Most work starts small, because guessing is expensive. We figure out what's actually wrong first; if it's worth building, I build it; and if it keeps paying off, I stay. You're never committed past the point where the value is clear.
A focused look at one workflow, or one "should we even use AI here" question. You get an honest read on where the time and money are leaking, what's worth fixing, and what isn't, including the cases where the answer is to not build anything at all. Short, fixed in scope, and useful on its own even if we stop there.
I design the fix and put it in production: automations, AI agents, LLM-backed tooling, the measurement that proves it worked. Real software that's documented and maintainable after I leave, not a prototype that impresses in a demo and rots in a month. People stay in the loop wherever the work needs judgment.
For teams that need a senior AI and operations brain in the room without a full-time hire. I steer tooling, mentor the people building, and keep shipping, part-time, hands-on, and accountable for whether things actually work.
I'll tell you when AI is the answer, and more importantly, when it isn't.
A lot of what I do is talk people out of expensive, fragile ideas and toward the boring thing that will still be running in a year. That honesty is the point; it's what makes the rest of the work worth trusting.