabling partners and join strategic calls to move pilots to business validation. • Build a repeatable Lab Operating System (pipeline reviews, kill reviews, demo days, post-mortems). • Use AI tools to accelerate research, synthesis, and prototyping. Explore AI-enabled product ideas with a realistic lens on cost, data, and accuracy. Publish decision memos and share failed experiments openly.

• Own the Lab bet portfolio. Size opportunities, set entry/exit criteria, and make decisive scale/iterate/kill calls. Maintain a visible exploration backlog. • Frame experiments around the single riskiest assumption. Define kill criteria before building. Choose the right fidelity (prototype, spike, wizard-of-oz, no-code, live pilot). Ship fast and protect learning speed. • Synthesize results into opinionated recommendations. Communicate what was tested, learned, and what remains unknown. Kill zombie initiatives — every experiment ends with a decision. • When a bet shows strong signal, prepare validated hypotheses, evidence packs, risks, and a proposed scaling model. Transfer ownership fully. • Source and close lighthouse pilots with clear scope, metrics, and off-ramps. Identify enabling partners and join strategic calls to move pilots to business validation. • Build a repeatable Lab Operating System (pipeline reviews, kill reviews, demo days, post-mortems). • Use AI tools to accelerate research, synthesis, and prototyping. Explore AI-enabled product ideas with a realistic lens on cost, data, and accuracy. Publish decision memos and share failed experiments openly.

• Portfolio & Strategy: Own the Lab bet portfolio. Size opportunities, set entry/exit criteria, and make decisive scale/iterate/kill calls. Maintain a visible exploration backlog. • Experimentation: Frame experiments around the single riskiest assumption. Define kill criteria before building. Choose the right fidelity (prototype, spike, wizard-of-oz, no-code, live pilot). Ship fast and protect learning speed. • Investment Decisions: Synthesize results into opinionated recommendations. Communicate what was tested, learned, and what remains unknown. Kill zombie initiatives — every experiment ends with a decision. • Handoffs: When a bet shows strong signal, prepare validated hypotheses, evidence packs, risks, and a proposed scaling model. Transfer ownership fully. • GTM & Partnerships: Source and close lighthouse pilots with clear scope, metrics, and off-ramps. Identify enabling partners and join strategic calls to move pilots to business validation. • Team: Build a repeatable Lab Operating System (pipeline reviews, kill reviews, demo days, post-mortems). • AI & Transparency: Use AI tools to accelerate research, synthesis, and prototyping. Explore AI-enabled product ideas with a realistic lens on cost, data, and accuracy. Publish decision memos and share failed experiments openly.