I make sense of messy systems, products and AI workflows, turning complex data and decisions into things that actually work.
About
I design complex, large-scale systems and have spent years grasping why things break and how to make them whole again. That experience means I can often work through a system in my head before putting it on paper, trace decisions and consequences, and predict how it will behave in the real world.
Most of my work starts where things are messy: too much data, conflicting goals, unclear decisions. The goal is to find the structure that brings everything together and makes complexity feel simple. That work has taken me across different enterprise products and industries.
The same approach extends into AI, and it sometimes feels more like being an AI squad lead: keeping agents in line, maintaining context, making decisions, and working toward the same goal. And preventing them from creating a total mess.
I rarely settle for defaults. Tools and methods are useful, but not the work itself. Clear principles and common sense scale better than rigid rules and passing trends.
In short: I turn messy data into clear, intuitive systems where everything clicks.