- Own end-to-end due diligence for a portfolio of potential AI-enabled programs, from rapid screen through deep dive, and recommend what should advance, pause, or be set aside.
- Frame decision-relevant questions, identify the crux of each opportunity, and determine what evidence could change the recommendation.
- Build evidence reviews, back-of-the-envelope and full cost-effectiveness estimates, risk assessments, landscape scans, and early operational and technical scoping.
- Write calibrated decision memos for 2AI leadership, including confidence levels and reasons for recommendations.
- Co-design pilots with leadership and program teams, defining scope, sample, measurement, cost tracking, timeline, and success and stop criteria.
- Travel to prospective pilot locations to assess partners and delivery channels, negotiate scopes with implementers, and help stand up pilot infrastructure.
- Build reusable data pipelines, monitoring dashboards, evaluation templates, and partner MOUs.
- Refine the Incubator’s screening criteria, activities, sequencing, roles, and supporting tools based on real cases.
- Build, test, and document AI workflows using frontier AI tools, including Claude Code, agentic pipelines, and LLM-assisted literature synthesis.
- Help source, assess, and onboard future Incubator team members.