AI-Powered Excel: Prompts and ROI
Key Points
- AI integration in Excel (via Claude and Microsoft Copilot) is a game‑changing development that lets large‑scale, complex spreadsheet tasks be handled automatically.
- Claude’s newest Sonnet 4.5 model can extract and analyze multi‑currency data from a simple screenshot, but the strongest features currently require the pricey “max” plan.
- Microsoft Copilot’s built‑in Excel builder, while a bit less powerful than Claude with optimal prompts, is readily available to most users and still offers substantial automation.
- The transition from text‑only LLMs to numeric‑aware models forces a new ROI mindset: we must decide which calculations are best left to AI versus human effort and budget accordingly.
- Practical prompt techniques demonstrated in the video can shave hours off daily Excel work, and these capabilities are expected to become broadly accessible within months, so early adoption is advised.
Sections
- Unlocking AI-Powered Excel - The speaker showcases how Claude’s new Excel capabilities and AI prompting can automate complex multi‑currency analyses, save hours of work, and reshape decisions about investing time and money in AI tools.
- Claude: AI Financial Modeling Assistant - The speaker highlights Claude’s ability to quickly generate and organize complex financial statements, ROI models, and note‑taking tasks, stressing that effective prompting delivers significant time savings and value for finance teams.
- Crafting AI Prompts for Excel - The speaker outlines a step‑by‑step method for designing clear, intent‑driven AI prompts that preprocess raw accounting CSV data and produce a monthly P&L in Excel, emphasizing modest upfront effort and modular prompt construction.
- Managing Ambiguity and Excel AI Integration - The speaker explains how to flag uncertain cases for human review while demonstrating the new Excel co‑pilot’s ability to create spreadsheets, apply formulas, and streamline budgeting tasks.
- AI‑Powered Financial Dashboard Guide - The speaker explains how to input data into Claude to generate growth analysis, cash‑runway projections, visual charts, and professionally formatted key‑metrics dashboards for use in presentations.
- AI-Assisted Assumptions Sheet Creation - The speaker outlines creating a master assumptions sheet, manually refining seasonal and hiring inputs, then using AI prompts to generate a cleaned spreadsheet and build a revenue model with cohort stacking.
- Briefing LLM for Data Cleaning - The speaker outlines how to describe a messy data export—detailing its inconsistencies, specifying precise cleaning steps, quality checks, and output expectations—to give an LLM a clear, actionable briefing for automated data remediation.
- Unlocking AI‑Powered Excel Efficiency - The speaker urges users to adopt Claude Max–driven AI prompts for Excel, emphasizing that even modest time savings can justify the cost and that AI has the potential to accelerate spreadsheet work by orders of magnitude compared to traditional methods.
Full Transcript
# AI-Powered Excel: Prompts and ROI **Source:** [https://www.youtube.com/watch?v=xCrd3ajdlzw](https://www.youtube.com/watch?v=xCrd3ajdlzw) **Duration:** 00:24:56 ## Summary - AI integration in Excel (via Claude and Microsoft Copilot) is a game‑changing development that lets large‑scale, complex spreadsheet tasks be handled automatically. - Claude’s newest Sonnet 4.5 model can extract and analyze multi‑currency data from a simple screenshot, but the strongest features currently require the pricey “max” plan. - Microsoft Copilot’s built‑in Excel builder, while a bit less powerful than Claude with optimal prompts, is readily available to most users and still offers substantial automation. - The transition from text‑only LLMs to numeric‑aware models forces a new ROI mindset: we must decide which calculations are best left to AI versus human effort and budget accordingly. - Practical prompt techniques demonstrated in the video can shave hours off daily Excel work, and these capabilities are expected to become broadly accessible within months, so early adoption is advised. ## Sections - [00:00:00](https://www.youtube.com/watch?v=xCrd3ajdlzw&t=0s) **Unlocking AI-Powered Excel** - The speaker showcases how Claude’s new Excel capabilities and AI prompting can automate complex multi‑currency analyses, save hours of work, and reshape decisions about investing time and money in AI tools. - [00:03:46](https://www.youtube.com/watch?v=xCrd3ajdlzw&t=226s) **Claude: AI Financial Modeling Assistant** - The speaker highlights Claude’s ability to quickly generate and organize complex financial statements, ROI models, and note‑taking tasks, stressing that effective prompting delivers significant time savings and value for finance teams. - [00:07:10](https://www.youtube.com/watch?v=xCrd3ajdlzw&t=430s) **Crafting AI Prompts for Excel** - The speaker outlines a step‑by‑step method for designing clear, intent‑driven AI prompts that preprocess raw accounting CSV data and produce a monthly P&L in Excel, emphasizing modest upfront effort and modular prompt construction. - [00:10:25](https://www.youtube.com/watch?v=xCrd3ajdlzw&t=625s) **Managing Ambiguity and Excel AI Integration** - The speaker explains how to flag uncertain cases for human review while demonstrating the new Excel co‑pilot’s ability to create spreadsheets, apply formulas, and streamline budgeting tasks. - [00:13:45](https://www.youtube.com/watch?v=xCrd3ajdlzw&t=825s) **AI‑Powered Financial Dashboard Guide** - The speaker explains how to input data into Claude to generate growth analysis, cash‑runway projections, visual charts, and professionally formatted key‑metrics dashboards for use in presentations. - [00:16:56](https://www.youtube.com/watch?v=xCrd3ajdlzw&t=1016s) **AI-Assisted Assumptions Sheet Creation** - The speaker outlines creating a master assumptions sheet, manually refining seasonal and hiring inputs, then using AI prompts to generate a cleaned spreadsheet and build a revenue model with cohort stacking. - [00:20:05](https://www.youtube.com/watch?v=xCrd3ajdlzw&t=1205s) **Briefing LLM for Data Cleaning** - The speaker outlines how to describe a messy data export—detailing its inconsistencies, specifying precise cleaning steps, quality checks, and output expectations—to give an LLM a clear, actionable briefing for automated data remediation. - [00:23:13](https://www.youtube.com/watch?v=xCrd3ajdlzw&t=1393s) **Unlocking AI‑Powered Excel Efficiency** - The speaker urges users to adopt Claude Max–driven AI prompts for Excel, emphasizing that even modest time savings can justify the cost and that AI has the potential to accelerate spreadsheet work by orders of magnitude compared to traditional methods. ## Full Transcript
If you are not using AI for Excel, you
are sleeping on the power of what it can
do. It is one of the biggest changes I
have seen in the last year for AI. This
video is all about AI and Excel. It's
about Claude. It's about C-Pilot. It's
about what we can do that we couldn't do
before. And I go farther than that. I'm
going to talk about specific prompts and
show you specific prompts and how I use
them to save hours of work. And I'm also
going to give you a sense of how we
should think about these new emerging
capabilities in AI and how they change
our own calculations of what's worth
doing for people versus what's worth
doing for AI and how much we should pay
for AI, invest time in AI when it
continues to gain capabilities like
this. So, lot to cover. Let's dive in
first to what launched and why I'm doing
this video now. Claude has launched
Excel capabilities for the last couple
weeks. It's extraordinary. It's really
good. It got better with the launch this
week of Sonnet 4.5. I was able to
oneshot complex Excel analysis out of a
screenshot for multiple currencies, like
four or five different currencies. This
week with Sonnet 4.5. It's gotten
really, really good. But people don't
know about it because it's in Claude's
max plan, which is expensive. We're
going to get to that in the ROI part and
how you think about that. So just put a
pen in that for now. If you're not on
the max plan, this is still for you
because one, Claude is bringing those
Excel files down. You can look for them
to come down market soon. Two, Copilot
launched this week also an Aentic Excel
builder, right? Like it can be in Excel,
it can be your assistant, it can build
Excel for you, can edit Excel for you.
I've played around with it. To me, it
reads as about a number two compared to
what Claude can do with a great prompt.
But it's the tool you got if you're in
co-pilot and it's fantastic and you
shouldn't sleep on it. And so I think
it's great. It's also another reason to
talk about this. The larger story is
clear. We had LLMs doing words for a
long time and now they do numbers. Now
they do numbers. And that means that you
need to think about ROI and value
differently. And it also means you
should assume that this video matters
for you. this capability. The prompts
I'm going to show matter for you
regardless of what plan you're in today
because the capabilities are coming to
you. They're coming to you in three
months. Everybody's going to have this
maybe in a month. Everybody's going to
have this. And frankly, if it's in
copilot, most people have it now
already. That is how quickly this is
changing. So, how do you think about the
value of Excel work? I feel like it's
very very different from words. When we
are prompting with words, primarily what
we are doing is we have a thought and we
are saving ourselves the hands-on keys
time to write it all out. And whether
you do that well or badly, that's the
idea. Now, you can prompt badly and get
malformed thoughts or thoughts that feel
like AI slop that aren't really your
thoughts, or you can prompt really well
and get stuff that is your thoughts just
written out really, really fast. It's an
accelerator, right? That's fundamentally
what words are. But it's different with
Excel and I think the leverage is in
some ways higher because what you get
with Excel is the leverage to compute
numbers and with Claude and with the new
co-pilot launch that leverage is
essentially production grade. It is not
as good as a CFO that has been doing
spreadsheets for 25 years. I don't want
to overstate it. It is not as good as
the person who has maintained the 20
sheet tab for 15 years in your office.
No, but it is an extremely good
professional assistant that can prepare
dozens of different financial statements
or models or attribution analyses or ROI
calculations. We'll get into all of
them. Like you you'll see the prompts
that I'm building. Like it can do all of
the standard business spreadsheet stuff
30 to 40 times faster than a human in a
better organized way. And I want to call
out Claude in particular here. Claude is
a good notetaker. Claude is so obsessive
about having a little tab that has all
of your notes there. And I love that so
much. And it's going to do that faster
than than anybody in the office,
including the CFO. And so really, when
you think about the ROI for these
investments, is it worth it going to
Claude Max? Now, I don't really think
about it as am I going to get the money
back per se. I think about it as am I
going to get the time back and do I need
it now now now or can I wait a month for
it to come down to the right plan. There
is no question I will get value back in
terms of what it can do for me if I know
how to prompt it. And that's exactly
what we're doing here is we're going to
talk about how you prompt it so you get
the value. There's no question at all.
the the prompts you are able to build
the revenue analysis the board ready
models these are going to save dozens of
hours for finance teams right they'll
save dozens of hours for PM teams who
are trying to build ROI models there
Excel
is extremely hard for humans to build
because it's all predicated on the idea
that you have to have control over every
individual cell and know what it says
and know how the formulas compute and
that is inherently a very high compute
task For us, it goes in our brains. This
is why I lose my hair. I had to do a 20
sheet Excel when I was a marketer back
donkeys years ago. And like the gray
hair is real. You have to think of these
as multiplied accelerators when it comes
to Excel. So if they just accelerate
linear production of words already LLMs
are amazing. But with Excel, they are
giving you not just quick thoughts, they
are giving you full models that you can
use to do real work with. To me that is
actually more time leverage. It saves
you another order of magnitude more
time. So if I am trying to write a
product requirements document and I can
get it done now in 20 minutes instead of
3 hours that's great. If I am trying to
build a set of board level analyses and
I can get that done in 60 minutes
instead of 8 days in a team of three
it's another order of magnitude of
improvement. It's a big deal. Now, now I
do want to emphasize that the entire
workflow shifts and moves the data
collection burden to you early in the
process. You still would have to collect
the data for Excel regardless to get all
of this work done. That doesn't change,
right? Same data, got to get it. You're
building an analysis. You need the same
input numbers. They got to be right. But
you have to get them up front now. And
so for people who are used to saying,
"Okay, I'm going to go to the next
sheet. Going to go get a cup of coffee.
Going to go pick this up off of Daryl's
desk." and then come back and look at
it. That's different now, right? You got
to get it all in advance. You got to
make sure you have it all. Now, you can
give relatively messy inputs. Like I
said, I gave a screenshot with numbers
in multiple currencies and I got frankly
surprisingly good outputs from sonnet.
It was like one mistake and I corrected
it quickly and that was it. I think we
are sleeping on the on the that we get
if we are willing to do just a little
bit more work up front. So do the little
bit of work up front, collect the data,
and without further ado, let me show you
four examples of prompts that I am
building and using for AI in Excel and
why I think they're so powerful. I
actually built a bunch more of these. I
think I have like 18 of them and I'm
putting them all together into a prompt
pack and and they'll be in the post, but
but I want you to at least get a sense
of the structure because my goal is for
you to understand how I put them
together. And there's not magic to it.
It's really about communicating intent.
And so, let's go look at our first
prompt. Okay, this is actually a
relatively short one. These are an
ascending order of complexity. I thought
I'd start you out easy. This is not
multiple hundreds of lines. This is just
a few dozen lines per step. Our goal is
to get a monthly P&L from raw data.
Let's say you have a CSV export from
your accounting system. It's a little
bit of a mess, but let's put it
together. My recommendation is that you
actually do these in pieces. And so
you'll notice that these Excel prompts
do come in pieces. They presume that you
will get a deliverable at the end. If
you notice at the end of this initial
step, it is return the clean data in a
new sheet called clean data. Just in
case, for example, you run out of
context window on one of the larger
prompts. This allows you to continue
your work and it doesn't become one of
those nightmares where like the thing
runs out of context and it does what
Claude at least does in a very
frustrating way and just says, "I I
can't do this. were out of context and
then you lose like half an hour. It's
designed to prevent that. So it's very
simple. You declare your columns and
then you just declare your intent.
Please create a clean data table and
then you start to define cleanliness,
right? Dates must be formatted properly.
Amounts must be formatted as currency.
Remove duplicate transactions. This is
an example of something where like if I
knew what was in the data set, I would
probably be much more declarative about
what counts as a duplicate to avoid
false positives. Uh, and so you can
expand that, make it yours. Number five,
add a column for month. That's something
that would be relevant for most people
to be able to filter. And then flag rows
with missing data. You can identify
other steps in your data hygiene
process. Most organizations will have a
data hygiene process that they can go
through that actually lays out all the
steps. Like it's an SOP. It's a it's a
standard operating procedure. You can
literally encode that as a prompt,
right? doesn't have to be a manual thing
that I do every time I open up the sheet
because this is what I would have to do,
right? I used to have to do this all
manually. Then second step, new prompt.
You use the sheet and now you start to
do work against it. Now you basically
take it and start to categorize it now
that the data is clean. And so you're
going to define categories. These would
be up to you, right? I made them up, but
you can define what you want them to be.
Right? This this seems standard but you
can sort of adjust them. Uh and then use
the description. This is something only
LLMs can do, right? This just was not
possible before with rules-based uh
categorization. I know I've written
those sort of if thens and they're
nightmares. This is much much easier.
The examples are good. If you feel like
you have some areas of concern where
it's like I don't know if this is
correct or incorrect or a duplicate or
not, you can include counter examples.
You can include tiebreakers or rules
around ambiguity. Um, and I love this at
the end. Mark that it needs review and
add a note explaining why it's
ambiguous. Yeah, that makes a lot of
sense because you don't want it to try
and declare something ambiguous. You
want to give it back to a human. All
right. Then we get to the monthly P&L. I
don't want to spend too long on this. We
have three others to go into. You create
a new sheet. Again, you're declaring
your rows. You're telling it what
formula to use. One of the breakthroughs
that Claude launched into the world and
co-pilot with Excel does this too is we
have fluency with formulas finally and
you can format it with bold headers,
subtotal rows. Can you tell I've been
having fun since Claude launched this
Excel thing? That was the beginning for
me, right? I was like, "Finally, it can
do Excel. How much can it do?" Well,
you're starting to see how much it can
do. And and then we got it's like
Christmas for nerds. We got to have the
co-pilot launch with Excel, too. And so
now we have multiple companies bearing
down on this Excel problem space. It's
going to be really exciting for folks
that do any kind of work with
spreadsheets in the next couple months.
We get to budget variance. And so you
can actually start to compute budget
variance here. And you'll notice at each
step we're just saying this is a new
sheet. This is a new sheet. It will come
back with a new sheet. And even if it
runs out of context window, you're okay.
And now you're doing one operation on
it, right? Just add the columns. By the
way, Copilot is really really good at
this like just like do this one thing in
the sheet. It lives in that embedded
sheet whereas Claude treats it like an
object and manipulates it from the
outside. And actually Claude is still
very very good. Like I said, I think
it's actually better overall in my
experience than Copilot with Excel in
the sense that it has more ability to
follow complex longunning prompts and
get high quality results. But if you
want the inline edits, like the ability
of like the Excel magical AI, that's
just something Microsoft has a
distribution advantage on and they're
just going to do it. And so this is an
example of something where I sort of
privately think Copilot is going to do
well here. Uh and then you can validate
it, right? You can add a validation
section at the bottom and you can make
it prove itself and display it as a
checklist. And then this is what you get
out of it. And so I do more, right? I
have a sales pipeline dashboard. There's
other ones, but this should give you an
idea if you were an individual
contributor of what you can do with
Excel. And you might think, well, Nate,
there's a lot, but like I'm saying,
like, how often do you touch monthly
P&L? You have to touch it every single
month. And let's say it takes you hours
and hours a month, and now it takes you
5 to 15 minutes. That's going to be ROI
that pays itself back really, really
fast. Let's get to the next. Okay, we're
going to go through this a little bit
quicker now that you know the idea. I
don't want you to get bored. This one is
for a board. Let's say you're a founder.
You're trying to put this together. You
want your chief of staff to put this
together, what have you. You need a
comprehensive financial package. What
does that look like? You can go through
and have it just create a revenue
analysis sheet with comprehensive
revenue tracking. And you're defining
that all here. You're declaring it. This
is what you want. By the way, these are
very standard. And that's good. You
actually want standard if you're talking
to the board. So, this is this is a
great thing. And it's just going to come
back with this. Like, it's going to come
back with the overall perspective.
you're going to need to supply all the
inputs for this. So, you should add that
in when you write this prompt, but then
it's going to come back with the growth
analysis, the calculated metrics, and
all the rest of it. And now you have a
separate step for cash runway. So, you
can go in and you can have inputs at the
top for cash balance, for month, for
burn rate. You get your projections, you
get your alerts, your milestones, and
you even get a visualization. And if
you're wondering if it makes
visualizations, yes, Claude in
particular is very good at
visualizations in a way that I am still
surprised by. When I ask it to make a
chart, it makes a good chart. And then
you can actually give it this little
instruction format for easy copy paste
into board slide decks. Uh which is nice
and touching. I you you can do all kinds
of things people don't realize. I have
told I have told the AI where to bold
and it will just bold it in the right
place, right? Like there's all kinds of
stuff you can do people don't realize
that make it seem more professional.
Step three, you want to get to a key
metrics dashboard. At this point,
honestly, you're just kind of dunking on
the competition because like you don't
have to have this as a separate
dashboard. It can be but but I wanted to
show you what you could do, right? So,
you can go through and you can calculate
these metrics in a new sheet. Um, and
you define how you talk about
benchmarking here. You can define your
metrics. Um, again, these are very
standard metrics, so there's nothing too
surprising, which is good because you
actually want AI working off of standard
metrics and also because you want your
board working off standard metrics.
Department spend breakdown very similar.
You want to go piece by piece. Are you
getting the idea? This may be hundreds
of lines in total, but we're breaking it
out so that it doesn't break the context
window. And it it's going to save you
days of work. It is worth figuring out
how to use it so that you can save the
days of work. And there's a ton here,
right? And now you're now you're
formatting it, right? Here's a board
summary sheet. You talk about sort of
what's in the overall report. you give
it very specific formatting specs and
export steps. Um,
and honestly like this is this is very
cloud specific because Claude can work
across PowerPoint and PDF and Excel
within one prompt whereas Microsoft's
Excel agent won't. So I wrote this for
the more complicated use case, but you
could obviously drop it out if you would
like. Is there other stuff? Yes, we can.
The 13week cash flow model is a totally
different thing. You you get the idea,
right? It's a longer prompt. It's broken
out in ways that the context window
works for. It uses standard terminology
which is good for the LLM and the board.
And it presumes that you can gather the
inputs that you need. Let's do a third
one. We're going to go up yet another
level here. Let's say you want to build
a three-year business plan. Now, you
might think, well, only founders need to
do that. But honestly, everybody should
build a business plan if they're doing
anything at all related to a side gig.
and everyone should be able to read one
if you are in a business because boy
does it shape your world whether you
like it or not. Um, and so at least you
should be able to understand this. And
by the way, one of the things that's
really interesting about AI as a sidebar
is that the availability of material
like this makes AI a phenomenal teaching
tool. You can go into AI and say, you
can go into cloud, chat, GPT, any AI and
say please tell me why the three-year
business plan has the elements it does.
And you can get a whole lesson. You just
get a whole lesson on it. Anyway, we
create an assumptions sheet which serves
as a source of truth. And so we start to
do that first. We go through each of
these. You'll notice we are getting very
clear with our seasonable seasonal
patterns. You will need to go through
and sort of hand hand brush these over
so that you have the right adjustments
for your business. Right? Similarly with
hires, right? You want to sort of be
able to hand hand adjust this. We get to
expenses etc. Now, the good news is,
let's say you were like, "Oh, Nate, I
don't want to go through and touch every
single line." Well, you don't have to.
You can go in and you can copy this
prompt and then you can get all of the
the the spreadsheet, the dirty CSV, the
picture of the cocktail napkin where you
have the data and you can say, "Put A
and B together in a smart way, right?
Like, here's my prompt. Do not follow
the prompt. Instead, fill in the prompt
with this information." and the LLM can
do it. It kind of doesn't matter. Any
cutting edge AI will be able to do that.
And you go through and you say, "This is
what I want, right? These are all of my
assumptions." You go down to step two
and now you're building a revenue model.
It's a separate sheet. And you're going
to go through, you're going to create
the revenue model and stack the cohorts
all the way through. Make sure that it
understands how you want to build your
build your business. And again, you'll
need to adjust this for your business.
We're assuming implicitly that there's
almost a B2B format here because that's
just become the standard for a lot of
these the the way we talk about business
in the software world. If you're not an
MR business, don't use MR, right? Use
use the the metrics that make sense for
you. Then you go through and you can
create the visualization, right? The
point is to show you what you are
capable of doing in these models. And
then step three, you get to expense
models by department. This is another
level deeper. You can see already you're
another level deeper versus the exact
the exact ready board props. I don't
want to bore you. This is a long prompt.
The good news is I wrote it already for
you. All you have to do is modify it.
Super super easy. And so you go through,
you can do that. You can do the
headcount model. If you're a tiny
startup, you don't need that. This that
is part of why I broke this up. It's all
optional. You can do a P&L rollup.
Again, it's more complex in the board
one, but it's good for a business plan.
And you can do finally a cash flow
statement. So there's a lot there, but
that's good, right? Because at the end
of the day, you actually get your entire
business plan done. This is the kind of
thing a bank needs or a venture capital
firm needs to think about investing
right. It's much more in-depth. But this
kind of thing saves you hundreds of
hours if you do it right. Let's look at
one more. And I saved the best for last,
guys. I saved the edits for last. Yes, I
want to talk about the possibility of
editing with Excel. That has been really
challenging for models in the past. And
I am so excited to share what I've
worked on here. Okay, it is really,
really important when you're editing to
be clear about what you want. And so
this is going to presume certain kinds
of mess. My goal here is to show you how
to clean up as a set of principles so
you can clean up your own mess with
prompts that are forked from this.
Right? So for example, I have a messy
data export from and then you'll have to
specify where it's from. uh this is the
current state. You want to describe this
as specifically as you can. So
inconsistent formatting, duplicate
entries, text and number fields, unclear
column headers, and this is what I want.
And then specifically, this is how you
clean the data. You want to be as
specific as you can here. And it should
map back to current state. This is what
categorization looks like if that
matters to you when you're cleaning the
data. So again, you're going to specify
that as cleanly as you can. Um this is
how you start to work against it. And
then this is your quality checks. The
output is a clean data set with a
summary dashboard showing total items by
category, monthly trends and items
required review. Ensure all formulas are
error-free and totals reconciles to
source data. You can actually do more
than this in validation. If you get
paranoid, you can make it produce a
separate document showing how it did all
the work and so it can go through and
sort of explain to you how it did it as
a way of auditing.
What would you change with your mess?
That is my question for you. Would you
change the data has issues like so it's
more specific? Would you maybe for
example say 80% of our issues are
inconsistent formatting and these are
the six ways that we see it. Um those
are all ways to give the the LLM more
clarity. Basically think of this as the
LLM's briefing before going into the
spreadsheet. And you want it to be as
comprehensive as you can so the LLM gets
no surprises and doesn't hit a point of
ambiguity. And so if you think it's
going to hit a point where something
might have inconsistent formatting or a
mixed date format and there might be two
correct answers based on your prompt,
your prompt is not clear enough. And
that is one of the reasons why edits
fail. And I've come through and I've
done some other edits like you can get
the fix the broken formulas and all of
that. These are complex prompts and
these ones because they're edits are
going to require another level of
involvement from you because everyone's
spreadsheet is broken in its own special
way. And so you will have to go in and
talk about how your spreadsheet is
especially broken to get this stuff
fixed. But this is really, as far as I
know, the first real effort anyone has
made to make AI do edits and not just
create from scratch. It is it is harder
because they're trained to create from
scratch. That's how reinforcement
learning works. it is still worth it to
figure out the edit piece because if you
can get a cleaner version of your
spreadsheet, if you can fix your
spreadsheets, again, dozens of hours
saved. It's it's a huge time savings.
Okay, you have been patient enough to
stare at four different kinds of
prompts. You have looked through IC
level prompts. You've looked through
executive ready board meeting prompts.
You've looked through business plan
prompts. You've looked through how to
edit with Excel, which is net new. I
hope what you walk away from is
realizing that you have the ability in
your pocket now to save hundreds of
hours on complex business computation.
To me, what has launched in the last 2
weeks has the same leverage and power
for numbers as the launch of the pocket
calculator. That's how big a deal it is.
and we're sleeping on it because most
people either don't have the claude max
plan, haven't really sat down and
thought about prompting the co-pilot AI
for Excel or they just don't have the
time to come up with these complicated
prompts and they've always done it this
way and so they're just always going to
do it. Let me challenge you. It is worth
it to go a little bit differently to try
a new prompt, to adjust one of my
prompts. If it saves you that much time,
if it saves you a dozen hours this
month, the Claude Max plan is probably
worth the money because you're going to
spend that amount of time, right? Like
your your time has some value to it. And
so I I would love it if you guys would
share ways you are using Excel and if
you guys would talk specifically about
what that speed up feels like when
you're using it well versus the speed up
you get from using AI for words because
I continue to come back to this idea
that AI for words was huge. It was like
a 10 or 100x speed up. But the potential
with Excel is a thousandx because of how
complex these numeric structures are.
They're not lists of numbers. They're
complicated multi-heet hundreds of
formula, multi-ellular structure messes.
And now we can finally deal with them.
So that's why I'm excited for AI for
Excel. This has been I I really think
this has been the biggest week for for
numbers for leveraging numbers and going
farther in business since the personal
calculator. Like it's huge. Maybe since
the original Excel. The original Excel
was pretty cool. Maybe we'll give them
credit there. But it's a big deal. So
have fun. Go dig into Excel. As you can
tell, I'm an Excel nerd. And so I hope
you enjoyed this one. Share it with
someone who loves Excel.