Catalyst with Shayle Kann - Can AI revolutionize EPC?
Episode Date: December 11, 2025Big construction projects in the U.S. are notoriously unpredictable, often finishing over budget and behind schedule. Part of the problem is the inherent complexity of these kinds of projects, like da...ta centers and first-of-a-kind plants. But there’s another problem: the companies that actually build these projects — called EPC firms for engineering, procurement, and construction — often lack strong incentives to control costs or deliver on time. That’s the thesis behind Unlimited Industries, a new startup focused on using AI to develop multiple project designs upfront and reduce project risks. So what would it take to actually cut costs and shorten construction timelines? In this episode, Shayle talks to Alex Modon, co-founder and CEO of Unlimited Industries. The company recently announced a $12 million fundraise as it emerged from stealth. Shayle and Alex cover topics like: How EPC incentives and contract structures drive cost overruns Why bespoke projects prevent learning and standardization The role software and AI can play in design and risk reduction EPC Managing risks – including geopolitics, contractor reliability, and supply chains Resources: Catalyst: FOAK tales The Green Blueprint: Shortening the nuclear development cycle from decades to years Catalyst: The cost of nuclear Credits: Hosted by Shayle Kann. Produced and edited by Daniel Woldorff. Original music and engineering by Sean Marquand. Stephen Lacey is our executive editor. Catalyst is brought to you by EnergyHub. EnergyHub helps utilities build next-generation virtual power plants that unlock reliable flexibility at every level of the grid. See how EnergyHub helps unlock the power of flexibility at scale, and deliver more value through cross-DER dispatch with their leading Edge DERMS platform, by visiting energyhub.com. Catalyst is brought to you by Bloom Energy. AI data centers can’t wait years for grid power—and with Bloom Energy’s fuel cells, they don’t have to. Bloom Energy delivers affordable, always-on, ultra-reliable onsite power, built for chipmakers, hyperscalers, and data center leaders looking to power their operations at AI speed. Learn more by visiting BloomEnergy.com.
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Welcome.
All right, so here's a cycle
that I have seen play out
many, many times.
Developer X of Project Y
wants to go build
a big new project.
And somewhere in the development process,
they engage in EPC,
EPC being an engineering procurement
and construction firm.
There are many of them,
many of them are very, very large.
And they're kind of ubiquitous
if you're going to build
a big capital project.
They engage the EPCC,
EPC, and then there's like a fairly painful process from there on, where it's slower than
they want it to be.
They have to go through multiple cycles of iteration.
There's value engineering.
The cost comes in higher than they expect.
And then at the end of the day, there are a bunch of change orders anyway, and there are
cost overruns, there are time overruns.
It's not necessarily the fault of the EPC, right?
Lots of things can happen in the world.
But the process of actually getting big projects constructed is notoriously hard.
And some folks have been wondering whether there is a way to leverage modern technology, AI included, to do it better.
Certainly that is the opinion of Alex Modon, who is our guest today.
Alex is the CEO and co-founder of Unlimited Industries, which is a startup that reasonably unstelfed to basically be a modern EPC.
They are trying to start from scratch to build a company that will do engineering, procurement, and construction with new technology, with a different business model to try to get projects built.
faster, more on budget, potentially cheaper.
It's an interesting question, and it applies to everything from data centers to power generation
projects, battery storage projects, new chemical plants, anything that we might build that's a big
capital project.
So it's relevant to basically everything else that we talk about here.
Anyway, here's Alex.
Alex, welcome.
Hello, thanks for having me.
Thanks for being here.
Let's talk about EPC, engineering procurement construction.
You founded a company based on the premise that it could be done.
better. So I want to start with what's wrong with it today. As you've observed EPCs and how they work,
like fundamentally, what is the problem that you see? Yeah. Well, it might be first contextualizing
like the what is EPC and where's the play in the value chain. So to start this, let's just imagine
we're going to build, I don't know, let's just say a data center project. So if we want to go
build a data center project as an owner of a project or a developer of a project.
The first thing that we do is we kind of find the land and we contract that and we start to figure
out what permits we need. We figure out what power we need to buy. And then, you know,
you typically go find an off-taker or some sort of tenant for that for that actual data center
project or, again, whatever the product is that comes out of the facility. And the last,
like, big contract that you're trying to do is go find the third party that's going to design and
build the thing. EPC, engineering, procurement, construction is basically,
the vertically integrated or all three of the kind of design, manage the supply chain,
actually managed the build of the project, all three of those in one contractor.
And for all intents and purposes, they are the people who design and build a thing, that
EPC piece.
And so I think when I got into it, I was actually really excited the first time we went to
go work with an EPC, thinking that there's going to be all these different kind of disciplines
and institutional knowledge under one shingle.
I think the biggest thing that's challenged with the industry today is that the incentives between the developer,
the person who actually wants to build a thing better, faster, cheaper, or some sort of metric like that,
versus the third party, the incentives are so fundamentally misaligned because of how these contracts get produced.
And so you either have, you know, the vast majority of these contracts have some element of cost plus,
where, you know, we'll say, you know, we'll give some sort of guidance about how much the project is going to cost.
But as a third-party contractor, your incentive is really, we only make money when the project costs more and takes longer.
Or there's sometimes these contracts that run on a fixed firm basis where that third party will actually say, hey, we'll build it for this much.
But they define the contract so tightly that inevitably what happens is when you learn something through the design process or when things change, which inevitably they always do, you get issued these massive change orders.
And at that point, that's where that kind of third-party EPC typically makes all their margin,
just because you're already working together and you can't really easily leave.
So, yeah, high-level what's broken is it's the incentive structure.
The incentives between the third-party, or the actual developer who wants to build better,
faster, cheaper, and the third-party who's in control of making all the decisions about what gets
designed and what actually gets built.
If I'm being charitable to EPCs, and I ask the question of, like, why is it cost-plus,
typically or fixed firm, but where change orders are the norm.
I would imagine, in part, it is because there's the, one, there's this like time lag, right?
Like, they're signing the contract on day one, but they're actually procuring the commodity
materials six months later, a year later, 18 months later, whatever it might be.
Those prices are volatile.
They would have to hedge them every single time if they weren't going to do that.
And not to mention, labor availability, labor costs.
and all this other stuff.
So is it because they just can't wear that kind of a risk,
the time risk?
Or is your experience that there's a different reason
why it ended up being cost plus or fixed firm
with all sorts of change orders?
No, I mean, definitely to Steelman.
It's because it's ultra complex to build these projects.
There is hundreds of people that will be evolved
in how the thing gets designed.
That manages the entire supply chain to get it built
and then manages all the boots on the ground
of the project that's actually.
actually doing the building. So there is tons of complexity. And the reason that these contracts are
structured in this inherently flexible way is because it's really hard to know at front how much
exactly is the thing going to cost. So yeah, it's, I mean, it certainly is like evolved this way
because when you when you think about these projects, and I mean, the small version of these
are like $100 million. The, you know, the more normal version of these is many hundreds of millions.
and then the bigger ones are certainly in the immediate billions of costs.
So because you have all that risk, the contracts effectively are this big risk mitigation strategy.
And the easy way for the EPC not to take any risk is just to say we're going to get a margin on top of what it costs us to build the thing.
But the problem is that there's no motivation then to make the thing cost less.
If anything, there's a motivation the other way to make it cost less.
If anything, there's a motivation the other way to make it cost more.
Yeah, you mentioned there's a lot of people and a lot of uncertainty.
I mean, I guess one way I think about it is that there's a spectrum of different types of projects
on one end of the spectrum is a thing that looks the same every time you build it, more or less.
I mean, maybe a version of this would be, I don't know, utility scale battery projects
or utility scale solar or something like that, where like, you know, we've built hundreds of them.
They generally look the same wherever you go.
and you would imagine that on those types of projects,
it would be pretty well known.
Maybe there's some commodity risk.
Maybe there's some labor risk.
But broadly speaking, the designs are going to be similar,
and the experience is high.
And then on the other end of the spectrum,
there's like a first-of-a-kind thing
that's never been built before.
And there are obviously your error bars
on the cost and the time, the labor, and all that
is going to be highest.
Do you, and then there's a bunch of stuff in between.
I imagine data centers are in between.
actually, because in some ways they look the same.
There's like a powered shell. The shell is a building.
But then inside the data center, right?
Like, there's all sorts of innovation.
Is this one liquid cool?
Is this one using?
Which invidia chips is it using?
How is it designed?
There's so much innovation in that space that it's changing all the time.
Which also changes the facility too, right?
Like, these changes trickle out for sure.
Right.
So I guess as you think about this, like, the incentive structure being misaligned,
do you view it as being more misaligned on the,
I guess, relatively speaking, easier stuff to build
because there you should be able to have high level of certainty
on what the cost should be a priori,
or is it more misaligned on the esoteric stuff
because the error bars are even higher,
and so the risk aversion of the EPC
leads them to, like, way over price, for example.
Yeah, I mean, definitely, definitely it's,
like, the contingencies are,
the egregiousness of this like cost misalignment is certainly true with the more custom the project it gets.
So the first of a kinds are a great example of that.
Or, you know, like you even mentioned, data centers that are shifting in the requirements, of course, have more and more of this baked in.
It's basically just correlated to risk.
Like how much risk is there in this?
Solar has less and less risk as we deploy more and more the exact same way.
Same thing with utility storage.
But I do think that like where you see, so you definitely.
get misaligned contracts or misline incentives, which kind of balloon costs. And that is the kind of
status quo for how you contract these things anyways. But the other thing that kind of falls into this is how
projects broadly are approached. And so if you think about how we build products, like we have a
metric for it, right? We say, hey, we're going to make this widget. It's going to come out of a factory.
We'll have some sort of cost per widget metric. And that allows us to kind of approach these projects
with this continuous improvement type approach
and drive costs down.
That's like our learning rate, I think arguably,
that's why solar has fallen so aggressively
is because we keep kind of making,
or at least I should say, the module costs,
which is even different than this is maybe a side tangent,
but it's like different than the actual installed costs.
Well, it's actually the problem with solar
is that the module costs have fallen much faster
than the installed costs have, right?
Like we haven't solved it on the construction
and all the other commodity materials and stuff.
Yeah, and that's because all progress
happens with this, like, you know, highly iterative process and this like continue improvement
process that we get out of manufacturing a thing. But when we move into projects world, everything's a
snowflake. It's like, you know, everything's end of one. Even a project that we're building,
you know, we built a lot of refineries. That next refinery we build is still an end of one project.
And because it's approached in that way, you don't really get any sort of benefits of learning
through that process. And, you know, by definition, each project's going to be unique. It's a different
piece of land. But yeah, and again, maybe this is a tangent, but that's like another big problem
in the industry is everything's done from scratch. So even if you're going to go design a new,
you know, a slightly different data center or a solar project or something else to that sort,
every tweak or change that you make effectively reintroduces the entire redesign of the process.
And so, yes, there's some stuff that gets lifted, but the overall amount of
work that happens is not the kind of delta of the change.
It is like a significant rehaul of work.
And it just keeps us from like learning and iterating to improve how something gets designed,
not just in terms of saving the engineering costs,
which is actually a pretty small piece of the cost anyways,
but actually like kind of having a better design that improves the overall cost
or performance of the facility.
I guess one thing I wonder is, okay, so let's take EPC, right?
like engineering, procurement, and construction,
just taking it at the simplest base layer
of what the work entails.
Let's just say you could dramatically improve,
because what you're describing is like
the learning, I think, I guess maybe is on all three,
but predominantly on like engineering.
Can you design this thing
so that it's fast and easy to design
and is definitely going to work up front?
My guess is that in most of these big capital projects,
the E out of EPC,
is the smallest slice of the pie
in terms of total cost. And like the bulk of the cost probably comes from a combination of
procurement, the actual physical materials, much of which are going to be like steel and cement and
aluminum and, you know, commodities that have prices that vary. And then construction, which is
sort of a function. It's an outcropping of how the engineering occurs, but certainly is also just
driven by construction process and labor and so on. So as you think about like, where is there an
opportunity to deliver cost reduction and also cost certainty, like how much of it is the E versus the P versus the C?
Yeah, totally.
Okay.
So those are two separate things, right?
Like, so let's say cost certainty versus like an overall reduction cost.
On the certainty side, everything, it's really kind of planned out or teased out in the engineering portion, right?
And so generally, again, life cycle of these projects are, you know, you start with some conceptual design.
you understand maybe plus or minus 50% how much the thing's going to cost.
Then for the most part, you dig into this front-in engineering design,
and you will get to totally changes per project,
but say you get to plus or minus 10% a cost.
And that gives you enough confidence to go to a lender,
an actual bank and say, hey, let's underwrite this project.
We think you're going to get the IRA you need, and then we move forward.
But in the vast majority of projects,
when you go to final investment decision and you have plus or minus 10% estimates,
you're only maybe 30% of the way through your engineering.
70% you still have to go do.
And it doesn't make sense to do it up front
because it takes a lot of time
and it costs a lot of money
and it's a lot easier to finance that
with the actual lender's money
rather than the development capital.
So the certainty that you have
going into a project
before you actually take the money from the bank
to go build it is actually pretty low.
There's so much more work to go do.
And you just don't do it
because there's a high marginal cost of the engineering.
So one way that you really
reduce all the risk,
if you will, or all this uncertainty
from how the project's going to work
is if you could instead just take these projects
further through the design process
so that by the time
you're doing your earthworks
or you're moving some sort of ground, you're actually
100% done. You have your issued for construction package,
which doesn't happen today.
And so there's that big piece on
how do you remove uncertainty?
How you remove costs?
I mean, yeah, you're totally right. The engineering cost
is anywhere from like
three to 10% or 15%.
percent of the project cost, so it's not a huge lever in itself. But if you think about the way
these projects are designed today, because, again, such a high marginal cost to engineering,
what you end up doing is you only really design something one pass through. There's no sort of
iteration. There's no optimization of design. And that leads you to a spot where you kind of
make early decisions, you freeze those design decisions, you kind of do the next stage gate of
your design process, and you eventually get stuck in these very low local optimums.
rather than ever understanding what the global optimum of that design processes.
So, yeah, I mean, I can get more into how we approach this problem,
but there's huge gains and opportunities to use the E to rapidly reduce the P and the C.
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Okay, let's talk about how to use technology,
which is, I think, what you're alluding to here, right?
Like, this is an area where my suspicion is,
generally it's not the first category of AI adoption,
or at least it hasn't been historically.
Where do you see the biggest opportunity?
Like, where are the step-function improvements
that one can achieve by leveraging modern technology,
be it AI or something else?
Yeah. So we have built a lot of technology to help accelerate that pre-construction phase. So this is basically the E and lots of the procurement management side of things. And we have a software and kind of like an AI-native version of this that helps accelerate the chemical design, mechanical, electrical, civil, structural controls. And in doing that, we basically are building a platform that allows us to remove that risk, but at a very, very low marginal cost.
So that helps you accelerate through the design process, not just saving time, but exploring a much wider search base and getting to much greater levels of definition before you actually have to freeze designs.
And that has a big impact to the previous point, right?
It's just like removing uncertainty, you know, reducing costs from through optimization.
Can you go level deeper on that?
Like, what does that actually mean to reduce uncertainty using software?
like, what are you actually doing?
Yeah.
It's just, you know, if you start a project today at like zero, you know, it's like completely uncertain, right?
And as you start specifying or defining the bringing definition to that project, which is the process of engineering it, you start to see more, you start to remove risk, right?
You say, hey, you know, we can actually size a pump that will solve that, you know, moving a fluid from point A to point B.
Or, you know, actually, we can design a tank.
like this to hold this amount of volume.
And once you start providing that level of definition,
you remove a lot of the kind of ambiguity,
but there's still tons and tons that goes into the thousands of documents
that you'll kind of generate to design a plant fully.
So this is what we kind of have built.
Like it is a platform that our engineers use.
I think the important distinction here is this is not like a software technology that we sell.
It's like we use this as an internal tool ourselves.
So our engineers,
have this kind of AI platform that has all of their data in one place,
all the kind of requirements about the project,
all of the potential vendors that could be used.
And they use it to basically accelerate that design process really significantly.
We haven't like redefined how you're engineering these projects.
We've kind of augmented it, like significantly augmented the people that are doing that work.
So that they're able to just, with the same amount of time and capital,
they're able to define way more and provide way more kind of engineering definition,
as well as time to optimize those designs
so you can remove
kind of suboptimal design.
Can you articulate a little bit
what is distinct about this from
the, you know, that EPCs have been
using engineering software
that is super mature
for a long time.
Maybe that's the problem.
But like, what's distinct about
what you just described from
what you could just get off the shelf
to design a project?
Most of the software in this industry
really hasn't changed much
in the last, like, maybe 20 years.
And I again, kind of always come back to the incentive structure.
There's no real incentive structure for an EPC to want better software.
It's the same reason your law firm doesn't necessarily want like AI software to help them accelerate, you know, and reduce their billables.
So the way these softwares work now is that there is a bunch of kind of distributed software solutions or maybe decentralized solutions.
So you'll have a CAD tool that you use to actually like do the designs.
You'll do almost all of your kind of rough engineering or hand calcs in Excel.
you'll use dedicated simulation software for some sort of fluid design or structural analysis or whatever that might be.
And then you use another tool to like review those PDFs, you know, with a tool to put red lines on them and go through design cycles and then push to drafters and then other tools to manage, you know, how do you reach out to your vendors.
And anyways, there's all these different solutions that, software solutions that you're using in order to like kind of quote unquote, like do engineering.
And what we built kind of from day one was just a modern version of this software.
So we put all those different disparate tools into one underlying platform,
and we gave modern software to them,
which is like automatically doing version control and collaboration
and everything that you would expect out of just like a modern tool.
And what that allows us to do is not just kind of have much more streamlined workflows,
but it allows us to kind of build AI in as a core primitive to a solution.
So now sometimes our engineers will do some sort of work manually within one of our softwares,
but often they will dedicate a, or they kind of delegate a task to an AI that knows how to use all those tools in our software
so that it can do that design task and then surface that back to the engineer who delegated it.
So it's, at least in significant part, it's like integration of a bunch of what otherwise are kind of disparate workflows
to allow for faster iteration and more automated iteration.
You do a change somewhere in one piece of software right now.
You'd have to go to another piece of software, like make the change in that software,
see how it changes the other thing, do that over and over again.
So it's like building everything into a single comprehensive suite, basically.
Yeah, totally.
There's like one underlying data model.
There's not, you know, the same piece of data that shows up in 10 different softwares.
And that's really helpful, not just, again, for streamlining your own workflows,
but it's so that an AI can do it.
And it doesn't have to like manage all these different tools and interfaces that, you know,
the same information is repeat.
but out of date and or edited by the wrong person who didn't have permission or something
that was right.
When you say AI in this context, what do you mean?
Like, is it LLM type AI where you're like, I want to be able to, in my single pane of glass,
be able to ask, you know, like, what would happen if I changed all the screws in this entire
project from X to Y or something like that?
Like, is it LLM AI?
Is it, what is the AI?
Yeah.
Because there's also a version of what you're describing that's like, at a problem.
software for sure, but doesn't just
and like there's a big data
component to it, but it's not inherently AI.
Yeah, no, it's like an exact use case,
the one that you gave that, you know,
you would do. So we'll like record all our
meetings. And that meeting
you're having with a handful of different disciplines
of engineers or people understand the commercial
of the agreement and what that'll
trigger through that recording is like a bunch
of tasks for AIs to go do. And it's
you just basically mentioned a trade
there, right? It's like, what if we had, I don't
know, one type of material over another
type of material, one type of conveyance over another type of conveyance for this project of this material.
RIA will go explore that different design path. And that's a trade that you would give to an engineer.
And you'd say, hey, go spend a week, like assess the tradeoff between using, you know, belt conveyance or
pneumatic conveyance for some sort of material handling problem. And then tell me back what do we feel like
is the right kind of total cost of ownership trade. And it'll just explore that. And so that's an LLM
who's doing a lot of that work. And importantly, you're not just kind of asking a chat GPT or something
in a sort to go explore that.
that and produce something, which it'll do.
And honestly, it'll do in a pretty impressive way.
But the way that we've built it is that it's grounded both inside of the data for the project,
because it has all that in one place, and then inside of the tools that we've fed it.
So it knows how to use a, you know, how to downselect actual vendors or how to read spec
sheets that we fed it or how to use simulation software that we fed it in order to derive these
answers.
You mentioned data centers, and I think you guys put that in as one of the categories you're most interested in in your announcement when you guys unveiled.
Is that because we're building a lot of data centers?
Or is that because there's something specific to data centers, data center construction and engineering that makes it especially attractive here?
Or is there something else that you would describe as like the perfect prototypical use case for this in the early days is X?
So these projects have a handful of different reasons of why you would apply this technology.
In the data center use case specifically, speed is really an important lever for them.
And so you can take, instead of the design portion taking, call it six to nine months of your critical path, we can massively collapse that period of time.
And that's really important for these data center projects to kind of accelerate how quickly we can actually build them.
The same piece, though, with the fact that, you know, if you right now budget six to nine months for your design portion, almost none of that, you're going to start to figure out, well, how do we optimize that design or do some sort of value engineering to save costs or to design for long lead items or to design for constructability.
So really strong value prop in these data center projects.
As we end up kind of increasing the capacity that we have on our team, though, it'll make sense to pick up a big.
basically many of these types of large industrial projects,
of which we've already pushed the kind of technology to be able to demonstrate,
and it will end up being really applicable across all types of construction.
So if you can deliver more certainty up front,
then that presumably is the thing that unlocks a different kind of business model
that hopefully solves the incentive problem.
Is that just a fixed price contract with no change orders allowed, or what does that look like?
That's exactly it. We literally put like no change orders in our contracts.
So you wear the risk. Like you wear all the risk, basically. If there's a cost overrun, you're going to go negative on the project. And the premise here is that because EPCs notoriously don't have huge margins, right? Construction firms are like high volume, low margin type businesses. And so I guess the thinking on your side has got to be because we're reducing the cost of everything along the way, we naturally have higher margins.
which would allow us a little bit of a buffer
if things do become a little more expensive than we expected,
at least we're not like in the red.
Do I have that concept right?
Yeah, I mean, we definitely will have a different margin profile
than the industry, but it's not that
because even when you think about it,
the engineering margin, it's pretty small
because the spend of the engineering is actually really small
relative to the larger construction scope of the project.
The important part of what allows us to absorb that risk
without the kind of risk that we go into the red,
or at least in a risk-adjusted way,
is because we've been able to do so much design up front.
And we've been able to not only kind of like remove all that extra risk
by taking the definition instead of doing that at 30%,
we can take that definition all the way through 100%.
You just remove all this ambiguity of how much the thing should actually cost.
So when you, again, traditionally,
when someone gives a contract to go build a project,
because they have such little core definition.
They don't know all the vendors that they're going to buy from.
You even mentioned, I think, this example earlier of, like, there's like a tariff risk.
By the time that you fund the project and you commit to a cost, tariff can change.
In the, you know, six more months you need to finish the design in order to order the parts.
That doesn't exist in our world because we've been able to just very, very quickly remove all this risk
before we actually commit to a price.
That's very unique.
Wait, how does that work?
So that's a very, it's a good specific example.
So I guess what you would do is issue the purchase order for all of the material before you commit to a price to the customer.
Like how do you avoid the tariff?
Yeah, exactly. It's timing it all out.
So when, just to compare this again to how it works today is you'd only, when you, when you say, hey, we're the EPC, we're going to give you a performance guarantee or some sort of fixed firm price when you go to buy this or fund this project.
with like a notice to proceed or final investment decision. At that point, you just, you literally
don't even know all your balks. Like so you're all your commodity equipment, you're the steel that
you need, the wire that you need, etc. We will know all of that at this point in time because
we're not 30% definition. We're 100% engineering definition. And because we have this entire
equipment list at this point in time, we know either how to say, hey, let's purchase everything at the same
day that the project gets funded. Let's go either purchase everything or let's design hedges from a
cost perspective so that we're not exposed to some sort of volatility or risk.
That's complex, right?
I'm thinking of these big construction projects, right?
And you're either on the day that you sign the contract, you're either buying all of the
steel, just as a random, specific example, or you're hedging steel prices at the project-by-project
level to make sure that you don't overpay for steel.
That's kind of what you need to do.
Yeah.
That's what allows you to truly, like, have kind of a very different,
risk assessment for how these projects get built.
And that what gives you an ability to do a fixed firm and actually mean it,
most of these fixed firms aren't really like industry themselves.
I mean, we've seen time and time again where it's like a fixed firm doesn't really mean
a fixed firm because there's inevitably some way that in the thousand page contract that
you assigned with your EPC, you went out of scope and invalidated that price.
Hence the kind of change order trickery.
You see, the other thing that I wonder how you manage is subcontractors, right?
It's another area where change orders come from not just the general contractor or the PC
having to make a change order, but also because some subcontractor made a change order.
So do you have to flow this all?
First of all, are you going to use subcontractors?
You're just going to do everything in house and have a ton of people on staff.
And if you are going to use subcontractors, do you have to then flow this change in a structure
down through all of them where they can't issue any change orders to you either?
Yeah.
Certainly long term, we will do everything in house.
we will vertically integrate as much as possible,
because that's where you can fix the incentives all the way through.
Yes, for these initial projects as we take,
we are working friendly with, like, the local GC or even the trades,
even the actual folks that we will subcontract a lot of this work out to.
For that, it is making sure that we prior to entering into a contract.
You have the kind of the same thing where often those contracts are not as,
the level of definition that you have when you're,
you're asking someone to actually give you a fixed price on what a scope of work is,
is very hard. We don't have that same problem because we take things way deeper through
definition. We have a much better understanding of what should this actually cost to go build.
So, yeah, there's a handful of different ways that we kind of approach working with the actual
subcontractors as we do this to hit our performance goals. But it is this kind of like a
continuing loop of how do you remove more and more risk through design.
All right, so I wrap it up.
You don't have to give me exact numbers,
but when should we expect to see the first COD?
When should we expect to see the first project constructed by you guys?
I love it.
Yeah, we'll hopefully see you next year.
So hopefully by the end up next year.
Fast is the rule.
Alex, thank you so much for the time.
Really appreciate it.
I appreciate it.
Thanks, Joe.
Alex Modon is the CEO and co-founder of Unlimited Industries.
This show is a production of Latitude Media.
You can head over to Latitude Media.com for links to today's topics.
Latitude is supported by Prelude Ventures.
This episode was produced by Daniel Waldorf, mixing and theme song by Sean Marquand.
Stephen Lacey is our executive editor.
I'm Shale Khan, and this is Catalyst.
