Gary D Murphy

The SoloEdge AIOS: Multi-Agent Command Center

Production AI infrastructure. Self-healing. Self-correcting. Built to deploy.

SoloEdge runs on a multi-agent crew where every agent owns exactly one job and escalates cleanly when it hits its boundary. No monoliths. No guessing.

Foreman: Engineering Manager agent. Routes work, owns escalation paths, dispatches specialist sub-agents on demand. Keeps context across sessions so nothing falls through.

Riley: Customer-facing voice agent. Answers inbound calls, qualifies leads, books appointments, logs to Google Sheets. Live in production since January 2026.

Alex: Murphy's personal PA. Screens inbound W2 recruiters 24/7, qualifies roles against Murphy's criteria, logs every call, and transfers qualified leads live to Murphy. No voicemail, no waiting. Call her at (512) 399-3404.

Onboarding Agent: Spins up new customer environments from a template. Target: under 15 minutes from zero to live, no human in the loop.

EM Code Review Agent: Reviews every commit. Enforces standards before anything hits production.

Argus: Ops watchdog. Monitors system health, flags anomalies, surfaces issues before they become incidents.

The whole stack runs on Docker, DigitalOcean, and a local Intel NUC. Infrastructure is version-controlled and templated. SoloEdge's own deployment pipeline is the product.

Why this matters for any AI engineering team: I didn't just build AI tools. I built the system that manages the AI tools, including the safeguards, the escalation logic, and the deployment repeatability. That's the discipline I bring to a production environment.

20 years in manufacturing, including 10 years in assembly-line automation and robotics on production lines at Tesla, Flex, Daikin/Goodman, Halliburton, and Pentagon Technologies (semiconductor cleanroom tooling) taught me what “production-grade” actually means. Not the demo screenshot, the 3am page when something breaks.

I apply that same discipline to AI: ship it, monitor it, page on it, fix it. Agents are the workforce. I’m the architect.

Flex , production floor

On the floor at Tesla

I authored the SoloEdge Doctrine, a multi-agent crew framework with three non-negotiable patterns: self-evaluation, correction loops, and stable spec testing. An agent that can't tell when it's broken is a liability. An agent that breaks the same way twice is malpractice. An agent that ships without spec testing is a demo, not production. v1.4 adds the Judge Layer: every agent action at a business boundary requires structured evaluation before execution. Agents that act without a judge are demos. Agents with a judge are infrastructure.

Core principle: AI Capital, including customer data, agent memory, and prompt history, must travel WITH the customer. Not locked into vendor silos.

Seven Anthropic certifications · 2026

Currently enrolled: UT Austin AI & Machine Learning with Python

Production tools

Infra: Self-operated hardened home lab with isolated networks, encrypted storage, and controlled access. Plus DigitalOcean production droplets and Cloudflare Tunnel.

AI Engineer · ML Engineer · Customer Engineer · Solutions Engineer / Architect · Applied AI Engineer roles at companies shipping real production AI.

Remote-first, Austin-based , open to Austin, Houston, or San Antonio metro. What matters is the AI is shipped.