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
- GPU PCI Address Instability: When Your Card Moves Between Reboots (2026-05-05)
- Cognitive Memory for Agents: Vector Search vs Activation-Based Recall (2026-05-03)
- AdGuard Home: Network-Wide DNS Filtering with Failover (2026-05-02)
- Unprivileged LXC + Docker: The runc Sysctl Permission Trap (2026-05-01)
- Three-Layer Safety for Autonomous Agents: Stopping the Infinite Loop (2026-04-28)
The best technology work happens at the boundary between domains.