How To Leverage AI In Marketing

Welcome to The Power Lounge! Today, dive into artificial intelligence in marketing with guest Pam Didner, a B2B consultant and author. Explore how companies like Google and Amazon use AI for recommendation engines and search optimization. Learn about generative AI tools like ChatGPT in creative fields such as copywriting. Pam shares insights on optimizing AI prompts for marketing, blending AI with human expertise. Discover the potential of AI agents in automating tasks, focusing on data quality and analyzing data for insights. Whether you're an AI enthusiast or a marketer, this episode offers practical insights for navigating AI and marketing.

Connect with Pam:

Guest LinkedIn: https://www.linkedin.com/in/pamdidner/

Guest Instagram: Instagram (@pam_didner)

Guest Website: Pam Didner B2B Speaker and Consultant

Episode Timestamps:

00:00 - Introduction

00:52 - Skill and Gift Exploration for Success

10:05 - Navigating Digital Tech: Pros and Cons

15:43 - Task Efficiency: AI Agents for Automation

18:51 - Empowering Education: Women and AI Knowledge

22:34 - Crafting Headlines: Unveiling Essentials

29:31 - Controversial OpenAI Public Offering

32:23 - Vision of Tomorrow: Easing Today's Turmoil

38:31 - Data for Enhanced Customer Engagement

46:31 - Tailored Communication with Targeted Audiences

52:08 - Human Touch: AI and Experienced Marketers

53:59 - CrewAI: Enhancing Tech Company Functions

01:02:40 - Outro

Quote of the Episode:

"Combine human creativity with AI precision for effective email subject lines."- Pam Didner

"Avoid generic prompts; place it in the right context for meaningful impact."  - Pam Didner

Support the show

Episode Transcript

Speaker 1 (00:10):
Hello everyone and welcome to our weekly Power
Lounge.
This is your place to hearauthentic conversation from
those who have power to share.
My name is Amy Vaughn and I amthe owner and chief empowerment
officer of Together Digital, adiverse and collaborative
community of women who work indigital and choose to share
their knowledge, power andconnections.
You can join the movement attogetherindigitalcom and today

(00:35):
I'm thrilled to introduce all ofyou and to have joined with us
for this next hour, an hour ofinsight, inspiration and
empowerment.
We are going to dive into atopic that's pretty much on
every marketer's mind right now,and that is how to leverage AI
in what we do In a world whereAI is rapidly evolving.
It's not about replacement,ladies and gents.

(00:57):
It is about enhancement, wherewe're here today to explore how
you can harness the power of AIto supercharge your marketing
strategies and drive betterresults.
Our special guest today, pamDiener, is a B2B consultant,
speaker and author with a wealthof experience in strategic
planning, account-basedmarketing and sales enablement.

(01:19):
Pam has written not one, nottwo, not three, but five
business books.
She just, you know, does allthe things and then, in her
spare time, writes all the books, including, very recently, the
Modern AI Marketer in the GPTera.
So we are in for a treat.
It is definitely somethingworth checking out and grabbing.

(01:40):
It is a great tool and resource.
It's not going to take youforever to read.
It is going to be somethingeasy.
It's not going to take youforever to read.
It is going to be somethingeasy and quick to digest, with
some fantastic prompts,something that you can take and
start to put into action rightaway.
So over the next hour, we'regoing to unpack AI's role in
marketing, dispel some of thosemyths about job replacement I
know it's a crazy market outthere right now and we're having

(02:01):
to shift and change and embracea lot and we're going to
discuss how you can adapt yourapproach to AI for maximum
impact.
All right, remember, folks,we've got our live listening
audience here with us today.
We love it that you are herewith us.
You keep us all honest and youkeep us all authentic as we have
our conversation here today.

(02:21):
So, live listening audience,please feel free to use the chat
, ask us questions, let us knowhow you're feeling.
We are all on this ride alongtogether, so let's listen and
learn and grow with one another.
Pam, welcome to the PowerLounge.
We're excited to have you herewith us today.

Speaker 2 (02:39):
Amy, thank you so much for having me.
I'm so excited to be here.
It's wonderful, it's live.

Speaker 1 (02:44):
Yes, for having me.
I'm so excited to be here.
It's wonderful, it's live.
Yes, I know right, we're goingright for it.
Going right for it, and youknow for those who don't know
you maybe as well as I do youhave had an impressive career as
a b2b consultant, speaker andauthor, and I would love for
those who are listening to heara little bit more about you and
your career journey so far, tohear a little bit more about you

(03:05):
and your career journey so far.

Speaker 2 (03:05):
Yeah Well, I'm not a typical B2B marketing person.
I'm actually have, kind of likea twist of fate, career change,
if you will.
So I'm actually was a CPA and Iwent to a dark side to become a
marketer Yep, so I work in abig corporation for a long

(03:26):
period of time, and way backthen they actually encouraged us
to move around and I was, veryfortunate, started with the
finance and accounting and thenmoved to operations and then
supply chain management,purchasing, and somehow landed a
job doing event operationsbecause I'm very good at
operations.
So that manager hired me toactually do event operations and

(03:47):
somehow that led to tradeshowing events, which I did for
four years.
So if any one of you are doingtrade showing events, salute.
It's a hard job and, amy, youknow pretty well if you do the
event, you know exactly what I'mtalking about.
And then from there, I made atransition to doing marketing

(04:08):
strategy as part of the COVIDmarketing team and set up a
direction marketing directionand campaign direction for the
regional marketing team.
So and I left that job.
It was great, but I left in2014.
And in the past 10 years I'vebeen on my own.

Speaker 1 (04:24):
I love it.
I love asking this firstquestion because it really,
again, every episodereemphasizes the nonlinear
direction that every successfulwoman's career takes.
I think for those who are earlyin their career, mid career, in
a career crisis, it might feellook at your collective
experience, all of your skillsare transferable, and I love how

(04:45):
your company encouraged that,because I know not all companies
do.

Speaker 2 (04:47):
I was very lucky yeah .

Speaker 1 (04:49):
That's fantastic and I love.
I love hearing that backgroundbecause sometimes you learn
things, even people that youknow.
You're like, oh didn't know CPA.
But then broadening thoseskills and taking, taking,
taking and embracing all of yourabilities and all of your gifts
.
And you know, running with thatusually lands you where you are
absolutely meant to be.
All right, let's talk about.

(05:11):
Let's talk about the books youknow, the, the the modern
marketing, the modern AImarketer guide to gen AI prompts
that you have beautifullydisplayed there behind you.
For those of you who like tosee the books, yay, go check it
out.
Kaylee, so amazing, has alsodropped that into the chat for
our live listeners to take alook at those who are viewing

(05:32):
after listening afterwards, besure to check it out in the show
notes as well.
You say that mastering AIprompting is no longer optional.
I think a lot of us listeningwould have to agree, and those
of us who are listening oraren't there yet will soon be
convinced.
When did you realize that thisshift was happening in the
marketing world?

Speaker 2 (05:50):
I think I started talking about AI back in 2019.
So I just want to put things inperspective.
Chatgpt was launched onNovember 30th 2022.
Yeah, and within five days fivedays it hit 1 million users.
1 million, and when I found outit hit 1 million users, I was

(06:12):
like, wow, I need to check thisout.
Yeah, and then, of course,within less than two months, it
hit 100 million users.
So everybody was going to chatGPT, which is kind of starting
up this Jan AI, you knowrevolution if you will.
And then they just stop askingquestions.
Why chat GPT is captivating isit gives you one answer One, if

(06:37):
you do.
You know it's kind of likeGoogle search, right, you're
asking Google for questions, foranswers as well, but you have
to sift through.
You know many articles.
You have to read it.
Do you know how much work thatis?
So much work?

Speaker 1 (06:50):
And then we know we're getting sold to right to
because, like the first page, isall sponsored anymore.
What are you?

Speaker 2 (06:57):
doing Right.
So everybody was like askingquestions and I was like, oh my
god, there's an answer.
You can ask pretty much anyquestions.
You can relate a codingquestion, you can ask him about
IDA, your birthday party.
You can ask anything marketingrelated.
You get answered.
The answer is good or bad.
You know, you need to be ajudge, you need to make a

(07:19):
judgment call, but one answer isthat instant gratification, oh
yeah.

Speaker 1 (07:25):
Yeah, it's like the marketer's magic eight ball.

Speaker 2 (07:28):
That's right.
Yeah, it is Because I wassaying.
I was saying, like you knowwhat this is all BFF.

Speaker 1 (07:32):
Uh-huh, yeah, yeah, and I mean as early as 2019,
that's really interesting thatyou kind of caught on that early
and was like, okay, this issomething we need to be paying
attention to.
Was there any initial fear foryou in that, or are you kind of
one of those people that you'relike, ah no no, actually.

Speaker 2 (07:51):
Um, that's a great question, to be honest, and a
lot of things, or a lot ofresearch.
I started doing that's becauseI have event organizers, so
people, clients, that come to meand say, hey, can you look into
this?
So I actually have an eventorganizer come to me and say,
hey, can you look into this?
So I actually have an eventorganizer come to me and say,
can you talk about AI?

(08:11):
And I was like sure, no problem.
And I turned around I was likeI don't know what I'm going to
say, I just don't know.
But you know, then I starteddoing research and way back then
you know, it's not I don't, Icall it like the chat GPT kind
of launch the consumerization ofAI.
But way before them that peoplecan actually use the algorithm

(08:33):
or use a large language model toactually take advantage of AI
is big companies like Google,like Amazon, you know, like, for
example, the great example ofai is when you buy something on
amazon, they have therecommendation.
You like this.
Therefore, you will like thesetwo and I'll check it out right.
So the the ai usage model I wasusing is more kind of like

(08:58):
enterprise applications, yep anduh, less on kind of like how
the marketer can apply to it.
Okay, and then, of course, uh,after chat, gbt generative, the
whole world changed.

Speaker 1 (09:11):
Generative yeah, I think generative really lit the
spark.
I think a lot of us kind ofdidn't really understand what ai
was and how much it wasactually like in the background
of our lives as marketers andbeing leveraged as a tool, I
mean even in like creativeapplications and, you know, like
image editing and things likethat.
Yeah, we don't realize how muchit was in the background.
But then we think ai and it'slike all generative, it's our

(09:34):
all lmlm and it's like um largelanguage models and it's not so
much in the space of you know,other technologies.
I think oftentimes we forgetWe've become so consumed with
just that, we kind of take itfor granted.

Speaker 2 (09:48):
We do For a long time .
The AI is really behind thescenes.
It's something that you cannottouch, you cannot smell, but it
is working there for a longperiod of time.
It is, for example, the Googlesearch.
I mean, google continuouslyoptimized the Google search
mechanism.
Yeah, the machine learning,before you have to type the

(10:12):
whole sentence.

Speaker 1 (10:13):
Now you just have two words and, yes, the predictive
text exactly, and that's, that'sai in the work it is, it is and
I think it does a lot too forthe sake of like,
personalization and just likecreating efficiencies and things
like that.
I mean, we get into and breakdown a whole mess of things as
to like how it's helpful but howit's harmful, but at the end of
the day it's.
I think you know, again, I'mlike a digital gal, sort of
through and through.

(10:33):
So for me, I think a lot of itwas like this odd fascination
that probably a lot of peoplefelt when, like in the sixties,
when we were trying to go to themoon, you know, it's like wow,
where will this take us?
What will?
this mean and it wasn't reallyfor me even being like a
background, like my background'scopywriting, and I mean that's

(10:53):
straight what AI?
Generative?
You know, generative AI iscoming for it's like it's those
who write, but then I'm alsolooking at it going okay.
But now people who aren't bytrade writers now have the
ability to actually storytellyou know I don't.

Speaker 2 (11:10):
I do agree with that.
I do agree with that and um.
So if you are a copywriter, Idefinitely feel there is a
threat and the entrance of likeai can write faster and quicker.
That doesn't mean you know AIcan write better Agreed, and you

(11:31):
need to be.
You need to understand yourbrand, you need to understand
your product.
You also need to understandyour audience, yes, and you know
what tone and manner will makethem click.
And you have that knowledge.
Ai doesn't.
The only way AI can have thatknowledge is through prompts,

(11:52):
through your direction ofguiding them.
So it's still coming from yourexpertise.
So I cannot generate anythingmagically.
Yeah, it can, but you stillhave to give them that direction
, the guidance.

Speaker 1 (12:07):
It's going to be very vanilla otherwise, which leads
beautifully into the nextquestion that I have for you is
you know, in your book you'veincluded over 75 prompts in 12
sales and marketing categories.
Yeah, there it is again.
Great product placement, I loveit.
Can you share all of those 75?
Because we don't want to givethem all away.
We're not giving them all awayfor free here today, folks.
Can you share one with oneprompt that you think would make

(12:32):
that every marketer should havein their toolkit?

Speaker 2 (12:36):
I think if you are using, I would say, the AI
prompts right now a lot of youare using for, like, you do a
social media post and you'regoing to write something and
then you're going to ask, like achat, gpt or AI prompt to
rewrite it, you know, just tomake sure that it's
grammatically correct or there'sanother way to say it better.

(12:59):
So I think the one thateverybody tends to use right now
, as far as I can tell, and youcan tell me otherwise, is um,
social media posting, right, soit's just like rewrite it and
then make it better and honestly, you don't like on linkedin,
you don't even have to get outto chat gbt, you don't.
Yeah they built it in and sayrewrite with ai and actually try

(13:23):
that.
I don't think it was that good,but anyway, that's just me,
okay, thank you.

Speaker 1 (13:28):
So you are the copywriter and you validated my
point of view.

Speaker 2 (13:31):
Yeah, and um so um.
I think the writing part of itis probably where majority of
people or the marketers areusing that for like writing a
blog or whatnot, and by I doactually have a point of view.
There's a lot of things you cando.
Like I said I created this isonly 50 pages, not, you know,
you can.
I can tell you, just go tochapter three.

(13:53):
Yeah, that's great, I love it.
All the comments and it's likedivided by uh 12 sales and
marketing categories, and Iwrite basically like, for
example, I need a social mediapost for my organization, you
talk about your company name andthat's public.
Write a post for you know,social media platform, which one

(14:15):
on this topic?
For that topic you should givea little bit more detail.
Yes, in a specific number ofcharacter.
That's assumed that you onlyhave to use.
You know, like uh 228characters or less.
You can provide that specificinstruction.
Write it in some sort of tone,in conversational.
A blog writing, formal,business writing, right, in

(14:37):
certain tone, right, so you canspecify that.
Include a call to action in theend, and then you specify code
of action yep, so.
So the way I write every singleprompt is um, it's kind of like
a paraphrase, yeah, orparagraph.
I love that.

Speaker 1 (14:53):
You can replace and add additional information to it
, yeah, and the more specificyou can get, the better.
And what I've done is I'vebegun to just kind of keep those
like saved and paste it andjust to kind of like plop them
back in, because I'm going touse the same sort of prompts
sort of over and over and overagain.
And I've definitely found that,like you know, you can train

(15:13):
your AI and we'll get into thisat some point too.
I've got a guest coming soontalking about AI agents, which
I'm not sure if you're superfamiliar with AI agents yet.

Speaker 2 (15:21):
Yeah, I'm familiar with it.
You can actually create an AIagent and, yes, to do that.
The bottom line is, amy, can Itake over what you just said?

Speaker 1 (15:30):
Elaborate a little more.
Yeah, absolutely.

Speaker 2 (15:33):
Like, for example, amy has this beautiful live, you
know podcasting.
And then she, every single timeshe does this podcast, she has
to come up with the title.
And then she, every single timeshe does this podcast, she has
to come up with the title, shehas to come with the meta
description, right, and theseare like repetitive tasks for
every single episode.
So there is a problem that hasbeen written for you know to

(15:55):
come up with a better title, tocome up with metadata and a
description, so that descriptionor that prompt doesn't change.
You can actually create acustomized agent or customize a
personal system that just focuson these two tasks.
So when you just have to change, maybe you know the title and

(16:18):
or give a little bit informationabout this specific episode and
then that agent will createsame the, the topic for you,
because it's repetitive tasksand you build an agi, a ai agent
for it.
So you kind of automate, if youthink about it, that specific
process yep, I was like, oh mygod, this is so good.

Speaker 1 (16:42):
It is so good.
Well, because it's, it's likethat next phase, right, it's
that next step.
So many of us are kind of.
It's maybe a little hard to getyour head around, but I love
the way you just explained it somuch, pam, and it's like it's
also I'd like to explain it aslike a toolkit right, like you
wouldn't grab a hammer out of atoolbox to tighten a screw,
right Thanks.

(17:06):
Box to tighten a screw right,thanks, thumbs up.
You would.
You want to grab, you know, ascrewdriver to do that and
you're not going to, you know,grab, build a tool to do that,
to screw in the screw every time, the screwdriver.
You're going to want to justhave the tool already built, you
know.
So it's like that's what anagent is.
It's like literally having ascrewdriver already set and
already made.

Speaker 2 (17:23):
Yeah, because you are using that same screw, you know
, every single time.
So that's built, that'sultimately that process to make
it easier.
So, amy, doesn't have to thinkall the time like, oh, my god,
I'm talking to pam, about ai.
So what should the title beright and the same problems over
and over.

Speaker 1 (17:41):
Yeah, and it's so great too, because once you've
like and I mean you know you'vegot processes out there too that
will help you kind of build andcreate your.
And I've seen this too I was ata black tech week here in
Cincinnati a couple months agoand there was a guy there
talking about like building outand programming agents for doing
even like financial reportingand finance work, talking to a

(18:01):
CPA here.
So like there's a lot of stuffnot just marketing tasks, even
now that can actually beautomated and done to a certain
degree.
Obviously, you have to keep whatthey call like the human in the
loop to check for like errorand processing, and management
Because, as these agents likethere's again, not to break
anybody's brain, here we'regetting a little off topic, but
I start to nerd out these agentscan actually like work across,

(18:25):
like collaborate and work witheach other and actually
oversight with one another tosome degree, apparently, within
some technologies and platformsI'm hearing about and seeing
which again, not to breakanybody's brain, but here's the
thing.
It's like it's important for usto hear, see and learn about
these things because, at the endof the day, this is just how
our work is evolving.
Right, and if you think aboutit, it used to be that you know

(18:46):
generations before we built carsand things by hand and then
there came a time when we gotout of the assembly line and
machines started being thethings Thinking over Yep, it's
kind of that same revolution.
You know what I'm saying?
It is, it absolutely is.
So, all of the work that you'redoing, I love that you're
creating content for folks thatfeels digestible and specific

(19:08):
and actionable, and so when youwere talking about creating
these books and sharing them andI got my hands on them, I was
like we have to have her on thepodcast because I know this is
such a big topic for a lot ofour women out there that are
members, and then those who arelistening to the podcast and
it's.
It can feel overwhelming and itcan feel daunting, because maybe
you aren't as big of a nerdabout this as maybe you and me,

(19:29):
and that's totally fine and youdon't have to be.
But, like, how can we empoweryou with a little bit more
education and information sothat you can, um, kind of get
your your hands on to the stuffso that you can move forward as
well?
Let's talk about a little bitmore of about prompting and how
your book emphasizes theimportance of building, because

(19:50):
we're kind of still on thattopic of prompting and building
sequences of AI prompts.
Talk us a little bit through,because agents kind of fall into
that space too right?
Could you talk us through anexample of how the sequential
approach works in practice?
Maybe?
building even off the socialmedia, one if you want, or give
another example, whichever so inthis book, especially uh

(20:13):
especially I did talk about.

Speaker 2 (20:15):
They are a different uh prompting technique.
This is actually on page 10.
So there's a chain of thoughtprompting which is you have a
specific thought and so youbuild a question kind of ask
like hey, what is commercialbanking?
And then the next question islike what is you know?
Then they will give you a lotof information and then one of

(20:36):
them is line of credit.
And then you move on, say whatis line of credit?
And then then maybe next one,you say how can I apply?
You know, it's the chain ofthought, right.
And then the other one iscalled treat of thought.
It's basically it's expansionon the chain of thought
prompting by asking the model togenerate multiple potential
steps, like line of credit.

(20:57):
So how do I apply?
Like, can you give me the steps?
What do I need to do?
Right?
And so there are many differenttype of prompting techniques.
It's kind, even though I thisis more kind of like I provided
the technique options, but setthis aside.
Just put that away.

(21:18):
The thing about the chat, gbt orany kind of GAN AI at this time
is you can carry conversations.
That's how you need to thinkabout it.
Don't think about any kind ofthe.
You know the technique option Imentioned.
It's no use, that's academia.
So you think about it.
When they build a sequence youdon't really have to like.

(21:38):
Oh my God, let me think aboutit first.
What I need to talk to AI?
No, it's not.
It's more or less like you havethis specific question.
The AI is not answering the wayyou want it.
Yeah, okay, now you have tothink about it.
How can I write it a little bitdifferently?
or and or they are answeringthis and it's like it's not
really that.
I don't know.
I I need to write it.

(21:59):
What is this?
Or can you explain a little bitmore?
You know those like veryconversational type of uh text,
yeah, or how we communicate withthe real humans.
You can write those and carrythat conversation forward Like
that's, for example, just likeyou said, the social media posts
, for example.

(22:19):
So you write a social mediapost but you're like I don't
know.
Then there are certain thingsyou need to.
You can say rewrite you knowthe two sentences.
Or you can say no, I needsentences.
Or you can say no and youchange my code of action to this
make it stronger.
So that is the sequencing I'mtalking about.
You can carry the conversationforward right and help them

(22:40):
understand a little bit more andthey keep forward yeah, I think
one one.

Speaker 1 (22:45):
I don't know if this would count as sequencing per se
and you can tell me if it is ornot, but like I will do it to
help generate um, because, gosh,as a copywriter it's got thrown
on me all the time as a juniorcopywriter, and those of you who
are out there listening thatare in that space you'll
empathize.
They're like write me a hundredheadlines because you know, I
know it won't be, we won't comeup with a good one unless you

(23:05):
write a hundred.
And I'm like I've written for solong now I know a good headline
when I see one.
Okay, and I used to have onelike chief creative officer.
I used to like he'd always belike you won't get to the good
one until it's like a hundred.
And so I used to like take myfirst headline and put it at the
bottom because I knew it wasthe best and the right headline

(23:27):
and that's the one I wantedanyways, and that's how I got
those guys.
I'm going to choose the one Iwanted.
Pick up on that is, I'm goingto pick up on that.
But yeah, now I use AI as mylittle, my little junior
copywriter be and my listen, youwrite me 10.
I'm not as demanding.
I'm like write me 10 headlinesin my sequences.

(23:50):
Then I'm like okay, given thatthis is my audience and that
this is my objective, which ofthese headlines do you think
will be the most effective?

Speaker 2 (23:59):
And I have it analyze itself.
That's a sequencing, because Ihave done that as well, so it's
very interesting to see how AIanalyzing yeah it's fun.
Some of that I was like oh myGod, okay, I get that, you know.
They were like well, this isactually more benefit driven and

(24:20):
the other one is moreconversion.
Yeah, and that one you know,it's like, yeah, analyzing, I
was like oh my God, it's so fun.

Speaker 1 (24:28):
It's so fun to watch it analyze itself.
And then what I'll do is I'llthrow it into a subject line
tester and I'll get the scoring,and I'll get the
recommendations from a subjectline tester and I'll take that
feedback, throw it into the chatGPT and I'll have chat GPT fix
it.

Speaker 2 (24:42):
See, now you talk about a process of using two
different tools.
I love it.
Yeah, it's fun.
I love it.
Yeah, I love it.
So you kind of asking thequestion and you find out and
get the best out of AI for thetime being right, and then you
do using a knowledge tool totest it and validate it and then
come back and make it evenbetter.

(25:02):
Yep, amy, you can do a prettygood job of it you're funny.

Speaker 1 (25:10):
well then I felt like I felt like super awesome
because then I got like a 100,which I, honestly, in all my
years of writing not going tolie friends I mean I've gotten
like a 95 writing my own, butI've never tested.
I've thrown it into a testerand got the 100.
I was like screenshotting thatshit.
I'm like I'm saving thisforever.
It was me and ChatGPT.

Speaker 2 (25:32):
We worked together on this.
You know what I help AI to besuccessful.
Right, I am so good at it we'rea great team, me and AI.

Speaker 1 (25:40):
Oh my gosh, so funny.
I love it, but yeah, I thinkit's just.
It's again.
I mean, it's just.
I'm a collaborative person, soeven whether it's a person or a
bot, i'm'm down for it.
I'm down for it.

Speaker 2 (25:52):
You are like equality inclusion it's all good.

Speaker 1 (25:57):
Yeah, I mean because, again, at the end of the day,
you know what I've got.
Like you said earlier, I've gotthe insights, the human
insights.
I have got the empathy, youknow, and I've got like the
final say and judgment on thosethings.
You know, it wouldn't have gotthere without me.
It wouldn't have got therewithout me.
It wouldn't have got therewithout me that's.

Speaker 2 (26:13):
that's where humans still provide.
Humans still provide value.
I don't know how that willevolve, that the AI becomes so
smart and because they arelearning fast, they are learning
every day.

Speaker 1 (26:29):
Well, that was my next question is how you see the
role of human expertiseevolving as AI prompting becomes
more sophisticated.
Like what does our role beginto look like?

Speaker 2 (26:41):
You know that's actually a $64,000 question.
I don't know, I don't want tobe a pundit.
Every time I predict something,it's always wrong, I'm the
first one to tell you You'refunny, it's like, okay, like
don't want to be a pundit.
Every time I predict somethingis always wrong, I'm the first
one to tell you're funny, like,okay, like, if you want to put
money actually on what Pam saidyou should, because you're gonna
win, you're obviously gonna win.
Um, I, I think about that oftenin terms of you know that ai

(27:11):
becomes super smart, and I mean,like several weeks ago, that
the open ai basically said thechat gpt will have reasoning
capability.
Okay, but who defines reasoning?
Right, what is their definitionof reasoning?
So do they have a cognizantcapability?
You know, but they said it'sgoing to.

(27:33):
Obviously, when you promptsomething, maybe they will
provide certain kind of logicbehind this.
So they are going to give youeven better and uh, answer that
tailor for you.
I don't know what that means.

Speaker 1 (27:47):
Yeah um, I know people that can't reason.
So yeah, sorry, sorry.

Speaker 2 (27:56):
I don't know, like how far that I can do, but you
also have to bear in mind AI atthis point, that working with us
, they are software, they arealgorithm embedded into devices
or embedded into a software.
Imagine one day they house thatwith a form, with a robot.

(28:19):
So, in a way, whatever we aredoing right now, we collectively
, as a human race, are buildingthe brain of AI, because
eventually you're going to hostit.
That's how I see it, yeah, yeah.
It just makes you wonder howdoes that, how does that, how
does that help us in the longrun?

(28:40):
I don't know, I cannot tell youand I, I we have seen enough.
I guess hollywood horror films,like in terms of, like the
terminator is probably the bestexample or even data from the
next, uh, the star trek, thenext generation, yeah, um, yeah,
that they do actually kind ofhave that, the human capability,

(29:02):
yeah, and it's obviously youknow.
You can also said will theyeventually have a conscious?
Yeah, and how they will treatus?
I don't have an answer for it,but I can only tell you is, at
this time, they are still justpart of the machine, yeah, or
part of the algorithm, yeah, andwhat can you do to make the

(29:23):
best out of it yeah, yeah, Iagree with you there.

Speaker 1 (29:26):
I think it is a more to me personally.
I think it's of like.
I think there's going to be aleveling out a little bit to
some degree, just based on, likecertain, you know, I think,
saber fighting Are we going tojust do saber fighting with AI?
No, no, I think it's going tobe more of like the.
I think it's going to level outbecause of corporate greed and
money.
You know they're going to gopublic or they're already gone,

(29:55):
or they have not already gonepublic or not.
People not walking out nowbecause they're talking about
going public.
I mean, I'm going to be gettingmy like headlines and stories
confused.
But like open AI is, is is kindof going to be going public
soon and you know the guys whohelped to start that don't want
that.
They wanted it to be an openresource for people.
But the problem also with thatis at the other end.
It's like collectiveintelligence.
When you kind of throw in allthe collective intelligence,

(30:15):
like gosh, we're notcollectively not always that
smart, right, because it's likeyou know, garbage in, garbage
out, we talk about that a lotwithin this space, right, we
know not all data is good data.
We know there's a lot of biaseswithin some of this stuff that's
being fed into the machine.
So just because it has, youknow, because it has input,
doesn't mean that the output isgood right, but I 100% agree.

Speaker 2 (30:38):
So, depending on the data they pull that information
from Exactly that provided youthe answer yes, exactly.

Speaker 1 (30:45):
So for me right now, I think the most critical human
role is, you know, really,responsibility, accountability,
making sure that you know biasand errors, are still something
that we're very much focused on.
I think conversations about,like regulation and
democratization because I reallydo see AI as something that can
help small businesses work, youknow, more effectively, more

(31:07):
efficiently but then you see bigcompanies and corporations
using it to make excuses toreduce and minimize headcount
and things like that becausethey see it as an opportunity.

Speaker 2 (31:16):
That's the saddest part.
That's the one I fear the mostfor the next generation.

Speaker 1 (31:21):
But to me it's going to be like a pendulum, Pam.
I think it's going to be likehow they go off and they
offshore, not to like totally gooff track and then you're like
this is not working and they gotfired people.
Yes, that's kind of myprediction and again, like I
mean, I don't know, I don't wantto be proven wrong in that I
wouldn't mind that pendulum toswing back the other way.

(31:41):
Where it's like the offshorejobs, they're like wait, that
didn't work, we got to bring itback stateside, and they do, so
it might be, yeah, okay, well,let's all go in.
On AI, we're going to be ableto reduce headcount and create
efficiencies and save our bottomline and pay our C-suite more
and our shareholders.
And then, oh crap, no, we'reactually creating marketing
campaigns that have bias anderrors and that aren't effective

(32:03):
.
We need to bring humans back in.
That's kind of my hope, but whoknows, we'll see.

Speaker 2 (32:19):
I guess we'll have to wait and see.
We'll like come back to thisepisode in five years.
It is, it is we are, it's.
It's kind of like a um, ablessing and a curse at the same
time.
It is that we are witness, weliterally just witnessing here
we are, how the ai is going toevolve I think it's absolutely
amazing?

Speaker 1 (32:31):
yeah, it is.
It's really an interesting timeand I like to also just fast
forward in my head and thinkabout that, like in the history
books, what is this time goingto look like?
And right now it feels suchlike madness and crisis.
But somehow fast forwarding inmy head makes it feel a little
less chaotic and be like youknow what.
It was just a time and a placeand an era, and that's, I think,
sometimes why equating it tothat assembly line and moving

(32:54):
towards more machines and thingslike that kind of makes it feel
.
I don't want to try to minimizeit at all, but it gives it
perspective.

Speaker 2 (33:02):
Honestly, amy, it's going to be chaotic, no matter
what.

Speaker 1 (33:05):
Sure it is.

Speaker 2 (33:06):
I don't think that.
You know.
I think it's going to continuebecause it's morphing and
evolving and some people willlike the direction we are going,
but you always find people whodon't like that direction, don't
want to move it and they wantto disrupt it.
So I personally think thatchaos will continue to stay.
I don't think it will ever goaway.

(33:27):
Yeah, because we are humans, wejust love to like.
You know what I disagree withyou?
I ever go away.
Yeah, because we are humans, wejust love to like.
You know what I disagree withyou.

Speaker 1 (33:33):
I see you differently .
Yeah, definitely yeah, you'vegot people that are going to
jump on board and move alongwith it and others who are going
to drag their feet.
Yep, let's dig in a little bitmore to some more areas of
marketing that you cover in yourbook, because you definitely
talk about seo, email marketingas well as social media.
Are there any other areas thatyou think um?
Which areas do you think um hasthe most untapped potential for

(33:57):
ai?

Speaker 2 (33:58):
prompting data analytics talk about that a
little bit really.
So you know, like content, youcan always like okay, write us a
post.
And you can even say, okay,create a demand.
Right, you can give a veryspecific prompt and, just like
you asking the questions,analyze this, right.

(34:18):
So is that analytics part of it?
I think we can explore a wholelot more.
Yes, and analyze this and tellme what's good and bad about it.
That's data analytics.
Or you input certain kind ofdata in that and say, hey, I
actually have this opening ratefor this kind of subject line

(34:46):
I'm just using, kind of take thecopywriting, elaborate a little
bit more.
Kind of take the copywriting,elaborate a little bit more.
And here is 50 subject linesfor the past 50 email campaigns
and each one of them haveaverage of the open rate
associated with it.
And can you analyze this for meand then tell me which one,

(35:10):
which subject line, performbetter?
Yes, and then, of course, thesequencing why is better?
Yep.
Then the next sequence is likeI have this email, I want to
push it out next month.
What, based on all youranalysis, what are your five
proposed subject line?
I love it.

(35:31):
It's that analysis part that weneed to tap into a whole lot
more.
Yeah, that requires all of usto think a little bit
differently.
Right?
So because you're a copywriter,the first thing you say is okay
, email, perfect, I'll write it,I'll write a subject line, or
just like you said, you have AIto write a subject line and you

(35:53):
test it, and then that's thenext step to move on.
But how can we leveraging pastinformation to train AI and see
how that information can beutilized?
And then we have data more datadriven type of insight moving
forward, data-driven type ofinsight moving forward.
I think that is one part I needto do better.

(36:13):
Honestly, I think all of us cando better.
It's that analytics part.

Speaker 1 (36:24):
A hundred percent and surprisingly honestly, pam,
this is where I thought I wouldsee more of it, even though my
background is writing, as manyof you know, who listened to the
podcast historically in pastepisodes, you've probably heard
me share this example.
I was working at an agency.
It was kind of like early daysof social listening and they
were talking about oh, we've gotall this data and again a big
data right, all this data andmarketing.
We're like look at all thiswealth of information that we're

(36:46):
sitting on.
But it's like what?

Speaker 2 (36:47):
are we gonna do?

Speaker 1 (36:47):
about it.
What in the hell are we doingwith it?
And I even wrote an article umback then.
I think it was in 2010.
I think it's like what are wegoing to do about it?
What in the hell are we doingwith it?
And I even wrote an articleback then I think it was in 2010
.
I think it's probably stillliving on my LinkedIn talking
about like the tension and thebalance of like big data and the
creative gut that was in thepost and it was like I love it
because I think data isimportant.
I'm married to an appliedmathematician.
He was like a PhD at the time.

(37:09):
He was at a university and hedoes the creative side and, yeah
, he's the opposite, althoughhe's very creative too.
I will argue he's very creativetoo and he does mathematical
modeling and computer science aswell.
And so in mathematical modeling, it is taking a lot of big data
and it's analyzing.
It's leveraging essentiallymachine learning AI effectively

(37:30):
and modeling, so computing andcreating and shaping and
analyzing.
It's leveraging essentiallymachine learning AI effectively
and modeling, so computing andcreating and shaping and showing
you know, with a ton of data,what might happen within a
clinical research environmentand setting without actually
having to do testing on likeanimals or people.
And so I'm watching at this.
You know company, this agency.
They're like oh, look at us,we've got all this sentiment

(37:52):
analysis and we're going to havea model that we've created to
show what that looks like.
And I knew they were justpulling it out of their asses,
really.
And I went home to him and Iwas like listen, what you're
doing?
We've got all this data butreally, like computing is the
way and I didn't know AI was athing and like, but I knew what

(38:14):
he was doing.
I was like that's, that's howwe analyze like for human brains
.
We can't process all thatinformation.
We can't scour all of that dataand find the nuance or model
right and put it in, visualizethat information in a way that
allows the human eye brain toprocess and go oh, there's the
pattern, that's what I need topay attention to, right, that's
what I need to look for.
And so now that's a lot of whathe's doing.

(38:37):
So you said you came to thedark side now he's on the dark
side.
I'm doing that for an AI companyas well and I think it's just
really awesome, because I again100% agree with you.
I think that's been a bigproblem for marketers is that we
do.
We have a half ton of data andit's fantastic, but it's like
what are you doing with it?
How are you using it?

(38:57):
How are you making customers'lives easier?
How are you solving problems?
How are you really findinginsights and creating
innovations that aren't justshiny objects but actually
making people's lives better,easier, you know, at the end of
the day, versus just adding afeature or a function because
you think it's just going to,you know, be the next big thing

(39:19):
and it's like I don't know, andthat's I agree.
I am very, very, I'm so gladthat was your answer, as you can
tell very excited about dataanalytics and what AI can really
do for that space as well.
For sure, For sure, and I getGen AI is like kind of where
it's all at right now, but Ireally think to me, the next,
the next phase is, is that wherepeople need to be paying

(39:42):
attention.
So if you're not using it inyour data analytics, start doing
it, folks.
All right, can you share alittle bit of an example of
before and after scenario wherea well-crafted prompt
significantly improved amarketing outcome yeah.

Speaker 2 (39:54):
So, uh, this is the way I would look in at the
before and after it's.
Unfortunately, it's more orless kind of like compare human
versus AI to some extent okay.
Like, for example, um, if I thebefore and after using AI, I
always kind of using myself asan example.

(40:17):
So before I use AI, what arethe things I usually do and what
is the outcome of that?
And the other one is do andwhat is the outcome of that, and
the other one is after using AI, what is the outcome of it?
So let's just use the emailmarketing as an example.
Yeah, same thing, right, so,before, before and after.
Before you use AI, you create asubject line, and then then we

(40:38):
use the same process, amy, thatyou talk about.
In terms of that, you areasking AI to actually create a
five subject line, do ananalysis, you run into the
testing to test the subject lineand you come back and have them
do better.
So the way I would see a lot oftime.
You need to have a point ofview or benchmark in terms of
how AI is doing or making animpact on the job that you do,

(41:02):
and that's assuming it's emailmarketing.
So you should have a subjectline that's 100% created by
human, you also should have asubject line 100% created by AI.
Can you do A B testing?
Yeah, oh, I love that.
Yeah, that's to me, it's beforeand after, and then you have
data to support it.
Like you know what, for thisround, human one ai zero.

(41:24):
But for next round might be youknow one and one who knows right
, but I think it's veryimportant, uh-huh, it's very
important that once you areusing ai, but you still need to
demonstrate your value add, yes,like the example I'm sharing
with you the example I'm sharingwith you that give you some
data.
If the AI is performing better,ok, so be it, great.

(41:47):
That's a data point.
But that's assumed that thehuman subject lines perform
better.
That's a data point that youcan, you know, speak loud and
proud, yeah Right.
So that's what I see in termsof you need to kind of quantify
ai's impact as well.
A lot of time we are using itas we are using it.
We just said, okay, they come apretty good post I just posted,

(42:13):
right.
So is it possible you can lookat a couple samples and I have a
point of view which oneperforms better?
If ai performs better, we'llmake a note of that.
You don't have to promote itloud and clear, but if you are
doing better, you know what youshould let people know.
So that's how I see in terms ofbefore and after.

(42:34):
I don't know if that's why youhave in mind, but, um, no,
that's a great example like um.
You know it's a it.
It's not human versus AI race.
Maybe it is to some extent, butyou need to have a point of
view.

Speaker 1 (42:46):
Yeah, no, I love that and I love that you're like
championing and asking people toremember to truly advocate for
themselves, and just keepconstantly reminding folks that
AI is the tool People are stilldoing.
You're still doing the work.
You're still doing the work.
It's like AI is not promptingitself.

Speaker 2 (43:08):
Like dude, when not yet.
No, that's maybe.
I don't know.
I don't know how that happens.
I don't know one day well it'snot now, I don't even know how
that happens.

Speaker 1 (43:15):
That would be creepy that would be absolutely creepy
okay, so your book is, uh,definitely aimed at more of
maybe the well, your book isaimed at various roles in both
sales and marketing.
How do you see AI promptingdifferently, benefiting, say, a
content marketer versus maybe asales or an enablement marketer?
Yeah, or manager, sorry, no,it's totally okay.

Speaker 2 (43:37):
It's totally fine.
Fine, um, it doesn't matterwhat.
When I was writing this, 75plus prompts and for different
marketing roles, because Icategorizing it 12 and sales and
marketing categories, if youwill.
So you have to think in termsof when you do your job, I'm

(43:59):
going to give a generic answerand I will give a specific
answer.
So, when you are doing your job, I'm going to give a generic
answer and I will give aspecific answer.
So, when you are doing your job, it doesn't matter what job
email marketing, event marketing, community managers and even,
you know, salesperson or salesenablement managers there's
always a problem you can ride,like to ask AI, for example, on
the sales enablement.

(44:20):
I need to create a pricing guidefor my sales manager for these
three products and compare withthese three competitive products
.
Can you pull the informationfrom my pricing?
You enter information and alsopull the pricing information
from their website, pricinginformation from their website.

(44:44):
You provide specificinformation and then create a
table that compare uh product a,b, c and d and with the
competitors product c, d and e.
Right, so you can actually do avery specific uh a prompt for
that.
And, by the way, when you saycreate a table, the, the, the
chat, gpt can actually do thatnice and uh.
So that's kind of what I see islook at your own job, the job

(45:07):
that you are doing on a regularbasis, and then you are thinking
, you know, you think about itand say, okay, I am thinking
hard about this specificquestion or the challenges.
Can I just write a prompt andask AI about it?
Yeah, okay, so that's one wayyou should turn around in terms
of how you think that helpful.

(45:27):
So focus on your job, what youdo, and then see if AI can
provide value.
Yep, yep.
Then of course, specific job,like if you are doing a content,
if you are content marketing,if you are a content marketer,
sorry and if you are creatingcontent, of course using AI, and
provide a very specificguidance and create long form
content or short form content.
Yes, that's definitely given,and we've been talking about

(45:51):
those examples plenty in thispodcast.

Speaker 1 (45:54):
Yeah, yeah, I mean, it's just amazing like the
amount of content, planning andstrategy and outlining you can
crank out in such a short amountof time.
Right, you know, it's just it'swonderful and, like I said it,
just when you are a smallbusiness and you've got limited
tools and resources, it's likeah, it's amazing.
And I love this idea of likethe competitor, like the
analysis, the table, the pricing.

(46:16):
I know I've definitely used ittoo for like writing or just
helping me get started onwriting, like those emails for
sales.
Because, sometimes I feel solike forced, even when I'm
trying to write them myself.
Hot tip, here I will go and Iwill find like their bio or any
personal information about them,and I'll put that into the
prompt as well and ask AI tomake sure that it includes some

(46:39):
sort of personal, like kind ofdetailed to them, so that it
really like actually was usingit more for, like press releases
and trying to reach out to thepress about our upcoming
conference, and I really wantedit to speak to again because I'm
like I want to grab theirattention.
Like they report on specificaspects about our community, so
I really want it to tie to whatthey are reporting on and so

(47:01):
it's like making sure that ithits those points.
This is also great for jobseekers too.
We do a job seekers peer groupevery Thursday for Together
Digital members and we weretalking a lot about this.
How much AI is a great tool forjob seekers right now, because
when you need to craft, you knowcover letters and resumes and
every single one has to be veryspecific.

Speaker 2 (47:21):
It has to be tailored and customized.

Speaker 1 (47:23):
Yes, yeah, ai can be such a fantastic way to really
help you kind of get a greatstart on making sure that you're
hitting all the right notes.
You know, again, obviouslyyou've got to kind of do the
work and go through and makesure everything is right there
and accurate.

Speaker 2 (47:38):
Exactly, exactly, but it really does help ahead.
That's what.
Sorry, I apologize to interrupt.
No, you're fine.
Sorry, but you hit the core.
You still have to do that, thatjob, the last 20 miles.
Yeah, even though they hadcreated a draft for you, you're
the one still needs to read itand you have to proofread it you
cannot just take it blindly,and I think that's very

(47:59):
important yeah, you've got toadd the finishing touches and
the color as well, because Ijust I can't again.

Speaker 1 (48:05):
I it's coming from a writer, right, it's especially
when it's coming from me I justfeel like there's just certain
words and I mean I will tell itover and over again.
I'm like stop saying thisspecific word.
Like nobody says yes, I willtell, I'll yell at it, I'll be
like nobody says this word.
You know, and I don't know why,I can't think of any of them
right now, but it'll like.
There's certain words It'lljust say over and over again.

(48:25):
I'm like please stop sayingthat in the digital world, in
the digital landscape, I'm likenobody says that, oh yeah, and
unleash.

Speaker 2 (48:32):
Unleash.
Yes, oh my God.

Speaker 1 (48:47):
Like you asked him power.
Yeah, I 100 agree with youbanning these words from your,
from your vernacular.
Ai, I love it, but yeah, youreally need to kind of make sure
you bring in the languagethat's truly used so it sounds
authentically you.
Yeah, all right, let's talkabout so.
On that note, I think this is agreat segue as well, like what
are some common mistakes thatyou see marketers making when it
comes to crafting AI prompts oreven just leveraging AI in
general.

Speaker 2 (49:05):
It is just too generic.
It's like you cannot say createa marketing plan for me, I'm
not like you know, it's not,it's, that's not going to happen
.
No, so you, you, you, you.
You have to put into yourthoughts in terms of your
prompts, like create a marketingplan for this type of company,

(49:27):
for this type of products.
Our challenges for ourmarketing plans so far are blah,
blah, blah blah, and we've beencreating marketing plan.
You can even upload yourmarketing plan and our target
audience is this, but so far wehave not been able to meet our

(49:49):
kpi, which is the following soyou provide all that information
, so you have to do prep in away.
You have to know your productspretty well.
You have to know stuff right.
So how do you convey thatknowledge of yours into part of

(50:10):
the prompt writing?
So, to brief the AI bot, theycan spit out the information
that you want.
Don't make it generic and alsoput put into the right context.
To me, those two are very, veryimportant.
That means sometimes you justhave to write a bunch and then

(50:31):
check it out and again do thesequencing, like amy indicated.
Yeah, I think the the commonmistake is really, first of all,
too generic and second thing isalso be patient, like I you
know how many times I write aproblem.
Oh my god, this is not what Iwant and I have to walk away.
I was like ai, you are notperforming today.

(50:52):
I'm really disappointed in you.
You know what I'm saying, andthen you have to freaking walk
away, yeah, and so you have tobe patient definitely definitely
well, and I, I, I, as you werespeaking of him, it really just
occurred to me too.

Speaker 1 (51:06):
For those of you that are listening that are non
marketers, I think you have tobe careful, like, do not think
AI will replace your marketers,and I think a really good
analogy is there is a gentlemanI'm not going to remember his
last name right now, gosh and Ifeel bad because I want to give
him some credit so you guys canfollow him on LinkedIn right now
.
His name's Terry and he doesbeautiful food photography with

(51:29):
AI, like complimentary foodphotography with AI, where he
puts together both real lifephotography, sometimes with AI
backgrounds, and AI integration.
And the reason why Terry is sobrilliant at what he does is
because he has been doing foodphotography, lighting, set
design and everything for 30years.

Speaker 2 (51:49):
Yeah, exactly the tribal knowledge, the tribal
knowledge A hundred percent.

Speaker 1 (51:54):
Your marketers know what to ask, they know what
dials to turn, they know what totweak, they know what to ask
for, they know when what chatDPT puts out is wrong.
And so it's like if you aretotally not well-versed in
marketing and you think that youcan just go in and say, give me
a marketing plan, no, like youcan't, like you don't.

(52:16):
What you're going to get out istotal BS and it's not going to
be accurate, it's not going tobe right.
Don't think that AI can replaceyour marketers.
Please, please, please, please,please.
And when you have people in AIusing you, know marketing for
marketing, make sure that theyare marketers themselves.
Because, again, I think that'sthe.
That's the beauty of what Terrydoes is because he's a
photographer first and foremostand he's still very much

(52:39):
champions doing the art that hedoes, but knows now, really
understands AI well and alsostill has that legacy knowledge,
obviously, of photography, andhe couldn't do one without the
other.

Speaker 2 (52:53):
So I just wanted to say that it's also your
expertise, right?
I mean you need to be able tojudge what AI's responses are.
You have to call it out.
It's like oh, this is a BSresponse, yes, or oh, this is
very, very good, 100% that thatkind of judgment call comes from
your expertise.

Speaker 1 (53:12):
Yes, Agreed, agreed, yeah, because I was even looking
at some of his stuff and he hadlike croissants with like the
layers and like crumbs, and I'mlike, oh, and I used to do food
photography for like Conagra andsome other food brands and I
was just, I was just blown away,I, you know, and I've seen
other stuff and I'm like, yeah,no, like that's the lighting is

(53:34):
really wonky Like you can justtell things aren't right.
But you know it's it's hard.
It's hard to prove what's realand what's AI with Terry's work.
All right, courtney, I seeyou've got a question here from
our live listening audience, sothank you, courtney.
She's calling out the fact thatI mentioned earlier that in
some cases, different AI agentscan work collaboratively with

(53:56):
each other.
Can you provide some examplesof that and how these use cases
might be valuable to marketers?
We'll get into this probablymore.
I've got, hopefully, anupcoming guest from Verve, sarah
, who works with them.
There will maybe get more intothis with us too.
And the case that I was sharingin that example they're more of

(54:18):
a tech company.
They're called, I think, crewAI, if I remember correctly, so
you can look them up and they'rea multi-agent platform and they
definitely look at it from likea multidisciplinary role in the
sense of you might have, youknow, a like a C, like a running
a reports type of a thing, likea financial reports person

(54:41):
running something who might thendo a run in a check of um, like
financial reports, then runninga check through.
I'm trying to think of the otheragent that he created.
He also created an agent thatwas like the cmo who maybe ran
marketing reports.
You know, um.
Thank you, kaylee.
Of course she found it reallyquickly and drafted into the

(55:01):
chat.
I love it, you're so awesome.
Um, so you can kind of take alook at there and at those, and
so what they would do from acollaborative standpoint is
actually a cross reference.
So you could basically, umcreate commands and prompts so
that whatever each agent iscreating reports on that, um
that they would then collaboratein the sense of creating an

(55:22):
additional cross-referencereport so that marketing might
feed into the financial reports.
So you wouldn't have your CMOcreate the marketing report and
how everything performed from aKPI standpoint, right, what the
spend was, that would feed intothe financial report.
The financial person wouldn'thave all that information and

(55:42):
data.
So it's more like they're kindof talking to one another.
How that might work for amarketer I don't know exactly
yet.
Like I said, this is like kindof newish territory, but I don't
know, pam, if you've got someexamples too of how other agents
and how maybe you've seen themor used them in the past too
might work for marketers if youhave a multi-agent tool that is
just marketing or for marketers.

Speaker 2 (56:08):
I don't have the multi-agent tools that I'm using
at all and each agent that Iuse tend to perform on its own
and is more task-driven.
But I can totally see that eachagent talks to each other.
So the analogy I would like touse on top of viewers think of
the each agent talk tothemselves like a data flow,

(56:29):
like you have like, for example,you have the data from like
marketing automation tool thatthat data needs to float into
CIM for you to track, kind oflike you know, mql to marketing,
qualified leads to sql, salesqualified lead.
So the way that you need tothink about how agents talk to
each other, think of thoseagents still as a software.

(56:50):
They are all our softwares.
Well, the the technical part ofit in terms of how they talk to
each other, that's going to letthe technical person figure it
out, but you have to think it'sa data flow from one place to
another.
If you think from thatperspective, then it's not
confusing.
It's pretty clear to you.
Yeah, true, software, they justneed to talk to each other.

Speaker 1 (57:08):
I think that's a great example.
Yeah, yeah, I love it.
That's very helpful.
Thank you, I know it's gonna beso.
I think that kind of stuff issuper interesting because I mean
I already like I loveautomation as well.
That could could be like awhole other conversation Also
love it All right, cool.
Well, if anybody else has anyother questions, we've got a few
minutes left.
Looking ahead, Pam, how do youthink AI prompting skills will

(57:32):
impact career advancement andmarketing and sales?

Speaker 2 (57:38):
I think this from a perspective of hard skills and
soft skills.
I think to be able to prompt isa hard skills you need to have.
Everybody should have thatskill set.
Okay, the soft skills on theprompt is like you need to have
a point of view what theprompting can do and cannot do

(57:59):
for you.
Yes, that is going to be up toyou to articulate.
Well, that is a soft skill.
Yep, right, so that to me, isunderstand.
Once you understand and, by theway, the prompting will continue
to evolve and ai might take onmore and more, uh, the stuff
that are off your plate.
So that soft skill ofexplaining what ai can do,

(58:21):
cannot do, will continue toevolve as well, and that having
that point of view will alsoguide your career development.
Absolutely, you're like, oh, myGod, you know what AI is kind
of like in my category right nowterritories.
Right now, maybe I need to lookat my job differently or I need
to change job.
So, from my perspective, is beable to articulate so well, yeah

(58:45):
, in terms of what I can do foryou, it's super critical, I
agree I love it.

Speaker 1 (58:49):
Take it, embrace it, own it, be the thought leader on
it.
I love that.
Yeah, be the one who's like,has a point of view on it.
Yeah, be the educator.
I think maybe you know, pam,like you just did pick it up and
write a book on it.
Damn it.
And Courtney's like.
So helpful, wonderfuldiscussion.
I'm getting Pam's books Awesome.

(59:10):
All right, we're at our our fun, fun time.
We're down to the last minute,so we're going to go through our
power round of questions, whichare fun, our little lightning
round of questions.
So what is one AI tool that youcan't live without?

Speaker 2 (59:23):
One is obviously chat GPT or something called magi.
This, the tool, actually hadcreated the interface that was
like a Gemini copilot, you know,claude and chat GPT, and you
can pick and choose which oneyou want to use Instead of going
to a different platform I likethat one m-a-g-a-i opus clip yep

(59:52):
.
And, for example, I create avideo and I have ai to cut a
different shorts and I kind oflike that.
Yeah, it's fantastic.
Yeah, I'm not always successful.
You still have to you stillhave to do the work
post-production yeah, I agree,but opus is amazing.

Speaker 1 (01:00:00):
I 100 agree, biggest ai failure you've experienced or
witnessed my own book.

Speaker 2 (01:00:08):
I actually do not want to write this book.
I want ai to take all thecredit.
I want to say created by ai.
Oh, that's so funny.
So I actually hired developerand worked with me to write not
just the prompts but code.
I have this person uh input andthe writer code to actually
read my blog post library andalso read all the videos I have

(01:00:32):
created, so to understand mytone and manner.
And I also created a table ofcontent, detailed table contents
with a subchapter and also thedescription for each chapter.
So so I got the tone and mannerdown, I got the skeleton of the
outline down and I tried toprovide as much information as
possible.
It failed miserably.

(01:00:52):
How dare you, ai, how dare you?
I failed and it failedmiserably.
And the thing is, when theywrite the 20,000 words and you
will understand this everysingle sentence sounds
beautiful's, very flowery, butwhen you read it carefully,
there's no substance underneathit, none uh-huh.

(01:01:13):
And I was like god damn it, Ihave to write a book now.
This is not acceptable, ai.
So here I am.
I ended up writing the wholebook.
That's hilarious.
If you actually do a certainparagraph, like you have, ai
rewrite certain paragraph.
They do a pretty good job, butif you are looking for AI to run

(01:01:33):
just like from page one to page100, no, not there yet Good to
know.
Oh my gosh, I love that so muchyou know what, Maybe you know
what, Amy, you might have abetter success than me.
I was.
I feel miserably.
I was so sad, I was crying.

Speaker 1 (01:01:49):
Well, you know what, pam?
It's okay.
That's how we learn, right?
That's how we grow, and I lovethat you're willing to share
that.
That's what it's all about,because Nobody got to success
without screwing up at somepoint.
This was so much fun.
All right, we're just past time.
So, folks, you know if you'vegot, if you've got questions if

(01:02:11):
you want to reach out to Pam.
We will include all of the waysyou can follow her, learn more
about her website.
Her books will be in the shownotes live listeners those are
also in the chat, so make sureyou grab those before we close
out here in a second.
Pam, thank you so much.
I knew this would be a blast,so it was wonderful to bring you
in and introduce you to ouramazing listeners and our
Together Digital community.
Thank you so much for all theawesome work you're doing.
This is a blast Thank you somuch for having me.

(01:02:32):
I mean wonderful Anytime, Allright, everyone.
Well, thank you for joining uson this Friday.
Hope you all are staying safeand enjoying the rest of your
Friday and we'll see you allnext week.
Until then, keep asking, keepgiving and keep growing.
See you all soon.
Take care.
Bye-bye.

Speaker 2 (01:02:58):
Produced by Heartcast Media.