I used Opus 4.6 to build in 10 minutes

what it takes a Goldman analyst to build

in a day. I'm not a Goldman analyst. And

then I built a board deck for that in

just 20 more minutes. General

intelligence just showed up in Excel and

PowerPoint and its name is Claude. I

built a full operating model last week.

Revenue projections, cost structure,

unit economics, the works. And that just

took a few minutes. And after that,

Claude in PowerPoint took over and built

slides, executive summaries, financials,

key metrics using an actual slide deck

template. Just a few minutes later, I

had a presentation with charts

referencing live Excel data formatted in

the correct fonts and colors. And this

is something that would have taken a

couple of days just a few months ago.

And yes, I did mean it about Goldman. A

Goldman Sachs analyst looked at the

model and told me it was solid. It's the

kind of output that would have probably

taken him a day to build. and it took me

30 minutes total with a deck included.

This is the piece of the week's news

that most people are going to sleep on

because it doesn't have the drama of a

benchmark score. It doesn't have the

spectacle of 16 agents building a

compiler or an agent managing 50

developers. This is just Excel, right?

It's just PowerPoint. The tools nobody

thinks about twice. And yet, we spend

our days there. And as of this week,

effectively, they have general

intelligence inside them. The same

intelligence that built that C compiler,

the same intelligence that found 500

zeroday vulnerabilities on its own after

security researchers had passed the code

as secure. And here's the point that

should really stop you. It's not about a

single product release. I don't care if

you think Opus 4.6 is the sauce or not.

The point is that this ship into Excel

and PowerPoint paves the way 4.7 and

then 5.0. It's not that the applications

are going to change. PowerPoint will

look the same. Excel will look the same,

but the intelligence inside them is

going to compound. This is the dumbest

Excel and PowerPoint will ever be. Now,

I covered Opus 4.6 in a separate piece

earlier this week. What the model can

do, why it matters. I talked a lot about

agents. This is about what happens when

that intelligence shows up out

billion people use every single day and

why it turns Microsoft into just a dumb

pipe and what that means for how you

think about work when your tools are

getting smarter faster than you can

update your assumptions about them. So

what actually shipped? Two things

happened in the past couple of weeks and

taken together they represent something

bigger than either one of them by

themselves. On January 24th, Anthropic

opened Claude and Excel to pro

subscribers. Anyone paying 20 bucks a

month or more. The feature had been

limited beta. The feature had been in

limited beta since October of last year,

but the January release made it broadly

available. Then on February 5th,

alongside the Opus 4.6 6 launch, two

things happened at once. Claude and

Excel upgraded to 4.6, the same model

that powered all of those amazing coding

results. And Claude and PowerPoint

launched for the first time. The Excel

integration is not a chatbot bolted onto

the sidebar, even though it looks like

it. It actually operates directly

against your work. It reads your

existing data. It understands your tab

structures. It writes and debugs

formulas. It builds pivot tables. Yes,

it's absolutely not perfect. Yes, it

needs work sometimes and a check from an

experienced analyst, but I'm going to

keep reminding you this is the dumbest

that model is ever going to get in

Excel. The PowerPoint integration is

more interesting than most coverage

suggests. It doesn't just generate

slides. It reads your slide masters,

your layouts, your fonts, your color

schemes, your template, your colors,

your template, your font hierarchy. It

produces slides that don't look like AI

made them because they match the design

system your team already uses. And that

has been a huge breakthrough for AI in

the past month or two that most people

have slept on. Back in the fall of 2025,

building an AI PowerPoint meant you had

to give up your own templates. Not

anymore. The combination of Excel and

PowerPoint together matters more than

any of these tools by themselves.

Because both run on the same underlying

model, Claude is able to bring the same

intelligence to bear across both. and

claude produced Excel documents play

very nicely with claude produced

PowerPoints. So if you're building an

analysis in Excel and then you tell

Claude in PowerPoint to generate the

board deck off of that analysis, it's

going to be very easy to get from data

to decision in a single sitting. That's

the promise of working with Claude

seamlessly across a bunch of different

Microsoft artifacts. So how do you get

it? This is the part most of the

coverage skips. So let me be specific.

Claude and Excel is available now to

everybody on Claude's pro plan at 20

bucks a month. That's it. Very simple.

Same price as Netflix. Just install the

Claude desktop app, enable the Excel

integration, and it appears inside

Excel. Claude in PowerPoint is harder to

get right now. It launched on February

5th and is currently only available on

Max Plan, which is like a hundred bucks

a month. I think it's because you burn

more tokens on PowerPoint than Excel.

It's not yet out on Pro. And if you need

both tools and you're an individual, the

max plan is the only option you've got.

The pricing matters because of what it

implies about the cost of intelligence.

Junior financial analysts can cost, I

don't know, six figures, $100,000,

$120,000 fully loaded. An associate at a

consulting firm can build 300 to 500 an

hour. At that price, between 20 and 100

bucks a month for Claude and Excel and

PowerPoint, there are a lot of

organizations that are going to start

asking themselves if junior analysts are

adding incremental value. I'm not saying

the junior analyst role is obsolete. I'm

saying the junior analyst who only

builds models and decks manually has a

big big problem because that scarce

skill is no longer scarce and you're

going to start to get measured by how

quickly you can ramp on AI tooling and

expand your spam. Here's where it gets

really interesting because most people

comparing Claude and Excel to Microsoft

Copilot miss the point entirely. They're

stuck in formulas. They're stuck talking

about Microsoft native integrations,

etc. Pay attention. Anthropic partnered

with Moody's, the London Stock Exchange

Group, Thirdbridge, and others to build

financial data connectors directly into

the Claude ecosystem. These are not

generic web scrapers. their

authenticated structured data feeds from

platforms that institutional finance

runs on. Which means in practice, you

can ask Claude to build a comparable

company analysis and instead of manually

pulling data from a terminal, the model

will query live financial data through

those connectors and populate your

spreadsheet with real numbers. Anthropic

also ship pre-built financial skills,

purpose-built workflows for the tasks

that eat most of the analysts week,

comparable company analysis, discounted

cash flow models, due diligence, data

packs, etc. These aren't templates that

you fill in. They're intelligent

workflows that understand what a

discounted cash flow model actually

needs and how to structure the

assumptions tab to support them. For

anyone who has built a discounted cash

flow model from scratch, you know that

the mechanical work involved takes a

long time. Not because it's conceptually

difficult, but because there are

hundreds of cells that all need to

reference each other correctly.

Enthropic spied that pile of mechanical

work and realized with the right data

feeds and the intelligence of Claude,

they could knock that out and it would

just make the spreadsheet dumb plumbing.

And the intelligence is what would

matter. I do need to address the is this

real or is it a demo question heads on

because I get so many questions in the

comments after videos like this. Nate,

this is hype. Nate, you're overhyping

things again. I think the answer really

matters here. Enthropic announced a

Goldman Sachs partnership on February

6th, and that has already been ongoing

for months and months and months, while

Goldman essentially pioneered this

behind the scenes. Goldman is deploying

Claude across accounting and compliance

workflows now as a production tool. When

the most prestigious investment bank in

the world puts this in production for

internal ops, I think you know the demo

question got answered. AIG reported that

Claude made their document reviews five

times faster with accuracy improving

from 75% to over 90%. Not faster at the

expense of quality. Faster and more

accurate at the same time. The error

rate went down while the speed went up.

That was impossible in the 2010s era of

software and earlier. That is a

signature of a tool that does not get

tired, that does not skip the boring

rows, that does not assume the numbers

in the summary tab match without

checking. Meanwhile, the banks that

manages Norway's $1.7 trillion sovereign

wealth fund reported an estimated

$213,000

hours saved from Claude and Excel. This

is what it looks like when you target a

painoint that is scaled across a 1 and a

half billion user base in Microsoft. And

this is why Microsoft should be worried

because Claude's entire strategy

disintermediates Microsoft's influence

on their own user base in their own

tool. Let me walk through a few specific

workflows because not everybody's a

financial analyst and I want to give you

a sense of what general intelligence in

your tools actually looks like. Let's

start with an operating model. Let's say

you open a blank workbook and you have a

dream of a small business and you tell

Claude, "Please build me a three-year

operating model for my small business.

This is my revenue target. This is my

dream of how many people I want to hire.

This is how many customers I want to

get. This is the kind of product I have

and what I want to sell it for. I don't

know how to build a business operating

plan. I need your help. It turns out

Claude does a really, really good job at

that. It may not be perfect, but it gets

you about 90 95% of the way there out of

the gate. How about a board deck? Let's

say you've built the model and you want

Claude to build a PowerPoint you can

show your banker to get a small business

loan to get started. Claude can read the

Excel file you upload. It can understand

it because again, it's the same

intelligence underneath both. It can

generate the charts that reference

actual numbers. It can apply your

company's slide template and put out

something that you can go to a banker

with or you can go to an investor with.

Let's say you're a startup founder and

you're pitching a series B. You have

your financials in Excel and a pitch

template your designer built last

quarter. All you have to do is tell

Claude, "Hey, build a 12 slide pitch

deck from these financials. Here's where

we want to go. Here's the arc of the

story." Claude will just do it. It will

use your fonts, your colors, your layout

grid. And by the way, that is all new

since last fall. The last time I talked

about Excel, I had to be like, "It's

amazing. It does PowerPoint, but one,

it's not in PowerPoint, and two, good

luck using your own templates and

layouts." Not anymore. Not anymore.

That's how fast things move. What about

due diligence? Let's say you're trying

to understand a small business you want

to buy. So, you upload 3 years of

financial statements, and you tell

Claude, "Please build me a due diligence

data pack and flag anything unusual."

Claude saves you dozens of hours combing

through those financial statements and

greatly increases the probability you're

going to see something that might be a

red flag that might stop that

acquisition and save you a business

deal. Let's say you're a product manager

and you want to do comparable company or

comparable product analysis. You name a

few companies that are competitors and

Claude can pull all of the relevant

trading data, but also the product data

and actually build you a competitor

spreadsheet analysis from scratch in

just a few minutes. What about a

quarterly business review? Your

department heads submit their numbers in

separate spreadsheets. You consolidate

it all in Excel. You can tell Claude and

PowerPoint, "Please build me the QBR

deck with 15 slides using our corporate

template using these numbers." Done.

Now, all of these are finance workflows,

but there are non- finance workflows

that are just as important. I want to

call out. What about a strategy

analysis? You have a spreadsheet of 50

competitors with market positioning and

recent funding routes. You want to

understand how to score each competitor

on six different dimensions and weight

by strategic priorities. You just give

it to Claude in Excel and it can do it.

You give it to Claude in PowerPoint

after that and it can build a

competitive landscape deck with a

positioning matrix, a threat assessment

by segment, recommended strategic

responses. What about sales enablement?

Your sales team sends the same 10 slide

pitch to every prospect. Why not

handclaw the company's CRM data and

their last three earnings transcripts

and tell it to customize the pitch for a

CFO audience at a mid-market

manufacturing company? That is trivial

to do. Now, what about HR and people

analytics? You export 12 months of

employee survey data, 2,000 responses,

free form text, like art scales, eight

departments. You tell cloud in Excel,

hey, analyze the sentiment by

department, identify the three strongest

predictors of attrition risk, and build

a summary dashboard. It'll do it. What

about program management? You have a

master tracker in Excel with 200 line

items across a dozen work streams.

Owners, deadline, status, dependencies.

Claude can oneshot a program status deck

for the steering committee. What about

the formula and data work that nobody

likes to talk about before you even get

to the headline workflows? There's just

the daily grind that cla and Excel can

eliminate. Debugging a VLOOKUP chain

that breaks when someone sorts a column.

Writing a Power Query transformation to

clean vendor data. building conditional

formatting rules, tracing a circular

reference across four tabs. This is the

kind of work that eats hours a day when

you live in spreadsheets. And it's just

and it's the first thing Claude handles

and the thing that frees up the most

time before you even start the big

workflows. Every one of these workflows

exists today, not next quarter, not as a

wait list, right now. And here's what

none of the individual workflows make

obvious enough. The time savings alone

aren't the thing that adds up. The time

savings don't just add up, they

multiply. Having Claude in Excel saves

you time on modeling. Having Claude in

PowerPoint saves you time on deck.

Having both can save you twice the time

because it eliminates an entire category

of work that existed solely because the

tools could not understand what each

other built in the age before shared

intelligence. Think about what actually

eats your week. It's not just building

the model. It's not just building the

deck. It's the mental work that comes

from the translation layer in between.

You finish the analysis in Excel. Then

you open PowerPoint. You have to start

thinking and reexplaining the same data.

You have to start trying to think about

how it changes when you position it in a

deck form versus a spreadsheet form.

That translation cost is where most

knowledge workers spend the majority of

our production hours. It's not

necessarily even thinking, right? It's

translating into a different format for

a different audience. When one

intelligence spans both tools, that

translation cost starts to drop towards

zero. Claude doesn't just export the

data from Excel and import it to

PowerPoint. It deeply understands the

data in Excel because the same

intelligence built it and it carries

that understanding without you having to

mess with it directly into the

presentation. The chart it builds in

PowerPoint reflects an understanding of

what the model extracted from the

analysis. The narrative on the slide

reflects a deeper interpretation that

the model formed when building the Excel

spreadsheet. Context flows more easily

because the same model is building both.

Now, I'm not saying that there's a

direct export to PowerPoint from Excel

today, but I would bet you a lunch that

is coming in the next couple months. And

in the meantime, having that ability to

have a model understand how both Excel

and PowerPoint works and easily

translate context between them is a

godsend. What we're talking about here

is the context layer that is the future

of work and it's going to be enormous.

It's not really about the application

layer anymore. Microsoft owns that. It's

not even necessarily about the data

layer. Your databases own that. The

context layer sits between them. It's

the AI's accumulated understanding of

your data, your brand, your audience,

your goals. Every time the model touches

a new tool, the context layer is going

to get a little bit richer. Every time

it sees how your board deck differs from

your team Slack update, it's going to

learn something about how your org

translates information for different

audiences. Applications are containers.

The data is raw material. The context

layer is what Anthropic is making a play

for here. It's the intelligence that

understands what the data means and how

to express it for different audiences in

different formats. That is where the

value is accumulating and that is what

Enthropic is laser focused on with

claude in Excel and Claude in

PowerPoint. And unlike the application

layer which Microsoft has owned for

decades and which barely changes year

after year, no matter what they say, the

context layer improves automatically

with every single model upgrade and

every new tool integration. It's the

fastest compounding asset in your tech

stack and most organizations don't even

know it exists. And that's what

separates what happened this week from a

normal product launch because on Tuesday

night, the night before Opus 4.6 launch,

Claude and Excel ran on Opus 4.5, a

strong model, capable, useful, and on

Wednesday morning, it ran on Opus 4.6.

Nobody installed anything. Nobody

downloaded a patch. Nobody sat through a

migration wizard. The spreadsheet looked

the same, but it suddenly had x more

context and dramatically better

reasoning and the ability to hold an

entire multi-tab model in working memory

and understand how every cell relates to

every other cell. Think about what that

means for the next upgrade. Opus 4.7 is

coming. So is 5.0. Each time a new model

ships, every claw powered Excel and

PowerPoint on Earth gets smarter

overnight without you doing anything.

The operating model that took 10 minutes

with Opus 4.6 six might take five with

4.7 and be 99% right, not 95. The pitch

deck that needed 20 minutes of back and

forth with 4.6 might need 5 minutes with

5.0. The quality of reasoning continues

to improve. The depth of analysis

deepens. The output moves closer to

perfect. And it's not because you

learned a new tool. It's because the

tool learned on its own and got better.

This is a fundamentally different

upgrade cycle from anything the software

industry has produced. Microsoft ships a

new version of Office every few years.

Feature updates land quarterly. The pace

of improvement is set by the software

company's release schedule, its

engineering priorities, its QA cycle.

The pace of improvement is actually set

by Anthropic's insanely fast pace of

model releases. And those are happening

every couple of months with capability

jumps that would be measured in years by

traditional software standards. That

3mon gap between 4.5 and 4.6

context expansion. 5xed in just 3

months. What's 4.7 going to bring?

Almost certainly your mental model of

what AI tools can do is now behind

reality. It is hard to keep up with how

fast reality is moving right now. The

task that Claude maybe couldn't handle

last month in Excel, maybe it handles it

now. The presentation quality that

wasn't sufficient in January because it

didn't match your templates, maybe it

works now. And by April, both will have

improved again. The assumption is that

you learn your tools once and they stay

the same. That the thing you tested last

quarter is the same thing that's running

today. That assumption is dead. Your

tools are getting smarter faster than

you're updating your expectations of

them. And the practical consequence is

that you're going to need to re-evaluate

your workflows continuously. Not

annually, not when someone sends you a

blog post all the time. because the

boundary between the tasks I do myself

and the tasks that it is smart to

delegate to AI just keeps moving and

it's moving in one direction and it's

moving real fast. I can hear the

Microsofties in the comments saying,

"Doesn't Microsoft Copilot already do

this?" Well, the answer is sort of and

the real answer leads somewhere more

important than a feature comparison.

Pilot's advantage of course is a native

integration. It's built into Microsoft

365 from the ground up. The UI is

seamless. It understands the Office

ecosystem in a way a third party tool

doesn't. If your org lives within

Microsoft, C-pilot is the path of least

resistance and sometimes it's sold that

way. Claude's advantages of course are

reasoning depth, local file support,

financial data connectors. Claude wins

on the tasks that require genuine

reasoning over complex multi-step

problems like debugging a formula chain

across 12 tabs or structuring an

analysis that requires judgment about

what matters. And the local file setup

matters a lot as well. C-pilot will

require one drive for most of its

functionality, which means your files

live in the Microsoft cloud. Of course,

it's a Microsoft play. For orgs handling

sensitive financial data, it's kind of

nice to not have to do that with claude.

But in the end, the co-pilot comparison

is the wrong frame for what's actually

going on. I think the real story is more

structural than that. In September of

2025, Microsoft added Claude models to

its co-pilot. Yes, that's right. There's

Claude in co-pilot, too. So Microsoft,

the company that invested $13 billion in

OpenAI, built C-pilot on OpenAI's models

originally, now hedged by putting a

competitor's brain, quote unquote,

inside its own product. When the company

that owns the application layer starts

offering someone else's intelligence

inside it, it tells you where the value

is migrating. Microsoft really is

becoming a dumb pipe. It's not

overnight. It's not completely, but the

pattern is unmistakable and it mirrors

what is happening to every platform that

is getting caught between a

commoditizing interface and a rapidly

improving capability layer. AT&T built

the network. Then the network became a

pipe for Google and Netflix. The value

migrated from the carrier to the

service. Browsers were supposed to be

the platform and then they became

rendering engines for web applications.

Value migrated from the container to

what ran inside it. Excel is a grid of

cells. has been essentially the same for

20 years. New features are at the

margins. It's the same fundamental tool.

PowerPoint is just a canvas for slides.

Same story. The intelligence layer is

what is compounding. The application

layer is frozen. And that is why

Microsoft is hedging by offering every

major AI model inside its own products.

That's exactly what a dump pipe does. It

carries whatever traffic flows through

it. The implication for your

organization is to stop thinking about

your tool choice quite as much and start

thinking about your intelligence choice.

The question is not should we use Excel

or Google Sheets. It's which AI model

powers our spreadsheet and is it the

best one for the work that we do and our

workflows. You need to start thinking of

applications as containers and asking

about where the intelligence is coming

from and whether the intelligence has

the value you're looking for. This is

the thing that we aren't talking about

enough. If the cost of producing these

artifacts is collapsing towards zero

extremely rapidly, what happens when

these artifacts are free? So much of our

traditional human-drived software model

starts to break apart. Consulting

breaks. Not because consultants are

unnecessary, but because the business

model depends on a very large time

component that is about to disappear.

When a deliverable that build at 40

hours of associate time could be

produced in 40 minutes, that whole model

isn't going to work anymore. The correct

response here is not panic. It's

recognizing what becomes valuable when

artifacts go to zero. Analysis is

becoming a commodity. Judgment is

becoming very, very valuable. Knowing

how to build a discounted cash flow

sheet, well, Claude can do that. knowing

which assumptions you want to stress

test, which scenarios to run, what

stories the numbers are telling, and how

to read the clawed spreadsheet and find

the mistakes. There's judgment there,

and judgment is what clients are going

to pay for and boards are going to need.

The people who thrive in this

environment are not the ones who will

build the best artifacts with AI.

They're the ones who know which

questions to ask before whatever the

model is building gets gets built.

They're the ones who can look at a

completed analysis and say, you know,

this is technically right, but the whole

question is wrong. It's framed wrong.

That's value. That's where human value

is going. They're the ones who

understand the business well enough to

know which of the 17 possible analyses

Claude produced is the one that should

actually drive the decision. This is the

strategic skill I keep coming back to.

When production is free, economic

returns flow to people who know what's

worth making. Not necessarily more of,

not necessarily better of, not even

faster, because the 10-minute operating

model is worthless if you're modeling

the wrong thing. The 30 minute board

deck I talked about is worthless if it

tells a story that doesn't match reality

and doesn't line up with investor

expectations. Sometimes reality and

investor expectations don't line up, but

that's a different story. The tool will

make you faster. Only you can make sure

it's right. And there's an uncomfortable

truth here that is hiding inside all of

this. capability and that is a tidal

wave of slop. Every tool that makes it

easy to produce excellent work makes it

super easy to produce garbage and we are

about to drown in AI generated garbage

that looks professional. Researchers

have started calling it work slop and

it's true. It's AI generated

professional content that looks

technically competent and is completely

hollow. The estimated productivity cost,

by the way, $186 per employee per month

in time wasted processing work. That

sounds like it means something and says

nothing. That adds up and I bet it's

underelling. This isn't really about an

AI adoption problem. It's not about

whether you rethink your workflow or

just bolt AI onto the old workflow. This

is a fundamentally different problem.

This is about whether you have the

judgment to know which work should exist

and whether you work on a team that

displays that judgment as well. The same

capability that lets a thoughtful

strategist produce a day's work in 10

minutes lets a careless operator produce

a week's worth of polished nothing in an

afternoon. The tool will never know the

difference because you are the one that

maps what is needed onto the business

context and what the market requires.

And that's on you. In this sense, taste,

which gets talked about a lot, it's not

an aesthetic preference. It's not

something that is impossible to learn.

It's just the ability to distinguish

between output that serves a really

interesting human purpose that matters

and output that just exists. It's

knowing that a 40 slide deck that Opus

can create may look impressive, but it's

not as valuable as the 10 slide deck.

It's knowing the third scenario in the

model is what the board needs to see,

not the other two. It's knowing when the

analysis is done,

you shouldn't add more data because

that's just going to dilute things.

Organizations that have people with good

judgment are about to massively

outexecute the same organizations with

the same tools in the same industry that

don't have people with good judgment.

Good judgment is about to supercharge

economic activity for organizations that

understand how to deploy it. I want to

leave you with the implication that I

think matters the most. For 30 years or

more, professional value has been built

on execution skills. Can you build the

model? Can you write the code? Can you

design the spreadsheet? Can you

structure the analysis? Those execution

skills created our whole modern

knowledge economy. They're what

universities teach. They're what hiring

managers were taught to screen for. That

execution premium is just evaporating

now. Not in five years. Now, the

10-minute operating model isn't a

preview of a future. It's a product you

could buy today. But what is not

evaporating is the thinking that sits

above the execution layer. We have to

move up a level of abstraction in our

work as knowledge workers all of us. Now

it's the ability to frame the right

question. It's the strategic awareness

to know which analysis matters because

the tools are going to keep getting

better. The thinking is the place that

has to have the value. Claude can build

the vehicle for your thinking, but

Claude cannot replace human judgment.

And in that sense, I think Anthropic has

done a great job calling out Claude as a

tool for human thinking, similar to a

chalkboard or a notebook. That's the

right frame. And I think that's a very

compelling frame for professionals who

are looking to elevate our art in the

age of AI. We got to do better because

the AI is coming for the traditional

execution skills that define knowledge

management. And so my challenge to you,

if you haven't tried Claude in Excel, if

you haven't tried Claude in PowerPoint,

give it a try. But more importantly, and

yes, I have tons of guides on that in

Substack, I wrote up a whole guide just

for that for today. It's going to be

great, but I don't care about that. The

point is that you need to try it and you

need to understand that it is your

ability to frame problems. It is your

ability to decide what is good that is

going to distinguish your value long

term. All of that stuff that you were

proud of around execution that's going

to go the way of the dodo. The models

are going to keep getting better. What

was 95% good will be solved by the

middle of the year. It's your ability to

say this is the right direction to go in

that is going to make or break your

career in 2026 and 2027. Good luck and

have fun in Excel. It's a lot less

painful now than it was 10 years ago.

And yes, it really is true. PowerPoint

can now work with your company's

templates. One of the biggest wins of

2026, I think. All right. Have fun,

guys.