I build practical automation systems for browser-heavy workflows, AI-agent workstations, engineering methods, and public-safe career proof.
My GitHub is organized as a closed-loop operating system I call LoopStack: set up the machine, capture opportunities, solve problems, turn the result into proof, and distribute the reusable parts back across machines.
- AgentDesk - workstation substrate for human + AI collaboration.
- OpportunityOS - external opportunity intake and routing for browser-heavy workflows.
- SystemSmith - engineering methods for code, agents, docs, security, and architecture.
- ProofStack - public-safe career proof, positioning, and writing systems.
- SkillPort - packaging and distribution backbone for reusable skills across machines and repos.
- Website / blog - public writing, case studies, and portfolio material.
- Making the loop explicit so each repo has one job and one audience.
- Turning solved work into reusable skills that sync across machines.
- Keeping the public layer safe to share while preserving enough proof to be credible.
- Website / blog - public-safe articles, notes, and project context.
- Data/AI engineer oriented toward practical systems and automation.
- Public projects are the visible layer; private employer work stays private.