Situation
The brief was open-ended: produce thought leadership content on the transformation happening in the US small business market.

Approach
Starting with the market rather than a hypothesis, I conducted extensive secondary research across government data, industry reports, and trade sources, drawing on two years of primary research with small business owners to ground the narrative in real examples. From there, I identified three converging forces to build story around: an aging owner population, accelerating AI adoption, and the collapse of barriers that had historically made small businesses difficult to serve at scale.

Outcome
A twelve-page market intelligence paper synthesizing more than forty sources into a strategic argument for why the small business technology market represents one of the most significant underappreciated opportunities in venture.

Read the full paper: The Next Small Business Revolution

Situation
Our satellite company’s subsurface imaging technology had broad potential across any industry that needed to see underground, but no defined primary market. The strategic question was which market to enter first and why.

Approach
Starting with the technology's capabilities rather than a predetermined market, I researched and mapped the full landscape of viable industry applications. Each market was evaluated against two parallel sets of criteria: commercial factors including market size, willingness to pay, sales cycle, competitive intensity, and urgency of need, and technical fit factors including required depth, resolution, and data accuracy required. The key question was whether what each industry needed matched what the satellite could actually deliver at each stage of development.

Outcome
A prioritized market roadmap sequencing entry into geophysical services first, with mining as the specific beachhead given its high willingness to pay, clear pain around the cost and environmental impact of current exploration methods, and strong fit with early satellite capabilities. From there, the roadmap expanded into water, geothermal, and infrastructure as satellite capabilities scaled. The longer-term vision extended beyond physical resource exploration into a data intelligence play, where the same subsurface dataset could serve real estate, insurance, and ESG markets. The market prioritization shaped the product roadmap, satellite build and launch sequence, fundraising narrative, and early commercial partnerships.

View the market opportunity map: Market Prioritization for a Novel Technology

Situation
The starting point was a broad, open question about what small business owners were currently struggling with.

Approach
I conducted 100 interviews with small business owners across 12 verticals to understand what was working, what wasn't, and where the real pain was. From that broad discovery, multiple problem areas emerged, and I prioritized operational inefficiency as the highest-signal space. I dug deeper, conducting 20 follow-up interviews focused specifically on how small businesses run day to day. I synthesized the findings into a jobs-to-be-done framework, including a critical reframe: the product shouldn't be better documentation, it should be decision support and just-in-time guidance delivered while work is actually happening.

Outcome
I led a four-day product sprint with engineering and design to produce an MVP, built in three days. The result was an AI-powered operations partner for small businesses built to capture how a business actually runs and deliver that knowledge to the team in real time, reducing owner dependency without adding administrative burden.

View the product discovery deck: From Signal to Product

Situation
The company was fairly new, moving quickly, and building as it went. Research processes were piecemeal, knowledge lived in disconnected places, and the tools and structures in place were borrowed from corporate environments that didn't quite fit a startup context.

Approach
After working within the existing structure long enough to understand exactly what wasn't working, I mapped out and built a new AI-native research infrastructure from the ground up. Core functions included ongoing industry intelligence reports across verticals of focus, primary and secondary customer research on small businesses, a structured ideation process to surface and prioritize new venture concepts, and thought leadership content synthesizing research into external-facing insights. Support functions included a research intelligence hub with vetted sources and best practices, an on-demand research fulfillment capability for teams across the company, and a centralized repository consolidating all past research with an AI-powered interface for querying it in real time.

Outcome
What started as a single research role became a fully operational research department. The company had a consistent, shared view of its markets, current intelligence on trends across its industries of focus, a structured process for generating and evaluating ideas, and institutional knowledge to build on.

View the framework: Building an AI-Native Research Department