Building the bridge between ops and engineering
7 years in logistics ops gave me a problem-solver's lens. Now I build production AI systems and homelab infrastructure that actually hold up in the real world.
Projects that ship
Real systems solving real problems. Not demos — production workloads running in the wild.
98% Faster Shipment Dashboard Modernization
How I moved a legacy shipment dashboard from 80-90 second load times to under 2 seconds using SQL preprocessing and a React/TanStack rebuild.
Safe Legacy Deprecation: Retiring Old Modules in a Live Logistics System
Mapped runtime usage, added feature switches and rollback guards, then removed deprecated PHP modules in waves—reduced ambiguity and maintenance risk with zero operational regressions.
Supply Chain / LogisticsModernizing Customer Workflows: From Legacy PHP/jQuery to React + Node
Led incremental migration of core logistics workflows from brittle PHP/jQuery to React + Node.js — frontend bugs dropped ~50% (directional), feature delivery sped up dramatically, all with zero customer downtime.
Want the quieter systems side too? Read the SilkCast release engineering case study for deployment habits, release discipline, and production confidence.
End-to-end, from mess to production
I don't just build prototypes. I take ideas through research, prototyping, production deployment, and iteration.
AI Systems
RAG pipelines, LLM integrations, predictive models. Production-grade AI that doesn't hallucinate at 2am.
Automation
n8n workflows, API integrations, scheduled jobs. Replace manual work with systems that just work.
Infrastructure
Homelab setups, Docker stacks, self-hosted services. Proxmox, Unraid, and the learning that comes from running them.
Full-Stack
Astro, React, Node.js, databases. Modern web apps with real-world usability.
Got a problem worth solving?
I'm currently taking on select projects. If you need someone who gets ops AND engineering, let's talk.