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
- Infrastructure as Code, but Automated: OpenTofu and GitHub Actions (2026-04-08)
- Equipment Health Scoring: How One Number Made My Operators Stop Checking the Dashboard (2026-04-07)
- Pod Disruption Budgets: Why kubectl drain Gets Stuck on Longhorn (2026-04-06)
- Attention Residuals: How Kimi Is Rethinking Transformer Depth (2026-04-05)
- Helm fullnameOverride: Naming Sanity in ArgoCD (2026-04-01)
The best technology work happens at the boundary between domains.