Tukan Das: Start ups, Scaling Up, and Exciting new ventures in A.I.

Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Cheers, cheers, cheers.
Welcome to the Afternoon Pint.
I'm Mike Dobin, I am Makhan,and who do we have with us today
?
We have Toukan Das here.
Toukan, wow, yeah, so say howwe got introduced.
Yeah, my brother-in-law, rick.
Shout out to Rick down inColorado.
Yep has his own podcast going.
He's quite successful in hisown right.

(00:20):
Thought you'd be a reallyinteresting guy to talk to, but
he kind of skimped on thedetails.
So tell me a little bit aboutwho you are.

Speaker 2 (00:29):
I have no idea why he thought I'd be interesting, but
sure I'm here.
My background as per LinkedIn,I am a co-founder of a new
stealth AI startup.
Yeah, but my background is incomputer science.
I'm originally from India,moved here right after high
school to do computer science.
I'm originally from India,moved here right after high

(00:49):
school to do computer science AtDalhousie.
Yes, I did at Dal.
That was 20, god, that was 21years ago, mm-hmm yeah 2002.
Well damn, 23 years ago.

Speaker 1 (00:58):
I can't count.

Speaker 2 (01:00):
I think, being a computer science student, I
should count better.

Speaker 3 (01:04):
But anyways.

Speaker 2 (01:05):
I studied, did my undergrad, worked here, started
my master's while working at adifferent company, and then,
while I was doing my master's, Istarted a company called
LeadSift.
Leadsift.

Speaker 1 (01:17):
Yes, that was after you were making search engines,
building search enginesbasically as a computer engineer
right, I was working at GenieGame.

Speaker 3 (01:25):
Genie, yeah, genienowscom they were one of
the top four game genies fromnintendo I just said the wrong
thing.

Speaker 1 (01:32):
That's fine, uh, so they were.

Speaker 2 (01:34):
We were building a search engine and we were
competing with the google andyahoo's of the world, right?
I was working there as aresearch engineer and then I um,
while doing my master's I wasworking there I dropped out and
started this company calledLeadsift with three of my other
co-founders, and I did that fornine years.
Leadsift, for a second, was apretty cool program right.

(01:55):
Thank you.

Speaker 1 (01:55):
I have an idea of what it did Basically when
social media was younger.

Speaker 2 (01:59):
we'll say right, I mean not today.
Yeah, yeah, yeah.

Speaker 1 (02:06):
And tell me if I'm wrong on this, but what it would
do is it would help businesses,with all the social noise and
stuff that was going out there,to find leads through various
social media platforms.

Speaker 2 (02:13):
That's what it started as, so funny story.
So the name was LeadSift andour core thesis was we would
mine social media data Twitter,blogs.
Back then, facebook had an APIanything that is public.
We would mine that to identifypeople who are in market for a

(02:34):
product.
So you talked about insurance.
We had RBC as a client, orTransamerica Insurance.
These are all clients of oursand what we would help them do
is identify who was in market.
So, for example, I would tellRBC that.
Did you know that there are9,000 people in Canada today
that we identified that wereshowing interest towards a new
health insurance product or ahouse insurance product by

(02:57):
analyzing text?
So we were doing a lot ofnatural language processing and
AI before.
The AI thing was cool, so wedid that.
That's how we started.

Speaker 3 (03:06):
Yeah, so are you telling me that you're the
reason that when I say out loud,hey, have you ever tried a
bidet before?
And then all of a sudden I gointo Facebook and I'm getting
bidet ads?
I wish I was.

Speaker 2 (03:18):
I wish I was no, but yeah, that's exactly it it's
looking at.
We were not looking at voicedata or anything, but we were
only looking at publiclyavailable data.
So, as an example, let's saysomeone put out a tweet or a
post saying dropping off my kidto daycare and then heading into

(03:44):
to drop my car off, and whenyou drop your car off, you had a
check-in location that maps toa BMW dealership.
Just by looking at that singletweet, I know you're a parent,
young kid, you drive a car,you're pretty affluent, because
the location you checked in wasa BMW dealership.

Speaker 3 (04:04):
Just by looking at it .

Speaker 2 (04:04):
Yeah, yeah so we can build a lot of profile
information, Again all frompublic, which you posted.

Speaker 3 (04:10):
But that also speaks to the security factor of how
people need to be more consciousabout what they put on social
media right, that is way past.

Speaker 2 (04:18):
We are way past that point now.

Speaker 3 (04:19):
No, I know you're right, but it's just something
for people to be cognizant about, right.

Speaker 2 (04:24):
We had from your public Twitter profile.
We were extracting 220attributes about every single
person, just from public Meaningand again it was not for
nefarious reasons but it wasmore for marketing.
For example, we could tell youwhich brand you are most likely
to wear.
Are you a runner?
Which airlines would you prefer?

(04:47):
Which coffee?

Speaker 3 (04:48):
drink.

Speaker 1 (04:49):
Like all of those things Around, what year was
this?

Speaker 2 (04:51):
This was around between 2012 to 2015.

Speaker 1 (04:54):
So we weren't really talking about that kind of not
even really, I don't think,realizing what was happening in
the social media world back then.

Speaker 3 (05:00):
Not quite as minding as that, but I mean there was
still like geofencing and stufflike that.
That was going on, Of course,yeah, so I mean that was not
that old.

Speaker 2 (05:08):
There was four square check-ins.

Speaker 3 (05:09):
There was a whole bunch of them.

Speaker 2 (05:11):
So we would look at all of these that's publicly
available, that anyone can seeyou're putting out.
We would do that.
But then this is one of theinteresting stories in 2015, we
were working with all these bigbrands, the ones that I
mentioned, whether it's a bigfinancial service or a
MasterCard, which is also afinancial service, or a car

(05:32):
company.
We used to work with Ford, ge,all of them, lg, big beverage
companies.

Speaker 3 (05:37):
Yeah.

Speaker 2 (05:39):
But in 2015, at a very eventful board meeting, we
had closed two of our biggestdeals.
It was one of the best quarters.
I presented to the board,saying, hey, we just closed a
lot of revenue this quarter.
Again, lot is relative, it'sall subjective.
True, yeah, for us, a smallfledgling company, that was a

(05:59):
lot.
But here's this one question Ican't answer.
And the board goes what is it?
And I said my engineering team,which is a team of four people
well, five engineers.
They don't seem to be motivatedwith what they're doing.
How can I motivate them?
Revenue is not motivating them.
And I remember our boardchairman, damien Steele.

(06:21):
He looked at me.
He's like, yeah, because you'rejust building, not a software
company, you're building aconsulting shop, body shop,
because basically, what you'redoing is you have these big
clients coming to you forone-off projects saying, hey,
can you do this analysis, canyou do this analysis?
Right, and you would go do thisfor them, a software product

(06:44):
that you build.
You build for the samerepeatable use case.
As an example 2014 Super Bowl,jaguar launched their new car,
xlri I forget what that is andit was the actor.
And they ran a big campaign inthe Super Bowl with Tom
Hiddleston, or Huddleston,whatever his name is Loki world,

(07:04):
world, tom hiddleston orhuddleston, whatever his name is
loki, loki, right.
So they came to us and said hey,I want to understand what the
potential jaguar audience lookslike, what they like.
So we gave that data again.
It was a custom, bespokeproject and we were doing this
multiple times over.
We're doing it for rbcsomething, transamerica,
chrysler, whoever did.
We did this and that was alight bulb moment.

(07:28):
I was not expecting that.
I was expecting them some pithyanswers like motivate them,
play ping pong, take them forlunch all that bullshit.
So I realized we did not haveproduct market fit that's the
term that they use in startupand we were just building custom
solutions.
Engineers don't sign up forsoftware companies to build
custom solutions.
They go work at a bigconsulting company, whether it's

(07:49):
an IBM or an Accenture orsomething.
So then in 2016, we had to makea tough choice.
We had one year's worth ofmoney left in the bank and we
had three options.
Option one was take that money,give it back to the investors.
We had raised venture capitalmoney, so they would get pennies

(08:11):
on the dollars.
Option two we had two offers toget us acquired.
It would look good on paper andpress, but there was no money.
It's basically a glorified joboffer.
That's what we'd get, and you'dget some stock options in the
company yeah, yeah that wasoption two.
One was in toronto, one was inwashington dc.

(08:32):
And option three was basically,figure it out.
Whatever money you have, yeah,see if you can come up with
something, because whateveryou're doing was not going to
scale, it would not work.
So our investors basically islike, look, I don't need your
three dollars on the dollar,three cents on the dollar return
.
Right, go, figure it out, we'llsee.

(08:53):
Um, and me and my otherco-founder, we made the call.
It's like you're not going tosell to them.
So we started from scratchagain.
But this this time the funny,the interesting story here is
there's always so many stories,man.
The interesting story that wehad was we had a salesperson
in-house and you guys are salesguys, so you'd understand.
He was doing cold calling andcold emailing for us, right, he

(09:18):
would reach out to the insurancecompanies, the car companies,
the marketing person and that,and he would reach out to them.
And so he came to us.
He's like hey, I know we areselling our data and
intelligence to these big brands, the Chryslers and the RBCs and
the MasterCards of the world.
Can we identify the same thingfor software companies, meaning

(09:39):
companies like us?
Can you tell me which carcompany would be a fit for me.
Rather than telling the carcompany which person is going to
buy a new chrysler, can youtell me a software company who's
going to be which car companymight need my solution and I
thought and I thought and it was.
He's an, he was an intern, hisname is cory.
Shout out to cory um.

(10:00):
And that was the moment I'mlike okay, that's interesting.
So we went all in on that andthat's the company.
We scaled.
We started from zero.
We lost.
We had about $400,000 inrevenue, so we got that to zero,
we let them go, we fired ourcustomers.

Speaker 1 (10:17):
Yeah, so you help software companies find their
niche almost in a sense.
Is that right?

Speaker 3 (10:21):
We help software companies find leads for their
sales and marketing their salesright.

Speaker 2 (10:27):
So that's what we did , and that's so the date, the
category is called in.
So it was b2b, it was intentdata, intent to buy.
Wow, we figured out a way, uh,by looking at text and different
signals in the graph, topredict who would be in market
for a new software yeah, that'swhat we did.
Yeah, that's what god hasacquired, so I know it was a

(10:48):
very long-winded.
What do you do?

Speaker 1 (10:51):
and foundry.
Uh, the company acquired wasfoundry, the company that rick
our, our mutual friend hereknows.
Uh, so like how, how didfoundry and how did that that
happen?

Speaker 2 (11:00):
it's the funniest story man yeah it's the funniest
story.
I remember clearly whathappened.
This was, this was.
This was November 2020.
Peak COVID yeah, I was in thecity thick of the day.
In August of 2020.
We had an offer to get acquiredby one of our biggest

(11:20):
competitors oh so we signed thisis exclusive content I'm
sharing here.
I don't know what the legalramifications of this were, but
anyways, I'm not mentioningnames.
We had signed an agreement toget acquired and then, after you
sign an agreement to getacquired, you get basically 60

(11:41):
days where that company whowants to acquire you for
whatever price you negotiate on,will do due diligence on you,
right, yeah?
So we went into due diligencewith this.
It was a 60 day process, so wesigned the deal in September.
It was supposed to close onNovember 7th and right out of
the gate, once we went into duediligence, we got a very sneaky

(12:03):
suspicion that these guyswhether they wanted to buy us or
not, but they were reallyinterested in figuring out what
the hell we were doing and howwe were doing it.

Speaker 3 (12:12):
So we got very scared .

Speaker 1 (12:14):
So they kind of made like an offer just to get an
inside look, potentially, yeah,potentially Do you feel they
were picking you apart in asense, too, to get that
information?

Speaker 2 (12:21):
They were, they were yeah yeah, because sense too,
they were, they were, they wereyeah, yeah.
Um, because here's the thing,just a little bit technical
details here.
When a company buys anothertechnical company, one of the
things they do is they do a lotof due diligence on your
finances, everything yeah, butthere's a big part which is due
diligence on your tech.
What does your tech look like?
And typically what they do is,if it's a direct competitor, it
doesn't matter.
Even if it's not they, theybring a third-party company to

(12:43):
analyze your code line by line,but it's a third-party company
who's neutral and they don'tshare what they found.
They just say, hey, this islegit, whatever they're claiming
is legit, or they'rebullshitting, because a lot of
companies lie about their tech.
What these guys did was theywere like no, no, no, we're not
going to bring in third party,our CTO is going to look at your
code and we were like no,that's not cool Seems good.

(13:05):
Because you're a directcompetitor.

Speaker 1 (13:06):
Right.

Speaker 2 (13:07):
So we both shook hands, we said no and it was a
big.
Personally, as a first-timefounder, it was a big blow, and
this was not the first time.
So, anyways, it was a big blow.
But going back on October 7th,the day the deal was supposed to
close, we knew it was not goingto happen.
I get an email from this personHis name is Matt Pearson, from

(13:30):
IDG.
That's the parent company.

Speaker 1 (13:32):
Oh, Foundry, yes.

Speaker 2 (13:33):
Yes, idg owns Foundry and.

Speaker 1 (13:35):
IDC yeah.

Speaker 2 (13:37):
Saying hey, I'm this, we're looking at intent data,
would love to explorepartnership.
That's how they do it.
They always ask it's apartnership.
I, as a founder, you get a lotof these emails where corp dev
people reach out.
It's like we want to explorewhat you're doing.
I almost ignored it.
I'm like I don't know man, butthen I happened to Google what

(13:58):
IDG is and I found a Wikipediapage.
Anytime there's a Wikipediapage for a company, it's a good
sign.
Yeah, and they had.
I realized they were like over6,000 employees.

Speaker 3 (14:10):
I'm like, okay, this is a legit company, yeah.

Speaker 2 (14:13):
And that's how the discussion started.
Wow.
So it was a cold email.
So I got in a meeting and we,we started the discussion.
But here's the here's alsoanother story to that.
There's never a straight path.
So we had a bunch of meetings.
They got their seniorleadership all on, zoom right,

(14:36):
presented and everything, andthen all of us and there was a
lot of momentum Like share this,share this.
So in a deal, momentum is key.
If the momentum is stalled,it's very difficult to reverse
it.
It's very difficult.
So it was happening and we were, we were very excited and then
in january they stopped, justthe discussions just stopped.
They didn't, they didn't reallytalk to us and I'm like, okay,

(14:59):
this is weird, um.
So I reached out to them.
I'm like, hey man, what's goingon?
I thought we were going to do adeal in 90 days, but he's like
Chukan, this is towards end ofJanuary.
He's like there's some thingsgoing on in our company.
It's not you, it's us.
So we cannot continue thisdiscussion at this point.
We will reconvene at somefuture point.

(15:21):
And I've heard this kind ofbusiness lingo very classic.
They will never say no.

Speaker 1 (15:25):
Yeah, yeah, yeah.
It's like the breakup, you know, with a cute girl it's not you,
it's me, it's not you, it's me,it's always.
Oh, okay, and that's exactlywhat.

Speaker 2 (15:31):
I thought and I was coming fresh from another
breakup, a corporate breakup.

Speaker 3 (15:36):
So To rebound, To rebound.
So I'm like you know what Screwit.

Speaker 2 (15:40):
We're just going to go ahead.
We were profitable at stop us.
We'll just keep going, but itwas still a blow.
And then in may I see a news.
It says idg acquired byblackstone right group.

Speaker 1 (15:56):
Blackstone is the largest private equity fund in
the world?

Speaker 3 (15:58):
yeah, exactly, massive I think a trillion
dollars.
I read that recently.
It's a trillion dollars.
Yeah, it's very big.

Speaker 2 (16:05):
Then it hit me.
I'm like shit, so they weregetting it yeah that's the
reason they couldn't continuethe discussion.
So immediately I I reached outto man.
I'm like, hey, congrats, let meknow when it makes sense to
reconnect.
Within five minutes.
He, or 15 minutes.
He gets back.
He's like, yeah, let's touchbridge next wednesday.
So the conversation startedback up in may.

(16:27):
We signed our agreement on 13thof August and we closed in
November.
Amazing, so that's the story.
Biggest deal of your life,right?
Biggest deal of my life.
It started right here, inHalifax too.

Speaker 1 (16:38):
I mean, I think that's really important for our
listeners.

Speaker 2 (16:40):
This is primarily a.

Speaker 1 (16:40):
Halifax show right, absolutely.
So you came to Dalhousie.
You studied computer sciences,you started an engineering job.
I'm sure some of that was alittle mundane in the beginning.
You probably didn't know whereit was going.
But like man, what a crazystory, just one small thing.

Speaker 2 (16:57):
I did my undergrad and I was also doing my master's
in natural language processing,but I didn't finish my master's
.
No, I dropped out.
Oh, I dropped out.
So I had taken all my courses.
I had my thesis left.
So I had taken all my courses.
I had my thesis left.
And thesis takes six to eightmonths of real deep down,
focused work.
By the time I was starting towrite my thesis, I literally had
one page written on my thesisand I started my company and I

(17:21):
thought I'll be able to do it onthe part time.
I lied to myself for a coupleof years but I never finished.

Speaker 3 (17:27):
So, yeah, yeah, but aren't all the most genius?
Rich people are all drop-dodesof something.

Speaker 2 (17:33):
Yeah, there's just a difference.
Neither am I genius, not superrich.
So yeah, you'll get there.

Speaker 3 (17:38):
You'll get there, you know hopefully yeah, it's cool
so and so as like a you knowkind of a resident expert in
this tech world, um, I've heardlike kind of whispers, that like
Halifax is kind of sneaky goodwhen it comes to in the tech
world.
There's more here than peoplereally realize.

Speaker 1 (17:57):
Oh, there's a lot here.
Yeah, I mean.
Well, you know Volta.

Speaker 3 (18:00):
We've had.

Speaker 2 (18:00):
Sean Meister on the show with.

Speaker 1 (18:02):
Volta Lab.

Speaker 2 (18:03):
That's a great little incubator over there 100% Right
, a lot going on 100%.

Speaker 1 (18:08):
Man, it's everywhere, the super cluster that we've
been developing.
We're doing a lot withtechnology here in Halifax.

Speaker 2 (18:15):
Yeah, we have to, to be honest with you, I mean for
Nova Scotia, to for any countryplace.
I mean from an economyperspective, we have to double
down on the IP or the knowledgeeconomy.

Speaker 1 (18:28):
Yes.

Speaker 2 (18:29):
And, given our geographical size, I think that
we have to do geographical likeknowledge-based economy.
So Halifax is good with that.

Speaker 1 (18:39):
Could be better.

Speaker 2 (18:40):
Could definitely be better.
Yeah, because we haven't hadnot that I'm aware.
Maybe meta material that wentpublic out of Nova Scotia was a
billion dollar exit orliquidation, but we haven't had
many billion dollar exits.
If you think about it,newfoundland had a big billion
dollar exit called Verifin thatgot acquired by NASDAQ for $3.4

(19:04):
billion.
That has helped the ecosystemtremendously in Newfoundland
because there's at least threemore companies that are already
on the path to be billiondollars the last four years.
Wow, shopify yeah.
Classic example of Ottawa.
I mean, Ottawa was a governmentplace.
Shopify made it a tech hub.

Speaker 3 (19:27):
Right, right.

Speaker 2 (19:28):
So Nova Scotia definitely needs that.
I mean, atlantic Canada needsmore of that.
There were a couple really bigones in New Brunswick.
Q1 Labs was one that gotacquired by IBM for $600 million
, and then Radiant 6 that gotacquired by Salesforce for $300
X million.
So those are things that arehappening, but we need more of
them.
Those bigger hits, yeah.

Speaker 3 (19:51):
It's too bad.
We're stupid and can't do that,because I'd love to sell our
podcast for $600 million.
I think we'll have to get a lotmore subscribers.

Speaker 1 (20:01):
But yeah, back to what.
Do you think what's missing inHalifax with the tech world?
What do you think would happento get more here?
Would you want more incubation,more money invested?
What's missing?

Speaker 2 (20:15):
Definitely more money helps.
There's not a lot of regionalventure capital in this province
In Atlantic.
Most of them are dried up,tapped out, so that's one thing
that will definitely help a lotof investors.
You know venture funds a lot ofthem either in Nova Scotia,

(20:36):
have been government funded.
We need high net worthindividuals funding them.
That'll help.
A lot of high net worthindividuals here are not
investing in risky assets like astartup.
Okay, they would much rather doit in real estate and like more
traditional.
That's different from the US.
Yes, big time, big time, right,big time.

Speaker 1 (20:52):
Yeah.

Speaker 2 (20:52):
Big time yeah, so that would help.

Speaker 1 (20:55):
And why do you think that is?
I mean, is there a stigmabehind it in Canada?

Speaker 2 (21:03):
that's different, or is it tax reasons?
More risk takers, right thatyou have to give it to them.
So, as this podcast comes outin April.

Speaker 1 (21:10):
It's going to be a pretty terminalist time.

Speaker 2 (21:12):
I think Trump's tariffs are finally going to hit
.

Speaker 1 (21:14):
This is coming out April 1st.

Speaker 2 (21:16):
Yeah, something like that.

Speaker 1 (21:17):
Trump's April 2nd if he goes through with his.
Did you hear what he said?

Speaker 3 (21:20):
announced today Threat of steel 50% up.
Yeah, he's because of Ford'sthreat of 25%.

Speaker 1 (21:31):
It was funny, my partner Andrea and I, we were
talking about that the othernight and I said I don't know
man.
I said I think it's unwise togo back on electricity like that
because I think it's just goingto get worse and worse in the
situation yeah, it did.

Speaker 3 (21:43):
You don't poke the beer.
Yeah, poke the beer is right.
Yeah.
That being said, I don't knowthe bear is right.
Yeah, it's, uh.

Speaker 2 (21:52):
Yeah, that being said I'm, I don't know I'm.
I have a newfound uhappreciation for doug ford.

Speaker 1 (21:54):
I, I, I agree with you.
You think so?
Yeah, I mean we'll see whathappens.
I mean here's my prediction.

Speaker 3 (21:58):
Here's my prediction we'll do a quick political
prediction, sure, if and when,slash whatever.
When, if pierre polly f can'tpull off a win against Trudeau?
Against, against Kearney, yeahthen he will step down, like
every other last conservativemember has, I think.

Speaker 2 (22:18):
Ford goes step up.
Yeah, I think Ford goes for it.
I think, that.

Speaker 3 (22:20):
I think that's what he's positioned himself.

Speaker 2 (22:22):
I'm surprised.
Yeah, yeah, that's not astretch and you know what.

Speaker 3 (22:26):
I think he'd have a decent shot just based on this,
but also the fact that he's alittle bit more of like a
moderate conservative.
Moderate conservative is goodright.

Speaker 1 (22:33):
So I think he could win some people over that,
depending on how Carney goes.
Be interesting what Carney does, though.

Speaker 3 (22:40):
Yes, I have high hopes for him.
I do too, I have really highhopes for him.

Speaker 2 (22:45):
He's not what they say like a traditional
politician.

Speaker 3 (22:51):
Yeah right, what they say like a traditional
politician.
Yeah right, background is infinance, so yeah, he's also
again also kind of more of amoderate, he is definitely right
definitely yeah.
So I think that's, I thinkthat's the biggest thing and
like he's the best of bothworlds to me, I yeah I don't
want people involved in mybusiness or anybody else's uh,
uh, beyond uh the financials ofrunning the country right like
uh and uh, that seems what hewants to focus on.

Speaker 1 (23:11):
so I'm all for that, Isn't he?

Speaker 2 (23:13):
the only person that was the head of.

Speaker 3 (23:17):
The UK, the Bank of the UK.
Right, I was from the UK.

Speaker 2 (23:20):
That shows some pedigree.
He has a pretty good resume.

Speaker 1 (23:24):
Yeah, pretty good, I mean you know and I don't know,
harper was denying it, but theywere saying that he was a big
reason why we got out of our2008 crisis.

Speaker 2 (23:35):
Financial crisis.
Right yeah, he was a big reason.

Speaker 1 (23:37):
So, yeah, so I mean, yeah, kudos to Kearney, we're
trying to get him on this show.
We're just going to keepputting that out to the universe
.
Man, let's just manifest thisyeah no.

Speaker 3 (23:45):
I was actually talking to someone close to him
today yeah really yeah, oh, yeah, yeah we were originally going
to have him on before, um, youknow, before he won, yeah, as
part of the leadership type ofthing, and the message I got
today was matt, we haven'tforgotten about you, it's just
it's been really busy.
And they said, uh, be a lotmore guards.

Speaker 2 (24:04):
He, he actually said the next time we will next time.

Speaker 3 (24:07):
If you're, if you guys are going to end up sitting
down with a pint, he's likethere'll just be a lot more rcmp
officers yeah, okay, that'sawesome yeah, so it's pretty
cool I mean you did get timhouston yeah, yeah.
Yeah, he didn't show up withany rcmp office, he just he
showed up with his media guythat was pretty tough.

Speaker 1 (24:20):
He just cracked his knuckles.
He said let's go and.

Speaker 2 (24:22):
Was it shot here?

Speaker 1 (24:24):
no, we shot that one at uh old triangle yeah, oh nice
, yeah, nice, he picked thatspot.
Actually, he picked that spotyeah, it was a great spot too.
And they have the littlebunkies, so it's kind of cool to
record these in the littlebooths.

Speaker 3 (24:35):
Just to clarify too.
He said here, so here is theOxford Tap Room by Garrison.

Speaker 2 (24:40):
We didn't actually say that.

Speaker 3 (24:42):
Just several streets down from Dalhousie, where you
went to school.
We're here on the Oxford TapRoom and I'm drinking the PB&J,
the peanut butter and jam, whichis their brown and their
raspberry put together, and it'sawesome, I love all of
Garrison's beers, including thisnew one I'm trying today.

Speaker 2 (24:59):
I have to try that.

Speaker 1 (24:59):
Except for that PB&J one.
I can't do it, but this matchalager for me is really cool.

Speaker 3 (25:05):
I have to try some of that.

Speaker 2 (25:06):
It's a matcha tea lager and they just had it on
tap here.
It's pretty cool and I'm tryingout the Georgia Peach.

Speaker 3 (25:11):
It's really good, it's really good and we actually
had a guest on there thatactually did a 50-50 juicy IPA
and Georgia Peach mixed together.
It was awesome First time I hadthat mixed and it was really
really good.

Speaker 2 (25:24):
I love this place because I'm a big dog person.
I did not know that you'reallowed to bring your dog inside
.

Speaker 3 (25:30):
Yes, yeah, they let the dogs come in.
That is the coolest thing andyou know, it's actually like you
kind of really have to fightfor that a little bit, because
anytime there's any dealings offood and stuff like that.

Speaker 2 (25:40):
Yes, that's a big deal.
How did they get that?

Speaker 3 (25:42):
I think it's because it might be because the food is
served in the cafe side, I see,I see, and they just let you
bring it here.
Okay, I don't know that forsure, but that would be my guess
based on kind of technicalities.

Speaker 2 (25:55):
Yeah.

Speaker 1 (25:56):
So when can I ask you about Stealth AI again?

Speaker 2 (25:59):
Hey, Stealth AI so.

Speaker 1 (26:00):
I'll tell you about it right now.

Speaker 2 (26:01):
Whatever you can tell me.

Speaker 1 (26:02):
I totally respect.
We're not here trying to getany information.

Speaker 2 (26:13):
You know one of the things I believe is at least in
a startup journey and in life.
It's basically a collection ofstories.
This new company, which onLinkedIn is Stealthai, and I'll
tell you what.
It's still very new, so Ihaven't had a lot of stories
collected.
I'll tell you one story thathappened today.
So what the company we arebuilding is I mean, it's so
early.
This is month four of me fulltime on this we don't even we're

(26:37):
just figuring out the name.
It's called HeyGia,h-e-y-g-i-aio HeyGiaio.
What it is is it's basically aplatform specifically built for
consultants and agency ownersand professional service firms
to help them run and grow theirbusiness.

(27:00):
In my previous company I soldinto B2B tech companies was
there are hundreds and thousandsof consulting firms and
consultants that are busy doingwork, doing client delivery work
.
They don't have the resourcesor the time to hire a marketing

(27:20):
person or a salesperson,operations person and they
struggle with.
They're so focused on clientdelivery they don't have time to
grow their business and this isa big pain point.
I want to build a platform thatsort of works as a growth
engine for this group ofcompanies, these professional
service firms and I'm nottalking the Deloitte's and PwC's

(27:40):
, I'm talking about the boutiqueones or the independent
consultants.
I'm trying to build an AIplatform that helps them
automatically, help them growtheir business, sort of, while
they're focused on doing clientdelivery work.
Yeah, that's what it isInteresting Right now, still
super early, yeah, in navigatingthrough this.

Speaker 1 (28:00):
It's kind of a natural path for you to go into
AI from what you've done before.
I mean especially when you talkabout how your last business
developed, to how it grew Right,right and everything here right
.

Speaker 2 (28:08):
Oh yeah, I about how your last business developed to
how it grew and everything here,right, oh yeah, I mean I did
not know what I was going towork on, but what I did know was
two things A, I wanted to solvefor something that could impact
a million people, and B, Iwanted to work with something
with the whole generative AI.

(28:30):
Because this is honestly, thisis the whole generative AI.

Speaker 3 (28:33):
Because this is honestly this is the internet of
our era?

Speaker 2 (28:35):
Yeah, it totally is.
You need to be working on this,if you can.
I feel blessed and gratefulthat I can be working in this
space, learning a shit ton andthen using that to build a
solution that serves sort of anunderserved market.
These consultants andprofessionals Everyone is
building for B2B tech companies.
No one is building for theseprofessional service firms.

(28:57):
So that's what I'm doing andthe reason it's Stealth AI is
when you don't want to letpeople know what you're working
on.
Yet LinkedIn has theseplaceholder companies you can
put where you work AI.

Speaker 3 (29:10):
Stealth, so I just put a place.
So you'll put where you work.

Speaker 2 (29:11):
Ai stealth, so I just put a place so you'll see
there's 150,000 people workingin stealth AI.
Everyone that don't want to letothers know you just label, so
they're right.

Speaker 3 (29:21):
When I heard stealth AI I was like this dude's
creating like Skynet Terminatoris kind of happening.

Speaker 2 (29:29):
No, not that cool or crazy, but yeah.
So that's what it's calledHeyGia, and the story that I
wanted to share was I sent aninvestor, so I send investor
updates every month just as agood practice, saying, hey, this
is what we achieved, this iswhat was good, which was not
good, and what are we going towork on the next 30 days?
One of our investors super niceguy, his name is Ian Cavanaugh.

(29:51):
He just went ahead and put iton LinkedIn.
He's like, oh god, this guy's,what they're building is a game
changer.
Yeah, what they're building isa game changer.
Yeah, wow, we didn't want toannounce it yet, but he posted
it and we got a bunch of inboundleads because of that.
I'm like sure we'll go for it.
That's amazing, yeah, so,anyways, yeah.

Speaker 1 (30:09):
Yeah, thank you.
Yeah, so like with thistechnology I mean with AI for me
, I just think of it as aconsumer on a very personal meta
Apple as a consumer on a verypersonal meta Apple, whatever
very elementary use how muchit's evolved in the last year.

Speaker 3 (30:27):
Well, not 12 months, it's ridiculous.

Speaker 2 (30:29):
It's crazy.
It's exponential right.
It's crazy.

Speaker 1 (30:31):
So this must be a new challenge in terms of goal
creating and path creating andvision creating, because it's
like, say, if Matt and I had avision and we're like, well,
three months we'll do this andsix months we'll do this, I mean
those timelines got to be allover the place Like, how would
you?
Yeah, so weeks, and how are youeven making goals at this point

(30:51):
in terms of how you progress?

Speaker 2 (30:53):
Struggling with it.
Yeah, it's got to be crazy.
So I'm going to sound super oldnow.
I've been working in theindustry.
My first co-op was 2005, so 20years.
I've been working in tech.
I've never seen the pace ofinnovation and things that are
happening ever in my life.

Speaker 3 (31:19):
It's shocking to the point, people that are in the
industry.

Speaker 2 (31:20):
It is overwhelming and they're feeling burnt out.
There is new technology that isimproving on what the previous
one was doing, every single week.

Speaker 1 (31:27):
Well, that's the thing and that's like, for I
mean a question.
I don't know if it's in our 10questions or not here that we'll
get into but I'm jumping allover the place because, I'm
genuinely so curious.
So it's like you got a young guythat says, hey, I want to get
into this ai learning, or I mean, I know, I know my buddy davis
kid's going to go to collegenext year and he probably wants
to get into computer science andwants to wants to make sure

(31:49):
that he's in the right place tosucceed.
Yeah, I mean, how does he evenknow where to go because it's
changing so rapidly?

Speaker 2 (31:55):
yeah, but um, from a.
So, for example, if he's goingto computer science, he should
be okay.
Yeah, he should be okay, goodplace to go, Good place to go.
Yeah.
What will happen is this is mycore belief and this is a core
stance I have on AI what?
Because there's a big talk,you'll hear in AI saying it'll

(32:17):
kill jobs, right.

Speaker 3 (32:19):
Yeah, that's the fear that everyone a fear, yeah it's
a valid fear.

Speaker 2 (32:23):
Let me just say that this is not a bullshit thing,
it's a valid fear, right?
Um, this is what.
What my take is.
We as uh, white collar workers,if you may are knowledge
workers, whatever field.
There's two kind of jobs.
We do in the course of ourtasks.
We do in the course of our dayor week One task.

(32:45):
I call them tasks that we wantto do.
These are things that you getjoy out of.
These are sort of complex,non-deterministic tasks.
You don't know what the outputwould be, but like a sales call.

Speaker 1 (32:58):
So a lot of the sales is enjoyable if you enjoy doing
it A hundred percent.
Going out for lunch with aclient A hundred percent.
Doing a business deal,relationship building, crafting
the email, the pitch, the story,all of this.

Speaker 2 (33:08):
Yeah, these are things that you enjoy doing, and
every job has their ownenjoyment, right, like an
engineer has certain things, yep, and then there's certain tasks
that you don't enjoy doing.

Speaker 1 (33:17):
These are things that you have to do Absolutely Admin
work, admin work, updating yourCRM or stuff like that,
connecting this person, thatperson, through email for
something that hasn't been donethree months ago.
There we go.

Speaker 2 (33:27):
Or a reminder of a follow-up or scheduling a
meeting Using an old system theold computer system.

Speaker 1 (33:32):
Fair enough.

Speaker 2 (33:34):
If there's any systems in place or if there's
people in place that are doingthose things that you don't want
to do, those jobs are going tobe gone.
Yeah, those jobs are going tobe gone.
As an example, if you're asoftware engineer, there's a set
of things that people do iswhich is called testing or
quality assurance.
When a software is built, theybasically manually go test it to

(33:57):
make sure or write code to makesure, right, nothing is broken,
everything's no.
Engineer wakes up and goes ohshit, I'm gonna write an amazing
testing program no one, thatjob's gonna be gone.

Speaker 3 (34:07):
The qa um think of in sales?

Speaker 2 (34:10):
yeah, a lot of people .
No one enjoys cold prospecting,sending an email, booking
meeting.
No one enjoys it.
That job is at the risk ofgoing, and if you look at US,
there's a bunch of companiesthat are called AI, sdr, sales
development programs gettingmillions, hundreds of millions
of dollars in funding to solvefor it.
So anything that I believe thathumans don't get joy out of

(34:36):
will be gone.

Speaker 3 (34:38):
I mean that makes a lot of sense.
I mean our sponsor, mark Zirka.
Oh, strategy Up, strategy Up.
So he told the story.
I was in a networking meetingwith him one time and he was
telling the story about how heworks One of his clients.
He works with the Saudigovernment, sure, so they do a
lot of, obviously, becausethey're a faith-based

(34:59):
organization as a government,they do a lot of their praying
throughout the day and they havebreaks and things like that.
And he was saying that the Saudigovernment was actually
bringing him in to try to makethings more efficient and to run
so that they could actually dolike, essentially do less work
right, actually do like,essentially do less work right,

(35:22):
so that they can only, they canonly have, but not to pay them
less, not to lay anybody off,because the saudi government has
money coming out of the wazoo.
Yeah, and you know so theydon't want to like lay, they
still want to hire all the samepeople have it all the same.
But it allows them to do theirprayers throughout the day, have
their tea time and their lunchand all that stuff.
So they only end up workinglike 50 of the day that we would
in the run of a day.
Yeah, but they have automationsto do the things that you know

(35:43):
what they would pay people to do, but no one's getting a pay cut
.

Speaker 1 (35:46):
This was totally in the Mandalorian, by the way.

Speaker 3 (35:48):
Yeah, there was that episode where Jack?

Speaker 1 (35:49):
Black lived on the planet and the people, humans
beings didn't do nothing.

Speaker 2 (35:52):
Okay.

Speaker 1 (35:52):
They figured everything out and technology
robotics took care of everythingfor them, but then there was a
murder.
That that?
That goes.

Speaker 3 (36:00):
That also goes to speak of like, you know what ai
can do and what we can get to ohyeah, that's a dream where
that's, it's, it's.
It's not really any differentthan like star trek right like
star trek, money doesn't reallyexist anymore.
Uh, you, because you,everyone's basic needs are
provided you there's a lot ofdiscussion around that yeah
there's universal basic incomemight happen, universal basic

(36:22):
income might happen.
I mean, I was kind of saying,like you know, instead of just
paying somebody, like wouldn'tit make it?
Because I'm still a cat, like,I still believe in capitalism,
but I also believe in socialism,right?
So it'd be almost interestingif, like everyone, instead of
having a universal basic income,the government just built mass
buildings of units and you had ahouse, okay.

(36:42):
Well, not a house, a unit,right, an apartment building.
You're given that if you wantto work, to have a house in a
backyard, sure, work for it,yeah, but everyone gets a unit
right, everyone's not cold,right, and is not being rained
on.
Yeah, yeah, I'd almost likethat's almost the world I'd like
to see us live in.
That sounds cool and dystopianSounds dystopianly awesome.

(37:04):
I would love that idea, but it'slike if you want the bigger
house, work for it.

Speaker 2 (37:10):
I'm back in the units .

Speaker 1 (37:11):
Boom, here you go.
You're back in the units.

Speaker 2 (37:12):
You're bankrupt, you're back in the units Wife
left me.
You're back in the units.
Maybe I'm going off on atangent.
Isn't this how it is right now?

Speaker 3 (37:20):
In a sense sort of but not really Meaning.
We're not giving people units,we're giving people barracks
made of pallets.

Speaker 2 (37:30):
Sure.
Or basically, let's say youdidn't do any specialized trades
or you didn't go to school forsomething and you're doing sort
of an entry-level job.
You can with your money.
The concept of money isgovernment is printing the money
or whatever.
With the money that you get,you get to rent, you don't get

(37:52):
to own.
But if you really go step upthrough whatever, you then get
to get a bigger house.
That's true, but that has movedin Canada and in the US.
Through whatever you then getto get a bigger house.

Speaker 1 (38:00):
That's true, but that that's that, that that has
moved in Canada and in the USand everywhere, like it's just
such a thing where, like myparents were in the trades, you
know we had a house when I wassix years old and you know they
both worked really hard nowtheir mortgage is paid off their
house the kid.
Today they follow the same pathas my father and my mother, god
bless.

Speaker 3 (38:18):
They're both hardworking people and that's
why I was saying is like you'renot even in these like
government units.

Speaker 2 (38:25):
You're not renting, you're paying nothing, right?
The government takes care of it.
The government gives it to you.
Yeah, you have to use it.
I mean, it'll be great if thathappens, right?

Speaker 3 (38:34):
But if you look at like Star Trek and stuff like
that and I use Star Trek becausethe food's provided, you live
on ships or you live on a planetand all this other stuff Now
there's still certain desires.
If you watch Deep Space Nine,it was the only Star Trek that I
actually really liked.
But if you watch that, theyhave gambling, money still
exists.
It's just your basics are takencare of and that's kind of

(38:55):
where I'm at.

Speaker 1 (38:56):
But I think AI can get us.
So you're going all this fromStar Trek.
Is that what you're saying?
The whole, that whole tangentwas just from Deep Space Nine.

Speaker 3 (39:02):
Yeah.

Speaker 1 (39:02):
Oh, okay, okay, I was just wondering.

Speaker 3 (39:04):
But I think that's where, like that's where I think
AI could get us right, Becauseit could eliminate jobs that we
hate doing anyway.
I think that's the dream, but Ijust don't know.

Speaker 2 (39:18):
There's a little there's.
That's what Sam Altman talksabout.

Speaker 1 (39:21):
Sam.

Speaker 2 (39:21):
Altman does talk about that basic.
Like the founder of open AI, hedoes talk about the universal
basic income.
He's like yeah that needs tohappen, yeah, but we'll see.
We'll see how that goes.
But the one thing that I willtell you, though in the AI space
, and how fast it's moving, it'snot a fad.

Speaker 1 (39:39):
Yeah, it is real.
No, no, I don't think that.
Again, I don't think everybodyshould think that at this point.

Speaker 2 (39:44):
I recently was talking to a friend of mine and
what I told her was the VCs, theventure capitalists in America.
What they're telling theirstartups is.
The narrative that they'resaying is look, the software
market is $86 billion.
Right, that's the total moneythat's spent in US for software.

(40:08):
The labor market in America isbetween $4 and $20 trillion.
Wow, he's like now you buildnot for the software market,
you're going after the labormarket yeah meaning the pitch
that I give to you.
As you, let's say, I'm trying tosell it to you.
I'm not going to say, buy mysoftware for $30,000 because

(40:32):
it's going to make your lifeawesome or your recording great.
My pitch is I'm going to sellthis to you for $30,000 because
you don't need to hire two moreguys to edit this podcast, right
?

Speaker 1 (40:44):
So it's a labor market cost, we wouldn't have
been able to do this podcast 10years ago.
This podcast is brought to youa little bit by AI, right?
I mean if you're in the backend to do the episode bios,
expedia.

Speaker 2 (40:55):
I use AI wherever I can to cut corners to get this
product out.
I work a full-time job.

Speaker 1 (41:01):
This is a hobby.
And I like seeing my family, sowe do what we can to utilize AI
for this show.

Speaker 2 (41:07):
Yeah, so we'll see how this pans out.

Speaker 1 (41:11):
Yeah, and AI is doing podcasts.
Now you can actually get AI todo an entire podcast for you,
with zero involvement with hosts, on any subject.
You can get my clone.

Speaker 2 (41:19):
Yes.

Speaker 3 (41:20):
Deep fakes, deep fakes, yeah.

Speaker 2 (41:21):
I invested in a company called One Mind.

Speaker 1 (41:24):
They do it for sales.

Speaker 2 (41:25):
Yep, it's literally the first call that you have the
discovery call.

Speaker 3 (41:30):
Yeah, yeah.

Speaker 2 (41:31):
When you're figuring out if you're really a fit.
It's an AI clone of thesalesperson doing the discovery
and then passing it over.
Then the human, the accountexecutive, comes in oh wow.
Crazy.
So anyways.

Speaker 3 (41:47):
So like as someone who's really you know in the
thick of it, like does AI scareyou?

Speaker 2 (41:53):
For someone building an AI company.
I shouldn't be saying that itscares me.
No, it doesn't scare me, itdoesn't Not yet.

Speaker 3 (42:00):
Not yet.
Do you think it ever will getto Terminator?
Because we had Giles on hereand he kind of actually kind of
said like no, he doesn't thinkit ever can get to that point.

Speaker 2 (42:08):
I think there will be enough checks and balances that
we put in that make sure itwill not.

Speaker 1 (42:12):
Yeah, I think there's a capability for sentient AI to
happen, though I mean certainlyRight, and there's already an
example of that, Some somethingI read not too too long ago
about something like thathappening, where the AI just
started kind of forming its ownmind and saying some pretty dark
stuff and yeah, yes, but I Ijust don't think it's going to
get that draconian.

Speaker 2 (42:32):
It's not going to go to that, and that's my thought.

Speaker 3 (42:36):
I mean what Giles said in the episode too, which I
found really interesting, isthat just how powerful and
complex the human brain is toactually truly create something.

Speaker 2 (42:44):
Yeah right.

Speaker 3 (42:45):
He was talking about.
In order for AI to get to thepoint that it could have the
capacity and brain power of ahuman brain, it would take
basically all of the energy onthe earth to run it and also
cool it because, as you wouldknow, like anytime you're
running anything like we need,you know our ai room in our
insurance office has to be extracold, otherwise it overheats.

(43:07):
So there's also the coolingfactor.
If something's using our brainthat much power, there may not
be enough resources on the earthfor it to continue going well,
that's what sam alperin talksabout is the most atomic unit.

Speaker 2 (43:21):
that is going to be important is compute.
Yeah, compute is basically thecycle processing unit it takes
to run any of these simulations,to build the model and then to
do the reasoning he does talkabout, that compute is going to
be like electricity units ofenergy Right, it'll be traded
and stuff like that.
So yeah, units of energy, it'llbe traded and stuff like that.

(43:42):
So yeah, we'll see.
But I don't think I'm more onthe positive side of things.
My bet is, five to 10 yearsfrom now, people will be working
on things that they enjoy doingand AI will take care of the
things that they have to do.
That's cool, Sounds beautifulto me.

Speaker 3 (44:00):
That's what I'm betting on, though, like I, I'm,
I don't worry about ai, I, I, Idon't know, call me naive, but
even especially after talking togiles, I'm like even less
worried about it.

Speaker 2 (44:12):
no, I'm not personally worried like, for
example, to be honest, classicexample yeah, this interview
that you guys are doing, right,an AI will not be doing that.

Speaker 1 (44:21):
Not in any time soon and not as genuinely like.
We're different levels ofintelligence.
Towards something sitting in aroom, the curiosity.
Right, that's not going tohappen.

Speaker 2 (44:29):
What AI will help us do it is after this is done,
it'll chop it up, edit it foryou.

Speaker 1 (44:34):
Exactly, and that's perfect because you don't get
joy out of editing it.
It can provide a subnosis ofwhat we said, what we discussed.
It can do all these things, itmight make short LinkedIn clips
for you.

Speaker 2 (44:42):
All of that, yeah, but because that's not what you
enjoy.
You're not doing afternoonpodcast, talking to people, so
that, oh man, I'm going tocreate a killer edit.

Speaker 1 (44:52):
No, that's the least fun part of it.
I said things that you want todo versus have to do.
Yeah, yeah, and AI alreadymakes it easier.
Yes, and it'll make it evenmore easier.
Yeah, that's amazing.

Speaker 3 (45:05):
No, that's great, Just to go back a little bit to
kind of for you, kind ofpersonally too, because I do
like to kind of learn a littlebit about people Whereabouts in
India you're from.

Speaker 2 (45:15):
I'm from Calcutta.
Oh, you're from Calcutta, india, yeah, yeah.

Speaker 3 (45:17):
Well, anyone who knows Mother Teresa, you know.

Speaker 2 (45:20):
Yes, yes, definitely that kind of thing.
Yeah, yeah, yeah.

Speaker 3 (45:22):
And so what originally kind of like, what
made you pick like Nova Scotia?
I'm always curious.

Speaker 2 (45:27):
Yeah, yeah, yeah, you know.

Speaker 3 (45:28):
I'm sure Nova Scotia is not on the map for most
Indians.

Speaker 2 (45:31):
I've heard this question so many times.
Yeah, it's a very genuinequestion.
My brother came a year beforeto study to dow.
He was doing computer scienceand sorry, math.
He did mathematics andstatistics.
That's what he did.
The reason he came was one ofhis high school buddies moved
here in 1997 because his dad hada business oh.

(45:52):
So he knew him and he's like,yeah, you should come here, come
to dow.
So when he moved the next year,I decided to come here.
So, yeah, that's the reason thatmade me come here, and I've
been here 23 years now.

Speaker 3 (46:04):
Yeah, yeah, this is home.
Well, that's the thing andthat's why I'm always genuinely
curious, because I was born andraised here, so obviously I love
it here.
But I'm always curious aboutpeople who decide to leave their
home and make my home theirhome, because that's a big thing
to me, huge For me to go andleave Nova Scotia.
That would be a hard thing,right?

Speaker 2 (46:26):
So I can only imagine that's exactly what is
happening to me now.
Yeah, being in a tech company,one of the things is you need to
move to San Francisco, right?

Speaker 3 (46:34):
Yes, right.

Speaker 2 (46:35):
And I can't even imagine moving out of Nova
Scotia.

Speaker 1 (46:40):
That's awesome, and I wish more people thought like
you People are I hope they do.

Speaker 2 (46:46):
You can still build a big business.
You travel a lot, you go spendtime.
But that's not a bad thingeither, though.
No, it's great.
Yeah, you asked me thisquestion.
What does Nova Scotia need?
Like the Volta, so I'm veryclosely associated with Volta.
I host this monthly AI meetup,where we get 150 people

(47:08):
registered coming every month,where local hackers basically
present cool shit they've beenworking on.
It's awesome, wow.

Speaker 1 (47:13):
Can anybody come watch this.
Can I come just hang out?
Yes, you'd love it.
I would send you a link.
I would definitely come.
I would come hang out, it'llblow your mind.
It'll blow your mind.
It'll blow your mind.
Do you think here?
Let me ask you this, and I meancameras rolling here but AP
could come and maybe film theevent just to help promote it?
Oh man, that would be awesome.
I would totally love to do that.

Speaker 2 (47:34):
I'm going to invite you guys for say is so there's a
lot of tech talent becausethere's universities, there's
good research happening at daland smu and all this, which is
great, but what we lack is thegrowth, or the growth mindset,
yeah, that you only get when youare in that environment.
So what?
What needs to happen is morepeople from atlantic canada if

(47:56):
they go spend time in the sanfrancisco or boston or new york
or what are the big, big ups,big ups of London, understand
what the companies there aredoing, what are the cool things
sorry, what they're doing andthen bring it over that
knowledge and share thatknowledge.
Right, that's how you iteratefast, yeah, so yeah, that's cool
.

Speaker 1 (48:14):
No, I mean, we'd love to check that out.

Speaker 2 (48:16):
Yes, I will send you an invite.
Done, yeah, to check that out.

Speaker 3 (48:19):
Yes, I will send you an invite Done, yeah, that'll be
good, Okay, yeah, so yeah, Ithink maybe 10 questions time.
10 questions time, okay, Ithink so 10 ridiculously dumb
questions.

Speaker 2 (48:27):
I am looking forward to it.
Don't make your head hurt.
I have no idea what's going on.

Speaker 1 (48:34):
I heard some of them, so they're always Ridiculous,
right?
Okay, let's do it.

Speaker 3 (48:37):
Welcome to the Afternoon Pint.
It's Matt.

Speaker 1 (48:40):
Conrad Mic to open.

Speaker 3 (48:41):
And we are doing 10 questions with.
Tukan.
Okay, let's go All right, soI'll start it off.
So question number one so whatwas the most cumbersome thing
you remember having to do whenyou helped build a search engine
back in 2005?
What?

Speaker 2 (48:55):
was the most cumbersome thing, yeah, spam
detection, I clearly remember.
So we were building a websearch engine and spam was a big
problem, meaning when peoplesearch for a keyword, there's
these spam websites that wouldshow up because they would try
all these hacks or nefarioustechniques so they can rank

(49:19):
higher.
And this is 2005, 2006.
Even in google there was a lotof spam problem.
Um, so one of the problemsprojects that I've started
working on there um, one of thefirst projects was actually spam
detection is how can youautomatically detect which
website was trying was a spammywebsite?

(49:40):
Underneath there were either agambling site or a porn site or
something, or selling Viagra orsomething like that.
That was like classic.
So I built some algorithms withmy teammates to detect spam and
we brought it down drastically.
We published some researchpapers in peer-reviewed journals
, so that was the mostcumbersome thing.

(50:01):
That's where it really got meexcited about research and AI
and text mining and informationretrieval, for sure.

Speaker 1 (50:11):
So, yeah, that was the most cumbersome thing.
All right, cool.
Question number two when youfirst moved to Canada from India
as a student, what was thefirst thing about Canada you
found weird or interesting.

Speaker 2 (50:22):
Yes, the first thing was so.
Two things was when I waswalking the first few days,
people would just smile at you.

Speaker 3 (50:32):
I initially thought they know me.

Speaker 2 (50:34):
That was my first reaction, like do they know me,
but they don't know me?
It's just a nice thing to do.

Speaker 1 (50:40):
So that I found You're like a bunch of serial
killers over here.

Speaker 2 (50:44):
Initially I'm like maybe I met them somewhere, at
the airport or something, andthen after the first week I'm
like okay, this is the norm.
People smile at you when youwork, when you walk.
I love it, I freaking love it.

Speaker 3 (50:57):
So yeah, there you go .
Oh man, all right, that's agreat answer.
So question number three so, asa leader, how do you set goals
when working in such a rapidlydeveloping field as artificial
intelligence?

Speaker 2 (51:10):
Yeah, this is a battle that I'm going through
right now.
It's very difficult to setgoals.
I guess the way we have set itis it might sound cliched, but
our goals are very focused oncustomer objectives.
So for this new startup, heygia, our goal is to help

(51:33):
consultants and professionalservice or agency owners help
them grow their business sothat's our goal.
That's a core pain point we aretrying to solve owners help
them grow their business sothat's our goal.
That's a core pain point we aretrying to solve.
And when we onboard a customer,we know what they're asking for
, what their goal is.
So we basically go all ourengineering, all our research,
all the cool ai things that wedo needs to map to this

(51:54):
customer's win, customer's value.
That's how we set our goals.
So literally we have some northstar metrics that each customer
that we onboard needs to dothese three things and the goals
are focused on that.

Speaker 1 (52:06):
Great answer.
Yeah, you're doing great man.
What's your favorite, one ofyour favorite books to read?
It could be from any time,place or wherever.

Speaker 2 (52:15):
Yeah, I was not a book reader when I was a kid,
but once I started Leadstift Ireally started reading a bunch
of books, mostly nonfiction,exclusively nonfiction.
I'm not proud of it, but that'swhat it is.
The favorite book there's two.
I will say.
One is called the hard thingabout hard things, by ben

(52:39):
horowitz okay, the founder andceo is a big bit it talks about
it's a very real talk about thelife of a startup ceo.
No bullshit, like very real.
The second thing is this bookcalled the last lecture.
Do you guys know?

Speaker 3 (52:53):
randy posh have you heard of that.
I don't know that name.

Speaker 2 (52:56):
I would highly recommend it.
It's got nothing to do withstartup.
Randy Posh was a professor atCarnegie Mellon University and
he was diagnosed when he was 48,he was diagnosed with
pancreatic cancer.
He had three months to live, sohe gave a talk at Carnegie
Mellon.
It's called the Last Lecture Ifyou could give one lecture
before you die.

(53:16):
It's theoretical, but for himit was real.
It's on YouTube, that's cool,and they made a book out of it.
I listen to that YouTube videoonce every three months,
religiously.

Speaker 3 (53:26):
Yeah, yeah, yeah so.

Speaker 2 (53:27):
The Last Lecture.
They have a book too, really.

Speaker 3 (53:30):
Geez, I'll have to go through.
Please do go through.
Yeah, please do.
Uh.
So question number five if youcould invent a new holiday, what
would it be and how would it be?

Speaker 2 (53:40):
celebrated this is interesting question.
One day I was thinking one dayevery quarter, but maybe that's
too.
You were quick on this, butyeah, you didn't even take a
breath.

Speaker 3 (53:49):
This is.
This is like a hey, that's aweird question.
He was like I already got thisplanned and I had, it was not
scripted right no, no, no maybeit's a dumb one, but here's the
thing.

Speaker 2 (53:58):
I've been thinking about it.
I was talking to my my mypartner.
What I told her was onesupporter there should be one
day both of us should be off,where we get to spend time the
whole day with the person welove the most outside of us.
For us, it's our dog okay wedon't have kids, but I think
everyone there should be one daya holiday, you, of your

(54:20):
choosing that could get uglythough, man, because like what
if like you're like I'm sorry, Ipicked my in-laws, this time
right uh you know, you know, orwhatever right you'd have to
shift.
It'll be a good test.
It'll be a good test, but Ithink you need to spend one day
I like that, that I love theidea no phones, no computer no
work the whole day with them.

Speaker 1 (54:38):
Oh man, shut the internet right down.

Speaker 3 (54:40):
Right, it just hit a big switch.
My wife would love that answer.
That's a great answer.
That's a cool answer.
Yeah, over to you.

Speaker 1 (54:45):
Sniffy number six oh sorry, yeah, okay, Okay when
focused on startups and buildingcompanies.
You know what's one of yourfavorite hobbies just to to
chill out with.
I like cooking.

Speaker 2 (54:59):
Oh yeah, cool, me too .
I love to cook.
Yeah, I think it's um for meit's, but I don't like to cook
for myself.
I never cook for myself.
It has to be from friends,family, nice, um, but yeah, that
that'd be one thing that I do.
And I like going on hikes, uh,outdoor hikes.
Nova scotia is blessed.
There's so many pretty trailsall over.
Yeah, you have a dog, so we gohiking our ourselves, our

(55:20):
friends dogs, so, yeah, so thosewill be two things I find
cooking the most relaxing thingto do in the world.

Speaker 1 (55:24):
What?
I find cooking is one of themost relaxing things to do in
the world, like it always justcomes my mind I could not agree
more yeah I I tell my friendsI'm like if you see me cooking
food, no

Speaker 3 (55:35):
you know, I'm in a good mood, I'm okay, that's
actually something my wife and Ilike actively like to do.
We get a bottle of wine andwe'll cook a meal, like on a
friday night or saturday that isperfect.
Yeah, that's awesome we actuallyI mentioned this, I think, on
the podcast before, but likeduring covid, when we were all
locked down talking about tryingto find things to do, my wife
and I decided that we would uh,every wednesday we would cook a

(55:56):
different meal from a differentculture, and like so it was
really cool because we didresearch through the week to try
to find, like, what we weregoing to cook next.
Love it, and you can learn somuch about a culture from their
meals right, I love it.

Speaker 2 (56:07):
Yeah, that's such a great idea.
Yeah, it was fun, as long asyou're not making bread, because
everyone was making bread?

Speaker 3 (56:13):
okay, we did.
We made pretzels and stuff likethat, right, but from different
cultures.

Speaker 2 (56:18):
Different kinds of.

Speaker 3 (56:19):
You know what we did?
Try our own naan.
We made pretzels, that'simpressive yeah, what else did
we make?
Yeah, there was another form ofbread, but yeah, we did some
stuff like that.

Speaker 1 (56:32):
Okay cool, Okay, question number seven.
Oh, Matt, this is you.
This, we did some stuff likethat.
Okay cool, Okay.
Question number seven.

Speaker 3 (56:36):
Oh, matt, this is you , this is me, I guess.
So, for those just enteringuniversity and wanting to get
into technology, what are therecommendations you'd have for
them to study?

Speaker 2 (56:45):
That's a good question, this one.
I would say.
You know what?
If you're in computer science,understand the applications of
different things, understand thecore concept, um, but this one
thing that I think universitiesdon't teach enough.
But if there is any way you canimprove your storytelling

(57:08):
skills, I think that will applyfor any different, whether you
commerce, science, computerscience, computer science,
accounting, business, doesn'tmatter.
Anything that helps you improveyour storytelling.
I think that would be helpful.
And if you're a computerscience, definitely think of

(57:30):
whatever you're learning.
Building a practicalapplication of it would be
fascinating.
So that would be my answer.

Speaker 1 (57:34):
Okay, love it.
Okay, it's funny.
We that would be my answer.
Okay, love it, okay it's funny.
We talked about this earlier inour episode.
Unprovoked, this questionwasn't asked.
You kind of answered it anyways.
Yeah, you did.
Yeah, as a leader, how do youmotivate people?

Speaker 2 (57:49):
Did I answer that question?
Well, you talked about it In aroundabout way.

Speaker 1 (57:52):
We talked about your team feeling a little bit lost
in what they were doing.

Speaker 3 (57:56):
You were saying that money revenue wasn't motivating
them.
Yeah, and they had to find anew motive.

Speaker 1 (58:02):
And then you figured out a new motive to get them to
kind of work with people moreclosely.

Speaker 2 (58:08):
In my first startup.
I was 28 years old when Istarted First time CEO, had zero
knowledge.
I made all the mistakes I couldhave made and I made that, and
one of the big things was wasculture?
This falls under companyculture.
Yeah, made all the mistakes, sofew things that I.
That I do is uber transparency,so everyone in my company knows

(58:31):
exactly what's going on in thecompany, how much money we have
in the bank, how much runwaywhen we are out of money.
Everyone knows.
So transparency is one.
The second thing is celebratingsmall wins.
This is something that I didn'tdo in my last startup.
For us, a big win was when Ionly won a big client or
something major, a biginvestment or something happened

(58:52):
, a big meeting.
Those are great.
Celebrate them, but rarely doesit happen that those things
happen frequently.
So celebrating small wins.
Now this time, what we have iswe literally have a channel on
Slack called Wins A win could be.
We got a lot of engagement on aLinkedIn post.
A win could be.

(59:13):
One of our engineers pushed ina code three days earlier.
A win could be.
An investor said awesome job.
A win could be anything small,but we share that.
A win could be an inbound leadwho found us from Mexico and
came to us.

Speaker 1 (59:28):
Yeah, it's a win.
Well, you get a lot of momentumfrom propelling all those base
hits right, that's a strong team.

Speaker 2 (59:33):
That's exactly it.
I love it.
I think that is the biggestthing.
Yeah, transparency andcelebrating small wins I like
that Great answer.

Speaker 3 (59:40):
So question number nine.

Speaker 2 (59:48):
What's the last common question or task that you
can remember utilizing?

Speaker 1 (59:52):
AI for Today.
Okay yeah.

Speaker 2 (59:53):
What was it?
There was a task Funny enoughtoday.
Okay, yeah, what was it therewas?
Uh, there was a task funnyenough.
I was giving some feedback tomy engineering team and I
basically said and I couldn'tframe it well enough so I
described the problem that theengineering team had and said,
hey, if you were me, how wouldyou answer it?
So they came up with an answerand then I'm like, okay, that's

(01:00:14):
a nice way of framing it,because this is how I would
answer and I leverage that.
So, yeah, internalcommunication for an engineering
problem internal communication.

Speaker 1 (01:00:23):
beautiful answer, alright.
So the last question and we askevery guest that's been on our
show this year this question apiece of advice you were given
at any time in your life,whether it's been last week or
20 years ago that you held on to, that you want to pass along to
others, just any kind of pieceof advice.
It could be a quote, it couldbe something your family member

(01:00:43):
said, anything.

Speaker 2 (01:00:45):
There's many.
I mentioned about Randy Posh,the last lecture.
I'll go back to this and thething that he said was you
cannot change the cards.
You are dealt just how you playthe hand there you go.
I believe in that, more nowthan ever, with AI and
everything like the tariffs, youcannot complain about the cards
you are dealt.
It's a card we have been dealt.

(01:01:06):
How we play the hand.

Speaker 1 (01:01:08):
How we play the hand.
The strategy of getting throughthis thing and carrying it on
is everything we can bitch andwhine about this or we play the
hand.

Speaker 2 (01:01:15):
Awesome that's a card .
We dealt so.

Speaker 1 (01:01:17):
I like that.
That's good advice.
Thank you, it was awesomemeeting you.
Thank you, man cheers.
I really enjoyed the chat thankyou, that's a wrap, my friend,
amazing just like that Bye.

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