Hello everyone, and welcome to
another episode of The Operations
Room, a podcast for CEOs.
I am Brandon Metzinger and I am
joined by my lovely co-host Bethany
Air is having some nice porridge.
Breakfast is what I want.
I'm looking at.
If only it were porridge.
Oh, it's not porridge.
Looks like porridge.
No, this is the chia seed concoction
that, thanks to Zoe, I eat every
day. From chia seeds,
other seeds, kefir,
milk, lots of nuts.
And therefore every
day.
Right. So every trendy ingredient
that I can imagine is on the list.
Pretty much.
So didn't you tell me before that
the taste of your dish
there, the cheesy delight, is not
great or it's rather plain.
Yeah. It's plain.
I have some strawberries in there
that helps the nuts help
it, but it's a bit of a slog.
And also because it's so
chewy, it requires
so much chewing
that it takes me absolutely forever
to eat it.
I don't know how much reading you've
done about ultra processed food.
So one of the things
with ultra processed food is it's
very soft.
And that has made our
jaws stop growing properly.
I've not heard this before.
Is that true?
Yeah. So children
and we were raised on enough ultra
processed food to make the
difference.
All of our jaws are more
recessed, and the reason why we need
our wisdom teeth taken out is.
Apparently your jaw grows
through hard work as
it's forming as a child.
And so it actually comes further
out. And then you have space
for your wisdom teeth.
But with ultra processed food, it's
really soft. So our jaws don't work
anymore. And that's why everybody
needs braces.
Oh my goodness. I did not know this.
Well, I would say this I ate a
tremendous amount of cashews.
And cashews are quite hard, so I
suspect my jaw line is
kind of being exercised.
From the outside, it looks like your
jawline is fine, but I don't know.
Did you take your wisdom teeth out?
Could you have had more of a jaw?
Had you
knocked everyday?
I don't even know.
I literally have no memory or
recollection of having them taken
out, so they must still be on.
Right. And came in in a normal
way. Like they didn't cause any
problems. You didn't need anything.
My superior jawline was
sufficient to house them.
All those cashew nuts and the clean
living of Canada.
So besides
the chia seed.
That's right. The ultra processed
food.
What is happening in Bethany's
world?
Just insanely busy.
So I've been working from home
this week. I managed to leave the
house on Wednesday and
now today it's Friday.
We're doing this at 8 a.m..
I have back to back meetings
like literally back to back in my
calendar. Not a sliver of
space until half six.
So luckily my husband is working
from home today and so he's going to
bring me some lunch around noon
so that I could continue to eat,
although at the rate it takes me to
eat the chia seeds, I might not
actually have finished them by the
time lunch arrives.
Okay, so that's fabulous.
So you have the in-house servant, in
this case being your husband to
deliver your lunch for.
Why not call him that?
That's that's I mean, this is the
give and take in a relationship, so
I don't know either. A quick note, I
just had this small thought this
morning. So I'm working with a
couple individuals right now that
are they do operations.
But really the granular operations
if you want to call it that.
One of the individuals was asking
me for a recommendation for
employment law.
So I just did a quick screenshot
of recommendations coming
out of the Operations Nation slack
channel to her that operations
Nation slack channel is good for
this kind of thing, which is vendor
sourcing recommendations around
products and people and that sort of
thing is fabulous for that.
People are very
proactive. I would say, in terms of
giving thoughts on who to speak to,
who's good to, you know, to work
with these sorts of things.
The other thought was just the
obvious one, which is she's an
operator. She's at that level.
She'd be perfect to be part of the
operations nation, or at least on
the slack channel, is just a good,
useful tool.
When these questions pop up like
this that are quite straightforward,
where people can respond back
and give you the kind of collective
set of good answers.
And it's free.
It's definitely a good community for
like having problems with my pension
provider or
the health insurance quote
has gone up by 40%.
What do I do?
Or is that the same for everyone
else? Like those are the types of
questions you see.
I went to a comedy show on Sunday
night and then a comedy show on
Wednesday night, and I was telling
a friend and he was just like, is
this a new thing?
Like, it's going to comedy shows
you're saying?
And said, in that kind of like
snide, dismissive way,
like, what is up with you?
It's not our new thing.
And I actually booked them ages
ago, maybe July, August time.
And it just happened to arrive now.
And there were two very different
comedy shows. So one of them was in
Hackney.
It was very trendy.
The guy is a Sri Lankan
comic, as you do
a Sri Lankan comic that kind of
looks like Jesus, like he is very
curly hair down to his waist.
Very good looking guy.
And he studied
medicine and then decided not to
become a medic, and
then became a developer and
a comic and is trying to be a comic
more than a developer.
So anyhow, I
have never felt like more out
of place.
Everybody was trendy.
Like, I don't think there were any
other women in the room.
They were just non-binary.
I guess we call them women anymore.
Like, I would have chosen to be
non-binary had I had
the option, because you kind of look
at it, you're like, oh, I could be a
woman, and that looks like a really
bad deal, or I can opt
out
and I think I'm going to opt out.
Yeah.
Fair enough. Yeah.
And then every man had a mustache.
Is that. Is that a thing right now?
It really is a thing.
And here we are like middle
class clap mites
nots with mustaches
and combat boots.
And I was just like.
And not non-binary.
Yeah.
And I just never felt so uncool in
my life.
But it was quite a good show other
than just feeling like such
the square.
And then on Wednesday
night, it was a
Irish comedian who's a couple years
older than me. Woman.
And other than the fact that at
least 90% of the audience were
Irish, everybody was a middle
aged woman and maybe
one and four brought their husbands
along. So I felt
totally in
my element. We all belonged.
We were all square, we
were all 50 ish,
and it was quite good, but totally
different sets.
One was around
like his was around not belonging
and racism
and privilege.
And hers is about
menopause and sex.
And husbands and children.
Congratulations though to you.
Because actually booking kind of
not social but like just outings
of fun and enjoyment.
You know, I feel like my calendar
right now is pretty sparse in that
respect.
So I'm always actively looking
for, I don't know, just interesting
things that would be, I don't know,
fun, enjoyable to do and were doable
just given our schedule with the
kids and all that jazz.
But nothing has really popped up
quite recently. That seems useful
enough or good enough to go to.
All right. So we have got
a great topic for today,
which is a returning topic, as
it were, building an AI for
Organization Part two.
We have an amazing returning guest
for this, which is Charlie Cowan.
We had so much fun with Charlie that
we had a second conversation.
And of course, he is an AI
strategist and AI change
agent within organizations
today. So before we get into our
part two with Charlie, Just wanted
to talk about a couple bits and
pieces here.
One of the elements that he spoke
about was leadership.
Using AI themselves
on a daily basis to really
understand what they're talking
about. So if they're going to encourage
the rest of the organization to
experiment with AI, the starting
point for these things, outside of
speaking about it, is for the
leadership to really understand what
they're actually talking about, or
what value they're actually getting
themselves, to be able to express it
in a more articulate way,
presumably.
What do you make of that? Is that a
hard requirement, do you think?
I don't know if it's a hard
requirement, but like once you start
using it, you can't go back.
So I think it's like the it's more
like in order to understand
what you're talking about, you
should. And also to understand the
what is the constraints, what it's
good at, what it's not.
But it's also just like a really
convenient tool.
So whether or not you're using it
for other people, you should start
to play around with it and use it
for yourself.
It's just so nice.
So we had a new
commission policy.
Somebody had written it.
It was just in legalese,
through and through.
In the old world, I would have had
to rewrite that or have somebody
rewrite it or, you know, give it to
our copywriter to just put it in our
tone of voice or, you know, it'd be
a total waste of time.
And instead, I stuck it in.
Claude said, keep it exactly
the same sections
don't change the content, just
make it sound like our tone of tone,
of voice.
And under a minute later, it was
done.
It was really good.
The only annoying thing is Claude
loses formatting, so I
had to go and reformat it.
But like, it's just so nice
to have those options or
handed a legalese documents
to have to understand.
Couldn't understand one paragraph.
No matter how many times I looked at
it, threw it
into ChatGPT to
just explain to me what the
paragraph is talking about and what
I need to worry about.
And it came out and told me
it's really nice.
It just makes life easier.
I mean, do you use it.
For me creating things I need to
distribute? I always end up passing
it through ChatGPT.
Now to kind of do a once over in
terms of making it better.
And all things being equal, I am not
a fabulous writer.
I can write and I can get my message
across, but every time I put it
through ChatGPT and get my output,
it is dramatically better for
the most part. So I'm like, oh,
great. And I might tweak it here and
there, but definitely use it for
that purpose. And then the reverse,
which is where you just pointed out
any kind of incoming document that
is highly annoying for me to
understand and read, passing it
through to you, but again, to either
simplify it or kind of expressing
it in a different way, where I can
actually pull out the key bits that
I need to quickly.
It's very useful for that.
I'm a little bit sometimes
skeptical, but for things that are
rather important where the detail
matters, I'm a little more worried
sometimes that it's not pulling out
all the bits that I actually need,
to be honest. There's some level of
my going back to the source
document just to check things and
verify that at all.
I'm getting what I need, basically.
But my suspicion is, and
this is separate from ChatGPT and
the generic tools right now.
But there's probably again, probably
AI agents out there that
are verticals that probably do a
much better job of this to ensure
that you're getting exactly what you
need with a higher level of
confidence and accuracy than using
the generic tools.
But that aside, your
use cases or my use cases, and I'm
sure for any C-suite leader or
that kind of incoming document
of complexity, output of actual
things that you need to communicate
seems like a no brainer.
And then the other one I use is
if I have writer's block
or I don't quite know how to get
started, and that blank sheet of
paper a moment, rather than
just the willpower of getting past
the blank sheet of paper that I have
used for the last, whatever,
30, 40 years of my life,
I'll go to ChatGPT or Claude
and just say, this is what I have
to do.
How should I get started?
You know, and just kind of what
would be the typical arguments in
this case? Or what would the AI
structure be?
And even if I don't end up using
that structure. I no longer have a
blank sheet of paper, and that just
really helps get me started.
And I don't need that same level of
willpower I used to have.
Yeah, I think you're exactly right.
So I was having to come up with
kind of a interview process for
sales reps, and also the kinds
of questions that I want to ask for
different elements that I was
looking for in terms of being able
to make judgments on the candidates
and ChatGPT for that kind of generic
interview process and questions
was absolutely fabulous.
And to your point, instead of me
having to I mean, I've interviewed
sales reps so many times before with
so many different question types and
processes.
It's all vaguely in the back of my
head, but it requires me
if I need to do net new, to think
about it again and kind of think
through. Okay, what did I do before?
Do I have some previous documents I
can rip off?
All that takes thinking time
basically, whereas now
I can just ignore all that wholesale
and very rapidly get
the process, get the steps, get the
questions and get the
criteria boxes all set up
basically within whatever, half
an hour and then ship it out to Emma
as part of the process and boom,
rocking and rolling.
So I think for that kind of
activity, for stuff that you kind of
know, but it's annoying to have
to re remember everything.
That's a great use case.
I love that like the annoying re
remembering.
That's why we're like yeah we're so
over it.
So Charlie talked several
times about this, which is every
time he has to do something,
he actually doesn't go to the
generic box, as it were.
He always creates a project for
himself and gives context
or the prompts around the particular
subject matter that he's wanting a
response to in this case.
And so his go to effectively is to
create projects, is what I'm saying.
So my curiosity with you,
do you use projects and
is it useful?
I'm very impatient and a little bit
lazy.
And so I'm using gen
AI to make my life easier
really quickly.
And I find projects kind of annoying
because it slows me down.
And I think if I were trying to do
the next level of work, it would be
worth the input.
But for the most part, I find
that without using projects, the
output is good enough that
I don't find it worthwhile
putting in that next layer.
I'm not like Charlie, who
has created an entire project
without, you know, to tie a product
and code without using
anybody but him.
I just want to know
what would be some good agenda items
for a sales kickoff.
As Charlie described, some of the
projects that he does, and some of
the prompts that he sets up are
super complex.
Like, like, you know, he described
like doing a five page prompt.
I think it was a 20 page prompt.
Yeah. Yeah, that sounds like a lot
of thinking.
Seems like so the subset
of that is he has created
what he called a CEO pod
with pre-built prompts for
interesting topics, and I thought
that seemed very interesting to me
as a senior executive.
So essentially, what he's done is
taking that product trumpet over the
trumpet before It's usually used for
like sales enablement for a buyer
to go in there with all the
documentation around the product,
this and the other is used it
to basically be a place for
anybody that goes to his LinkedIn
feed to go into that little
box world, and in that box world
that is called the CEO pod.
He has three prompts that are
sitting there as defaults.
One prompt is for
all hands prep and
the definition or the.
I guess the objective of that prompt
is to develop your messaging
and talk track to convey your vision
and inspire your employees.
So it's kind of a drop in prompt for
a project, presumably for all
hands that you could use going
forward. So my suspicion
is for people like us where
we don't do spending hours building
prompts of five pages, that
there should be good, healthy,
generic prompts for things like all
hands or this then the other, that
we can simply take it and drop in
and use it, where we actually get
a better answer than what we would
have got generically to the box, but
I don't have to think about
creating that problem myself in this
case.
Yeah. And then the question is
who's going to provide it?
Like is it going to be the rise of
a bunch of apps that are
basically rap arounds of the
labs?
Is it going to be the
labs themselves providing it,
or is it going to be consultants, or
is it going to be like your really
talented 22
year old who comes into the business
is like, you know that going to be
their future, but I don't think it's
gonna be the future for very long,
because ChatGPT
is just going to create a better
user interface and eat up
all of these other businesses.
Another one that I hear is not doing
well is 11 X.
Like the first automated
one of these like SDR offerings,
they got to 10 million super fast.
For what I hear, they're about to
that 50% churn
and wasn't a good product.
Not worth it after people gave it a
go. And then also just loads
and loads of people are now building
their own automated stores.
And so that's another example of
there's going to be a lot of crashing
and burning while figuring out where
the real value is, and that
apps layer is definitely at
risk and probably
like how specialized
can you go?
So when you talk about like ones
for lawyers, one's for
doctors, like, you know, the very
specific horizontals are probably
safe.
But let's say.
I somehow feel it's like the hype
curve where the companies come out
of nowhere. They create first
versions of the product around stars
or whatever people are.
Budgets are excited.
They spend it, they use it.
It's very disappointing for all
sorts of reasons.
Then we go through that phase where
all these companies and products
go to the trough of like
disillusionment and like not getting
the revenues, high churn, this, that
and the other.
But slowly but surely they figure
it out and they figure out how to
build real value and they come back
up the curve eventually.
So it feels like on balance,
I would imagine this will happen in
this sector, but there is
that kind of risk that sits there in
terms of open AI ultimately eating
into these stocks in a way where
somehow it becomes so easy
for a single individual organization
to do it all themselves.
They don't actually need to go to
these companies to buy these
products, to your point.
And it's all happening so fast.
So you have these rises and falls
within months, not
years.
Yeah, exactly.
So what I wanted to ask you was
how to communicate the importance
of experimenting
with ChatGPT and Claude
and know PLM and Gemini
across the organization to get
people that dropped people's minds
around the fact that this is very
important for businesses going
forward. And we need to start
experimenting. We need to start
doing things. And obviously, from an
operator standpoint, there's all
sorts of things you can do to make
that happen.
But purely in terms of just straight
up communication to the company,
what are the kind of like key
messages that are
the most powerful to just get into
people's minds that this matters.
And we need to do something about
it.
So I'm just stuck on your mention
of Gemini, and I'm using Gemini
right now, and I can't really tell
if I'm using the paid version of the
free version, but whatever I'm using
just sucks.
So first of all, I just want to add
that in like it is
massively underwhelming.
It doesn't help me in any way.
It doesn't do any of the things I
would like it to do, and its answers
are stupid.
Slam on Gemini.
Basically, everywhere I
go on the Google suite,
there's a little like, how can I
help you box?
And then I ask it to help me and it
just does not do anything helpful.
And so perfect example
is I took
the commission policy,
ran it through Claude, made it
friendly and pleasant, stuck
it in a Google doc.
Then I asked Google to format
it like the above
policy, and it just rewrote
the policy for me in
a stupid way.
And it didn't reformat anything.
And it only does stuff in the chat
box.
But like, I don't care about the
chat box. I would think that if
you are Google and it's integrated,
it should do things in my document
and not just produce me.
Like all it is, is an integrated
chat box.
That's not the power of Google
having it.
They need to get to that next level.
When you think about canvas within
chat GPT, that is genius.
That works so well in that respect.
And you can imagine from a Google
doc point of view, they should do
exactly the same thing, and it
should be way better given as Google
Docs as opposed to some flimsy
canvas thing that ChatGPT just
created.
So anyhow, that wasn't your
question.
So your question was what are
the reasons why?
What's the message to the company?
You know, we need have this idea
that for employees that
this is the future, this is how we
win. Part of that is to take
A.I., truly embrace it,
Activate ourselves to use it to help
us with what we're doing to to get
to the promised land effectively,
and that this is a winning mindset
and don't see it as cheating.
We should be using it and
it's very sensible.
So we have for
engineering, we've thought through
the workflows and the tools to
be used and have some
guidance is quite specific.
And then for the rest of the
business, what we're doing is
in every single weekly
stand up, somebody does a show
and tell on what they've done
with Jenny that week
and what they've learned and what
worked and what didn't work.
And so it can be really high
level stuff for what marketing's
doing. Or this week's
was somebody in our R&D
team going into
huge amounts of detail with,
I don't know, I think it was
Claude's coding
program and
it's now becoming a genetic.
And so like how it was solving the
problem and working on
multiple versions.
And when it got itself into a death
loop and how they got out of that
death loop. So it was like super
detailed and technical,
but it wasn't a set training
program.
But we are giving people
guidance and
thinking through more than
just a policy on how to use
it and what
to get out of it.
And then the other thing is we do
have budgets to experiment.
So people are looking at windsurf
and cursor and the ChatGPT
and the Claude and
Copilot,
GitHub Copilot and
Amazon Q so we're looking
at like all of the different coding
tools and not
embedding them, but just
experimenting and seeing
which ones are good and which ones
are shit. And just as another FYI,
nobody seems to like copilot very
much. It sounds like copilot
might be a bit like Gemini,
where it's just not there.
So Charlie has services that he
provides.
The primary one is his AI
Inspiration workshop, where he goes
into an organization and
gets them really not just excited by
the possibilities around Cod and
ChatGPT, but they kind
of work hands on.
What kind of use cases might be
interesting for that particular
group? And I think he referenced
working in a organization for this
workshop with the finance team
and with that finance team.
They outline all sorts of possible
ways to use it within finance.
That's part of that workshop where
they got those finance individuals
on their pathway to take
those projects and start building
them out, basically with projects
or custom chat gifts or what have
you, I suppose.
So I was kind of wondering, what
do you make of that activation of
people getting things to happen,
workshops like this?
Yeah, I think it's a really good
idea. And also like
finance might be a bit risk averse
and not wanting to change, but they
have some of the most boring,
tedious, repetitive jobs out there.
If I were the person who had to,
like, handle all
of the expenses
and accounts, I would be crying
out and experimenting to see how
I can make my job less boring and
let the machines do all of the shit
work. And I think that that's kind
of the inspiration is
what are the things
that are mind numbingly boring
that you have to do all the time,
and then it's worth taking the
time to create the prompts and to
create the agent that just does
the shit work for you.
And that's kind of like my
inspiration, you know, it's like all
of those back office roles
that are horrible.
They're the first place to look
because you just have happier people
who aren't just doing
awful stuff, and they
don't have to do awful stuff the
whole time. But like months end,
nobody looks forward to month end in
finance.
Yeah, it's a lot of pressure.
A lot of pressure and a lot of
boring shit.
So I will report on this at
some point in the future, but I'm
very keen in an organization I'm
currently working with to take
all the policies and to
stick them into notebook alarm
specifically. So this company uses
the Google Suite.
So notebook alum, you can share
your notebooks across your
organization seamlessly.
And notebook alum seems very well
suited for this task which is
taking documents inserting them,
not using the extended world of
alums, whereby gets confused between
your documentation and the greater
world of documentation around those
policies, and
also with that podcast
interface and different ways to
access the information.
And it seems so much more obvious.
I wouldn't say fun, but just like
different ways to like allow
the employee to get information
in a fast, efficient, timely basis.
So I think that as an actual kind of
low hanging fruit as a CEO,
that seems like just a fun
thing to start with.
Yeah, I agree.
Let me know how it goes.
So let's park it here and let's get
on to our conversation.
Part two with Mr. Charlie Callum.
The more that I learn about AI,
the more I realize you don't need
to know anything about AI to
embed AI and benefit
from AI, and you
need to know about neural networks
to benefit from AI.
In the same way, you need to know
about nuclear fission to benefit
from electricity.
You don't. You just need to plug in
to the wall and consume the
electricity.
How it gets to your plug
socket is really I have no interest
to you, and we
very much seen this with AI
over the last, you know, sort of 10
or 20 years where it's been, oh,
you need to be a data scientist.
You need to have a machine learning
degree to be able to understand
what's going on.
But November 22nd,
with the arrival of ChatGPT,
that is the plug socket.
The plug socket is the chat input
window.
That is all you need to know what
happens behind it.
Neural networks.
Reinforcement learning.
You don't need to know that to
benefit from it.
We are all
CEOs of organizations
that don't want to be left behind.
We understand the importance of AI.
How do we get started?
There's a few things that I would
think about as a sort
of setting the scenes as an
executive, as a CEO, as part of that
leadership team.
And that is firstly, just
understanding what is our
approach here.
You can be an AI
pessimist, which is where
you're like, oh, you know, I'm not
really sure about this thing.
And if we are going to use it, I'm
going to be thinking about how do we
strip out costs from
our business.
How do we become more
efficient and do things with less
people?
I think of this if you're a company
of a thousand people, well,
we can get to the same destination
now with only 500.
So that's the pessimistic view.
The alternative is to be an
AI optimist and go right, we're
going to lean into this and
we're a company of what do I say, a
thousand people and we're now over
500 people. We're not going to act
like a company of 5000 people.
We're going to be able to go further
with the same amount of resource.
And that kind of, are we leaning
into this thing or are we leaning
out of it is a real
precursor to everything that you're
going to do afterwards.
So having defined right, we're going
to lean into this and we're going to
figure out how do we act like a much
bigger company by using
these tools.
Next thing you probably want to do
is very quickly codify
that into some form of
AI policy.
Now I'm very nervous about
mentioning AI policies
because it's like, oh my goodness.
Like, this is just like, you know,
who's going to read it?
What's the point.
Where CEOs, we love a good policy.
You don't need to say that policies
are a problem here.
One of the common things that we see
is that if you ask companies,
you know, what are you doing with
AI?
You know, what benefits are you
seeing? You often see quite
muted responses.
We're not really seeing it.
We've got some pieces.
There's nothing really that's out
there in production.
If you go and speak to the people
one by one, are you using
ChatGPT every day?
Every day? I'm using it all the
time. You know, it's where I go to
ask any task that I've got.
So where is this discrepancy
coming from?
People are saying they're using it
all the time, and yet companies
are saying we're not really using it
after this because people are not
telling their manager, their
leaders, their colleagues when
they're using it. It's kind of under
the radar a little bit.
You know, oh, I'm just going to ask
ChatGPT or Claude.
It might be seen as cheating.
And often this is because certainly
when I'm speaking to teams, I'm
not sure what the rule is.
I'm not sure whether I'm allowed
to use it, so I'm definitely doing
it because I know that it gets me
where I want to go faster, but
I'm not being very public about it.
So one of the things that you can do
with creating a short,
pragmatic, positive
AI policy is
we are leading into AI.
We encourage your use.
We encourage you to experiment with
new tools, but be
sensible. Here are some guardrails
that you might want to follow so
that you know we're not sharing
confidential data or so on,
but having that policy where we're
setting what's right and what's
wrong, but reinforcing to everyone
we are leaning into this and we want
you to lean into it is
it's a really good approach.
And I can't remember if I asked this
question before, but it's something
I really want to know about.
And it's probably like the next
layer of depth rather than like,
should you have a AI policy?
But being in tech, everybody says
that 2025 is the year of
a genetic.
It's all about a genetic AI.
And yet we mostly just talk about
the chat bot and using ChatGPT
to do a bit of thinking for us,
rather than to actually start to
automate our lives and be
proper agents.
I really want to understand about a
genetic, because it's
like the year of people creating
agents to sell to other people,
but if you're in a business and
don't want to buy 500 million
different vertical agents,
how do you start to actually
automate with agents and are there
any good platforms to do that?
Agent says the password.
So first let's define what
an agent is.
And as everyone's talking about it,
suddenly it becomes just like this
fake. No one's quite sure.
For an agent to have agency,
it has to have the ability to choose
what tools, if any,
it is going to use to complete
the task.
The opposite of that is what we
might think of a workflow
or an automation.
So if people are building things
with it's happier if they're
building things would make if they
built integrations with Boomi
or Informatica.
If those things are predetermined,
even if it is an alarm call
and then another alarm call
that is still more of a workflow or
an automation because whatever
happens has been predetermined.
The true agent is
that I've got this alarm
tool and it is able to
decide now I'm going to
go and check a stock price.
Now I'm going to create a document.
Now I'm going to go and ask, you
know, another alarm for for
something else.
And I'm going to decide because
I've got the agency about
what to use and when.
And so for any company that is
thinking of building agents
or is being sold an agent
by someone else, that's the
important thing to dig in.
Have we really got an agent which
is able to make decisions, or
we just got a workflow?
And why that's important is that
if we're saying 2025 is the year
of the agents.
What does that mean?
We start to think about true
digital workers,
digital employees that
can make decisions.
So if we I don't
know if someone working in HR as
an HR administrator,
I'm able to as a digital
agent, I'm receiving a
request or a job posting
request from a manager.
I'm then able to go and
use another tool to go and write up
the job description.
Then able to go and decide if
we're going to have that budget and
when we're going to post it, I'm
then going to choose which
job boards we're going to post it
on. Then maybe if and I'm going to
choose which candidate I'm
going to shortlist and get invited
in for an invite, that would
be one or a series of agents
that are making decisions as
opposed to a true workflow.
But that's when you're starting to
really replace humans.
So that's a great definition
of agents.
This year is supposed to be the year
of a genetic AI.
By the way, genetic is a word that's
been basically made up.
That means agent, IC
agent. Like now everybody
in here, like I think I saw a
genetic for the first time about
nine months ago. And I was like,
what is this word? Is it a typo?
And now, like my entire life is
about a genetic.
It sounds great, I want some
if this is the year of a genetic, I
said, this is a year that all
software companies create agents
that other people can buy.
Or is this the year that I can
suddenly have a million agents in
my business by
using ChatGPT?
I'll answer that by talking
to maybe some of the steps that
a CEO or a company might
want to go through when
embarking on trying to make that
decision, both on anthropic
docs, website documentation,
and also on eyes.
They talk about passing the the
intern test, which is
you should think of I as
a brand new, eager,
but poorly informed intern.
And if you provide that intern
with a badly defined
instructions, you will get
what you deserve in return.
The original request
is quite poorly defined,
and that's often because
the person that's doing the job
today has been doing it for a while.
They kind of know it.
There's lots of sort of assumptions
or well, I'm sure you know what that
means.
And this is often why
you see in companies that when
someone asks, you know, how do I
do this? Or, you know, need and you
can speak to Gary.
He's been here for 20 years and he
knows how that works.
You can't take what's in Gary's
head and just give that to
the LM, because there's so much
of Gary's experience and knowledge
that's wrapped up in there.
So I find myself writing
a lot of long, prompt documents
that are maybe anything from 10 to
20 pages long, which is first
we do this, then we do that.
Then we do that.
This is what that means
to pass the internal test.
If I gave that Google doc to
an intern, could they do
what I'm asked them to do and I
would get the output?
And with anthropic and OpenAI,
when they say pass the intern test.
If the answer to that is no, that
if I gave that document to an
intern, would I get the response
I wanted?
Then how is an El Alam going
to do that?
It's not.
So I'd say a large proportion
of the time that I spend is in
getting the ask correct.
Once you've got the ask correct,
then creating whether as a
custom GPT or whether it is
building out some form of agent that
is able to access different function
calls, that becomes relatively
easy, because what you've said to
the intern is, let's do that HR
hiring example, right.
The first thing that you're going to
do is you're going to be on the
lookout for job requests
that come from hiring managers.
The second thing that you're going
to do is you're going to take all
the details of that job request, and
then you're going to start drafting
up a more detailed job description.
This is what our job descriptions
should look like, and all of the
details of what should be in each
section.
And then you're going through all of
that. We use some examples
of how that H.R.
Hiring person would have
the choice of choosing which job
boards to post on.
Well, how do we make that decision
and how do we access those job
boards.
And that's really the instructions
that you're going to end up providing
to the AI.
Now, if you don't need to access any
tools because the human wouldn't
access any tools, then you're
thinking more of just a simpler
implementation.
If you are looking at accessing
tools or you need to access your HR
system or your payroll, then
you're thinking more of, I need to
create some kind of agent that can
choose when to use these tools.
And how do you create the agent?
That's my question.
My recommendation is a tool
called the vessel
AI SDK.
So vessel VR CEO
and vessel is a web
hosting and deployment company.
So anyone that's an AI product
management product development role
may have come across V0.
So that's a v not dev.
That also comes from vessel.
And that is a AI
generative UI.
So you can design your applications.
But there's vessel AI SDK
is a really neat way
of plugging in to open AI
and to anthropic and to Gemini
and to any of your preferred
LMS, and it
gives you the ability to create
these calls out, these tool calls,
which is what makes an agent.
Well, because I guess if I step
back to what I'm thinking about
and maybe it can help is in
the past, and particularly
as my experiences as Crow, which
I complain about bitterly.
Not the crow part, but the number
of tools I had to buy.
Because you had this tech stack, the
revenue tech stack and
everything costs like 20
K other than Salesforce, which
of course costs shitloads more.
But it'd be like, okay, now it's 20
K for this and 20 K for
this and 20 K for that, and you add
it all in, and then suddenly
you had a tech stack
of, I don't know, 20 different
things and half 1 million pounds.
What I don't want to do
when I'm looking at my
IT stack for the future,
is to have that 20,
30, 40 pieces
of tooling that are critical for the
business, and some of them are big
and some of them little, and they're
all whacking some AI on,
so they all have a chat bot.
Nobody seems to have a particularly
compelling vision.
I know that we are not all that
impressed by GitHub copilot,
you know, versus Verses like
cursor and some of the others.
It's I don't want to blindly
buy all of these tools
that say they have something, that
maybe have an agent, and
I still just have to pay shitloads.
What I would like to understand
is how to think about
what the future
tech stack should be for
a scale up. So a couple hundred
people to a thousand people.
Technology's moving really quickly.
This is the year of the agent.
What should I be buying today
or what should I be evaluating?
Because my ideal and my vision,
and I'm guessing that other people
would have this vision, is that
everybody has
their own assistant
who can do all of this shit work,
and it's really easy.
And you just say to your assistant,
can you look through all of these
CVS for me and stick
them and highlight the best
ones, or contact them or,
you know, and be able to write The
foreign intern prompt that's 20
pages long.
But once I do that, I never
have to do that work again.
And I want everybody in my company
to be able to do that, not just the
individual who understands how to
use VSL or
API's.
How far away are we from
that and
what are the steps to get there
this year?
It is such a
fast moving space
that it is just impossible
to say, you know, use
this tool or use that tool
because so much is coming out,
whether that's models or whether
it is tools that are set over the
top of these models that
help to create these workflows
is speaking to a CEO.
This would be my advice
is that there is never
been a better opportunity right now
to internalize
some of these skills.
Previously you might have said, you
know, build versus buy while the
building is just too complicated.
We're not going to go and set up
some massive infrastructure
and start investing in people to
run that. So we're going to buy
we'll buy a CRM, we'll buy
an air platform, whatever that might
be. But I think we're seeing now
that pioneering companies,
and that doesn't have to be just
like some funky startup.
But actually, I mean, you saw this
with Klarna recently
and saying, you know what with some
of these tools, whether that is
universal, whether that is V0,
whether it is a
new development platform
that people are going to, you know
what, I can take non
development people.
So a product manager or
someone in an operations team and
I can start building out proof
of concepts and building internal
products without
having to go and get a SAS
subscription from someone else.
And suddenly I'm relying on
their roadmap rather than
our own.
So I think there's going to be,
you know, some companies that just
don't get involved in this at all
and just stay. Let's leave AI
aside.
Then there are going to be some that
go. We want to buy stuff.
So let's rely on someone
else's a platform
for stars
or for marketing or whatever.
But I think there's going to be an
increasing number of companies said,
you know what?
We have got insight
into what are our challenges.
And we think it's quite unique to
us. And we're just going to
have a go at building something
internally using these
publicly available tools.
It's about using as
many tools as you can come across,
as they keep getting developed to
improve your learning and the way
of working.
This all feeds into that first
bit, which is about, you know, AI
positive or a negative
AI going to lean into AI
or lean out of it.
And again, checkers is important.
So having done that
then the primary
driver of a good change program,
and everyone will know this
regardless of what it is you're
trying to change, is having
empowered and inspired
senior leaders that are at
the top of that program.
So I would then be looking at
who's the rest of your executive
leadership team. So if you are the
CEO, I'd be looking left at the
CFO. I'd be looking at that chief
Revenue Officer.
I've been looking at the Chief
People officer and a level
down into those VP's
and figuring out quickly,
how do we get those people
comfortable with using
AI for their own tasks?
It is so important to have that
team really understand
how I can help them personally,
because that immediately filters
down to the rest of the
team. So you've got to get that team
on board so that could be just
running.
So inspirational workshops for those
leaders.
Maybe have a breakout session at
your next leadership offsite.
And it's not about encouraging
them about how their teams should be
using AI.
It's about how do you
use AI?
If you're a c o,
you have a set of
direct reports that you need to
manage and inspire.
You have got colleagues
who run finance or on
HR, or who run legal.
And how do you better understand
their view of the world as a
CEO? Or you may be just
going through a merger or
acquisition, and you may be having
to figure out, how do I
align this whole new set of people
and processes and data into our
organization?
So it's thinking about how does
ChatGPT, how does Claude, how
does Gemini, how does that solve
your personal, daily
and monthly working processes?
And if you can figure that out
immediately, it gives that
permission to everyone below
to explore and experiment as well.
I tried to just have one
subscription, but I now end up
having to have two.
So I have both Claude
and Betty because I
just find Claud writes things
better. But ChatGPT has a wider
range of capabilities and
functionality and also is attached
to the internet, and I use it when
I'm stuck thinking,
but and kind of in those use cases
you talked about and like the team
use it for ideas for deal
reviews or how to write a better
proposal.
But what I really want to use it for
is all of the hard things
that are boring.
And I hate like org charts,
but I ended up spending about 2.5
hours trying to get it to write me
an org chart, and I could not.
And I was asking it to help me
figure out how to tell it, to write
me an org chart, and I could not.
Is this what it's worth, going for
some sort of AI training course?
Or is it just really bad at making
org charts no matter what?
Because for whatever reason, they're
incredibly difficult.
So there's some basic tips that you
can follow. So whether you're using
code called ChatGPT.
Gemini.
Any of these tools.
Firstly, in both Claude and ChatGPT,
you can set up a project and
set a project as a wrapper
around a task or a set of
chats.
So as a CEO, if
you're doing anything repeatedly.
So that might be a set of chats
about one of your direct reports.
It might be a set of chats about an
acquisition you're going through.
It might be a set of chats about a
policy or process that you're
crafting.
Create a project.
You then upload background
information so that could be
documents. It could be
just your instructions about how
you want ChatGPT to
respond to you.
And then you get into how do you
craft a prompt.
And I'll give you some specifics
here. So my typical
prompt, especially something when
I'm reusing it, is anything from
6 to 8, nine, ten
pages long ago.
That's that's longer the little chat
window there.
But because I'm, I'm using that
prompt again and again, it's
worthwhile.
So I break it up with
XHTML tags.
Now you don't need to be a developer
to know this. I'll just explain it
super simply. If you don't want to
add XML tags.
So a left arrow kind of opens
it. And then you write the word
objective and then a right arrow
to close it. So that's your opening
tag objective.
And then to close that XML
tag you do exactly the same, except
there's a backslash up at
the start after the first opening
bracket.
And I'll put some of the notes about
this prompt and guidelines so that
you can have it in the show notes.
Now when you're writing your prompt
you're basically structuring.
So I say objective.
This is the first part.
The objective of this prompt is
to develop a job description
or a merger plan, whatever it might
be. Then the next tag might be
open the tag instructions.
Right. This is how I want you to do
it. The user is going to provide you
with this information.
I mean, I'm the user, but I'm going
to provide you with this information.
I then want you to ask me some
questions. And here are the
questions which I put in another
question tag.
Then you get to the two most
important parts of a really
great prompt.
And they're often the hardest bits
to put it in.
And this is what takes their long
time and makes it a ten page
document.
So examples.
So think about the intern.
If I ask you to build
me an org chart, but I don't
show you what a good org
chart looks like.
2 or 3 of them, you're just
running around in the darkness.
If I don't show you a bad
org chart, you don't know what bad
looks like.
So whether it is,
you know, a job description,
whether it's a spreadsheet table,
whether it is a project timeline,
whatever it is that you want.
A good prompt should always have at
least 2 or 3 examples,
a good one, and then a bad one.
So that can take up quite a bit.
The final tag that I always
have in there is exceptions.
So what should the
AI do if
you don't have certain information
that you've asked for?
So for example, if I'm drafting
a job description and I've asked
the AI and the instructions to
ask me for the salary range,
let's say I haven't got the salary
range yet. Well, what should the AI
do in that situation?
You might say if the user does not
have a salary range, then
know that this is to be verified
later and at the bottom of
your response, put some next
actions or follow ups or whatever.
So this sounds quite
detailed, but if you're
doing one to ones with your direct
reports, you do that regularly
and you're going to do it a lot.
So it's worth spending an hour
writing the prompt
so that you've got that in there.
So there's just a bit of guidance.
If you put the the right
in front to really
pass the intern test.
If you gave that to an intern,
they'd give you a good response.
Then I think you'll start to find
you get better.
Whether that's an org chart
has on that, because maybe you're
trying to get a visual, which it
probably wouldn't be very good at.
But in terms of the hierarchical
structure would probably be
pretty handy at doing that.
We in our company
kick off this year, we had everybody
working groups to identify use
cases along the customer journey
where applying.
I would be really cool.
And every single
team, they came up with loads of
different ideas, but every single
team came up with one idea that was
the same, which is basically
putting all
of our internal data
in a data repository and putting
ChatGPT on top, or a GPT
on top. So like all of the
historic slack
information, all of our Google
drives.
Then you have Salesforce
data, etc., then be able
to from that repository, ask
like, give me a summary of
what the customer relationship has
been like to date.
Give me a summary about like
usage of that customer, all of those
types of things.
So that we go think about the
build versus buy.
I'd be taking a look at glean.
I'm not sure if you come across Glen
GLE and.com.
And it's exactly that use case.
So founded by some ex Googlers.
How do we use AI
to search across our
existing data sources.
And at first glance you say,
well, you know, the challenge
is quite easy because we just go
and, you know, plug it in via APIs
to all these different things, but
you need to preserve the
data privacy rights of
the source material.
So if I go search customer
X, how much did they spend last
year. Well, I should only be able
to get that answer if
I would be able to get that
information in the actual source
system, because I've got access to
that data or whatever.
Anyway, so I had a chat with
one of their team just before
Christmas and it was a super
interesting use case.
But that's exactly what Glenn is
targeted, that.
When we first kind of reconnected
and started talking and you talked
about your Power Hour,
and I think I have told everybody I
know about it, and I thought, why
not share it with the rest of
our listeners?
What's your power hour?
So my Power Hour started
during Covid,
and like many of us,
I was a commuter before
Covid, jumping on a train.
God knows what hour into
London.
Covid came along and suddenly
I had all this time in the morning
and my wife would take the kids to
school and, you know, I'd
be up and about, you know, having
taking the dogs for a walk.
7:00.
And then the kids are off.
And then I had to sort of hour from
eight till nine when nothing
was really happening.
And so I decided that I was going
to start to write a book
during that hour.
And so I would just write, you
know, a chapter in an hour, having
thought about what was going to
write in the shower.
And suddenly I found it was like
super productive.
Like by the time I got to 9:00, I
had done a ton of work and probably
my most creative work of the
day. I was lucky enough to finish
published that book, and I just kept
that power hour going.
And it's the hour that I work for
myself, whether that's on
sort of personal writing, whether
it's recording a YouTube video.
And I'm very humbled
that I get lots of lovely comments
from people like, I've got no idea
how you create so much stuff.
You know, there's always a new
e-book that you've published, or
you've recorded a video for YouTube,
or you've done a podcast, or you've
published a book and you know, how
are you doing all this stuff?
And you've got four children and two
dogs and you've got, you know, your
work and everything, and it's that
Power hour has been
super helpful.
And once you get into the
habit of it, then
it's very difficult to break.
It doesn't actually seem like work
anymore. It's just a routine I
find myself.
Weekends included at
my desk from eight till nine.
Just crank through some great work.
The book that inspired that was
Atomic Habits, which came out
pre-COVID. I'm sure many people have
read it was an Amazon bestseller,
but it was all about, you know, if
you create the framework
at 8:00, I will sit down
at my desk, create the input,
and then the output arrives
magically.
Lovely. So if you like what you
hear, please leave us a comment or
subscribe and we will wrap on
this episode of The Operations Room.
Thank you for joining us, Charlie.