I started in science, moved through sales, and I’m finding my “next thing”, drawn not just to how things work but how they could work better. I like messy systems, tangled workflows, and half-finished ideas because that’s where the fun starts. My work lives at the intersection of structure and creativity, whether I’m writing, building automations, or redesigning a process from the ground up. I’m wired for clarity, allergic to bloat, and happiest when I can make something both functional and elegant.

Over the past year, I’ve also engaged in daily prompt engineering work, refining inputs for different LLM use cases including code generation, documentation drafting, structured research, and knowledge synthesis. I’ve developed an intuition for prompt tailoring based on output type: when correctness is directly observable (e.g., formatting, copy, code behavior), versus when deeper prompt structure is needed to elicit fact-checked, citation-backed, or context-sensitive outputs. This hands-on prompting experience has deepened my understanding of agent reliability and how to align AI workflows with real-world deliverables.