Production-grade web applications built with React, Next.js, Node.js, and PostgreSQL. Mobile-first design, real-time features, and robust APIs.
I run 25+ production apps on my own hardware. Docker orchestration, CI/CD pipelines, Cloudflare tunnels, and zero-trust security — all self-managed.
Building with local LLMs, AI agents, and automation pipelines. From intelligent assistants to computer vision — practical AI that ships.
Real-time product availability tracker with push notifications, auto-buy automation, and a public-facing dashboard.
Drag-and-drop project management with document linking, real-time sync, and cross-app integration.
Notion-style document editor with Google OAuth, real-time collaboration, and granular sharing controls.
Automated content workflow — video ingestion, transcoding, thumbnail generation, and multi-platform publishing.
Always-on AI assistant with multi-channel messaging, automated monitoring, sub-agent orchestration, and memory persistence.
Centralized navigation portal for 25+ self-hosted services with health monitoring, search, and role-based access.
I'm Ray — a software engineer who ships fast because I understand what's happening under the hood. I've worked with AWS, Vercel, GCP, and every major cloud platform. I know how to architect systems the traditional way — and that's exactly why I can move 10x faster with AI.
When you understand Docker networking, database indexing, CI/CD pipelines, and infrastructure-as-code, AI doesn't replace your judgment — it amplifies it. I use AI agents and local LLMs as force multipliers, not crutches. The result? I built and deployed 25+ production apps on my own infrastructure — each one containerized, monitored, and running 24/7 with automated CI/CD through GitHub Actions.
I don't just pick the trendy tool — I pick the right tool. Sometimes that's a managed service on AWS. Sometimes it's a self-hosted solution on dedicated hardware with GPU compute. The difference is I've done both, so I know when each one matters.
Outside of engineering, I create content on YouTube covering hardware deep dives, AI experiments, and real-world engineering workflows — not tutorials, but how things actually get built.