I architect production AI systems.
Agent Orchestration, Distributed Systems, Cloud Infrastructure.
The Process
1
Architect
DiscoveryRead the system end to end. Design the solution. Surface tradeoffs and failure modes in a brief that scopes the build.
Design Brief
2
Build
ImplementationImplement the system end to end. Real architecture, real infrastructure, real error handling. Code that runs in production.
Repo + Tests + Docs
3
Ship
OperationDeploy, operate, iterate. I keep ownership in production and ship the next thing alongside your team.
Retainer Available
Featured Work
Systems Engineering
Argus
A TUI-based unified control plane for agent sandboxing, written in Rust. 8 modules, 9 dependencies, no async runtime. 3.7 MB binary.
Explore →Product
ArchByte
Real-time architecture maps for any codebase. Your model, your machine.
Explore →Showcase
Silicon Cortex
Event-driven AI agent orchestration on Kubernetes. Zero idle cost.
Explore →Showcase
Meridian
Uber for RoboTaxis. AI agents coordinating at scale.
Explore →Frequently Asked Questions
What AI systems do you build?
Agent orchestration layers, event-driven pipelines, multi-agent architectures, and developer tools. Rust for systems work, Python for AI services, TypeScript for full-stack. Every project ships with real error handling, observability, and infrastructure as code.
What is the Customer Zero approach?
I run every system I build in production before I ship for anyone else. Real workloads, real failure modes, real fixes shipped. By the time a client sees it, the second-mile integration friction is already gone.
What does a Build Sprint look like?
Production-grade implementation shipped end to end. Real architecture decisions, infrastructure as code, error handling, observability. Code that runs in production, not a slide deck. Delivered as a repo with tests, docs, and a video walkthrough.
What tech stack do you work with?
Rust for systems and CLI tools (Argus). Python for AI services and event-driven backends (Silicon Cortex, Meridian). TypeScript for full-stack and visualization (ArchByte). Kubernetes, Kafka, NeonDB, Redis, Docker, Cloudflare across projects. Claude, OpenAI, and Gemini for LLM integration.