Home lab notes, project logs, and occasional thoughts.
~$106/mo, zero API costs, all inference local. Two years, 11 hosts, 6 local LLMs, and one NVIDIA driver rollback that nearly bricked the lab — the real build vs buy math of self-hosting AI at home.
AI renamed my network interface. It asked for SSH to a box already sharing via NFS. It skipped 3TB of media without an error. These aren't edge cases — they're the current state. Three concepts and five war stories from running AI agents in the trenches.
How I built a production RAG pipeline using Open Brain (OB1), ChromaDB, and local LLMs — turning 322 career thoughts into a conversational AI with zero third-party API dependencies.
A cautionary tale of AI-assisted data migration, ZFS backups that aren't rsyncs, and why the only bad actor was me. A lightly disguised position paper on managing access with vibe coding tools — born from the real loss of a Jellyfin library during a home lab migration.
Three machines, five LLMs, zero API costs — how I built a local AI pipeline to automate my job search, and what it taught me about frameworks, hallucinations, and knowing when to write it yourself.
How and why this site is built on a home lab with local AI — a hands-on exercise in data sovereignty and independence.
How I built a Cloud Center of Excellence from scratch at Micro Focus — 47 AWS accounts, Guardrails, IAM redesign, SRE transition, and the company's first legacy-to-Fargate SaaS migration.
The framework that gave 10+ product groups a shared language for cloud adoption — six areas, progressive maturity levels, self-assessment methodology, and why the lab work mattered more than the slides.
The technical deep-dive on migrating a heritage Java workload from over-provisioned data center VMs to AWS ECS Fargate — GitOps, Firecracker microVMs, 8-week migration timeline, and lessons learned.
The migration that nearly broke the model — 1,000 VMs, eight years of organic growth, hand-operated monitoring, four unowned failure modes, and the organizational politics of cross-continent coordination.
Privacy-first AI deployment, the VM sprawl parallel, and why local LLMs are a market — size depends on how the pay-per-play model executes over the next 3-5 years.
Two truths and a lie about vibe coding — the 80/20 trap, hallucinations in practice, and why you can actually do something about it.
How we built SREs from scratch — career pipelines, retention math, compensation advocacy, and why a central CCoE is the right place to develop cloud talent.