I build practical systems at the intersection of customers, AI, workflows, and implementation.
My background is in customer-facing GTM and Customer Success, including as a Founding Customer Success Manager. I use coding agents, Python, APIs, and lightweight applications to turn ambiguous customer and operational problems into working, validated systems.
A deterministic, source-backed system for exploring the 2017 SDSU baseball season.
Historical sources are preserved, normalized, validated, and loaded into SQLite. Answers are backed by provenance, and the system fails explicitly when evidence is ambiguous or unavailable.
A portable GTM workflow for taking one target account from fit assessment through research, first-touch outreach, and discovery preparation.
The workflow is designed to run across AI assistants while keeping evidence, seller context, and human review explicit.
I am interested in founding Customer Success, AI implementation, and customer-facing technical roles where I can own difficult customer problems from discovery through implementation and adoption.
