Selected work
How I used customer discovery to shape sales conversations, define AI product workflows, and clarify the data infrastructure needed for scale.
Sales enablement
After an initial discovery call with a healthcare data and analytics company, I shaped the demo around two workflows most relevant to its business: reviewing large clinical datasets and producing reviewable submission outputs. This allowed me to address both executive and technical priorities and guide the conversation toward a focused pilot, partnership, or resale opportunity.
Open demo narrativeProduct requirements
An enterprise customer needed two connected clinical AI workflows: one for developing Statistical Analysis Plans and another for using approved plans to generate Python analysis and code. I translated the request into product scopes for two agents, including their roles, inputs, outputs, and review requirements.
Open clinical AI requirements memoProduct requirements
A blended-learning provider wanted an AI-enabled platform that could support personalized learning across 200–400 schools. I translated customer feedback into two connected product scopes: the learner and teacher experience, and the student-data infrastructure needed for profiling, knowledge-gap tracking, feedback loops, privacy, security, and scale. The engagement resulted in a pilot serving 60,000 students.
Open learning platform requirements memo