I build AI agents and production infrastructure for industrial companies. 10+ years bridging the physical world — sensors, machines, factory floors — with intelligent automation that runs unsupervised.
I take on consulting projects when the problem is interesting. If you're figuring out how AI agents, predictive maintenance, or infrastructure automation could work for your business, let's talk.
AI Agent Systems — Multi-agent platforms with MCP servers, cognitive memory, safety boundaries, and real-time infrastructure monitoring. Production systems, not demos.
Infrastructure — Kubernetes on bare metal, GitOps with ArgoCD, CI/CD pipelines, GPU passthrough for LLM inference, automated everything.
IIoT & Predictive Maintenance — Vibration analysis, sensor architectures, condition monitoring pipelines, and the analytics that keep machines running.
Python TypeScript Go Kubernetes ArgoCD OpenTofu Proxmox Prometheus Grafana PostgreSQL Qdrant FastMCP
- Condition-Based vs Time-Based Maintenance: Making the Switch (2026-05-22)
- Longhorn Volume Health: The Gap Between 'Healthy' and Actually Working (2026-05-20)
- Proxmox Cluster Quorum: How Many Nodes Do You Actually Need (2026-05-18)
- Privacy-Routed LLM Inference: Keeping Sensitive Data Out of the Cloud (2026-05-15)
- Kyverno Admission Controllers: Policy-as-Code That Actually Works (2026-05-13)
The best technology work happens at the boundary between domains.