01 / Platform engineering for AI systems

Reliable
systems for
unreliable
frontiers.

I build the infrastructure behind production AI: infrastructure-as-code, Kubernetes, model serving, observability, and agent governance.

Explore work ↗Professional record ↗
Bracknell, UK → SwitzerlandTerraform certifiedOpen to platform / research roles
Active systems / topologyPlatform
engineeringIaC
TerraformAI agents
MCPObservability
SRESecurity
IAM
Status: operating5+ years
Uptime99%infrastructure uptime maintained
Platform53services in a 100% IaC homelab
Research12axes in the Rubicon benchmark
Scale4K+enterprise endpoints operated

02 / Selected systems

Case studies, not
a technology list.

[ 03 CASE STUDIES ]
01100% IaC Homelab PlatformA private cloud built entirely as code — Proxmox, Terraform, Traefik, and 50+ services with secrets management and observability.↗02notification-state PlatformA production incident-notification system: FastAPI + SQLite dashboard, n8n routing, ntfy push, six systemd-timer producers, and encrypted backups.↗03Hermes Agent + TaskNotes SkillA persistent AI agent (DeepSeek backend, Telegram interface, memory) extended with a custom skill that manages tasks across Obsidian vaults.↗

03 / Active research

Can an AI model be trusted with production infrastructure?

At Segen, I work on AI platforms. Independently, I am developing Rubicon, a 12-axis benchmark for evaluating AI infrastructure work with safety in mind.

Read the research note ↗
JUDGEMENT
OVER
COMPLIANCE.