September 3, 2025 • 46 mins
Founder and CEO of Robo Source, Jason Beutler, joins Risk and Resolve to share his journey from failed startups to building a thriving automation and AI-driven consulting firm. Jason breaks down the truth about artificial intelligence, how business leaders should think about AI, and why his mission is centered on empowering people—not replacing them. We explore the evolution of technology, the misconceptions around AI, the art of prompting, and the role of meaningful work in company culture.
Main Talking Points:
• Jason Beutler’s entrepreneurial journey and lessons from early business failures
• How Robo Source evolved from consulting to holistic workflow automation
• The biggest misconceptions about AI and what it actually does
• How to create effective prompts for ChatGPT and other AI tools
• AI bias, truth, and why human-like responses matter
• The role of AI as a tool versus a business strategy
• How automation can empower teams to focus on meaningful, impactful work
• The accelerating pace of technology and where it’s headed
• Communication challenges and lessons learned as a business leader
• Jason’s future vision: transitioning from consulting to a product company
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:01):
You're listening to Risk and Resolve, and now for
your hosts, Ben Conner and ToddHufford, Welcome back to another
episode of Risk and Resolve.
Today we are blessed to havethe brilliant Jason Butler join
us from RoboSource.
Jason is the founder and CEO ofRoboSource, a company
(00:23):
specializing in processautomation and AI-driven
solutions to help businessesstreamline operations and
improve efficiency.
Jason, thanks for being with ustoday.
Speaker 2 (00:36):
Hey, thanks a lot, Ben Looking forward to it.
Speaker 1 (00:38):
Yeah, so it looks like you founded RoboSource back
in 2012.
Tell us about the reason andthe why behind starting
RoboSource at that time?
Speaker 2 (00:53):
Well, there's probably two things that were
driving me at that point.
I had started and failed threebusinesses prior.
So from 1998 to 2006, I hadstarted well, 98 to 2003, I ran
a business, learned everything,what not to do.
In that timeframe I basicallyran it into the ground and was
(01:15):
not super successful with it.
I ended up starting anotherconsulting business about two
years later, from 2005 to 2007.
Wasn't super successful, wasn'treally growing it, but was
doing essentially a lot ofindependent consulting, and so I
decided that I wanted to.
If I was going to do this, Ihad to learn what I was, how to
actually do it.
So I went to the University ofNotre Dame and got an MBA, most
(01:36):
specifically so that I couldstart a business and know how to
run it.
So when I graduated from that,we set ourselves on the path to
start a business.
You know, I'd like to say I satdown and thought here is a gap
in the market and I've got asolution and I'm coming at it.
Really, that wasn't the case.
I am an entrepreneur throughand through.
I'm a creative engineer and theidea of working for somebody
(01:59):
else just wasn't sitting greatwith me and I just I needed to
go after it, and so that'sreally was the impetus behind it
.
So in 2010, I actually went outon my own and started doing
some of my own independentconsulting, ended up starting to
get more and more successfulwith it.
I'd learned some of the toolsthat were necessary and by 2012,
we officially formed RoboSourceand have been growing it ever
(02:21):
since, and over time, as youlearn more about yourself, you
start to realize really kind ofwhere you fit in the market, and
that's where, for us, it'sabout helping people do
meaningful, impactful work, andthat's really what resonates
with us is we want to.
I don't know.
I feel like most people.
When they wake up in themorning, they don't think, man,
I can't go away to put a bunchof numbers in this spreadsheet,
(02:42):
but they're like if they couldhave an impact or talk with a
person or engage with somebodyon a human level, that's what
motivates them or they could dosomething strategic, creative.
So that's really whereRoboSource came from is how can
we get some of that mundane,repetitive stuff off your plate
(03:03):
so you can do the impactful,meaningful things that are why
we actually get up in themorning in the first place, and
so that's really what's kind ofevolved and driven us for the
last 12, 13 years?
Speaker 1 (03:07):
now I know that this is a business that you've
partnered with your wife ingrowing.
Tell me about that, because itsounds like you started in the
consulting realm, which mighthave been you individually, and
then this endeavor you knowincluded your wife.
Tell me about that genesis andhow that came to be.
Speaker 2 (03:24):
So again I'd like to say it was strategic.
It was probably more of anaccident and came out of
necessity really so starteddoing a lot of consulting, was
starting to build a name formyself on that front, started to
get more and more opportunities, and in order to meet those
opportunities I needed to bringin additional people, and so
started bringing in othertechnology focused individuals
(03:46):
to help me deliver on thepromises I was making to clients
.
I think we're about two orthree years in at that point and
my wife goes have you done?
And she listed out all these HRtasks that were like apparently
necessary to hire someone.
And I was like I don't reallyknow what you're talking about.
And she's like I'm afraidyou're going to go to jail.
I'm going to take over all ofthat.
So she came in and organized allof the stuff that needed to get
(04:09):
done right the compliancethings, the things that actually
are driving a business.
And so again I here I paintmyself as this like
absent-minded professor type ofrole, but that's really.
I mean, I really kind of amthat I'm.
I'm an engineer, my focus ishow to apply technology to help
people and a lot of the rest ofthe stuff I kind of lose track
of.
And so my wife is a very detailoriented, business minded
(04:30):
individual that came in and said, hey, let's, let's get the rest
of the business kind of inorder, and she made a lot of
that to happen.
And so I think she came in in2013, 2014, and really started
to make that, just took thatunder her wing and they really
is the reason why we've grownand been successful as we are is
because she just keeps that allunder control.
Speaker 1 (04:49):
That's awesome.
You know, our spouses tend tocover our weaknesses and their
strengths and God bless us forit.
Yes, so you've been in, likethe advanced technology
automation robotics, if you will, for a long time.
If you don't mind, like startfrom today, of like what does
(05:10):
RoboSource look like today, frombusiness application versus
maybe what it was when youstarted and went down this path?
Speaker 2 (05:20):
Yeah, so today is a lot more focused on so we're
really.
What we end up talking about isdigital transformation.
So how do you take yourbusiness that has been operating
successfully but is maybeoperating more manually than
digital?
So by that, most businessesstart off figuring out how to
solve a problem and they putpeople in positions to solve
(05:41):
those problems.
We're not thinking about how dowe build the most efficient,
optimal computer program to makethat all work.
We're thinking about meetingour clients' needs and we do
that by getting people doing thejobs that need to get done.
So today what we do is we comein and we look at those
processes, we look at what'shappening there and we identify
(06:01):
what transformation needs tohappen in order to hit the
business need more effectively,like what does the client really
want and how can we transformour business in order to be able
to meet that need moreeffectively?
So, yes, do we use high-endtechnology?
Absolutely, why?
Because artificial intelligenceis a really powerful tool and
it does some really amazingthings and most people have no
(06:23):
idea what it's even capable ofdoing.
So someone like me that hasfigured out the business side
but came from a technology sidecan help do that translation
from here's what technology iscapable of doing and here's why
you should care and what it willdo for your customers at the
end, because, at the end of theday, that's really why we're in
business.
So that's where we're at todayis really helping look at that
(06:47):
path, looking at that map andapplying and kind of
transforming the business to bereally effective at rolling out
the kinds of solutions thatreally their customers want.
And yeah, we use artificialintelligence almost exclusively
these days because of thecapabilities that it has.
Contrast that to let's go backto 2012.
Ai has been around for a verylong time.
(07:08):
So I studied it in the 90s.
The principles of thetechnology has been evolving for
a very, very long time, in themid in the 2000s into the early
2010s.
The primary form of AI there'sa lot of predictive analytics, a
lot of some of the basicmachine learning, and you see
that on like Amazon, right, likeyou go to Amazon and it says
10s.
The primary form of AI.
There's a lot of predictiveanalytics, a lot of some of the
basic machine learning, and yousee that on like Amazon, right,
like you go to Amazon and itsays people who bought this also
(07:31):
bought other things like this.
Well, that's a form of AI.
It's using some predictive mathto figure out how to make that
all happen.
There's another form of AI thatI spent most of my career in,
and that's expert systems.
And what an expert system is,is it essentially?
Well, the one that I rolled outspecifically was it would
capture a bunch of facts abouthow a business should operate
(07:51):
like or actually a better way tothink about it.
It would be like, say, a doctor.
If you're to capture a doctoras an expert, you might say
things like if your nose isrunning and you have a fever and
you're achy, we're going toassert that you might have the
flu.
And so we create a whole slewof these facts that would exist
(08:12):
inside of a system, and thenwhen someone came in, they could
basically answer questionsabout themselves asserting
certain information oh, my noseis running, no, I'm not achy.
So it would then kind of decidewhich of the outcomes would
happen from there.
So I wrote quite a few of toolsaround that technology, and
that's really where we kind ofstarted was on this expert
system level, but at the end ofthe day, most of it ended up
(08:35):
being pretty low level in mymind, pretty low level software
just to automate some of thebasics, things like you're
probably used to seeing online.
Actually, most people use todayright Like QuickBooks Online or
tools along those lines.
Those are forms of automationand they really do help speed up
a business and make a businessmore effective.
They're not taking entireworkflows and automating them.
(08:58):
They're taking bits and piecesof it and making those tools
more effective.
So we went from a lot ofindividual bits and pieces of
tools to a more holisticworkflow type solution over the
last 12 to 15 years.
Speaker 1 (09:11):
Yeah, it almost seems like.
Yeah, point-in-time solutionsare becoming more systematized
you talked about.
You know most people don'ttruly understand AI or how
automation really works.
Like how would you describewhat most people think about AI?
Like this is the preconceivednotion that everyone has, versus
(09:35):
like this is what peopleactually should know, as they're
like getting into the realm ofthis kind of a conversation.
Speaker 2 (09:44):
Yeah, so marketing has done a really good job of
making you think that artificialintelligence is actually
intelligent.
So most people think that theartificial intelligence, the AI
let's say, chat, gpt, gemini,claude, any of those they
believe that that tool isactually thinking they believe
that that tool is actuallythinking, meaning it's
(10:05):
assimilating its own thoughtsbased upon prompts that you're
giving it, and that feels alittle magical.
At the end of the day, though,that's not really what's going
on.
What we've done is we've takenthe sum total of all the
knowledge that we have writtenon the Internet and we've put
them together into bigprobabilistic models, and so, at
(10:27):
the end of the day, it's a mathequation that is tuned to say
what do you want to hear, andI'm going to try and figure out
how to give that to you.
So it's going to look at all ofthe stuff we put on the
internet, all the words we puttogether, and it's going to try
and figure out what the next setof words should be to give you
the outcome that it thinksyou've asked for.
(10:48):
And the way that it determineswhat it thinks you've asked for
is also a mathematical equation.
So it's not really thinking,it's spitting back to us what we
have historically, through abunch of patterns put all over
the internet for the last 20years.
So is it biased?
Well, are humans biased?
Like yeah, it is, because whatyou're going to read on the
(11:10):
internet is probably biased Like, does it hallucinate?
Well, yeah, do humans.
And at first you're like no, wedon't hallucinate.
Well, you kind of do, though.
Like I think about last weekwhen I had a conversation with
my wife and all of a sudden I'mtexting her and all of a sudden
the text goes cold and likeshe's not responding anymore.
What did I just?
What do I do?
(11:30):
I started telling myself awhole bunch of stories, like I'm
sitting here going like oh, Ijust said something that really
irritated her.
What did I say?
I started scrolling, like whatdid I do that?
Oh, no, what's going on here?
And then she's like sorry,ended up getting interrupted.
(11:52):
Here's what I think I was likeoh, right, right, we hallucinate
too.
Given lack of information, wemake it up.
So dai is doing the same thingwhen it has lack of information.
It has seen patterns of usmaking it up, so it makes it up.
So the thing that I wish peopleunderstood is that, because
it's predictable.
You therefore can't control it.
Because you you can't controlit Like because it is a
mathematical equation, we can'tactually drive it towards the
outcome that we want.
It's not like a human in itsentirety, where it's completely
(12:15):
unpredictable and you can, youknow, feel like you communicated
with it really clearly and itdoesn't understand or it goes
different directions.
You have a lot more controlover this than normal If you're
working with a normal individual.
Speaker 1 (12:28):
A lot more consistency.
It's not going to get caught upin emotions of things or
otherwise, because it's workingoff of that main foundation.
One thing you brought up I kindof find interesting and since
you opened the can of worms I'mgoing to go there Just the idea
of truth in AI.
I think there's a lot of fearabout explicit bias being
(12:49):
influenced into AI.
What's your take on that?
Speaker 2 (12:53):
It's a reflection of humanity.
It's literally mimicking thesame patterns that we put into
it and I don't know that you'reever going to take that out,
because it's always going to bebased upon human communication
patterns and human communicationmodels.
I'm also not sure in itsentirety that you want to take
it out, because if you took thatout, it wouldn't feel cute and
(13:14):
it wouldn't feel intelligent.
I think that part of theconversation that happens with
people is that we we pick up on.
You were raised in a differentplace than I was raised.
You have different experiencesthan I have.
That's part of what makes youinteresting to me, and if we
took all of that out and reducedthis all down to whether or not
we can have a logical,consistent, straight, 100% true
(13:36):
conversation, it's not a veryinteresting relationship we're
going to have, and the reasonwhy AI is reflecting a lot of
that is because that's whatmakes it feel human and that's
what we want in ourconversational AI when it's
having a conversation with us.
We want it to feel human, wewant it to have opinions.
Unfortunately, because we'rehuman, we want it to have our
(13:57):
opinions and so, as a result, weget a little bit worried when
it starts reflecting opinionsthat aren't ours.
But that's part of humanity.
And in my mind, how great is itthat I can go in and I can
prompt an AI because I cancontrol this one.
I can prompt it to take theulterior viewpoint of something
(14:18):
that I have and allow me toengage that in a non-emotional
way, where a human is notengaged, so I can actually
explore my own emotions on that.
That's pretty powerful.
That allows you to do things interms of your own personal
development that you can't dobefore, because you now can
explore the counterpoints toyour own way of thinking.
Speaker 1 (14:38):
What an interesting way to potentially prepare
yourself for a situation thatmay be a little unknown, if
you're going to have aconversation with someone in a
different job, role or, to yourpoint, from a different culture
or otherwise.
But you mentioned the wordprompt, yeah, and I think that
that when I think of AI or evenengaging with chat GPT,
(15:00):
sometimes I'm like I don't knowif I am setting it up correctly
and I don't know if this is areasonable question.
But like, how should peoplethink about like prompting, a
chat GPT or using the rightsetup are using the right setup?
Because I think when you gointo it, you at least I'm going
to speak on behalf of me like Ikind of think of chat GPT as
(15:23):
like interfacing with Google,which is like find me this, well
, there's no prompting to that,it is just going to spit back
something.
How do you see prompting, orwhat are the best ways to use
prompting to get a better useout of like an AI, an AI setup?
Speaker 2 (15:40):
So it is interesting.
That is how most peopleapproach it, and the first time
they get it in front of a chattype of AI is they just start
asking it questions like theywould Google, and it actually
doesn't do a very good job ofanswering those, because at
least a lot of the currentmodels are delayed by months of
the amount of information theyactually have access to.
(16:01):
Now some of the new ones willallow you to connect and
communicate with the Internet aswell, but it's essentially
doing a search for you.
So the prompting idea, whatyou're trying to do with the AI
is you're trying to give it thecontext that it needs to
understand why you're asking thequestion you're asking.
And there's a lot of mathbehind this and it's really
(16:23):
fascinating.
There's this concept calledembeddings that essentially turn
your language into mathematicalequations.
Then, because you now havethese mathematical we call them
vectors and you can thinkexactly like you know physics
vectors from high school Becausewe now have these mathematical
vectors, we can now doessentially similarity searches
(16:43):
based upon the vector to bringback information.
That's the same.
So what you're trying to do isyou're trying to give the
language in such a way that themath will know how to pull back
things that are the same.
So what we want to do and we'reprompting is we want to give it
a couple of things.
We want to first tell it therole that it's playing, and more
prompting is we want to give ita couple of things.
We want to first tell it therole that it's playing.
We want to say, hey, you'regoing to be a business
(17:04):
consultant that is helping mefigure out my go-to-market
strategy.
You gave it context.
You just gave it some wordsthat allow it now to go find
information that is aroundbusiness consulting and
go-to-market strategy.
It's then going to pull thatdata back and start to use that
as its mechanism to answer yourquestion.
Then the next thing you want todo is you want to give it
(17:26):
step-by-step reasoning.
You want to say, first I wantyou to do this, then I want you
to do the next step, then I wantyou to do the third step, and
the reason you do that is eachof those is going to give it
context on what to pull back,but you're also telling it the
order of how to go about doingthat actual work, and so
step-by-step reasoning tends togive you a better result.
(17:47):
Finally, the third area that Ifind to be really effective is
they call it few shot training,but it's basically giving
examples and then what you wantto see back.
So hey, as a businessconsultant, you're going to help
me figure out my go-to-marketstrategy.
Here is a paragraph of thoughtsand ideas about my business and
here's what I would come backwith if I were you.
(18:08):
Now here's another idea Usethat same model and come back
and give me the information thatyou pulled for me so you can
give it training.
You can say essentially example, here's my input, here's my
output, and do that a couple oftimes and then when you ask it
the next question, it will usethat example to kind of
(18:28):
formulate how you want to seethat response.
Speaker 1 (18:31):
Wow, that's really good.
What kept coming up in my mindwhile you were talking is that's
probably exactly how I shouldprobably set up my training for
anyone internally, and it's notlike specific and regimented,
which potentially goes back toyour point about it.
It really isn't intelligent asmuch as it is, like you know.
(18:56):
If you give it the guidelinesof how to think, it can think
really well or it can producethe results that you're.
It's not even thinking.
It's producing the results thatyou're really looking for.
Speaker 2 (19:08):
Yeah, A thought that I've been playing with in my
head for a while now is what isintelligence Like?
When we say, oh, that person'sreally intelligent, what are we
really referring to, and that's.
It's just.
I've been playing with it andI'm sure there's a whole bunch
of psychologists out there thathave studied this.
I haven't, but what I keepcoming back to is the people
(19:29):
that I think are intelligent arethe ones that can recall
information really quickly rightoff the top of their head.
When I say something like Ican't, I start talking about a
business, a business concept.
I'm't I started talking about abusiness, a business concept.
I'm like man, from a marketingstandpoint, I wish I could do
this.
And they go oh, you know what,this book said this and this
book said that, and they startreferencing experts on how to do
it.
I'm like really smart,well-read people, and that's why
(19:50):
I think we start to confuse AIwith intelligence, because it's
way better at recalling thingsthan we are.
So it can go, pull all thatinformation instantly and then
spit it back to us.
So we go really, really, reallysmart system, but it's just a
recall mechanism and it's justrecalling it in a way that is
(20:12):
more natural for us to interactwith.
I think the actual intelligencecomes into the creative
application of it, and that'sjust now starting to emerge in
some of these AI tools, butcurrently they just recall
information really well, whichis what makes it feel like it's
intelligent.
Speaker 1 (20:26):
And they have a broad spectrum of where it can go to
recall information or to accessinformation quickly.
When it comes to AI, likespecifically like business
leaders you know we talked aboutthe general person of like how
(20:47):
should they think about maybe AIa little bit differently or
where do they get it wrong?
But how should business leadersthink about the context of AI
and then how it can actually beimpactful into their business?
Speaker 2 (20:55):
Yeah, one of the things that I'm really
passionate about is the factthat AI is a tool, and it's just
that it's a tool.
So, as a business leader, whatproblems are you dealing with?
They need versus they needsolutions, like like that's
where that's where we start is.
We don't start with I need touse AI in my business or I'm
(21:16):
going to get left behind.
No, you're not.
Like it's a tool Like what inmy business?
Or I'm going to get left behind.
No, you're not.
Like it's a tool Like what inyour business is keeping you
from scaling?
What tools might exist to makethat more effective?
Maybe it's AI, maybe it's not.
But let's shift our thinking tosay I'm afraid I'm going to get
left behind from this AI wave,and instead say no, what's
(21:37):
keeping my business from growing, and let's find the right tools
to fit to help solve thatproblem.
That's the big shift that Ithink CEOs need to think about.
Speaker 1 (21:50):
Do you think that's the unlock that's happening with
the craze on AI?
Is that it's leading to thatquestion?
Speaker 2 (21:53):
and then businesses can actually get better.
That's what I'm hoping.
There's still a lot ofbusinesses I talk to come to me
and they're like I don't want toget left behind.
What do I need to do, Tell me,and I'm like that's the wrong
question, Like you're settingyourself up for massive failure
because I can put AI into aboutanything.
It doesn't mean it can actuallychange anything.
So let's, let's talk about thatfirst.
(22:13):
Then the second thing is tostart to understand what.
What is the tool good for?
If you've got a hammer and Ihand you a screw, it's not going
to work real well.
They're not made to worktogether.
So what is it really good at?
And some of the things that AIis really good at, and I'm just
going to sum it up in onesentence.
There's a lot of nuance aroundthis, but what AI is really good
at is evaluating text.
(22:39):
In my world I call thatunstructured data, so not like
databases where you've got lotsof formal relationships.
I'm talking about like I got anemail and I want to be able to
understand what's going on inthat email.
So AI is really good atevaluating text.
And then, as a result, becausewe're human and most of our
communication happens inunstructured textual formats.
Human and most of ourcommunication happens in
(23:01):
unstructured textual formats.
Emails, word documents,PowerPoints, PDFs like Excel
files, Like those are allenvironments that pretty much
run business.
80 to 90% of all of ourinstitutional knowledge exists
in unstructured formats that AIis now unlocking, that allows us
to work with and sounderstanding that that's the
tool and that's what it's usedfor right now.
Speaker 1 (23:22):
Another question just about AI in general, and then I
kind of want to go back toRoboSource in particular and
your mission, but it seems andmaybe it's not true, but it just
seems that the last 12 monthsor 18 months has been way more
ridiculous in the tech worldthan even before.
(23:43):
One, is that true?
And then two, like where istech headed in the foreseeable
future from your perspective?
Speaker 2 (23:51):
It's been in the news a lot more than it has been
historically over the last 10years or so, but I don't really
think that it's accelerating ata pace that is outside of
everything it's been doing forthe last 20 years.
It's an area that, for one Ithink AI captures our
imagination.
You go back to the Terminatorseries right when was that?
Early 90s?
And it's like ooh, ai isrunning the world, like that's a
(24:14):
sci-fi concept that we all kindof like geek out about a little
bit, and so this now isstarting to kind of feel real.
So people want to engage thatstory.
Speaker 1 (24:25):
My story, by the way, is iRobot.
That's the movie that I waslike that is crazy.
And now it's happening, Like, Ithink, elon's robots even look
like the iRobot robots.
Anyway, go ahead.
Speaker 2 (24:39):
So there's part of that, just the human interest
piece, right when we care aboutit more because it just is
sci-fi and cool and I mean Igrew up on Star Wars.
I can't wait to have a droid,like I want one, like you know.
That's the kind of mindset thatwe're getting out of that.
So it's fun to imagine about,to imagine about.
But technical technology hasbeen basically accelerating at
(25:00):
that speed for the last 20 yearsanyways, um, going forward,
there are a lot of things thatare coming.
I mean you think we've beengoing fast.
We're gonna be going way faster, partly because ai is good at
unstructured data and it is goodat finding patterns, so it's
gonna find patterns faster thanwe can.
So pharma and biotech like it'sgonna find patterns way faster
than scientists can.
So pharma and biotech, it'sgoing to find patterns way
faster than scientists can andthey'll allow us to experiment
(25:22):
with a whole lot more compoundsthan we've ever thought we could
.
Before you start getting intoquantum computing I don't know
if you've read much about that,but there's some crazy things
going on with quantumentanglement and being able to
show teleportation in thequantum realm and that's how
that's translating into thingslike maybe potentially faster
than light communication.
(25:42):
That's all a little speculativestill, but we're starting to
see some things that mightactually indicate that could
happen.
So there's some crazy thingsthat are happening on all these
different sides, and I think theability to identify patterns
faster from using the technologythat's being developed right
now is going to greatlyaccelerate that in terms of how
(26:03):
much and how quickly we bring innew technologies.
Hopefully we should see thatreflect in human standard of
living.
If we can get compoundsdiscovered faster and tested
faster and through clinicaltrials faster, can we bring
cancer drugs to market faster.
That's pretty cool.
That impacts lives, you know.
(26:23):
Same with communication.
If we can communicate evenfaster, like right now we're
able to do.
You know the internet and I cancommunicate around the world
within seconds.
What if it was milliseconds?
When does that change and whatcan we do as a result of that?
So yeah, I think you're goingto see technology really take
off and we're really just kindof at the beginning of this
information age.
That's going to just sort ofaccelerate.
(26:44):
Let's be honest, ai is stillpretty in fit.
It's still not.
I mean, it's smart, but it'sstill not very smart like the
dumbest it's ever going to be,so we need to prepare ourselves
for it.
We know what that looks, butwe're still really early.
Speaker 1 (26:59):
You're right, because I even see, like, when people
do like AI, like images orsomething, where things are like
misspelled wrong or there'slike an arm coming out of
someone's head or something likethat, when AI gets really good,
what type of like securityissues?
Speaker 2 (27:16):
might we have.
Oh, security is a huge problemalready, but it's not just an AI
problem, it's a problem withall digital information, and I
mean cyber has been an issue fordecades now, right, and it's
not getting better with AI.
There's a whole slew ofinteresting questions around
intellectual property and whoowns what, and I'm intrigued to
(27:37):
see what happens in the legalsystem around that, because
there's just not a lot ofprecedent around it to the not a
living being.
Speaker 1 (27:45):
You can't break laws that don't exist, right?
So you're just pressing forwardand then you discover the
problems later, right, Yep?
Speaker 2 (27:52):
And then we create laws retroactively and some of
it will be right and some of itwill be really wrong.
Speaker 1 (27:57):
Yeah, well, yeah, because laws are passed by
people who really don't evenunderstand the thing.
Speaker 2 (28:02):
Yep exactly.
Speaker 1 (28:03):
Whoever gets to them and prescribes some of that?
What's the fix on security fromyour perspective?
What should lawmakers consideraround that?
Speaker 2 (28:12):
Take the internet the internet is probably one of the
single most impactfultechnologies to ever hit
business in terms of like whatit's actually done to the
business world business in termsof like what it's actually done
to the business world.
But, yeah, it's also one of themost vile tools on the planet
in terms of the horrible thingsthat can happen on the dark web.
Right, and how do you controlthat?
(28:34):
We have the same problem, onlyworse, with AI.
It's probably going to be oneof the most impactful tools on
humanity and business, but it'sgoing to have a dark side to it
too, and so we didn't figure itout with the internet.
We're still trying to figure itout, and so I think you're
going to have the same problemwith AI in terms of how you
control and manage the securityaround it.
(28:55):
Now, I think, from a businessstandpoint, you can do certain
things to manage your risk Sameas with the internet, right,
like VPNs and firewalls, andthere's tools that we can put in
place to help manage our risk.
They're not foolproof there'sstill some risk involved but you
can do things to be safer inthe way that you interact with
the internet.
You're going to be able to dothe same thing with AI, in that
(29:17):
there are concepts like they'restarting to come around they're
called guardrails thatessentially will look at the
prompt that you're putting inand the information you're
sending into the AI and say, hey, whoa time out.
There's no security number inhere.
Let me just go ahead and aliasit to a non-real one and then
I'll send it out to the AI, andwhen the AI gives me a response,
I'll go ahead and swap it backfor you.
(29:39):
So that way we're not sendinginformation out on the internet
that it shouldn't be, but you'reable to interact with it as
though it did.
Speaker 1 (29:48):
Yeah, that's definitely important to keep
private information and thosesorts of things out of these
LLMs.
So let's go back to RoboSourceand what you guys are doing in
particular.
What you guys are doing inparticular, one thing I find
just incredible is the missionalaspect of taking something that
(30:10):
is so technical, likeautomation and AI and that sort
of thing, and tying it back tohow are we impacting the society
or workers, because it'd beeasy to say this is a worker
replacement, but that's not whatyou say.
You say no, we are actuallyempowering your current
(30:32):
workforce to do more meaningfulwork.
So when did that occur to youof like, this is really what
we're doing and this is reallywhat we're pursuing.
Speaker 2 (30:41):
You know, I don't know that I ever thought
otherwise, and part of that isbecause I guess I just believe
in the value and the meaning ofwork and that I believe that we
want to do things that feelconnected to our like, we want
to be a part of a team, we wantto engage on that level, and so
I feel like every business isgoing to have an issue.
(31:02):
Every business has people thatwant to feel like their job is
important and want to feel likeevery business is going to have
an issue.
Every business has has peoplethat want to feel like their job
is is important and want tofeel like they're contributing
and that's what brings meaningto them.
And it's not the same foreveryone.
Like my grandfather worked on aassembly line and you know, for
him he's bolting things into acar and I don't even know what
all he did, but he's puttingthis all in.
But at the end of the day, whenyou asked him what he did, he
(31:25):
was making cars safe for kids,like that's why he was there.
That was his meaning.
Like it was meaningless workbut it wasn't meaningless to him
.
And so I guess from thatperspective, I come in and I say
, hey, what is meaningless toyou and what can we get off of
your plate so you can do thethings that add meaning, because
I think that's how people aredriven.
I also don't buy into this myththat all these AI tools are
(31:46):
going to replace people.
I don't think you can replacerelationships.
Business is not done off oftechnology.
Business is done off ofrelationships with people.
Even Amazon, who has automatedbasically the entire buying
cycle, at the end of the day,what do we still make our
decisions off of?
The reviews at the bottom ofthe Amazon product that's human,
(32:07):
like those are human to humanrelationships that are making
that decision.
Now, they were able to do thatin a more efficient way, but
they still put the humanresponse in front of us for us
to make a decision off of.
So I don't see that going away.
So I think if you're a businessthat's trying to make it go
away, I think you're going tofind that you actually push away
the very people that you triedto serve, because they want to
have a human relationship withsomething.
(32:28):
They want to have a creativeconversation.
So it always felt to me likethis was a tool to empower
humans, not a tool to replacethem.
Speaker 1 (32:36):
You've been leading RoboSource for, I guess, going
into 13 years.
What have been some of thebiggest learning lessons or
takeaways from your perspectivein leading and running the
business itself?
Speaker 2 (32:51):
I'm not a very good communicator and I think I am.
But it comes right down to itwhat I think I'm telling people
and what they're hearing isn'tconnecting, and I have to really
really work on communication.
At first I thought that wasmaybe unique to me, because I
tend to be an engineer and so Imaybe think a little too
engineering.
But the more I talk with otherbusiness leaders, the more I
(33:12):
think that that's just a humancondition, is that none of us
are really communicating what wethink we're communicating, or
maybe say to differently.
People aren't hearing whatyou're saying because they have
their own filter.
They're putting it through andso you have to repeat over and
over and over again in variousdifferent ways and formats for
it to actually connect withpeople so that they're able to
do and get in line and aligntheir efforts with where you're
(33:36):
trying to lead an organization.
Otherwise you have everybodypulling in different directions
and it's chaos and it's chaos.
So I've learned that I have alot more work to do to learn how
to communicate effectively withpeople and make sure that the
message is being received.
That's one area that I'velearned a lot on.
I've also learned that the besttechnology doesn't make the best
(33:56):
solution just because thetechnology is superior and
effective and can do some crazyamazing things, it doesn't mean
that it's the right tool for theorganization or the company.
Either they're not ready for itculturally, or they're just not
positioned to take advantage ofit, or they're skeptical in
some way, shape or form.
Like just because I have theright solution and you've got a
(34:19):
nail and I've got a hammer and Ican come in and just pound that
thing right for you, but that'snot what they're ready to do.
And I've got a hammer and I cancome in and just pound that
thing right for you, but that'snot what they're ready to do.
And if you don't get people onboard with the transformation,
then it doesn't matter whattools you put in place, they
will not use them.
And so this isn't a technicalproblem, this is a person, this
is a human problem.
In order to optimize it,optimize processes.
Speaker 1 (34:45):
So that's really good .
I can relate to a lot of those,because I think when you go
back to like communication inand of itself, that's not
something where like, oh well,I've become good at that, so I'm
good.
Yeah, it's never done.
It's always like it's arelentless pursuit of it and
it's either on or you're not,and that could be a daily thing.
(35:05):
And then, from the technologyperspective, jason, I feel that
wholeheartedly from a healthplan perspective, because we can
have people that really desirea different outcome, but it
doesn't necessarily mean thatthey're willing to walk through
the steps to actually deliverthat, or they maybe don't
understand what it really meansto do that in relation to their
(35:27):
culture and maybe it reallyisn't something that they want.
So, very, very, veryinteresting, as I listened to
you of like I'm learning thesame lessons, my friend, yeah,
you said something about and Ithought it was a fascinating
comment you made that you saidyou're a creative engineer and
(35:47):
at first, when you said that, Iwas like well, those two words
don't necessarily go together,but clearly, as you've been
talking like, it's very apparent.
That's actually like the bestdescription for it.
When did you realize aboutyourself that like this is your
gifting that, like this, is yourgifting.
Speaker 2 (36:05):
So my father's a pastor and when I was about
eight or nine years old he andso this is we're talking early
to mid eighties he decided hewanted to buy a computer to
write his sermons.
So he went to Radio Shack andhe bought a Tandy 1000.
Didn't have a hard drive, right, just the old disc drives, the
big ones too like.
And so he bought this computerso that he could he could write
(36:26):
his sermons, and they had.
My parents had no idea how torun this thing, but they were
intrigued with it.
Well, I'm an eight, nine yearold kid.
My dream in life at that pointwas I wanted to be a disney
cartoon animator.
I wanted to draw goofy.
That's I.
I would sit around for hours onend practicing drawing goofy
because I wanted to get a job atDisney drawing Goofy for
(36:47):
animations.
I was there at that timerealizing that I was actually
very good at art.
I don't have a lot of artistictalent and it didn't really
matter how hard I practiced, itjust never got a lot better.
But I found myself keep drawingback to this computer that my
dad had bought and it came witha book called Basic and it was
like it was the most logical,obvious thing I had ever
(37:07):
experienced in my life.
I could open the book, Iunderstood what was going on and
I could tell the computer to dothings that I wanted it to do.
And I started to realize that Iactually am kind of excited
about this.
So I did that for the nextprobably, you know, till I was
ready to go off to college, atwhich point Pixar had become a
thing and I thought I can get ajob with my computer and
(37:29):
animation and that's my dreamjob.
So I looked for schools thathad computer graphics as a
foundation and I that's where Ifound my undergrad school.
I ended up going to Tayloruniversity in Indiana.
They had a computer graphicsprogram and they also had an AI
track.
So in the nineties I did bothcomputer graphics so that I
could be a Pixar animator andartificial intelligence, and
(37:51):
that's when I could justresonated with me.
It was this creative engineeringside of things is really what
drove me, and that's what I getexcited about is was that side
of it.
But the AI piece kept comingback around and I kept wanting
to use it and that's where Iended up kind of more in
business than in animation is.
I was drawn that way, and Iwould say, over the years, I
(38:14):
found that my favorite thing todo is to especially after I went
to Notre Dame and I had afoundation of understanding what
what business was was to pulltogether the ideas from business
, the ideas from psychology, theideas from organizational
leadership, the ideas fromtechnology, and pull them all
together in a way that peoplecan understand and do something
with it, because that, to me, isreally why technology exists,
(38:37):
and so I knew all this stuff waspossible, but the rest of the
world doesn't know.
So I wanted to figure out howto share that with people in a
way that they could actually useit, and that's, I think, where
it all came from so, wow, I kindof think about taylor.
Speaker 1 (38:50):
I mean, taylor's not a big school, no, and to have an
ai track and a graphic designer, computer graphic track, that
had to have been a very likesmall nucleus of people that
were on that journey with you attaylor yes, yes, there was a
very small few.
So peeling away from, I mean youwere wanting to be more or less
(39:11):
in like the computer and theentertainment world and you
gravitated towards business.
Do you feel like your dream wasbeing continually shaped toward
business, or was there somewhatlike a death to this?
You know, entertainmentPixar-esque view of where you
(39:33):
wanted your life to go?
Speaker 2 (39:34):
I feel like I sort of just refined my edges as I was
going through school and it justsort of like I still love the
graphic side and the math thatmakes up all the you know, pixar
type work.
Like that's fascinating to mebut I struggled with making it
practical to people.
There was the storytelling sideof it but especially at that
age and at that time I was nevergoing to be a part of the
(39:56):
storytelling.
I was never going to shape thestory.
I was going to be the technicalimplementation of fulfilling
that story and I just wanted tobe a part of telling the story.
And that's what drove me, Ithink, towards business is
because I could look you in theeye and have a conversation
about your story and then helpapply the right tools to make
that happen.
And that's what I wanted to bea part of.
So I love the animation sideand I still dig out about Disney
(40:20):
cartoons from the 1930s Like Ithink they're awesome.
But at the end of the day Iwanted to help shape the
business story and engage withpeople more one-on-one as
opposed to more like behind thescreen to the masses.
I want to be able to look themin the eye and have a
conversation about the realityof what's going on there.
Speaker 1 (40:39):
So do you think you'll ever like attempt a short
cartoon.
Speaker 2 (40:46):
I've attempted many.
They're fun, but I'm not verygood at that either.
Speaker 1 (40:53):
You made the right choice.
I made the right choice.
I think you did too Well, jason, thanks for joining today.
It's been a absolutelyfascinating learning about your
vision and talent of not onlyimplementing advanced technology
and automations and AI and allthose kinds of things, but just
(41:17):
the method of which you do.
It is absolutely fantastic ofthe people side and really the
teaching.
You're a great teacher.
So again, creative engineer,you've proven the point not only
of what you're actually doingtoday, but how you wanted to be.
You know, on the cartoon side,even with computers.
That's pretty incredible.
We have two questions that weask every guest that would like
(41:42):
to ask you too.
First question is what is arisk you have taken that has
changed your life?
Speaker 2 (41:49):
So I grew up a huge Notre Dame football fan.
My family is originally fromSouth Bend, indiana, and that
was kind of an area.
Notre Dame was kind of themecca of college football to me.
And then I also spent some timegrowing up.
I graduated high school atSouth Bend and I worked at a
country club, and at the countryclub there were a lot of Notre
(42:10):
Dame grads that had come through.
I had tremendous amount ofrespect for them.
I had built Notre Dame up to adream school in my mind.
There was no way I was going togo there as undergrad.
They're ridiculous graduationacceptance day.
In 2007, my wife talked me intoapplying to Notre Dame.
So on one hand, the risk thereseems pretty minor and trivial,
(42:31):
but it was, I guess, such aninside of me dream to be a Notre
Dame man, to be somebody thathad gone to Notre Dame, that the
idea of them rejecting me andsaying that I was not the kind
of person that wanted to gothere like hit really deep.
It scared me to death, and Iwas.
I was terrified to applybecause I was terrified of being
told that I was not good enough, and so the risk that I took to
(42:55):
actually put together.
That application was probably,emotionally for me, one of the
highest risks I couldn'tpossibly take, because it was
literally putting it down onpaper.
I'm deciding, I'm going to findout if I am good enough or not
for this dream, and so I wasable to get into their program.
I graduated from there in 2009with an MBA, and that has
(43:19):
changed a lot of the trajectoryof what we've done.
A lot of it because I nowunderstand how to communicate
with the C-suite, I understandwhat it is that we're actually
all driving towards and Iunderstand the issues that
they're faced with.
Because one of the neat thingsabout the program that I got to
be a part of was there werepeople from all over the world
that had flown in to Notre Dameon a monthly basis and they were
(43:41):
like the chief accountingofficer of eBay her name on a
monthly basis, and they werelike the chief accounting
officer of eBay partners at KPMG, the director of negotiations
for Alcoa, and it was like I getto sit in the room with them
and learn, and that changed mylife, because it opened my eyes
to the way that people actuallyare running business and
thinking and allowed me then tobe able to come in and really
address the issues that weneeded to address.
(44:01):
So that's probably the riskthat I took.
That was probably more internaland emotional than it was
really like risky in any otherway, but it had the biggest
impact, probably on me.
Speaker 1 (44:13):
Yeah, that's a great story.
It's like, well, obviously Iknow you and Kendra but the
microcosm of like just herencouraging you to do that is
such a great microcosm of likewhat I see, your business
relationship and how you guyssupport each other and have
success together.
(44:33):
So that's such a cool story.
Thanks for sharing that.
Second question what'sunfinished that you have the
resolve to complete in the nearor not so near future?
Speaker 2 (44:45):
So we've been a consulting firm since the
beginning of the company andthat's pretty much how we make
our living.
As we've learned more aboutbusiness, a product has emerged
and we've got an opportunityreally to take a lot of the
learnings that we've createdover the last 10 to 12 years and
put it into a product that wethen could ship to the
(45:09):
marketplace and they could takeadvantage of a lot of the tools
and learnings that we'veassembled over the years.
And that is a hard transition togo from a consulting to a
product company, and my resolvefor that is it runs deep, and so
that's the thing that is goingto happen.
But it is not a quickturnaround, it is a long-term
(45:31):
process.
That's probably going to happenover the next three to four
years, three to five years, butit is again my resolve to make
that happen is it's imperativeto who we are, because I think
it opens up doors for us to beable to help more and actually
be able to help more andactually be able to help bring
that meaningful, impactful workto more people, and that's what
we're about.
So we'd be remiss to not do itbecause we're limited in the
(45:52):
scope of what we can do in aconsulting realm, but with this
product I think we can actuallyopen the doors to hundreds of
thousands of people to be ableto do more meaningful, impactful
work.
And that's so.
That's just deep in me.
Speaker 1 (46:05):
That's awesome.
Well, it's been, as I mentioned, just a true pleasure to watch
you in action and see how you'rechanging the business and
making it better and reallyimpacting an important industry
with a strong mission in mind.
So, jason, thanks for joiningus today.
Have a good one.
Speaker 2 (46:24):
Thanks for tuning in to Risk and Resolve.
See you next time.
You're listening to Risk and Resolve, and now for
your hosts, Ben Conner and ToddHufford, Welcome back to another
episode of Risk and Resolve.
Today we are blessed to havethe brilliant Jason Butler join
us from RoboSource.
Jason is the founder and CEO ofRoboSource, a company
(00:23):
specializing in processautomation and AI-driven
solutions to help businessesstreamline operations and
improve efficiency.
Jason, thanks for being with ustoday.
Speaker 2 (00:36):
Hey, thanks a lot, Ben Looking forward to it.
Speaker 1 (00:38):
Yeah, so it looks like you founded RoboSource back
in 2012.
Tell us about the reason andthe why behind starting
RoboSource at that time?
Speaker 2 (00:53):
Well, there's probably two things that were
driving me at that point.
I had started and failed threebusinesses prior.
So from 1998 to 2006, I hadstarted well, 98 to 2003, I ran
a business, learned everything,what not to do.
In that timeframe I basicallyran it into the ground and was
(01:15):
not super successful with it.
I ended up starting anotherconsulting business about two
years later, from 2005 to 2007.
Wasn't super successful, wasn'treally growing it, but was
doing essentially a lot ofindependent consulting, and so I
decided that I wanted to.
If I was going to do this, Ihad to learn what I was, how to
actually do it.
So I went to the University ofNotre Dame and got an MBA, most
(01:36):
specifically so that I couldstart a business and know how to
run it.
So when I graduated from that,we set ourselves on the path to
start a business.
You know, I'd like to say I satdown and thought here is a gap
in the market and I've got asolution and I'm coming at it.
Really, that wasn't the case.
I am an entrepreneur throughand through.
I'm a creative engineer and theidea of working for somebody
(01:59):
else just wasn't sitting greatwith me and I just I needed to
go after it, and so that'sreally was the impetus behind it
.
So in 2010, I actually went outon my own and started doing
some of my own independentconsulting, ended up starting to
get more and more successfulwith it.
I'd learned some of the toolsthat were necessary and by 2012,
we officially formed RoboSourceand have been growing it ever
(02:21):
since, and over time, as youlearn more about yourself, you
start to realize really kind ofwhere you fit in the market, and
that's where, for us, it'sabout helping people do
meaningful, impactful work, andthat's really what resonates
with us is we want to.
I don't know.
I feel like most people.
When they wake up in themorning, they don't think, man,
I can't go away to put a bunchof numbers in this spreadsheet,
(02:42):
but they're like if they couldhave an impact or talk with a
person or engage with somebodyon a human level, that's what
motivates them or they could dosomething strategic, creative.
So that's really whereRoboSource came from is how can
we get some of that mundane,repetitive stuff off your plate
(03:03):
so you can do the impactful,meaningful things that are why
we actually get up in themorning in the first place, and
so that's really what's kind ofevolved and driven us for the
last 12, 13 years?
Speaker 1 (03:07):
now I know that this is a business that you've
partnered with your wife ingrowing.
Tell me about that, because itsounds like you started in the
consulting realm, which mighthave been you individually, and
then this endeavor you knowincluded your wife.
Tell me about that genesis andhow that came to be.
Speaker 2 (03:24):
So again I'd like to say it was strategic.
It was probably more of anaccident and came out of
necessity really so starteddoing a lot of consulting, was
starting to build a name formyself on that front, started to
get more and more opportunities, and in order to meet those
opportunities I needed to bringin additional people, and so
started bringing in othertechnology focused individuals
(03:46):
to help me deliver on thepromises I was making to clients
.
I think we're about two orthree years in at that point and
my wife goes have you done?
And she listed out all these HRtasks that were like apparently
necessary to hire someone.
And I was like I don't reallyknow what you're talking about.
And she's like I'm afraidyou're going to go to jail.
I'm going to take over all ofthat.
So she came in and organized allof the stuff that needed to get
(04:09):
done right the compliancethings, the things that actually
are driving a business.
And so again I here I paintmyself as this like
absent-minded professor type ofrole, but that's really.
I mean, I really kind of amthat I'm.
I'm an engineer, my focus ishow to apply technology to help
people and a lot of the rest ofthe stuff I kind of lose track
of.
And so my wife is a very detailoriented, business minded
(04:30):
individual that came in and said, hey, let's, let's get the rest
of the business kind of inorder, and she made a lot of
that to happen.
And so I think she came in in2013, 2014, and really started
to make that, just took thatunder her wing and they really
is the reason why we've grownand been successful as we are is
because she just keeps that allunder control.
Speaker 1 (04:49):
That's awesome.
You know, our spouses tend tocover our weaknesses and their
strengths and God bless us forit.
Yes, so you've been in, likethe advanced technology
automation robotics, if you will, for a long time.
If you don't mind, like startfrom today, of like what does
(05:10):
RoboSource look like today, frombusiness application versus
maybe what it was when youstarted and went down this path?
Speaker 2 (05:20):
Yeah, so today is a lot more focused on so we're
really.
What we end up talking about isdigital transformation.
So how do you take yourbusiness that has been operating
successfully but is maybeoperating more manually than
digital?
So by that, most businessesstart off figuring out how to
solve a problem and they putpeople in positions to solve
(05:41):
those problems.
We're not thinking about how dowe build the most efficient,
optimal computer program to makethat all work.
We're thinking about meetingour clients' needs and we do
that by getting people doing thejobs that need to get done.
So today what we do is we comein and we look at those
processes, we look at what'shappening there and we identify
(06:01):
what transformation needs tohappen in order to hit the
business need more effectively,like what does the client really
want and how can we transformour business in order to be able
to meet that need moreeffectively?
So, yes, do we use high-endtechnology?
Absolutely, why?
Because artificial intelligenceis a really powerful tool and
it does some really amazingthings and most people have no
(06:23):
idea what it's even capable ofdoing.
So someone like me that hasfigured out the business side
but came from a technology sidecan help do that translation
from here's what technology iscapable of doing and here's why
you should care and what it willdo for your customers at the
end, because, at the end of theday, that's really why we're in
business.
So that's where we're at todayis really helping look at that
(06:47):
path, looking at that map andapplying and kind of
transforming the business to bereally effective at rolling out
the kinds of solutions thatreally their customers want.
And yeah, we use artificialintelligence almost exclusively
these days because of thecapabilities that it has.
Contrast that to let's go backto 2012.
Ai has been around for a verylong time.
(07:08):
So I studied it in the 90s.
The principles of thetechnology has been evolving for
a very, very long time, in themid in the 2000s into the early
2010s.
The primary form of AI there'sa lot of predictive analytics, a
lot of some of the basicmachine learning, and you see
that on like Amazon, right, likeyou go to Amazon and it says
10s.
The primary form of AI.
There's a lot of predictiveanalytics, a lot of some of the
basic machine learning, and yousee that on like Amazon, right,
like you go to Amazon and itsays people who bought this also
(07:31):
bought other things like this.
Well, that's a form of AI.
It's using some predictive mathto figure out how to make that
all happen.
There's another form of AI thatI spent most of my career in,
and that's expert systems.
And what an expert system is,is it essentially?
Well, the one that I rolled outspecifically was it would
capture a bunch of facts abouthow a business should operate
(07:51):
like or actually a better way tothink about it.
It would be like, say, a doctor.
If you're to capture a doctoras an expert, you might say
things like if your nose isrunning and you have a fever and
you're achy, we're going toassert that you might have the
flu.
And so we create a whole slewof these facts that would exist
(08:12):
inside of a system, and thenwhen someone came in, they could
basically answer questionsabout themselves asserting
certain information oh, my noseis running, no, I'm not achy.
So it would then kind of decidewhich of the outcomes would
happen from there.
So I wrote quite a few of toolsaround that technology, and
that's really where we kind ofstarted was on this expert
system level, but at the end ofthe day, most of it ended up
(08:35):
being pretty low level in mymind, pretty low level software
just to automate some of thebasics, things like you're
probably used to seeing online.
Actually, most people use todayright Like QuickBooks Online or
tools along those lines.
Those are forms of automationand they really do help speed up
a business and make a businessmore effective.
They're not taking entireworkflows and automating them.
(08:58):
They're taking bits and piecesof it and making those tools
more effective.
So we went from a lot ofindividual bits and pieces of
tools to a more holisticworkflow type solution over the
last 12 to 15 years.
Speaker 1 (09:11):
Yeah, it almost seems like.
Yeah, point-in-time solutionsare becoming more systematized
you talked about.
You know most people don'ttruly understand AI or how
automation really works.
Like how would you describewhat most people think about AI?
Like this is the preconceivednotion that everyone has, versus
(09:35):
like this is what peopleactually should know, as they're
like getting into the realm ofthis kind of a conversation.
Speaker 2 (09:44):
Yeah, so marketing has done a really good job of
making you think that artificialintelligence is actually
intelligent.
So most people think that theartificial intelligence, the AI
let's say, chat, gpt, gemini,claude, any of those they
believe that that tool isactually thinking they believe
that that tool is actuallythinking, meaning it's
(10:05):
assimilating its own thoughtsbased upon prompts that you're
giving it, and that feels alittle magical.
At the end of the day, though,that's not really what's going
on.
What we've done is we've takenthe sum total of all the
knowledge that we have writtenon the Internet and we've put
them together into bigprobabilistic models, and so, at
(10:27):
the end of the day, it's a mathequation that is tuned to say
what do you want to hear, andI'm going to try and figure out
how to give that to you.
So it's going to look at all ofthe stuff we put on the
internet, all the words we puttogether, and it's going to try
and figure out what the next setof words should be to give you
the outcome that it thinksyou've asked for.
(10:48):
And the way that it determineswhat it thinks you've asked for
is also a mathematical equation.
So it's not really thinking,it's spitting back to us what we
have historically, through abunch of patterns put all over
the internet for the last 20years.
So is it biased?
Well, are humans biased?
Like yeah, it is, because whatyou're going to read on the
(11:10):
internet is probably biased Like, does it hallucinate?
Well, yeah, do humans.
And at first you're like no, wedon't hallucinate.
Well, you kind of do, though.
Like I think about last weekwhen I had a conversation with
my wife and all of a sudden I'mtexting her and all of a sudden
the text goes cold and likeshe's not responding anymore.
What did I just?
What do I do?
(11:30):
I started telling myself awhole bunch of stories, like I'm
sitting here going like oh, Ijust said something that really
irritated her.
What did I say?
I started scrolling, like whatdid I do that?
Oh, no, what's going on here?
And then she's like sorry,ended up getting interrupted.
(11:52):
Here's what I think I was likeoh, right, right, we hallucinate
too.
Given lack of information, wemake it up.
So dai is doing the same thingwhen it has lack of information.
It has seen patterns of usmaking it up, so it makes it up.
So the thing that I wish peopleunderstood is that, because
it's predictable.
You therefore can't control it.
Because you you can't controlit Like because it is a
mathematical equation, we can'tactually drive it towards the
outcome that we want.
It's not like a human in itsentirety, where it's completely
(12:15):
unpredictable and you can, youknow, feel like you communicated
with it really clearly and itdoesn't understand or it goes
different directions.
You have a lot more controlover this than normal If you're
working with a normal individual.
Speaker 1 (12:28):
A lot more consistency.
It's not going to get caught upin emotions of things or
otherwise, because it's workingoff of that main foundation.
One thing you brought up I kindof find interesting and since
you opened the can of worms I'mgoing to go there Just the idea
of truth in AI.
I think there's a lot of fearabout explicit bias being
(12:49):
influenced into AI.
What's your take on that?
Speaker 2 (12:53):
It's a reflection of humanity.
It's literally mimicking thesame patterns that we put into
it and I don't know that you'reever going to take that out,
because it's always going to bebased upon human communication
patterns and human communicationmodels.
I'm also not sure in itsentirety that you want to take
it out, because if you took thatout, it wouldn't feel cute and
(13:14):
it wouldn't feel intelligent.
I think that part of theconversation that happens with
people is that we we pick up on.
You were raised in a differentplace than I was raised.
You have different experiencesthan I have.
That's part of what makes youinteresting to me, and if we
took all of that out and reducedthis all down to whether or not
we can have a logical,consistent, straight, 100% true
(13:36):
conversation, it's not a veryinteresting relationship we're
going to have, and the reasonwhy AI is reflecting a lot of
that is because that's whatmakes it feel human and that's
what we want in ourconversational AI when it's
having a conversation with us.
We want it to feel human, wewant it to have opinions.
Unfortunately, because we'rehuman, we want it to have our
(13:57):
opinions and so, as a result, weget a little bit worried when
it starts reflecting opinionsthat aren't ours.
But that's part of humanity.
And in my mind, how great is itthat I can go in and I can
prompt an AI because I cancontrol this one.
I can prompt it to take theulterior viewpoint of something
(14:18):
that I have and allow me toengage that in a non-emotional
way, where a human is notengaged, so I can actually
explore my own emotions on that.
That's pretty powerful.
That allows you to do things interms of your own personal
development that you can't dobefore, because you now can
explore the counterpoints toyour own way of thinking.
Speaker 1 (14:38):
What an interesting way to potentially prepare
yourself for a situation thatmay be a little unknown, if
you're going to have aconversation with someone in a
different job, role or, to yourpoint, from a different culture
or otherwise.
But you mentioned the wordprompt, yeah, and I think that
that when I think of AI or evenengaging with chat GPT,
(15:00):
sometimes I'm like I don't knowif I am setting it up correctly
and I don't know if this is areasonable question.
But like, how should peoplethink about like prompting, a
chat GPT or using the rightsetup are using the right setup?
Because I think when you gointo it, you at least I'm going
to speak on behalf of me like Ikind of think of chat GPT as
(15:23):
like interfacing with Google,which is like find me this, well
, there's no prompting to that,it is just going to spit back
something.
How do you see prompting, orwhat are the best ways to use
prompting to get a better useout of like an AI, an AI setup?
Speaker 2 (15:40):
So it is interesting.
That is how most peopleapproach it, and the first time
they get it in front of a chattype of AI is they just start
asking it questions like theywould Google, and it actually
doesn't do a very good job ofanswering those, because at
least a lot of the currentmodels are delayed by months of
the amount of information theyactually have access to.
(16:01):
Now some of the new ones willallow you to connect and
communicate with the Internet aswell, but it's essentially
doing a search for you.
So the prompting idea, whatyou're trying to do with the AI
is you're trying to give it thecontext that it needs to
understand why you're asking thequestion you're asking.
And there's a lot of mathbehind this and it's really
(16:23):
fascinating.
There's this concept calledembeddings that essentially turn
your language into mathematicalequations.
Then, because you now havethese mathematical we call them
vectors and you can thinkexactly like you know physics
vectors from high school Becausewe now have these mathematical
vectors, we can now doessentially similarity searches
(16:43):
based upon the vector to bringback information.
That's the same.
So what you're trying to do isyou're trying to give the
language in such a way that themath will know how to pull back
things that are the same.
So what we want to do and we'reprompting is we want to give it
a couple of things.
We want to first tell it therole that it's playing, and more
prompting is we want to give ita couple of things.
We want to first tell it therole that it's playing.
We want to say, hey, you'regoing to be a business
(17:04):
consultant that is helping mefigure out my go-to-market
strategy.
You gave it context.
You just gave it some wordsthat allow it now to go find
information that is aroundbusiness consulting and
go-to-market strategy.
It's then going to pull thatdata back and start to use that
as its mechanism to answer yourquestion.
Then the next thing you want todo is you want to give it
(17:26):
step-by-step reasoning.
You want to say, first I wantyou to do this, then I want you
to do the next step, then I wantyou to do the third step, and
the reason you do that is eachof those is going to give it
context on what to pull back,but you're also telling it the
order of how to go about doingthat actual work, and so
step-by-step reasoning tends togive you a better result.
(17:47):
Finally, the third area that Ifind to be really effective is
they call it few shot training,but it's basically giving
examples and then what you wantto see back.
So hey, as a businessconsultant, you're going to help
me figure out my go-to-marketstrategy.
Here is a paragraph of thoughtsand ideas about my business and
here's what I would come backwith if I were you.
(18:08):
Now here's another idea Usethat same model and come back
and give me the information thatyou pulled for me so you can
give it training.
You can say essentially example, here's my input, here's my
output, and do that a couple oftimes and then when you ask it
the next question, it will usethat example to kind of
(18:28):
formulate how you want to seethat response.
Speaker 1 (18:31):
Wow, that's really good.
What kept coming up in my mindwhile you were talking is that's
probably exactly how I shouldprobably set up my training for
anyone internally, and it's notlike specific and regimented,
which potentially goes back toyour point about it.
It really isn't intelligent asmuch as it is, like you know.
(18:56):
If you give it the guidelinesof how to think, it can think
really well or it can producethe results that you're.
It's not even thinking.
It's producing the results thatyou're really looking for.
Speaker 2 (19:08):
Yeah, A thought that I've been playing with in my
head for a while now is what isintelligence Like?
When we say, oh, that person'sreally intelligent, what are we
really referring to, and that's.
It's just.
I've been playing with it andI'm sure there's a whole bunch
of psychologists out there thathave studied this.
I haven't, but what I keepcoming back to is the people
(19:29):
that I think are intelligent arethe ones that can recall
information really quickly rightoff the top of their head.
When I say something like Ican't, I start talking about a
business, a business concept.
I'm't I started talking about abusiness, a business concept.
I'm like man, from a marketingstandpoint, I wish I could do
this.
And they go oh, you know what,this book said this and this
book said that, and they startreferencing experts on how to do
it.
I'm like really smart,well-read people, and that's why
(19:50):
I think we start to confuse AIwith intelligence, because it's
way better at recalling thingsthan we are.
So it can go, pull all thatinformation instantly and then
spit it back to us.
So we go really, really, reallysmart system, but it's just a
recall mechanism and it's justrecalling it in a way that is
(20:12):
more natural for us to interactwith.
I think the actual intelligencecomes into the creative
application of it, and that'sjust now starting to emerge in
some of these AI tools, butcurrently they just recall
information really well, whichis what makes it feel like it's
intelligent.
Speaker 1 (20:26):
And they have a broad spectrum of where it can go to
recall information or to accessinformation quickly.
When it comes to AI, likespecifically like business
leaders you know we talked aboutthe general person of like how
(20:47):
should they think about maybe AIa little bit differently or
where do they get it wrong?
But how should business leadersthink about the context of AI
and then how it can actually beimpactful into their business?
Speaker 2 (20:55):
Yeah, one of the things that I'm really
passionate about is the factthat AI is a tool, and it's just
that it's a tool.
So, as a business leader, whatproblems are you dealing with?
They need versus they needsolutions, like like that's
where that's where we start is.
We don't start with I need touse AI in my business or I'm
(21:16):
going to get left behind.
No, you're not.
Like it's a tool Like what inmy business?
Or I'm going to get left behind.
No, you're not.
Like it's a tool Like what inyour business is keeping you
from scaling?
What tools might exist to makethat more effective?
Maybe it's AI, maybe it's not.
But let's shift our thinking tosay I'm afraid I'm going to get
left behind from this AI wave,and instead say no, what's
(21:37):
keeping my business from growing, and let's find the right tools
to fit to help solve thatproblem.
That's the big shift that Ithink CEOs need to think about.
Speaker 1 (21:50):
Do you think that's the unlock that's happening with
the craze on AI?
Is that it's leading to thatquestion?
Speaker 2 (21:53):
and then businesses can actually get better.
That's what I'm hoping.
There's still a lot ofbusinesses I talk to come to me
and they're like I don't want toget left behind.
What do I need to do, Tell me,and I'm like that's the wrong
question, Like you're settingyourself up for massive failure
because I can put AI into aboutanything.
It doesn't mean it can actuallychange anything.
So let's, let's talk about thatfirst.
(22:13):
Then the second thing is tostart to understand what.
What is the tool good for?
If you've got a hammer and Ihand you a screw, it's not going
to work real well.
They're not made to worktogether.
So what is it really good at?
And some of the things that AIis really good at, and I'm just
going to sum it up in onesentence.
There's a lot of nuance aroundthis, but what AI is really good
at is evaluating text.
(22:39):
In my world I call thatunstructured data, so not like
databases where you've got lotsof formal relationships.
I'm talking about like I got anemail and I want to be able to
understand what's going on inthat email.
So AI is really good atevaluating text.
And then, as a result, becausewe're human and most of our
communication happens inunstructured textual formats.
Human and most of ourcommunication happens in
(23:01):
unstructured textual formats.
Emails, word documents,PowerPoints, PDFs like Excel
files, Like those are allenvironments that pretty much
run business.
80 to 90% of all of ourinstitutional knowledge exists
in unstructured formats that AIis now unlocking, that allows us
to work with and sounderstanding that that's the
tool and that's what it's usedfor right now.
Speaker 1 (23:22):
Another question just about AI in general, and then I
kind of want to go back toRoboSource in particular and
your mission, but it seems andmaybe it's not true, but it just
seems that the last 12 monthsor 18 months has been way more
ridiculous in the tech worldthan even before.
(23:43):
One, is that true?
And then two, like where istech headed in the foreseeable
future from your perspective?
Speaker 2 (23:51):
It's been in the news a lot more than it has been
historically over the last 10years or so, but I don't really
think that it's accelerating ata pace that is outside of
everything it's been doing forthe last 20 years.
It's an area that, for one Ithink AI captures our
imagination.
You go back to the Terminatorseries right when was that?
Early 90s?
And it's like ooh, ai isrunning the world, like that's a
(24:14):
sci-fi concept that we all kindof like geek out about a little
bit, and so this now isstarting to kind of feel real.
So people want to engage thatstory.
Speaker 1 (24:25):
My story, by the way, is iRobot.
That's the movie that I waslike that is crazy.
And now it's happening, Like, Ithink, elon's robots even look
like the iRobot robots.
Anyway, go ahead.
Speaker 2 (24:39):
So there's part of that, just the human interest
piece, right when we care aboutit more because it just is
sci-fi and cool and I mean Igrew up on Star Wars.
I can't wait to have a droid,like I want one, like you know.
That's the kind of mindset thatwe're getting out of that.
So it's fun to imagine about,to imagine about.
But technical technology hasbeen basically accelerating at
(25:00):
that speed for the last 20 yearsanyways, um, going forward,
there are a lot of things thatare coming.
I mean you think we've beengoing fast.
We're gonna be going way faster, partly because ai is good at
unstructured data and it is goodat finding patterns, so it's
gonna find patterns faster thanwe can.
So pharma and biotech like it'sgonna find patterns way faster
than scientists can.
So pharma and biotech, it'sgoing to find patterns way
faster than scientists can andthey'll allow us to experiment
(25:22):
with a whole lot more compoundsthan we've ever thought we could
.
Before you start getting intoquantum computing I don't know
if you've read much about that,but there's some crazy things
going on with quantumentanglement and being able to
show teleportation in thequantum realm and that's how
that's translating into thingslike maybe potentially faster
than light communication.
(25:42):
That's all a little speculativestill, but we're starting to
see some things that mightactually indicate that could
happen.
So there's some crazy thingsthat are happening on all these
different sides, and I think theability to identify patterns
faster from using the technologythat's being developed right
now is going to greatlyaccelerate that in terms of how
(26:03):
much and how quickly we bring innew technologies.
Hopefully we should see thatreflect in human standard of
living.
If we can get compoundsdiscovered faster and tested
faster and through clinicaltrials faster, can we bring
cancer drugs to market faster.
That's pretty cool.
That impacts lives, you know.
(26:23):
Same with communication.
If we can communicate evenfaster, like right now we're
able to do.
You know the internet and I cancommunicate around the world
within seconds.
What if it was milliseconds?
When does that change and whatcan we do as a result of that?
So yeah, I think you're goingto see technology really take
off and we're really just kindof at the beginning of this
information age.
That's going to just sort ofaccelerate.
(26:44):
Let's be honest, ai is stillpretty in fit.
It's still not.
I mean, it's smart, but it'sstill not very smart like the
dumbest it's ever going to be,so we need to prepare ourselves
for it.
We know what that looks, butwe're still really early.
Speaker 1 (26:59):
You're right, because I even see, like, when people
do like AI, like images orsomething, where things are like
misspelled wrong or there'slike an arm coming out of
someone's head or something likethat, when AI gets really good,
what type of like securityissues?
Speaker 2 (27:16):
might we have.
Oh, security is a huge problemalready, but it's not just an AI
problem, it's a problem withall digital information, and I
mean cyber has been an issue fordecades now, right, and it's
not getting better with AI.
There's a whole slew ofinteresting questions around
intellectual property and whoowns what, and I'm intrigued to
(27:37):
see what happens in the legalsystem around that, because
there's just not a lot ofprecedent around it to the not a
living being.
Speaker 1 (27:45):
You can't break laws that don't exist, right?
So you're just pressing forwardand then you discover the
problems later, right, Yep?
Speaker 2 (27:52):
And then we create laws retroactively and some of
it will be right and some of itwill be really wrong.
Speaker 1 (27:57):
Yeah, well, yeah, because laws are passed by
people who really don't evenunderstand the thing.
Speaker 2 (28:02):
Yep exactly.
Speaker 1 (28:03):
Whoever gets to them and prescribes some of that?
What's the fix on security fromyour perspective?
What should lawmakers consideraround that?
Speaker 2 (28:12):
Take the internet the internet is probably one of the
single most impactfultechnologies to ever hit
business in terms of like whatit's actually done to the
business world business in termsof like what it's actually done
to the business world.
But, yeah, it's also one of themost vile tools on the planet
in terms of the horrible thingsthat can happen on the dark web.
Right, and how do you controlthat?
(28:34):
We have the same problem, onlyworse, with AI.
It's probably going to be oneof the most impactful tools on
humanity and business, but it'sgoing to have a dark side to it
too, and so we didn't figure itout with the internet.
We're still trying to figure itout, and so I think you're
going to have the same problemwith AI in terms of how you
control and manage the securityaround it.
(28:55):
Now, I think, from a businessstandpoint, you can do certain
things to manage your risk Sameas with the internet, right,
like VPNs and firewalls, andthere's tools that we can put in
place to help manage our risk.
They're not foolproof there'sstill some risk involved but you
can do things to be safer inthe way that you interact with
the internet.
You're going to be able to dothe same thing with AI, in that
(29:17):
there are concepts like they'restarting to come around they're
called guardrails thatessentially will look at the
prompt that you're putting inand the information you're
sending into the AI and say, hey, whoa time out.
There's no security number inhere.
Let me just go ahead and aliasit to a non-real one and then
I'll send it out to the AI, andwhen the AI gives me a response,
I'll go ahead and swap it backfor you.
(29:39):
So that way we're not sendinginformation out on the internet
that it shouldn't be, but you'reable to interact with it as
though it did.
Speaker 1 (29:48):
Yeah, that's definitely important to keep
private information and thosesorts of things out of these
LLMs.
So let's go back to RoboSourceand what you guys are doing in
particular.
What you guys are doing inparticular, one thing I find
just incredible is the missionalaspect of taking something that
(30:10):
is so technical, likeautomation and AI and that sort
of thing, and tying it back tohow are we impacting the society
or workers, because it'd beeasy to say this is a worker
replacement, but that's not whatyou say.
You say no, we are actuallyempowering your current
(30:32):
workforce to do more meaningfulwork.
So when did that occur to youof like, this is really what
we're doing and this is reallywhat we're pursuing.
Speaker 2 (30:41):
You know, I don't know that I ever thought
otherwise, and part of that isbecause I guess I just believe
in the value and the meaning ofwork and that I believe that we
want to do things that feelconnected to our like, we want
to be a part of a team, we wantto engage on that level, and so
I feel like every business isgoing to have an issue.
(31:02):
Every business has people thatwant to feel like their job is
important and want to feel likeevery business is going to have
an issue.
Every business has has peoplethat want to feel like their job
is is important and want tofeel like they're contributing
and that's what brings meaningto them.
And it's not the same foreveryone.
Like my grandfather worked on aassembly line and you know, for
him he's bolting things into acar and I don't even know what
all he did, but he's puttingthis all in.
But at the end of the day, whenyou asked him what he did, he
(31:25):
was making cars safe for kids,like that's why he was there.
That was his meaning.
Like it was meaningless workbut it wasn't meaningless to him
.
And so I guess from thatperspective, I come in and I say
, hey, what is meaningless toyou and what can we get off of
your plate so you can do thethings that add meaning, because
I think that's how people aredriven.
I also don't buy into this myththat all these AI tools are
(31:46):
going to replace people.
I don't think you can replacerelationships.
Business is not done off oftechnology.
Business is done off ofrelationships with people.
Even Amazon, who has automatedbasically the entire buying
cycle, at the end of the day,what do we still make our
decisions off of?
The reviews at the bottom ofthe Amazon product that's human,
(32:07):
like those are human to humanrelationships that are making
that decision.
Now, they were able to do thatin a more efficient way, but
they still put the humanresponse in front of us for us
to make a decision off of.
So I don't see that going away.
So I think if you're a businessthat's trying to make it go
away, I think you're going tofind that you actually push away
the very people that you triedto serve, because they want to
have a human relationship withsomething.
(32:28):
They want to have a creativeconversation.
So it always felt to me likethis was a tool to empower
humans, not a tool to replacethem.
Speaker 1 (32:36):
You've been leading RoboSource for, I guess, going
into 13 years.
What have been some of thebiggest learning lessons or
takeaways from your perspectivein leading and running the
business itself?
Speaker 2 (32:51):
I'm not a very good communicator and I think I am.
But it comes right down to itwhat I think I'm telling people
and what they're hearing isn'tconnecting, and I have to really
really work on communication.
At first I thought that wasmaybe unique to me, because I
tend to be an engineer and so Imaybe think a little too
engineering.
But the more I talk with otherbusiness leaders, the more I
(33:12):
think that that's just a humancondition, is that none of us
are really communicating what wethink we're communicating, or
maybe say to differently.
People aren't hearing whatyou're saying because they have
their own filter.
They're putting it through andso you have to repeat over and
over and over again in variousdifferent ways and formats for
it to actually connect withpeople so that they're able to
do and get in line and aligntheir efforts with where you're
(33:36):
trying to lead an organization.
Otherwise you have everybodypulling in different directions
and it's chaos and it's chaos.
So I've learned that I have alot more work to do to learn how
to communicate effectively withpeople and make sure that the
message is being received.
That's one area that I'velearned a lot on.
I've also learned that the besttechnology doesn't make the best
(33:56):
solution just because thetechnology is superior and
effective and can do some crazyamazing things, it doesn't mean
that it's the right tool for theorganization or the company.
Either they're not ready for itculturally, or they're just not
positioned to take advantage ofit, or they're skeptical in
some way, shape or form.
Like just because I have theright solution and you've got a
(34:19):
nail and I've got a hammer and Ican come in and just pound that
thing right for you, but that'snot what they're ready to do.
And I've got a hammer and I cancome in and just pound that
thing right for you, but that'snot what they're ready to do.
And if you don't get people onboard with the transformation,
then it doesn't matter whattools you put in place, they
will not use them.
And so this isn't a technicalproblem, this is a person, this
is a human problem.
In order to optimize it,optimize processes.
Speaker 1 (34:45):
So that's really good .
I can relate to a lot of those,because I think when you go
back to like communication inand of itself, that's not
something where like, oh well,I've become good at that, so I'm
good.
Yeah, it's never done.
It's always like it's arelentless pursuit of it and
it's either on or you're not,and that could be a daily thing.
(35:05):
And then, from the technologyperspective, jason, I feel that
wholeheartedly from a healthplan perspective, because we can
have people that really desirea different outcome, but it
doesn't necessarily mean thatthey're willing to walk through
the steps to actually deliverthat, or they maybe don't
understand what it really meansto do that in relation to their
(35:27):
culture and maybe it reallyisn't something that they want.
So, very, very, veryinteresting, as I listened to
you of like I'm learning thesame lessons, my friend, yeah,
you said something about and Ithought it was a fascinating
comment you made that you saidyou're a creative engineer and
(35:47):
at first, when you said that, Iwas like well, those two words
don't necessarily go together,but clearly, as you've been
talking like, it's very apparent.
That's actually like the bestdescription for it.
When did you realize aboutyourself that like this is your
gifting that, like this, is yourgifting.
Speaker 2 (36:05):
So my father's a pastor and when I was about
eight or nine years old he andso this is we're talking early
to mid eighties he decided hewanted to buy a computer to
write his sermons.
So he went to Radio Shack andhe bought a Tandy 1000.
Didn't have a hard drive, right, just the old disc drives, the
big ones too like.
And so he bought this computerso that he could he could write
(36:26):
his sermons, and they had.
My parents had no idea how torun this thing, but they were
intrigued with it.
Well, I'm an eight, nine yearold kid.
My dream in life at that pointwas I wanted to be a disney
cartoon animator.
I wanted to draw goofy.
That's I.
I would sit around for hours onend practicing drawing goofy
because I wanted to get a job atDisney drawing Goofy for
(36:47):
animations.
I was there at that timerealizing that I was actually
very good at art.
I don't have a lot of artistictalent and it didn't really
matter how hard I practiced, itjust never got a lot better.
But I found myself keep drawingback to this computer that my
dad had bought and it came witha book called Basic and it was
like it was the most logical,obvious thing I had ever
(37:07):
experienced in my life.
I could open the book, Iunderstood what was going on and
I could tell the computer to dothings that I wanted it to do.
And I started to realize that Iactually am kind of excited
about this.
So I did that for the nextprobably, you know, till I was
ready to go off to college, atwhich point Pixar had become a
thing and I thought I can get ajob with my computer and
(37:29):
animation and that's my dreamjob.
So I looked for schools thathad computer graphics as a
foundation and I that's where Ifound my undergrad school.
I ended up going to Tayloruniversity in Indiana.
They had a computer graphicsprogram and they also had an AI
track.
So in the nineties I did bothcomputer graphics so that I
could be a Pixar animator andartificial intelligence, and
(37:51):
that's when I could justresonated with me.
It was this creative engineeringside of things is really what
drove me, and that's what I getexcited about is was that side
of it.
But the AI piece kept comingback around and I kept wanting
to use it and that's where Iended up kind of more in
business than in animation is.
I was drawn that way, and Iwould say, over the years, I
(38:14):
found that my favorite thing todo is to especially after I went
to Notre Dame and I had afoundation of understanding what
what business was was to pulltogether the ideas from business
, the ideas from psychology, theideas from organizational
leadership, the ideas fromtechnology, and pull them all
together in a way that peoplecan understand and do something
with it, because that, to me, isreally why technology exists,
(38:37):
and so I knew all this stuff waspossible, but the rest of the
world doesn't know.
So I wanted to figure out howto share that with people in a
way that they could actually useit, and that's, I think, where
it all came from so, wow, I kindof think about taylor.
Speaker 1 (38:50):
I mean, taylor's not a big school, no, and to have an
ai track and a graphic designer, computer graphic track, that
had to have been a very likesmall nucleus of people that
were on that journey with you attaylor yes, yes, there was a
very small few.
So peeling away from, I mean youwere wanting to be more or less
(39:11):
in like the computer and theentertainment world and you
gravitated towards business.
Do you feel like your dream wasbeing continually shaped toward
business, or was there somewhatlike a death to this?
You know, entertainmentPixar-esque view of where you
(39:33):
wanted your life to go?
Speaker 2 (39:34):
I feel like I sort of just refined my edges as I was
going through school and it justsort of like I still love the
graphic side and the math thatmakes up all the you know, pixar
type work.
Like that's fascinating to mebut I struggled with making it
practical to people.
There was the storytelling sideof it but especially at that
age and at that time I was nevergoing to be a part of the
(39:56):
storytelling.
I was never going to shape thestory.
I was going to be the technicalimplementation of fulfilling
that story and I just wanted tobe a part of telling the story.
And that's what drove me, Ithink, towards business is
because I could look you in theeye and have a conversation
about your story and then helpapply the right tools to make
that happen.
And that's what I wanted to bea part of.
So I love the animation sideand I still dig out about Disney
(40:20):
cartoons from the 1930s Like Ithink they're awesome.
But at the end of the day Iwanted to help shape the
business story and engage withpeople more one-on-one as
opposed to more like behind thescreen to the masses.
I want to be able to look themin the eye and have a
conversation about the realityof what's going on there.
Speaker 1 (40:39):
So do you think you'll ever like attempt a short
cartoon.
Speaker 2 (40:46):
I've attempted many.
They're fun, but I'm not verygood at that either.
Speaker 1 (40:53):
You made the right choice.
I made the right choice.
I think you did too Well, jason, thanks for joining today.
It's been a absolutelyfascinating learning about your
vision and talent of not onlyimplementing advanced technology
and automations and AI and allthose kinds of things, but just
(41:17):
the method of which you do.
It is absolutely fantastic ofthe people side and really the
teaching.
You're a great teacher.
So again, creative engineer,you've proven the point not only
of what you're actually doingtoday, but how you wanted to be.
You know, on the cartoon side,even with computers.
That's pretty incredible.
We have two questions that weask every guest that would like
(41:42):
to ask you too.
First question is what is arisk you have taken that has
changed your life?
Speaker 2 (41:49):
So I grew up a huge Notre Dame football fan.
My family is originally fromSouth Bend, indiana, and that
was kind of an area.
Notre Dame was kind of themecca of college football to me.
And then I also spent some timegrowing up.
I graduated high school atSouth Bend and I worked at a
country club, and at the countryclub there were a lot of Notre
(42:10):
Dame grads that had come through.
I had tremendous amount ofrespect for them.
I had built Notre Dame up to adream school in my mind.
There was no way I was going togo there as undergrad.
They're ridiculous graduationacceptance day.
In 2007, my wife talked me intoapplying to Notre Dame.
So on one hand, the risk thereseems pretty minor and trivial,
(42:31):
but it was, I guess, such aninside of me dream to be a Notre
Dame man, to be somebody thathad gone to Notre Dame, that the
idea of them rejecting me andsaying that I was not the kind
of person that wanted to gothere like hit really deep.
It scared me to death, and Iwas.
I was terrified to applybecause I was terrified of being
told that I was not good enough, and so the risk that I took to
(42:55):
actually put together.
That application was probably,emotionally for me, one of the
highest risks I couldn'tpossibly take, because it was
literally putting it down onpaper.
I'm deciding, I'm going to findout if I am good enough or not
for this dream, and so I wasable to get into their program.
I graduated from there in 2009with an MBA, and that has
(43:19):
changed a lot of the trajectoryof what we've done.
A lot of it because I nowunderstand how to communicate
with the C-suite, I understandwhat it is that we're actually
all driving towards and Iunderstand the issues that
they're faced with.
Because one of the neat thingsabout the program that I got to
be a part of was there werepeople from all over the world
that had flown in to Notre Dameon a monthly basis and they were
(43:41):
like the chief accountingofficer of eBay her name on a
monthly basis, and they werelike the chief accounting
officer of eBay partners at KPMG, the director of negotiations
for Alcoa, and it was like I getto sit in the room with them
and learn, and that changed mylife, because it opened my eyes
to the way that people actuallyare running business and
thinking and allowed me then tobe able to come in and really
address the issues that weneeded to address.
(44:01):
So that's probably the riskthat I took.
That was probably more internaland emotional than it was
really like risky in any otherway, but it had the biggest
impact, probably on me.
Speaker 1 (44:13):
Yeah, that's a great story.
It's like, well, obviously Iknow you and Kendra but the
microcosm of like just herencouraging you to do that is
such a great microcosm of likewhat I see, your business
relationship and how you guyssupport each other and have
success together.
(44:33):
So that's such a cool story.
Thanks for sharing that.
Second question what'sunfinished that you have the
resolve to complete in the nearor not so near future?
Speaker 2 (44:45):
So we've been a consulting firm since the
beginning of the company andthat's pretty much how we make
our living.
As we've learned more aboutbusiness, a product has emerged
and we've got an opportunityreally to take a lot of the
learnings that we've createdover the last 10 to 12 years and
put it into a product that wethen could ship to the
(45:09):
marketplace and they could takeadvantage of a lot of the tools
and learnings that we'veassembled over the years.
And that is a hard transition togo from a consulting to a
product company, and my resolvefor that is it runs deep, and so
that's the thing that is goingto happen.
But it is not a quickturnaround, it is a long-term
(45:31):
process.
That's probably going to happenover the next three to four
years, three to five years, butit is again my resolve to make
that happen is it's imperativeto who we are, because I think
it opens up doors for us to beable to help more and actually
be able to help more andactually be able to help bring
that meaningful, impactful workto more people, and that's what
we're about.
So we'd be remiss to not do itbecause we're limited in the
(45:52):
scope of what we can do in aconsulting realm, but with this
product I think we can actuallyopen the doors to hundreds of
thousands of people to be ableto do more meaningful, impactful
work.
And that's so.
That's just deep in me.
Speaker 1 (46:05):
That's awesome.
Well, it's been, as I mentioned, just a true pleasure to watch
you in action and see how you'rechanging the business and
making it better and reallyimpacting an important industry
with a strong mission in mind.
So, jason, thanks for joiningus today.
Have a good one.
Speaker 2 (46:24):
Thanks for tuning in to Risk and Resolve.
See you next time.
Popular Podcasts
On Purpose with Jay Shetty
I’m Jay Shetty host of On Purpose the worlds #1 Mental Health podcast and I’m so grateful you found us. I started this podcast 5 years ago to invite you into conversations and workshops that are designed to help make you happier, healthier and more healed. I believe that when you (yes you) feel seen, heard and understood you’re able to deal with relationship struggles, work challenges and life’s ups and downs with more ease and grace. I interview experts, celebrities, thought leaders and athletes so that we can grow our mindset, build better habits and uncover a side of them we’ve never seen before. New episodes every Monday and Friday. Your support means the world to me and I don’t take it for granted — click the follow button and leave a review to help us spread the love with On Purpose. I can’t wait for you to listen to your first or 500th episode!
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
The Joe Rogan Experience
The official podcast of comedian Joe Rogan.