About
I’ve built my CRO career as a founder, director, and hands-on practitioner.
More than a decade in leadership. Work with more than 100 companies, including Fortune 500 and FAANG companies. Experience building experimentation programs from scratch and scaling them.
My work spans building an agency, consulting engagements, and directing CRO within companies. Each has given me a different responsibility for experimentation: choosing the problems, building the team, and creating the conditions for a program to keep improving.
Over the past two to three years, AI has transformed how I do that work. I now use customer context to review copy, make my research criteria explicit through conversations with AI, and build a skill to support experiment development at LawnStarter.
My background
I co-founded Supersonic with Filipe Reis in 2013. We built Latin America’s largest CRO agency and sold it to Etus in 2024. That chapter involved building a specialist business, developing a team, and taking responsibility for client delivery.
I served as Director of CRO at Seer Interactive in the US. Today, I’m Director of CRO at LawnStarter, a US platform for booking lawn care services. These roles put experimentation inside the organization’s decisions and priorities.
Across that career, I’ve worked with more than 100 companies and built and scaled multiple experimentation programs. That experience has helped me distinguish what depends on a particular business from what a consistent CRO operation needs.
How I approach the work
Starting from scratch changes the question. Building a program means deciding what it should solve, how to investigate opportunities, and what the team can execute and measure. Test ideas sit within those choices.
Scaling means making decisions across the operation. Priorities, execution capacity, and interpretation of results need to keep pace as the program grows. That is a central part of directing CRO.
Experience needs to reach the team. The skill I’m building at LawnStarter turns criteria for hypotheses, evidence, and feasibility into a process other people can use to develop their experiments.
Context is part of the system. I’ve been connecting AI to customer feedback, using interviews to make my research criteria explicit, and building a skill that helps the team develop experiments. That work includes evaluating the output and refining the criteria as mistakes and opportunities emerge.
What you’ll find here
Writing, case studies, and appearances that draw on founding an agency, directing CRO, and building programs across different companies. My recent writing shows how I’m applying that experience to working with AI.