Build real AI systems. Locally and in the cloud.
For engineers who want to actually use AI, not just watch demos. Practical setups, real workflows, and infrastructure you can run yourself.
Latest builds.
Ralph Wiggum Plugin Makes Claude Code 10x More Powerful
Setting up a Kubernetes Cluster with Kubeadm and Containerd (v1.28)
Kubernetes Certificates with Traefik + Cert-Manager + Let's Encrypt Tutorial
How to Install Jenkins in Kubernetes with Kaniko for Container Building
Kubernetes CI/CD Pipeline Using Jenkins | DevOps Tutorial/Project - 2023
The modern AI stack.
The topics I keep coming back to. Real systems, real trade-offs, filmed as they’re built.
Agent systems in production
Orchestrating real work through AI agents. What actually ships, what breaks under load, and when the added complexity earns its keep.
Cloud and self-hosted AI
Running real workloads in the cloud when that wins, locally or air-gapped when it doesn't. Observability, cost control, and the infrastructure underneath.
DevOps for AI
Guardrails, CI, monitoring, and incident response for AI workloads. The discipline that keeps agents out of the on-call channel.
Workflows and tooling
Editor integrations, automation, and the small moves that compound over time. How I use AI day to day, and what's worth the setup.
A few partners each quarter.
The channel has over 15,000 subscribers building AI systems in production. I take a small number of technical sponsors each quarter. Good fits: developer tools, AI infrastructure, observability, and security products built for senior engineers.