I build and operate self-governing AI systems — and I run a production business on top of them.
Self-taught, outcomes-first. Over the past few months I designed and built Gridline, a private multi-agent AI operating system: AI agents that work under a shared contract, remember across sessions, review each other's output, measure their own performance, and improve over time. The AI writes the syntax — I architect the system, the governance, and the operating discipline.
Not a chatbot or a pile of scripts — a working AI environment built for sustained work at scale.
- ~49,000 image renders through a fully tracked production pipeline (~137,000 artifacts under hash-based chain of custody)
- ~1,700 work tickets executed (~1,337 completed) — every decision, reason, and outcome recorded
- ~80 codified operating rules · ~18 telemetry databases · multiple coordinated machines
- Multi-model agent orchestration with independent review gates before changes land
- Measured reliability & self-improvement — 96% success across 1,300+ tracked tasks (zero hard failures); self-audit policy-violation rate cut ~12× (2.3% → 0.18%) even as activity tripled
- Custom render engine (5 generations) that replaced commercial tools — tuned to run oversized models on constrained hardware
Work → record → review → measure → learn → update the system. That loop is the point.
A multi-machine estate I run end to end:
- Compute: AMD RX 7800 XT · NVIDIA GTX 1080 Ti · Apple Silicon
- Virtualization: Proxmox VE
- Network: OPNsense · Unbound recursive DNS · AdGuard Home
- Ops: Docker · systemd · Linux servers · RAID · disk encryption · full observability
Philosophy: own the complete stack, no vendor lock-in. I debug down to the metal — including a PyTorch memory fix derived from production profiling.
pytorch-memory-fix — environment variables that eliminate PyTorch memory creep with zero code changes, derived from real production profiling.
Applied-AI · AI / agent engineering · forward-deployed & solutions engineering · consulting on AI operating systems and agent governance.