The generalist who is an AI specialist.
Jack of all trades, king in a few. I was a specialist first, then I kept adding trades until they started compounding. What I do with that: build the revenue operation you keep meaning to hire for, across six specialties, and you leave owning all of it.
Pick what you sell. The six stages below are what I install, running on a business like yours.
This is what it looked like at two in the morning. You were asleep.
These are the six things I have built over and over, and they stack. You cannot do the AI layer without memory underneath it, and you cannot do memory without foundations. Start anywhere, but this is the order that works.
Drag through them. Each one is a layer, and each one sits on the one before it.
I am not much use to a company still looking for its offer. I am very useful to one that has found it and cannot execute fast enough to keep up.
Sectors I have already shipped systems into. The revenue mechanics rhyme across all of them.
No discovery phase that bills for six weeks and produces a document. The first thing I do is build something small that works, so you can judge me on output rather than on a proposal.
One call. You tell me what keeps not getting done, I tell you honestly whether I can fix it and roughly what it takes. If I cannot, I say so on that call.
Not a sandbox, not a mock. Your tools, your data, your credentials, which stay yours the whole time. You watch it take shape rather than waiting for a reveal.
Real data breaks assumptions in week one that a specification would have protected for a quarter. So the first system goes into production before I plan the second.
Pricing, an unusual reply, anything irreversible, anything reaching a customer for the first time. The mechanical ninety percent runs itself. The consequential ten percent comes to you.
Not summarised afterwards from memory. Written during the build, in plain language, including the two things that broke and why the obvious approach was wrong.
Credentials in your vault, repositories under your organisation, workflows in your account. If we never speak again it all keeps running. That is the point.
Not a list of things I have read about. Every one of these has been in a system I built, broke, and put back together for a real client or for myself.
Your stack is probably in here already. If it is not, it usually has an API, and that is enough.

Bengaluru · Cornell Chief AI Officer Program · Seven years in revenue operations
I learn the new thing, teach it to whoever is nearby, then build the system that makes it repeat. That has been the pattern since a university classroom, and it is also exactly what I am selling you, except the thing being made repeatable is your revenue.
Before any of this I spent seven years in commercial and revenue operations. That is the part most AI builders are missing. I have carried a number, so I know which automation actually moves one and which just looks impressive in a demo.
The generalist half is why I can see the whole pipeline at once. The specialist half is why the AI holds up when it meets real traffic. Most people selling this have one or the other.
Everything on that list runs right now, most of it on my own server.
Installing the software is the easy half. The half that tends to matter more is what happens in the room while we build it, and what I am reading about at midnight when I am not building yours.

What attention actually is, and whether any of what we are building has a shape like it.

The only industry where the unhappy path gets modelled first. I steal that discipline constantly.
Nobody asks me to. Three come up almost every time:
These are not workshop exercises. They land in the middle of building something real, which is the only time anyone answers them honestly.




It records, it talks back, it takes my calls, and it can drive my terminal for me. Next week it will be something else. You are hiring the person who keeps doing this, not only the one who ships the six specialties.