I don't just design the system. I build it.
That's what makes this practice different from every strategy deck and vendor pitch you've sat through.
Operator first. Builder second. Consultant third.
Most AI projects fail because someone started with a tool instead of a problem. A vendor pitches a platform, leadership gets excited, and the implementation begins before anyone has answered the most important question: what is actually breaking in this business, and why?
I got tired of watching that pattern repeat. So I built a practice around doing it the other way around.
My background isn't in AI research or software engineering. It's in operations. I spent nearly a decade inside a $2B SaaS company running complex programs across product, strategy, and go-to-market. Before that, Big Four management consulting and an MBA. I know what it takes to get a business to actually change. Not just to design a system, but to get a team to use it, maintain it, and own it.
What makes this practice unusual: I also build. I've shipped live AI applications without a development team. Not demos. Not prototypes. Production tools that run, that people use, that solve real problems. That means when I walk into an engagement, I'm not recommending things I can't execute. I'm telling you what I know will work because I've built it.
I'll also tell you when AI isn't the answer. Sometimes the problem is upstream: a data issue, a process gap, a people question. Solving the wrong thing with the right technology is still the wrong thing. That honesty is what I'd want from any advisor I hired, and it's what I bring to every engagement.
The track record behind the work
The principles behind every engagement
AI isn't a tool upgrade. It's a structural shift.
Companies treating it like a software rollout are going to fall behind. Real transformation means aligning your strategy and your goals with how work actually gets done. Not just adding a new layer on top of a broken process.
The real problem is usually one level up from where everyone is looking.
Clients come in thinking they need a tool, a new workflow, or better reporting. Sometimes they do. More often, the issue is upstream. Finding that before touching anything else is the actual work.
Most transformations fail at rollout, not at design.
A solution that isn't easy to adopt just becomes another thing people work around. I build for repeatability from the start. A system that only works when someone is explaining it isn't a system yet.
Change that doesn't bring people with it doesn't stick.
AI is changing what work looks like. Sometimes the goal is doing more with fewer people. I don't pretend that conversation isn't happening. I help you move through it honestly, because change that bypasses your team doesn't hold.