Chief Program Officer → Chief Product Officer at a global startup accelerator.
Architected a strategic pivot from generalist accelerator to five-sector platform. Redesigned how MassChallenge captures, qualifies, nurtures, and places volunteer experts with startups — with AI-native tools built as core infrastructure, not as add-ons. This chapter isn't in past tense yet. It's the chapter I'm writing.
A global accelerator looking for its next chapter, right as generative AI landed.
MassChallenge runs one of the largest early-stage startup accelerators in the world — 16+ years, 5,000+ alumni, thousands of mentor touchpoints. By early 2024, the organization was ready for a structural pivot: from generalist accelerator to a sector-focused platform concentrated on five high-impact verticals — health, climate, sustainable food, financial inclusion, and security & resiliency.
I joined as Chief Program Officer with responsibility for Programs, Community, and Marketing — roughly 40% of the organization's headcount and a $3M operating budget. The remit was to architect the pivot, redesign the programmatic experience for founders and mentors, and rebuild the tooling layer underneath everything. I was promoted to Chief Product Officer in September 2025 as the platform vision expanded.
The timing was right for something I'd been waiting to do. Generative AI had landed commercially in late 2022. For the first time, the tooling cost curve for a non-technical team to build meaningful internal software had collapsed. Same pattern I'd seen at One Degree Solar with LEDs and at Formlabs with desktop SLA — a technology going from expensive and specialist to cheap and generalist. MassChallenge was a place where that unlock could matter in weeks, not years.
Architected a generalist-to-sector-platform pivot across strategy, team, stack, and operating model.
The pivot wasn't cosmetic. We redesigned how the organization qualified and onboarded startup cohorts, how programs were delivered across five sectors, how the mentor network was organized, and how we measured outcomes. Some of that was structural. More of it was operating discipline — the weekly cadence, accountability design, and cross-functional handoff work that either compounds or collapses an organization depending on how seriously you treat it.
The board directed a parallel shift toward more mature startups — companies with revenue, traction, and near-term capital needs, rather than pre-product concepts. 2025 cohorts represent $96M in collective revenue and $260M in funding — roughly 2× prior-year totals.
We revamped the flagship Early Stage program, moving from a one-size-fits-all curriculum with 120+ startups to smaller, sector-specific cohorts of 25–35 founders each — anchored by personalized mentorship and advanced support from industry Experts in Residence. For the first time, we required clear performance and commitment from our startups, and we removed teams from the program when necessary. We overhauled internal operations, empowered the Community team to vet and nurture our pool of volunteer judges and mentors, and reimagined the digital tools — optimizing the Accelerate platform for applications, judging, and matching, and building out the new MC Hub for program delivery and alumni engagement.
The result was a 90% average CSAT score from external stakeholders across every touchpoint, and a measurably happier, higher-performing internal team.
The most structurally important piece of work was redesigning how MassChallenge captures, qualifies, nurtures, and places volunteer experts with startups — what we call the Network. At scale, an accelerator isn't really in the training business or the capital business. It's in the network-orchestration business: matching the right mentor, investor, or operator to the right founder at the right moment.
The old model had legacy constraints. Mentor qualification was informal. Matching was human-intensive and inconsistent. Placement data was scattered across tools. I redesigned the full lifecycle — capture, qualify, nurture, place — and built the AI-native tools underneath to operate it at scale. This is the work that's most analogous to portfolio operations inside a venture firm, which is where my thinking about what comes next is increasingly oriented.
Not a "using AI" initiative. An AI-native operating layer.
By 2024 I was building functioning AI tools inside MassChallenge — not commissioning them, not vendor-managing them, building them. Python, pandas, React, Anthropic API, Netlify. The specific tools matter less than the stance: AI infrastructure is now a core operating capability, and I wanted to be the person in the organization who treated it that way.
MC Alumni Explorer. A full-stack search tool indexing all 4,486 MassChallenge alumni companies, deployed on Netlify. Anyone on the team can find relevant companies by industry, stage, geography, or fuzzy semantic search. Hosted live.
LLM sector classifier. Replaced a keyword-based classification approach that had a 26% error rate with an LLM-based pipeline that cut error rates dramatically and made the underlying data usable for the first time.
AI content generation tool. Built on the Anthropic API with Netlify serverless functions. Handles specific content workflows across the Community and Marketing teams.
Five-part LinkedIn data journalism series. A published analysis of 16 years of MassChallenge portfolio data — sector patterns, survival rates, capital raised, geographic distribution. Used internally for strategy and externally for positioning.
2026 marketing framework. An Excel planning framework and an interactive HTML dashboard. Replaces what had previously lived in static slide decks.
"Rare Humans" gala shortlist tool. An internal tool for identifying and shortlisting gala honorees based on structured criteria across the alumni base.
What this changed about the work, more than any single tool, is that AI infrastructure now sits inside my scope as an operator — the way cloud infrastructure or analytics sat inside a prior generation's. Understanding what these tools can and can't do, where they fit in an operating stack, and how to deploy them for real leverage comes from building them, not from reading about them.
Network orchestration is the real work of an accelerator. The Network redesign is the thing I'm most proud of at MassChallenge because it's the thing that most directly affects founder outcomes. Placing the right person at the right moment is what an accelerator does; everything else is scaffolding.
AI builder skills change what an operator's scope looks like. Being able to ship working tools — not just commission them — changes what kinds of bets are feasible and how fast a lean team can move. That's the capability I've been building inside this chapter.