Build clearly
Test quickly
Keep it useful
My work sits between engineering, product thinking, and design. I care about interfaces that explain themselves, systems that hold up under real use, and AI features that stay understandable to the person using them.
I started with privacy tools, file workflows, and edge-native services, then moved deeper into AI infrastructure: gateways, agents, retrieval, and the practical plumbing required to make model-based products reliable.
The goal is not to make the work sound bigger than it is. It is to build useful things, document the decisions clearly, and leave each project with a path to improve.
CLEX AI
Building one endpoint for model access, provider routing, API keys, usage visibility, and playground testing.
Privacy and utility tools
Shipped work across file movement, disposable mail, receipt parsing, and race-weekend intelligence.
Machine learning systems
Working through Stanford CS229 material while applying the concepts to practical product infrastructure.
Focused collaboration
AI builds, product engineering roles, technical prototypes, and projects where design and engineering both matter.