She said so herself this week, in a post about how she uses Astra as OpenAI’s CFO. By the time she’s awake, the day is already scattered across Slack, email, spreadsheets, dashboards, the calendar, and ChatGPT Work, which pulls it into one update under four headers.

• Who owns it?

• What changed?

• What needs attention?

• What do we need to decide today?

Every CFO I know does a version of that triage by hand.

Phone in one hand, coffee in the other, flipping between Gmail and Slack and a tracker someone updated on Friday, trying to work out which of the six things on fire is actually the one that matters before the 8 a.m. call.

You open your inbox and someone wants approval for $250,000.

The forecast looks good.

The agency needs an answer.

You could approve it and move on.

But in another email, HR says the store has lost four experienced people. In Slack, someone on the floor says customers are waiting 20 minutes for help. Two have already walked out.

You would want to know that before paying to bring more customers through the door. This is the kind of work I wanted to test after reading Sarah Friar’s post about her morning routine.

I wanted to see how much of that I could reproduce.

I went back to Born2Cycle with a different question.

Could Astra read the information arriving between meetings and help the CFO work out what to do next? I gave it three emails, a Slack channel, a calendar, and two finance files. Then I asked it for a morning briefing.

I set the whole thing up, ran it, and read what came back.

This is going to make every CFO’s job easier.

Let’s dive in.

Building OpenAI’s CFO routine with ChatGPT-6 Astra

Step 1: Give Astra your business situation

To get started, go to chatgpt.com and start a new conversation.

Chose work in combination with Astra Medium or High.

Download these 2 Excel files below and import them to Google Sheets

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And Insider Members are a small, practical group of top CFOs who are willing to go ahead and participate in the LIVE events. The live events are open only to Insider Members to keep it practical and interactive.

But regular paid members get full access to the live recordings.

Most CFOs start in the wrong place.

They start with the tool. They buy the licenses, run a few experiments, and wait for something to happen. Gartner found that 84% of finance organizations have deployed AI, and only 7% report high impact.

Everyone bought the same models.

Almost nobody followed a sequence.

Glenn’s argument is that the order matters more than the technology, and he has the engagements to prove it.

Glenn Hopper is the real AI CFO who led this session.

Decades in finance leadership, running AI-powered workflows inside his actual planning process today. He is the author of The AI-Ready CFO, and he advises finance teams on AI deployment through his consulting practice.

All paid members can watch the full recording below

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Every few months a model gives a life-changing experience.

After spending a great amount of time using GPT-6 Astra for building CFO apps and finance tasks. I’m convinced it feels really close to AGI.

The idea of letting GPT-6 use Claude feels amazing.

This is as cool as it gets.

Hang on tight.

Just in a moment, I’d share with you how I am using GPT-6 for CFO and finance-related tasks.

Every CFO has systems that will never integrate with anything. The old ERP module nobody will touch. The bank portal. The state filing site. The reporting tool your predecessor bought that has no API and never will.

I just built a planning application and deployed it to the cloud. Then I connected Claude to it, loaded the actuals, answered a few questions about assumptions, and had a first version of the budget.

(GPT-6 Astra did everything itself.)

The whole thing took no more than an hour.

You can see it here.

The workflow is simple.

Claude loads and maps the actuals straight from the app. Nothing to export.

Claude asks you for the budget assumptions. Growth, headcount, pricing, whatever the model needs. You answer in plain language.

Claude builds the first version of the budget.

You are not typing numbers into cells.

You are having a conversation about assumptions while the model does the assembly. The mechanical part of planning is the part that eats your quarter, and it is the part that was never the valuable bit.

Read on to see how easy it gets with GPT-6 to build a planning app and get finance work done.

The best thing is now you can build your own MCP server

But let me take this moment and explain to CFOs the concept of an MCP server.

Think about your bank feed.

Your accounting system does not make you export transactions every morning and upload a CSV. It connected once, and the balance is simply there, current, whenever you look at it.

MCP does that for AI. Instead of exporting your actuals and pasting them into a chat window, the AI connects to the system and reads what is sitting there right now.

A file goes stale the moment you export it, and then it scatters into email and Slack and somebody’s laptop. A connection does not. And you decide what it can read and whether it can write anything back.

So in what follows, the app holds the data. The MCP server is the doorway. Claude walks through the doorway and works with numbers that are actually current.

Back to the flow.

How to use GPT-6 Astra as a CFO for Planning and Budgeting

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You struggle day to day with administrative burdens.

You can't be present with your families.

This is the biggest reason every CFO wants a chief of staff.

• Someone who’s got the board pack prepared before you’ve remembered to ask.

• Someone who takes notes in the meetings and reminds you what actions to take.

• Someone who reads the docs you never opened and tells you the two things in them worth knowing.

Just think about it … why as a CFO you have to chase things and remember simple stuff all the time when you are hired to focus on the strategic stuff?

You are supposed to spend time with your family on weekends.

And not check emails and Slack threads.

Do you know the Chief of Staff role is growing fastest at public companies and PE-backed businesses!

So the thing works if The New York Times wrote about this.

I know… I know... it’s easy to say I want a Chief of Staff. But hiring one is really hard. And CFOs have a reputation of freezing new hires, so if you go to your CHRO or CEO and ask for a headcount, it’d look awkward.

So I built one in Claude instead.

You’ll get one master skill to upload inside Claude.

The Claude skill will become your chief of staff and help you prepare with the following:

• Morning CFO Brief

• Meeting preparation

• Action and decision-making

• Weekly CFO review

I’ll show you how you can connect your Gmail and Slack.

It’s really simple.

Let’s dive in.

Download the CFO Chief of Staff Skill below and upload it inside Claude

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And Insider Members are a small, practical group of top CFOs who are willing to go ahead and participate in the LIVE events. The live events are open only to Insider Members to keep it practical and interactive.

But regular paid members get full access to the live recordings.

Yesterday I built a Chief of Staff for CFOs live in 60 minutes.

And we covered how to connect live financial systems through MCP.

Why local memory is yours alone, and what has to go into Notion instead because that is the only memory your team can share.

I built the CFO skills. Scheduled tasks in Cowork, so the brief runs whether or not you open your laptop.

Paid members can watch the full recording below

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And Insider Members are a small, practical group of top CFOs who are willing to go ahead and participate in the LIVE events. The live events are open only to Insider Members to keep it practical and interactive.

But regular paid members get full access to the live recordings.

You can learn how to build a skill from scratch

• What a skill actually is, in plain terms, and why it beats a prompt.

• Building all three live, from start to finish, in my own Claude environment.

• How a skill forces Claude through the same steps every time: inventory the inputs, flag the exceptions, check its own math, and write the summary.

• Why you should build your own instead of downloading mine.

The skills every finance function must own

• A month-over-month dashboard that is identical every time. Same accounts, same comparisons, same visuals.

• A budget variance analysis that drills into what matters, hunts the drivers, asks you questions, and writes commentary sharp enough to send.

• A board deck that follows the same layout and pattern every month.

Paid members can watch the full recording below

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Every Insider Member found it super helpful.

The full recording is now available for all Paid Members.

• A complete monthly reforecast cycle inside a Claude Project.

• His exact custom instructions, 5 copy/paste prompts.

• The full dataset, and his honest take on where Claude saves time and where it doesn’t.

Live Sessions are exclusive to Insider Members only.

It’s a group of top CFOs on purpose. The conversation is open-camera, open-mic, with real questions from CFOs and FP&A leaders.

People ask the questions they would not ask on LinkedIn.

But the regular Paid Members will get all the live recordings and editorial content.

If you are a paid member, you can access the recording link below.

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You struggle day to day with administrative burdens.

You can't be present with your families.

This is the biggest reason every CFO wants a chief of staff.

• Someone who’s got the board pack prepared before you’ve remembered to ask.

• Someone who takes notes in the meetings and reminds you what actions to take.

• Someone who reads the docs you never opened and tells you the two things in them worth knowing.

The job exists, by the way.

Chief of Staff to the CFO.

But you’re not getting one. Sorry.

Just think about it … why as a CFO you have to chase things and remember simple stuff all the time when you are hired to focus on the strategic stuff?

You are supposed to spend time with your family on weekends.

And not check emails and Slack threads.

Do you know the Chief of Staff role is growing fastest at public companies and PE-backed businesses!

So the thing works if The New York Times wrote about this.

I know… I know... it’s easy to say I want a Chief of Staff. But hiring one is really hard. And CFOs have a reputation of freezing new hires, so if you go to your CHRO or CEO and ask for a headcount, it’d look awkard.

So I built one in Claude instead.

You’ll get one master skill to upload inside Claude.

The Claude skill will become your chief of staff and help you prepare with the following:

• Morning CFO Brief

• Meeting preparation

• Action and decision-making

• Weekly CFO review

I’ll show you how you can connect your Gmail and Slack.

It’s really simple.

Let’s dive in.

How to build a Chief of Staff with Claude as a CFO

Step 1: Connect Email and Slack

Go to Claude.ai, then Customize, select Connectors, and select Gmail & Slack.

Okay, while connecting Gmail. Please approve all read-only tools.

Step 2: Create a new Project

Let’s use Claude Co-work for this.

Keep the instructions simple.

Please give Co-work a local folder to store and update files.

Download the CFO Chief of Staff Skill below and upload it inside Claude

Read more

So does your board. So does the peer CFO who posted about their transformation on LinkedIn last week. The pressure is coming from every direction, and none of it is wrong. AI is the biggest shift this seat will manage in a generation, and the CFO who sits it out loses.

But here is the trap almost nobody is naming.

You can believe in AI completely, commit real budget to it, move faster than your competitors, and still lose. Not because the technology fails. Because you pointed the money at the wrong layer.

That is the collapse CFOs are not prepared for.

It is not a story about AI disappointing anyone.

It is a story about where the profit actually lands, which layer keeps it, and which layer quietly pays for everyone else’s. Most finance leaders are committing three years of budget to the layer that pays.

I am not asking you to take my word for it.

In the last 90 days, four stories came out that change how you should think about your AI budget.

• Peter Thiel sold his entire Nvidia stake.

• Nvidia posted a profit margin almost no company ever reaches.

• OpenAI lost 21 billion dollars in a single year.

• And a Bank of America analyst told clients the SaaS software you already pay for is being repriced for good.

Read them in order.

You will look at your own AI budget differently.

Let’s dive in.

Peter Thiel sold every share of Nvidia

He sold all of it.

In the third quarter of 2025, Thiel’s fund sold every share of Nvidia it owned. All 537,742 of them were worth over $100 million. That position was roughly 40% of the entire fund.

The most successful technology investor of his generation looked at the defining company of the AI era and walked out the door.

Thiel is not anti-AI.

He funded the first outside check into Facebook. He runs Palantir. He believes the technology is real. He compared this moment to the internet in the late 1990s: more than a nothing burger, and less than the total transformation everyone promises.

Both halves of that sentence are the point.

The internet was exactly as real as everyone believed in 1999. That did not save the companies that bought into the wrong layer at the wrong price.

Thiel’s discipline is one question.

Follow the money. Where is the profit actually landing?

He answered it himself at the Aspen Ideas Festival in 2024. He estimated that 80 to 85% of the money being made in AI is made by one company, Nvidia. He called it “very strange,” because the profit sits at the hardware layer, a place he said Silicon Valley “doesn’t even know much about anymore.”

Nearly all the profit in AI is made at the layer almost no CFO is buying.

Before you commit a dollar to AI, ask Thiel’s question. Which layer captures the profit, and which layer pays for it?

Nvidia makes the profit. Everyone else pays the bill

In one quarter, Nvidia earned $58.3 billion in net income on $81.6 billion in revenue, at a gross margin of nearly 75%.

Data center revenue alone was $75.2 billion, up 92% from a year earlier. Strip out one-time gains and the company still keeps more than 55 cents of every dollar as profit.

That is not a good business.

That is the best business in the history of business.

Now look at who is buying.

The big cloud companies are on track to spend somewhere between $500 billion and $600 billion on AI infrastructure this year. One recent estimate has them recycling more than 100% of their cloud revenue straight back into capital spending. They are running to stand still, and the profit from all that motion pools in one place: the chip layer.

Sequoia’s David Cahn named the gap.

He called it “AI’s $600 billion question,” the distance between what the industry spends building AI and the revenue AI actually produces.

That gap has only widened since.

The AI economy is a shovel business, and one company sells the shovels.

The SaaS layer you already pay for is being repriced in public

Dario Amodei, the CEO of Anthropic, said it plainly at a financial services event. If a software company’s only moat is that its product is complex and hard to build, that moat is disappearing.

In 2026, Salesforce fell around 30%.

Workday fell around 33%.

The main software index dropped more than 20% into a bear market, and by some counts one to two trillion dollars of software value evaporated in about a year.

On May 18, 2026, a Bank of America analyst named Tal Liani cut Salesforce to Underperform with a $160 target, well below the Street.

The per-seat software model is being repriced in real time, in public, by the analyst community. And CFOs are still signing three-year, per-seat renewals into the middle of it.

Every SaaS renewal on your desk this year is a different decision than it was two years ago. The vendor needs you more than you need them, and the analyst community just handed you the leverage. Renegotiate. Shorten the term. Tie price to usage, not seats.

One honest caveat, because your credibility depends on it: the software sector bounced off its lows by mid-2026. But a repricing is exactly when contract terms get rewritten, and that window is open now.

OpenAI’s own CFO is living the fight you are about to have

Here is the fight in its purest form, at the largest scale on earth.

OpenAI lost $20.9 billion on $13.1 billion of revenue in 2025. Its research spending alone, $19.2 billion, was larger than its entire revenue. And the company has committed to roughly $1.4 trillion in compute over the next eight years, against a revenue run rate of around $20 to $25 billion.

That is a commitment-to-revenue gap of nearly 100 to 1.

When OpenAI’s CFO, Sarah Friar, floated the idea that the government might backstop AI financing, the backlash was immediate, and she walked it back within a day.

When an investor pressed Sam Altman on how the spending squares with the revenue, Altman’s answer was not a spreadsheet. It was, roughly, if you want to sell your shares, I will find you a buyer.

That exchange is the CEO-versus-CFO tension of this entire era, playing out in public.

You are about to have a smaller version of that exact conversation.

Your CEO sees AI as the future and wants to spend.

You see the contracts, the burn, and the missing return. The board watches both of you. The only thing that resolves it is your ability to answer three questions the whole industry is currently failing to answer.

What did we sign for?

What are we using.

What is it producing?

The Bottom Line

Thiel sold his Nvidia stake and told you the profit sits at a layer you are not buying. Nvidia’s 75% margin proved him right.

The SaaS layer you already pay for is being repriced in public. And OpenAI’s own CFO is fighting the exact fight you are about to have, at a 100-to-1 scale.

The disciplined CFO does three things with this.

First, follow the profit, not the story. For every AI dollar, ask which layer keeps the money and which layer feeds it. Treat the application on top as disposable and the capability underneath as the thing worth owning.

Second, build the measurement before the commitment. Do not sign the three-year deal and hope. Put a simple test on every AI workflow. What did we sign for, what are we using, what is it producing. If it cannot answer the third one in ninety days, it does not get renewed.

Third, stay liquid on tools, committed to capability. The tooling in 2026 is disposable and a single model release can obsolete it. The capability compounds. Do not lock three years of budget into a layer one launch can erase.

Do this, and the collapse is something you watch happen to other companies.

Fail to do it, and you are the case study in someone else’s newsletter next year.

The CFO who commits budget to the story is replaceable.

The CFO who follows the profit is not.

See you on Thursday.

Whenever you’re ready, there are 2 ways I can help you:

1. Advertise with the AI CFO Office.

2. If you have an interesting AI use case, or you have already put AI into your finance function, I’d love to see it.

I’m Wouter Born. A CFOTech investor, advisor, and founder of finstory.ai

Find me on LinkedIn

Insider Members are a small, practical group of top CFOs who are willing to go ahead and participate in the LIVE events. The live events are open only to Insider Members to keep it practical and interactive.

But regular paid monthly/annual members get full access to the editorials recap of live events.

Insider Members can access the full recording below

Read more

They can’t see their families on weekends. They have to spend so much time reviewing data and building board decks. But it doesn’t have to be this way.

Al can change how a CFO works.

You don’t have to be chained to spreadsheets anymore.

Paulo Tabarelli has been a CFO several times over. He now runs finance for a family conglomerate in petrochemicals and paints, with businesses across the UAE, Saudi Arabia, Oman, Qatar, Lebanon, Italy, and Nigeria.

Over steak, he told me his previous boss once asked him where he added the most value. Not the close, not the reporting. The daily commercial meeting.

He sits in that room, hears what is going on, and connects it to the numbers he already has. That is where the job actually happens.

Think about your own week.

Every transaction in your business has an account it belongs to.

The rumor a salesman repeated to you on Tuesday has nothing.

So you carry it. And two weeks later you half remember it. Two months later it is gone, and the thing it would have warned you about arrives anyway.

That is the real cost. Not the hours.

The call you can no longer make, because the inputs are gone.

So Paulo built a second CFO Brain.

Claude reads it every morning, before it analyzes anything.

I rebuilt the whole thing from scratch this week, so the screenshots and numbers below are mine rather than his. Setup takes one prompt and about ten minutes.

Setup takes a few Claude prompts and about 10 minutes.

Let’s dive in.

Building a second brain as a CFO with Claude and Notion

Read more

By May, about 40%.

The technology did not get 5 times better in four months. You already know that. What you may not know is where the money actually went.

It went to GPUs. And the people cut were the financing.

And when a stated reason moves that fast while the underlying thing barely moves at all, you are not looking at a technology story. You are looking at a narrative that pays.

I want to walk you through what is actually happening in these decisions, because it is a finance story, not a technology one. It is being decided in capital allocation meetings by people who do your job.

And the version being told publicly is not the version in the model.

Let’s dive in.

Sam Altman calls it AI washing

Challenger, Gray & Christmas has now tracked AI as the single most-cited reason for US job cuts for four straight months in 2026. In April alone, employers attributed 21,490 cuts to AI, roughly a quarter of that month’s total.

Some of these cuts are genuine automation. Support, QA, content production, and routine coding. That work is being absorbed, and the people doing it are losing jobs.

None of what follows is a denial of that.

But look at who is questioning the story.

Cognizant’s Chief AI Officer Babak Hodjat, whose entire job is selling AI transformation, told Nikkei Asia that

“Sometimes AI becomes the scapegoat from a financial perspective, like when a company hired too many, or they want to resize, and it gets blamed on AI.”

Sam Altman calls it AI washing.

A layoff framed around AI reads to investors as technological ambition.

The same layoff framed as over-hiring or soft demand reads as failure.

Executives cite AI when the real driver is that they lack the cash flow to fund AI investment without freeing up capital somewhere else.

It is not a technology claim at all.

It is a funding claim.

Layoffs are not the savings. Layoffs are the financing.

Here is the arithmetic that reframes the entire story, and it comes from the cleanest case study available.

Meta’s total human compensation, every salary, every benefit, and every stock grant comes to roughly $27 billion a year.

Meta’s 2026 capital expenditure guidance runs to $145 billion.

If Meta fired every single employee tomorrow, the entire payroll saving would cover less than a fifth of the infrastructure bill.

The capex line is four to five times the whole payroll line. So when 8,000 people were cut in May, that was never a cost-reduction program in any meaningful sense. The savings are a rounding error against the spend.

Meta’s own CFO said so on the Q1 earnings call. Susan Li’s words:

A leaner operating model “will allow us to move more quickly while also helping to offset the substantial investments we are making.”

Offset the investments. That is a CFO describing a financing decision in public, correctly, using the right word.

The pattern repeats across the sector.

• Oracle cut roughly 30,000 roles, about 18% of its workforce, trading an estimated $8 to $10 billion of annual operating cash flow for GPU capacity to service a $300 billion contractual obligation through 2032. The company was profitable and growing while it did this.

• Cisco’s CFO Mark Patterson was unusually direct about his own restructuring. It was, he said, “really not a savings-driven restructure.”

• Across Amazon, Microsoft, Alphabet, and Meta, 2026 capital expenditure runs to roughly $700 billion, close to double 2025.

So when a company says it is reducing headcount because of AI, there are two possible meanings, and they are not the same thing at all.

One is that software now does the work.

The other is that the company wants the payroll dollars for compute.

Only the first is a story about your team’s productivity. The second is a story about your balance sheet, and it is the one running at scale right now.

I have not seen this written anywhere, and this is the reason this matters more than a media-criticism argument.

Capital expenditure does not hit the P&L when you spend it.

It arrives later, as depreciation, spread across the asset’s useful life.

Meta is running something in the region of $145 billion of capex against an AI server life of roughly five and a half years. That implies something close to $26 billion of annual depreciation from those assets alone, starting around 2027.

Microsoft faces comparable arithmetic. Oracle’s is worse because its buildout is heavily debt-funded, so it carries interest alongside the depreciation.

Now, let’s put the two facts together.

These companies are cutting operating expense today, in advance, so that the depreciation wave arriving in 2027 and 2028 does not destroy their margins when it lands.

That is not AI replacing workers.

That is a CFO looking at a five-year depreciation schedule and pre-emptively taking cost out of the operating line to protect a future EBITDA number.

And the cash pressure is already visible.

Meta’s free cash flow is projected to fall from $43.6 billion in 2025 to around $8.5 billion in 2026, roughly an 80% collapse, as capex absorbs operating cash. The company is spending somewhere between $315 and $370 million per day on infrastructure.

When free cash flow falls 80%, something has to give.

What gave was headcount, and the press release said AI.

Both statements are technically true.

Only one of them is the reason.

The Bottom Line

I am not arguing that AI destroys no jobs.

It clearly does, in specific functions, and the people affected are not comforted by the distinction I am drawing.

I am arguing something narrower and more useful to you.

The largest wave of AI-attributed layoffs in history is substantially a capital allocation event. Payroll dollars are being converted into compute dollars, on the judgement that GPUs will generate more return than the people they displaced.

That is a defensible position for a board to take. It is a normal finance decision, made by people in your seat, using your tools.

It is simply not the decision that is being described in public.

Which brings this to your desk, because the same logic is coming for you at your own scale.

You will not be spending $145 billion.

But you will be asked to fund an AI project, and the question of where that money comes from has exactly one honest answer. Something else stops being funded. Usually it is headcount, because headcount is the largest and most flexible line you control.

When that conversation happens, three things are worth holding onto.

1. Know which decision you are making. Cutting ten roles because software genuinely does that work is one decision. Cutting ten roles to free up budget for an AI investment is a completely different one, with a different risk profile and a different set of things that can go wrong. Both can be right. They should not be confused, least of all in your own model.

2. Say it accurately internally, whatever goes in the press release. If the board paper says AI efficiency and the model says funding reallocation, you have created a gap between the story and the numbers. That gap will be found. It is usually found by an auditor, a journalist, or an employment lawyer, and none of those are good days.

3. Watch your own depreciation schedule. If you are capitalizing AI infrastructure, that spend is coming back as depreciation for years. Model it now. The hyperscalers are cutting today for a bill that lands in 2027. If you are building anything meaningful, you have the same shape of problem in miniature and far less room to absorb it.

The headline says AI is taking the jobs.

The cash flow statement says something more specific.

Capital moved, and payroll paid for it.

Every CFO must be able to tell the difference.

And that’s all for today.

See you on Thursday.

Whenever you’re ready, there are 2 ways I can help you:

1. Advertise with the AI CFO Office.

2. If you’re building an AI-powered CFO tech startup, I’d love to hear more and explore if it’s a fit for our investment portfolio.

I’m Wouter Born. A CFOTech investor, advisor, and founder of finstory.ai

Find me on LinkedIn

Paulo Tabarelli got a call from an insurance company.

One of his customers had just had their credit insurance revoked.

He didn’t wait for it to show up in the numbers. He went straight to notion and wrote it down: customer X, insurance revoked, flag it if it shows up on tomorrow’s sales report.

All unwritten knowledge evaporates.

• A credit controller sends an email. Nobody reads it in time.

• A customer goes under. And a month later, the CFO is explaining to the board why the company sold six figures to a company that couldn’t pay, when someone on the team knew three weeks before it happened and said nothing, because there was nowhere to say it.

Paulo has been a CFO three times over, across a multinational FMCG business spanning more than 30 countries, a PE-backed retailer in the UAE, and a telecom in Dubai.

He’s now running finance for a family conglomerate.

And he’s rebuilding the finance function with AI around a loop instead.

Let’s dive in.

Roadmap to becoming an AI-native CFO

Most CFOs don’t fail at AI because they picked the wrong tool.

They fail because they never had a map for where the tool can take them.

Below is that map. Four stages, each one building on the last, from asking AI a question in a browser tab to running a finance function where the loop closes itself.

You won’t be at Level 4 by Friday. Almost nobody is.

Notion’s own research puts fewer than 2% of companies there today. What you can do is place yourself honestly on the curve, see exactly what separates your stage from the next one, and stop mistaking “I use Claude sometimes” for an architecture.

This AI roadmap will help you see how the work itself changes, how AI actually operates at each stage, what it does for the business, and which piece of the skill stack gets built to make it happen.

Download the full breakdown below

Read more

Thursday, August 13, at 11:00 AM ET.

This is not a demo. This is a 90-minute end-to-end walkthrough of how a real CFO actually uses Claude across every part of a modern finance function.

Live. Ask questions. Challenge what works and what does not.

Claude Masterclass for CFOs (LIVE)

Paulo Tabarelli Batista runs finance at RAR Holding in Dubai today, with the close and the board pack and the follow-ups that come with it. Over 15 years across multinationals, private equity-backed businesses, and family-owned groups. Transformations in FMCG, retail, e-commerce, telecom, and petrochemicals. Operations across five continents. Portfolios above $1B.

What Paulo will cover

• Chat for daily questions and quick analysis

• Projects for persistent work with the right files in context

• Skills for the workflows that compound every month

• Cowork for collaborative work across the team

• Connectors for live data from your ERP, BI, and source systems

The workflows running on top

• Monthly close and reforecast

• Board pack assembly and narrative

• Scenario planning and sensitivity analysis

• Audit and SOX response

• Strategic capital allocation

The qualitative layer nobody builds

• Turning meeting inputs and transcripts into structured follow-ups

• Using connectors to bridge conversation and analysis

• Building a system that remembers context between runs

• Where the numbers stop and judgement starts

The strategic view

• How to make your finance function AI-native

• Where Claude saves real time and where it does not

• What to deploy this quarter and what to wait on

Who this is for

CFOs, VPs of Finance, FP&A leaders, and controllers. Anyone running a finance function that needs to be ready for what comes next.

What to expect

90-minute live masterclass with Paulo walking through each surface in his actual Claude environment, joined by Wouter Born on the strategic CFO layer. Open Q&A throughout. Honest discussion of what works and what breaks.

Live masterclasses are exclusive to Insider Members, keeping them practical.

As a regular paid member, you will get an editorial recap of this session.

To enjoy the live experience, upgrade to Insider Member.

If you are already an Insider member, the registration link is below.

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This is not a demo. This is a 90-minute end-to-end walkthrough of how a real CFO actually uses Claude across every part of a modern finance function.

Live. Ask questions. Challenge what works and what does not.

Claude Masterclass for CFOs (LIVE)

Paulo Tabarelli Batista runs finance at RAR Holding in Dubai today, with the close and the board pack and the follow-ups that come with it. Over 15 years across multinationals, private equity-backed businesses, and family-owned groups. Transformations in FMCG, retail, e-commerce, telecom, and petrochemicals. Operations across five continents. Portfolios above $1B.

Most CFOs are using Claude wrong.

Every CFO reading this knows the moment arrived.

The question is no longer whether to learn Claude.

It is about how fast and how to make it safe.

What Paulo will cover

• Chat for daily questions and quick analysis

• Projects for persistent work with the right files in context

• Skills for the workflows that compound every month

• Cowork for collaborative work across the team

• Connectors for live data from your ERP, BI, and source systems

The workflows running on top

• Monthly close and reforecast

• Board pack assembly and narrative

• Scenario planning and sensitivity analysis

• Audit and SOX response

• Strategic capital allocation

The qualitative layer nobody builds

• Turning meeting inputs and transcripts into structured follow-ups

• Using connectors to bridge conversation and analysis

• Building a system that remembers context between runs

• Where the numbers stop and judgement starts

The strategic view

• How to make your finance function AI-native

• Where Claude saves real time and where it does not

• What to deploy this quarter and what to wait on

Who this is for

CFOs, VPs of Finance, FP&A leaders, and controllers. Anyone running a finance function that needs to be ready for what comes next.

What to expect

90-minute live masterclass with Paulo walking through each surface in his actual Claude environment, joined by Wouter Born on the strategic CFO layer. Open Q&A throughout. Honest discussion of what works and what breaks.

Live masterclasses are exclusive to Insider Members, keeping them practical.

As a regular paid member, you will get an editorial recap of this session.

If you want the live experience, upgrade to Insider.

If you are already an Insider member, the registration link is below.

Read more

Right question, wrong place.

Because here’s what actually happens.

Someone exports the P&L into Excel, drops it into Claude, and gets a good answer. Now two files exist. Next month, two more.

Count where they end up.

Slack. Email, forwarded twice. A laptop that goes home every night. A hotel PC during a board trip. WhatsApp, because that’s how your team works when something is urgent.

And at least one pasted into a free personal ChatGPT account, which trains on it.

Nobody made a bad decision.

Everyone was trying to work faster.

But think about what’s in those files. Next quarter’s numbers before they’re announced. The restructuring scenario with names attached. The commentary you wrote for the board and then quietly softened.

You can’t say where any of it sits right now or who has a copy.

So, to answer her directly: yes, Claude is safe.

Team and Enterprise sit outside model training entirely.

The model was never the risk. The files are.

Connect Claude through an MCP server with real authentication, and none of this happens.

• Users read only what they’re permitted to read.

• Claude writes back into the system, not into a file. Nothing gets exported.

• One version, because there’s one source.

The connection is the security control, not the policy asking people to stop emailing spreadsheets.

Most CFOs worry about the wrong layer.

They ask whether the model is safe while their financials sit in 14 spreadsheets and nobody knows which one is current.

This letter is how to configure Claude properly.

Five layers, in order, ending with the one that removes the files entirely.

Let’s dive in.

How to set up Claude safely as a CFO

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They’ve started asking what it returned.

And most CFOs can’t answer that, because nobody set up the measurement. The spend went through as a technology line. The pilots got approved on the promise of efficiency. Nobody agreed a baseline, and now there’s nothing to measure against.

Three things landed i…

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This is not a demo. This is a 90-minute end-to-end walkthrough of how a real CFO actually uses Claude across every part of a modern finance function.

Live. Ask questions. Challenge what works and what does not.

Claude Masterclass for CFOs (LIVE)

Most CFOs are using Claude wrong.

The CFOs getting the biggest results are not writing better prompts.

They are building skills.

Anthropic’s own finance uses Claude’s skills. Their CFO has said a report that used to take hours now takes 30 minutes, and the heaviest Claude user on the team is not the youngest analyst; it is the head of tax.

Every CFO reading this knows the moment arrived.

The question is no longer whether to learn Claude.

It is how fast.

Paulo is a sitting CFO. Not a former one.

Paulo Tabarelli Batista runs finance at RAR Holding in Dubai today, with the close and the board pack and the follow-ups that come with it. Over 15 years across multinationals, private equity backed businesses, and family-owned groups. Transformations in FMCG, retail, e-commerce, telecom, and petrochemicals. Operations across five continents. Portfolios above $1B.

He is not demonstrating a product.

He is showing you the environment he actually works in, including the parts that break.

What makes this session different

Most AI-in-finance content stops at the numbers.

Build a dashboard, run a variance, and produce a forecast. Useful, and it is only half the job.

Paulo’s angle is the other half.

Analyzing numbers is great, but the real problem was always the qualitative side. Connecting what people said in meetings to what actually needs to happen. Tracking whether things moved. All of that used to live in his memory, and nowhere else.

So he built Claude into the bridge.

Inputs come in from meetings and transcripts through connectors. He runs the analysis, layers his own context on top, and has Claude write the outcome to Notion. Next time it runs, it reads what is already in Notion, uses it as context, updates what changed, and flags what still needs exploring.

That is not a dashboard. That is a finance function with a memory.

What Paulo will cover

The surfaces, and where each one earns its place

• Chat for daily questions and quick analysis

• Projects for persistent work with the right files in context

• Skills for the workflows that compound every month

• Cowork for collaborative work across the team

• Connectors for live data from your ERP, BI, and source systems

The workflows running on top

• Monthly close and reforecast

• Board pack assembly and narrative

• Scenario planning and sensitivity analysis

• Audit and SOX response

• Strategic capital allocation

The qualitative layer nobody builds

• Turning meeting inputs and transcripts into structured follow-ups

• Using connectors to bridge conversation and analysis

• Building a system that remembers context between runs

• Where the numbers stop and judgement starts

The strategic view

• How to make your finance function AI-native

• Where Claude saves real time and where it does not

• What to deploy this quarter and what to wait on

Who this is for

CFOs, VPs of Finance, FP&A leaders, and controllers. Anyone running a finance function that needs to be ready for what comes next.

What to expect

90-minute live masterclass with Paulo walking through each surface in his actual Claude environment, joined by Wouter Born on the strategic CFO layer. Open Q&A throughout. Honest discussion of what works and what breaks.

As a paid member, you get full access to all written content. Live masterclasses are exclusive to Insider members.

If you want the live experience, upgrade to Insider. If you are already an Insider member, the registration link is below.

Read more

Not a variance commentary. Not a board deck.

Something where the model has nowhere to hide.

The message we get most often is some version of: give it a multi-entity, multi-currency consolidation, then tell us what happens.

Fair. That’s where real complexity starts.

And it’s the task most likely to break an AI model.

Every multinational CFO has plugged a CTA.

It’s 11pm. The group pack goes out tomorrow morning.

Four entities, four currencies, and your consolidation is off by an amount too small to justify another two hours and too big to pretend you didn’t see.

So you find the account that exists for exactly this.

The Cumulative Translation Adjustment, the equity reserve that absorbs the arithmetic gap you get when one balance sheet is translated at three different rates.

P&L at average rates, assets and liabilities at closing, and equity at historical.

You put the difference there.

Everything ties. You go to bed.

And some part of you knows you didn’t solve it.

You buried it in the one account nobody opens.

That’s the problem. A balance sheet that balances proves nothing if you decided the answer and worked backwards.

And it's exactly what AI models do when they hit something they can't resolve. They don't stop. They produce the number that makes it work. Every model before this one would have plugged the CTA, presented immaculate statements, and never mentioned it.

So I gave Claude Opus 5 the job your consolidation engine does.

Four entities, four currencies, a twenty percent minority interest in Canada, intercompany loans, management fees, product transfers, and goods still in transit at cutoff. Seven source files, no template, one rule: calculate the CTA from the actual translation mechanics, roll it forward, and never insert it as a plug.

I also stripped out the flags marking the duplicate invoice and the cutoff errors.

It had to find those itself.

If Claude Opus 5 can pass this test, it changes what CFOs can trust it with.

Let’s dive in.

How I built a multi-entity FX consolidation with Claude Opus 5

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“References to EBITDA make us shudder. Does management think the tooth fairy pays for capital expenditures?”

• EBITDA tells a story about profit.

• Cash tells the truth about the business.

• The gap between the two is exactly what a month like this is hiding.

No single report holds it. Finding it means reading a dozen files against each other, and that has always been a job for a senior person and a long week.

Until now, AI did not help much with this.

It answered questions. You asked what the AR balance did; it told you. You asked it to explain a variance; it explained the one you had already found. The thinking, the part where you decide which threads to pull and how they connect, stayed with you.

But when Anthropic released Claude Fable 5, the public version of its Mythos-class model, the coverage was all about cybersecurity because that is where Mythos built its name. It can take a pile of small, unremarkable signals and chain them into a vulnerability that no single signal reveals.

Finance has the same shape.

The cash miss is never one thing.

It is a channel mix that quietly shifted toward slower-paying customers, plus an AR build, plus inventory bought for the old mix, plus AP going out the door faster than planned, plus settlements that lagged, plus returns running hot, plus a forecast still running on last quarter’s assumptions.

Each one looks like noise. Chained together, they are the whole story.

That is the shift, and it has nothing to do with benchmarks.

• The old use case was: explain this variance.

  

• The new use case is: investigate why the result does not make sense, prove it with evidence, and help me decide what to tell the board.

  

The first is a chatbot, and the second is a forensic investigator.

You’ll get the forensic-finance-investigation skill (.md) and data pack.zip; download it below.

You can download the skill and the data pack this weekend and point it at your own close. Pick the question your team has been stuck on for a quarter. Let it investigate.

Let’s dive in.

How to run a forensic-finance investigation with Claude Fable as a CFO

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