Agentic workflows, LLM orchestration, and production autonomous systems. I architect the tools that think and act—not just the interfaces that pretend to.
Start a ConversationA selection of production systems and frameworks built entirely with AI
Real-time AI industry monitoring and analysis
Built on OpenClaw to continuously monitor the AI industry — funding rounds, product launches, partnership announcements, talent moves. Pulls from multiple sources and synthesizes into actionable intelligence briefs. The kind of system that turns noise into signal.
Competitive intelligence for managed services
An OpenClaw-powered system that aggregates industry news, analyst reports, and market signals across the managed services landscape. Automated competitive intelligence that keeps me ahead of trends without manually reading 50 sources a day.
Personal dashboard — revenue, journal, docs, daily actions
I needed one place to track everything — revenue goals, journal entries, concept docs, daily actions, health metrics. So I built a React dashboard that does all of it. It's been rebuilt twice (once after a filesystem wipe). It's ugly in places but I use it every single day.
"The best tool is the one you actually use."
Consumer app — decode the energy of any date
Turned years of numerology study — Pythagorean system, Chinese Zodiac — into a real consumer app. Built in React, deployed on Vercel, designed the brand. It's live and people actually use it.
getdaycode.com →"Ship it ugly. Fix it live."
Find brands actively running UGC campaigns
Scrapes signals like job posts, ad spend, and social activity to identify brands that need UGC creators. Surfaces the right contacts — including LinkedIn profiles — so I can pitch directly. Built with Claude Code as the development environment.
Observations from building with AI
Enterprise adoption requires more than technical capability. It demands integration depth, security architecture, and workflows that honor existing systems.
Read →Just as USB standardized hardware connectivity, MCP is standardizing how AI agents connect to external systems. The implications are profound.
Read →Theory is cheap. Understanding comes from building. Building autonomous systems reveals what actually works—and what's still smoke and mirrors.
Read →Today I build with AI daily. Not theorizing from the sidelines. Not advising what's possible. Actually building, shipping, and pressure-testing autonomous systems. That's where the credible work happens.