June 12, 2025 ā¢ 38 mins
In this episode, Mark Brennan shares his incredible journey from working at Salesforce to founding Kynoch Labs, where he's pioneering the use of autonomous AI agents for business growth. Mark dives deep into the current state of AI, how businesses can leverage agent-based AI to boost efficiency and customer service, and why the AI revolution is closer than you think. This episode is packed with insights on how to integrate AI into your business and stay competitive in a rapidly evolving market.
š” What You'll Take Away For YOUR Business
š Why mid-market businesses are the best place to innovate with AI
Ā š¤ How autonomous AI agents workāand why theyāre a game-changer for customer service
Ā š° Why the future of AI isnāt about large language modelsāitās about application
Ā š ļø How to assess where to apply AI in your business for the greatest impact
Ā ā” The biggest challenges businesses face when adopting AIāand how to overcome them
Ā š Why businesses that embrace AI now will have a competitive edge by next year
Ā š¼ How to balance human teams with AI agents for maximum efficiency
š About Mark Brennan
Mark Brennan is a tech industry veteran and entrepreneur who started his career at Salesforce in 2007. After working with some of the biggest names in tech and helping IT departments globally, Mark founded Kynoch Labs, a trusted Salesforce partner specializing in building AI-driven autonomous agents. His expertise lies in business process automation, AI strategy, and empowering mid-market businesses to harness the power of AI for real-world results.
šÆ Markās BEST Piece of Advice for Wantrepreneurs and Entrepreneurs
"The safest place is to be a fast-moving entrepreneur who is nimble and willing to adjust frequently. Success comes from adapting and evolving quickly."
Key Takeaways from Mark's Advice:
Ā āļø Success isnāt about being perfectāitās about staying adaptable
Ā āļø Fear of failure shouldnāt stop you from experimenting with new strategies
Ā āļø The business world is evolving fastāadaptability is the key to survival
š¢ Memorable Quotes
āWeāre limited not by budget or resourcesābut by our imagination.ā ā Mark Brennan
āAI isnāt comingāitās already here. The businesses that adopt it now will have a major competitive advantage.ā ā Mark Brennan
āEntrepreneurship is scary, but the freedom to adapt and adjust quickly is worth it.ā ā Mark Brennan
š” Actionable Takeaways
ā
Start small: Test AI with customer service or operational tasks
Ā ā
Focus on AI that improves efficiencyānot just automating for the sake of it
Ā ā
Train your AI agents to know when to hand off tasks to human teams
Ā ā
Keep customer data secure by working with trusted AI partners
Ā ā
Stay adaptableāAI solutions will continue to evolve rapidly
š Links & Resources
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Hey, what is up?
Welcome to this episode of theWantrepreneur to Entrepreneur
podcast.
As always, I'm your host, BrianLofermento, and I am so excited
about today's guest, anincredible fellow entrepreneur
and expert, because I'll tellyou what as I was preparing to
interview him here today.
What I really loved about whathe wrote in our pre-interview
(00:20):
questionnaire is he said I lovetalking to business leaders with
vision who are ready to have usbuild digital workforce
assistance that do real workalongside their human teams.
Most business leaders don'tknow how achievable this really
is, and I feel like that's sucha great teaser to today's
conversation in today's episodebecause today's guest and
(00:41):
entrepreneur really believes notonly in the future of AI, but
in the today, the present, thecurrent of AI.
So let me introduce you totoday's guest.
His name is Mark Brennan.
Mark previously has worked atSalesforce all the way back,
starting in 2007, which is wherehe was introduced to a powerful
platform, a rapid developmentenvironment and super smart
(01:02):
people.
He then embarked on a journeyto deliver greatness to
struggling IT departmentsglobally.
He's had some CIO stints.
He started a few of his ownbusinesses.
We're definitely gonna talkabout Mark, the entrepreneur, as
well as the subject matterexpert, but his current company,
Kynock Labs, is a trustedSalesforce partner specializing
in building autonomous agentsand related AI solutions for
(01:23):
businesses.
Their services includeassessment, gap analysis,
business process analysis, anoverview of possibilities I love
the expansive thinking thereDesign and build of agent
solutions, and ongoingmonitoring and refinement.
There are so many cool thingsthat Mark and his company are up
to, and I think that it'sreally going to paint a picture
of how far along we are in theAI race.
(01:45):
Whether we realize it or not,there's so much that we could be
tapping into, so I'm excitedabout this one.
I'm not going to say anythingelse.
Let's dive straight into myinterview with Mark Brennan.
All right, Mark, I am so veryexcited that you're here with us
today.
First things first.
Welcome to the show.
I'm very excited that you'rehere with us today.
Speaker 2 (02:04):
First things first, welcome to the show.
Great to be here, brian, greatkickoff and excited to talk to
you.
Speaker 1 (02:10):
Heck.
Yes, the one thing I didn'tmention in the intro is that
your accent.
I already know it's going tosteal the show here today, so
let's dive straight into yourbackground.
It's a perfect segue, mark.
Who is Mark?
Well, how did you get intodoing all these cool things?
Speaker 2 (02:29):
Awesome.
Well, brian, you were askingwhere's my accent from and all
that stuff.
I don't think about that veryoften.
But yeah, irish family grew upin a few different countries and
came to America in 1993, thedraw of Silicon Valley Just
couldn't resist.
In fact, I left a gorgeousapartment in Switzerland on the
shores of Lake Neuchatel to comehere.
(02:50):
My friends thought I was nuts,but I wasn't, because I was
attracted to where the coolstuff gets invented.
I wanted to breathe the sameair as Steve Jobs and the likes
of, and here we are a lot of,lot of adventure, you know, just
to sum it up, brian, I'm I'm atech industry veteran now.
I really admire the inventorsand the visionaries.
(03:14):
I have worked for some of thegreat companies in Silicon
Valley and I I found that well,I, you know I was implementing
big ERP systems and workingalongside big consulting firms
and there was a point in the 90sthere where I got a little bit
disillusioned with big promises,bloated budgets and then
(03:37):
disappointment when we didn'treally achieve the vision of
these big projects.
And that's why I started to fallin love with mid-market
companies.
And also I discoveredSalesforce and that's where
everything changed for me, boththe speed of delivering value to
mid-market companies that areable to make decisions quickly
(04:01):
and you're able to talk toleaders who can they have vision
themselves and you bring yourown vision to the conversation
and we create a vision togetherand then we go do it which I was
not finding in, you know, giantcompanies.
It's kind of difficult toaccess those visionary leaders
at the very top.
And so here we are.
(04:21):
We've been a fantastic journeyand kind of collapse is now my
third venture, entrepreneurialventure, and we can talk a
little bit about the other two,but that's kind of my journey to
here yeah, I love that overview, mark, especially because I
think it really, right off thebat, showcases your unique
vantage point of obviously thirdentrepreneurial venture.
Speaker 1 (04:43):
You've already talked about your love for mid-market
businesses and I want to go intothere and the contrast between
the big businesses, the S&P 500that we all see and hear about
in the media headlines.
I would argue that each bringsvalue to the marketplace and to
society as a whole.
Because entrepreneurs, mark, wecan move fast with minimal
costs.
We can break things, we canfigure things out, we can be the
(05:03):
early adopters of technology,of innovations, of approaches,
of strategies.
Mid-market businesses it soundslike they're really those ones
that flesh those out and applythat growth fuel.
Then, of course, the bigbusinesses turn it into a
finished product that benefitsall of society.
That's my perspective on it.
But, mark, you have such aninteresting vantage point.
I'd love to hear you compareand contrast those three
(05:25):
different value points and whatmatters for each of those
different business sizes.
Speaker 2 (05:31):
Absolutely Well.
Firstly, you know we're nothere to criticize the titans of
industry.
If I were able to sit next toyou know Larry Page or Larry
Ellison or Mark Benioff or anyone of the giants, and to help
(05:52):
them make a vision come true,that would be extremely exciting
.
But that's not who you getaccess to.
Normally when you work.
You work for a fortune 100 orfortune 500 company, especially
if they're not in tech, ifthey're more of a financial
services or manufacturing orthey're kind of outside of
(06:15):
silicon valley.
The risk is and this is whathappened to me is I am not
sitting next to that visionarygenius.
I'm sitting with a group ofpeople who are in middle
management and they are riskaverse.
They don't like my appetite fornew stuff and so I find myself.
It's not my happy place.
And, by contrast, when I canconnect with a leader, it
(06:41):
doesn't have to be the CEO, butit has to be somebody who's got
real kind of decision power andis able to make a vision come
true In a mid-market company.
I actually have access to thesefolks and we can create a
vision together and then we canmake that dream come true.
That's where that's my happyplace.
Speaker 1 (06:59):
Yeah, I love that.
Well, I know that one of yourother happy places is in the
incredibly evolving world of AIand, mark, I want to put AI
right in the center of ourconversation.
You heard me tease it at thevery top of today's episode.
All business sizes.
That's.
The cool thing about the AIrace right now is that we're all
trying to figure it out indifferent capacities.
Where's that fit in, especiallytalking to you as a fellow
(07:21):
entrepreneur, and then alsoapplying it to the mid-market
businesses that we're talkingabout?
Speaker 2 (07:32):
Where are we today?
How far along are we?
That you don't think mostpeople realize it, excellent.
Well, brian, maybe we need togo back a bit just to see where
we you know the you are here,arrow on the map.
Salesforce came into the AIworld about 10 years ago with
Einstein, einstein 1, and it waspretty good.
It was more visionary thanreally highly effective.
It didn't really shake theworld, but it was a predictive
(08:01):
tool and also an insights tool.
It was able to look at all yourdata and able to see things
that maybe humans don't have thebandwidth or the or the ability
to focus, you know, to seethose, see those insights.
Um, and then it was able to, tosome extent, kind of connect
with some automation.
Um, salesforce never got into,uh, training a large language
model, an llm uh, I think thatwas genius of them to say.
(08:27):
That's not where the money is.
And you know, you and I readthe news and all we hear about
with AI is really which LLMoutperformed everybody else this
week and how much money gotpoured into their compute
infrastructure.
And we wonder how does thisaffect us?
How does it affect you and me?
And the answer is not very much.
(08:47):
I mean, we can switch from oneNLM to another without much
friction doesn't really matter.
If you want to sit in front ofa different prompt and ask the
same question and compare thetwo, you could do that all day
long.
It's not very sticky.
So I think what Salesforce istelling us is that that's not
where the money is.
(09:07):
The money is how are you goingto use AI in your business this
year?
And that's where I think themost exciting stuff is happening
.
Think about it.
The bit about sitting in frontof a prompt and asking it to
write a document for you orsolve a fairly simple problem
for you is played out.
We've been doing that for twoyears now, and I think anyone
(09:28):
who hasn't done that yet isprobably living under a rock,
right?
So I think everybody knows howto do that, and it's not like
it's not going to get better.
It is going to continue toimprove.
You're going to be able to askopen AI agents to do a series of
tasks for you, not just one.
(09:48):
But what's really exciting atthis moment is, last October,
salesforce announced AgentForce,which is essentially agentic AI
, an agent that works 24-7 foryou, alongside you and your
human team, and actually worksindependently and autonomously,
(10:08):
but you're able to monitor itand you're able to keep it safe
and you're able to keep it from,you're able to put in
guardrails that keep it fromhallucinating or saying toxic
things to customers, and you'realso able to tell it when to
hand over to your humans, whenit's kind of off its skis on you
know it's, the question is toohard or the topic has kind of
(10:31):
moved, it's about to move offscript.
No problem, just call, you know,hand it over to a human and
it's done most of the work foryou.
So this is really where therevolution is happening.
This year and I think by thistime next year we'll see a large
number of kind of leading edgebusinesses that see the value
(10:56):
here and have built a few agentsand I've got them working
alongside their humans, and wecan talk a lot about what this
does to the job market.
What does it do to the economy?
What does it do to the economy?
What does it do to, most of all, to the customer experience?
That's what I think is the mostimportant part of of this
revolution that we're in yeah,mark, hearing you talk about
that.
Speaker 1 (11:14):
There's two things that I really enjoy.
One is it's really cool to hearactual use cases of ai instead
of just prompting.
But then the second thing thatI want to point out for
listeners is you and I we're nottalking about years away from
this.
You're saying this time nextyear, and I think that that just
speaks volumes to the rate ofacceleration in this marketplace
.
So, with that in mind, mark,when you talk about agents we've
(11:36):
all kind of heard that term ina very loose way what are some
of those use cases of what theseAI agents can actually do
inside of businesses?
Speaker 2 (11:44):
use cases of what these AI agents can actually do
inside of businesses, absolutelyso.
Let's compare it to over here.
You've got a person sitting infront of a screen and they've
opened an AI.
They've opened OpenAI or Geminior any one of the sort of top
seven or eight, and they'reasking it to do something.
They're asking it to researchsomething, or to write a
(12:05):
document, or to write a poem ora short story or whatever it is
that you're asking.
It can do that for youreasonably well.
You might need to ask thequestion a few times until
you've prompted it correctly andyou've got yourself the right
output output.
(12:29):
An agent, by contrast, is usingthat LLM, that large language
model in the background, butwhat it's doing is it's tasked
mechanically to do certainthings to reason with either an
employee or a customer and tounderstand what the intent is.
What is it being asked to do?
And to understand what theintent is, what is it being
asked to do?
And then to call on a number ofactions that sit inside of its
(12:51):
kind of toolkit and call theright one and, at the same time,
call the large language modelin the background to assemble
responses back to you.
So that may sound reallynebulous.
So let's go straight into acouple of examples.
The most obvious example iscustomer service.
You go to the chatbot on thewebsite for your credit card
(13:12):
company or your health insurancecompany or your you know, pick
any number of scenarios andyou're asking for help.
Why are you doing that?
Well, one, because we're kindof tired of calling call centers
in faraway countries andexplaining ourselves six times
after waiting on the phone andthen finding that they weren't
(13:33):
able to solve the problem.
Two, because normal chatbotsactually don't work.
All they do is just point youto the frequently asked
questions, and then you have toread reams of documentation and
find that you have to solve theproblem by yourself.
So now what we're, the worldthat we're in, is the chatbot is
actually driven by an agent,not a human, and the agent is
(13:54):
able to understand what you'reasking and go find the
information that will resolveyour problem if it holds it, and
it's using the llm in thebackground to basically blend
private internal information umin in salesforce.
Let's talk about this for asecond.
Salesforce is probably the onlyplatform in in the enterprise
(14:16):
business world that is able tooffer this agent force end to
end.
Why is that?
Because it's a unified platformthat's got your customer
relationship management data.
It's got your service data,including knowledge articles
about cases, problems, how weresolve them, what the questions
(14:38):
are and what the answers tothose questions are.
Nobody else has that integratedin one.
You know, one pane of glass.
And now it's got this Atlasreasoning engine, which is able
to understand your intent.
You've gone to that, to thechatbot, or you're texting, or
you're on the phone.
It's able to manage all ofthese channels and it's able to
(15:02):
go fetch internally and thenblend with a public AI
formulating the answer to you.
Now the first thing you mightwonder is what about your
private data?
Are you training a public AIwith your customers' data?
Well, no, you're not.
So Salesforce is taking greatcare to make your data safe and
(15:24):
to mask it.
They've done a whole lot ofwork on prompt defense and data
masking and zero retention sothat your data is safe.
So what's happening here is,essentially, we're able to carry
the luggage for the human teamand do the more base level tasks
(15:48):
and free them up to do morevaluable work.
Now, for example, you may beasking your credit card company
about a transaction that tookplace in Pakistan and you were
not in Pakistan this week, sothere's a problem.
And it was able to look it upfor you and able to to do so,
you know, to find it for you andtell you about it.
(16:09):
But the next thing might be thatmight actually be fraud and we
might need to hand it off to ahuman team.
And the agent is able to istrained, you've told it to do
this is to hand it off to ahuman and to basically prompt
somebody in the fraud team, forexample, to pick up the
conversation seamlessly.
You don't need to explainyourself again, you don't need
(16:30):
to reintroduce yourself, they'lljust take up the conversation
seamlessly.
You don't need to explainyourself again, you don't need
to reintroduce yourself.
They'll just take over theconversation and read the
summary of what the agent hasfound so far.
So let's think about that andunpack it for a second.
That's kind of revolutionary,isn't it?
So you've just got half yourproblem solved by a non-human,
by an autonomous agent, and nowthe human is jumping in and they
(16:50):
already know everything theyneed to know about where we are
so far and what to do next.
Speaker 1 (16:56):
Yeah, Mark.
I love that tangible examplebecause I feel like this is part
of the mainstream conversationof people saying, well, yeah, us
as consumers, we're going toget solved better, we're going
to get solved quicker.
There's so many big advantagesthere from a business
perspective.
I'm thinking well, we get touse our human capital in far
more intelligent ways.
We get to take them away fromsome of those those things that
(17:17):
just clog up their to do lists.
With that said, I also knowthat the macro argument is
what's going to happen to jobs?
Are they going to shift, Arethey going to change?
The answer, of course, is forsure.
It is what's your take on whatthe future looks like in the
jobs market?
Sure?
Speaker 2 (17:34):
well, brian, let's preface this by saying I, I am a
techno optimist, uh and uh, butthat has worked really well for
me.
Uh, so far, so um, I thinkwhat's happening is, you know,
you've got to look at job titlesand you know income streams
that exist today, that didn'texist 10 years ago or 15 years
(17:56):
ago Podcasters, influencers,youtubers, gopro influencers.
Those are just some examples,but there are many, many more
include inside of the bankingworld, inside of the healthcare
world, there are job titles thatdidn't exist before and that do
(18:17):
now.
So let's go back to theautomobile industry.
And how many people in thehorse and buggy industry thought
they were going to lose theirlivelihood.
But what they didn't see iswe're not just buying cars, we
have car mechanic shops, we havebody shops, we have car washes,
(18:39):
we have everything related tothe car industry.
The automobile industry hascreated a massive kind of
ballooning economy andessentially you can't argue that
there are not more jobs thanthere were before.
And this happens time and timeagain.
Same with, you know, 1993, 95,the birth of the World Wide Web
(19:01):
on top of the internet.
And you know there were thosepeople who said, oh, it's just a
fad, it's not really going tochange anything, and that's kind
of funny to think back now asthe people who thought that is
there going to be damage to thejob market before there is
growth?
Possibly yes.
We're seeing already the jobmarket is a little bit tough for
(19:22):
software engineers, lawyers andmarketers particularly, but
also for many other job titles.
They're kind of struggling atthe moment.
I think the business world haskind of decided hold on the
hiring for now, essential hiresonly.
We're not sure how this isgoing to play out and and there
are folks kind of seeing oh,they got laid off a few months
(19:43):
ago and it's it's not easy tofind the next.
The next thing, I think I heardan amazing line at a Salesforce
event last week was tomorrow'sjobs belong to today's learners,
and so that's suggesting that,you know, give ourselves the
(20:03):
flexibility to kind of changelane a little bit and use
bringing all of our skills andour experience, our knowledge,
just a little bit over here towhere we can see momentum, and
then we'll be rewarded for thatcourage and that curiosity yeah,
I love that answer, mark.
Speaker 1 (20:20):
Anytime people tell me ai is going to take away jobs
, that's the answer that I'mgoing to share with them right
there.
I think that the car analogy isis so fruitful, especially
because a lot of people pointtowards mechanics, but I love
all the auxiliary industriesthat you just pointed out car
washes.
There's entirely differentbusinesses, business models,
services, all of that that popup because of this, and so it's
really cool to think about allthe ways that we're going to
(20:41):
apply AI.
When I think about that, mark,one thing that always fascinates
me is kind of the yin and theyang, the balance on both sides
of things, because when you lookat a business, there's areas
where we can and should apply AI, but there's also that wisdom
and that experienced perspectiveof knowing where not to apply
AI, and I feel like that's kindof where we're at right now is.
(21:02):
A lot of businesses are askingwhere do we and where don't we?
Part of your job and part ofyour value add with Kynock is
that you assess businesses andyou look at them and say, hey,
let's start here.
What are you looking at whenyou look at a business from the
outside and when you get on theinside.
How do you assess where youshould be starting and where you
should?
Speaker 2 (21:21):
be building AI solutions.
Yeah, I love that question.
It's so much fun, you know.
So we start by saying we're notconnecting with as many
businesses ready to hit thestart button right now and say,
let's, do we want to spend X ona few agents that will do these
(21:42):
tasks and these and these jobs?
And we're ready.
And whether it's experimental,whether it's just a proof of
concept type of you know,putting some POC dollars into
something that is more of alearning experience or whether
we are assured success, we'revery confident we can design
this, build this and make itwork.
(22:02):
And I think that there's still alot of I wouldn't even call it
hesitation.
It's kind of still pondering dowe have to do this, do what if
we don't do it this quarter?
What if we don't do it thisyear?
Our argument is you willeventually be behind and either
(22:22):
be left behind or you'll have toplay catch up.
And it's hard to play catch upwhen the market is ahead of you,
when your competitors are aheadof you, and this is the moment
right now.
You're not behind If you'regetting started.
Started now looking at whatagents can do for you.
In start with a corner of yourbusiness and start simple.
We can talk about this somemore, like where do you start
(22:44):
and how and and?
How do you assess what would bethe the best couple of
candidates for agents to getstarted?
And then you're not behind.
Then you know the first agentthat you build is a fabulous
learning experience for yourentire company, and then it will
give you the confidence to say,wow, we were able to do that.
Now, where else can we putagent number two, number three,
(23:08):
and you know there isn't a setnumber of agents that you need
to have.
But you now have yourself asituation where your humans are
being assisted by autonomousagents.
And you've done it.
You're in the pool right Nowyou can start to.
You know, I say this a lot we'relimited by our imagination more
(23:29):
than our budget, more than ourlegal constraints or regulatory
constraints.
You know legal constraints orregulatory constraints.
The real constraint is can youimagine what will you do when
you can hire digital workforceagents?
You can basically extend yourworkforce digitally, without the
(23:51):
headcount and without thepayroll increment.
What will you do with them?
And so these are, these aregreat questions, brian, and so
I'll give you an example.
We, we've done.
We've done a number of fairlybasic, either employee support
or customer support, the service.
It's an obvious first place tostart if you, you know you've
got Salesforce up and running.
(24:12):
You use cases, right, you havecases for customer support.
Why not start with solving thesimplest and most, shall we say,
uninteresting cases for humans,make them interesting for
agents and then solve them?
And it will start off withsomething really, really simple
(24:33):
and prove that it works and thenexpand from there.
On the other end of the scale,we've got we're working on one
right now with a biosciencesresearch company, little startup
, and they're finding that theirmolecular research is really
manual and it's really laborintensive and they're accessing
(24:56):
a number of public databases tolook up organisms.
Imagine you start with the endin mind and you want to break
down hydrocarbon fuels infilling station sites after
they've been shut down.
You wanna grow a garden wherethere used to be a gas station,
where you can't right now, untilyou break down those diesel and
(25:18):
petrol residues.
Can I create a natural productthat would break down those
hydrocarbon residues withoutchemicals?
Well, let's find out.
And so they start researchingwhat kind of organisms have
those qualities?
And weeks later you've done,you know, hundreds of hours of
(25:41):
research on these publicdatabases and you've got
yourself a list of organismswhich, when put together, would
interact with each other to forma formulation that would
probably work.
And then you go into labtesting and you actually test it
.
So we're building an agent thatwill do a lot of that research.
Well, actually, you start bydescribing your end goal and it
(26:06):
will then go and access thosepublic databases for you and
bring back summary of its of itsfindings, which is incredibly
exciting.
When you think about, this isnot just doing a, you know, a
low level task.
It's kind of kind of gone up alevel.
It's not built yet, so we don't, you know, check in with us a
(26:28):
little bit later, but there's isone example of things getting
more ambitious, right and morevisionary.
Speaker 1 (26:33):
Mark, I love that, especially because the word that
stands out to me it's a word Iuse about my work a lot, which
is exciting, and hearing youtalk about these sort of AI
solutions.
What I hear is, obviously, I'mhearing you talk about the
subject matter itself, butgetting the chance to interview
you here today, mark, what I'mreally hearing and absorbing is
your genuine excitement.
You called it out earlier thatyou're a tech optimist, and so
(26:55):
for me, as a fellow optimist inlife and especially in business,
I know that what drives me isthat I firmly believe and deeply
believe that entrepreneurshipmakes the world a better place.
And it's so clear in talking toyou today that you also firmly
believe not onlyentrepreneurship but also AI and
technology can make the world abetter place.
With that in mind, mark, I wantto ask you about what motivates
(27:17):
you, because a lot ofentrepreneurs you know we face
all the ups and downs, andyou've experienced this.
This is your thirdentrepreneurial venture as well.
You're one of us.
I always remind listeners aboutthat.
What's that like as you pushforward through those ups and
downs?
Where's that entrepreneurialmindset kick in, and how do you
continue to have that drive?
Speaker 2 (27:37):
Sure, brian.
Well, you know, I think it'sscary in a really great way.
So when the world is moving sofast I mean the AI world is
moving so fast that, you know,as we sleep, we're missing news,
(27:59):
and we wake up, we catch up, weoh, that happened, um.
And so what I'm afraid of isthe crowd catching up, uh, with
with me and with, you know, withmy team, and suddenly everyone
knows how to do this stuff andwe're not differentiated.
So I think that's a reallyscary thing.
Um, the reason I'm not stilldoing the first venture you know
, I founded Benissimo in 2012,is we kind of had a different
(28:24):
purpose.
We were still, we were aSalesforce partner and we, you
know, we were very successful,but our mission was different
and we kind of accomplished thatmission, sold that company and
then did the second one.
So, you know, our mission thistime is to bring success with AI
(28:46):
, especially to the mid-marketcompanies who might still think
it's too expensive or too risky,and we want to take the risk
out of it while still beingquite visionary.
And the scary part is, you know, a lot of consulting firms tend
to cater to that risk-aversemiddle management sort of
(29:08):
thinking in the corporate world,you know, at the enterprise
level, at the Fortune 500 level,and we're here to connect with
the mid-market leaders who seethat they want to do this.
They're not quite sure aboutthe risk and the cost and the
probability of success.
So we have that conversationand we get them to a level of
(29:30):
comfort that says this is Xamount of dollars that you're
going to spend here and we'revery confident that we'll get
this to accomplish its statedpurposes.
Stated purpose, and from thereyou can layer on.
You're not done, but you've.
You've got success with yourfirst spend, right.
So I think it feels it feelsgreat to be doing this.
(29:53):
Our challenge is to find more ofthose companies where we have a
lot of conversations, wherethey're just not ready.
They're just, um, they they saywe love what you're doing and,
um, you know, give us more time.
We're thinking about this.
They're kind of thinking about,uh, do they have to?
Or they're also thinking like,which platform uh is the best
one for them and what's it goingto do to their operation?
(30:15):
And I think the biggest thingthey're afraid of is that they
have to keep spending more moneyto achieve the initial kind of
definition of success.
So it's a very exciting year.
I mean, I do believe that 2025is the year of agent AI and I do
believe that Salesforce isprobably the absolute best
(30:35):
platform.
Nobody else can really offerthis unified platform, on top of
which to put your autonomousagents and what Kind of Labs.
Offers is the visionary skillsthat a lot of consulting firms
don't quite have yet becausethey play it safe.
(30:55):
So we're not risky, we're justmore leading edge and we're able
to give you confidence that youwill succeed while adopting the
new stuff and not waiting forit to be mainstream.
Speaker 1 (31:08):
Yes, so well said, mark.
I keep coming back to itSomething you've already said
here in our conversation todayand it's going to leave a
lasting impression on me, andthat is we're limited not by
budget, not by resources, but bythat imagination.
And here it is again showing upin that visionary thinking that
you've obviously injected intothe way that Kynock operates,
and it's so cool to hear that.
So, mark, I've got one last bigchallenge for you.
(31:31):
It's the question I ask at theend of every single episode, and
that is what's your one bestpiece of advice, knowing that
we're being listened to by bothentrepreneurs and entrepreneurs
at all different stages of theirown growth journeys.
And also I know that from ourconversation today, they're all
going to be excited about thenew way, the more expansive way
to imagine, to dream big, tomake these things happen in
(31:51):
their business.
You're a fellow entrepreneur,so what's that one piece of
advice that you want to leavethem with today?
Speaker 2 (31:58):
Oh gosh.
Well, I think you look in themirror and you ask yourself, do
I have entrepreneurial bloodflowing through me?
And you know it's okay to havedoubt through me.
And you know it's okay to havedoubt, it's okay to sometimes
(32:19):
wonder, like, wouldn't I be justsafer with a, you know, a
regular paycheck and just staywith some big company where I'll
be safe?
Well, number one, nobody'sreally safe anymore.
You know, the job for lifething has been gone for a long
time and now, with you know theincreased kind of crazy pace of
business, nobody's safe.
So I think the safest place isactually to be a fast moving
(32:43):
entrepreneur who is very agile,very nimble and is able to kind
of not a U-turn but is able tokind of change lanes, um,
quickly and say it's over here,it's over here and it's.
That's not a pivot, it's just aslight adjustment to where we
thought we were going, and to dothat frequently and to be able
to, to, to say right, we're notwrong, but we need to adjust
(33:07):
slightly where we're going andwhat we're seeking and we'll be
okay.
And if we keep doing that, it'snot.
It's not even about money,although when we are successful
the money just takes care ofitself.
It's really about the um, thecuriosity, um and um and the
ability to see that we need tomake an adjustment every day.
Speaker 1 (33:30):
Yeah, so well said Advice.
Listeners, as Mark is sayingthat, I'm nodding my head the
entire time because I'm thinking, yes, we all have those moments
, Mark.
I can't tell you the number oftimes I've said wouldn't it be
easier to just have a paycheckevery single week?
Wouldn't it be easier to justhave an HR department that plans
out all of our benefit programs?
Wouldn't all that be easier?
(33:56):
But, holy cow, the juice is soworth the squeeze and you
encapsulated so well the realentrepreneurial mindset and the
real entrepreneurial ups anddowns in that answer and that
advice.
So I so appreciate you forsharing that with our audience
here today.
I also know that our audienceis going to be super keen to see
a lot of these things that youand I talked about.
See them in action, and I loveyour website.
One of the things that you andI talked about see them in
action, and I love your website.
One of the headlines rightthere on your website is are you
ready for agent force?
Learn more and seeing all thematerials that you've put
(34:19):
together about why it's sopowerful to hire an agent.
I put hire in quotes becausethese are things that we can
build for our businesses Thanksto visionaries like you.
So, Mark, for those listenerswho want to go deeper into your
business and all the great workyou're doing, drop those links
on us.
Where should listeners go fromhere?
Speaker 2 (34:37):
Stay curious.
So, again, you know, tomorrow'sjobs belong to today's learners
and they're not necessarilyjobs there.
They might be entrepreneurialventures.
And I would say you knowsomething?
Um, there's always stress inlife, no matter what you're
doing, right?
Yeah, I mean, you could be akid playing soccer and it's
stressful because you're doinghard things and you might lose,
(34:59):
and that's terrible, right?
So, um, stress is good.
Uh, pressure is privilege.
Now the the time, the kind ofstress that I was never able to
shake off, the kind of stressthat I was never able to shake
off, was the corporate frictionbetween people, sharp elbows and
, you know, somebody kind ofputting a thumbtack in you, so
(35:26):
just kind of making your daydifficult unnecessarily.
I was not able to shake thatoff.
Whereas the stress of running acompany and just cash flow and
you know, are we going to winthis next deal, are we?
There's a project that's runinto a, you know, a problem.
You're always going to havethese, you're always going to
have these things.
But that stress I can managebecause I can make decisions and
(35:46):
I have the scope to navigatefrom here through challenges,
and I think it's much lessstressful to do that than to be
in an environment where I don'thave access to.
I can't change my environment.
I can either leave or I canstay and tolerate it, and that's
not good for me.
Speaker 1 (36:07):
Yes, spoken like a true entrepreneur.
Mark, I love hearing yourperspectives on that.
Listeners, you are in for sucha treat because we are dropping
the links to Mark's businesswebsite, to his personal
LinkedIn, down below in the shownotes.
No matter where it is thatyou're tuning into today's
episode, you'll be able to go somuch deeper into a lot of these
things that we've talked abouthere on the air, on his website
(36:28):
and if you want to continue theconversation, you heard that
Mark is very keen on havingconversations with business
leaders who want to startimplementing this stuff not
thinking about it, not beingaware that it's out there, but
actually implementing it.
So we're dropping a link to hispersonal LinkedIn down below in
the show notes.
Otherwise, mark, on behalf ofmyself and all the listeners
worldwide, thanks so much forcoming on the show today Super
(36:51):
fun.
Thank you, brian hey, it'sBrian here and thanks for tuning
in to yet another episode ofthe Wantrepreneur to
Entrepreneur podcast.
If you haven't checked us outonline, there's so much good
stuff there.
Check out the show's website andall the show notes that we
talked about in today's episodeat thewantrepreneurshowcom, and
I just want to give a shout outto our amazing guests.
(37:12):
There's a reason why we are adfree and have produced so many
incredible episodes five days aweek for you, and it's because
our guests step up to the plate.
These are not sponsoredepisodes.
These are not infomercials.
Our guests help us cover thecosts of our productions.
They so deeply believe in thepower of getting their message
out in front of you awesomewantrepreneurs and entrepreneurs
(37:35):
, that they contribute to helpus make these productions
possible.
So thank you to not onlytoday's guests, but all of our
guests in general, and I justwant to invite you check out our
website because you can send usa voicemail there.
We also have live chat.
If you want to interactdirectly with me, go to
thewantrepreneurshowcom.
Initiate a live chat.
It's for real me and I'mexcited because I'll see you, as
(37:58):
always every Monday, wednesday,friday, saturday and Sunday
here on the Wantrepreneur toEntrepreneur podcast.
Hey, what is up?
Welcome to this episode of theWantrepreneur to Entrepreneur
podcast.
As always, I'm your host, BrianLofermento, and I am so excited
about today's guest, anincredible fellow entrepreneur
and expert, because I'll tellyou what as I was preparing to
interview him here today.
What I really loved about whathe wrote in our pre-interview
(00:20):
questionnaire is he said I lovetalking to business leaders with
vision who are ready to have usbuild digital workforce
assistance that do real workalongside their human teams.
Most business leaders don'tknow how achievable this really
is, and I feel like that's sucha great teaser to today's
conversation in today's episodebecause today's guest and
(00:41):
entrepreneur really believes notonly in the future of AI, but
in the today, the present, thecurrent of AI.
So let me introduce you totoday's guest.
His name is Mark Brennan.
Mark previously has worked atSalesforce all the way back,
starting in 2007, which is wherehe was introduced to a powerful
platform, a rapid developmentenvironment and super smart
(01:02):
people.
He then embarked on a journeyto deliver greatness to
struggling IT departmentsglobally.
He's had some CIO stints.
He started a few of his ownbusinesses.
We're definitely gonna talkabout Mark, the entrepreneur, as
well as the subject matterexpert, but his current company,
Kynock Labs, is a trustedSalesforce partner specializing
in building autonomous agentsand related AI solutions for
(01:23):
businesses.
Their services includeassessment, gap analysis,
business process analysis, anoverview of possibilities I love
the expansive thinking thereDesign and build of agent
solutions, and ongoingmonitoring and refinement.
There are so many cool thingsthat Mark and his company are up
to, and I think that it'sreally going to paint a picture
of how far along we are in theAI race.
(01:45):
Whether we realize it or not,there's so much that we could be
tapping into, so I'm excitedabout this one.
I'm not going to say anythingelse.
Let's dive straight into myinterview with Mark Brennan.
All right, Mark, I am so veryexcited that you're here with us
today.
First things first.
Welcome to the show.
I'm very excited that you'rehere with us today.
Speaker 2 (02:04):
First things first, welcome to the show.
Great to be here, brian, greatkickoff and excited to talk to
you.
Speaker 1 (02:10):
Heck.
Yes, the one thing I didn'tmention in the intro is that
your accent.
I already know it's going tosteal the show here today, so
let's dive straight into yourbackground.
It's a perfect segue, mark.
Who is Mark?
Well, how did you get intodoing all these cool things?
Speaker 2 (02:29):
Awesome.
Well, brian, you were askingwhere's my accent from and all
that stuff.
I don't think about that veryoften.
But yeah, irish family grew upin a few different countries and
came to America in 1993, thedraw of Silicon Valley Just
couldn't resist.
In fact, I left a gorgeousapartment in Switzerland on the
shores of Lake Neuchatel to comehere.
(02:50):
My friends thought I was nuts,but I wasn't, because I was
attracted to where the coolstuff gets invented.
I wanted to breathe the sameair as Steve Jobs and the likes
of, and here we are a lot of,lot of adventure, you know, just
to sum it up, brian, I'm I'm atech industry veteran now.
I really admire the inventorsand the visionaries.
(03:14):
I have worked for some of thegreat companies in Silicon
Valley and I I found that well,I, you know I was implementing
big ERP systems and workingalongside big consulting firms
and there was a point in the 90sthere where I got a little bit
disillusioned with big promises,bloated budgets and then
(03:37):
disappointment when we didn'treally achieve the vision of
these big projects.
And that's why I started to fallin love with mid-market
companies.
And also I discoveredSalesforce and that's where
everything changed for me, boththe speed of delivering value to
mid-market companies that areable to make decisions quickly
(04:01):
and you're able to talk toleaders who can they have vision
themselves and you bring yourown vision to the conversation
and we create a vision togetherand then we go do it which I was
not finding in, you know, giantcompanies.
It's kind of difficult toaccess those visionary leaders
at the very top.
And so here we are.
(04:21):
We've been a fantastic journeyand kind of collapse is now my
third venture, entrepreneurialventure, and we can talk a
little bit about the other two,but that's kind of my journey to
here yeah, I love that overview, mark, especially because I
think it really, right off thebat, showcases your unique
vantage point of obviously thirdentrepreneurial venture.
Speaker 1 (04:43):
You've already talked about your love for mid-market
businesses and I want to go intothere and the contrast between
the big businesses, the S&P 500that we all see and hear about
in the media headlines.
I would argue that each bringsvalue to the marketplace and to
society as a whole.
Because entrepreneurs, mark, wecan move fast with minimal
costs.
We can break things, we canfigure things out, we can be the
(05:03):
early adopters of technology,of innovations, of approaches,
of strategies.
Mid-market businesses it soundslike they're really those ones
that flesh those out and applythat growth fuel.
Then, of course, the bigbusinesses turn it into a
finished product that benefitsall of society.
That's my perspective on it.
But, mark, you have such aninteresting vantage point.
I'd love to hear you compareand contrast those three
(05:25):
different value points and whatmatters for each of those
different business sizes.
Speaker 2 (05:31):
Absolutely Well.
Firstly, you know we're nothere to criticize the titans of
industry.
If I were able to sit next toyou know Larry Page or Larry
Ellison or Mark Benioff or anyone of the giants, and to help
(05:52):
them make a vision come true,that would be extremely exciting
.
But that's not who you getaccess to.
Normally when you work.
You work for a fortune 100 orfortune 500 company, especially
if they're not in tech, ifthey're more of a financial
services or manufacturing orthey're kind of outside of
(06:15):
silicon valley.
The risk is and this is whathappened to me is I am not
sitting next to that visionarygenius.
I'm sitting with a group ofpeople who are in middle
management and they are riskaverse.
They don't like my appetite fornew stuff and so I find myself.
It's not my happy place.
And, by contrast, when I canconnect with a leader, it
(06:41):
doesn't have to be the CEO, butit has to be somebody who's got
real kind of decision power andis able to make a vision come
true In a mid-market company.
I actually have access to thesefolks and we can create a
vision together and then we canmake that dream come true.
That's where that's my happyplace.
Speaker 1 (06:59):
Yeah, I love that.
Well, I know that one of yourother happy places is in the
incredibly evolving world of AIand, mark, I want to put AI
right in the center of ourconversation.
You heard me tease it at thevery top of today's episode.
All business sizes.
That's.
The cool thing about the AIrace right now is that we're all
trying to figure it out indifferent capacities.
Where's that fit in, especiallytalking to you as a fellow
(07:21):
entrepreneur, and then alsoapplying it to the mid-market
businesses that we're talkingabout?
Speaker 2 (07:32):
Where are we today?
How far along are we?
That you don't think mostpeople realize it, excellent.
Well, brian, maybe we need togo back a bit just to see where
we you know the you are here,arrow on the map.
Salesforce came into the AIworld about 10 years ago with
Einstein, einstein 1, and it waspretty good.
It was more visionary thanreally highly effective.
It didn't really shake theworld, but it was a predictive
(08:01):
tool and also an insights tool.
It was able to look at all yourdata and able to see things
that maybe humans don't have thebandwidth or the or the ability
to focus, you know, to seethose, see those insights.
Um, and then it was able to, tosome extent, kind of connect
with some automation.
Um, salesforce never got into,uh, training a large language
model, an llm uh, I think thatwas genius of them to say.
(08:27):
That's not where the money is.
And you know, you and I readthe news and all we hear about
with AI is really which LLMoutperformed everybody else this
week and how much money gotpoured into their compute
infrastructure.
And we wonder how does thisaffect us?
How does it affect you and me?
And the answer is not very much.
(08:47):
I mean, we can switch from oneNLM to another without much
friction doesn't really matter.
If you want to sit in front ofa different prompt and ask the
same question and compare thetwo, you could do that all day
long.
It's not very sticky.
So I think what Salesforce istelling us is that that's not
where the money is.
(09:07):
The money is how are you goingto use AI in your business this
year?
And that's where I think themost exciting stuff is happening
.
Think about it.
The bit about sitting in frontof a prompt and asking it to
write a document for you orsolve a fairly simple problem
for you is played out.
We've been doing that for twoyears now, and I think anyone
(09:28):
who hasn't done that yet isprobably living under a rock,
right?
So I think everybody knows howto do that, and it's not like
it's not going to get better.
It is going to continue toimprove.
You're going to be able to askopen AI agents to do a series of
tasks for you, not just one.
(09:48):
But what's really exciting atthis moment is, last October,
salesforce announced AgentForce,which is essentially agentic AI
, an agent that works 24-7 foryou, alongside you and your
human team, and actually worksindependently and autonomously,
(10:08):
but you're able to monitor itand you're able to keep it safe
and you're able to keep it from,you're able to put in
guardrails that keep it fromhallucinating or saying toxic
things to customers, and you'realso able to tell it when to
hand over to your humans, whenit's kind of off its skis on you
know it's, the question is toohard or the topic has kind of
(10:31):
moved, it's about to move offscript.
No problem, just call, you know,hand it over to a human and
it's done most of the work foryou.
So this is really where therevolution is happening.
This year and I think by thistime next year we'll see a large
number of kind of leading edgebusinesses that see the value
(10:56):
here and have built a few agentsand I've got them working
alongside their humans, and wecan talk a lot about what this
does to the job market.
What does it do to the economy?
What does it do to the economy?
What does it do to, most of all, to the customer experience?
That's what I think is the mostimportant part of of this
revolution that we're in yeah,mark, hearing you talk about
that.
Speaker 1 (11:14):
There's two things that I really enjoy.
One is it's really cool to hearactual use cases of ai instead
of just prompting.
But then the second thing thatI want to point out for
listeners is you and I we're nottalking about years away from
this.
You're saying this time nextyear, and I think that that just
speaks volumes to the rate ofacceleration in this marketplace
.
So, with that in mind, mark,when you talk about agents we've
(11:36):
all kind of heard that term ina very loose way what are some
of those use cases of what theseAI agents can actually do
inside of businesses?
Speaker 2 (11:44):
use cases of what these AI agents can actually do
inside of businesses, absolutelyso.
Let's compare it to over here.
You've got a person sitting infront of a screen and they've
opened an AI.
They've opened OpenAI or Geminior any one of the sort of top
seven or eight, and they'reasking it to do something.
They're asking it to researchsomething, or to write a
(12:05):
document, or to write a poem ora short story or whatever it is
that you're asking.
It can do that for youreasonably well.
You might need to ask thequestion a few times until
you've prompted it correctly andyou've got yourself the right
output output.
(12:29):
An agent, by contrast, is usingthat LLM, that large language
model in the background, butwhat it's doing is it's tasked
mechanically to do certainthings to reason with either an
employee or a customer and tounderstand what the intent is.
What is it being asked to do?
And to understand what theintent is, what is it being
asked to do?
And then to call on a number ofactions that sit inside of its
(12:51):
kind of toolkit and call theright one and, at the same time,
call the large language modelin the background to assemble
responses back to you.
So that may sound reallynebulous.
So let's go straight into acouple of examples.
The most obvious example iscustomer service.
You go to the chatbot on thewebsite for your credit card
(13:12):
company or your health insurancecompany or your you know, pick
any number of scenarios andyou're asking for help.
Why are you doing that?
Well, one, because we're kindof tired of calling call centers
in faraway countries andexplaining ourselves six times
after waiting on the phone andthen finding that they weren't
(13:33):
able to solve the problem.
Two, because normal chatbotsactually don't work.
All they do is just point youto the frequently asked
questions, and then you have toread reams of documentation and
find that you have to solve theproblem by yourself.
So now what we're, the worldthat we're in, is the chatbot is
actually driven by an agent,not a human, and the agent is
(13:54):
able to understand what you'reasking and go find the
information that will resolveyour problem if it holds it, and
it's using the llm in thebackground to basically blend
private internal information umin in salesforce.
Let's talk about this for asecond.
Salesforce is probably the onlyplatform in in the enterprise
(14:16):
business world that is able tooffer this agent force end to
end.
Why is that?
Because it's a unified platformthat's got your customer
relationship management data.
It's got your service data,including knowledge articles
about cases, problems, how weresolve them, what the questions
(14:38):
are and what the answers tothose questions are.
Nobody else has that integratedin one.
You know, one pane of glass.
And now it's got this Atlasreasoning engine, which is able
to understand your intent.
You've gone to that, to thechatbot, or you're texting, or
you're on the phone.
It's able to manage all ofthese channels and it's able to
(15:02):
go fetch internally and thenblend with a public AI
formulating the answer to you.
Now the first thing you mightwonder is what about your
private data?
Are you training a public AIwith your customers' data?
Well, no, you're not.
So Salesforce is taking greatcare to make your data safe and
(15:24):
to mask it.
They've done a whole lot ofwork on prompt defense and data
masking and zero retention sothat your data is safe.
So what's happening here is,essentially, we're able to carry
the luggage for the human teamand do the more base level tasks
(15:48):
and free them up to do morevaluable work.
Now, for example, you may beasking your credit card company
about a transaction that tookplace in Pakistan and you were
not in Pakistan this week, sothere's a problem.
And it was able to look it upfor you and able to to do so,
you know, to find it for you andtell you about it.
(16:09):
But the next thing might be thatmight actually be fraud and we
might need to hand it off to ahuman team.
And the agent is able to istrained, you've told it to do
this is to hand it off to ahuman and to basically prompt
somebody in the fraud team, forexample, to pick up the
conversation seamlessly.
You don't need to explainyourself again, you don't need
(16:30):
to reintroduce yourself, they'lljust take up the conversation
seamlessly.
You don't need to explainyourself again, you don't need
to reintroduce yourself.
They'll just take over theconversation and read the
summary of what the agent hasfound so far.
So let's think about that andunpack it for a second.
That's kind of revolutionary,isn't it?
So you've just got half yourproblem solved by a non-human,
by an autonomous agent, and nowthe human is jumping in and they
(16:50):
already know everything theyneed to know about where we are
so far and what to do next.
Speaker 1 (16:56):
Yeah, Mark.
I love that tangible examplebecause I feel like this is part
of the mainstream conversationof people saying, well, yeah, us
as consumers, we're going toget solved better, we're going
to get solved quicker.
There's so many big advantagesthere from a business
perspective.
I'm thinking well, we get touse our human capital in far
more intelligent ways.
We get to take them away fromsome of those those things that
(17:17):
just clog up their to do lists.
With that said, I also knowthat the macro argument is
what's going to happen to jobs?
Are they going to shift, Arethey going to change?
The answer, of course, is forsure.
It is what's your take on whatthe future looks like in the
jobs market?
Sure?
Speaker 2 (17:34):
well, brian, let's preface this by saying I, I am a
techno optimist, uh and uh, butthat has worked really well for
me.
Uh, so far, so um, I thinkwhat's happening is, you know,
you've got to look at job titlesand you know income streams
that exist today, that didn'texist 10 years ago or 15 years
(17:56):
ago Podcasters, influencers,youtubers, gopro influencers.
Those are just some examples,but there are many, many more
include inside of the bankingworld, inside of the healthcare
world, there are job titles thatdidn't exist before and that do
(18:17):
now.
So let's go back to theautomobile industry.
And how many people in thehorse and buggy industry thought
they were going to lose theirlivelihood.
But what they didn't see iswe're not just buying cars, we
have car mechanic shops, we havebody shops, we have car washes,
(18:39):
we have everything related tothe car industry.
The automobile industry hascreated a massive kind of
ballooning economy andessentially you can't argue that
there are not more jobs thanthere were before.
And this happens time and timeagain.
Same with, you know, 1993, 95,the birth of the World Wide Web
(19:01):
on top of the internet.
And you know there were thosepeople who said, oh, it's just a
fad, it's not really going tochange anything, and that's kind
of funny to think back now asthe people who thought that is
there going to be damage to thejob market before there is
growth?
Possibly yes.
We're seeing already the jobmarket is a little bit tough for
(19:22):
software engineers, lawyers andmarketers particularly, but
also for many other job titles.
They're kind of struggling atthe moment.
I think the business world haskind of decided hold on the
hiring for now, essential hiresonly.
We're not sure how this isgoing to play out and and there
are folks kind of seeing oh,they got laid off a few months
(19:43):
ago and it's it's not easy tofind the next.
The next thing, I think I heardan amazing line at a Salesforce
event last week was tomorrow'sjobs belong to today's learners,
and so that's suggesting that,you know, give ourselves the
(20:03):
flexibility to kind of changelane a little bit and use
bringing all of our skills andour experience, our knowledge,
just a little bit over here towhere we can see momentum, and
then we'll be rewarded for thatcourage and that curiosity yeah,
I love that answer, mark.
Speaker 1 (20:20):
Anytime people tell me ai is going to take away jobs
, that's the answer that I'mgoing to share with them right
there.
I think that the car analogy isis so fruitful, especially
because a lot of people pointtowards mechanics, but I love
all the auxiliary industriesthat you just pointed out car
washes.
There's entirely differentbusinesses, business models,
services, all of that that popup because of this, and so it's
really cool to think about allthe ways that we're going to
(20:41):
apply AI.
When I think about that, mark,one thing that always fascinates
me is kind of the yin and theyang, the balance on both sides
of things, because when you lookat a business, there's areas
where we can and should apply AI, but there's also that wisdom
and that experienced perspectiveof knowing where not to apply
AI, and I feel like that's kindof where we're at right now is.
(21:02):
A lot of businesses are askingwhere do we and where don't we?
Part of your job and part ofyour value add with Kynock is
that you assess businesses andyou look at them and say, hey,
let's start here.
What are you looking at whenyou look at a business from the
outside and when you get on theinside.
How do you assess where youshould be starting and where you
should?
Speaker 2 (21:21):
be building AI solutions.
Yeah, I love that question.
It's so much fun, you know.
So we start by saying we're notconnecting with as many
businesses ready to hit thestart button right now and say,
let's, do we want to spend X ona few agents that will do these
(21:42):
tasks and these and these jobs?
And we're ready.
And whether it's experimental,whether it's just a proof of
concept type of you know,putting some POC dollars into
something that is more of alearning experience or whether
we are assured success, we'revery confident we can design
this, build this and make itwork.
(22:02):
And I think that there's still alot of I wouldn't even call it
hesitation.
It's kind of still pondering dowe have to do this, do what if
we don't do it this quarter?
What if we don't do it thisyear?
Our argument is you willeventually be behind and either
(22:22):
be left behind or you'll have toplay catch up.
And it's hard to play catch upwhen the market is ahead of you,
when your competitors are aheadof you, and this is the moment
right now.
You're not behind If you'regetting started.
Started now looking at whatagents can do for you.
In start with a corner of yourbusiness and start simple.
We can talk about this somemore, like where do you start
(22:44):
and how and and?
How do you assess what would bethe the best couple of
candidates for agents to getstarted?
And then you're not behind.
Then you know the first agentthat you build is a fabulous
learning experience for yourentire company, and then it will
give you the confidence to say,wow, we were able to do that.
Now, where else can we putagent number two, number three,
(23:08):
and you know there isn't a setnumber of agents that you need
to have.
But you now have yourself asituation where your humans are
being assisted by autonomousagents.
And you've done it.
You're in the pool right Nowyou can start to.
You know, I say this a lot we'relimited by our imagination more
(23:29):
than our budget, more than ourlegal constraints or regulatory
constraints.
You know legal constraints orregulatory constraints.
The real constraint is can youimagine what will you do when
you can hire digital workforceagents?
You can basically extend yourworkforce digitally, without the
(23:51):
headcount and without thepayroll increment.
What will you do with them?
And so these are, these aregreat questions, brian, and so
I'll give you an example.
We, we've done.
We've done a number of fairlybasic, either employee support
or customer support, the service.
It's an obvious first place tostart if you, you know you've
got Salesforce up and running.
(24:12):
You use cases, right, you havecases for customer support.
Why not start with solving thesimplest and most, shall we say,
uninteresting cases for humans,make them interesting for
agents and then solve them?
And it will start off withsomething really, really simple
(24:33):
and prove that it works and thenexpand from there.
On the other end of the scale,we've got we're working on one
right now with a biosciencesresearch company, little startup
, and they're finding that theirmolecular research is really
manual and it's really laborintensive and they're accessing
(24:56):
a number of public databases tolook up organisms.
Imagine you start with the endin mind and you want to break
down hydrocarbon fuels infilling station sites after
they've been shut down.
You wanna grow a garden wherethere used to be a gas station,
where you can't right now, untilyou break down those diesel and
(25:18):
petrol residues.
Can I create a natural productthat would break down those
hydrocarbon residues withoutchemicals?
Well, let's find out.
And so they start researchingwhat kind of organisms have
those qualities?
And weeks later you've done,you know, hundreds of hours of
(25:41):
research on these publicdatabases and you've got
yourself a list of organismswhich, when put together, would
interact with each other to forma formulation that would
probably work.
And then you go into labtesting and you actually test it
.
So we're building an agent thatwill do a lot of that research.
Well, actually, you start bydescribing your end goal and it
(26:06):
will then go and access thosepublic databases for you and
bring back summary of its of itsfindings, which is incredibly
exciting.
When you think about, this isnot just doing a, you know, a
low level task.
It's kind of kind of gone up alevel.
It's not built yet, so we don't, you know, check in with us a
(26:28):
little bit later, but there's isone example of things getting
more ambitious, right and morevisionary.
Speaker 1 (26:33):
Mark, I love that, especially because the word that
stands out to me it's a word Iuse about my work a lot, which
is exciting, and hearing youtalk about these sort of AI
solutions.
What I hear is, obviously, I'mhearing you talk about the
subject matter itself, butgetting the chance to interview
you here today, mark, what I'mreally hearing and absorbing is
your genuine excitement.
You called it out earlier thatyou're a tech optimist, and so
(26:55):
for me, as a fellow optimist inlife and especially in business,
I know that what drives me isthat I firmly believe and deeply
believe that entrepreneurshipmakes the world a better place.
And it's so clear in talking toyou today that you also firmly
believe not onlyentrepreneurship but also AI and
technology can make the world abetter place.
With that in mind, mark, I wantto ask you about what motivates
(27:17):
you, because a lot ofentrepreneurs you know we face
all the ups and downs, andyou've experienced this.
This is your thirdentrepreneurial venture as well.
You're one of us.
I always remind listeners aboutthat.
What's that like as you pushforward through those ups and
downs?
Where's that entrepreneurialmindset kick in, and how do you
continue to have that drive?
Speaker 2 (27:37):
Sure, brian.
Well, you know, I think it'sscary in a really great way.
So when the world is moving sofast I mean the AI world is
moving so fast that, you know,as we sleep, we're missing news,
(27:59):
and we wake up, we catch up, weoh, that happened, um.
And so what I'm afraid of isthe crowd catching up, uh, with
with me and with, you know, withmy team, and suddenly everyone
knows how to do this stuff andwe're not differentiated.
So I think that's a reallyscary thing.
Um, the reason I'm not stilldoing the first venture you know
, I founded Benissimo in 2012,is we kind of had a different
(28:24):
purpose.
We were still, we were aSalesforce partner and we, you
know, we were very successful,but our mission was different
and we kind of accomplished thatmission, sold that company and
then did the second one.
So, you know, our mission thistime is to bring success with AI
(28:46):
, especially to the mid-marketcompanies who might still think
it's too expensive or too risky,and we want to take the risk
out of it while still beingquite visionary.
And the scary part is, you know, a lot of consulting firms tend
to cater to that risk-aversemiddle management sort of
(29:08):
thinking in the corporate world,you know, at the enterprise
level, at the Fortune 500 level,and we're here to connect with
the mid-market leaders who seethat they want to do this.
They're not quite sure aboutthe risk and the cost and the
probability of success.
So we have that conversationand we get them to a level of
(29:30):
comfort that says this is Xamount of dollars that you're
going to spend here and we'revery confident that we'll get
this to accomplish its statedpurposes.
Stated purpose, and from thereyou can layer on.
You're not done, but you've.
You've got success with yourfirst spend, right.
So I think it feels it feelsgreat to be doing this.
(29:53):
Our challenge is to find more ofthose companies where we have a
lot of conversations, wherethey're just not ready.
They're just, um, they they saywe love what you're doing and,
um, you know, give us more time.
We're thinking about this.
They're kind of thinking about,uh, do they have to?
Or they're also thinking like,which platform uh is the best
one for them and what's it goingto do to their operation?
(30:15):
And I think the biggest thingthey're afraid of is that they
have to keep spending more moneyto achieve the initial kind of
definition of success.
So it's a very exciting year.
I mean, I do believe that 2025is the year of agent AI and I do
believe that Salesforce isprobably the absolute best
(30:35):
platform.
Nobody else can really offerthis unified platform, on top of
which to put your autonomousagents and what Kind of Labs.
Offers is the visionary skillsthat a lot of consulting firms
don't quite have yet becausethey play it safe.
(30:55):
So we're not risky, we're justmore leading edge and we're able
to give you confidence that youwill succeed while adopting the
new stuff and not waiting forit to be mainstream.
Speaker 1 (31:08):
Yes, so well said, mark.
I keep coming back to itSomething you've already said
here in our conversation todayand it's going to leave a
lasting impression on me, andthat is we're limited not by
budget, not by resources, but bythat imagination.
And here it is again showing upin that visionary thinking that
you've obviously injected intothe way that Kynock operates,
and it's so cool to hear that.
So, mark, I've got one last bigchallenge for you.
(31:31):
It's the question I ask at theend of every single episode, and
that is what's your one bestpiece of advice, knowing that
we're being listened to by bothentrepreneurs and entrepreneurs
at all different stages of theirown growth journeys.
And also I know that from ourconversation today, they're all
going to be excited about thenew way, the more expansive way
to imagine, to dream big, tomake these things happen in
(31:51):
their business.
You're a fellow entrepreneur,so what's that one piece of
advice that you want to leavethem with today?
Speaker 2 (31:58):
Oh gosh.
Well, I think you look in themirror and you ask yourself, do
I have entrepreneurial bloodflowing through me?
And you know it's okay to havedoubt through me.
And you know it's okay to havedoubt, it's okay to sometimes
(32:19):
wonder, like, wouldn't I be justsafer with a, you know, a
regular paycheck and just staywith some big company where I'll
be safe?
Well, number one, nobody'sreally safe anymore.
You know, the job for lifething has been gone for a long
time and now, with you know theincreased kind of crazy pace of
business, nobody's safe.
So I think the safest place isactually to be a fast moving
(32:43):
entrepreneur who is very agile,very nimble and is able to kind
of not a U-turn but is able tokind of change lanes, um,
quickly and say it's over here,it's over here and it's.
That's not a pivot, it's just aslight adjustment to where we
thought we were going, and to dothat frequently and to be able
to, to, to say right, we're notwrong, but we need to adjust
(33:07):
slightly where we're going andwhat we're seeking and we'll be
okay.
And if we keep doing that, it'snot.
It's not even about money,although when we are successful
the money just takes care ofitself.
It's really about the um, thecuriosity, um and um and the
ability to see that we need tomake an adjustment every day.
Speaker 1 (33:30):
Yeah, so well said Advice.
Listeners, as Mark is sayingthat, I'm nodding my head the
entire time because I'm thinking, yes, we all have those moments
, Mark.
I can't tell you the number oftimes I've said wouldn't it be
easier to just have a paycheckevery single week?
Wouldn't it be easier to justhave an HR department that plans
out all of our benefit programs?
Wouldn't all that be easier?
(33:56):
But, holy cow, the juice is soworth the squeeze and you
encapsulated so well the realentrepreneurial mindset and the
real entrepreneurial ups anddowns in that answer and that
advice.
So I so appreciate you forsharing that with our audience
here today.
I also know that our audienceis going to be super keen to see
a lot of these things that youand I talked about.
See them in action, and I loveyour website.
One of the things that you andI talked about see them in
action, and I love your website.
One of the headlines rightthere on your website is are you
ready for agent force?
Learn more and seeing all thematerials that you've put
(34:19):
together about why it's sopowerful to hire an agent.
I put hire in quotes becausethese are things that we can
build for our businesses Thanksto visionaries like you.
So, Mark, for those listenerswho want to go deeper into your
business and all the great workyou're doing, drop those links
on us.
Where should listeners go fromhere?
Speaker 2 (34:37):
Stay curious.
So, again, you know, tomorrow'sjobs belong to today's learners
and they're not necessarilyjobs there.
They might be entrepreneurialventures.
And I would say you knowsomething?
Um, there's always stress inlife, no matter what you're
doing, right?
Yeah, I mean, you could be akid playing soccer and it's
stressful because you're doinghard things and you might lose,
(34:59):
and that's terrible, right?
So, um, stress is good.
Uh, pressure is privilege.
Now the the time, the kind ofstress that I was never able to
shake off, the kind of stressthat I was never able to shake
off, was the corporate frictionbetween people, sharp elbows and
, you know, somebody kind ofputting a thumbtack in you, so
(35:26):
just kind of making your daydifficult unnecessarily.
I was not able to shake thatoff.
Whereas the stress of running acompany and just cash flow and
you know, are we going to winthis next deal, are we?
There's a project that's runinto a, you know, a problem.
You're always going to havethese, you're always going to
have these things.
But that stress I can managebecause I can make decisions and
(35:46):
I have the scope to navigatefrom here through challenges,
and I think it's much lessstressful to do that than to be
in an environment where I don'thave access to.
I can't change my environment.
I can either leave or I canstay and tolerate it, and that's
not good for me.
Speaker 1 (36:07):
Yes, spoken like a true entrepreneur.
Mark, I love hearing yourperspectives on that.
Listeners, you are in for sucha treat because we are dropping
the links to Mark's businesswebsite, to his personal
LinkedIn, down below in the shownotes.
No matter where it is thatyou're tuning into today's
episode, you'll be able to go somuch deeper into a lot of these
things that we've talked abouthere on the air, on his website
(36:28):
and if you want to continue theconversation, you heard that
Mark is very keen on havingconversations with business
leaders who want to startimplementing this stuff not
thinking about it, not beingaware that it's out there, but
actually implementing it.
So we're dropping a link to hispersonal LinkedIn down below in
the show notes.
Otherwise, mark, on behalf ofmyself and all the listeners
worldwide, thanks so much forcoming on the show today Super
(36:51):
fun.
Thank you, brian hey, it'sBrian here and thanks for tuning
in to yet another episode ofthe Wantrepreneur to
Entrepreneur podcast.
If you haven't checked us outonline, there's so much good
stuff there.
Check out the show's website andall the show notes that we
talked about in today's episodeat thewantrepreneurshowcom, and
I just want to give a shout outto our amazing guests.
(37:12):
There's a reason why we are adfree and have produced so many
incredible episodes five days aweek for you, and it's because
our guests step up to the plate.
These are not sponsoredepisodes.
These are not infomercials.
Our guests help us cover thecosts of our productions.
They so deeply believe in thepower of getting their message
out in front of you awesomewantrepreneurs and entrepreneurs
(37:35):
, that they contribute to helpus make these productions
possible.
So thank you to not onlytoday's guests, but all of our
guests in general, and I justwant to invite you check out our
website because you can send usa voicemail there.
We also have live chat.
If you want to interactdirectly with me, go to
thewantrepreneurshowcom.
Initiate a live chat.
It's for real me and I'mexcited because I'll see you, as
(37:58):
always every Monday, wednesday,friday, saturday and Sunday
here on the Wantrepreneur toEntrepreneur podcast.
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