Greater Milwaukee, Wisconsin
I lead technology strategy and execution at a global manufacturer. On my own time, I build AI products that do real work — not demos, but systems that operate on their own and hold up in the wild. Each one is a test of where autonomous AI is genuinely ready. Frontier models changed the question I ask — less “how do we do this faster,” more “what’s actually possible now.” Everything here is me chasing that.
Every project here began with the same question: What can an AI system reliably own from end to end?
Most ideas never make it beyond an experiment. The ones that prove themselves become production systems designed to operate with minimal human intervention—not as demos, but as software that people can actually depend on.
Some research and publish on their own. Some help people make difficult decisions. Others interact with the outside world, take action, and continuously evaluate their own performance. Each is an opportunity to better understand where today’s AI is genuinely capable—and where reliability, reasoning, or safety still break down.
Building these systems has become my fastest path to learning. There’s no substitute for observing AI outside the lab, where edge cases, uncertainty, and real users expose the difference between an impressive prototype and a trustworthy system.
It connects directly to the work I lead in enterprise technology: I build these knowing what it actually takes for autonomous AI to survive in production — not just in a demo.
How I think about and build AI.
Agent Runtime
A persistent orchestration engine for autonomous AI. Loom coordinates multiple agents, preserves long-term memory, and continuously rebuilds context so work can continue across interruptions, model limits, and restarts. Rather than treating each interaction as isolated, it gives AI systems durable state, recoverability, and the ability to pursue long-running objectives with minimal human intervention.
Because autonomous systems shouldn’t forget who they are.
Read how it works — the architectureAgentic research platform
ATLAS is a research platform for agentic AI disguised as a trading system. It autonomously researches, plans, executes, and reviews decisions within a tightly constrained portfolio, using every trade as an opportunity to study reasoning, risk management, feedback loops, and the practical requirements for safe autonomous AI.
Measured in lessons, not returns.
Autonomous voice agent
An experiment in real-world AI agency. Concierge autonomously places calls, navigates conversations, discloses its AI identity, completes routine tasks, and reports back with structured results. The project explores the practical challenges of deploying trustworthy voice agents in environments designed for humans.
It handles the conversation. I handle the exceptions.
What I build with it.
Government stock-trade tracker
A nonpartisan intelligence platform that transforms government financial disclosures into structured, searchable data. Covering Congress and senior executive-branch officials, it delivers weekly insights and exposes an MCP API that enables AI systems to reason over government trading activity.
potomacledger.comTechnology studio & advisory
Seven Roots is an independent technology studio focused on building reliable AI systems that do useful work. Every project begins as an experiment in autonomy and ends only when it can be trusted to operate in the real world. The studio is still evolving, and I’m always interested in conversations with people who care about thoughtful engineering, practical AI, and long-term impact.
sevenrootsconsulting.comAI technology-decision advisor
An AI system for high-stakes technology decisions, producing structured, transparent, and defensible reasoning for complex platform and architecture choices.
heartwood.sevenrootsconsulting.comFertility-navigation platformSupporting · Coming soon
A technology-enabled fertility navigation platform designed to make one of healthcare’s most complex journeys more accessible and easier to navigate. By combining frontline nursing expertise with trustworthy AI, it helps patients better understand treatment options, improve medication access, and make informed decisions with confidence. Founded by my wife, an experienced nurse, I lead the technology, AI architecture, and product development to build intelligent systems that responsibly augment—not replace—clinical guidance.
Autonomous events newsletter
A fully autonomous local discovery agent for busy families. Every week it searches southeastern Wisconsin for the best kid-friendly events, filters the noise, writes a curated newsletter, and sends it on schedule—all without anyone pressing “send.” What began as a simple automation became an exploration of how AI can quietly handle recurring, real-world tasks people genuinely value.
Every Sunday. Without me.
Self-maintaining media catalog
An autonomous media catalog for the AI-generated music I create. Every new track triggers an agent that ingests the audio, extracts metadata, generates artwork and a song summary, and organizes everything into a searchable, self-maintaining library. Built to explore how AI can continuously structure and manage growing collections without manual curation.
It organizes itself.
Local-government meeting monitor
Local government decides a lot in public meetings almost nobody reads. Docket watches the agendas and minutes across a whole metro, pulls out what’s actually being decided, and flags the businesses it affects before the vote lands. The newest experiment here — still taking shape.
Reads every room, so you don’t have to.
