May 16, 2024 • 28 mins
Discover the future through the eyes of a tech visionary as HackTech's CEO, Hakab Sharabkhanyan, joins us to unveil how AI is catapulting industries into new heights of efficiency and innovation. At the young age of 19, Hakob embarked on a journey that has led to commanding an 80-person team at the forefront of digital transformation.
Our discussion orbits around the strategic application of AI in sectors such as legal, marketing, and advertising, and how these integrations are not just about ubiquity, but about enhancing business processes with precision. From reshaping the traditional roles of sales teams to the necessity of human oversight in AI-assisted legal documents, Hakob provides an invaluable perspective on the delicate dance between AI-driven advancements and the irreplaceable human touch.
We also tackle the burgeoning challenges and opportunities presented by AI. The episode peels back the layers on the intricate relationship between human judgment and AI outcomes in the legal field, especially when the stakes are as high as immigration. As marketing strategies become increasingly personalized, we discuss the importance of maintaining authenticity in a world proliferated with deepfakes and AI-generated content.
With Hakob's insights, learn how companies are navigating the complexities of adopting an AI-first strategy despite obstacles like a lack of expertise and understanding of AI.
Join us for a conversation that promises to enlighten, inspire, and provoke thought on integrating AI into the fabric of industry operations.
About Hakob:
https://www.linkedin.com/in/hakobsharabkhanyan/
About HackTech LLC
https://gohacktech.com/
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:44):
Thank you very much.
Welcome back, fellow travelers.
In today's episode, we're goingto dive deep into the topic of
how AI is going to impactindustries such as the legal,
marketing and the advertisementindustry, and joining us on this
topic, we have an amazing guest, hakab, who is the visionary
CEO and founder of HackTech.
(01:05):
Hacktech is not just riding thewaves of digital transformation
, they're creating it.
They offer tailored AIsolutions and custom software
engineer to help skyrocketproductivity.
Hakab's expertise is pushingthe boundaries, for the legal
and marketing sectors have madehim a sought after voice in this
digital transformation.
So, hacab, welcome to the show.
(01:27):
We're excited to have you.
I think you're also joining usfrom Armenia, is that correct?
Speaker 2 (01:31):
Yeah, that's correct.
Thanks, steve.
Thanks for being here.
Speaker 1 (01:34):
Absolutely Welcome to the show.
So tell us a little bit aboutwhat HackTech does and how you
became CEO of this amazingcompany.
Speaker 2 (01:42):
Yeah, actually I founded the company when I was
19 years old so I was studyingin the second year in my
university and I decided that Ineeded to start a software
engineering firm.
So it makes us already nineyears and during nine years we
reached from a single mancompany to a team of 80
(02:03):
professionals.
And what Haktan does and theway we position ourselves, that
we are not a traditionaloutsource or outsource agency.
What we do is engineeringpartnerships.
So with this big team like 80people, we have right now just
nine clients, so all initialclients.
We have a dedicated team, fullcycle engineering, from idea
(02:24):
like, from product management,business analyst to actual
development, design, developsall the stuff together.
And what makes the most sensein this model for me is that our
team is kind of becoming partof our client's team and like
just being motivated by theimpact they make on our client's
project, which is a very bigdriver in IT.
(02:47):
By our logic, we are industryagnostic, but it just happened
the way that we accumulated somuch knowledge in the legal and
marketing and other types ofindustry that right now it's
mainly main focus in terms ofdigital transformation.
Speaker 1 (03:06):
That's incredible.
I know that AI has definitelybeen riding a wave and we've
started to see itstransformation starting to occur
and even some disruptions thatwe're starting to see kind of in
different industries andindustries in different segments
.
So walk us through a little bitkind of what you're seeing from
, let's just say, advertisementand marketing.
(03:26):
How is AI really kind ofplaying a role in transforming
these very kind of?
You can think of them astraditional, very legacy type of
industries.
Speaker 2 (03:37):
Yeah, I think it's just becoming like you either
adopt AI, use AI or you will beout of the market very soon.
And it doesn't mean that youneed to use AI in every part of
your business.
It's more about using it theright way to boost your
productivity.
For me, if I talk to a companynow and I'm sure it will be
everyone in one, two years whenyou talk to a company and ask,
(04:00):
how do I see you leverage AI, ifthe answer is we don't use AI,
then you look at these companiesthat are at least 20-30% less
productive than theircompetitors and like leverage AI
doesn't mean that everyone isgoing to build their own AI
solution.
It can be like just learning howto properly prompt a talk to
(04:21):
GPT, because it's not so easy tolearn this.
So for me, it's kind of likeusing the internet, so if you
are not using an internet, youcan't be in an industry.
Now, the same is true formarketing and other item
industries.
And if you are a product likeyou have a marketing or
advertising product then youneed to adopt AI as a solution
(04:44):
in every part of your business,because from creating to
measuring the success metrics,because AI is not just like GDP
or just conversational.
So check how your campaigns are.
I mean, automatically adjustthe campaigns.
All these different kinds of AI.
I believe everyone reminds meof Matthew.
Speaker 1 (05:05):
Yeah, I would think that with marketing, you know,
there's a real push towards, youknow, a really big push in
marketing towards morepersonalization.
There's more things around dataanalytics.
There's more things aroundtrying to build more creative
and interactive customerengagements, and I really think
that you know, and I think I seethe data is starting to move
(05:25):
this way.
I really think that you knowand I think I see the data is
starting to move this way too.
Is that you know?
Is that there's marketingcompanies are starting to they
need to embrace kind of an AIfirst strategy.
Is that right?
Speaker 2 (05:36):
Yeah, yeah, that's right, but again like they don't
need to fully rely on AIbecause it will kill the
personalization.
If you like, just use GVD towrite a copy and send it to
people.
They will not read because evenfrom the first line, you can
understand that this is AIgenerated.
So it's all about using AI inthe right way, like still
(05:56):
putting your fork on creatingyour campaigns, creating your
copies, but using AI wheneverit's best, whenever it can hit
the most value.
Speaker 1 (06:08):
So definitely, dr Andy Roark.
So definitely okay, so we needto.
I think that there's kind of acrawl, walk, run type of
perspective, right Is that?
I think it starts witheducating the right type of AI
and being very prescriptiveabout how it's being used with
things that are customer facing.
I think that's where you'retrying to go right, okay, and
what have you been seeing, Iknow, in terms of kind of you
(06:30):
know, when you're gettinginvolved with certain customers
in these industries, are youseeing?
Is it that there's a lack ofadoption due to lack of
understanding and how AI works,or understanding and expertise
with an AI?
Where do you start to kind ofsee more of a skill or a
technical deficiency with them,kind of moving forward with an
AI?
Where do you start to kind ofsee more of a skill or a
technical deficiency with them,kind of moving forward with an
AI approach?
Speaker 2 (06:49):
Yeah, actually, for me, some of these industry
companies having like CTO or CIO, even if they don't have a
product, even if they don't havelike internal software, they
still have this role to keepthem up to date with technology.
And in this case it is mucheasier because these people
understand the value.
These people know that at somepoint they need to build
(07:11):
something for them.
And the other scenario, wherethe founder or CEO is not
technical, you need to do a lotof job to educate them.
Sometimes calculate like returnon investment.
So, hey, you know like you arelosing 20% of productivity here
and we build these customsoftware or implement this AI
(07:32):
solution for you that like in amonth or in six months or in a
year, and we'll cover your costs.
So the way we typically workwhen starting a new relationship
is opening a deep logisticproduct manager.
So a product manager spends amonth or two with their company,
sees all their day-to-dayprocesses and then comes up with
(07:54):
a product solution that they'llsolve their needs.
Speaker 1 (07:57):
That's interesting.
I mean, talk to me a little bitabout what you're seeing across
the C-suite.
I know you mentioned CIO andCTO.
Those tend to kind of be moreof the technology and
information leaders inside of anorganization.
Do you see organizations thatdon't have CTOs or CIOs that
have the right type of expertise?
(08:18):
I mean, is that typically whereHackTech comes in?
Talk to me a little bit abouthow you kind of bridge these two
roles together with this newkind of disruptive form of
technology.
Speaker 2 (08:28):
Yeah, that's exactly what Haktek does.
If a company is not having aCTO, they need to go to digital
transformation.
It's very hard because youcan't just hire, like even
senior developers, and expectthat something will be built.
You need the domain knowledge,you need the tools, expertise,
all these that CTO usuallybrings to the table, and with
Haktek, that's what we bring tothe table.
(08:49):
So we are not just outstaffing,because for me, outstaffing is
not an IT business, it's more anHR business.
So we are not just deploying,like saying that, a local, we
are deploying the team who knowsthe processes well, everyone in
Hacktech aligned with theprocesses that we are working
and they are coming with theseprocesses implementing it to the
Hmm, what do you, what are youseeing and kind of going to
(09:12):
dovetailing back here is, youknow I want to work through, you
know, kind of the the the roleof AI in startups.
Speaker 1 (09:18):
I know we talked about CTOs and CIOs.
You know we we see how mostestablished companies kind of in
in in the space have kind ofgot a very mature C-suite of
your board of directors.
Startups, you know they'retrying to get a product out to
the market pretty quickly, right, so they're trying to scale for
growth and efficiency.
What do you see as somepotential pitfalls when it comes
(09:41):
to startups?
When they start to leveragethings like AI, where do you
start to see some of them notreally hitting their mark?
Speaker 2 (09:49):
Yeah, actually, again here there are two types of AI.
One is just actually a coupleof levels or just two like.
First level is just leveragingthe GPT APIs or any other model
APIs to bring some AI componentsinto your product, Like it
doesn't matter if you are an AIstartup or any other industry
startup.
I mean, if you have a text boxwhere someone should type
(10:11):
something, it's a verylow-hanging fruit to integrate
GPT and give the userpossibility to generate it
automatically.
The next level is promptengineering, to deeper
understand how all it works andcome up with prompts that will
give the most value.
And the other level is trainingthe models itself, getting the
(10:33):
most value.
If the R&B data and the otherlayer would be like going and
creating your own models andsocial models.
Speaker 1 (10:42):
That's interesting.
You know, you mentioned datamodeling and I really wanted to
kind of double click on this onehere, and this is just maybe
just kind of helping ouraudience just understand a
little bit.
More is, if you've got an ideawith a startup, right, they're
leveraging some sort of languagemodel, they're leveraging some
sort of AI.
Where do they get the data tostart doing the data modeling?
(11:05):
Where does that typically tendto come from, right?
Where do they leverage thatsame type of you know the amount
of data, or do they?
Or do they not?
They don't use the data.
Speaker 2 (11:17):
Most AI startups don't, and I was making this
joke.
I was recently in a bigconference like Web Summit in
Qatar and, like I would say, 80%of startups were having an AI
next to their own name.
So it's like something AI,something AI, and you see that
everyone is just leveraging theapis or calling it an ai product
(11:38):
, which actually is a.
It's just a software using likebasic integrations.
So most of the companiesbecause, like for very, very
easy, very basic model training,you will need at least like,
let's say, if it'sconversational ATA and we will
have thousands of conversationsand we know that we're already
adding more For something likemore to get a better result, you
(12:00):
will need like hundreds ofthousands of them.
So most companies just eithernew ATAs or, if they are like,
getting stronger skills, theyare doing some problem.
Speaker 1 (12:09):
Hmm, so what do you think that the three key, what
would you say are three key?
Three key, uh, or three keyassets that a startup needs to
be successful when they'relooking to leverage things like
AI and not just basically saying, hey, we're X company and that
we've got, you know, ai next toit.
What do you start to see?
And when you evaluate startupsin terms of kind of three key
(12:32):
components that they need tohave in order for them to say
there's a potential for you tohave great success or you're
just never going to go anywhere?
Speaker 2 (12:40):
Yeah, I fully.
First of all, again, if it's atechnological startup and they
want to adopt AI, they need tohave a CTO.
It's a must.
They need someone whounderstands.
First of all, they need AI ormore, because sometimes you can
just go train models and do allthis complex stuff and meet us
at dollar, while you can justuse some open source model.
(13:01):
And we saw a lot of things afterthis AI hype A lot of startups
who were doing their internalengineering, like doing some
complex researches on their ownbusiness model and all
investments that they weregetting was related to this uh
core, uh ai research and thensomething like from this giant
(13:22):
tech company something opensource coming and killing their
business.
So it happened a lot.
Like many companies before gptbecame available to everyone,
many companies were were doingresearch in a lower scale and
getting investment in thisresearch.
Then, with GPT, I guess 90% ofthem just get out of the market.
So the first is having propertexting there.
(13:44):
Second, understanding thevision, making sure like you
need that AI solution, you needthat to go and actually research
, do the research in that field.
And the third one was checkthat nothing exists in that
space, nothing these tech giantsare doing in that space.
Speaker 1 (14:04):
It definitely seems okay.
So you definitely got to havethe right leadership in place to
kind of help steer and kind, ofcourse, correct kind of where
the vision is actually going tobe and then setting the journey
for how we're going to achievethat as an organization.
Sounds like those are some keydifferentiators every startup
needs to have.
Is that key leadership here?
I wanted to kind of justdovetail back into the topic
(14:28):
around AI's influence around thelegal industry.
I know that there's a lot ofpotential for AI to disrupt
traditional type of legalpractices.
What are you seeing from thisparticular angle when it comes
to leveraging AI with regards tolegal industry, legal type of
contracts or even if, in fact,if it's just kind of mixing
(14:50):
these two together, is it a goodcombination or is it you start
to see that there might be someother way that there might be?
Speaker 2 (14:58):
some some other other way that this might go.
Yeah, actually, a little tech,little industries being affected
with AI.
And again, it's not going tochange people, it's not going to
replace human, but it's goingto make them more productive,
starting from like just researchthat any other rebuild should
do, or they really like justresearch that any R&D build
should do on their daily job,from to creating contracts,
(15:21):
creating some documents, and wehave a very successful case
study right now working with abig integration company who is
dealing with O1, h1b visas.
If you know, it's very complex,like five, six hundred pages of
PDF per weekend and they arehandling it in a scale.
And we started working withthem about two years ago.
We came up with the customsoftware which accumulated all
(15:43):
the data and it was the AI juststreamlining the processes, the
data from practitioners, etcetera, et cetera, and with this
AI we started to automate a lotof.
I think like 50, 60% of thepetition can be automated by AI
and then just immigrationspecialist or a common agent
will approve and send to thenext teenager.
(16:05):
So and this is just one examplefrom immigration law, but it's
a completely different way.
Speaker 1 (16:13):
No right, you would think that at least I know.
I probably would think that youknow planning low price.
You would think that at least Iknow.
I probably would think that youknow leveraging things to be
able to look at things withinlegal such as looking at things
such as you know contracts andthen looking at things such as
you know keywords to be able tolook at and assess certain
levels of risks within contracts.
I know you mentioned H-1Bs andvisas and things like that.
(16:36):
There's a lot of documents thathas to source through, so I
think AI is great applicationthere.
Where do you see as a potentialpitfall when it comes to AI?
Where do you see that thereneeds to be some sort of
boundary or guardrail where youmight need to have some sort of
kind of human interaction tokind of say, hey, I need to make
a call on the field.
This was a false positive onAI's part, or where do you kind
(16:59):
of see this?
Speaker 2 (17:00):
Yeah, again, like, for example, O1 or H1B is super
important, like for some people,it's like life's important
thing.
So what we are doing every partof AI generation should be
checked by a foreign orimmigration specialist.
So AI is doing.
Every part of AI generatedshould be checked by a foreign
or immigration specialist.
So AI is doing a lot ofmistakes.
Again, it's helping you toboost productivity, but you can
(17:21):
just ask AI to generate 600pages of petition for you and
you hope that you will beapproved.
So whatever AI doing in anyindustry where there is
importance to be always correct,it should always pass through
the human.
Speaker 1 (17:39):
Okay, so that's where I was getting at.
So, yeah, so it seems likeyou're offloading the
undifferentiated heavy liftingto the AI model to do kind of
more of the work or the analysis, maybe more of the consensus
mechanism, where it kind of thengives you some sort of
predictive outcome, where itkind of then gives you some sort
of predictive outcome and thenkind of that last check or
(18:02):
verification kind of goesthrough.
An attorney or somebody thatthen looks at everything to kind
of says, yes, this basicallydoes look good, does look
accurate or no, this wascompletely inaccurate.
We need to run it through an AImodel again.
So there definitely needs tokind of be human element, or the
human in the room, so to speak,to make that last verification
on whether or not this is goodor good, good decision or bad
decision.
Right, okay, now also, I want tokind of touch on the part of I
(18:24):
go back to this again inmarketing is you know, I am very
, very curious to kind of seewhere we start to see future
trends with AI and market-drivenstrategies.
What are you seeing from yourperspective in this space?
Have you had a chance to workwith a customer or a client
where they've been able to sayhey, we've taken the traditional
(18:46):
model of marketing andadvertisement and we've been
able to completely game-changeit using AI strategies.
Have you seen that yet?
Speaker 2 (18:55):
No, not yet.
Actually, I think marketingwill be changed totally because
the way we look at the contentright now, it will be changed
totally in a couple of years.
Because we see the content, apiece of content like just
posting LinkedIn right, we usedto read all of it.
Now you lose trust towardsLinkedIn posts because I can go
(19:18):
and post about, likeastrophysics, that I don't have
any knowledge about it, and thesame is starting to happen to
creatives like images, and samething starting to happen to
videos.
So all these things which make ahuge difference in marketing.
For example, if you want tobring bigger attention, you
should create an e-joke and ittakes a lot of effort and it
(19:39):
resonates with the higher viewsand nowadays it's becoming just
accessible to everyone.
So I believe there will be ahuge shift how we look at the
content, how it attracts us, interms of our clients using AI to
make their sales and marketingstrategies better.
Right now, we are working on anAI product which already, in
(20:02):
eight months, we created a POCwhich is already able to replace
low-level sales teams.
So, basically, as soon as thelead is coming to the CRM, the
bot is able to start theconversation itself.
Go to the booking.
Actually it's like sportingindustry class booking type of
CRM Actually push to the bookingand when it sees that there is
(20:26):
a positive answer that hey, yeah, I want to book this class
tomorrow at 8 pm it will go backto the CRM border class.
So it completely replaced theselow-quality salespeople that
were not able to close the leads.
Speaker 1 (20:40):
Hmm, Interesting.
I know you mentioned aroundcontent creation not being
authentic or being inauthenticand I think that's kind of a
concern is.
You know, you don't knowwhether or not whoever generated
the content actually has thecredentials to be actually doing
that from maybe somecryptographic keys to maybe NFTs
(21:03):
or some sort of way to kind ofencrypt or digitally sign
something as an authenticcreator.
Are you seeing that as well?
Do you start to hear this frompeople saying, as we start
moving into marketing andadvertisement, we need to find a
way to protect our brand, tomake sure that it's authentic
and we've digitally signed thatthat it's authentic and we've
(21:24):
digitally signed that.
Speaker 2 (21:26):
Yeah, it's becoming very popular, like digital
signage, because I can just takean image of any celebrity, like
30-minute talk, create anAI-generated video of any goal
there, and right now, I guess70% of people will not
understand that it's fake.
In the very future, it will beso realistic that maybe 90 95%
(21:47):
of people will think that it'sreal.
So this digital signage, thesethings that can able to
understand deepfakes a sign thatis getting very popular and
also in terms of just regularcontext, like LinkedIn, Google
all of them starting to improvesome logic there to be able to
(22:09):
understand the AI generatedcontent and just rank it very
low.
So you can just go and create 30log posts in your website with
AI, hoping that Google willraise your SEO rank.
Speaker 1 (22:24):
What would you say would be things that everyday
listeners need to be aware ofwhen it comes to AI-generated
content.
Speaker 2 (22:32):
I think they just need to take a look at how deep
the context is.
For example, for me, if I see acouple of keywords like delving
into the sound thing, there arejust keywords that if you use
ai daily, it's very easy tounderstand.
This context was written by aior no other than that.
Just you need to analyze andfilter.
(22:53):
How deep is the context.
So that's how google boardsworking as well.
If it goes to your blog, post ithas an ability to understand if
it's deep research, deeptechnical, unique content or not
.
So the same thing should ourbrains too, if you see content
that it has an ability tounderstand, if it's deep
research, deep technical, unique.
All that and all.
So the same thing should ourbrains do.
If you see it all, then thatlike very AI.
Then you're just ignoring.
Speaker 1 (23:17):
Yeah, I definitely see that.
Where you know there's that,you start to see similarities
amongst different languagemodels that kind of produce
certain type of keywords orphrases that you kind of hit on
and if you've seen it and youkind of know it, you go well,
that's definitely written by AI,it's definitely AI generated,
non-authentic, and things likethat.
You know what is your outlookwhen it comes to you know kind
(23:37):
of looking forward at you knowwhat's your advice for a certain
type of startups, or even youknow some founders who are
trying to journey on thisnavigation within AI.
How do you stay ahead of thecompetition with these technical
advancements?
What's your message for them?
Speaker 2 (23:53):
First of all, it's very hard because, if you are
daily checking AI news, it'sgrowing so fast that you can
just spend a couple of months onsome research and then see that
it became an open source,killing your business.
So it's just predicting thefuture, trying to understand
what is going to become amainstream, like if you are
(24:14):
trying to create, uh, forexample, voice cancellation
thing, I think what will be yourunique proposition when it
becomes an open source.
It's's very hard and it's noteasy, but that's what every AI
founder should do to understandwhat will be their advantage
compared to the others.
And also, very specifically, Isee recently that startups who
(24:39):
are very specific are doing amuch better job than the
startups who are trying to covereverything and actually not
covering anything.
That's quality that willattract users.
Speaker 1 (24:50):
Yeah, so they're basically going too broad.
They're too broad, they need togo deeper.
Right, you can't covereverything.
You need to have a very hyperfocus on a particular niche.
You need to have something thatis actually solving a real
world problem.
Basically, right.
Speaker 2 (25:07):
Yeah, exactly.
I mean, if you want to buildthe next generation startup,
then you need to find a niche.
For example, if you want yourproduct to create perfect
LinkedIn posts, then you need toconcentrate only on that,
understand all the aspects andwho are on that way, only that
(25:27):
way, you can like beef chat, gptLima, all these other models.
Yeah.
Speaker 1 (25:34):
What do you think about the new Facebook model?
Was it the Lama 3 that's justrecently come out?
They're talking about how it'sgoing to be like the chat, gpt
and open AI killer.
What's your perspective on that?
I've not had a chance to diveinto it, so I wanted to ask an
expert.
So what's your thoughts on thisnew Lama3?
Speaker 2 (25:50):
I haven't tried it in engineering level yet so I
can't tell too much, but itlooks very promising and,
considering all the dataFacebook has and it is a huge
data it has the chances to beatGPT in terms of conversational
AI, For example, like Microsoftdefinitely will be stronger in
(26:12):
all generation because it ownsthe GitHub, so it has also
trained.
The model basically has accessto all these conversations, so
it will have a completelydifferent conversational level.
Speaker 1 (26:24):
Yeah, it's going to be interesting to see what
happens.
I know that everyone's watchingand everyone's kind of waiting
to see, kind of, what's the nextbig wow factor.
What are some things thatyou're working on at HackTech
that you're very passionateabout?
What do you see on your radarover the next 12 months?
Speaker 2 (26:41):
Yeah, we are now fully concentrated again on
digital transformation type ofthings, because it's super
interesting to go to a company,traditional legacy company- find
out where you can give thebiggest value to increase the
performance and start workingfrom there, and our main target
right now are, like Lego andmarketing agencies, just because
(27:02):
, except that involve theseengineering skills, we also have
a very strong domain knowledgethere, which is very important.
Speaker 1 (27:09):
That's incredible and for our listeners.
Where can they follow you togain more insights on HackTech
and on your travels and youramazing journey through this
incredible landscape that we'renavigating today?
Where can folks follow you?
Speaker 2 (27:24):
LinkedIn.
I'm very active in LinkedIn.
I would say 24-7 in LinkedIn.
So, yeah, that's a place tofind and chat with me.
Speaker 1 (27:34):
I really appreciate this.
Thank you so much, jacob.
I really appreciate ourdiscussion today.
I really enjoyed diving intothis topic with you.
I know our listeners are somore informed than you know now
that they've had a chance tokind of understand a little bit
more around AI marketing,advertisement and how it's going
to change the legal field,would definitely love to have
you on as a guest on our show.
(27:55):
Again and again, thank you somuch for taking the time.
I know you're all the way outin Armenia, so it's very late in
the evening for you there, butso it's very late in the evening
for you there.
But again, thank you for takingtime to come on the show.
Really much appreciate yourinsights on this topic.
Speaker 2 (28:09):
Thanks.
Speaker 1 (28:10):
Steve, I enjoyed it.
Thank you so very much forjoining us on today's show.
Join us next time as we ventureinto the realms of technology
and, until then, stay curious,stay informed and, most of all,
happy travels.
Thanks so much for listening tothe Tech Travels Podcast with
Steve Woodard and, most of all,happy travels.
Thank you very much.
Welcome back, fellow travelers.
In today's episode, we're goingto dive deep into the topic of
how AI is going to impactindustries such as the legal,
marketing and the advertisementindustry, and joining us on this
topic, we have an amazing guest, hakab, who is the visionary
CEO and founder of HackTech.
(01:05):
Hacktech is not just riding thewaves of digital transformation
, they're creating it.
They offer tailored AIsolutions and custom software
engineer to help skyrocketproductivity.
Hakab's expertise is pushingthe boundaries, for the legal
and marketing sectors have madehim a sought after voice in this
digital transformation.
So, hacab, welcome to the show.
(01:27):
We're excited to have you.
I think you're also joining usfrom Armenia, is that correct?
Speaker 2 (01:31):
Yeah, that's correct.
Thanks, steve.
Thanks for being here.
Speaker 1 (01:34):
Absolutely Welcome to the show.
So tell us a little bit aboutwhat HackTech does and how you
became CEO of this amazingcompany.
Speaker 2 (01:42):
Yeah, actually I founded the company when I was
19 years old so I was studyingin the second year in my
university and I decided that Ineeded to start a software
engineering firm.
So it makes us already nineyears and during nine years we
reached from a single mancompany to a team of 80
(02:03):
professionals.
And what Haktan does and theway we position ourselves, that
we are not a traditionaloutsource or outsource agency.
What we do is engineeringpartnerships.
So with this big team like 80people, we have right now just
nine clients, so all initialclients.
We have a dedicated team, fullcycle engineering, from idea
(02:24):
like, from product management,business analyst to actual
development, design, developsall the stuff together.
And what makes the most sensein this model for me is that our
team is kind of becoming partof our client's team and like
just being motivated by theimpact they make on our client's
project, which is a very bigdriver in IT.
(02:47):
By our logic, we are industryagnostic, but it just happened
the way that we accumulated somuch knowledge in the legal and
marketing and other types ofindustry that right now it's
mainly main focus in terms ofdigital transformation.
Speaker 1 (03:06):
That's incredible.
I know that AI has definitelybeen riding a wave and we've
started to see itstransformation starting to occur
and even some disruptions thatwe're starting to see kind of in
different industries andindustries in different segments
.
So walk us through a little bitkind of what you're seeing from
, let's just say, advertisementand marketing.
(03:26):
How is AI really kind ofplaying a role in transforming
these very kind of?
You can think of them astraditional, very legacy type of
industries.
Speaker 2 (03:37):
Yeah, I think it's just becoming like you either
adopt AI, use AI or you will beout of the market very soon.
And it doesn't mean that youneed to use AI in every part of
your business.
It's more about using it theright way to boost your
productivity.
For me, if I talk to a companynow and I'm sure it will be
everyone in one, two years whenyou talk to a company and ask,
(04:00):
how do I see you leverage AI, ifthe answer is we don't use AI,
then you look at these companiesthat are at least 20-30% less
productive than theircompetitors and like leverage AI
doesn't mean that everyone isgoing to build their own AI
solution.
It can be like just learning howto properly prompt a talk to
(04:21):
GPT, because it's not so easy tolearn this.
So for me, it's kind of likeusing the internet, so if you
are not using an internet, youcan't be in an industry.
Now, the same is true formarketing and other item
industries.
And if you are a product likeyou have a marketing or
advertising product then youneed to adopt AI as a solution
(04:44):
in every part of your business,because from creating to
measuring the success metrics,because AI is not just like GDP
or just conversational.
So check how your campaigns are.
I mean, automatically adjustthe campaigns.
All these different kinds of AI.
I believe everyone reminds meof Matthew.
Speaker 1 (05:05):
Yeah, I would think that with marketing, you know,
there's a real push towards, youknow, a really big push in
marketing towards morepersonalization.
There's more things around dataanalytics.
There's more things aroundtrying to build more creative
and interactive customerengagements, and I really think
that you know, and I think I seethe data is starting to move
(05:25):
this way.
I really think that you knowand I think I see the data is
starting to move this way too.
Is that you know?
Is that there's marketingcompanies are starting to they
need to embrace kind of an AIfirst strategy.
Is that right?
Speaker 2 (05:36):
Yeah, yeah, that's right, but again like they don't
need to fully rely on AIbecause it will kill the
personalization.
If you like, just use GVD towrite a copy and send it to
people.
They will not read because evenfrom the first line, you can
understand that this is AIgenerated.
So it's all about using AI inthe right way, like still
(05:56):
putting your fork on creatingyour campaigns, creating your
copies, but using AI wheneverit's best, whenever it can hit
the most value.
Speaker 1 (06:08):
So definitely, dr Andy Roark.
So definitely okay, so we needto.
I think that there's kind of acrawl, walk, run type of
perspective, right Is that?
I think it starts witheducating the right type of AI
and being very prescriptiveabout how it's being used with
things that are customer facing.
I think that's where you'retrying to go right, okay, and
what have you been seeing, Iknow, in terms of kind of you
(06:30):
know, when you're gettinginvolved with certain customers
in these industries, are youseeing?
Is it that there's a lack ofadoption due to lack of
understanding and how AI works,or understanding and expertise
with an AI?
Where do you start to kind ofsee more of a skill or a
technical deficiency with them,kind of moving forward with an
AI?
Where do you start to kind ofsee more of a skill or a
technical deficiency with them,kind of moving forward with an
AI approach?
Speaker 2 (06:49):
Yeah, actually, for me, some of these industry
companies having like CTO or CIO, even if they don't have a
product, even if they don't havelike internal software, they
still have this role to keepthem up to date with technology.
And in this case it is mucheasier because these people
understand the value.
These people know that at somepoint they need to build
(07:11):
something for them.
And the other scenario, wherethe founder or CEO is not
technical, you need to do a lotof job to educate them.
Sometimes calculate like returnon investment.
So, hey, you know like you arelosing 20% of productivity here
and we build these customsoftware or implement this AI
(07:32):
solution for you that like in amonth or in six months or in a
year, and we'll cover your costs.
So the way we typically workwhen starting a new relationship
is opening a deep logisticproduct manager.
So a product manager spends amonth or two with their company,
sees all their day-to-dayprocesses and then comes up with
(07:54):
a product solution that they'llsolve their needs.
Speaker 1 (07:57):
That's interesting.
I mean, talk to me a little bitabout what you're seeing across
the C-suite.
I know you mentioned CIO andCTO.
Those tend to kind of be moreof the technology and
information leaders inside of anorganization.
Do you see organizations thatdon't have CTOs or CIOs that
have the right type of expertise?
(08:18):
I mean, is that typically whereHackTech comes in?
Talk to me a little bit abouthow you kind of bridge these two
roles together with this newkind of disruptive form of
technology.
Speaker 2 (08:28):
Yeah, that's exactly what Haktek does.
If a company is not having aCTO, they need to go to digital
transformation.
It's very hard because youcan't just hire, like even
senior developers, and expectthat something will be built.
You need the domain knowledge,you need the tools, expertise,
all these that CTO usuallybrings to the table, and with
Haktek, that's what we bring tothe table.
(08:49):
So we are not just outstaffing,because for me, outstaffing is
not an IT business, it's more anHR business.
So we are not just deploying,like saying that, a local, we
are deploying the team who knowsthe processes well, everyone in
Hacktech aligned with theprocesses that we are working
and they are coming with theseprocesses implementing it to the
Hmm, what do you, what are youseeing and kind of going to
(09:12):
dovetailing back here is, youknow I want to work through, you
know, kind of the the the roleof AI in startups.
Speaker 1 (09:18):
I know we talked about CTOs and CIOs.
You know we we see how mostestablished companies kind of in
in in the space have kind ofgot a very mature C-suite of
your board of directors.
Startups, you know they'retrying to get a product out to
the market pretty quickly, right, so they're trying to scale for
growth and efficiency.
What do you see as somepotential pitfalls when it comes
(09:41):
to startups?
When they start to leveragethings like AI, where do you
start to see some of them notreally hitting their mark?
Speaker 2 (09:49):
Yeah, actually, again here there are two types of AI.
One is just actually a coupleof levels or just two like.
First level is just leveragingthe GPT APIs or any other model
APIs to bring some AI componentsinto your product, Like it
doesn't matter if you are an AIstartup or any other industry
startup.
I mean, if you have a text boxwhere someone should type
(10:11):
something, it's a verylow-hanging fruit to integrate
GPT and give the userpossibility to generate it
automatically.
The next level is promptengineering, to deeper
understand how all it works andcome up with prompts that will
give the most value.
And the other level is trainingthe models itself, getting the
(10:33):
most value.
If the R&B data and the otherlayer would be like going and
creating your own models andsocial models.
Speaker 1 (10:42):
That's interesting.
You know, you mentioned datamodeling and I really wanted to
kind of double click on this onehere, and this is just maybe
just kind of helping ouraudience just understand a
little bit.
More is, if you've got an ideawith a startup, right, they're
leveraging some sort of languagemodel, they're leveraging some
sort of AI.
Where do they get the data tostart doing the data modeling?
(11:05):
Where does that typically tendto come from, right?
Where do they leverage thatsame type of you know the amount
of data, or do they?
Or do they not?
They don't use the data.
Speaker 2 (11:17):
Most AI startups don't, and I was making this
joke.
I was recently in a bigconference like Web Summit in
Qatar and, like I would say, 80%of startups were having an AI
next to their own name.
So it's like something AI,something AI, and you see that
everyone is just leveraging theapis or calling it an ai product
(11:38):
, which actually is a.
It's just a software using likebasic integrations.
So most of the companiesbecause, like for very, very
easy, very basic model training,you will need at least like,
let's say, if it'sconversational ATA and we will
have thousands of conversationsand we know that we're already
adding more For something likemore to get a better result, you
(12:00):
will need like hundreds ofthousands of them.
So most companies just eithernew ATAs or, if they are like,
getting stronger skills, theyare doing some problem.
Speaker 1 (12:09):
Hmm, so what do you think that the three key, what
would you say are three key?
Three key, uh, or three keyassets that a startup needs to
be successful when they'relooking to leverage things like
AI and not just basically saying, hey, we're X company and that
we've got, you know, ai next toit.
What do you start to see?
And when you evaluate startupsin terms of kind of three key
(12:32):
components that they need tohave in order for them to say
there's a potential for you tohave great success or you're
just never going to go anywhere?
Speaker 2 (12:40):
Yeah, I fully.
First of all, again, if it's atechnological startup and they
want to adopt AI, they need tohave a CTO.
It's a must.
They need someone whounderstands.
First of all, they need AI ormore, because sometimes you can
just go train models and do allthis complex stuff and meet us
at dollar, while you can justuse some open source model.
(13:01):
And we saw a lot of things afterthis AI hype A lot of startups
who were doing their internalengineering, like doing some
complex researches on their ownbusiness model and all
investments that they weregetting was related to this uh
core, uh ai research and thensomething like from this giant
(13:22):
tech company something opensource coming and killing their
business.
So it happened a lot.
Like many companies before gptbecame available to everyone,
many companies were were doingresearch in a lower scale and
getting investment in thisresearch.
Then, with GPT, I guess 90% ofthem just get out of the market.
So the first is having propertexting there.
(13:44):
Second, understanding thevision, making sure like you
need that AI solution, you needthat to go and actually research
, do the research in that field.
And the third one was checkthat nothing exists in that
space, nothing these tech giantsare doing in that space.
Speaker 1 (14:04):
It definitely seems okay.
So you definitely got to havethe right leadership in place to
kind of help steer and kind, ofcourse, correct kind of where
the vision is actually going tobe and then setting the journey
for how we're going to achievethat as an organization.
Sounds like those are some keydifferentiators every startup
needs to have.
Is that key leadership here?
I wanted to kind of justdovetail back into the topic
(14:28):
around AI's influence around thelegal industry.
I know that there's a lot ofpotential for AI to disrupt
traditional type of legalpractices.
What are you seeing from thisparticular angle when it comes
to leveraging AI with regards tolegal industry, legal type of
contracts or even if, in fact,if it's just kind of mixing
(14:50):
these two together, is it a goodcombination or is it you start
to see that there might be someother way that there might be?
Speaker 2 (14:58):
some some other other way that this might go.
Yeah, actually, a little tech,little industries being affected
with AI.
And again, it's not going tochange people, it's not going to
replace human, but it's goingto make them more productive,
starting from like just researchthat any other rebuild should
do, or they really like justresearch that any R&D build
should do on their daily job,from to creating contracts,
(15:21):
creating some documents, and wehave a very successful case
study right now working with abig integration company who is
dealing with O1, h1b visas.
If you know, it's very complex,like five, six hundred pages of
PDF per weekend and they arehandling it in a scale.
And we started working withthem about two years ago.
We came up with the customsoftware which accumulated all
(15:43):
the data and it was the AI juststreamlining the processes, the
data from practitioners, etcetera, et cetera, and with this
AI we started to automate a lotof.
I think like 50, 60% of thepetition can be automated by AI
and then just immigrationspecialist or a common agent
will approve and send to thenext teenager.
(16:05):
So and this is just one examplefrom immigration law, but it's
a completely different way.
Speaker 1 (16:13):
No right, you would think that at least I know.
I probably would think that youknow planning low price.
You would think that at least Iknow.
I probably would think that youknow leveraging things to be
able to look at things withinlegal such as looking at things
such as you know contracts andthen looking at things such as
you know keywords to be able tolook at and assess certain
levels of risks within contracts.
I know you mentioned H-1Bs andvisas and things like that.
(16:36):
There's a lot of documents thathas to source through, so I
think AI is great applicationthere.
Where do you see as a potentialpitfall when it comes to AI?
Where do you see that thereneeds to be some sort of
boundary or guardrail where youmight need to have some sort of
kind of human interaction tokind of say, hey, I need to make
a call on the field.
This was a false positive onAI's part, or where do you kind
(16:59):
of see this?
Speaker 2 (17:00):
Yeah, again, like, for example, O1 or H1B is super
important, like for some people,it's like life's important
thing.
So what we are doing every partof AI generation should be
checked by a foreign orimmigration specialist.
So AI is doing.
Every part of AI generatedshould be checked by a foreign
or immigration specialist.
So AI is doing a lot ofmistakes.
Again, it's helping you toboost productivity, but you can
(17:21):
just ask AI to generate 600pages of petition for you and
you hope that you will beapproved.
So whatever AI doing in anyindustry where there is
importance to be always correct,it should always pass through
the human.
Speaker 1 (17:39):
Okay, so that's where I was getting at.
So, yeah, so it seems likeyou're offloading the
undifferentiated heavy liftingto the AI model to do kind of
more of the work or the analysis, maybe more of the consensus
mechanism, where it kind of thengives you some sort of
predictive outcome, where itkind of then gives you some sort
of predictive outcome and thenkind of that last check or
(18:02):
verification kind of goesthrough.
An attorney or somebody thatthen looks at everything to kind
of says, yes, this basicallydoes look good, does look
accurate or no, this wascompletely inaccurate.
We need to run it through an AImodel again.
So there definitely needs tokind of be human element, or the
human in the room, so to speak,to make that last verification
on whether or not this is goodor good, good decision or bad
decision.
Right, okay, now also, I want tokind of touch on the part of I
(18:24):
go back to this again inmarketing is you know, I am very
, very curious to kind of seewhere we start to see future
trends with AI and market-drivenstrategies.
What are you seeing from yourperspective in this space?
Have you had a chance to workwith a customer or a client
where they've been able to sayhey, we've taken the traditional
(18:46):
model of marketing andadvertisement and we've been
able to completely game-changeit using AI strategies.
Have you seen that yet?
Speaker 2 (18:55):
No, not yet.
Actually, I think marketingwill be changed totally because
the way we look at the contentright now, it will be changed
totally in a couple of years.
Because we see the content, apiece of content like just
posting LinkedIn right, we usedto read all of it.
Now you lose trust towardsLinkedIn posts because I can go
(19:18):
and post about, likeastrophysics, that I don't have
any knowledge about it, and thesame is starting to happen to
creatives like images, and samething starting to happen to
videos.
So all these things which make ahuge difference in marketing.
For example, if you want tobring bigger attention, you
should create an e-joke and ittakes a lot of effort and it
(19:39):
resonates with the higher viewsand nowadays it's becoming just
accessible to everyone.
So I believe there will be ahuge shift how we look at the
content, how it attracts us, interms of our clients using AI to
make their sales and marketingstrategies better.
Right now, we are working on anAI product which already, in
(20:02):
eight months, we created a POCwhich is already able to replace
low-level sales teams.
So, basically, as soon as thelead is coming to the CRM, the
bot is able to start theconversation itself.
Go to the booking.
Actually it's like sportingindustry class booking type of
CRM Actually push to the bookingand when it sees that there is
(20:26):
a positive answer that hey, yeah, I want to book this class
tomorrow at 8 pm it will go backto the CRM border class.
So it completely replaced theselow-quality salespeople that
were not able to close the leads.
Speaker 1 (20:40):
Hmm, Interesting.
I know you mentioned aroundcontent creation not being
authentic or being inauthenticand I think that's kind of a
concern is.
You know, you don't knowwhether or not whoever generated
the content actually has thecredentials to be actually doing
that from maybe somecryptographic keys to maybe NFTs
(21:03):
or some sort of way to kind ofencrypt or digitally sign
something as an authenticcreator.
Are you seeing that as well?
Do you start to hear this frompeople saying, as we start
moving into marketing andadvertisement, we need to find a
way to protect our brand, tomake sure that it's authentic
and we've digitally signed thatthat it's authentic and we've
(21:24):
digitally signed that.
Speaker 2 (21:26):
Yeah, it's becoming very popular, like digital
signage, because I can just takean image of any celebrity, like
30-minute talk, create anAI-generated video of any goal
there, and right now, I guess70% of people will not
understand that it's fake.
In the very future, it will beso realistic that maybe 90 95%
(21:47):
of people will think that it'sreal.
So this digital signage, thesethings that can able to
understand deepfakes a sign thatis getting very popular and
also in terms of just regularcontext, like LinkedIn, Google
all of them starting to improvesome logic there to be able to
(22:09):
understand the AI generatedcontent and just rank it very
low.
So you can just go and create 30log posts in your website with
AI, hoping that Google willraise your SEO rank.
Speaker 1 (22:24):
What would you say would be things that everyday
listeners need to be aware ofwhen it comes to AI-generated
content.
Speaker 2 (22:32):
I think they just need to take a look at how deep
the context is.
For example, for me, if I see acouple of keywords like delving
into the sound thing, there arejust keywords that if you use
ai daily, it's very easy tounderstand.
This context was written by aior no other than that.
Just you need to analyze andfilter.
(22:53):
How deep is the context.
So that's how google boardsworking as well.
If it goes to your blog, post ithas an ability to understand if
it's deep research, deeptechnical, unique content or not
.
So the same thing should ourbrains too, if you see content
that it has an ability tounderstand, if it's deep
research, deep technical, unique.
All that and all.
So the same thing should ourbrains do.
If you see it all, then thatlike very AI.
Then you're just ignoring.
Speaker 1 (23:17):
Yeah, I definitely see that.
Where you know there's that,you start to see similarities
amongst different languagemodels that kind of produce
certain type of keywords orphrases that you kind of hit on
and if you've seen it and youkind of know it, you go well,
that's definitely written by AI,it's definitely AI generated,
non-authentic, and things likethat.
You know what is your outlookwhen it comes to you know kind
(23:37):
of looking forward at you knowwhat's your advice for a certain
type of startups, or even youknow some founders who are
trying to journey on thisnavigation within AI.
How do you stay ahead of thecompetition with these technical
advancements?
What's your message for them?
Speaker 2 (23:53):
First of all, it's very hard because, if you are
daily checking AI news, it'sgrowing so fast that you can
just spend a couple of months onsome research and then see that
it became an open source,killing your business.
So it's just predicting thefuture, trying to understand
what is going to become amainstream, like if you are
(24:14):
trying to create, uh, forexample, voice cancellation
thing, I think what will be yourunique proposition when it
becomes an open source.
It's's very hard and it's noteasy, but that's what every AI
founder should do to understandwhat will be their advantage
compared to the others.
And also, very specifically, Isee recently that startups who
(24:39):
are very specific are doing amuch better job than the
startups who are trying to covereverything and actually not
covering anything.
That's quality that willattract users.
Speaker 1 (24:50):
Yeah, so they're basically going too broad.
They're too broad, they need togo deeper.
Right, you can't covereverything.
You need to have a very hyperfocus on a particular niche.
You need to have something thatis actually solving a real
world problem.
Basically, right.
Speaker 2 (25:07):
Yeah, exactly.
I mean, if you want to buildthe next generation startup,
then you need to find a niche.
For example, if you want yourproduct to create perfect
LinkedIn posts, then you need toconcentrate only on that,
understand all the aspects andwho are on that way, only that
(25:27):
way, you can like beef chat, gptLima, all these other models.
Yeah.
Speaker 1 (25:34):
What do you think about the new Facebook model?
Was it the Lama 3 that's justrecently come out?
They're talking about how it'sgoing to be like the chat, gpt
and open AI killer.
What's your perspective on that?
I've not had a chance to diveinto it, so I wanted to ask an
expert.
So what's your thoughts on thisnew Lama3?
Speaker 2 (25:50):
I haven't tried it in engineering level yet so I
can't tell too much, but itlooks very promising and,
considering all the dataFacebook has and it is a huge
data it has the chances to beatGPT in terms of conversational
AI, For example, like Microsoftdefinitely will be stronger in
(26:12):
all generation because it ownsthe GitHub, so it has also
trained.
The model basically has accessto all these conversations, so
it will have a completelydifferent conversational level.
Speaker 1 (26:24):
Yeah, it's going to be interesting to see what
happens.
I know that everyone's watchingand everyone's kind of waiting
to see, kind of, what's the nextbig wow factor.
What are some things thatyou're working on at HackTech
that you're very passionateabout?
What do you see on your radarover the next 12 months?
Speaker 2 (26:41):
Yeah, we are now fully concentrated again on
digital transformation type ofthings, because it's super
interesting to go to a company,traditional legacy company- find
out where you can give thebiggest value to increase the
performance and start workingfrom there, and our main target
right now are, like Lego andmarketing agencies, just because
(27:02):
, except that involve theseengineering skills, we also have
a very strong domain knowledgethere, which is very important.
Speaker 1 (27:09):
That's incredible and for our listeners.
Where can they follow you togain more insights on HackTech
and on your travels and youramazing journey through this
incredible landscape that we'renavigating today?
Where can folks follow you?
Speaker 2 (27:24):
LinkedIn.
I'm very active in LinkedIn.
I would say 24-7 in LinkedIn.
So, yeah, that's a place tofind and chat with me.
Speaker 1 (27:34):
I really appreciate this.
Thank you so much, jacob.
I really appreciate ourdiscussion today.
I really enjoyed diving intothis topic with you.
I know our listeners are somore informed than you know now
that they've had a chance tokind of understand a little bit
more around AI marketing,advertisement and how it's going
to change the legal field,would definitely love to have
you on as a guest on our show.
(27:55):
Again and again, thank you somuch for taking the time.
I know you're all the way outin Armenia, so it's very late in
the evening for you there, butso it's very late in the evening
for you there.
But again, thank you for takingtime to come on the show.
Really much appreciate yourinsights on this topic.
Speaker 2 (28:09):
Thanks.
Speaker 1 (28:10):
Steve, I enjoyed it.
Thank you so very much forjoining us on today's show.
Join us next time as we ventureinto the realms of technology
and, until then, stay curious,stay informed and, most of all,
happy travels.
Thanks so much for listening tothe Tech Travels Podcast with
Steve Woodard and, most of all,happy travels.
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