How is this different from generic AI training?

Generic training teaches the tool. This teaches the operating system — how to put AI to work on your team's real tasks, with the judgment and governance to keep it trustworthy. It is taught by someone who implements AI in live finance functions, not someone demoing features.

Is this just about saving time?

Time is the smallest part. The bigger return is mental energy — removing the cognitive drag that sits behind the tasks people dread, so your most senior people are sharper for the work that actually matters. A team that is not buried shows up differently in every client conversation.

What does the format look like?

Live, hands-on sessions built around your team's real work. Session 1 sets the foundation — the shift underway, the cost of cognitive drag, the six elements of a working prompt, and a live exercise on a real task. Later sessions go deeper by function, with a framework the team keeps using after the training ends.

Do you actually recommend AI everywhere?

No. I am more skeptical of AI than enthusiastic about it. The training is honest about where it earns its place and where it does not — the same standard I apply when I implement it with governance built in from day one.

AI OS Training

AI training for finance and professional-services teams.

Not a tools overview. A working operating system for using AI on the work your team actually does.

Most AI training tells a team which buttons to press. It does not change how the work gets done on Monday. AI OS Training is built the other way around: it starts from the real tasks your people are already doing — the close, the deck, the client memo, the reconciliation — and gives them a repeatable way to put AI to work on them, with judgment and governance intact.

I teach it the way I implement it: more skeptical of AI than enthusiastic about it, focused on where it earns its place. The goal is not novelty. It is a team that gets its time and attention back and shows up sharper for the work that actually matters.

Who this is for

Finance and professional-services teams that do real knowledge work — accounting and FP&A groups, operators, and the people around them. It is built for teams that want AI woven into the actual work, not a one-off seminar that nothing follows.

Why it matters

The real cost of not using AI.

The expensive part of skipping AI is not the software you did not buy. It is the daily drag your team is absorbing without naming it.

The tasks draining your team most are not the longest ones — they are the ones sitting in the back of everyone's mind.
You hear “cognitively overwhelmed,” “boring,” and “keeps me from the work that matters” before anyone has tried a better way.
Work stalls at the blank page, before it has even started.
Your most senior people spend hours on production work that should not require them.
AI is being talked about, but nothing has actually changed in how the work gets done.
Tools were bought, but adoption never followed.

Inside the program

What Session 1 covers.

The program runs as live, hands-on sessions built around your team's real work — not a generic curriculum. The opening session sets the operating system; later sessions go deeper by function. Everyone walks away with something usable that week and a framework for building more.

The shift — and what it means for your team

Where professional services is heading as AI becomes part of the work, and what that actually changes about how your team spends its day.

Why daily cognitive drag is the real cost

AI's leverage is not only speed — it is mental load. We name the drag that accumulates before work even starts, and where removing it changes how people show up in every client conversation.

The six elements of a prompt that works

What separates a good prompt from a generic one, taught as a repeatable framework your team can apply to any task — not a list of tricks to memorize.

A live exercise on real work

Each person takes one real task and builds a prompt that actually works, then leaves with a prompt they can use this week and a framework for building the next one.

Proof

AI deployed where it earns its place.

The same operator lens behind the training — AI implemented in real finance functions, with governance built in from day one.

Data infrastructureAI implementationOperating intelligence

First enterprise data warehouse deployed. AI tools live across Finance, Accounting, and field support. Silent margin expansion through automation.

PE-backed multi-unit operator · 900+ locations across multiple brands, operating on fragmented legacy analytics

Read the engagement

Revenue recognitionData infrastructureAI-assisted delivery

ASC 606 recognition engine delivered in under a quarter using AI. Ongoing journal entries automated. Defensible path off cash basis.

Online coaching & subscription business · Multi-product subscription catalog across coaching programs and digital products, multiple payment processors

Read the engagement

Operating intelligenceData infrastructure

Enterprise-grade data warehouse and AI analytics built for an operator-owned franchise — run by one person, no BI team. Daily operating intelligence at a scale where nobody builds this.

Operator-owned multi-unit franchise · Small business — operator-owned and run, not PE-backed, not venture-funded

Read the engagement

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Questions

Frequently asked.

Who is AI OS Training for?: Finance and professional-services teams that do knowledge work — accounting and FP&A groups, operators, and the people around them. It is built for teams that want AI woven into the actual work, not a one-off seminar that nothing follows.
How is this different from generic AI training?: Generic training teaches the tool. This teaches the operating system — how to put AI to work on your team's real tasks, with the judgment and governance to keep it trustworthy. It is taught by someone who implements AI in live finance functions, not someone demoing features.
Is this just about saving time?: Time is the smallest part. The bigger return is mental energy — removing the cognitive drag that sits behind the tasks people dread, so your most senior people are sharper for the work that actually matters. A team that is not buried shows up differently in every client conversation.
What does the format look like?: Live, hands-on sessions built around your team's real work. Session 1 sets the foundation — the shift underway, the cost of cognitive drag, the six elements of a working prompt, and a live exercise on a real task. Later sessions go deeper by function, with a framework the team keeps using after the training ends.
Do you actually recommend AI everywhere?: No. I am more skeptical of AI than enthusiastic about it. The training is honest about where it earns its place and where it does not — the same standard I apply when I implement it with governance built in from day one.

Finance infrastructure The Operator's Capability Framework Fractional CFO for multi-unit operators

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