I am an AI automation specialist focused on building reviewable agent workflows, operational dashboards, and internal tools that reduce repetitive work while keeping people in control. I am prepared for sales automation work with an emphasis on practical implementation, documentation, QA, and reliable handoff.
I design and build AI automation systems that turn repetitive operations into reliable, reviewable processes. My work includes agent workflows, operational dashboards, and internal tools that improve visibility and execution consistency.
I built AgentGate, an approval-gated orchestration system with staged actions and a human-controlled execution checkpoint for high-impact workflows. I also designed the SkybridgeCX Agent Factory to connect research, proof packaging, proposal drafting, and outreach preparation in one workflow.
My project work includes Stability-OS, a personal operations dashboard with daily stacks, source digests, priorities, and weekly review flow. I also built Frontier Lab OS, a command center for research threads, experiment logs, proof artifacts, and learning paths.
In addition to automation and systems building, I have experience with AI training tasks that require careful judgment, labeling, and escalation of ambiguous cases. I value accuracy, structure, and clear process design.
I am based in Northern Virginia and work remotely. My background in information technology supports my ability to build practical systems, document processes, and support sales and operations workflows effectively.
Design and build AI automation systems, agent workflows, operational dashboards, and internal tools that turn repetitive operations into reliable, reviewable processes. Built AgentGate, an approval-gated orchestration system with staged actions and a human-controlled execution checkpoint. Designed the SkybridgeCX Agent Factory to connect research, proof packaging, proposal drafting, and outreach preparation in one reviewable workflow.
Rank and compare language-model responses using detailed rubrics and careful preference judgments for AI training tasks. Annotate, label, and categorize data under task-specific guidelines while escalating ambiguous or edge-case items instead of guessing.
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