The first time I sat in a board meeting and heard someone say "we need an AI strategy," I'd already been running one for six months. It just didn't have that name yet. It was a set of workflows I'd built with Claude and a handful of scripts that cut our contract review time from four hours to forty-five minutes. Nobody called it a strategy — they called it "that thing Brian set up that actually works."
That's more or less the story of my career: building things that work at the intersection of technology, revenue, and strategy, usually before there's a playbook for it.
I started in sales. Not SaaS demos to other tech companies — the kind where you're selling into operations teams that had never heard of a CRM. That taught me something that's shaped everything since: technology only matters when it changes what a person can do on a Tuesday afternoon. Not in a keynote. Not in a pilot. On a regular workday.
From sales I moved into technology operations, then into roles that blurred the lines between the two. I've run revenue teams, architected infrastructure, built AI-powered workflows, and sat in enough strategy sessions to know that the gap between "what the technology can do" and "what the business actually needs" is where most projects go to die.
I currently operate across multiple companies, which means I context-switch between operational problems daily. Some weeks I'm debugging a pipeline integration. Other weeks I'm presenting to a board about where to place a technology bet. Most weeks, both.
That breadth isn't a quirk of my resume — it's the point. I think of my work in three modes:
The Three Modes
Operator — Build & Run
As an operator, I run revenue organizations and build the systems underneath them. That means pipeline architecture, forecasting models, team workflows, and the connective tissue between a company's strategy and its quarterly numbers. I care about what ships, not what gets approved.
Technologist — Design & Deploy
As a technologist, I design and deploy systems — with a particular focus on applied AI. I've built workflows using Claude, GPT-4, and a range of automation tools, always measured against the same question: does this actually save time, or does it just feel futuristic? I'm interested in infrastructure that survives contact with real users.
Strategist — Plan & Decide
As a strategist, I sit between the technical team and the decision-makers. I help boards and executive teams evaluate technology investments, understand what AI can realistically do today, and avoid the two most common mistakes: ignoring it entirely, or betting on demos that don't translate to operations.
What This Site Is
This site is where I write about those intersections. The essays are practitioner-first: what I tried, what worked, what didn't, and what I'd do differently. I'm not interested in predictions — I'm interested in outcomes. If something I write helps you make a better decision about where AI fits in your business, that's the whole point.
I don't have all the answers. I'm wrong regularly and I'll tell you about it. But I've been in the room where these decisions get made, and I've been in the codebase where they get implemented. That perspective is what I'm sharing here.