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Welcome to "Visionary Voices" the podcast where we dive into the minds of business owners, founders, executives, and everyone in between.
Each episode brings you face-to-face with the leading lights of industry and innovation.
Join us as we uncover the stories behind the success and the lessons learned along the way.
Whether you're climbing the corporate ladder or just starting your business journey, these are the conversations you need to hear - packed with visionary voices and insights.
Let's begin.
So Craig, thank you so much for joining me on today's episode of Visionary Voices.
Can you give us a top level view of what it is that you do right now and your journey so
far?
Absolutely.
First of all, thanks for having me.
I've enjoyed our conversations up to today and I'm sure today will be lot of fun as well.
So what I'm doing today is an advisor and a consultant to different companies, companies
across verticals.
But I do like to kind of give the background because I've always felt when working with
people, once you know little bit about their background, you know what they can bring to
the table.
But also I think you get to know kind of their lessons learned.
And I know when you and I talked early on,
You know, we talked about this being an audience that might be quite a few entrepreneurial
types.
And then they're going to want to know what it took to build companies in the past.
And I have been able to be part of four different startups in a row, actually.
And with each one of these startups, it's like a garage band.
They're never overnight.
You build it, you build it, you build it, you go test it in the market.
And then five years later, you have a hit.
So that's the first thing is set expectations is my background is building companies like
mission critical software software company back in the day of shipping software.
So I just dated myself a company called NetIQ, which was a company that did systems
management tools.
then one, believe it or not, over 20 years ago, I saw for as a service company.
So if you could believe, you know, we had shipped software for a number of years and built
companies.
So we understood.
the complexities of that.
So when I came across Salesforce.com, I'll give them a shout out here, in 2002, myself and
a couple of founders thought that's just a better way to go.
So we too kind of joined into the SaaS revolution, if you want to say it like that.
So we've had a chance to build a number of companies and some of those companies as we get
into it, I'll make sure I reference, but we were fortunate.
A couple of those companies went public and
One was bought by a private company, that was the SaaS company.
But with each one of those, for the entrepreneurs that are out there, none of them
happened overnight.
It did take a whole lot of energy.
I will say this though, AI expedites things.
It's kind of a lead into some other conversations here.
Yeah, awesome.
mean, quite a journey, right?
You're very successful in the entrepreneurial world.
So I'd love to zoom in a little bit more with those companies that you said, you you went
public with.
So, I mean, what was that experience like?
Because as an entrepreneur, right, we always dream of, you know, growing up a business,
you know, raising that capital and then you go and go in public and all these different
things and you managed to get there.
So what was that experience like for you?
Well, during the garage band years, right, when we're back, you know, building, building,
building, beginning to sell it, you know, one of the early thoughts we had was why not
begin to do win-loss reports?
And this is early on, this is before we were, you know, raising capital.
And the spirit of the win-loss report was to better understand what it is the consumer not
just was willing to buy, you know, you can get people to buy stuff, especially with
really, really good sellers, but to get them to use stuff, that's something different.
And so we spent early days in these companies, building them before raising money, getting
a sense for how clients were going to use the technology, and then ultimately see and kind
of reach the dream of value realization.
And value realization is a big, big deal when you see the work that companies like Genius
Drive, Tom Pasello, and I want to talk about some of these people going through here
because with each of these journeys, it was a network, right?
You kind of have your loose network of friends and family, if you will.
that you go to market with.
so working with people that knew ROI, that understood great ways of marketing was
instrumental to doing everything from angel rounds, today a safe round is pretty popular
way of doing it, the series ABC.
But then also the ultimate journey to go public where you actually raise money to go
public.
And so what does that mean?
You're spending a lot of time with investors explaining
how in this case here before you go public, you're gonna repeat success.
And for anybody who has ever built anything, starting off with maybe a bicycle repair shop
out of your garage, repeating success, not easy.
And then repeating it in a way that's profitable, even harder.
We used to like to say, it's easy when you're flooded with capital and it's all about
market share, but then all of sudden the CFO comes down the hall.
And trust me, if you want to go public, the CFO is going to spend a lot of time with you.
And the other thing you find is that you transition away from talking to clients every
day, because that is your CFO, right?
The client is funding your company.
And then the bank does, or the investor does.
But ultimately, you know, with a public IPO, your investors do, so you're spending as much
time with them as you are with your clients.
So just know it doesn't ever get easier.
And be careful for what you ask for.
That's an old saying, right?
Yeah, that's what you wish for.
put more time and effort in front of you.
But it's super exciting too.
I don't want ever say that, sure it might be more work, but to be able to see a company
grow is fantastic.
No, no, amazing, amazing.
And how did you deal with, I guess, the team growing as well, because obviously your
team's growing exponentially during this period of getting capital in, you know, get going
public and everything.
So how did you deal with that yourself?
And what challenges or solutions did you implement to help that side of the business?
Yeah, and my role within a couple of those firms, again, very fortunate to go public, was
in operations and enablement.
And then just so happened to have the engineering team that did the deployments.
So I was customer facing.
So when you think about that, what does that mean?
So you're enabling the success of your messaging, your ultimate selling, your deployments.
So from an operational standpoint, the name of the game was
identifying use cases that you absolutely had to have to make things right.
Now I'm being broad here, but when you're sitting in front of a group of investors and
their question is, all right, you went from the founder and a couple people selling to
five people selling, that probably wasn't so hard.
It just took time, right?
But going from five to 50 wasn't as easy.
But the idea of going from 50 to 500 from a couple of partners, probably part of your
network,
to hundreds if not thousands of partners.
If you can tackle that issue, basically outline a couple of use cases.
When I say couple, maybe five to 10 go to market use cases.
If you can get those right, this is not a technology discussion I'm entering into here.
If you can get the disciplines right, everything from what type of hiring you need to do.
In other words, the profile of the person that's gonna be successful in different roles to
how you're gonna onboard them.
how you're going to enable their success to ultimately how you're to enable the success of
the client.
know, five to 10 use cases, it's all discipline, it's processes.
And it's not just the, you know, selling cycle or selling process here, your
understanding.
It's understanding what it takes for people coming into your organization.
Again, imagine going from five sellers.
They're needy, 50 sellers.
They're even needier because they're everywhere, you know, in the country, maybe the world
now, but the 500.
Yeah.
a lot of discipline behind that, not just throwing technology at
Hmm.
So I think my biggest takeaway from that is building up those repeatable actions.
And so therefore, you can keep building it up really, is essentially what you need to be
doing if you're at that stage.
You know, the repeatable actions, those SOPs and everything that you need to make it
consistent, right?
Because as you said, you know, when it's just five of you there, from your network, you
managed to bring them in great that that's fine.
But as you said, right, going from five to 50 to 500 is leaps and bounds in terms of the
processes that you need to have to get to that point.
Yeah, and don't be afraid to get into the field.
We've done different things over the years to make sure that our enablement operations
developers are actually with us.
So go on a sales call or 50.
Go on a webinar or in this case here a one-on-one web conference call or 50.
And I'm only half kidding, by the way, because the more you go on them, you might get
hooked.
Now, some would say, don't I have time for that?
My response is you don't have time.
Or I should say, you can't afford not to do that.
Because the more you're spending in front of clients, the more objections you're hearing
firsthand, the more market input you're hearing as they're trying to understand what it is
you do and then also how to deploy your stuff, the more focused you become.
You might build a better product.
I think inflection points are found in the field.
Andy Grove wrote about that years ago, CEO of Intel, that ask sales, they'll tell you.
Because they're in front of clients, and they know what sells, and they know what
ultimately drives success.
So find out those inflection points, but don't be afraid to get into the game.
If you do an event down in Orlando or wherever, there's great booths that everybody likes
to do them.
But do them.
We brought some engineers to one of our events.
And after a couple of days, their response was, all right, that was a lot harder than I
thought.
But secondarily, I heard things that I've never heard before.
And I'm like, well, that's interesting because I hear something new every week too.
Whether it be from an analyst, for a buyer, from an investor, you kind of get the point,
right?
You just have to get in front of people with test these ideas and hear it firsthand.
Hmm.
Yes.
Speak to your customer essentially.
And I think that's something, especially in the early days when I was getting into the
business world is I would always build what I thought the customer would want without
actually speaking to the customer.
And then it got to a point I would launch a product or launch the service and I speak to
the customer finally.
And then I don't actually need the thing that I've built out for them.
And that could have all been avoided if I just spoke to them in the first place and got
that feedback loop, you know, set in stone really.
And so yeah, I completely agree, right?
You need to do.
let's say the unscalable things, right, which is speaking to these customers really
understanding because ultimately, that's going to help them build the processes and the
next steps for the company as a whole.
So yeah, I think I think that's really key operation that people need to start
implementing into their companies for sure.
And then moving forward, I know you had one of the companies which was acquired as well.
So talk to me about that process.
How did that differ from I guess, going public and everything?
And what challenges or advice do you have for people who want to get to that stage of
exiting that company and what does that look like on the real side?
Yeah, I mean, when you're building a company, you're always thinking about what's next.
Always be raising capital.
Some of these things have been said a million times, right?
Always be raising capital.
But also, always be talking to partners and working with partners.
Because you may find, you know, when we're building a SaaS company in 2003, and we're
trying to build out our network, there wasn't a lot of people to talk to.
You know, they were still trying to put a label on SaaS.
In fact, it wasn't called SaaS at that point.
And so at our first Dreamforce, suddenly we had 60 or so vendors.
You could actually meet all the vendors in a day or two at that point, Dreamforce One.
But at Dreamforce One, we used that opportunity to get an understanding of a company
called Eloqua.
Maybe you've heard of them, right?
Marketo wasn't on the scenes yet.
Eloqua did demand generation.
We did sales enablement.
Salesforce did CRM.
you know, talk to the people behind those companies, then talk to those that cleaned up
the data, the serious decisions of the world who, you know, had this demand gen waterfall,
right?
In other words, think about the disciplines, think about the technology, get together with
these people in those early days, because they're going to be your go-to-market partners.
And I say that because the exact same, I'm having flashbacks, that the exact same thing is
happening today with AI.
Find others that are like you.
You'll know it from a mile away because they'll say, why would you ever ship software?
Or why would you not use AI to begin your day?
So now we're back.
We're back partnering with companies that I don't want to say they get it because I think
more people are getting AI faster than SAS.
But there's those that are really innovative right now that are completely rethinking.
You and I talked in how you do podcasting.
You completely have changed.
what used to be a manual then semi-automated process.
And I say that because when you went through it with me, I kind of knew you got it.
You've done the homework.
were there a lot of webinars on this topic about a year two ago?
The answer to that.
So I think early on before we ended up selling, and that company was called Ice and Terra.
And by the way, there's always something behind the name.
I always ask a founder, what in the world were you guys thinking of?
Ice and Terra stood for intelligence center for a new era.
And that was short for a new era of marketing and selling because we thought, you know,
and this is now well over decade ago, that going to market meant getting materials in
front of your selling team, your partner team and your client team faster and
personalized.
You know, I used to tell the story of the sales rep I used to sell with many years ago.
where he would stop off on the way to the call and print off the brochure.
And I'm thinking, well, what happened to the corporate brochure?
And he goes, well, that one doesn't sell.
He had his own brochure.
And I said, all right, this is all wrong.
You can't spend your energy building brochures.
He goes, well, I can, actually, because I got a vertical today and a persona I'm selling
to.
And I'm like, all right, you really get this.
So tell me more.
that, born out of that, was Ice and Terra.
And so the intelligence center concept was salespeople every day, know, the people that
you pay to really know your clients are in the best spot to take your messaging and make
it relevant.
You know, it only made sense, right?
My Kinko's example, now I am dating myself, was classic because I went back to corporate
and said, look, if you don't think they're doing this, they are.
It's kind like today.
If you don't think they're using AI, well, think again.
I think most people know, right, they're using AI, but to the extent in which, may not
know.
But back to this company, we had to prove, you know, not just that we could add clients
every quarter, we also had to prove we were profitable to put ourselves in a position in
where, you know, public companies are very different in which they buy.
Maybe you're a very strategic buy, in which case you don't have to be profitable, but
that's not typically the case.
At least I didn't find that to be the case.
They wanted to know that within a couple of years, you were going to pay for yourself, if
you understand what I'm saying.
right, that the acquisition was going to pay for itself.
So you had to have great clients that stayed with you.
You had to have a product that was adapted based on the latest market demand.
You had to have a partner team that went to market with you.
You know, there was only so many Salesforce.coms back then.
They had, think, a Series A round about $90 million, which was a lot back then.
Well, look at today.
There's a little over a trillion dollars being poured into AI.
So there wasn't a whole lot of money.
So we need to do it together, we felt.
I think today, the same thing holds true because the reach of AI is so broad, the pie is
pretty big.
So back to promoting this company to be sold, at a certain point I found a company, a
company called Caledas Software that said, look, we're gonna scale this company and we're
gonna actually acquire an intelligence center, sales enablement, we're gonna acquire a
learning company.
that we're going to acquire a CPQ kind of company and we're going to put that together as
a more holistic solution.
And the idea worked.
So it was a strategic.
Again, you have to have everything from your product to your financials to be clean.
That that's back to the garage band.
You got to do a lot of practice.
But I think what was interesting about that one was just shortly after being bought, we
were doing bigger deals.
And the reason being is that, you know, as a small company yourself,
you know, the mid to big size companies are going to ask questions about the size of your
organization, your financials, know, great terms like runway, how long do have to live?
You know, some of these things where you're scratching your head and you're saying, all
right, let me, you know, take a look at that number.
All right, it's 18 months.
Well, you know, they're going to say 18 months.
So you could be gone in two years.
So those are some of the tough questions I think, you know, entrepreneurs have to kind of
look within and say, how do we get more and more clients?
to ensure we have a runway that is never gonna end.
And I'm not gonna be naive, that it is gonna end if you don't have a market that isn't
rich.
And we did, selling SaaS well over a decade ago was a target rich market.
Well today it's a different set of questions, isn't it?
Different set of problems.
So it always changes.
Definitely, definitely.
What's your take on or your opinion on bootstrapping versus raising capital in today's
environment?
What's your take on that?
think the first take is that I don't know that you have a choice.
I think you have to bootstrap it.
I mean, if you don't have 20 logos and you don't start your venture pitch with that slide
with the 20 logos, you know, we used to use the 20 logo slide.
It's kind of like looking at a NASCAR car in the runway or the drag strip, right?
It's got all the stickers on it.
You know, in fact, use that idea.
We use that once a car and we put all the logos on the side.
The idea was that
If you could go around those logos for a few moments and then just ask the investors, pick
a logo, and they pick a logo of a client of yours, and then you'd speak to it.
How did you find them?
How did you sell to them?
Who bought within that company?
And then ultimately, and this is the biggest, I think, of all SaaS questions, not just who
bought, but how did you figure out how to expand?
If there's something we learned from the early SaaS partner of ours was land and expand
was the name of the game.
you know, skip the 12 month selling cycle.
Why not?
You know, have quick wins that you land, may not be profitable, get to expand.
But I think if you're raising capital, that's it.
know, put that slide up with the logos, with or without the car, by the way.
We did that because somebody asked for it.
And so we had this car with all the logos on it.
But I think it was an interesting point that that's what you're using to promote and
that's what's paying your way.
And I think if I look back at some of those logos, we were able to win some pretty
strategic clients because they knew full well we were, in a sense, like an R &D lab.
In other words, they'd come to us with a big idea, and we wouldn't say, yeah, we'll get
back to you in two years.
We would do it in two weeks.
Not easy to manage.
Drives your developers crazy.
If they're listening today, I'm sure they'd say, yeah, that's why his approach doesn't
work.
But it did work because if you pick clients that you know there's more of, and I'll give
you an example.
We had an early on client that did channel selling.
So we had to enable not just their direct group, but their channel group.
And we really didn't have a way of satisfying that need.
So we took a look at the opportunity.
We did a three year deal.
It was the largest deal in our company's history.
But what we built,
was basically a rolled base approach to enabling the partner success.
So that the partner in France that was Redwashed, we called it because that was their logo
and their theme was red, would get their content in French.
So we did it.
And the engineering that went behind that, we turned around and sold some of the biggest
companies in America at the time, which said, yeah, we can enable our direct group.
and then as a byproduct or indirect group.
So suddenly now our value proposition was not just the direct team.
So examples like that where pay attention to a couple of those because you may not have
to, right?
Going back to bootstrapping, you might not have to.
Go raise capital until you're ready to scale.
And there's a big difference between raising it to survive and raising it to scale.
And then you're smiling so you probably know exactly what I mean.
You know, and can you get there is that question.
But yeah, find a client that may be, you know, a 500, maybe a billion dollar client and
say, you know what, you know, we're going to work with you every week and we're going to
satisfy needs that nobody in the market can't.
Maybe it's verticalizing it.
In this case, it was, you know, enabling a different group.
But that same team and that same approach they took go to market.
We found 20 other companies like them after that.
So.
Yeah.
have to them earlier because we didn't have the ability.
But I think also it's not just we didn't have the functionality, we didn't have the
discipline.
We learned channel enablement very rapidly.
And then we were able to win some other clients that we couldn't have just the year
before.
Yeah, very interesting.
Like actually, if you have one of those huge clients, which if you signed, it will open up
the doors to many is tailoring some additional service or the service around what they
actually need and want.
Cause as you said, right, if you can unlock it, unlock the value for that huge client,
then naturally that's going to unlock value for more potential clients, just like them,
which you can just catapult the business up.
I think that's a really cool way of playing that side of the client acquisition piece and
building other services.
And maybe even using it as an example as you're raising money to say, look, with capital,
we can accelerate this kind of work and go after companies like this and then be able to
have that conversation.
I love those conversations with the CFO.
And I don't mean that at all, by the way.
And so because you're explaining to them how you're going to enable sales, channel sales.
Well, they've never channel sold, let's say.
Now I'm going to give you the opposite of that story.
That was the upside.
I'm going to give you the downside.
But be very sure that the things that you're building for one-off kind of opportunities is
scalable.
In other words, somebody else would buy it.
Because I have heard stories, and I have had instances where I'm thinking to myself, boy,
if we build this, it's a multi-tenant app, first of all.
So it's kind of all for one, one for all.
That's the SaaS world.
But you can always customize it.
But you can build for certain clients that will derail you from your ultimate customer
base of many.
It is one of many kind of a proposition SaaS.
But I remember one client in particular where I just had to say, we're not going to do
that anymore.
And then we ended up splitting off the product.
They wanted us to do portals.
So we came up with this lightweight portal product.
Well, that distracted us from our enterprise deals.
And to share more about the story, we even called it Portals for Mortals.
We thought it was kind of a clever way of repackaging the product, but it distracted us.
Yeah.
And a company would say, well, we don't want the portals from Ordles Park, but we want the
Enterprise Park.
So just know that there are clients that can take you down a road.
Be careful, right?
Because every one of these roads, especially if you have an MSA agreement in place, can
take you to somewhere you don't want to be.
And so just make sure you know what you're agreeing to.
The other fact, and maybe we can jump to this at some point, is form a customer advisory
board if you're building a company.
as early as he can.
So what does that customer advisory board, what's that role within this piece?
Yeah, you know, it's referred to as a cab.
I think many companies, you know, have kind of caught on to this idea of the years.
you know, we use the cab as a sounding board.
So, you know, instead of a developer coming to me with an idea or me going to developer
with an idea, you know, we would go to the customer advisory board.
And these were people that when they signed up to use our subscription service, that was
part of the agreement.
You know, we're going to give you a discount, but you're going to sit on a conference call
with us once a month.
You
by the way, most of want to do that.
And so what you're doing is seven to 10 clients, let's say, pick clients of different
sizes, different verticals, and let each one of them have a voice.
They're not going to define the roadmap.
They're going to help you shape it.
My classic question at the beginning of the cab was, all right, we're considering these
five things in the next five months.
So would you buy it?
And then of course they'd want it for free and you because they're on the cow and most
often case they would but it's really a group where you're giving them a sense for what it
is you're about to build.
You know there is an agreement in place right to protect you know you're not a public
company so you've got some latitude there.
You don't have to have you know long disclosure slides that you got to put in front of
them but you really give them a chance to be with you.
So they do two things they're a sounding board for the idea and they're also the first
beta.
tester.
So you turn the feature on, you know, and you don't turn it on for all you turn it on just
for them.
And you really work with the cab.
And then finally, they're your best go to market client, you know, they're the ones that
are in your press releases.
They're the ones you bring along to a webinar where you have to have a client present,
right to a thought leader discussion where you have to have a client present, you know,
they become part of your go to market.
That's very cool.
I've never heard of that being within a company, but it makes so much sense.
And it's quite interesting because there's a few key clients that I have within my
business, which ultimately have become that customer advisory board really as well,
because whenever I'm looking to roll out a new thing or I have some ideas, I'll speak to
them first because I'd love to get their input in it, see if that's something, again,
would they actually need these features or am I just thinking of features that I think
they'll need without actually, you know.
using them as a way to test the system that I want to build out or the next feature.
So I think that's a really cool thing that people can just implement into their business
with their clients that they already have.
Pick those clients, as you said, create a spectrum of different clients, but then use them
to really bounce off of and see if the next movie you're to make makes a lot of sense.
So I think that's really cool.
And then guess moving forward a little bit to the AI piece now, because I know you're in
the tech scene back in the 2000s and everything and now back.
with AI, you're coming back into it.
So what are you seeing within the market and why are you looking to get back into the tech
world, especially within AI itself?
Yeah, when I saw AI a while back and this idea that you can actually interact with it,
there's always that hit song, right?
And that's Chat GPT.
That's the hit.
Suddenly I can interact with this thing.
So this was a while ago.
mean, it was at least about a year and a half ago.
And that seems like a while ago with the AI world.
And I was leading up sales for a group.
And what we were looking at was a market, a new market that we wanted to specialize in.
So we were using it.
to understand the market, the potential.
And so we kept interacting.
When I say we, a small team of us, kept interacting before we did our messaging.
So I was leading sales, doing sales, doing events, doing webinars.
And I'm thinking to myself, this is kind of like this discussion I used to have with
agencies and clients.
Now I'm having it with this AI model.
So then I started digging in.
So I mean, you had to see early on.
the inevitable nature of this thing being your sounding board.
So I'm not saying you'd eliminate the cab.
I'm not saying eliminate the sales calls because I'm something every day.
But then about a year ago, I began to dig in on what if you were to take the ideas.
So you and I talked about the use cases, right?
Everything from hiring better to onboarding better to selling better and so on.
So what if you took those use cases and you train the AI model on it?
And then you started using the AI, and this is kind of the beauty of it.
We used to do enablement.
We probably did sales enablement deployments at well over 200 clients that we had over the
years.
And in some of these clients, know, CDW, Motorola, some big brand names, some you've never
heard of at the time, Omniture in their early days.
And I remember each and every one of them saying, you know, the same thing.
How do we do this at scale?
You know, we build websites.
Now you're asking us to do playbooks.
We don't have enough time to keep our website current.
And we used to do the slide deck for the pitch.
And now you're asking us to do leading questions.
And then who's this Neil Rackham and spin thing?
What in the world is that?
This is product managers now.
Well, then they learn the I and spin, and they go, So if we can solve the I, people will
buy.
So I give that as an example because that work had to be done by individuals.
They created the S question situation, the P question for problems.
clients would have for that vertical, for that size company.
The infamous implication question, which determined as to whether not that was a
forecastable deal, as we used to say.
If they have no eyes and they just believe they need it, then good luck selling.
You might be really, really good and you could sell them anyway, but you have to have an
impact to the business.
But to create those questions took time.
To learn those questions took time.
What if you had a sales call in about 20 minutes?
into a vertical and this is now flash forward to my company today.
I talked to a HVAC construction company in Massachusetts.
What's my first HVAC discussion?
So I have no idea, right?
And this is a real example because I started doing some research around what they did and
all the regulations they have and how they do business with clients.
And let's say that on the call, I wanted to find an entry point
for AI.
Well, the entry point ended up being to scale sales in 2025, they're going to be hiring
estimators.
And these estimators have to understand that business.
Because you've got a number that you win the bid on, and then you have a number that you
deliver on.
Right?
So in other words, your bid versus your actuals.
So, you know, the discussion on that first call was, why don't we do the job description?
Why don't we take a look at the candidates in this market?
Why don't we look at the pay scales in this market?
Now let's take a look at what if we were to bring in just the people we hired, the five
resumes, and the 75 we didn't hire, all those resumes, and begin to learn who we hired,
why we hired them.
So it really is fascinating.
This actually makes all this fun again, if you want to know the truth, because it used to
be hard work to figure this stuff out.
Now you can figure out things literally in an afternoon where you had in the past
scheduled calls with three people in your network to understand something, a new vertical.
But I use that example because now you want to socialize those hires.
Well, your job description, you're posted.
You can do that in about 20 minutes, probably less.
The job description itself should have something about why your company's been around 30
years.
Well, you can scrape that from the website.
So yeah, mean, this takes some of those disciplines we've talked about up until now in
this call and it makes them a lot easier.
And it lets you go after markets.
You know, when you go after HVAC in Massachusetts, but then you pivot and you go after,
you know, I'm working with company now that does wealth management, completely different,
you know, and then you pivot and you talk to a new SaaS company that just did a capital
raise of 200 million and they're being told,
scale not just through people the way we used to but through people and AI innovation.
know, prove to us you can scale and do the things that we've been talking about in the
last what 20-30 minutes here.
Prove you can do those things at scale without having to hire you know all these people
and that's kind of the older school thinking.
So the model's changed.
It's changed literally overnight.
You know that because you
kind of are in the middle of it and you're doing it yourself.
Yeah, yeah, definitely.
And I guess with businesses that you're speaking with, you know, where do they fit within
the, guess, their knowledge of AI, right?
Because I think, you know, we spoke before and some people you speak to, they're using
chat GPT all the time now and that they're really, you know, start to understand it.
But then to be honest, a majority of people have used it a handful of times.
Whenever it's been used, it's blown their minds, but it's not been adopted into their way
of life of dealing with work and projects and everything.
So where do you think a lot of companies fit within that scale?
Yeah, well, it's kind of back to where we were with SAS early days.
Tell me again how this is going to be delivered.
Tell me again what sales enablement stands for.
And by the way, it's not a word.
And it's interesting because now you flash forward.
I was talking to somebody in the commercial real estate market about a month ago.
And I've learned more about that market now using AI.
And then when I come into a conversation with somebody that hasn't been using it for the
last year plus like you and I have, when I come to that conversation, what I'm finding is
that
you really have to just show it to them.
In other words, when I say techie, I am not technical.
So, create an AI agent.
Use Chad's cheap BT, use the team edition so you're not training the LLMs, you're
basically just creating something.
And for that very first discussion, it doesn't take much effort once you've done it once.
Have an AI agent that takes a look at their market and gives them a sense for their
competition.
gives them a sense for their strength in the market.
You can do that with an AI agent in a very rapid form.
But I'm now starting my discussions showing them the art of the possible first.
And then pivoting and saying, so let's say you're going to scale, whether you're hiring
estimators or marketeers or whatever, certainly sales, if you're scaling your direct sales
model, show them how you can create a job description, a job post.
blog to maybe attract them, create what makes you better than the competition, show them
some of those things.
One of the investors I was talking to recently, I showed him an agent that goes out every
Monday and picks up what the 10 tech titans, they call them the magnificent seven, I add
three to that.
Some of my favorites like Salesforce and Oracle and some of the others, Microsoft,
actually they were part of the seven.
have an agent that goes out and finds out not just how much they're investing, but what
they're investing in, and rerun it every Monday.
Because that number has gone like this.
It hasn't gone like this.
It's a little over a trillion dollar spend that they're going to make between 24 and 2028.
So huge spending.
So coming back to your question, the maturity level is low.
So showing them the art of the possible.
the beginning and then coming back and saying, what if we were to take just this example
and introduced it to your team?
Pick an internal use case, something that there's no risk, right?
Because the immediate is going to be, you know, are we going to be legally liable for
using this thing?
Right?
Especially like wealth management or investments.
You know, I am talking to one of the larger investment companies and they say, we can't
even recommend the stocks that you showed me there.
You know, they're just too risky.
Hmm.
But you can't ignore them, can you?
And in some of these private companies, you shouldn't ignore them because they're chasing
a market.
If you believe the market's 17 trillion by 2030, let's say it's just one.
It's still huge.
So the question becomes is, which ones are investing and how rapidly, and then what are
they doing with it?
So what I'm finding is that I started building agents and it's one of those things where
you got
You get kind of addicted to it, so you got to be careful.
You're building these agents for umpteen different things, but do it in a way that you're
starting to collect data, data sets, in a way that's different.
You know, we used to think of everything as relational databases, highly structured,
taxonomy made a difference.
You know, people hated to hear that you had to tag all the stuff.
You don't have to do that now.
And when you get into, you know, new acronyms like reg and data sets,
Suddenly now you're finding, I can drop all these resumes, my example earlier, the five
you hired and the 75 you didn't, and then in a year I can analyze which ones worked and
didn't.
And I didn't have to have some, you know, huge project with a relational database.
I'm not saying you don't want to get there with a smarter way like with a reg, but in the
short term, you know, load up the knowledge and begin to analyze it.
I think it's examples, and this is a long answer.
because I'm right in the throes of understanding how to do this, to be honest.
Everyone is the same.
If you get to the end of the 30 minute discussion, they say their head's spinning, you
have to stop.
Because you have to stop and say, what if we just take two examples in a protected area
where all of that information is not being shared with the LLMs?
We show you how to use multiple LLMs, the best one for the use case.
What if we show that?
and we start with your executive team first.
And especially when the executive team just came back from a conference that said you have
to start AI, so there's that level of excitement, but they're not sure where.
Well, show them a couple examples.
Show them how you're doing analysis without any kind of sophisticated project.
And you're doing it based on data sets that you have now.
And we did a survey on where data is today.
It's more distributed than ever.
So in other words, 20 years of trying to consolidate and we're no better off.
Yeah.
As you were saying, right, the bar to entry with AI, it's so low, right?
And so pretty any business can go in and start utilizing these tools to some degree, as
you said, right, you don't need to build out these fancy data structures or anything
initially, right?
Just to get started, to do the research, to do some of those tasks.
As you said, right, go to areas within the business, which are really low risk, where if
you're to start using it and see what it does, right.
But it's going to be interesting over time.
And we spoke about this on one of our previous calls is companies adopting this technology
into their companies.
And as you rightly said, if it's getting sent to an LLM, which is relatively public,
right?
Or the company can see all that information and everything, then they're probably going to
want to bring that infrastructure in house or protect that infrastructure in some way,
shape or form.
So it's going to be very interesting to see how the marketplace shapes over time.
And it might bring it back to, you know, instead of
It went from people having servers within their own building to then moving it to, you
know, remote servers, know, within SaaS companies, say, and then moving it probably back
into their own organization and own building again, having their own AI, LLMs or any,
whatever that looks like, to run their own sophisticated model, which they want to protect
everything.
Because as you said, there's certain industries, which they might have just a lot of
pushback right now to, to adopt the technology because there's not that protection in
place.
Well, we'll know that the big enterprises, and this is a call out to the SMBs now, know
that the big enterprise is already doing this, right?
They're building it.
They can afford to build it.
They can build it on their own for that matter.
Who knows?
They might do the LLM, you know, but that said, the beauty of the SMBs, you don't have to.
You just have to, I call it foundational AI.
Let's say you did foundational AI, what's this protected workspace where you started to do
these quick wins.
And let's say you did one for hiring, right?
You did one in this case here for social, right?
Those are two obvious ones you can start doing tomorrow.
But then let's say you pivot because you want to win over the executive team and you do
one for legal.
I haven't talked about legal yet, but who hasn't gone through a red line contract and then
had a lawyer spend 30 minutes, 60 minutes with you, and you're still confused?
Yeah.
And you're thinking to yourself, all right, even with an expert, I'm still confused.
I don't know what I'm signing.
Well, load up three different mutual NDAs.
being asked to sign and compare them and ask which ones have gaps, which ones have
concerns.
And it'll start speaking to you.
So the use cases are endless.
But start doing these internally.
You can get going.
And I don't work for OpenAI, but you can create this teamwork area.
where you can, for $60 for a couple of users, two in particular, $60 have access to the
latest LLM, the ability to create agents, to create now tasks, to have embedded search, to
create videos.
So go create your wins.
And you might, in three to six months, have those be your MVPs.
Those are your prototypes.
That's where your company was learning how to better organize the data, which isn't hard
anymore.
to better understand the content that you have today and consolidate it, at least into a
directory of 500 files.
I, by the way, already have 150 in my own for growth IQ, it's amazing.
But I use them and tap into them whenever I do a new agent.
And start with those MVPs, if you will, and make those a success before you do the
organizational rollout.
So let's say that you did foundational AI in the next three months.
And SMB can have the same level.
automation.
In other words, those LLMs, those are available to all of us.
And you can use technologies like, I'll give a shout out to Double O, you know, this
company out of California, where they do the workflow part.
And they want to automate these agents to make it dead simple for people, business users
like myself, to chain together these agents to do the work.
You know, you still have to give a context.
But do this.
where you do an agent, you chain them together with workflow.
There's a lot of technologies out there you can use right now.
And it doesn't cost you what it used to cost you to not just scale up the solution and the
subscriptions and the people.
You're basically riding on there eight, nine years.
They've been at since what, 2015?
Nine years.
So there's your garage band right there.
So they've been doing this for nine years.
You're tapping into that and you're building agents.
And I think when I saw OpenAI in particular do the GPT store, and I thought, all right, so
now they're thinking through the go-to-market part.
So you're building this.
Most companies will look at this as their IP.
They'll never put this up on the GPT store, because that's their differentiator.
Their go-to-market is quicker and better than the competition.
So I think you're starting to realize the dream of repeating those use case success
without
you know, more and more and more bodies.
You still need people to do this work.
You just won't need as many.
But I think, you know, coming back to the SMBs, you could be a company, and they write a
lot about this, right?
That first company will do $100 million in revenue, and it'll be a few people.
The billion dollar company that'll have 10.
You know, I think to me, conceptually speaking, that's interesting, you know, we'll see.
I think that's going to take time.
But the idea...
is absolutely possible, but you have to have foundational AI in place first for your
company.
Yeah, so I guess once they've got that foundational AI built out there, what do think the
next step is for them?
You know, once they've proven those MVPs and everything, how do they get to that next
stage?
Yeah, that serves as basically the foundation of the house.
How many analogies can I throw at you here?
So you got level one, got level two.
Level one was foundation.
Level two is going to be guided AI.
And think of guided AI as, and you can actually use AI models to do this.
And I like using some of these workflow tools because they'll point to the right one for
the job.
So start automating certain parts of the buyer journey.
And so let's say to begin with, it's creating awareness for your company, brand new
company, Growth IQ.
We've been around for a little over a year.
We're in stealth mode in 24.
So we've been at this for a year.
We built the foundational line.
Now we're starting to build out guided AI, which are basically these agents.
I think Salesforce talks about this as the digital workers, those agents to do the stuff,
the manual tasks.
And they're not necessarily the true optimization.
get to that in a minute, Tess.
These are the low-hanging fruit tasks.
Do those from awareness building to promoting.
And think about it from a buyer standpoint, to decision making, to value realization.
And then ultimately, them buying more.
Build guided AI or these AI agents for that journey.
Maybe it ends up being 10 to 15, which are your go-to agents.
Include in that project.
Don't ever include just sales with this go-to-market stuff.
That was always the beginning of the end of sales enablement was it was a company thing.
It was never a sales thing.
So build agents for the product team, the marketing team, the selling team, the service
team.
A lot of people are starting with the service team because
They can get better literally overnight.
That's probably your low hanging fruit.
So maybe even start there and make your current clients more successful and have them
buying more product then go upstream.
But either way, guided AI is going to be these digital workers or these agents.
And that positions you to the sort of big deal that I know you're part of, and that's
data, capitalizing on data.
Definitely, definitely.
I think data is going to be so important, right?
Especially with these AIs, once you've obviously gone through those phases, right?
Foundational and then to guided and you start to build out those, those data sets, those
databases for the AI to pull information from and to use it in the right way.
Honestly, the efficiency is crazy.
I mean, there's a lot of tasks that we do internally for the podcast specifically and for
client work and everything.
And we've not had to hire like three, four people.
just because we've got the systems in place now utilizing AI.
And so it's so interesting once you have the databases all set up and the data were
formatted and you're pulling from that with AI, it's incredible what you can speed up when
it comes down to the efficiencies within the company.
So guess once someone's gone through that guided AI stage, then what's the next stage
after that to really elevate them to the next level.
This is, I'll come back to my current company, this is why when I say to somebody, sure, I
want you to start working with me starting tomorrow.
I mean, why not, right?
But more importantly, if you put a stake in the ground in January of 2025, for those that
have been using this now for a year, these models and training a model, by mid-year,
you're going to have analytics by way of data that you never had before.
You know, I'm doing today scheduling using AI, so I'm getting better at scheduling.
So somebody asked, you know, isn't that a manual effort?
Well, it is, but understanding who should be on that call.
I'm using AI right now.
Otter, give a shout out to some of the AI technologies I'm leveraging for conversational
intelligence so that at the end of this call, you know, my note taking skills I used to be
pretty good at.
Now I don't have to do it anymore and I'm not unhappy about that.
But imagine having with a client every conversation you had over the next six months,
sitting at summer.
And you're looking at the meetings you scheduled, the calls that you had, the research you
did with them, and for each client having an AI project folder, if you will.
And you can do that with these automations.
And you can go to that folder and say, what have we learned?
And the KPIs we said in January, what do we actually realize by June?
Mm.
Some of their pie in the sky, know, some are derailed because of organizational drag, you
know, companies that are siloed.
It doesn't matter what you bring to the table.
It could literally be magic and it doesn't matter.
You know, they're going to derail it.
You know, it's just, that's just going to happen.
But what did we learn?
So what I'm saying is that if you get foundation and then these guided, and then you have
a combination of the companies and they are going to start building their own model and
their own agents specific to their company and their culture.
So they're going to be building more again.
So it's kind of what's old is new.
But then they're going to combine it with the power of the LLMs and the strength of some
of the other technologies.
You know, I'm using an AI CRM now.
I'm using an AI on the back end with clients now.
But by this fall, I'm referring to it as optimized AI.
We're going to be able to take a look at and say, you were having a conversation with me
on January 20th.
And now you have
30 AI agents in place, you are now serving this many more clients.
Some of those KPIs that we never really get to them.
Conversion rates, average deal size, win rates, very hard.
Content consumption, who's using what, clients, what was the reason they actually bought.
Some of those things we're gonna be gleaning through the AI now.
It's very hard to sit down.
Maybe you could do it at your sales kickoff meeting or maybe your club trip.
Those are always fun to sit down in a social atmosphere and say, all right, tell me really
why you won.
And then tell me why you lost.
I'm not saying those conversations should be replaced.
But if you started now, by this fall, you're going to have that same conversation with
your trained AI model.
And I think for those that do this, they're to be looking back at
what they learned.
I learned a lot from YouTube videos.
I don't know where you learn from, but I'm part of now the global AI community and it's
fun to get together them because we're all kind of brainstorming.
It's this new sort of world.
But if you got started now, the information that you're going to have by this fall is
going to be organized in a way and an AI is going to be helping you organize it.
Also the innovation in this next year.
It's not going to take five years.
Some of the automation, some people are going to say, well, it gives me wrong answers.
It hallucinates.
There's already automation that will fix hallucinations, pick the right model, give you
better results because it picked the right model.
So can you imagine after another several hundred billion dollars of investment in 25, how
much further these technologies?
Now, it might seem like I drank the Kool-Aid.
Well, the more you use these technologies,
and you have the foundation and guide it in place, we're now beginning to get there.
We do an AI maturity model.
We've done 130 surveys.
And so far, we haven't found anybody that optimized AI.
Flash forward in two years.
Let's do another one of these podcasts.
Yeah.
Yeah, no, no, a hundred percent.
this, uh, when you're saying that, I think about some of the processes that we've built
out.
mean, one of them, and we started this back right when chat GPT first really came out and
the APIs were available is, every sales call, right.
It's sending in that transcript to, to the AI and then pumping out, or, know, what are the
common objections, what the common hesitancies with it, or what are the pros of it as
well.
And now it's actually recently last week, I was going back through it.
using again, AI to figure out, what do need to change within the sales process to tackle
these questions that we always get or whatever that looks like.
And it's crazy, right?
Cause to do that before you'd have to sit through all the recordings, right?
Or read through all the transcripts, try and figure that out or scribbling it down during
the call, right?
When they mentioned something.
And now when you implement all these things and then you have the data at the end of it.
And as you said, right, you're optimized in that area that you've implemented it.
It's crazy what you can get out of it.
And, uh, and so, yeah, I completely agree.
And what you said about how this year is just going to get to the next level.
It's exponential, right?
With AI, it is exponential.
The way it's been learning and evolving over the last, you know, six, seven years.
It's crazy what we've seen in the last two years.
Right.
And then you look at just the last year itself.
And again, it's been crazy.
I mean, I still remember when there was that, that Will Smith video of him eating some
spaghetti or something back when, uh, you know, they started rolling out video AI and now.
you know, people were making jokes about it saying how bad it was and now you look at it
and you look at the videos and it's like you can't tell the difference, right?
And so it's going to be crazy what happens in the next year.
And so I agree.
think people need to start using it right now to be honest with you, because if you're not
thinking of using it or you're just hesitating around it, your competitors probably
aren't.
They're probably
maybe, maybe, and this is reality, right?
You we've sold to companies over the years where they're not able to buy our solution.
And the people literally leave that company because they so believe that this is a
difference maker.
I'm not saying leave your company.
Instead, do this.
Use it in your personal life.
If you can't get going with it at work.
I was told by somebody from Italy where to go to Italy.
And he said this, the region of Puglia.
I'm like, well, first of I got to go look that up.
So, you know, I'm thinking to myself, well, all right, before you go to some map, Google
Maps, you know, I went to AI and identified four cities, identified how to get there, how
to travel, you know, the sites, all the way down to the bands in the different towns, you
know, the entertainment.
And so did the trip.
And then at the end of the trip, I actually had to do a trip review and I sent it to one
of my relatives who said, how did you do a four day trip review?
I should say four page trip review.
I said, I didn't do that.
And I'm not saying AI is going to do things completely for us.
But the point is, it gave me an example.
I traveled to somewhere I'd never been.
I actually did a report.
And by the way, I actually learned myself based on the report because I didn't go to all
those sites.
I didn't know the actual population of some of these places, which I thought was cool and
one that were formed.
But by the way, whoever that person was from Italy that recommended Puglia, thumbs up.
It's an amazing area of Italy.
And so we never did that either, but that was a person that gave me that hot tip.
That was the context.
But use this.
Pick an example.
If there's a contract at work that you're staring at, take a picture of it, have AI scan
it and start analyzing it.
Just do it.
Do it in a protected workspace.
I want to be sure to say that.
You can't just use the free version of any of this because your payment's you.
and instead do it in your protected workspace.
But if you can't use it at the job, use it in your personal life, because you're going to
end up using this to brand a new and the skills going to be asked for.
You know full well that during the interview process at that next role in 2026, 27, you
know, how do you leverage, you know, AI and oh, by the way, do you have a network of
people that can provide context?
To me, that's the other big learning is
you know, continue to build your network of people that are subject matter experts,
because they're the ones that are going to give you context to use it.
Yeah, because with a lot of this, right, you don't know what you don't know.
And so until you start using the tool or speak to those, you know, those industry experts
is that you start realizing, oh, I can actually do this with AI, can do that with AI.
I mean, I remember, you know, back about a year and half ago, two years ago, I didn't know
anything about API's and know how you can connect them or anything like that.
And then I use TrackGBT to actually teach myself how to how to connect all these tools
together.
And now it's quite funny, you know, a lot of companies
Even if they don't say they have an API, you know that you could that you can use that you
can actually find the public API and start connecting things up within within their system
and everything.
And, you know, manage to do all that and learn all that through AI itself.
And so yes, it's phenomenal, phenomenal what this technology is going to bring for for
everyone.
So so I agree, if you can just start using it within your own life, or even within the
company, either or, but in the cup in a couple years, know, prompt engineering, it's one
of the highest paid tech roles out there right now, right, because people, people and
companies want this.
So even if in your personal life, you can start learning that skill, that's going to pay
dividends in the next five, 10 years for sure.
And maybe, sorry to interrupt, maybe I'm lazy, but as people hear terms like prompt
engineering.
So I remember early on hearing that term and I'm thinking, I'm just going to have AI
create my prompt.
So I what Gunn did.
So I like using examples like that because if maybe you need a quick win, you don't have
to learn prompt engineering over the course of hours or the study, use AI.
But then, I used AI early on to update the CRM.
mean, who likes updating CRMs?
The CRM is needed, and you have to collaborate.
But why not use a prompt that you create to, like you say, use a Zapier or some other kind
of API?
don't, beyond knowing what API stands for, I don't know how they work.
But what I do know is that I can go find out about a company in the next five minutes and
update the CRM to prepare for that call.
And I'm working with a workflow company right now that's going to take that agent combined
with an online discovery.
in a sense do that for a sales call.
So you're learning, you're updating the CRM about the company, then you're learning about
the specific needs of the company, and then you're updating the CRM on those needs.
And in a sense, you know, the CRM is is transparent to me.
Again, it's needed, but you know, do I want to spend time?
So these are the quick wins, you know, that you can do and knowing a little bit about
prompt engineering, you could do that starting today.
amazing.
I feel like we could talk about AI for for another few hours for sure.
But I know we're getting to time now.
So one of the final questions we always ask on this podcast is, if you can go back to your
18 year old self, and you could only take three lessons with you, right, whether it's some
philosophy, some business knowledge, some technical knowledge, what those three things be?
And, and why would it be those three things?
So I saw that question and I love that question.
So when I was 18 or 19, and this is me at one of our family Christmases, my uncle Dick
came over and he said, hey, look, I understand your business is construction where I grew
up.
We were in the construction business.
He goes, but give technology a whirl.
And so I had him explain to me again what he was doing.
They were building systems for the NASDAQ.
And so he started to explain to me, you know, the project he was on in Manhattan.
Well, I'd never been to Manhattan.
So I still remember the conversation because it caused me to pivot from what it is, you
know, my family did for a living, not saying that this is what, you know, every person
should do, but it gave me a chance to, you know, jump to do something that I never
considered doing.
And that was technology.
That was a while back.
So my timing was very good.
But the more important part was
you know, listening to that uncle that started explaining to me, you know, the things he
was doing in Manhattan that, you know, I'd never even dreamed of.
I just didn't know of them.
And today, of course, you can learn all about these things online, but do you want to
really do them?
And I've worked for vendors over the last couple of decades.
I've worked with hundreds of clients.
And I still remember my Uncle Dick saying, well, Nasdaq is one of 50 clients.
So, you know, you're not just going to the same job every day.
So I recommend
you know, jump to that career that suddenly becomes your passion and then, you know, be
able to build companies.
We were able to do that.
And don't be afraid to test your ideas.
You know, you've done it.
You've tested your ideas.
There's nothing better than seeing the ideas work.
And there's a coach that I had many years ago that said, do you ever notice when you're
coaching?
I coach hockey, you know, ice hockey.
He goes, ever notice that coaching is not a group thing, it's an individual thing?
So you keep learning, right?
So each individual on that team, you had to figure them out.
And then to be able to coach them.
The same thing with companies.
Each one, you got to figure them out.
So yeah, thanks, Uncle Dick, because he got me into this field.
Never looked back.
I was planning on being on the road for a couple of years.
I never came off the road and had a chance to do some of the things that you I talked
about on today's call.
Thanks for having me today.
It's kind of fun to go back through memory lane.
But as you could tell, I'm more excited right now.
This potential right now eclipses SAS 20 years ago.
It's like night and day.
Yeah, yeah, completely agree.
Well, thank you so much for taking the time to jump on this episode.
I've really enjoyed it.
We'll definitely get a second one booked in because I think we can talk about so many
other topics around AI and its use cases and everything.
Thanks again for having me.