Work With Me
Have the Company OS installed in yours.
I come into a company, learn how it actually operates, find where AI creates real value, and build the operating system that makes it part of how the team works. Strategy through implementation through adoption, one person accountable for the whole span.
The Engagement
Not a deck. An installation.
Plenty of people will assess your AI readiness and leave you a roadmap. That is the part I consider table stakes, and it is not what you would hire me for. You would hire me to take the company from strategy all the way through implementation and adoption, and to still be accountable when the question is whether people actually use it.
The shape of it is the same eleven steps every installation follows, written out in full as the Company OS Method. What that covers in practice:
- Business discovery. How the company operates: departments, workflows, pain points, tools, outside dependencies, and what people already do with AI when nobody is watching. What that turns up sets the build order, so the first thing shipped is a job somebody is already doing by hand.
- The right use cases. Where AI genuinely saves time, improves output, grows revenue, or replaces an outside dependency. Not everywhere. The right places.
- The Company Brain. Your knowledge, prior work, and rules structured so AI can use them: one source per truth, a trust hierarchy, UNKNOWN where the record is silent. Two people asking the same question get the same answer, and where the company never decided, the system says so.
- Agents, skills, and workflows. The capabilities your work actually needs, with routing, memory, and approval logic around them. The job that used to wait for the one person who knew how now runs on a schedule.
- Brand OS. Your identity written down as a system AI can obey, with the gate that enforces it. The work comes back on brand before anyone reviews it, so review stops being a rewrite.
- Governance and the Gates. What AI may access, what it may do, when a human approves, and quality checks that stop the line instead of shipping a mistake.
- Integrations. Your files, your systems, your live data. The OS works inside the business, not beside it, so nobody has to paste in the numbers before they can ask a question about them.
- Training and adoption. The employee experience, the onboarding, and the unglamorous work that turns a clever system into one people open every morning.
- The learning loop. Approved work compounds into organizational intelligence, so the system is worth more in month twelve than month one.
The Evidence
Not a proposal.
This is not a pitch about what I would build. It is the thing I have already built four times, documented on this site in unusual detail. The systems run in production, the last three were deployed in under 60 days, and one client's three-person team now performs like a team of fifteen while saving $1,000+ a month.
The Honest Fit
Done experimenting?
The best fit is a company that already believes AI matters: you want it working inside your operation, producing work your team trusts enough to send. Size matters less than seriousness. The method has run at a multi-brand manufacturer and at a one-person firm.
I take a small number of advisory and build engagements alongside my full-time work, which keeps each one real: if I take yours, I am in it. The first conversation costs nothing and usually earns its time either way, because the most useful thing I do early is help you work out what is actually worth building before anyone builds anything.