20+ years building enterprise systems. Now exploring where software meets the physical world.
Day job: .NET/C# enterprise architecture, REST APIs, vertical slice patterns, legacy modernization
Nights & weekends: Edge AI, industrial IoT, robotics, and bridging IT/OT systems
🤖 Edge AI & Computer Vision — Deploying models on Jetson Orin Nano and Raspberry Pi 5
🔧 Industrial Protocols — MQTT, Modbus, OPC-UA integration patterns
🚗 Robotics Fundamentals — Robot car platform for computer vision and autonomous navigation
📊 Sensor Integration — Building data pipelines from physical sensors to cloud analytics
🧠 MCP Servers — Python-based Model Context Protocol servers for AI agent tooling
📚 RAG Applications — Retrieval Augmented Generation pipelines for domain-specific knowledge
🦙 Local LLM Integration — Ollama workflows for privacy-sensitive development environments
Enterprise: .NET 10, C#, Entity Framework, Blazor, Azure, REST APIs, CQRS
AI/ML: Python, Ollama, LangChain, RAG pipelines, MCP servers, TensorFlow Lite
Edge/Embedded: Python, OpenCV, computer vision, sensor integration
Hardware: Jetson Orin Nano, Raspberry Pi 5, various sensor arrays, Picar-X AI Video Robot Car
Environment: Pop!_OS, System76 Thelio Mira (RTX 3080), Linux-first approach
Most industrial automation folks come from controls engineering. Most enterprise devs never touch hardware. I'm interested in the gap between them — how do you build systems that scale from sensor to cloud with proper architecture?
The factory floor is about to get a lot smarter. Companies will need people who understand both worlds.
I write about the journey from enterprise software to industrial systems on Substack — lessons learned, architecture decisions, and project breakdowns.
Open to conversations about industrial IoT, edge AI deployment, or bridging enterprise and embedded systems.