March 27, 2025 • 22 mins
Roberto Cervantes, CEO and co-founder of Flowlly, takes us on a fascinating journey into the world of AI agents for construction, revealing the crucial distinction between automation and true artificial intelligence. "Automation is a set of steps that are executed with no leeway to deviate," he explains, while AI brings the flexibility to navigate obstacles and find alternative paths to solutions.
The conversation uncovers a painful reality for many construction professionals - project managers trapped behind computers instead of being where they're most needed: on job sites. This observation became Flowlly's catalyst for creating AI solutions that handle the mundane document processing work that consumes valuable time. "My job is to be outside, not here in front of a computer," is the common refrain Roberto heard from construction managers, highlighting the urgent need for technological intervention.
We explore how AI is fundamentally changing our relationship with software. Rather than humans adapting to technology through clicks and manual inputs, Roberto envisions a future where technology adapts to us through natural, conversational interfaces. This shift represents a profound evolution - "Instead of us working for the software, the software is working for us." Yet amid this technological revolution, Roberto emphasizes that human connection remains irreplaceable, especially for building trust and relationships in construction. The greatest challenge isn't implementing AI but teaching people to critically evaluate its outputs rather than blindly accepting them. As Roberto warns, "The biggest risk is people being zombies, accepting everything the AI is putting out."
Ready to explore how AI agents could transform your construction workflow? Listen now to discover how the balance between technological efficiency and human oversight will shape the future of building.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Welcome to the Site.
Visit Podcast, leadership andPerspective from Construction
with your host, james Faulkner,recorded live from the show
floor at BuildX Vancouver 2025.
All right, roberto, how are youdoing?
(00:24):
Good?
And you, james, I'm doing verywell, thank you.
So you are co-founder of Flowly, yes, and you are making AI
agents.
That's right.
Speaker 2 (00:36):
Very cool.
Speaker 1 (00:36):
AI agents for construction, nice.
And so, yeah, I wanted to chatwith you a little about.
I mean, I'm obviouslyfascinated with where AI is
going, so maybe we can talkabout some specifics there, yep.
So first of all, how do peopledistinguish between AI and
(00:59):
automation?
Speaker 2 (01:01):
I think automation is more a set of steps that are
executed, but there's no leewayfor it to deviate.
So if one thing breaks, thenthe automation stops there.
Speaker 1 (01:23):
I see.
Speaker 2 (01:24):
AI gives flexibility to that automation right.
So even if you find an edgecase, it will find its way
around and execute it.
So it's doing a little bit ofthinking, if we can call it that
way, but it's just finding itsway through.
So it's more open to automation.
To just tell it this is wherewe start, this is where we end.
(01:44):
You figure out the in-betweenskind of I see, okay Now.
Speaker 1 (01:51):
So we've seen like big startups, like makecom,
you've seen that Yep, where youcan basically plug in Zapier
does the same thing.
So building agents to be ableto do a number of different
sequences to pull data from onesource, crunch that data, then
(02:12):
spit it out to another one andmaybe do a loop of that.
What other industries are youmodeling some of this from?
Is there other industries thatare doing great things with this
?
Are you modeling some?
Speaker 2 (02:25):
of this from.
Is there other industries thatare doing great things with this
?
I think one of the first onesis marketing, and I think it's
where the initial LLMs reallyshine.
They were able to write a lotof marketing copy and then
create images and now creatingvideos.
It's an easy way for someone tokind of automate their
(02:46):
marketing teams.
So I think marketing is one ofthose industries that's been
really good.
The other is the whole salesside.
Speaker 1 (02:55):
Sales automation yes.
Speaker 2 (02:57):
BDMs, bdrs, sending emails, even calling people the
voice.
Ais are getting so, so goodthat in a few years we're not
going to be able to distinguishan AI to a human calling us.
So those are the two that Ithink are taking more advantage
of the AI agents right now.
Other industries are startingto pick up, but those are the
(03:19):
two big ones.
Speaker 1 (03:20):
Yeah, so obviously we're looking at, um, how to
save time.
This is there's uh inconstruction.
We talk about a number ofthings I mean, robotics gets
into this too uh, which is dull,dirty and dangerous, and this
is the dull part.
Yeah, this is the stuff you'relike.
(03:41):
Seriously, I gotta go andcrunch all this crap.
It takes me hours a I don'twant to do this.
So initially, we had thistransformation from paper to
digital.
That was like the first thing,and then the next one.
Then is that, what do we dowith that digital Right?
So this is like the and I thinkthat this is where I have an
(04:04):
interest, obviously, withSiteMax and what we can be doing
.
Thank you In terms of theopportunity there is in order to
have people doing more onconstruction, that is, more
(04:26):
critical work rather than thedull work.
So this is kind of your mantrais like how do you, how do you
get people to be actuallyworking in construction rather
than uh on mindless stuff?
Speaker 2 (04:39):
yeah, and I think when, when we started, uh, we
were in toronto and we went outto talk with project managers
and construction sites and theyall said the same thing, which
was I'm sitting here in front ofa computer all day reading all
these documents to try to dosomething, but I should be
outside.
My job is to be outside, nothere in front of a computer, but
(04:59):
for contracting, whatever, Ineed to be reviewing all these
documents.
And that was kind of like thelight bulb moment for where it
was like, well, the ais arereally good at just reading the
documents.
They don't complain.
They can read thousands ofpages in seconds.
So can we do something to helpthere?
So so, yeah, the idea is howcan we make people engage in
more thinking activities?
(05:20):
and there's just normal copypastpasting activities.
Speaker 1 (05:23):
Right, okay, yeah.
So it's basically alleviatingthe bottleneck of volume versus
consumption of pertinent data.
Yeah, okay, Lord's heart.
So where do you see this allgoing 10 years from now?
(05:44):
What's your pillow dream?
Speaker 2 (05:47):
that you think about, when you think of.
Where all this?
Speaker 1 (05:49):
is going.
Speaker 2 (05:51):
I think what AI and its agents and the way things
are evolving is changing the waywe interact with software.
Before, like you mentioned,when we moved from paper to
digital, it was still a lot ofclicking on buttons.
Right, that was the best wecould do at that point with the
technology, and that was fineand we all got used to that.
(06:13):
But now these AIs are allowingus to work with technology in a
way that doesn't requireclicking on buttons, doesn't
require changing how we dothings.
So, instead of us working forthe software, the software is
working for us, if that makessense.
So, for example, you can havethe bot that joins meetings
(06:35):
right and writes the meetingminutes For a human.
The only thing they have to dois just click on the accept the
bot to the meeting right, thesame button they're clicking to
accept all the other people whoare joining the meeting and from
there the AI will take over andwrite the meeting minutes.
It could extract a lot ofinformation, do graphs and
whatever you want with themeeting data, right?
So I think it's changing how wework with technology and so
(06:57):
that's going to completelychange how we feel about
software, right?
So the new generations aregoing gonna grow up used to
talking to an ai right, havinghaving an ai as a friend and
things like that.
So they're gonna expectdifferent things when they come
to to to work right, instead oflooking at things in a computer
(07:18):
just asking, asking about to tofind some information and tell
me or create a podcast with thatinformation, right.
So I think that's where we are,is where we'll be seeing less
user interfaces like we use,like we know now, and more
interacting like if we wereinteracting with another human
with technology.
Oh, interesting.
Speaker 1 (07:39):
Okay, yeah, I mean I think you and I see the same
thing.
That's good, yeah, no, I seeexactly the same thing.
So as you look around a showlike this, you know here at
BuildX, like, what are yourthoughts?
When you see everybody sellingthere, does this seem like an
(08:00):
old school method to you ingeneral, people trying to sell
their stuff, communicating witheach other and because, like
when let's just say you have,instead of coming to the show,
let's say I have an AI agent,that's like just get me all the
(08:20):
information from all the booths,and maybe we need virtual
booths because maybe that's thereason.
But some things are physical.
There's door companies here.
You actually need to feel whatit looks like.
There's physical things and thephysical world is difficult.
But do you think we're going toget there in terms of I don't
(08:42):
need to come to something likethis for some things and I can
just have an agent go and getstuff for me?
Is it really about therepetitive and redundancy?
That's just a waste of time.
Speaker 2 (08:56):
That's a good question.
I think some parts of thisprocess, yes, but I think what
we learned from COVID is we aresocial creatures, so we very
quickly got bored of beinginside right.
We crave going outside andinteracting with people.
So definitely there are thingsabout this process that me
(09:19):
sometimes, as an introvert, gaveand I would love an AI to take
over.
But at the same time, seeingsomeone gives me certain trust
that I maybe don't have if I'mjust interacting with a website.
So I think that that partthat's so very ingrained in
humans, the trust you won't beable to to take over with, AI,
(09:40):
right, okay, what is so?
Speaker 1 (09:46):
let me ask you this.
So, in terms of, let's say thata lot of the, what are the
risks of AI in construction ingeneral on the job site?
Is there like a what like theAI?
And construction in general onthe job site Is there like a
what like the?
There is a safety elementbetween, and there's obviously
(10:13):
going to be safety pluses, as in, benefits, as in can predict
more things, et cetera, butthere is a consciousness of
human beings interacting withother human beings that a human
needs to fact check.
If you will, you need toactually open your eyes and go
okay.
So do you see the dovetailingof cameras and AI replacing that
(10:38):
person's having to fact checkthat thing?
Speaker 2 (10:41):
I hope not, and I think that's the biggest risk
People getting complacent andtrusting the output of the AI
forever.
Speaker 1 (10:49):
Isn't that inherent that they're going to do that
though?
Speaker 2 (10:52):
I think, yes, they will, and there probably has to
be some control systems toprevent that from happening,
because we don't want thathappening.
Maybe in five years, the AIsare so good that, yes, we don't
need to supervise the outputanymore, but right now it's not
there and, by definition, an AIis just predicting the next
(11:15):
token.
So, as much as we try to controlwhat that prediction is, we
never know what that predictionwill be.
So that means we always need tocheck the output, because it's
going to be a random output, sothere's always still a need for
a human to supervise.
So the biggest risk, I think,is that people are just being
zombies, accepting everythingthat the AI is putting out Right
(11:37):
and everything that the AI isputting out.
Speaker 1 (11:40):
Right.
So one of the things that weare experiencing today and this
is where I think this is a greatconversation- Maybe we need to
have some booze or something.
(12:01):
So we're in an economy right nowwhere people are in a
consumption economy with theirphone.
So you'll see people spending.
They'll come home from work,they'll spend four or five hours
on their phone and they'reconsuming.
They're not making anything,they're just consuming and the
level of consciousness of theconsumption is very low and it's
(12:25):
required that they findsomething that tweaks their
interest, because when you haveso much volume, only some things
get through for you to stop andwatch that again or whatever it
is.
So do you think that this isgoing to these controls that
you're talking to have thesecontrols in place to mitigate
(12:46):
the flow?
Like if you, let's just say,old school, you had to go and
look through 50 documents andyou'd be like, okay, and then
you'd do an analysis betweenthem and you'd go what are the
trends here?
Put something into aspreadsheet.
You do an analysis between them, you go what are the trends
here?
Put something into aspreadsheet.
There is an interactivebackwards and forwards there for
(13:07):
the consciousness of data.
If you just give that to me, Imight just rely on it, and this
is kind of what you're gettingat right on.
Do you think that there willbecome a point of complacency
that needs to be mitigated, andI'm just trying to figure out
(13:29):
how that.
I mean the opportunities inconstruction are all things that
are I mean, everything'smission critical, but some
things are less crucial.
They're all crucial, don't getme wrong.
Everything's important inconstruction.
But there are some thingscrucial.
They're all crucial, don't getme wrong.
Everything's important inconstruction.
But there are some things whereyou're like yeah well, if we
didn't get that right?
you know it wasn't a huge miss,whereas, like safety or
(13:51):
something, it's something thatgets killed.
So there's it seems likethere's opportunity for these
controls to get put in place onthings that are not so crucial.
Right that these?
Controls to get put in place onthings that are not so crucial.
Right, that are just a benefitto me.
So maybe there are things that,well, maybe we're in there.
Wouldn't it be great ifbusiness?
(14:13):
Wouldn't it be great if I couldget this information?
I can't get it today, ratherthan I have it today.
It takes too long.
What about the?
I can't get it?
Yeah, because the efficiencyside is going to have risks,
whereas if I never had it before, it's a net benefit regardless
(14:35):
of what happens.
Speaker 2 (14:36):
But do you?
Right now we don't have itbecause we are not thinking
about those things, because wedon't have the time to think
about those things, we'respending all the time doing the
other stuff.
Speaker 1 (14:48):
No, I just think it was too arduous and maybe it was
coming out of multiple systemsand APIs weren't connecting.
Zapier wouldn't do it.
You know, what I mean.
We couldn't get it becausethere wasn't a method.
So, that's what I'm saying.
I think that there's somesignificant opportunities there.
Speaker 2 (15:04):
Yeah, and that, I think, would help us take
everything to the next level.
Right, because now you'reseeing things that you were not
seeing before.
So what does that mean and whatdo you do with that data?
So definitely the AIs could bedoing that, but I still think
people the first thing they'regoing to go for is the
automation of the things they'redoing today, and I think
(15:26):
they're part of the thing thatwe need to figure out is how to
teach people to do criticalthinking.
How can they understand theoutput by asking questions to
the AI to find hey, this numberthat you're putting here, why is
it there?
What is it coming from?
So, trying to understand thosethings, and how do people learn?
(15:49):
Today?
They first have to go throughthat process of being the ones
filling in the forms, filling inthe spreadsheets kind of
understanding where the data isin the PDFs and all those things
.
But are they really thinking?
Not right?
They're just copy pasting andthey're just walking there.
So you start learning once yougive that to someone and that
(16:10):
person turns back and startsscreaming at you because you did
something wrong.
Right now you're all okay, Imessed it up here.
So how do we help young peoplebecome that person that screams
at the AI to know that somethingis wrong Because, yeah, the
data inputting is no longergoing to be done by a human.
So what's the next thing thathumans do today after someone
(16:34):
filled in the spreadsheet?
Speaker 1 (16:35):
Yeah, it's interesting when you say
screaming at the AI, becausethat can be kind of interesting.
It's kind of like, you know,when there's a company that you
have a service with and theyonly have an email address for
you to contact them and they'renot getting back to you.
Yes, it feels like that.
Sometimes you get someone onthe phone and you're like what
the hell?
Like well, I can't get thisthing to do something.
So, yeah, so you when you showup in places and obviously you
(16:58):
know I want to sort of keep thisconfidential, but when you show
up places and people are like,oh shit, the AI guy's here.
Do people think about their jobs?
Do they see the net positive ofmaybe their job being easier,
or do they see it as a threat?
Speaker 2 (17:16):
I think it depends on who we talk with.
If we talk with the peoplewhose tasks the AI will do, they
feel threatened by it, but thenit's a matter of having them
understand.
Is it really you and your jobfilling in spreadsheets, or
you're here for more than that?
So having them understand thatfilling a spreadsheet is not a
(17:39):
high value thing you could bedoing.
So there are more things.
It is not a high value thingyou could be doing, so there are
more things.
But what we've seen changesince two years ago when we
started is then people startedto hear about AI.
They were concerned because allthe things that they were
seeing in the news is thatthings are hallucinating, that
things are stealing your data.
That was everything that was onthe news.
(18:00):
Now, when we talk with people,they're way more interested,
because this thing has beenhappening for three years now.
So more and more of mycompetitors are using it.
More people are talking aboutit.
So I want to know about it.
Maybe not start using it, butat least I want to understand
what this thing is and, if itcan help me, how it can help me.
So it changes and even maybethe people who felt threatened
(18:24):
in the beginning now they'restarting to see.
Well, maybe this is the way inwhich I can differentiate myself
and the job site yeah, thatmakes sense, if I take a tool,
then I can be more productive,more efficient and my boss will
be happier with me yeah, that'scool.
Speaker 1 (18:39):
Yeah, I think what we uh, it's going to be one of
those things where you see the,the sort of larger companies
doing the tech adoption and thensort of moving their way down.
I had a podcast I did inToronto with one of the guys
from Lafarge Concrete Companyand he's like the transformation
guy and he's doing he's makingagents, like you are, for them
(19:03):
internally, and so it's aninteresting path that we're at.
Now.
Let me ask you this At whatpoint is making agents agentable
?
What do you mean by agentable?
Well, at what point agentable?
What do you mean by agentable?
(19:24):
Well, at what point?
I mean so to make in order to.
At what point can you ask anagent to make the agents like
you're talking?
Do you know what I'm saying?
Yes, like, at what point doesthat?
Because we're looking at thatin software in general.
Right, at what point do you getAI to make the software for you
?
Well, it's multifaceted in thatpoint, right, because it's
(19:45):
complicated-ish, but it can geteasier Once one does it.
Once, then you can startspitting this stuff out pretty
easy, right, it's just the onethat's going to be.
So, you know, if I look atSitemax, for instance, I go okay
, well, what AI can just makeour whole platform?
Well, not that easy to do today, but once one person does
(20:06):
something like SightMax, it'sgoing to be easier and way
easier and way easier and wayeasier.
And then suddenly that's thewatershed moment, right?
But yeah, do you think aboutthat in terms of at what point
is the action become?
(20:27):
Does it self-cannibalize itself?
Speaker 2 (20:30):
So, for example, if you look at Zapier right now,
they actually have that featurenow where you describe your
agent and it will try to findwhat's the best way to build it
based on what they have right.
So that's already happening.
But there are two pieces to theagent.
One is what is the agentinteracting with?
(20:51):
So if you don't have thoseintegrations, it doesn't matter
what you ask the agent, it won'tbe able to pull the data or
push the data.
So that's one piece.
The second piece is the prompt,which is what makes the agent
act.
So I think the prompt iseasier-ish to do, as long as the
(21:11):
agent, or this AI, is capableof asking the relevant questions
and asking for the relevantinformation to then be able to
generate its own prompt.
The integration is where itbecomes harder, because someone
might be using a software you'venever heard of and it's going
to ask for that integration.
So today you won't be able todo that.
So I think that's really wherethe challenge is, because there
(21:32):
is no universal API to connectto whatever is out there, so it
won't be something that canintegrate with all your tools
whenever you need it.
Speaker 1 (21:44):
I mean, it's getting, it will get that way, but it's
going to take some time, yeah,but yeah, that's pretty cool,
all right, well, that's prettycool, man, um.
So yeah, well, you did a goodthing at the show here.
That's been awesome, and I lookforward to having more chats
with you.
Maybe this is just the firstone.
I think it might be, yes, um,but but yeah, we wish you luck
with everything and yeah, let'skeep our conversations going.
Speaker 2 (22:07):
Perfect Love, it All right, well, thank you.
Speaker 1 (22:08):
Thank you very much, Bye.
Well, that does it for anotherepisode of the Site Visit.
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(22:28):
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All right, let's get back tobuilding.
Welcome to the Site.
Visit Podcast, leadership andPerspective from Construction
with your host, james Faulkner,recorded live from the show
floor at BuildX Vancouver 2025.
All right, roberto, how are youdoing?
(00:24):
Good?
And you, james, I'm doing verywell, thank you.
So you are co-founder of Flowly, yes, and you are making AI
agents.
That's right.
Speaker 2 (00:36):
Very cool.
Speaker 1 (00:36):
AI agents for construction, nice.
And so, yeah, I wanted to chatwith you a little about.
I mean, I'm obviouslyfascinated with where AI is
going, so maybe we can talkabout some specifics there, yep.
So first of all, how do peopledistinguish between AI and
(00:59):
automation?
Speaker 2 (01:01):
I think automation is more a set of steps that are
executed, but there's no leewayfor it to deviate.
So if one thing breaks, thenthe automation stops there.
Speaker 1 (01:23):
I see.
Speaker 2 (01:24):
AI gives flexibility to that automation right.
So even if you find an edgecase, it will find its way
around and execute it.
So it's doing a little bit ofthinking, if we can call it that
way, but it's just finding itsway through.
So it's more open to automation.
To just tell it this is wherewe start, this is where we end.
(01:44):
You figure out the in-betweenskind of I see, okay Now.
Speaker 1 (01:51):
So we've seen like big startups, like makecom,
you've seen that Yep, where youcan basically plug in Zapier
does the same thing.
So building agents to be ableto do a number of different
sequences to pull data from onesource, crunch that data, then
(02:12):
spit it out to another one andmaybe do a loop of that.
What other industries are youmodeling some of this from?
Is there other industries thatare doing great things with this
?
Are you modeling some?
Speaker 2 (02:25):
of this from.
Is there other industries thatare doing great things with this
?
I think one of the first onesis marketing, and I think it's
where the initial LLMs reallyshine.
They were able to write a lotof marketing copy and then
create images and now creatingvideos.
It's an easy way for someone tokind of automate their
(02:46):
marketing teams.
So I think marketing is one ofthose industries that's been
really good.
The other is the whole salesside.
Speaker 1 (02:55):
Sales automation yes.
Speaker 2 (02:57):
BDMs, bdrs, sending emails, even calling people the
voice.
Ais are getting so, so goodthat in a few years we're not
going to be able to distinguishan AI to a human calling us.
So those are the two that Ithink are taking more advantage
of the AI agents right now.
Other industries are startingto pick up, but those are the
(03:19):
two big ones.
Speaker 1 (03:20):
Yeah, so obviously we're looking at, um, how to
save time.
This is there's uh inconstruction.
We talk about a number ofthings I mean, robotics gets
into this too uh, which is dull,dirty and dangerous, and this
is the dull part.
Yeah, this is the stuff you'relike.
(03:41):
Seriously, I gotta go andcrunch all this crap.
It takes me hours a I don'twant to do this.
So initially, we had thistransformation from paper to
digital.
That was like the first thing,and then the next one.
Then is that, what do we dowith that digital Right?
So this is like the and I thinkthat this is where I have an
(04:04):
interest, obviously, withSiteMax and what we can be doing
.
Thank you In terms of theopportunity there is in order to
have people doing more onconstruction, that is, more
(04:26):
critical work rather than thedull work.
So this is kind of your mantrais like how do you, how do you
get people to be actuallyworking in construction rather
than uh on mindless stuff?
Speaker 2 (04:39):
yeah, and I think when, when we started, uh, we
were in toronto and we went outto talk with project managers
and construction sites and theyall said the same thing, which
was I'm sitting here in front ofa computer all day reading all
these documents to try to dosomething, but I should be
outside.
My job is to be outside, nothere in front of a computer, but
(04:59):
for contracting, whatever, Ineed to be reviewing all these
documents.
And that was kind of like thelight bulb moment for where it
was like, well, the ais arereally good at just reading the
documents.
They don't complain.
They can read thousands ofpages in seconds.
So can we do something to helpthere?
So so, yeah, the idea is howcan we make people engage in
more thinking activities?
(05:20):
and there's just normal copypastpasting activities.
Speaker 1 (05:23):
Right, okay, yeah.
So it's basically alleviatingthe bottleneck of volume versus
consumption of pertinent data.
Yeah, okay, Lord's heart.
So where do you see this allgoing 10 years from now?
(05:44):
What's your pillow dream?
Speaker 2 (05:47):
that you think about, when you think of.
Where all this?
Speaker 1 (05:49):
is going.
Speaker 2 (05:51):
I think what AI and its agents and the way things
are evolving is changing the waywe interact with software.
Before, like you mentioned,when we moved from paper to
digital, it was still a lot ofclicking on buttons.
Right, that was the best wecould do at that point with the
technology, and that was fineand we all got used to that.
(06:13):
But now these AIs are allowingus to work with technology in a
way that doesn't requireclicking on buttons, doesn't
require changing how we dothings.
So, instead of us working forthe software, the software is
working for us, if that makessense.
So, for example, you can havethe bot that joins meetings
(06:35):
right and writes the meetingminutes For a human.
The only thing they have to dois just click on the accept the
bot to the meeting right, thesame button they're clicking to
accept all the other people whoare joining the meeting and from
there the AI will take over andwrite the meeting minutes.
It could extract a lot ofinformation, do graphs and
whatever you want with themeeting data, right?
So I think it's changing how wework with technology and so
(06:57):
that's going to completelychange how we feel about
software, right?
So the new generations aregoing gonna grow up used to
talking to an ai right, havinghaving an ai as a friend and
things like that.
So they're gonna expectdifferent things when they come
to to to work right, instead oflooking at things in a computer
(07:18):
just asking, asking about to tofind some information and tell
me or create a podcast with thatinformation, right.
So I think that's where we are,is where we'll be seeing less
user interfaces like we use,like we know now, and more
interacting like if we wereinteracting with another human
with technology.
Oh, interesting.
Speaker 1 (07:39):
Okay, yeah, I mean I think you and I see the same
thing.
That's good, yeah, no, I seeexactly the same thing.
So as you look around a showlike this, you know here at
BuildX, like, what are yourthoughts?
When you see everybody sellingthere, does this seem like an
(08:00):
old school method to you ingeneral, people trying to sell
their stuff, communicating witheach other and because, like
when let's just say you have,instead of coming to the show,
let's say I have an AI agent,that's like just get me all the
(08:20):
information from all the booths,and maybe we need virtual
booths because maybe that's thereason.
But some things are physical.
There's door companies here.
You actually need to feel whatit looks like.
There's physical things and thephysical world is difficult.
But do you think we're going toget there in terms of I don't
(08:42):
need to come to something likethis for some things and I can
just have an agent go and getstuff for me?
Is it really about therepetitive and redundancy?
That's just a waste of time.
Speaker 2 (08:56):
That's a good question.
I think some parts of thisprocess, yes, but I think what
we learned from COVID is we aresocial creatures, so we very
quickly got bored of beinginside right.
We crave going outside andinteracting with people.
So definitely there are thingsabout this process that me
(09:19):
sometimes, as an introvert, gaveand I would love an AI to take
over.
But at the same time, seeingsomeone gives me certain trust
that I maybe don't have if I'mjust interacting with a website.
So I think that that partthat's so very ingrained in
humans, the trust you won't beable to to take over with, AI,
(09:40):
right, okay, what is so?
Speaker 1 (09:46):
let me ask you this.
So, in terms of, let's say thata lot of the, what are the
risks of AI in construction ingeneral on the job site?
Is there like a what like theAI?
And construction in general onthe job site Is there like a
what like the?
There is a safety elementbetween, and there's obviously
(10:13):
going to be safety pluses, as in, benefits, as in can predict
more things, et cetera, butthere is a consciousness of
human beings interacting withother human beings that a human
needs to fact check.
If you will, you need toactually open your eyes and go
okay.
So do you see the dovetailingof cameras and AI replacing that
(10:38):
person's having to fact checkthat thing?
Speaker 2 (10:41):
I hope not, and I think that's the biggest risk
People getting complacent andtrusting the output of the AI
forever.
Speaker 1 (10:49):
Isn't that inherent that they're going to do that
though?
Speaker 2 (10:52):
I think, yes, they will, and there probably has to
be some control systems toprevent that from happening,
because we don't want thathappening.
Maybe in five years, the AIsare so good that, yes, we don't
need to supervise the outputanymore, but right now it's not
there and, by definition, an AIis just predicting the next
(11:15):
token.
So, as much as we try to controlwhat that prediction is, we
never know what that predictionwill be.
So that means we always need tocheck the output, because it's
going to be a random output, sothere's always still a need for
a human to supervise.
So the biggest risk, I think,is that people are just being
zombies, accepting everythingthat the AI is putting out Right
(11:37):
and everything that the AI isputting out.
Speaker 1 (11:40):
Right.
So one of the things that weare experiencing today and this
is where I think this is a greatconversation- Maybe we need to
have some booze or something.
(12:01):
So we're in an economy right nowwhere people are in a
consumption economy with theirphone.
So you'll see people spending.
They'll come home from work,they'll spend four or five hours
on their phone and they'reconsuming.
They're not making anything,they're just consuming and the
level of consciousness of theconsumption is very low and it's
(12:25):
required that they findsomething that tweaks their
interest, because when you haveso much volume, only some things
get through for you to stop andwatch that again or whatever it
is.
So do you think that this isgoing to these controls that
you're talking to have thesecontrols in place to mitigate
(12:46):
the flow?
Like if you, let's just say,old school, you had to go and
look through 50 documents andyou'd be like, okay, and then
you'd do an analysis betweenthem and you'd go what are the
trends here?
Put something into aspreadsheet.
You do an analysis between them, you go what are the trends
here?
Put something into aspreadsheet.
There is an interactivebackwards and forwards there for
(13:07):
the consciousness of data.
If you just give that to me, Imight just rely on it, and this
is kind of what you're gettingat right on.
Do you think that there willbecome a point of complacency
that needs to be mitigated, andI'm just trying to figure out
(13:29):
how that.
I mean the opportunities inconstruction are all things that
are I mean, everything'smission critical, but some
things are less crucial.
They're all crucial, don't getme wrong.
Everything's important inconstruction.
But there are some thingscrucial.
They're all crucial, don't getme wrong.
Everything's important inconstruction.
But there are some things whereyou're like yeah well, if we
didn't get that right?
you know it wasn't a huge miss,whereas, like safety or
(13:51):
something, it's something thatgets killed.
So there's it seems likethere's opportunity for these
controls to get put in place onthings that are not so crucial.
Right that these?
Controls to get put in place onthings that are not so crucial.
Right, that are just a benefitto me.
So maybe there are things that,well, maybe we're in there.
Wouldn't it be great ifbusiness?
(14:13):
Wouldn't it be great if I couldget this information?
I can't get it today, ratherthan I have it today.
It takes too long.
What about the?
I can't get it?
Yeah, because the efficiencyside is going to have risks,
whereas if I never had it before, it's a net benefit regardless
(14:35):
of what happens.
Speaker 2 (14:36):
But do you?
Right now we don't have itbecause we are not thinking
about those things, because wedon't have the time to think
about those things, we'respending all the time doing the
other stuff.
Speaker 1 (14:48):
No, I just think it was too arduous and maybe it was
coming out of multiple systemsand APIs weren't connecting.
Zapier wouldn't do it.
You know, what I mean.
We couldn't get it becausethere wasn't a method.
So, that's what I'm saying.
I think that there's somesignificant opportunities there.
Speaker 2 (15:04):
Yeah, and that, I think, would help us take
everything to the next level.
Right, because now you'reseeing things that you were not
seeing before.
So what does that mean and whatdo you do with that data?
So definitely the AIs could bedoing that, but I still think
people the first thing they'regoing to go for is the
automation of the things they'redoing today, and I think
(15:26):
they're part of the thing thatwe need to figure out is how to
teach people to do criticalthinking.
How can they understand theoutput by asking questions to
the AI to find hey, this numberthat you're putting here, why is
it there?
What is it coming from?
So, trying to understand thosethings, and how do people learn?
(15:49):
Today?
They first have to go throughthat process of being the ones
filling in the forms, filling inthe spreadsheets kind of
understanding where the data isin the PDFs and all those things
.
But are they really thinking?
Not right?
They're just copy pasting andthey're just walking there.
So you start learning once yougive that to someone and that
(16:10):
person turns back and startsscreaming at you because you did
something wrong.
Right now you're all okay, Imessed it up here.
So how do we help young peoplebecome that person that screams
at the AI to know that somethingis wrong Because, yeah, the
data inputting is no longergoing to be done by a human.
So what's the next thing thathumans do today after someone
(16:34):
filled in the spreadsheet?
Speaker 1 (16:35):
Yeah, it's interesting when you say
screaming at the AI, becausethat can be kind of interesting.
It's kind of like, you know,when there's a company that you
have a service with and theyonly have an email address for
you to contact them and they'renot getting back to you.
Yes, it feels like that.
Sometimes you get someone onthe phone and you're like what
the hell?
Like well, I can't get thisthing to do something.
So, yeah, so you when you showup in places and obviously you
(16:58):
know I want to sort of keep thisconfidential, but when you show
up places and people are like,oh shit, the AI guy's here.
Do people think about their jobs?
Do they see the net positive ofmaybe their job being easier,
or do they see it as a threat?
Speaker 2 (17:16):
I think it depends on who we talk with.
If we talk with the peoplewhose tasks the AI will do, they
feel threatened by it, but thenit's a matter of having them
understand.
Is it really you and your jobfilling in spreadsheets, or
you're here for more than that?
So having them understand thatfilling a spreadsheet is not a
(17:39):
high value thing you could bedoing.
So there are more things.
It is not a high value thingyou could be doing, so there are
more things.
But what we've seen changesince two years ago when we
started is then people startedto hear about AI.
They were concerned because allthe things that they were
seeing in the news is thatthings are hallucinating, that
things are stealing your data.
That was everything that was onthe news.
(18:00):
Now, when we talk with people,they're way more interested,
because this thing has beenhappening for three years now.
So more and more of mycompetitors are using it.
More people are talking aboutit.
So I want to know about it.
Maybe not start using it, butat least I want to understand
what this thing is and, if itcan help me, how it can help me.
So it changes and even maybethe people who felt threatened
(18:24):
in the beginning now they'restarting to see.
Well, maybe this is the way inwhich I can differentiate myself
and the job site yeah, thatmakes sense, if I take a tool,
then I can be more productive,more efficient and my boss will
be happier with me yeah, that'scool.
Speaker 1 (18:39):
Yeah, I think what we uh, it's going to be one of
those things where you see the,the sort of larger companies
doing the tech adoption and thensort of moving their way down.
I had a podcast I did inToronto with one of the guys
from Lafarge Concrete Companyand he's like the transformation
guy and he's doing he's makingagents, like you are, for them
(19:03):
internally, and so it's aninteresting path that we're at.
Now.
Let me ask you this At whatpoint is making agents agentable
?
What do you mean by agentable?
Well, at what point agentable?
What do you mean by agentable?
(19:24):
Well, at what point?
I mean so to make in order to.
At what point can you ask anagent to make the agents like
you're talking?
Do you know what I'm saying?
Yes, like, at what point doesthat?
Because we're looking at thatin software in general.
Right, at what point do you getAI to make the software for you
?
Well, it's multifaceted in thatpoint, right, because it's
(19:45):
complicated-ish, but it can geteasier Once one does it.
Once, then you can startspitting this stuff out pretty
easy, right, it's just the onethat's going to be.
So, you know, if I look atSitemax, for instance, I go okay
, well, what AI can just makeour whole platform?
Well, not that easy to do today, but once one person does
(20:06):
something like SightMax, it'sgoing to be easier and way
easier and way easier and wayeasier.
And then suddenly that's thewatershed moment, right?
But yeah, do you think aboutthat in terms of at what point
is the action become?
(20:27):
Does it self-cannibalize itself?
Speaker 2 (20:30):
So, for example, if you look at Zapier right now,
they actually have that featurenow where you describe your
agent and it will try to findwhat's the best way to build it
based on what they have right.
So that's already happening.
But there are two pieces to theagent.
One is what is the agentinteracting with?
(20:51):
So if you don't have thoseintegrations, it doesn't matter
what you ask the agent, it won'tbe able to pull the data or
push the data.
So that's one piece.
The second piece is the prompt,which is what makes the agent
act.
So I think the prompt iseasier-ish to do, as long as the
(21:11):
agent, or this AI, is capableof asking the relevant questions
and asking for the relevantinformation to then be able to
generate its own prompt.
The integration is where itbecomes harder, because someone
might be using a software you'venever heard of and it's going
to ask for that integration.
So today you won't be able todo that.
So I think that's really wherethe challenge is, because there
(21:32):
is no universal API to connectto whatever is out there, so it
won't be something that canintegrate with all your tools
whenever you need it.
Speaker 1 (21:44):
I mean, it's getting, it will get that way, but it's
going to take some time, yeah,but yeah, that's pretty cool,
all right, well, that's prettycool, man, um.
So yeah, well, you did a goodthing at the show here.
That's been awesome, and I lookforward to having more chats
with you.
Maybe this is just the firstone.
I think it might be, yes, um,but but yeah, we wish you luck
with everything and yeah, let'skeep our conversations going.
Speaker 2 (22:07):
Perfect Love, it All right, well, thank you.
Speaker 1 (22:08):
Thank you very much, Bye.
Well, that does it for anotherepisode of the Site Visit.
Thank you for listening.
Be sure to stay connected withus by following our social
accounts on Instagram andYouTube.
You can also sign up for ourmonthly newsletter at
sitemaxsystemscom slash the sitevisit, where you'll get
(22:28):
industry insights, pro tips andeverything you need to know
about the site visit podcast andSitemax, the job site and
construction management tool ofchoice for thousands of
contractors in North America andbeyond.
Sitemax is also the engine thatpowers this podcast.
All right, let's get back tobuilding.
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