I help organizations turn insight into institutional change — building the teams, programs, and operating systems that make strategy executable.

When I joined Newlab in 2021, design and strategy was a two-person function without formal operating systems or a clear institutional mandate. I built the performance management infrastructure, scaled the team from two to ten, and repositioned the function from internal support to a growth engine. That expansion helped grow the Ford relationship into a 3-year, $9M engagement and establish strategy and design as a core capability across the organization.

I also led cross-sector partnerships beyond New York — including work with Shell, LSU, and partners that contributed to a $450K DOE grant in carbon removal, helping establish the foundation for what later became Newlab New Orleans.

The assignment sounded straightforward: quantify Newlab's impact. The real challenge was structural. Newlab had grown rapidly across multiple functions with different theories of change — some focused on commercialization, some on economic development, some on network value. Before measuring impact, we first needed to resolve which of these narratives was primary.

I led the leadership team through an alignment process to establish a shared theory of value creation, introduced the CRANE tool to model projected GHG reductions from the startup portfolio, and built the institutional narrative that made Newlab's work legible to partners, funders, and civic stakeholders. The report mattered. But the deeper outcome was alignment — people began making decisions from the same map.

New York City faced a genuine crisis: tens of thousands of delivery workers were charging e-bikes in apartments, contributing to fires across the five boroughs. We reversed the typical municipal procurement playbook — mapping delivery workers' route constraints and operational needs before looking at technology solutions. We translated these human parameters into technical criteria, managed competitive open calls for tech partners, and monitored live urban pilots.

Most convenings optimize for attendance. This one optimized for action. Participant selection, room design, facilitation, and follow-through were treated as variables to engineer collaboration rather than discussion. Partnership generation became an explicit success metric measured before, during, and after the event.

Convenings are infrastructure.

True enterprise AI strategy is a question of political economy before it is a technical one — about who bears the cost of algorithmic error, who has the power to audit systems, and how public and private actors distribute accountability. I led 25+ expert interviews spanning the Partnership on AI, the NYU Governance Laboratory, Harvard researchers on race and algorithms, Tech Policy Press, the Columbia University Chief Data Scientist, the German AI Association, and founders of relevant startups. The research surfaced 24 solution areas across algorithmic bias, misinformation, and online harassment.

A global consumer goods manufacturer faced rising tariff exposure and geopolitical volatility across its supply chain. The challenge was not identifying risks — each function had partial visibility. The challenge was converting fragmented insight into coordinated action across supply chain, finance, and commercial leadership.

Getting senior leaders from three functions to agree on priorities is a harder problem than modeling the exposure. The deliverable was not analysis but governance: ownership, mitigation actions, escalation triggers, and decision rights.