March 11, 2025 • 47 mins
Like all things in tech, AI is a tool that can be used for good or bad. Today we talk with Chase Friedman, managing partner of Alpine Anchor, about leveraging AI to improve processes, outputs, and profitability.
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Episode Transcript
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Justin (00:15):
Welcome everybody to episode 42 of Unhacked. Guys,
Unhacked is a bit of adeliberate misnomer. We talk
about, preventing breachesbecause here's the sad truth.
97% of the stuff we read aboutin the headlines is preventable
with basic security measures.But once you get hit, man, it's
just kinda too late.
There is no such thing asgetting unhacked. So, we lure
(00:37):
you in with a title that reallymeans nothing. I'm Justin
Shelley, CEO of Phoenix ITAdvisors. I keep businesses
protected from Russian hackers,from government auditors, and,
goddamn, the the attorneys thatcome up afterwards with the
class action lawsuits. We workwith clients in Texas, Nevada,
and Utah.
And I am here today with myusual cohost, Mario, and we've
(00:59):
got a special guest, Chase,today. Mario, real quick, tell
everybody who you are, what youdo, and who you do it for.
Mario (01:05):
How are you guys? As you know, Mario Zdaki, CEO of MasTec
IT. We are in New Jersey rightoutside of Manhattan, and we do
support for anybody who wants togive us their money.
Justin (01:20):
A specialist, I take it.
Mario (01:22):
Exactly. Now we we work with medium to small, small to
medium sized businesses, keepingthem protected, working
smoothly, and we specialize ingiving CEOs peace of mind and
help help them sleep better atnight.
Justin (01:37):
Love it. And, Brian's, AWOL again this week. We're
gonna hope he makes it nextweek. And that said, though,
we've got, we've got somebody tofill a spot. Brian, you better
hurry back.
You might get replaced. Today,we're sitting here with a guy
who who thinks he knows somestuff about AI. Now I don't
know. I've I probably nobody hasheard of AI yet. It's this new
(01:59):
trend.
Nobody's really talking aboutit, but it's it's starting to
evolve and develop. I've got Iwish that was true. It's like
all you hear about anymore isAI, and we're gonna dive into it
today. And I brought Chase hereto help us out with that. Now,
Chase, you are also kind of inthe Dallas area.
Yes?
Chase (02:19):
So BMW. Going on almost ten years.
Justin (02:22):
Okay. Alright. Well, I I bounce around. I've I'm home
based in Dallas. I've got stuffgoing on, like I said, in Nevada
and Utah, but we're gonna haveto get together one time and
grab beer or whatever and talkface to face even as much fun as
it is over the, you know, thethe computers.
Oh, I love it.
Chase (02:41):
Whatever your vice is.
Justin (02:42):
Oh, I forgot. Bourbon.
Chase (02:44):
Oh. You wanna bowl? Let's go bowl.
Justin (02:46):
Oh, now now you're speaking my language. Alright.
I've got all those vices. So,Chase, let me give you a little
bit of an introduction, and thenI'm gonna turn you loose and
tell me a little bit more inyour own words about what you
do. But, what I pulled off offof your profile here, Visionary
managing partner of AlpineAnchor, cutting edge com company
(03:07):
dedicated to elevatingbusinesses to the summit of
their industries.
I noticed that you kinda play onthe, Sherpa walking up the
mountain to, which well, I mean,which which one of the seven
great mountains is it that's
Chase (03:20):
All of them.
Justin (03:20):
All of them. Okay. Alright. I didn't wanna make any
assumptions. You know?
Anyways, passion for leveragingautomation, analytics, and AI. I
mean, this this is the word ofthe day. This is what
everybody's talking about. So Ithink you're a great fit for the
show. We're gonna talk about it,and we're gonna kinda bring it
home with what we always talkabout, which is cybersecurity
because as technology evolves,which it does, sometimes we
(03:42):
kinda think after the fact, oh,shit.
I forgot. We just opened upeverything to the bad guys,
including our bank account. So,Chase, tell me a little bit
about what you do, who you do itfor, and and maybe even a couple
of client success stories ifyou've got them.
Chase (03:55):
Yeah. Well, Justin, thanks for having me on the
show. Mario, good to meet
Justin (03:59):
you. Nice meeting you, Chase.
Mario (04:00):
Thank you for hopping on.
Chase (04:02):
Yeah. Looking forward to replacing Brian. But if he hops
on, you know, mid flow here, wecan, we can poke him a little
bit. But Yeah. Yeah.
Mario (04:09):
Well, you're gonna have to shave your head if you wanna
be a regular. You know?
Chase (04:13):
Like got some hair up here still.
Mario (04:14):
You took you took the hat off before, and I'm like, oh,
you know, on the from the sides,it looks like you fit in
perfectly.
Justin (04:20):
Supposed to be bald. We'll rename the show after us.
Chase (04:23):
Well, guys, I've I've built a career off of
interpreting, right, the thebusiness requirements, the
business process, thetechnology, the people involved.
Right? And what I've learned isthat nobody knows what they're
doing. They're all making it up.I'm making it up.
Justin (04:39):
Oh, god. That's so true.
Chase (04:40):
And everybody Googles it, but now everybody chat chippy
tees it. Right. But, I've landeda number of really great success
stories on basically, taking theprocess. Process. Right?
Making it more efficient. Andthat's before AI really came
around. Right? We leveragedautomation between CRMs and ERPs
(05:02):
to move significant, volumes ofthese transactions. And so
that's where I kind of, cut myteeth, deploying Salesforce for
enterprise grade companies, lotsof SMB, little bit of nonprofit.
Right? And got a really good,like, over the course of the
last eight years, basically gotthirty years of education in
(05:24):
back to back Zoom calls evenbefore Zoom was cool. But, yeah,
that's where that's where Ieffectively learned, like, hey.
Here's how we can can connectthese things in a way that makes
sense. Right?
And, leverage your time and yourmoney, right, and your resources
to do things faster, better,stronger. And so what I'm
focusing on now as I exited mylast company, right, I'm
(05:47):
building out a platform thatdoes the same exact thing.
Right? We're just adding in thisnext API, and that is AI. Okay.
But in thinking about clientsuccess stories, you know,
there's there's a lot of them.Part of those success stories
start with the process. Oneclient, right, that I'm, that I
(06:10):
worked on walked into the door.Hey. Show me the process.
Oh, I can't. It's all in ourheads. Right? So okay. Well,
what are we Mhmm.
What are we doing? You know, youwanna send me a lot of money,
but y'all can't even explainwhat it is you do. So for so for
one client, right, basicallystepped into the door. The
Salesforce world is is broken.They they didn't do it right.
It needs to be reimplemented. Wereimplemented it, scoped it,
(06:34):
architected it, reimplementedit. That client is still a
client today, and this is seven,eight years later. And then we
connected it to their ERPsystem. We're moving contractual
data back and forth.
We're moving data from Stripe.So a whole lot of automation and
integration. They are a a verywell known cybersecurity
(06:56):
nonprofit. And, obviously, theyare barely stepping into the AI
world, but had a lot of fun,hanging out with them, continue
to do so. Another one that, Ilove to think about or talk
about, right, are are, the oneswhere there's really no
technology in place.
It's kind of the like, well, webuilt a business off of Excel
(07:18):
sheets. Right? So, those are alot of fun because you can step
into the world of technology andme maybe being as good as I am
or maybe I'm terrible. I don'tknow. Right?
But I can step into that worldwith a well defined process.
Right? And now I can make it 10times more efficient. Right? 20
times more efficient.
I hate when people are like,well, I made it 37.35% more, you
(07:42):
know, more better.
Justin (07:44):
Why did
Chase (07:44):
you make that up? I don't know. You know?
Justin (07:46):
It's math. You wouldn't understand it.
Chase (07:48):
Yeah. Like, they they ran Google Analytics, and it said I
made money. You know? But what Ifound is that when you have that
that solid process that makesmoney, right, that does this
thing, that delivers on thisvalue, then you apply technology
to it. You really can achievesome really, really cool and
interesting things.
(08:09):
So, yeah, those those clientsare are still around today.
That's kind of where this Alpineanchor thing came into play.
Right? My goal with theseclients isn't to just get in
there, make some money, and thenwalk away. My goal is to get in
there and push them more andmore up to the top of that
mountain.
And I'll I'll leave it withthis. Right? But, got to spend
(08:30):
many years at Texas a and mUniversity where I gave them too
much money. I got too manypieces of paper. Right?
But, got to take my last companyto be a a twice twice over
winner of what they call theAggie one hundred. It's really
just like.
Justin (08:43):
Oh, nice.
Chase (08:46):
Top 100 Aggie companies. I got to see and interact with a
lot of people in that room. Thattotally get the process side.
Right? They scale their businessvery quickly.
You know? And they did itwithout well, some of them did
with VC money. Right? But theynailed the process. They killed
it.
They got into a market that wasunderutilized, under whatever.
(09:07):
Right? And they were walkingaway with 275% growth trajectory
pass over the last five years,you know, audited financials,
you know, so they couldn'treally I mean, I'm sure they
fudged some of it, but for themost point, for for the most
part, they did it. And that'swhat I wanna do. So with Alpine
Anchor, right, we're buildingout a platform where you can
take AI, not understand what itdoes, click to deploy it, and do
(09:33):
it in a way that makes sensecoming from somebody that's been
in the enterprise spaceleveraging security.
Right? All of these, like, it'snot a POC. Right? Like, this is
ready to roll for an enterprise,but I wanna do it for SMB.
Right?
I wanna focus on the companiesthat deliver lots of value, to
their to their clients, to theircustomers. Anyway, that's what
(09:54):
I'm up to these days.
Justin (09:56):
Alright. Well, that sounds like a lot. Now do you
fancy yourself a coder? Are youwriting code?
Chase (10:00):
I am. I Okay. I'm sure there's people that know me that
are like, yeah. Whatever. I gotto build back in the day, I was
translating Fortran, into,vb.net to build out some of the
first inter Internet connectedapps.
That was a lot of fun. We wereautomating HVAC, not Wagyu,
(10:23):
Wago. It's a German,programmable logic controller,
and they had it connected to theInternet. And I was like, this
is so cool. Let's do it.
And everybody's like, I don'tknow what you just did, but
we're gonna sell it for a lot ofmoney. And I was like, I was
like, oh, that's how the worldworks. So That
Justin (10:39):
is how the world works.
Mario (10:41):
So who's like, like, who's like the ideal type of
customer that would walk intoyour door Yeah. You know, email
you, you know, whatever whateverway of your communication
requirement is.
Chase (10:54):
It's, you know, that's something that I've been
unpacking as it relates to thisnew venture. Right? Because it's
very different than maybe yourtraditional, sales pipeline.
Right? My the person that I'mlooking for are the owners of
the business, right, wherethey've got too many people,
right, or their process isn'twell defined, right, or they've
(11:17):
got too much technology or maybenot enough.
Right? But, ultimately, it's theperson that's trying to scale
their company to make moremoney, right, to get more value,
right, but do it with less. Sothat's the person. In in a
vertical space, we're reallylooking for, legal or, law
firms. Right?
(11:38):
Commercial real estateinsurance. Really, the easiest
way for us to think about it isbasically, anybody that has some
regulated degree or the bar. Youhave to pass this big test to be
certified, licensed, whatever.Because the reality of the world
is those aren't going awayanytime soon, and they happen to
(11:59):
make a lot of money. So theyhave a lot of money to spend,
but that's where we're looking.
Mario (12:05):
Got it.
Justin (12:07):
Alright. That's, that's a lot, Chase. That's a lot. I'm
trying to figure out how to,like, respond and summarize and
say something intelligent. I'mjust gonna move on.
That no. Interestingly, though,we're we're going after a very
similar audience, which I dolove to hear because there's
there's so much room forcollaboration in a lot of this
stuff. I absolutely love whenyou're talking about process
(12:27):
improvement, and I don't thinkyou use that term. That's kinda
what I distilled it down to. ButI think that's kinda the the
really the key to everything.
You know? You have to workefficiently, and you've been
doing that for a very long time.If, dude, if you're working in
Salesforce and programming that,if I had a hat, I'd take it off
to you. Hats off. That's that'ssome serious stuff.
(12:51):
Writing code is serious stuff.And, really, AI is just kind of
an iteration of what you'realready doing. Correct?
Chase (12:58):
Yeah. That's actually the the best way to think about it.
I myself have written more codein the last six months than I
have in my entire life. So that,you know, the guy that's been
the coder his entire life islike, well, I bet it was really,
you know, really I don't can wecuss? Are we cussing on the
show?
Justin (13:15):
Oh, hell, yeah. Yeah. Okay.
Chase (13:16):
Well, that's really shitty. Well, it's not
documented. Right? Well, itdoesn't work. And Right.
Problem with that statement isit doesn't matter. Right?
Because I can iterativelyimprove it. This is what some
folks are doing in GitHub or inAzure DevOps. Right?
It's because the the codingprocess is asynchronous. It's
all text files. I mean,variations of text files. Right?
(13:37):
I can leverage AI to iterate onit and improve it.
So it doesn't matter that it'sgood. It's what matters is that
it's possible or it can be done.Yeah. Right. That it works.
Yeah. Absolutely.
Justin (13:47):
That's a key component. Okay. So let's let's just go
ahead and define AI. And I dothis because it's it's the term
that's getting thrown around byeverybody on the planet. And,
usually, what people mean whenthey say I, AI, Jesus, is chat
GBT.
Like, it can write a report forme in high school. Great. What
is and I'm gonna throw thisMario, why don't you you start
(14:10):
and then Chase come in andcorrect him if he's wrong. No
pressure, Mario. What exactly isartificial intelligence?
Explain it to an idiot like me.
Mario (14:20):
I I mean, honestly, your guess is as good as mine at this
point, but it it it it's they'vewith lately, what they've have
is they have machines, you know,computers that are now being
able to start thinking likehuman beings. It is analyzing
(14:41):
certain things coming up withintelligent it's not guesses,
but, you know, it it it analyzesit on the fly, and it ends up
producing what a, you know,smart human being would
eventually produce in matter ofseconds.
Justin (15:00):
Okay. That's a great way to explain it, non technically.
Now, Chase, I'm gonna punt toyou. Give us a little bit more
of a technical breakdown of whatthat how it's done. Because
you're right, Mario.
It is. It's like we're we'retrying to make computers act,
think, behave like humans.Right? Because then we can
replace humans, and we're gonnacome back to that later. But,
Chase, what's what goes onbehind the curtains?
Chase (15:21):
Yeah. I'm sure, OpenAI, Sam Altman's team would rip me
to shreds, but, you know,generically speaking, the goal
is to interpret the questionright in in a way that makes
sense to everybody. And the waythat I like to think about it is
that it's ultimately justpattern recognition. Right?
(15:41):
Yeah.
They cook that is into decisiontrees. Well, if yes, then that's
right, like traditional logic.And then what about now there's
multiple questions to answer andthere's multiple answers to
these questions. How do I figureout, like, what's the right path
to take? The first version thatmany like, the world saw of AI
(16:02):
was that predictive text on yourphone with iPhones and Androids.
Right? It would guess that youwere gonna type this word. And
that's where, like, that wholething again, the people that
wanna rip me to shreds, throw iton LinkedIn, tell me I'm an
idiot. But, when you take allof, like, the really technical
stuff out for just a second,it's really all just recognizing
(16:23):
the pattern, predicting whatthat next letter is or that next
decision. Right?
And then do that over largeamounts of datasets. That's why
we see all this talk aboutNVIDIA blowing up these h one
hundreds. Right? Those thosethings are basically like human
brains, and they can process itinfinitely faster than we can.
(16:45):
So then you apply the largedataset.
You give it a problem statement.Right? And now I can predict
what it thinks would be theanswer to whatever question you
come up with.
Justin (16:56):
So it's interesting these the way you both described
it because the human brain,Mario, going to you, is designed
for pattern recognition. That iswhat we do all day long. People
talk about their their gut,their instinct, their whatever.
That's just subconscious,subliminal not not subliminal,
subconscious, messages. Like,our our brain is looking out at
(17:17):
everything that it sees whetherwe're aware of it or not and
looking for patterns, lookingfor dangers, looking for
threats, and making predictions.
So, I I love that description,Chase, and it is exactly what
you said, Mario. We are teachingcomputers to be human, which
scares a few people. Correct?And now let's, let's kinda pivot
(17:37):
and talk about, because we ashumans have been able to
hallucinate for a long time. Oh,it turns out these computers are
doing the same thing as we teachthem to be human.
So now let's talk about what ahallucination is. And this time,
Chase, I'm gonna start with you.What is a hallucination in the
world of artificialintelligence?
Chase (17:56):
I I have not, had the opportunity of taking any
mushrooms, but I'm justimagining, like, as you're
describing that, like, well, letme give a mushroom to a
computer. What would that do?But, I think, for anybody that's
in a been in a self driving carand it does something like, oh,
or like a fast stop. Right? Orit it just kinda freaks out.
(18:18):
Right? Like, those are the veryfirst hallucinations that a
large population set has seen.You know? It's just
automatically breaking. Well,it's hallucinating something
that's a car is in the way, aperson's in the way, or it
hallucinates that the personisn't there when they actually
are.
Right? And we've seen some, youknow, tragic responses to that.
You take out the the drivingscenario. Right? A hallucination
(18:41):
is just an incorrect prediction.
Right? If you think about whenyou're driving and somebody is
looks like they're gonna come infront of you and you respond to
that, well, you're you'rehallucinating. Not in like the I
took some mushroom sense, but,like, I think he's going to do
x. Mhmm. But then he doessomething else, and you respond
to that x, that's thehallucination.
(19:02):
So we see a lot of this. It'sreally easy to, connect it to
human hallucinations. Like, Ithink I should do this. Well,
some people I I don't I don'tlove the alert the word
hallucination because itimplies, like, I took something.
Right?
I, like, took some drugs, andnow I'm hallucinating. It really
(19:22):
is just an incorrect prediction.If we tried to task Chat GBT
with predicting the price ofApple tomorrow, well, they have
some hallucination controls. Butultimately, right, it's just
gonna make an incorrectprediction because it has
doesn't have enough data. Andthat's what we see happening
when you're in the chat GPTs.
Right? It's just this is justwhat it thinks. But it moves so
(19:44):
fast. Right? It like, to thenext letter, to the next word,
to the next token.
Right? It doesn't stop to think,and that's why I've seen some of
these reasoning models pop up.But
Justin (19:53):
You know, a couple of couple examples I've heard of,
one from an attorney, and onefrom, you know, in the health
care space, attorneys will useit to try to find case studies,
right, and and take those tocourt. And then they find and
they're great, you know, perfectexample. It applies perfectly,
and it's true because AI said,except that it isn't.
Chase (20:14):
You know?
Justin (20:14):
And then I want that. You got disbarred or whatever?
That was like
Mario (20:19):
yeah.
Chase (20:19):
Oh, yeah. I know what you're talking about.
Justin (20:21):
And then you've got in health care, you know, it is
fascinating because it can beused to, diagnose diseases and
and prescribe treatments or atleast aid in that process, which
is great until it's not. So nowwe've got potential problems
because we've got thesecomputers that we're trying to
teach to be human, but they'renot. So it it brings up some
(20:43):
problems that we've illustratedhow and I'll you know, for
either one of you guys, how dowe prevent this? How do we get
ahead of this? Because it issomething that's happening right
now as we speak.
Mario (20:54):
Get ahead of what? I'm sorry.
Justin (20:55):
These hallucinations. How do we how do we make sure
that when we put something intoan AI machine, a generator,
whatever platform you're using,and it spits something out that
just looks spot on. Yeah. Butit's wrong. Like, how do you
know?
How do you fix it? How do youhow do we prevent this from
becoming a problem that killspeople or disbars attorneys or,
you know, like, keeps you put injail. Like, this is this can be
(21:16):
bad.
Chase (21:17):
Yeah. It can be really bad. It can be really scary.
Right? But if if I came to you,Justin, and said, you must tell
me, right, what the price ofApple will be tomorrow to the
dollar.
And if you get it wrong, thensomething bad happens. Well
Mhmm. You're gonna try to guess.Right? None of us are stock
brokers.
Right? And then something badhappens. Well, that's what
you're describing. So what youend up doing is reducing down
(21:40):
the question, reducing down thecontext, reducing down the
number of options. Okay.
Right. And and that's what Ifound works really well,
especially in these chat, chatrooms, chat bots. Right. Is just
break it down to the most simplequestion. It goes back to the
process.
Right? What's the what's thewhat's step one? Right. Don't
don't ask for an answer for thisthis 10 step process. Ask for
(22:03):
the answer of the step one.
And so what I found really worksworks really well even in
building out these agents,right, with these skills and
these apps that we're working onis just break it down to the
most like, the dumbest thing.Right? Like, how do I create an
email? Oh, okay. Yeah.
Like, I can tell you how to dothat. Right? The moment that you
try start trying to say in fact,this is something that I was
(22:24):
doing, literally this week.Like, I gave it the entire
problem statement to create asite to site VPN connection
Azure because that was myrequirement. I'm not a
networking guy.
Like, I know how to get my my,my home network working with
Ubiquiti. But, naturally, ithallucinated because it doesn't
know every single feature insideof Azure. Anyway, when I started
breaking it down, hey, tell methis one thing. Okay. Yeah.
(22:47):
Actually, that makes way moresense. You know? The
hallucinations are reduced whenyou reduce the size of the
problem.
Justin (22:54):
I like that. That's, that's a great great point.
Mario, did you have any input onthis one?
Mario (23:00):
Yeah. I mean, it's what I am what I was gonna say is that,
you know, what it's doing is thework of what a human being will
do. Right? In in but it's doingit at a much faster pace. So,
you know, in in Chase's example,create me, like, a step by step
direction.
A human being is gonna be ableto do it, but a human is gonna
(23:23):
probably say, take an hour, twohours, five hours to take care
of it. You know? It will do itin a matter of a minute. And in
just like a human, it's notpredicting the future. It cannot
predict the future.
So it can't tell you what theprice of Apple is gonna be
tomorrow or what's gonna happentomorrow. But it's scanning the
(23:45):
network, things that havealready been applied, and it's
bringing everything, you know,super fast, making it an like,
an intelligent, you know well, Idon't know what the word I'm
looking for, like, anintelligent documentation of
everything that it found, justlike a human would do it, but it
would be at a much faster pace.You know? And and, you know, I
(24:08):
know we're probably gonna talkabout it, but that is why, you
know, like Chase was talkingearlier, you know, companies
that have a lot of employees andthey owner wants to reduce it,
you know, with technology likethis is what's gonna help it
because he can this machine orthis AI can do whatever human
whatever a human being is doing,but it'll do it on a much faster
(24:31):
pace.
Justin (24:32):
Are you are you trying to say, Mario, that, somebody's
job might be at stake here? Areare we gonna be delving into the
world of South Park? They tookour jobs. And oh, god. I'm gonna
embarrass everybody with this,but, have either of you seen the
South Park episode where thealiens and, I mean, no.
(24:53):
They're where their future.There are people from the
future, I think, come back intime, and they're working for
pennies because they can investit and then whatever. I'm not
gonna get too far into SouthPark, but it is it's where I get
most of my intelligence,unfortunately. Nerd. So, Chase,
one of the things that caught myattention on a in a recent
episode of your podcast, whichis called The Junction.
(25:16):
Just a quick plug for you there.Although I hear you're coming
out with a new one, so we'lltalk about that more later. But,
50% of jobs will be replaced byAI by the year 2027. A, I'm
calling bullshit. I want you toback that up, and I know you
were deciding another source, sothat's fine.
B, that was something you saidor or cited about a year ago,
and I wanna know if there's anyupdates to that. And, c, this is
(25:38):
a multipart question if youcan't tell. If 50% of our jobs
go away, how screwed are we?Guys, discuss.
Chase (25:45):
Yeah. I mean, I think the headline is still valid, but I
think it's as we start tounderstand more and more how all
these things work, right, it'sit's that they're not going to
be replaced. It's that they'rejust they're they're going to be
replaced in a different way.Right? And the way that I liken
it is is now I can take aportion of this person's job and
(26:08):
I can automate it.
But you have 10 people doing it.Now you only need one. Right? So
it's it's a reduction ofrequirement a reduction in the
requirement of of resources.Right?
And so what we're gonna see islots of companies basically
reorganizing, rebuildingthemselves. And all of those
(26:29):
people that lost their jobs, Iwould encourage them to read,
the book called millionaire fastlane. Right? We're gonna see a
lot of one to five personbusinesses spin up and take tons
of market share from thesebigger companies that just have
too much overhead. Right?
They can't fire people fastenough. They can't let them go.
They can't retrain them. Theycan't whatever. Right?
(26:51):
But I can write code. I'vewritten more code. Right? Like I
said, in the last six monthsthan I have in my entire life.
Right.
Like, I don't need 30 coders. Idon't need $10,000,000. You
know? I don't need any of that.Well, there's people out there
that are smarter than me thathave better ideas.
And all of those people that areabout to have a ton of free
time, you know, the first thingthey're gonna do, hey. I need to
(27:12):
make money. Hey. I can't get ajob. Oh, I should start a
business.
So I think that's where we'regoing.
Justin (27:18):
Okay. Mario, thoughts?
Mario (27:20):
I like that. You know, it it it is you know, we we do see
it a lot already. You know, wefor example, being in IT and
stuff like that, we work with,like, companies, and it's all
about, like, SEO and blog postsand stuff like that. You know, I
actually attended a, a workshopa few weeks ago about somebody
(27:45):
you know, how they said thatthey could create a hundred
posts, in a matter you know,instead of whatever, whatever
time, they could create ahundred posts and have it
automatically post to yourLinkedIn, Instagram, Facebook,
all that stuff in under tenminutes. And, you know, Justin,
(28:07):
as you know, like, in themarketing group that we're in,
they have, like, a wholedepartment based just around,
you know, SEO and marketing andstuff like that.
Justin (28:17):
Right.
Mario (28:18):
This stuff could easily be done, in in a matter of
minute. And I imagine being ableto do about three posts per day
for the entire month in just tenminutes. You know? In in you
know, like, just Chase issaying, like, you can have a
company that has one to fivepeople, and they in one day,
they can service the service,like, a hundred different
(28:39):
customers and and and andcollect all the money.
Justin (28:44):
So let's let's actually take that point right there and
talk about the future of AI,both short term and long term.
And and this is a great way todebate this, because here's the
thing. While I agree that thatcan be done, I also feel like
the content that gets generated,number one, at least today can
(29:06):
be sniffed out as AI. You don'teven have to hardly look at it.
Right?
And it's it's terrible. I hatereading that stuff. I get I get
fooled by it sometimes. I'm notgonna lie. And it it'll take a
comment.
Maybe it's a some post I'mlooking at, some video, some
picture. I don't know. I alwaysgo to the comments, and it's
always like fake, fake, fake,fake, fake. AI, AI, AI, AI. So,
(29:29):
yes, let I mean, let's let'stalk about right now with with
AI the way it is, how valuableis this AI generated content for
SEO, for social mediaengagement, and and stuff like
that?
Either one of you guys' thoughts
Mario (29:42):
on that? At the moment and I agree. Yeah. And the thing
is the beauty of AI is that it'sgetting better every day.
Justin (29:48):
Right? Absolutely. You know? Yep.
Mario (29:50):
Because it is learning. And the the beauty of it is that
at very minimum, I think rightnow where we are today, we use
it as a starting tool or atleast a tool that will help you
get to wherever you wanna get tojust a little bit faster. You
know? I don't think it's at thepoint where it's completely
(30:11):
eliminating a lot of jobs, but Ithink it's kind of making
people's jobs a little easier, alittle faster, you know, better
service, you know, like in inthe I our IT field. Like, you
know, when we need to dosomething, yeah, we throw
something in chat.
GPT says, write me a PowerShellscript that will do this, you
(30:32):
know, and it will do it. It'smaking my technician's job a
little easier and is able toprovide a service faster, but
it's not necessarily replacingany of my guys at the moment.
Justin (30:45):
Okay. Chase?
Chase (30:47):
I think that the economic impact is going to not be talked
about because people that haveaccess and understand the
technology in a way that can beleveraged, right, they're not
gonna be on LinkedIn saying,hey. I posted three times a day.
It was all AI while I was on thebeach playing with my kid.
Right? Like, we're just notgonna see it.
(31:09):
We're gonna see it in, you know,like, layoffs. We're gonna see
it in this new company. You'reyou're starting to see some of
these on LinkedIn where they'reone to five people, and they've
got $10,000,000 in, annualrecurring revenue. Right? We're
gonna see more of those.
And so I don't think the theeconomic impact is detrimental.
Right? But it's effectivelygiving people the tools to build
(31:32):
out big, big companies thatprovide a lot of value. Dare I
say, a trickle down effect. Buteffectively, anybody today can
build a multimillion dollarbusiness and not need any kind
of investment.
They don't need to build out ateam of developers. They don't
need to go offshore anymore.
Mario (31:51):
Right.
Chase (31:52):
So I think it'll be really interesting because I
that's that's what I see now.The teams that we're working
with, they're one to two people.They've got a four person
office. Right? They've got aprocess that works, that makes
money.
And, traditionally, you'd goraise some money so you could
speed up that growth. Right?That you could market more, all
that stuff. Right, you'd have ateam of developers that can
(32:13):
develop it faster. Well, I don'tI don't need the that anymore.
And the people that I work with,neither do they because I'm
gonna provide that kind oftechnology for them. So, I mean,
the economic impact, you know,it's it it can be scary to see
lots of these layoffs, butultimately, it opens up more
time for people to build thetypes of things that we're
talking about.
Justin (32:33):
Okay. So that I I'm glad you went there because that's
kinda what my crystal ball saysas well. We we hear all this
scary bullshit. Alright. 50%layoff.
50 per and and listen. The newsright now is backing it up.
Great big tech companies arelaying off just ridiculous
numbers of people. Alright? Andand I think there's a shakeout.
(32:53):
There's gonna it'll take sometime for this to settle down.
But in the end, I think whatwe're really gonna end up with
is just any other advancement intechnology where you're able to
leverage what you have, do abetter job, do it faster, do
more of it. Right? I don't thinkthat that's going to I mean,
look at the industrialrevolution. We're just doing
another version or anotheriteration of that.
That's what we're dealing with.Right? So we're gonna have more
(33:16):
wealth creation, more jobopportunities, better output,
better availability of productsand services. We're gonna this
is my belief. I think we'regonna do, like, live better
lives as a result.
Now, of course, there's scarystuff. There's unknowns. There's
there's threats. You know, andnow we need to we need to soon
get to the security aspect ofthis because this is a podcast
(33:36):
about cybersecurity. But as faras just productivity, I'll I'm
gonna use an example of, youknow, one of the most recent
things I did with AI, which isI'm I'm preparing to do a
podcast.
Right? Jesus. We're on thepodcast. I'm preparing for a
webinar.
Chase (33:54):
He's gonna make another one, y'all. Yeah.
Justin (33:56):
No end to the number of podcasts I can create. So I'm
I'm prepping for a webinar, andand it's something that I've
been talking about on thispodcast, the subject of the
webinar is, for over a year now.But for me to go ahead and and
prepare the bullet points andthe, you know, the slide deck
for it takes a shit ton ofresearch and preparation. But in
(34:18):
about, five to ten minutes, Idid punch it into an AI engine,
and I'm like, hey. Give me agood title for my webinar.
And it gave me a few things. Ifound one. I'm like, alright.
Hey. Why don't you throw somebullet points out there at me?
And I I did this accidentally,Chase, the way you said to do
it. I didn't say write awebinar. I said, what's a good
title for my webinar? And Ialready knew what I wanted to
(34:38):
talk about. And I'm like, hey.
What are what are some bulletpoints? Hey. Can you give me
some examples of, you know, howI can back that up? And so it's
going out and it's pulling allthe research and it's building
the the just the, you know, topto bottom, what I should talk
about in what order, and I cantell it to rewrite and and and
expand or or consolidate orwhatever. But I did probably
(34:59):
about a full day's worth ofresearch and preparation in
roughly ten minutes.
Now that's not to say that I canthen just read this thing word
for word and have any kind ofengaging content. I will use
those bullet points just to makesure that I'm staying on track,
kinda like I I'm doing rightnow. I've got a document that
I'm I'm going over, but I'm notreading it. Right? So because
(35:20):
I've got the experience, I'vedone the the research over the
last years, you know, of mycareer, I could get in front of
a group of people, and I cantalk way more intelligently than
I would have, but it's about asubject that I already know.
I'm not relying on AI for theactual intelligence. I'm just
using it for some of the theworkload. You know? So that's
(35:42):
that's what I love about itpersonally. And now we've gotta
talk though about some of thesecurity implications because
anytime, like I said in thebeginning, when we when when
technology grows and progresses,the bad guys find a way to
exploit it.
They they find a way to tosteal. Ultimately, they're
(36:03):
stealing our money. You know,however they do it, they're
getting out our money. So,Chase, what have you seen in in
your career, where AIspecifically has become a
threat, and how do we deal withthose threats?
Chase (36:21):
You know, I think I get, like, at least, like, 10 to 15
automated phone calls, 20 textmessages. Like, the the hot
thing right now is that I justsubmitted my loan application,
and we could talk
Justin (36:33):
to
Chase (36:33):
you and save you $85,000 I think what we're going to see,
just to continue on what you'retalking about is more targeted
like, hey, Justin, I know youjust bought a car, you know, and
more information about youthat's already available on the
Internet. Right? They're gonnause that to make more, more
complicated phishing attacks.Right? So I think part of the
(36:56):
answer here is, education.
Right? Teaching our parents,moms and dads, the old people.
Right? Like, don't answer thatphone call. In fact, I basically
never answer the phone anymore.
You know? So in thinking aboutsecurity, it has some level of
it is training. Right?Education. Hey.
We're gonna we're gonna get itfrom every single direction
(37:17):
because it's it's just nevergonna end. Right? I don't see
necessarily the governmentmoving anytime soon to, make a
change here unless you, heardthe state of the union the other
night. Maybe that happens. Maybeit doesn't.
But, you have a we havegenerations of the population
that don't even know, you know,like, how to log in to their
email. You know? Those are thepeople that we should be worried
(37:39):
about. When you get more into,like, SMB space, right, it's the
traditional frameworks, the NISTframeworks. Right?
SOC two, all that stuff. If yourorganization isn't hasn't
doesn't have a, you know, atight security policy and have
those things implemented and youdon't follow those guidelines,
you're gonna get hacked. Andthat's it. You know? I'm gonna
(37:59):
see AT and T got hacked.
They have all of the SocialSecurity numbers, you know?
Giant organization thatsupposedly is locked tight and
boom, everybody's SocialSecurity numbers on the
Internet. You know? I thinkyou're gonna get hacked. It's
gonna happen.
Right? So it's how do we dealwith that? How do we train
people to do it well? But youguys know this more than me. All
I can tell you is if you thinkit's bad now, it's gonna get
(38:20):
worse.
So Mhmm. Prepare for the worseand educate frameworks,
compliance. Right? Nobody lovesnobody loves the word
compliance. Going through SOCtwo is, you know, a lot of
documentation.
But then you get audited toensure that you're actually
doing it. That's the point.Right? That you're actually
Yeah. Secure.
If you're not, then you're gonnaget hacked. But I know you guys
(38:42):
know this better than I do.Mario, I'm curious what, you
know, what are you saying? Whatdo you think on this front?
Mario (38:48):
Yeah. No. I I completely agree exactly with everything
you just said, Jace. I mean, inin our world, we always say, you
know, it's it's those lowhanging fruits, the ones that,
are going to be, you know, it'sit's going to happen not you
know, if it happens, it's when.But, you know, you take the
proper precautions.
And like Justin says, you know,you you do everything you you
(39:11):
you're supposed to do. You'll be97% of the way there. You know?
Nobody's gonna be ever a %.Nobody's gonna guarantee you to
be a %.
But, you know, with technologyand with every tool out there,
there's gonna be those bad guysbecause these this is their
jobs. They're not this isn'tthose guys sitting in the
basement of their mother's housein their in their underwear just
(39:34):
trying to, like, cause chaos.They this is actually somebody's
job, and it's their job to, youknow, write that code and test
this and buy this and, you know,do that. It's gonna happen, but,
you know, with you know, justlike everything else, if you
take the proper steps, you know,you will you you know, you
you're you wanna deter them ormake their life a little harder
(39:57):
where that they move on to thatlow hanging fruit that I've
helped them.
Chase (40:01):
You remind me of, this actually happened. This is a
real life scenario. My aunt inlaw I think I didn't say that.
Right? My aunt in law got a,what there was a password drop
on the Internet, used,Suddenlink, which is now optimum
or something else.
Right? Their email has beentrashed forever. I remember when
I had it in college, like,there's no security. You know?
(40:21):
Mhmm.
Guy logs into her email, sendsher sends an email to herself
saying, I've hacked your email.Send me a bunch of money. Right?
And she's freaking out becauseshe doesn't, you know,
understand, like, the technicalpieces behind an actual email.
Sent off $250, created a Bitcoinsorry, a Coinbase account.
Right? And, like, he's goingthrough just resetting all of
(40:43):
her passwords because she's thesame password. I mean, it's,
like, basic it's a basicsecurity deal. You know? And we
can have the best securitypolicies setting up that VPN
site to site connection, butyou're never gonna get around
somebody being like, oh, yeah.
My password is one two threefour five. Please log in for me.
You know? So I don't know theanswer to that. That's why we
(41:04):
hire guys like you to come inand solve those problems
because, you know, I I canbarely set up a VPN deal.
But, yeah.
Justin (41:13):
I mean, you already said it. The it's education. Right?
We've we've put things in place,but a lot of times and what's
really tragic about the world ofcybersecurity is that we do all
this stuff behind the scenes. Weset stuff up.
But unless the people areproperly educated, and I would
argue a very strong culture putaround it, a culture of security
minded, security awareness, noneof it matters. None of the
(41:36):
technology matters because ittakes one click, it takes one
phone call, it takes onepassword given out. We can they
can undo everything that we putin place. Right?
Chase (41:44):
Yeah. Well, I and then it's too late. Right? My my
aunt-in-law, they were stepsaway from her Fidelity account.
I'm like, you give me theusername and password right now,
I'm gonna lock you out of youraccount.
And they were just steps away.I'm like, you know and and
that's when it's too late. It'slike, oh, yeah. Security. You
know?
And Right. No. Maybe no fault tothem, but, that's what's
(42:06):
unfortunate is, like, when youonly care about it after the
fact. So part of the challenge,right, being like, hey. This is
important because of x, y, andz.
And stories like that, I think,are really impactful. Yeah. You
know, she her retirement countson there, and she could've lost
all of her money. You know,thankfully, there's some I'm
sure Fidelity has rules inplace. But
Mario (42:24):
Yeah. And it's it's a lot of pea and a lot of times, it's
all avoided. You know, it can beavoided if you do it. If you do
the work, you are annoyed in theprocess of doing it. Like,
nobody likes two FA, you know,but you have to do it.
You know? And and that's noteven bulletproof itself, but
it's so much better than withoutit. You know? Like, in in your
(42:46):
example, if she had two FA andall that stuff, chances are he
wouldn't have been That
Chase (42:50):
would have happened.
Mario (42:51):
You know? But, you know, I'm gonna quote Justin again. If
if it's not annoying you, thenyou're, you know, you're not
doing it or or whatever Ibutchered your quote,
Justin (43:00):
Justin. Because the way to say this is security isn't a
giant pain in your ass. You'redoing it wrong. Exactly. That's
the actual Exactly.
Chase (43:08):
I love it.
Justin (43:08):
Alright, guys. Good stuff. As promised, we were
gonna keep today's episode rightat thirty minutes or less. We
are coming up on that mark rightnow with forty three minutes and
change. My math isn't very good,but, anyways, we're gonna go
ahead and and move to wrap thisup.
Guys, let's go ahead and assumethat somebody only listened to
this part of the podcast. We'regonna distill it down to your
(43:30):
number one key takeaway. What isit that is the most important
thing that people need tounderstand about artificial
intelligence, the responsibleuse of it, the secure use of it,
and how can we make their livesbetter? Mario, I'm gonna let you
go first.
Mario (43:47):
Yeah. I mean, for me, I I think it's something that people
need to understand that it isnot perfect. It is getting
better, but it is a tool. It'snot you know, just like any
other tool you get from, like,your hardware store, you have to
know how to use it, and you haveto use it properly and make sure
(44:08):
it's doing the job that youwant. You know, you whatever you
like, if you're if you have arewrite an email for you, you
know, and tell it to redo agrammar, you have to still read
it.
You know? You can't just blindlysay, do this for me and done. I
I'm finished. It it's supposedto make your life a little
(44:28):
easier. It's not supposed toreplace you right now.
That's my key takeaway.
Justin (44:34):
Okay. Chase, thoughts.
Chase (44:36):
Yeah. I would I would say for those that are scared, you
need to know that this isdecades in the making, not, you
know, not like overnight. Right?People have been working on this
literally for decades before,you know, maybe before they're
even real these real computersthat we use every day. But
instead of being scared of it,right, everybody should be
thinking about how to leverageit for their own benefit.
(45:00):
That's that's the only way,right, that you're gonna walk
away from this and not be theguy that lost his job and now
can't get another one. And sofor for those people, right,
that are in that spot or have abloated business, right, I would
say you need to leverage this,but to do it in a secure way.
Find the platforms that are SOCtwo compliant. Right? Not just
(45:21):
the mom and pop shops that havejust iterated their technology,
not just the platforms thatroped in AI.
Right? But I would say if you ifyou don't wanna be leveraged out
of the job, right, you gottaleverage AI to to be the thing
that you want it to be.
Justin (45:38):
Yeah. Okay. Alright, guys. And my key takeaway for my
fellow South Park fans is the AItook our jobs. It's happening.
It's real, but I really dobelieve my crystal ball says
that this is going to besomething that makes life
better. It makes our economybetter. It makes our businesses
better. We do need to learnabout it. We do need to use it
(46:00):
responsibly, efficiently.
And and, we've got guys likeChase to help us out with that.
You know, Mario and I alsodabble in this space, but,
Chase, I really love that, youknow, you're you're really
digging into processes andimprovements and streamlining.
And, I I think that is thefuture of not just AI, but
technology in general. So thankyou. Thank you for being here.
(46:24):
Mario, as always, thank you forbeing here. Guys, we're gonna go
ahead and wrap this up. So saygoodbye, and we'll see you next
week.
Chase (46:30):
Alright, guys. Bye, guys. Good luck out there. Ciao. Take
care.
You too.
Welcome everybody to episode 42 of Unhacked. Guys,
Unhacked is a bit of adeliberate misnomer. We talk
about, preventing breachesbecause here's the sad truth.
97% of the stuff we read aboutin the headlines is preventable
with basic security measures.But once you get hit, man, it's
just kinda too late.
There is no such thing asgetting unhacked. So, we lure
(00:37):
you in with a title that reallymeans nothing. I'm Justin
Shelley, CEO of Phoenix ITAdvisors. I keep businesses
protected from Russian hackers,from government auditors, and,
goddamn, the the attorneys thatcome up afterwards with the
class action lawsuits. We workwith clients in Texas, Nevada,
and Utah.
And I am here today with myusual cohost, Mario, and we've
(00:59):
got a special guest, Chase,today. Mario, real quick, tell
everybody who you are, what youdo, and who you do it for.
Mario (01:05):
How are you guys? As you know, Mario Zdaki, CEO of MasTec
IT. We are in New Jersey rightoutside of Manhattan, and we do
support for anybody who wants togive us their money.
Justin (01:20):
A specialist, I take it.
Mario (01:22):
Exactly. Now we we work with medium to small, small to
medium sized businesses, keepingthem protected, working
smoothly, and we specialize ingiving CEOs peace of mind and
help help them sleep better atnight.
Justin (01:37):
Love it. And, Brian's, AWOL again this week. We're
gonna hope he makes it nextweek. And that said, though,
we've got, we've got somebody tofill a spot. Brian, you better
hurry back.
You might get replaced. Today,we're sitting here with a guy
who who thinks he knows somestuff about AI. Now I don't
know. I've I probably nobody hasheard of AI yet. It's this new
(01:59):
trend.
Nobody's really talking aboutit, but it's it's starting to
evolve and develop. I've got Iwish that was true. It's like
all you hear about anymore isAI, and we're gonna dive into it
today. And I brought Chase hereto help us out with that. Now,
Chase, you are also kind of inthe Dallas area.
Yes?
Chase (02:19):
So BMW. Going on almost ten years.
Justin (02:22):
Okay. Alright. Well, I I bounce around. I've I'm home
based in Dallas. I've got stuffgoing on, like I said, in Nevada
and Utah, but we're gonna haveto get together one time and
grab beer or whatever and talkface to face even as much fun as
it is over the, you know, thethe computers.
Oh, I love it.
Chase (02:41):
Whatever your vice is.
Justin (02:42):
Oh, I forgot. Bourbon.
Chase (02:44):
Oh. You wanna bowl? Let's go bowl.
Justin (02:46):
Oh, now now you're speaking my language. Alright.
I've got all those vices. So,Chase, let me give you a little
bit of an introduction, and thenI'm gonna turn you loose and
tell me a little bit more inyour own words about what you
do. But, what I pulled off offof your profile here, Visionary
managing partner of AlpineAnchor, cutting edge com company
(03:07):
dedicated to elevatingbusinesses to the summit of
their industries.
I noticed that you kinda play onthe, Sherpa walking up the
mountain to, which well, I mean,which which one of the seven
great mountains is it that's
Chase (03:20):
All of them.
Justin (03:20):
All of them. Okay. Alright. I didn't wanna make any
assumptions. You know?
Anyways, passion for leveragingautomation, analytics, and AI. I
mean, this this is the word ofthe day. This is what
everybody's talking about. So Ithink you're a great fit for the
show. We're gonna talk about it,and we're gonna kinda bring it
home with what we always talkabout, which is cybersecurity
because as technology evolves,which it does, sometimes we
(03:42):
kinda think after the fact, oh,shit.
I forgot. We just opened upeverything to the bad guys,
including our bank account. So,Chase, tell me a little bit
about what you do, who you do itfor, and and maybe even a couple
of client success stories ifyou've got them.
Chase (03:55):
Yeah. Well, Justin, thanks for having me on the
show. Mario, good to meet
Justin (03:59):
you. Nice meeting you, Chase.
Mario (04:00):
Thank you for hopping on.
Chase (04:02):
Yeah. Looking forward to replacing Brian. But if he hops
on, you know, mid flow here, wecan, we can poke him a little
bit. But Yeah. Yeah.
Mario (04:09):
Well, you're gonna have to shave your head if you wanna
be a regular. You know?
Chase (04:13):
Like got some hair up here still.
Mario (04:14):
You took you took the hat off before, and I'm like, oh,
you know, on the from the sides,it looks like you fit in
perfectly.
Justin (04:20):
Supposed to be bald. We'll rename the show after us.
Chase (04:23):
Well, guys, I've I've built a career off of
interpreting, right, the thebusiness requirements, the
business process, thetechnology, the people involved.
Right? And what I've learned isthat nobody knows what they're
doing. They're all making it up.I'm making it up.
Justin (04:39):
Oh, god. That's so true.
Chase (04:40):
And everybody Googles it, but now everybody chat chippy
tees it. Right. But, I've landeda number of really great success
stories on basically, taking theprocess. Process. Right?
Making it more efficient. Andthat's before AI really came
around. Right? We leveragedautomation between CRMs and ERPs
(05:02):
to move significant, volumes ofthese transactions. And so
that's where I kind of, cut myteeth, deploying Salesforce for
enterprise grade companies, lotsof SMB, little bit of nonprofit.
Right? And got a really good,like, over the course of the
last eight years, basically gotthirty years of education in
(05:24):
back to back Zoom calls evenbefore Zoom was cool. But, yeah,
that's where that's where Ieffectively learned, like, hey.
Here's how we can can connectthese things in a way that makes
sense. Right?
And, leverage your time and yourmoney, right, and your resources
to do things faster, better,stronger. And so what I'm
focusing on now as I exited mylast company, right, I'm
(05:47):
building out a platform thatdoes the same exact thing.
Right? We're just adding in thisnext API, and that is AI. Okay.
But in thinking about clientsuccess stories, you know,
there's there's a lot of them.Part of those success stories
start with the process. Oneclient, right, that I'm, that I
(06:10):
worked on walked into the door.Hey. Show me the process.
Oh, I can't. It's all in ourheads. Right? So okay. Well,
what are we Mhmm.
What are we doing? You know, youwanna send me a lot of money,
but y'all can't even explainwhat it is you do. So for so for
one client, right, basicallystepped into the door. The
Salesforce world is is broken.They they didn't do it right.
It needs to be reimplemented. Wereimplemented it, scoped it,
(06:34):
architected it, reimplementedit. That client is still a
client today, and this is seven,eight years later. And then we
connected it to their ERPsystem. We're moving contractual
data back and forth.
We're moving data from Stripe.So a whole lot of automation and
integration. They are a a verywell known cybersecurity
(06:56):
nonprofit. And, obviously, theyare barely stepping into the AI
world, but had a lot of fun,hanging out with them, continue
to do so. Another one that, Ilove to think about or talk
about, right, are are, the oneswhere there's really no
technology in place.
It's kind of the like, well, webuilt a business off of Excel
(07:18):
sheets. Right? So, those are alot of fun because you can step
into the world of technology andme maybe being as good as I am
or maybe I'm terrible. I don'tknow. Right?
But I can step into that worldwith a well defined process.
Right? And now I can make it 10times more efficient. Right? 20
times more efficient.
I hate when people are like,well, I made it 37.35% more, you
(07:42):
know, more better.
Justin (07:44):
Why did
Chase (07:44):
you make that up? I don't know. You know?
Justin (07:46):
It's math. You wouldn't understand it.
Chase (07:48):
Yeah. Like, they they ran Google Analytics, and it said I
made money. You know? But what Ifound is that when you have that
that solid process that makesmoney, right, that does this
thing, that delivers on thisvalue, then you apply technology
to it. You really can achievesome really, really cool and
interesting things.
(08:09):
So, yeah, those those clientsare are still around today.
That's kind of where this Alpineanchor thing came into play.
Right? My goal with theseclients isn't to just get in
there, make some money, and thenwalk away. My goal is to get in
there and push them more andmore up to the top of that
mountain.
And I'll I'll leave it withthis. Right? But, got to spend
(08:30):
many years at Texas a and mUniversity where I gave them too
much money. I got too manypieces of paper. Right?
But, got to take my last companyto be a a twice twice over
winner of what they call theAggie one hundred. It's really
just like.
Justin (08:43):
Oh, nice.
Chase (08:46):
Top 100 Aggie companies. I got to see and interact with a
lot of people in that room. Thattotally get the process side.
Right? They scale their businessvery quickly.
You know? And they did itwithout well, some of them did
with VC money. Right? But theynailed the process. They killed
it.
They got into a market that wasunderutilized, under whatever.
(09:07):
Right? And they were walkingaway with 275% growth trajectory
pass over the last five years,you know, audited financials,
you know, so they couldn'treally I mean, I'm sure they
fudged some of it, but for themost point, for for the most
part, they did it. And that'swhat I wanna do. So with Alpine
Anchor, right, we're buildingout a platform where you can
take AI, not understand what itdoes, click to deploy it, and do
(09:33):
it in a way that makes sensecoming from somebody that's been
in the enterprise spaceleveraging security.
Right? All of these, like, it'snot a POC. Right? Like, this is
ready to roll for an enterprise,but I wanna do it for SMB.
Right?
I wanna focus on the companiesthat deliver lots of value, to
their to their clients, to theircustomers. Anyway, that's what
(09:54):
I'm up to these days.
Justin (09:56):
Alright. Well, that sounds like a lot. Now do you
fancy yourself a coder? Are youwriting code?
Chase (10:00):
I am. I Okay. I'm sure there's people that know me that
are like, yeah. Whatever. I gotto build back in the day, I was
translating Fortran, into,vb.net to build out some of the
first inter Internet connectedapps.
That was a lot of fun. We wereautomating HVAC, not Wagyu,
(10:23):
Wago. It's a German,programmable logic controller,
and they had it connected to theInternet. And I was like, this
is so cool. Let's do it.
And everybody's like, I don'tknow what you just did, but
we're gonna sell it for a lot ofmoney. And I was like, I was
like, oh, that's how the worldworks. So That
Justin (10:39):
is how the world works.
Mario (10:41):
So who's like, like, who's like the ideal type of
customer that would walk intoyour door Yeah. You know, email
you, you know, whatever whateverway of your communication
requirement is.
Chase (10:54):
It's, you know, that's something that I've been
unpacking as it relates to thisnew venture. Right? Because it's
very different than maybe yourtraditional, sales pipeline.
Right? My the person that I'mlooking for are the owners of
the business, right, wherethey've got too many people,
right, or their process isn'twell defined, right, or they've
(11:17):
got too much technology or maybenot enough.
Right? But, ultimately, it's theperson that's trying to scale
their company to make moremoney, right, to get more value,
right, but do it with less. Sothat's the person. In in a
vertical space, we're reallylooking for, legal or, law
firms. Right?
(11:38):
Commercial real estateinsurance. Really, the easiest
way for us to think about it isbasically, anybody that has some
regulated degree or the bar. Youhave to pass this big test to be
certified, licensed, whatever.Because the reality of the world
is those aren't going awayanytime soon, and they happen to
(11:59):
make a lot of money. So theyhave a lot of money to spend,
but that's where we're looking.
Mario (12:05):
Got it.
Justin (12:07):
Alright. That's, that's a lot, Chase. That's a lot. I'm
trying to figure out how to,like, respond and summarize and
say something intelligent. I'mjust gonna move on.
That no. Interestingly, though,we're we're going after a very
similar audience, which I dolove to hear because there's
there's so much room forcollaboration in a lot of this
stuff. I absolutely love whenyou're talking about process
(12:27):
improvement, and I don't thinkyou use that term. That's kinda
what I distilled it down to. ButI think that's kinda the the
really the key to everything.
You know? You have to workefficiently, and you've been
doing that for a very long time.If, dude, if you're working in
Salesforce and programming that,if I had a hat, I'd take it off
to you. Hats off. That's that'ssome serious stuff.
(12:51):
Writing code is serious stuff.And, really, AI is just kind of
an iteration of what you'realready doing. Correct?
Chase (12:58):
Yeah. That's actually the the best way to think about it.
I myself have written more codein the last six months than I
have in my entire life. So that,you know, the guy that's been
the coder his entire life islike, well, I bet it was really,
you know, really I don't can wecuss? Are we cussing on the
show?
Justin (13:15):
Oh, hell, yeah. Yeah. Okay.
Chase (13:16):
Well, that's really shitty. Well, it's not
documented. Right? Well, itdoesn't work. And Right.
Problem with that statement isit doesn't matter. Right?
Because I can iterativelyimprove it. This is what some
folks are doing in GitHub or inAzure DevOps. Right?
It's because the the codingprocess is asynchronous. It's
all text files. I mean,variations of text files. Right?
(13:37):
I can leverage AI to iterate onit and improve it.
So it doesn't matter that it'sgood. It's what matters is that
it's possible or it can be done.Yeah. Right. That it works.
Yeah. Absolutely.
Justin (13:47):
That's a key component. Okay. So let's let's just go
ahead and define AI. And I dothis because it's it's the term
that's getting thrown around byeverybody on the planet. And,
usually, what people mean whenthey say I, AI, Jesus, is chat
GBT.
Like, it can write a report forme in high school. Great. What
is and I'm gonna throw thisMario, why don't you you start
(14:10):
and then Chase come in andcorrect him if he's wrong. No
pressure, Mario. What exactly isartificial intelligence?
Explain it to an idiot like me.
Mario (14:20):
I I mean, honestly, your guess is as good as mine at this
point, but it it it it's they'vewith lately, what they've have
is they have machines, you know,computers that are now being
able to start thinking likehuman beings. It is analyzing
(14:41):
certain things coming up withintelligent it's not guesses,
but, you know, it it it analyzesit on the fly, and it ends up
producing what a, you know,smart human being would
eventually produce in matter ofseconds.
Justin (15:00):
Okay. That's a great way to explain it, non technically.
Now, Chase, I'm gonna punt toyou. Give us a little bit more
of a technical breakdown of whatthat how it's done. Because
you're right, Mario.
It is. It's like we're we'retrying to make computers act,
think, behave like humans.Right? Because then we can
replace humans, and we're gonnacome back to that later. But,
Chase, what's what goes onbehind the curtains?
Chase (15:21):
Yeah. I'm sure, OpenAI, Sam Altman's team would rip me
to shreds, but, you know,generically speaking, the goal
is to interpret the questionright in in a way that makes
sense to everybody. And the waythat I like to think about it is
that it's ultimately justpattern recognition. Right?
(15:41):
Yeah.
They cook that is into decisiontrees. Well, if yes, then that's
right, like traditional logic.And then what about now there's
multiple questions to answer andthere's multiple answers to
these questions. How do I figureout, like, what's the right path
to take? The first version thatmany like, the world saw of AI
(16:02):
was that predictive text on yourphone with iPhones and Androids.
Right? It would guess that youwere gonna type this word. And
that's where, like, that wholething again, the people that
wanna rip me to shreds, throw iton LinkedIn, tell me I'm an
idiot. But, when you take allof, like, the really technical
stuff out for just a second,it's really all just recognizing
(16:23):
the pattern, predicting whatthat next letter is or that next
decision. Right?
And then do that over largeamounts of datasets. That's why
we see all this talk aboutNVIDIA blowing up these h one
hundreds. Right? Those thosethings are basically like human
brains, and they can process itinfinitely faster than we can.
(16:45):
So then you apply the largedataset.
You give it a problem statement.Right? And now I can predict
what it thinks would be theanswer to whatever question you
come up with.
Justin (16:56):
So it's interesting these the way you both described
it because the human brain,Mario, going to you, is designed
for pattern recognition. That iswhat we do all day long. People
talk about their their gut,their instinct, their whatever.
That's just subconscious,subliminal not not subliminal,
subconscious, messages. Like,our our brain is looking out at
(17:17):
everything that it sees whetherwe're aware of it or not and
looking for patterns, lookingfor dangers, looking for
threats, and making predictions.
So, I I love that description,Chase, and it is exactly what
you said, Mario. We are teachingcomputers to be human, which
scares a few people. Correct?And now let's, let's kinda pivot
(17:37):
and talk about, because we ashumans have been able to
hallucinate for a long time. Oh,it turns out these computers are
doing the same thing as we teachthem to be human.
So now let's talk about what ahallucination is. And this time,
Chase, I'm gonna start with you.What is a hallucination in the
world of artificialintelligence?
Chase (17:56):
I I have not, had the opportunity of taking any
mushrooms, but I'm justimagining, like, as you're
describing that, like, well, letme give a mushroom to a
computer. What would that do?But, I think, for anybody that's
in a been in a self driving carand it does something like, oh,
or like a fast stop. Right? Orit it just kinda freaks out.
(18:18):
Right? Like, those are the veryfirst hallucinations that a
large population set has seen.You know? It's just
automatically breaking. Well,it's hallucinating something
that's a car is in the way, aperson's in the way, or it
hallucinates that the personisn't there when they actually
are.
Right? And we've seen some, youknow, tragic responses to that.
You take out the the drivingscenario. Right? A hallucination
(18:41):
is just an incorrect prediction.
Right? If you think about whenyou're driving and somebody is
looks like they're gonna come infront of you and you respond to
that, well, you're you'rehallucinating. Not in like the I
took some mushroom sense, but,like, I think he's going to do
x. Mhmm. But then he doessomething else, and you respond
to that x, that's thehallucination.
(19:02):
So we see a lot of this. It'sreally easy to, connect it to
human hallucinations. Like, Ithink I should do this. Well,
some people I I don't I don'tlove the alert the word
hallucination because itimplies, like, I took something.
Right?
I, like, took some drugs, andnow I'm hallucinating. It really
(19:22):
is just an incorrect prediction.If we tried to task Chat GBT
with predicting the price ofApple tomorrow, well, they have
some hallucination controls. Butultimately, right, it's just
gonna make an incorrectprediction because it has
doesn't have enough data. Andthat's what we see happening
when you're in the chat GPTs.
Right? It's just this is justwhat it thinks. But it moves so
(19:44):
fast. Right? It like, to thenext letter, to the next word,
to the next token.
Right? It doesn't stop to think,and that's why I've seen some of
these reasoning models pop up.But
Justin (19:53):
You know, a couple of couple examples I've heard of,
one from an attorney, and onefrom, you know, in the health
care space, attorneys will useit to try to find case studies,
right, and and take those tocourt. And then they find and
they're great, you know, perfectexample. It applies perfectly,
and it's true because AI said,except that it isn't.
Chase (20:14):
You know?
Justin (20:14):
And then I want that. You got disbarred or whatever?
That was like
Mario (20:19):
yeah.
Chase (20:19):
Oh, yeah. I know what you're talking about.
Justin (20:21):
And then you've got in health care, you know, it is
fascinating because it can beused to, diagnose diseases and
and prescribe treatments or atleast aid in that process, which
is great until it's not. So nowwe've got potential problems
because we've got thesecomputers that we're trying to
teach to be human, but they'renot. So it it brings up some
(20:43):
problems that we've illustratedhow and I'll you know, for
either one of you guys, how dowe prevent this? How do we get
ahead of this? Because it issomething that's happening right
now as we speak.
Mario (20:54):
Get ahead of what? I'm sorry.
Justin (20:55):
These hallucinations. How do we how do we make sure
that when we put something intoan AI machine, a generator,
whatever platform you're using,and it spits something out that
just looks spot on. Yeah. Butit's wrong. Like, how do you
know?
How do you fix it? How do youhow do we prevent this from
becoming a problem that killspeople or disbars attorneys or,
you know, like, keeps you put injail. Like, this is this can be
(21:16):
bad.
Chase (21:17):
Yeah. It can be really bad. It can be really scary.
Right? But if if I came to you,Justin, and said, you must tell
me, right, what the price ofApple will be tomorrow to the
dollar.
And if you get it wrong, thensomething bad happens. Well
Mhmm. You're gonna try to guess.Right? None of us are stock
brokers.
Right? And then something badhappens. Well, that's what
you're describing. So what youend up doing is reducing down
(21:40):
the question, reducing down thecontext, reducing down the
number of options. Okay.
Right. And and that's what Ifound works really well,
especially in these chat, chatrooms, chat bots. Right. Is just
break it down to the most simplequestion. It goes back to the
process.
Right? What's the what's thewhat's step one? Right. Don't
don't ask for an answer for thisthis 10 step process. Ask for
(22:03):
the answer of the step one.
And so what I found really worksworks really well even in
building out these agents,right, with these skills and
these apps that we're working onis just break it down to the
most like, the dumbest thing.Right? Like, how do I create an
email? Oh, okay. Yeah.
Like, I can tell you how to dothat. Right? The moment that you
try start trying to say in fact,this is something that I was
(22:24):
doing, literally this week.Like, I gave it the entire
problem statement to create asite to site VPN connection
Azure because that was myrequirement. I'm not a
networking guy.
Like, I know how to get my my,my home network working with
Ubiquiti. But, naturally, ithallucinated because it doesn't
know every single feature insideof Azure. Anyway, when I started
breaking it down, hey, tell methis one thing. Okay. Yeah.
(22:47):
Actually, that makes way moresense. You know? The
hallucinations are reduced whenyou reduce the size of the
problem.
Justin (22:54):
I like that. That's, that's a great great point.
Mario, did you have any input onthis one?
Mario (23:00):
Yeah. I mean, it's what I am what I was gonna say is that,
you know, what it's doing is thework of what a human being will
do. Right? In in but it's doingit at a much faster pace. So,
you know, in in Chase's example,create me, like, a step by step
direction.
A human being is gonna be ableto do it, but a human is gonna
(23:23):
probably say, take an hour, twohours, five hours to take care
of it. You know? It will do itin a matter of a minute. And in
just like a human, it's notpredicting the future. It cannot
predict the future.
So it can't tell you what theprice of Apple is gonna be
tomorrow or what's gonna happentomorrow. But it's scanning the
(23:45):
network, things that havealready been applied, and it's
bringing everything, you know,super fast, making it an like,
an intelligent, you know well, Idon't know what the word I'm
looking for, like, anintelligent documentation of
everything that it found, justlike a human would do it, but it
would be at a much faster pace.You know? And and, you know, I
(24:08):
know we're probably gonna talkabout it, but that is why, you
know, like Chase was talkingearlier, you know, companies
that have a lot of employees andthey owner wants to reduce it,
you know, with technology likethis is what's gonna help it
because he can this machine orthis AI can do whatever human
whatever a human being is doing,but it'll do it on a much faster
(24:31):
pace.
Justin (24:32):
Are you are you trying to say, Mario, that, somebody's
job might be at stake here? Areare we gonna be delving into the
world of South Park? They tookour jobs. And oh, god. I'm gonna
embarrass everybody with this,but, have either of you seen the
South Park episode where thealiens and, I mean, no.
(24:53):
They're where their future.There are people from the
future, I think, come back intime, and they're working for
pennies because they can investit and then whatever. I'm not
gonna get too far into SouthPark, but it is it's where I get
most of my intelligence,unfortunately. Nerd. So, Chase,
one of the things that caught myattention on a in a recent
episode of your podcast, whichis called The Junction.
(25:16):
Just a quick plug for you there.Although I hear you're coming
out with a new one, so we'lltalk about that more later. But,
50% of jobs will be replaced byAI by the year 2027. A, I'm
calling bullshit. I want you toback that up, and I know you
were deciding another source, sothat's fine.
B, that was something you saidor or cited about a year ago,
and I wanna know if there's anyupdates to that. And, c, this is
(25:38):
a multipart question if youcan't tell. If 50% of our jobs
go away, how screwed are we?Guys, discuss.
Chase (25:45):
Yeah. I mean, I think the headline is still valid, but I
think it's as we start tounderstand more and more how all
these things work, right, it'sit's that they're not going to
be replaced. It's that they'rejust they're they're going to be
replaced in a different way.Right? And the way that I liken
it is is now I can take aportion of this person's job and
(26:08):
I can automate it.
But you have 10 people doing it.Now you only need one. Right? So
it's it's a reduction ofrequirement a reduction in the
requirement of of resources.Right?
And so what we're gonna see islots of companies basically
reorganizing, rebuildingthemselves. And all of those
(26:29):
people that lost their jobs, Iwould encourage them to read,
the book called millionaire fastlane. Right? We're gonna see a
lot of one to five personbusinesses spin up and take tons
of market share from thesebigger companies that just have
too much overhead. Right?
They can't fire people fastenough. They can't let them go.
They can't retrain them. Theycan't whatever. Right?
(26:51):
But I can write code. I'vewritten more code. Right? Like I
said, in the last six monthsthan I have in my entire life.
Right.
Like, I don't need 30 coders. Idon't need $10,000,000. You
know? I don't need any of that.Well, there's people out there
that are smarter than me thathave better ideas.
And all of those people that areabout to have a ton of free
time, you know, the first thingthey're gonna do, hey. I need to
(27:12):
make money. Hey. I can't get ajob. Oh, I should start a
business.
So I think that's where we'regoing.
Justin (27:18):
Okay. Mario, thoughts?
Mario (27:20):
I like that. You know, it it it is you know, we we do see
it a lot already. You know, wefor example, being in IT and
stuff like that, we work with,like, companies, and it's all
about, like, SEO and blog postsand stuff like that. You know, I
actually attended a, a workshopa few weeks ago about somebody
(27:45):
you know, how they said thatthey could create a hundred
posts, in a matter you know,instead of whatever, whatever
time, they could create ahundred posts and have it
automatically post to yourLinkedIn, Instagram, Facebook,
all that stuff in under tenminutes. And, you know, Justin,
(28:07):
as you know, like, in themarketing group that we're in,
they have, like, a wholedepartment based just around,
you know, SEO and marketing andstuff like that.
Justin (28:17):
Right.
Mario (28:18):
This stuff could easily be done, in in a matter of
minute. And I imagine being ableto do about three posts per day
for the entire month in just tenminutes. You know? In in you
know, like, just Chase issaying, like, you can have a
company that has one to fivepeople, and they in one day,
they can service the service,like, a hundred different
(28:39):
customers and and and andcollect all the money.
Justin (28:44):
So let's let's actually take that point right there and
talk about the future of AI,both short term and long term.
And and this is a great way todebate this, because here's the
thing. While I agree that thatcan be done, I also feel like
the content that gets generated,number one, at least today can
(29:06):
be sniffed out as AI. You don'teven have to hardly look at it.
Right?
And it's it's terrible. I hatereading that stuff. I get I get
fooled by it sometimes. I'm notgonna lie. And it it'll take a
comment.
Maybe it's a some post I'mlooking at, some video, some
picture. I don't know. I alwaysgo to the comments, and it's
always like fake, fake, fake,fake, fake. AI, AI, AI, AI. So,
(29:29):
yes, let I mean, let's let'stalk about right now with with
AI the way it is, how valuableis this AI generated content for
SEO, for social mediaengagement, and and stuff like
that?
Either one of you guys' thoughts
Mario (29:42):
on that? At the moment and I agree. Yeah. And the thing
is the beauty of AI is that it'sgetting better every day.
Justin (29:48):
Right? Absolutely. You know? Yep.
Mario (29:50):
Because it is learning. And the the beauty of it is that
at very minimum, I think rightnow where we are today, we use
it as a starting tool or atleast a tool that will help you
get to wherever you wanna get tojust a little bit faster. You
know? I don't think it's at thepoint where it's completely
(30:11):
eliminating a lot of jobs, but Ithink it's kind of making
people's jobs a little easier, alittle faster, you know, better
service, you know, like in inthe I our IT field. Like, you
know, when we need to dosomething, yeah, we throw
something in chat.
GPT says, write me a PowerShellscript that will do this, you
(30:32):
know, and it will do it. It'smaking my technician's job a
little easier and is able toprovide a service faster, but
it's not necessarily replacingany of my guys at the moment.
Justin (30:45):
Okay. Chase?
Chase (30:47):
I think that the economic impact is going to not be talked
about because people that haveaccess and understand the
technology in a way that can beleveraged, right, they're not
gonna be on LinkedIn saying,hey. I posted three times a day.
It was all AI while I was on thebeach playing with my kid.
Right? Like, we're just notgonna see it.
(31:09):
We're gonna see it in, you know,like, layoffs. We're gonna see
it in this new company. You'reyou're starting to see some of
these on LinkedIn where they'reone to five people, and they've
got $10,000,000 in, annualrecurring revenue. Right? We're
gonna see more of those.
And so I don't think the theeconomic impact is detrimental.
Right? But it's effectivelygiving people the tools to build
(31:32):
out big, big companies thatprovide a lot of value. Dare I
say, a trickle down effect. Buteffectively, anybody today can
build a multimillion dollarbusiness and not need any kind
of investment.
They don't need to build out ateam of developers. They don't
need to go offshore anymore.
Mario (31:51):
Right.
Chase (31:52):
So I think it'll be really interesting because I
that's that's what I see now.The teams that we're working
with, they're one to two people.They've got a four person
office. Right? They've got aprocess that works, that makes
money.
And, traditionally, you'd goraise some money so you could
speed up that growth. Right?That you could market more, all
that stuff. Right, you'd have ateam of developers that can
(32:13):
develop it faster. Well, I don'tI don't need the that anymore.
And the people that I work with,neither do they because I'm
gonna provide that kind oftechnology for them. So, I mean,
the economic impact, you know,it's it it can be scary to see
lots of these layoffs, butultimately, it opens up more
time for people to build thetypes of things that we're
talking about.
Justin (32:33):
Okay. So that I I'm glad you went there because that's
kinda what my crystal ball saysas well. We we hear all this
scary bullshit. Alright. 50%layoff.
50 per and and listen. The newsright now is backing it up.
Great big tech companies arelaying off just ridiculous
numbers of people. Alright? Andand I think there's a shakeout.
(32:53):
There's gonna it'll take sometime for this to settle down.
But in the end, I think whatwe're really gonna end up with
is just any other advancement intechnology where you're able to
leverage what you have, do abetter job, do it faster, do
more of it. Right? I don't thinkthat that's going to I mean,
look at the industrialrevolution. We're just doing
another version or anotheriteration of that.
That's what we're dealing with.Right? So we're gonna have more
(33:16):
wealth creation, more jobopportunities, better output,
better availability of productsand services. We're gonna this
is my belief. I think we'regonna do, like, live better
lives as a result.
Now, of course, there's scarystuff. There's unknowns. There's
there's threats. You know, andnow we need to we need to soon
get to the security aspect ofthis because this is a podcast
(33:36):
about cybersecurity. But as faras just productivity, I'll I'm
gonna use an example of, youknow, one of the most recent
things I did with AI, which isI'm I'm preparing to do a
podcast.
Right? Jesus. We're on thepodcast. I'm preparing for a
webinar.
Chase (33:54):
He's gonna make another one, y'all. Yeah.
Justin (33:56):
No end to the number of podcasts I can create. So I'm
I'm prepping for a webinar, andand it's something that I've
been talking about on thispodcast, the subject of the
webinar is, for over a year now.But for me to go ahead and and
prepare the bullet points andthe, you know, the slide deck
for it takes a shit ton ofresearch and preparation. But in
(34:18):
about, five to ten minutes, Idid punch it into an AI engine,
and I'm like, hey. Give me agood title for my webinar.
And it gave me a few things. Ifound one. I'm like, alright.
Hey. Why don't you throw somebullet points out there at me?
And I I did this accidentally,Chase, the way you said to do
it. I didn't say write awebinar. I said, what's a good
title for my webinar? And Ialready knew what I wanted to
(34:38):
talk about. And I'm like, hey.
What are what are some bulletpoints? Hey. Can you give me
some examples of, you know, howI can back that up? And so it's
going out and it's pulling allthe research and it's building
the the just the, you know, topto bottom, what I should talk
about in what order, and I cantell it to rewrite and and and
expand or or consolidate orwhatever. But I did probably
(34:59):
about a full day's worth ofresearch and preparation in
roughly ten minutes.
Now that's not to say that I canthen just read this thing word
for word and have any kind ofengaging content. I will use
those bullet points just to makesure that I'm staying on track,
kinda like I I'm doing rightnow. I've got a document that
I'm I'm going over, but I'm notreading it. Right? So because
(35:20):
I've got the experience, I'vedone the the research over the
last years, you know, of mycareer, I could get in front of
a group of people, and I cantalk way more intelligently than
I would have, but it's about asubject that I already know.
I'm not relying on AI for theactual intelligence. I'm just
using it for some of the theworkload. You know? So that's
(35:42):
that's what I love about itpersonally. And now we've gotta
talk though about some of thesecurity implications because
anytime, like I said in thebeginning, when we when when
technology grows and progresses,the bad guys find a way to
exploit it.
They they find a way to tosteal. Ultimately, they're
(36:03):
stealing our money. You know,however they do it, they're
getting out our money. So,Chase, what have you seen in in
your career, where AIspecifically has become a
threat, and how do we deal withthose threats?
Chase (36:21):
You know, I think I get, like, at least, like, 10 to 15
automated phone calls, 20 textmessages. Like, the the hot
thing right now is that I justsubmitted my loan application,
and we could talk
Justin (36:33):
to
Chase (36:33):
you and save you $85,000 I think what we're going to see,
just to continue on what you'retalking about is more targeted
like, hey, Justin, I know youjust bought a car, you know, and
more information about youthat's already available on the
Internet. Right? They're gonnause that to make more, more
complicated phishing attacks.Right? So I think part of the
(36:56):
answer here is, education.
Right? Teaching our parents,moms and dads, the old people.
Right? Like, don't answer thatphone call. In fact, I basically
never answer the phone anymore.
You know? So in thinking aboutsecurity, it has some level of
it is training. Right?Education. Hey.
We're gonna we're gonna get itfrom every single direction
(37:17):
because it's it's just nevergonna end. Right? I don't see
necessarily the governmentmoving anytime soon to, make a
change here unless you, heardthe state of the union the other
night. Maybe that happens. Maybeit doesn't.
But, you have a we havegenerations of the population
that don't even know, you know,like, how to log in to their
email. You know? Those are thepeople that we should be worried
(37:39):
about. When you get more into,like, SMB space, right, it's the
traditional frameworks, the NISTframeworks. Right?
SOC two, all that stuff. If yourorganization isn't hasn't
doesn't have a, you know, atight security policy and have
those things implemented and youdon't follow those guidelines,
you're gonna get hacked. Andthat's it. You know? I'm gonna
(37:59):
see AT and T got hacked.
They have all of the SocialSecurity numbers, you know?
Giant organization thatsupposedly is locked tight and
boom, everybody's SocialSecurity numbers on the
Internet. You know? I thinkyou're gonna get hacked. It's
gonna happen.
Right? So it's how do we dealwith that? How do we train
people to do it well? But youguys know this more than me. All
I can tell you is if you thinkit's bad now, it's gonna get
(38:20):
worse.
So Mhmm. Prepare for the worseand educate frameworks,
compliance. Right? Nobody lovesnobody loves the word
compliance. Going through SOCtwo is, you know, a lot of
documentation.
But then you get audited toensure that you're actually
doing it. That's the point.Right? That you're actually
Yeah. Secure.
If you're not, then you're gonnaget hacked. But I know you guys
(38:42):
know this better than I do.Mario, I'm curious what, you
know, what are you saying? Whatdo you think on this front?
Mario (38:48):
Yeah. No. I I completely agree exactly with everything
you just said, Jace. I mean, inin our world, we always say, you
know, it's it's those lowhanging fruits, the ones that,
are going to be, you know, it'sit's going to happen not you
know, if it happens, it's when.But, you know, you take the
proper precautions.
And like Justin says, you know,you you do everything you you
(39:11):
you're supposed to do. You'll be97% of the way there. You know?
Nobody's gonna be ever a %.Nobody's gonna guarantee you to
be a %.
But, you know, with technologyand with every tool out there,
there's gonna be those bad guysbecause these this is their
jobs. They're not this isn'tthose guys sitting in the
basement of their mother's housein their in their underwear just
(39:34):
trying to, like, cause chaos.They this is actually somebody's
job, and it's their job to, youknow, write that code and test
this and buy this and, you know,do that. It's gonna happen, but,
you know, with you know, justlike everything else, if you
take the proper steps, you know,you will you you know, you
you're you wanna deter them ormake their life a little harder
(39:57):
where that they move on to thatlow hanging fruit that I've
helped them.
Chase (40:01):
You remind me of, this actually happened. This is a
real life scenario. My aunt inlaw I think I didn't say that.
Right? My aunt in law got a,what there was a password drop
on the Internet, used,Suddenlink, which is now optimum
or something else.
Right? Their email has beentrashed forever. I remember when
I had it in college, like,there's no security. You know?
(40:21):
Mhmm.
Guy logs into her email, sendsher sends an email to herself
saying, I've hacked your email.Send me a bunch of money. Right?
And she's freaking out becauseshe doesn't, you know,
understand, like, the technicalpieces behind an actual email.
Sent off $250, created a Bitcoinsorry, a Coinbase account.
Right? And, like, he's goingthrough just resetting all of
(40:43):
her passwords because she's thesame password. I mean, it's,
like, basic it's a basicsecurity deal. You know? And we
can have the best securitypolicies setting up that VPN
site to site connection, butyou're never gonna get around
somebody being like, oh, yeah.
My password is one two threefour five. Please log in for me.
You know? So I don't know theanswer to that. That's why we
(41:04):
hire guys like you to come inand solve those problems
because, you know, I I canbarely set up a VPN deal.
But, yeah.
Justin (41:13):
I mean, you already said it. The it's education. Right?
We've we've put things in place,but a lot of times and what's
really tragic about the world ofcybersecurity is that we do all
this stuff behind the scenes. Weset stuff up.
But unless the people areproperly educated, and I would
argue a very strong culture putaround it, a culture of security
minded, security awareness, noneof it matters. None of the
(41:36):
technology matters because ittakes one click, it takes one
phone call, it takes onepassword given out. We can they
can undo everything that we putin place. Right?
Chase (41:44):
Yeah. Well, I and then it's too late. Right? My my
aunt-in-law, they were stepsaway from her Fidelity account.
I'm like, you give me theusername and password right now,
I'm gonna lock you out of youraccount.
And they were just steps away.I'm like, you know and and
that's when it's too late. It'slike, oh, yeah. Security. You
know?
And Right. No. Maybe no fault tothem, but, that's what's
(42:06):
unfortunate is, like, when youonly care about it after the
fact. So part of the challenge,right, being like, hey. This is
important because of x, y, andz.
And stories like that, I think,are really impactful. Yeah. You
know, she her retirement countson there, and she could've lost
all of her money. You know,thankfully, there's some I'm
sure Fidelity has rules inplace. But
Mario (42:24):
Yeah. And it's it's a lot of pea and a lot of times, it's
all avoided. You know, it can beavoided if you do it. If you do
the work, you are annoyed in theprocess of doing it. Like,
nobody likes two FA, you know,but you have to do it.
You know? And and that's noteven bulletproof itself, but
it's so much better than withoutit. You know? Like, in in your
(42:46):
example, if she had two FA andall that stuff, chances are he
wouldn't have been That
Chase (42:50):
would have happened.
Mario (42:51):
You know? But, you know, I'm gonna quote Justin again. If
if it's not annoying you, thenyou're, you know, you're not
doing it or or whatever Ibutchered your quote,
Justin (43:00):
Justin. Because the way to say this is security isn't a
giant pain in your ass. You'redoing it wrong. Exactly. That's
the actual Exactly.
Chase (43:08):
I love it.
Justin (43:08):
Alright, guys. Good stuff. As promised, we were
gonna keep today's episode rightat thirty minutes or less. We
are coming up on that mark rightnow with forty three minutes and
change. My math isn't very good,but, anyways, we're gonna go
ahead and and move to wrap thisup.
Guys, let's go ahead and assumethat somebody only listened to
this part of the podcast. We'regonna distill it down to your
(43:30):
number one key takeaway. What isit that is the most important
thing that people need tounderstand about artificial
intelligence, the responsibleuse of it, the secure use of it,
and how can we make their livesbetter? Mario, I'm gonna let you
go first.
Mario (43:47):
Yeah. I mean, for me, I I think it's something that people
need to understand that it isnot perfect. It is getting
better, but it is a tool. It'snot you know, just like any
other tool you get from, like,your hardware store, you have to
know how to use it, and you haveto use it properly and make sure
(44:08):
it's doing the job that youwant. You know, you whatever you
like, if you're if you have arewrite an email for you, you
know, and tell it to redo agrammar, you have to still read
it.
You know? You can't just blindlysay, do this for me and done. I
I'm finished. It it's supposedto make your life a little
(44:28):
easier. It's not supposed toreplace you right now.
That's my key takeaway.
Justin (44:34):
Okay. Chase, thoughts.
Chase (44:36):
Yeah. I would I would say for those that are scared, you
need to know that this isdecades in the making, not, you
know, not like overnight. Right?People have been working on this
literally for decades before,you know, maybe before they're
even real these real computersthat we use every day. But
instead of being scared of it,right, everybody should be
thinking about how to leverageit for their own benefit.
(45:00):
That's that's the only way,right, that you're gonna walk
away from this and not be theguy that lost his job and now
can't get another one. And sofor for those people, right,
that are in that spot or have abloated business, right, I would
say you need to leverage this,but to do it in a secure way.
Find the platforms that are SOCtwo compliant. Right? Not just
(45:21):
the mom and pop shops that havejust iterated their technology,
not just the platforms thatroped in AI.
Right? But I would say if you ifyou don't wanna be leveraged out
of the job, right, you gottaleverage AI to to be the thing
that you want it to be.
Justin (45:38):
Yeah. Okay. Alright, guys. And my key takeaway for my
fellow South Park fans is the AItook our jobs. It's happening.
It's real, but I really dobelieve my crystal ball says
that this is going to besomething that makes life
better. It makes our economybetter. It makes our businesses
better. We do need to learnabout it. We do need to use it
(46:00):
responsibly, efficiently.
And and, we've got guys likeChase to help us out with that.
You know, Mario and I alsodabble in this space, but,
Chase, I really love that, youknow, you're you're really
digging into processes andimprovements and streamlining.
And, I I think that is thefuture of not just AI, but
technology in general. So thankyou. Thank you for being here.
(46:24):
Mario, as always, thank you forbeing here. Guys, we're gonna go
ahead and wrap this up. So saygoodbye, and we'll see you next
week.
Chase (46:30):
Alright, guys. Bye, guys. Good luck out there. Ciao. Take
care.
You too.
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