Alright, welcome. Welcome back to another episode of the First Principles
podcast. Today we're joined by Garrett. Garrett is the
CEO of PipeDream. Why don't you tell us about what PipeDream
Yeah, so PipeDream is the easiest, fastest, and
highest volume way to move things from one spot to another. So
whether that's underground or through buildings or whatever
it is like it's really easy to move from one spot to
another spot to another spot to another spot so kind of like a train so if you thought you
think about like a really small subway for things that's
Heck yeah so it's like the simple like the way to get people's minds
around why it's useful is basically like there are tons of
things that you want to move from place to place you want to move groceries from
the grocery store into your house you want to move package from
the reception desk up to your office. I think people
don't really think about that a lot, don't think about that logistics stuff and how
things actually move around in the world, but actually this just
occurred to me. I just remembered that one of the biggest things that helped skyscrapers
come to be, skyscrapers really couldn't have existed either before the
elevator, which everybody knows, or the phone. It was really hard to
move literal messages up and down a large distance.
So, until they figured out the logistics of moving a message up and down,
they couldn't build skyscrapers. So, I don't know. Oh, that's so cool. I didn't know
that. What's the next type of logistics? What else is it
going to bring about? Why don't you talk a little bit about
why this is helpful? What sorts of things people want to move around and where you're
Um, so Pipe Tree was really born out of, you know, we were looking for something that had 10 years
of innovation to go in it, something that, Jeff Bezos has this
great quote, uh, my quote is not as good, but
essentially like, you gotta know where the puck is going. Um, in like AI,
you could have been working on the old AI paradigm for
like, five, 10 years, and all of a sudden Transformers comes
out, and you're at the same starting place everyone else is, you're zagging
with everybody else. And so we wanted to find something that had 10 years
of innovation left in it, meaningfully changed
everyone's lives, and was really easy to know where the
puck is going. Logistics is easy, we just need to move more
stuff around faster for less money. And that is
always true. It's always gonna be that. So
we really just had this frustration with how
long it was taking for autonomous logistics to scale. And
so just dug into it and realized that There
are a few reasons, but one of the main reasons was
how hard it was to get something in and out of the building. If
you think about humans delivering things, it is
expensive to deliver things for a variety of reasons. Main one
being that for last mile delivery, we're usually using this
giant car to deliver this super small package, but also
because the world is super complicated. And where you
are, in what building, and then if you're in an apartment, if you're in a house, trying
to figure out, okay, where do I actually put this thing for this person is
super hard. Same thing with going from warehouse out
into the world. That's super complicated. And
then going longer distances, having to wait for batched
payloads to fill up an 18-wheeler or
fill up a delivery truck. Everything is really locked
by having to have a human be
part of that. And autonomous logistics is
just, the amount it's going to change the way that we live our
lives is drastic. And we're so close,
like drones are there. Sidewalk robots are there. Self-driving
cars are there. We're so close. We're just like, okay, what is it
gonna take? What is gonna be needed to take it across the finish line? And
that is the thing that we should be building. And then we can get into
it. Our goal is to make autonomous logistics happen
as fast as possible and then make this next state of logistics
happen right after that. But that was ultimately why
So what, how much of this was informed by like the crazy stuff that's happening in,
you know, factory automation? Like if you look at, or maybe even just
warehouse automation, like if you look at Amazon, there's not, they're not picking
and packing with people anymore. Like they're, I'm sure that that's all like
robots and you see those cool like vertical moving robots that go
get something off the shelf or whatever. Like, so how much of what you guys were
doing was informed by that versus by, you know,
Yeah. I mean, we really had to come at it from
the other way. I think if you look at, especially in robotics, if
you try to use too much of something to inform how
to build an automated system, then you don't realize just
how much minutiae and nuance is put into
that robot. Like the Kiva system that Amazon uses, it's
So sick. And you look at it and you're like, oh, so simple. It's
such a good idea. You have this thing that lifts a shelf and it carries that
shelf over to somewhere else and it drops it and then they can, you know, kind of like
drive around underneath. It's such a simple concept, but there's
so much that goes into that. Like those floors have to be so
level that if they're coming to retrofit a warehouse, that floor
they already know isn't level enough. And to get that floor level enough
takes like, it's this huge engineering effort to make it like smooth and
level enough for the Kiva robots to run. So
you push these robots really simple, but you add a little complexity in
the building process and making sure that you've reduced variables in
the work environment. So usually like,
and Canon are my CTOs, so
good at this. He's so good at this. It's just, you need
to look at the problem set, and you need to look at the variables
that go into it, and you need to look at, okay, what can we control? What can we not control? What
are the most important things to optimize for? And then
you build the simplest robot that meets all
those requirements. And that is the best way, like, if you didn't introduce
any other Like trying
to make this thing like that thing or this thing like that thing, then you've
introduced bias into the creation process. So it's really a
from first principles approach, which is ultimately how we
got to Pipestream in general. We
didn't ever start the company and be like, hey, we should do underground delivery. That would
be... We
came at it from first principles and said, what is the best thing to
build? And then after a series of
Yeah. So what were those kind of constraints? What were the
Yeah, so it was really what we told ourselves is
we want to make autonomous delivery work in every city as
fast as possible. That's number one. So we want to do
that. And then number two is we want to make this next stable
logistics we called hyper logistics happen as soon as possible after that.
So when we do our monthly meeting, monthly meeting starts with saying, you
know, we want to make hyper logistics possible by 2030. That is our number
one goal outside of any tech or anything that we
build trying to get to there. So
hyper-logistics, just really quick, is the ability to
get something delivered in under 10 minutes for
less than a quarter, and just as easily as you can receive that
object, you can send it back. So bi-directional, up-down,
ability to get something delivered and really easily send it back. So
we're looking at that problem set and just started talking to cities and
companies in the space, just different stakeholders.
Originally thought drones. I'm gotta be
the biggest drone fan in the world. I
love drones, always been obsessed with them, done several
drone projects. So kind of like went in with that bias. And
then after talking to people, realized that there was this missing space that
no one was building in, that
if we went and built it, that was going to be the multiplier that
would allow autonomous logistics to scale throughout cities. So
ultimately it was that, plus we saw it as this
really, really, really important piece to making Hyperlogistics happen
by 2030. And without it, we would be so far behind in making
that happen. So for us, it was that
spot in that we knew no one was
building in right now. It was so big that we knew if we got
three competitors, we probably should be friends with them because it would take all
of us to actually make it actually happen. And
What were the reasons, were there like physics reasons or
I mean, drones are a super important part of the autonomous
delivery. I mean, they're gonna be, I think they're gonna be the lion's share
of deliveries are gonna be done by drones. They're like perfect. There's
so much space up there. There's just so much.
They're quick. I think people overestimate how
much noise there is. I mean, cars
make a ton of noise, and we ultimately just kind of like, let
that one go. The safety protocols are
great. If you look at, I mean, that's ultimately what
is taking the longest on them, is making sure everything's safe. But
like, the FAA does a great job of making sure That things
are crazy. I mean, Boeing is, I mean,
they've lost a door, they've been on fire, and
there's been no deaths. It's because they just have an insane amount of safety protocols. They
can handle these crazy events happening and everyone
is safe, which is wild. But they're
gonna be a huge part. It is just a really tough space to be
in. It's one of those things that when
you get to a service that is that cheap, it
really starts to be a commodity unless
you have something crazy unique that
you're providing. So if you think about like the internet
of goods, At times,
vehicles, as they get more and more efficient, ultimately
just become a bit. And it's kind of, you know, whatever is carrying
that bit doesn't really matter. It's going to be sufficiently fast and
sufficiently good. You've got to really, really have an
edge to really compete. I
think that when we were looking at it, it was like, well, we were getting such a late start. It
just didn't see us catching up with anyone else. It's
also, like, and then we were looking at it, and
there are so many other problems that aren't drone-related that
we're gonna take, it was like, a ton of people are working in the drone space.
Not a lot of people are working on the rest of
Is the problem so big that you'll just have to have as
many possible solutions working on it as possible? Or
do you feel like there's a specific niche that you guys can do that maybe drones
Yeah, I think it's both. If you look at global
logistics, there's just so many different things to
deliver, and there's so many different geographies that it needs to be delivered for. There's
so many different climate and weather conditions and entry and exit points.
It's just a really complicated space. I mean, like, sidewalk
robots have a spot in that. Self-driving cars have a spot in that. Drones.
Underground, I think, has a spot in that. And then there's probably like two or three other modalities
that just we haven't even heard of yet. They're going to be super important to
doing that. I think when you
look at our space, it's what we really focus on is how
do you move around a building really well.
So if you kind of think of like plumbing doesn't
end at a building, you have the main line and
then you have the auxiliary lines and then you have It's ultimately got
to get to the sink, right? You need that point of delivery and then you need
a really efficient way, you know, horrible example here, but
like if I'm using a toilet, you think a toilet is like a really efficient
poop delivery method, right? It's delivering it away from you to a
Yeah, yeah. But like you need,
your poop start originates in like one point at
a toilet, and then it needs to make it to the main line. It's got to make it efficiently, and
then it's got to like be able to go on the main line all the way to the processing
Where does poop go? Answering the big questions on the first
I'm this close to flushing a GoPro. We're going to crack
this wide open. But yeah,
that and then same thing with warehouse. If you think about, okay, you
have right now 10,000 deliveries that
need to go out this hour. Being able to get all those
deliveries into the vehicle that needs to take
them to where they need to go is about half of the time it
takes to actually get that thing to the end user. So
it's a huge coordination problem. And then same thing
on the other side. Accepting a delivery in an apartment building,
getting it to the end user, going from warehouse
to in a city, moving around
district. I think there's a lot of different
problems and I don't think right now We know
how big each of those is going to be in what places. We
know there will be problems. And so our goal is to take the
ones that are going to
be the biggest problems, focus on those, and then let
Sweet. All right, let's hop into the product. Let's talk about
what you're actually building, like how you're building it and what led you there. So do
you want to lead us through the idea maze a little bit of like, you know, how you
started, how you got, how you kind of like got closer to a prototype
or like a point design, really, and then moved on to a prototype, like
Yeah, so once we kind of landed on that idea space,
there were a few truths we needed to come up
with. So the number one one was for
any type of utility like infrastructure to work, it's
got to be as cheap as possible per linear foot to install. So
whether you're whether it's Greenfield or otherwise, like The
only utilities that actually scaled were
the ones that you were able to retrofit into existing
locations. So it had to be able to be retrofitted.
It had to be cheap. And
the way to think about it is like, yeah, how much does it cost per linear foot
to install? So it had to be as cheap as possible to put in per linear foot. It needed
to be able to be serviced without being reinstalled.
So anything you put in the ground or you put into a building that
is locked, you need to be able to fix it without going
down there and fixing it. A good example would be plumbing. I think plumbing is
a great example. When you put plumbing in the walls, it's not
very often that you're actually having to tear up the floor of your
house and tear out the walls to fix
the pipes. There's so many ways to
fix pipes, whether you're using a rotoscope, Great
way to unclog them. If they break, they break in a way
that you just have to open up one little thing and put them back together. There's like
a whole, whole industries have been created to like make plumbing be
super simple and super cheap to put in and then make sure that it
lasts a long time. So we had to mirror that.
And three, a lot of this is really complex. The way you would
put this in to, you know, going
30 miles across the city versus the
way that you would put this in an apartment building, the way you put this into a
retail space. are going to be super different. And
so we needed the simplest way to be
able to work in all those different environments. And so the way that we looked
at doing it was reducing the core actions to
individual components that could all work on their own and didn't need
to be tied together. So the
idea made there was a lot. We tried to make
it too simple, and then we added complexity back in, made it
a little too complex. We kind of ended up in this middle ground. Originally,
we were gonna use the pipe walls as the
rigid body, and so the wheels were pushing out
on the wall. This was like super, super early on,
which is like a great idea, and it's out there. I don't know
It's like right. Dude, no, it's blurry. Go get it. Is it like a little drone
that has the wall, like on the walls or whatever? Like is it? Yeah, yeah. Is it like a triangle? Hold
Hell yeah. All right, this is what's left of it. The engineering team
loves taking parts out of it, and I think it's because they hated existing.
But this is like the very first one, maybe
a couple in. There's three wheels
or two wheels? It's three, we lost the top
wheel. That was one of the things that got cannibalized. But
yeah, so it would flex in and then each
one was loaded so that it would keep itself in the center. But
trying to do that, it caused, it was so cool
how we made it work. way too complex. The
package, because the body of
the robot was so close to the wall of
the pipe, then the package had to be pooped out. So there's
a whole mechanism to poop it out and handle it
after that. But yeah,
it was not the right answer. And so that's when we introduced a rail.
So instead of using the walls as that modular, or
the rigid body, then you just have the rail as a rigid body. So
the robot doesn't actually touch the pipe, which is great for
a few reasons, but it means that the amount
of variables you're dealing with are really
reduced. You just have the robot on the rail. The
open cavity that it's using doesn't matter. So this
is great. It means that the robot that works for underground works the
same way in the utility space, in buildings,
in the attic of buildings, on
the roof. All of it works the same way and you can fit the
enclosure to fit the environment. So
that is a great example of Caden
and the team doing a good job making things more simple. So
we have the robot that handles horizontal movement, it handles
all the fast movement, and it is fully autonomous
and does all its own wayfinding, navigation, and
then it's just riding the rail. And then what
we call the portal, handles vertical movement and
also handles storage and deployment
into the robots. So it picks
stuff up in the robots. We have them in here. So
everything works with the Tout. It picks up the Tout. and
stores it and then either deploys it to the end
Is that the actual size of it? Yeah. Nice. That's big. It's
like a huge
shopping thing that you pick up at a grocery store. It'd be like a huge one
Like a double size. That's exactly what it is. It's a standardized tote. Yeah,
Cannon knows so much about totes now. He's got to have
every single tote that exists. Wow. They call them totes.
It's a huge industry. It's massive. I think he could look at any tote and
rip off the serial number. He just got
really into totes. So we
didn't mean to, but ultimately
what we ended up making was really similar to a port
where you have a modular piece that
handles stacking, it's able to be grasped really
easily, manipulated really easily, that's the
shipping container for it, it's the tote. And then you have the thing that's
handling vertical movement and storage, That's
the cranes, they grab them off the ships and then they put them in stacks
and then they deploy the stacks on the trains or 18 wheelers. And
then you have the world's arm movement with those trains or 18 wheelers. And
so it's like, did it mean to? But
we just kept, Canon team just kept taking complexity out, taking complexity out,
making it more reliable, making it cheaper. And ultimately, that's
where we got. And it's just like, it's kind of funny that it
mirrors global logistics. Yeah, seriously. Maybe part
of me is always worried that there's some inherent bias
there. Yeah, but we
have gut checked that one about as much as humanly possible.
Heck yeah. Well, I'm curious to learn more about the tubes, randomly
enough. If you are
going to lay a new tube in a new development or a new store
or something, if you're going underground, how do you do that? Do
you just trench and then drop? Do you tunnel
Yeah, I mean, if it's a new build, it's super easy. You either
trench, or when other utilities are being put in, it's already
exposed, and you just go drop the pipe in. That's super
easy. And then, if you are
doing, the retrofit is where all the complexity comes in, but it's also where
90% of the value is. Sure. So, if
we're doing a parking lot install into
a building, then you would do a cut and cover. So
it's like a super standardized method for putting
pipes in, where you cut the asphalt or concrete, you pull
the blocks up that you cut, you excavate
the ground, pop your pipes in, you put the soil back
on, and then you either put the blocks that you took off back on, or you do
an asphalt patch, which is just put asphalt back over it.
It could be as quick as a two-day process, But
doing trenching or cutting covers are super easy. Once
you know where the utilities are and then you have the space to do
it, they're pretty quick and painless. Where it
gets more complicated is going underneath roads or
underneath other infrastructure, and that's where you do a horizontal
directional drill, which is, and I
think this is where sometimes people think about putting underground infrastructure as being a
lot harder, Because you only see it when it interrupts
your life. And you don't see how much is put in around
you that's not interrupting your life. So
Don't think about a dancing bear? What's that?
Oh, so, uh, it may not be a bite. Maybe it's called something else. Uh,
this is where staying up of material last night is killing
me. But, um, there's these videos you can find online where,
There's like the gorilla that walks across and it's like, okay. Yeah,
Yeah, yeah, yeah, yeah. So when that dancing bear's in
front of the thing you're watching, you're like, oh, this dancing bear's in my way. But
then when it's not interrupting your life, you just don't even see it. But once
you know what those machines look like, like I probably
crossed two or three of them away in the office this morning. They
happen all over the place. They are a
little more costly and complicated to
work, but they're still pretty simple, a lot simpler
than people think. So the horizontal directional drill goes
in like this, so it's kind of like, if you've ever seen a video of a
non-invasive surgery, where you come in at an angle, and
then you go down, and then you come back up. So
it does that in a small bore, and then
you grab either the pipe or you grab a bigger drill head, and
you go back through the path you already made. So
once you have that big enough, then ultimately you grab the pipe and pull the
pipe through. So you can do that as long as
a mile. More expensive
than trenching, but it's still pretty easy and still doesn't, I think people have
this idea of when you put it in a ground structure, you have to like, tear
up the roads and it stops traffic in Europe, but the
underground infrastructure industry has been away from that for a
long time. Every once in a while, you have to actually excavate
the ground. For the most part, you're staying off the roads in
the median. So
that's how you would get all the way up in there. And then in
buildings, we try to stay in
the air conditioning space. So wherever you put your air
conditioning layer, use that same infrastructure. So like if
you're in like a Walmart and you look up and you see
these big like stainless steel, like
they look like square tubes. And then they're put into the ceiling through
this common protocol called thread-all. So you put the thread-all and
it screws into the roof. We just do the same thing. So
if you thread-all into the roof and then you have the stainless
What I'm envisioning is basically just like, you know, in every action
movie, there's a scene where like the protagonist is like crawling through an air vent.
I'm just, I'm imagining that's your robots, except they're like delivering packages.
Yeah. That's actually, man, I'm stealing that. Yeah. That's a perfect example. So.
Yeah, how it works is that robot scrawls through the space and
then ultimately the container drops down
Very cool. So how did you choose the
bore of, is it called the bore or whatever, the diameter of the
Yeah, I think the balance we try to find is we
think there needs to be a common protocol. That
way, no matter where you're at, if you're going into
like, imagine you're putting this into an
apartment building that's gonna be there for like 20 years. You're
defining the amount of things that can go in, right? So it
needs to be big enough that it's capturing this big standard deviation so
that you're never like, I'm trying to think of an analogy, you're never like
putting in coaxial and then ultimately you
gotta put fiber in. So you want to make sure that it's big enough
to handle the stuff that people want to have delivered in
the future. But you don't want to go too big, because you can start to
chase that tail, the long tail of
all the objects and all the different orientations and the sizes and the everything.
And ultimately you get to something that's too big to actually put into cities
and put into buildings. So, you know, we've, 18 inches
is pretty much there. It's,
there's like a few sizes that cities are used to putting in there, the standardized sizes.
So you have 12, 16, 18, 24. Ultimately we landed on 24. Just
there were too many grocery and other items
and other like standardized ways
things are done in logistics that being
at 24 just allowed us to kind of like slip into those. And
it means that we can come down in the future so we can go back down to 18. 18 is
where it's most efficient for the future. At 18, you've
captured 99.2% of all Amazon SKUs by
volume, by the amount of things that people are
ordering per day. So I think it's the most efficient long term.
But I think to fit into today's world,
24, is what gets you enough to fit
Okay, let's talk about the drone and the track. So
I think one thing that people might
be wondering is, okay, what do people know
of like a tube that delivers you stuff? Oh, it's the thing at the
bank, you know, that you put in the thing, and then you close the door, and
it like pneumatic tubes, like poof, and like goes up and delivers to the person
on the other side. I'm sure maybe you thought
about pneumatic or maybe you just immediately dismissed it, but why not? Why
Yeah, we never thought about it. We didn't think about it until much,
like, embarrassingly later. It
was because we were coming at this from first principles, and we probably thought about it
as like a check down at some point, but
it just didn't fit that really tight, set
of rules that we were building towards.
It is not something that is really cheap per linear foot to
build. It is not something where
it is super easy to
break and cause a problem throughout the system. So your uptime
is dependent on the infrastructure. That is the worst. And
ultimately, people tried to put in pneumatics in the 1800s, and there
was this big push by the
Postmaster General for that to be the way that cities operated, was
through pneumatic mail tubes, and they did a huge test.
But ultimately, when they would break, when they would lose pressure, you
lost that whole route until someone could dig up the road to go and fix the
air pressure leak. And so it is not resilient. And
so it broke a lot of our rules. And so I'm sure at some point it
crossed someone's mind, but it didn't fit in that set of
rules that we're building towards. But it is a really good proxy
for thinking about ways
that we can fit into buildings and why it's helpful. I
think in like if you look at like a Home
Depot or, like, stores that use, like, facility-wide
pneumatic tubes, they move a lot of stuff around through those pneumatic
tubes, and usually the thing that's holding them back is
the size of the payload. So you look at, like, hospitals. Hospitals
have smaller payloads for the most part, and so they
get all this use out of their pneumatic tube system. They're able to really quickly
send things to, like, oncology or get
medicine through the tubes. But
in just other industries, you just need a much bigger payload. But it's
a really good proxy of like, okay, here's
how it would feel to interact with the system. And anyone
who's been at a bank, if someone's been to
a bank and gone through a bank drive-through, it's a really good
Yeah. Um, okay. So tell us about the drone. So why,
um, I'm curious why you decided to make it autonomous for one. I
mean, it, it definitely sounds cooler. So I get that for sure. But
like, why, why does it need to be able to wifi by itself? Like, why can't you just have an operator that
Yeah, well, I mean, if you think about our
level of autonomy, it's not that much. I
would even call it a controls problem more than an autonomy problem, just
because there's so few variables that we're actually dealing with. We
call it autonomous because there's not a better way to say it, but it's a little much.
So if you think about having an operator, Our
goal is for the system to be essentially free. It's
automated end-to-end. There is a drawer where you put something in,
and then the cost from getting that thing to the next place
is the cost of electricity. the maintenance schedule of the
robot and the cost of installing the original infrastructure. And
so we've way overspecced
the robots. They are absolute
units. So the only thing that is
really on a maintenance schedule are the tires and the motors. So
those are the two places that we've put, those are
our two wear items, just because they're easy to replace, easy
to swap. So if you have an operator anywhere in that
loop, that's a huge cost. And
the effort to get it to be autonomous is
pretty simple. I mean, you have a really defined flow
space where there aren't that many decisions to
make. The main one is what to do when something goes wrong.
So being able to identify that something has gone wrong, to change routes. You
don't always have signal. So those robots need
to be able to make those decisions on their own. Ultimately, end of
the day, they're going forward or backward. Every once in a while, they turn left or right.
So it's not like, it's not a crazy car. Yeah, it's very different than an autonomous car where
it's like you have to worry about rain and then like dumb humans that are
getting in your way and like, I don't know, the infinite number of things that can happen on
a road. If it's a closed environment and literally, I guess,
yeah, you are turning, well, okay, here's a question. What is
doing the like load balancing across the network? So like, let's say that
we're in the future, there's like thousands of these things flying throughout a
city, flying in and out of a particular warehouse. Will the
individual robots decide among themselves, basically? Like,
you go first? No, I'm taking this path. Don't run into
Uh, yeah, so the junctions would be the only place where that's happening.
Um, and then junctions have their own protocol, uh, that operates at
a junction because any place we have a junction, um,
it is connected, uh, to the cloud. So we'll be able to do,
um, uh, real time load balancing.
Junction meaning like place where you could turn or like
Yeah, or like an intersection. So you have one crossing this
Does that imply, then, that all of the tubes are one-ways? There's
never going to be a time when you go back and forth? Yes. Okay, that makes sense. I
didn't actually know that, but that makes sense that you wouldn't ever want to run into a time when there
Yeah, totally. The
amount of space you would need to handle that is
at minimum 30% more diameter, and
that is super costly diameter. It would mean that we
would get 18-inch payloads out of 24-inch pipe. or
you have to use 36-inch diameter pipe to get 24-inch
payloads. Very tough to handle
there and back. It is cheaper just to put it in a second smaller
See, okay, this is my own fault for not
thinking of this or whatever, but my mental model was, okay, if I wanna connect Amazon
warehouse to my house, there's gonna be one tube that's going that
way, and I'll put it down, it'll drop down on Amazon, it'll go to
my house, and then it'll literally come back through the same tube. It'll just go the opposite direction
through that tube. That's the way that I thought about it. But so what
you're saying is that everything is one way and you're just creating, you know, you
have to have a forward link and a return link basically from each house or
Yeah, I mean, if you think about it, in practice, you
already have the mental model for building this out. It's
just like a train. So you want to build a loop as much as possible.
You want everything to have kind of like this common flow. It's the most efficient,
least amount of feet of track. It is to do a
loop. Only if you have to, do you actually
do forward and back right next to each other. So if
you think about trains, usually you just see one track.
In high volume places, you'll see multiple. But
for the most part, when you were to go the long distances, it's just one.
And then when you go the longer distances, having an ability to pull off
for a part of it, so that you
can do bi-directional without putting in extra
pipe. So there's like, you know, it's pretty much like a train. Only
difference is you can go top and bottom as well. So you can
have, you can put pipes on top of each other. So just one
trench, you put those pipes up and down, and
then you have the bottom one goes one way, the top one goes the other way. Other
That does make sense. So when you're building out those
networks, you do probably, like you have to introduce turns eventually.
I mean, you're not just doing straight shots all the way there. Can you talk about that? Like how
you would plan a network basically and like the ability for
the things to do turns. Can you talk about how that whole planning
Yeah, so in longer stretches, we're just following
the roads. Because you put in all utilities right next
to a road. That's where the easements are. So when you think about a
road, every once in a while, you want to turn a hard 90. But it's
usually at an intersection. So for us, if you're
building out a larger network, we would say, at a turn,
do we need to build out a network to the left? Only,
does it need to be a bank and we just put a corner here? Does
it need to be able to go straight, left, or right? That would be a junction, so we'd
put the ability for it to lane switch and go front, left, or right. And
then where that's, neither of those are trail, we
just follow the curvature of the road. So the
pipes, if you look at them, they're crazy rigid. They seem super
rigid, but in practice they're super malleable, so
they'll, both take the form of
the cut that you make. So when you're going through it, it
looks like it's doing this, because it is. It's super
windy. So you can make pretty good
bank turns, but there's actual discrete
90 degree corners, we should put in a junction
and put in just a hard corner, or you put in a
Interesting. That seems like it would make the track a lot harder. If the thing's moving around a
lot and going up, down, left, right, or whatever, what considerations do
you have to think about for the track then? Because you want to keep it level, obviously. Yeah.
This is where I absolutely, I
think Canon is one of the best engineers. Canon and then Thomas
is on that team making this decision. I think Mac,
who does all our software, was part of this. They are so
good at thinking
about problems from first principles. Because I think it would have been really easy
to over-engineer into
that problem set, which is what a lot of younger engineers do.
You see this problem, you go, okay, I need this highly dynamic track
that needs to affix to the pipe. And I've got to build this way to then
go install it. And it's so fun to think about that. It's
so interesting. And it's so much more fun to show people that solution
than the actual solution. And so
many engineers get tripped up there. While we
came in, Thomas and the rest of the team, they
are about solving the problem, and they are so absolved of
their own ego, they will just make the simplest thing
that works, and they will fight for the simplest thing that works.
So on the track side, you need that flexibility to be
able to handle a bunch of turns and swivels, and you also need to be
able to, as a train goes, or
a robot goes and it hits a trap, it's
going to hit it with some momentum as it's doing
that swirly thing. So if you try to
fix it to the pipe, you're creating a brand new wear item and
a brand new place where the track can get
dislodged away from that attachment. You're
creating just all these variables. So the
way they designed the track, is the track can pivot against
itself, so it can flex up and down, left and right, and
snake along with the pipe. And then it's not affixed to the pipe at all.
So we just slide it through any cavity. There's
nothing holding it down on the bottom. the robot and
the way that the rail's designed, it naturally finds its level, so if
it gets out of whack, it will just, next time a robot comes by, it
will just shift it back over to the middle. So
whether there's like, you know, shifting in the ground, and there's
a new type of snake, it's
dynamic to be able to handle that. So
it's just like, that's another example of them taking complexity out, so
there are less things that can go wrong, less things that can break. It is
like, if you look at our first prototypes and our current
one, it's so much more fun to show people the old ones, because they
have all these cool little, cute little engineering things
that are so impressive, and then I'm impressed
by it, but now if you look at the current system, people almost go, oh, that's
It's pretty easy. Yeah, it's like, yeah. It
is cool. It is cool how that works though. It's like, I think, I think that is
something that people don't appreciate if they've not been around. A lot of engineers is
like, you know, or maybe they've only been around some than like, you know, like kind of
like, as you mentioned, people who are relatively early in their career, like building things,
like it's so fun to work on that, like 99 to
a hundred percentile, you know, like just like getting every single
corner case that could possibly exist, like building the perfect system. Like,
especially I think like people are graded that way sometimes in school too,
where it's like, okay, did you think through everything? everything. And
well, that's not actually what matters. Like when an engineer is trying to put something into
the real world and they're trying to do it, like you said, cheaply, quickly,
you know, just solving the problem. Like that's when, okay, it
seems like you're cutting corners or something to do something really simple and like really
Yeah, totally. I feel
like an engineer's work doesn't shine as much. It's almost underappreciated when
it is really simple. It's like, well, that didn't take long to figure out
how simple that thing is. It's not very complex. I
think end of the day, There's two camps
of engineers. There's ones who have actually had to
manufacture their designs at scale, and then the ones who've
done all their designs on 3D printers. And
those are just like, it puts the fear of God in you in putting complexity into
Okay, one more chunk of the solution which you haven't talked about yet, which is
the portals. So tell me about the portals. How do they work, and
Yeah, so a portal, if you think about the train analogy, that's
the station. So that is a thing that is onboarding
and offloading goods. That's where storage happens. That's
where people are actually interacting with the system. Or
that's where a drone is dropping off or picking up
from a system or self-driven car, cyber robot. They're
kind of like the USB port of the system. The
internal mechanisms need
to be really similar. So all the portals work on
the same internal infrastructure. And
so all the parts on the inside are pretty much
the same. But we have several portals that all work differently
on the outside. So in some scenarios, someone
needs to be able to drive up next to a portal and get their thing in 15 seconds and keep driving,
not getting out of the car. So that portal is very different
from a high-volume portal where you have a delivery driver who's
loading the truck, and he needs to be able to get out of his car and really
quickly put in 40 boxes into his truck.
So that portal looks different than the other one. And both
of those are handing off to humans. Now you have portals that hand off and
pick up from drones. You have ones that hand
off and pick up from self-driving cars. You
have some that need to be space efficient and exist in
someone's apartment. You need to have some that
are easy to interact with like in
a, like outdoors and the weather and the like.
So all these different things are very different
about the portal, but they all work on the same common
framework. So it's kind of like you have the, be
able to have the similar internals of an iPhone and
then adapt them to different sizes. This
one has a third camera, this one is just a little longer, this
one has a bigger battery. You add those external features
that are helpful for people, but for the most part, 90% of the build
That's actually a pretty good segue to talk about the different types of products or whatever, like ultimate
solutions that you delivered to customers. And so do you want to tell us about what
those are and where you're starting and what sorts of customers you're actually
Yeah. So right now we're really focused on what we call instant pickup,
which is automating curbside delivery. So if you think about the
bank tube, It's basically BingTube for
everything. So when you get your groceries ordered
and you've done it for pickup, making that
a faster experience than going through drive-thru. Getting
that under 30 seconds, you pull up. You get your groceries in 30 seconds and
you keep going. Both being able to make that happen
really quickly, make it super easy for the user,
and then be able to automate that whole workflow so
that the store ultimately becomes kind of like a vending machine where you
need a lot less people to maintain it. It's
ultimately like if you think about where logistics is going, stores
that exist in cities, today they're kind of like, I
think if we talk to our kids, in 10, 20 years,
we're gonna tell them about grocery stores, and they're gonna be like, they made you work
the warehouse to get your stuff? And you'd be like, yeah, I
guess so. I guess that's kinda what it was, you know? It's like you're doing
your own pick and pack. You get your little card, and you go around the shelves, and
you make your order, and then you have to sign them out
of the warehouse, and all that happy, you do all that
work. But ultimately, those stores just
become really It's kind
of like edge computing. Those become really dynamic edge
warehouses to get stuff to users really quickly. And
for now, that means we're going to pick them up. And then in
five to 10 years, that means those
are just going to be interfacing with self-driving cars and drones
or going to other places. through
trucks or pipes or they're ultimately
going to be just this node on a network that have
a good amount of volume close to users. And so
anyways, this is the part of that is, you know, as they make that transition, being
able to handle their in-house automation, you
know, our goal is we have this way that we really help them
out today. We help them out as they make some transition to autonomous logistics,
and then those become all our supply-side nodes to make hyperlogistics happen.
It's a crazy, complicated process, but... It's
super interesting. So that's what we're focused on right now is instant pickup.
And then we're also working on the bigger in-city network. So going longer
distances in cities from warehouse districts to neighborhoods.
creating kind of like a, if you think about like
a subway system for a city, but for goods. So being able to
put goods a lot closer to the end user so that a
human can make that last drive to
the end user or put in a drone or put in a self-driving car. Sidewalk
Robot, just making those networks
more efficient. And then ultimately, the
third step of that is creating a retrofit
system for apartment buildings and office buildings and homes
so that you can accept deliveries straight up into your living area, into
your office, into your apartment. I
think that is the one that is the hardest to see the value. And I think
the value is low today. So that's
why we're not super focused on it. But
ultimately, that is going to be the thing that changes your life. If
you think about if a building had one toilet at
the front door, And everyone who was in that building had to
go up to the front door and use the toilet or it had one sink in Or
you had like one light switch that controlled all the lights of the house That
is is you know when autonomous logistics starts to scale
that's gonna be the biggest choke point is is being able to make
the inner workings of the house, be
able to bring those orders, apartment building or office building to the
end user really efficiently. And then that is going to
be the most important thing to making hyperlogistics works. If
you can, that drawer that you're accepting your delivery
from, if you can put something back in it and know
that that thing is on its own, going to find its way back to
the warehouse through a variety of methods, That's
the part that's just gonna change the way commerce works, the way we
live. And so that's the,
not to go too much into detail, there's some other pieces
in between those, but ultimately that's our current strategy for capture,
we call it capturing nodes. Capturing nodes, that's
Capturing nodes, yeah. That's like, I mean it's really interesting because So
here's a little bit of like an aside or story or whatever. So I used to work at Target headquarters.
And when I was at- No way, in Minneapolis? Yeah, in Minneapolis. So I'm from Minneapolis. So
it's like the greatest place to work in downtown Minneapolis. It's awesome. That's
awesome. So when I was there though, this was like, I
guess this was probably like 10 or more than 10 years ago now.
But it was when Amazon was still sort of like, they weren't super
Not for you, but when they started that partnership. Target
at that time was really interesting because the internal discussions
that they were having were not about them as a disperser
of goods. It was not about them as a, we're just going to get
people things as cheap as possible. That was not how they talked about it. But
it was how Walmart was talking about themselves. At the
time, Walmart was the biggest competitor in Target's mind to Target. And
Target would talk them down. They would be like, hey, Walmart, you go in
the store and there's pallets just sitting there. And they
don't even take things out of the shipping containers that they get them in and whatever.
I find that there's a super cool parallel to what you're doing because, you
know, the Target mindset is like, okay, we think of the store as
like an experience or something, but Walmart totally
ate Target's lunch. Like, Target totally failed to go into Canada and
expand, for instance. And I think the reason for that is that Walmart
was really logistics-oriented. Walmart's thing was,
who cares how it looks or whatever on the shelves of the store? We're just
gonna take it in, the thing which ships in, and plop that thing directly down
on the shelf. And so that's sort of what you're doing. You're kind of taking it
the next step beyond that. The target to Walmart to now
Pipetream is that you don't even, who even cares about the store as a
place you walk it. It's like a cloud kitchen. It's like you don't care
to sit down at the table and see the chef
back there making only one thing. You just want the food out of it. You go to a grocery store,
you just want the groceries out of the store. And so it's like, I love
that you say capturing the nodes. That's really interesting because you're
clearly, obviously, you're already thinking about this as a big logistics challenge and it's like, Okay,
what are the highest value nodes? It's like grocery stores and restaurants
That's fascinating. Yep. And then, yeah, so that's in kind of like that
first bucket of nodes is high supply, really,
really close to end users already. And then your
second tier of nodes are warehouses that are outside the city, they're
farther away, but super high volumes. a
really, really high storage. And then
yeah, you just do a bunch of other nodes from there. But yeah,
it is super interesting. I think like the future,
and you can already see this now, is like what
The real store experience is how good your app is and
how good and how easy it is to to get stuff from you. I
think there's like five years of that then ultimately I
think where we get is is all of that changes
because right now. Walmart is beating some
places because it is the closest store to you.
And Target beats some people because of their selection
and how good the experience is, and that they're close to you. And
ultimately, they have about the same SKUs.
It's ultimately the experience is putting a modifier on
top of the convenience. But convenience is most
the reason people are going to Walmart to get their pint
of Cherry Garcia Ben & Jerry's ice cream versus Target
to get the exact same pint. And I think once
things become more automated in delivery, Where
you get that from isn't going to be a location. It's going to be an
app experience. It's going to be an API that
AI plugs into. And the person who gets to win getting
that pint of Cherry Garcia to
the end user is the person who can do it the quickest. And
so it's a mix of who has it in stock
close by, who can quickly deploy that to
a self-driving car or drone, what drone can get it there the quickest. All
that, it would become a lot more commodified, who
is storing that thing near the user. So it would just become who
can get the Pilot of the Chariot of Garcia on the edge of the network, right
near the user and then who can quickly deploy it and get to the
What do you think is like the hardest problem that you guys are solving right
now? I mean, the reason I asked to just maybe motivate
the question is like, from the outside perspective, like
if you're thinking about that speed problem, like how do you get things
there as fast as possible? The most naive way to answer that question would be
build a faster robot. Like, just get it there, just
make it like 100 miles an hour underground. Just have
that thing whip through those pipes. But I imagine that that's wrong,
and I'm curious why it's wrong. And maybe it's right, but I don't think it is.
What are the sort of hard problems that you guys are
Yeah, right now it's a problem of like, you can get
things fast, but it gets prohibitively expensive. And
so the most important thing is, you need to
have that kind of cherry Garcia. I've never had cherry Garcia. I don't
I appreciate it. My dad used to work at Haagen-Dazs and Ben & Jerry's. So it's like, we
Yeah, yeah, yeah. You know what? Do you know Ben & Jerry's is
the biggest manufacturer of
like DoorDash and GoPuff and like all of them, no matter what
company gets you under like 30 minute
delivery, number one SKU has been Jerry's. Brilliant. They
Whenever I get DoorDash, they always will recommend ice cream. They'll say, hey,
you ordered like, you know, whatever Korean food. Do you also want a pint
of ice cream? Like every time. A lot of people do.
But if you think about it, it's like kind of the example of where everything goes, where it's like,
okay, we used to have ice cream in this big tub, and we get it when we want it.
Now we can get whatever flavor we want in an itemized, smaller
thing, and because you're already paying for dinner, it's
But no, how we got there was by saying, what are the hardest things in making things go
I gotcha. Yeah, I think the hardest thing is
when you order that pint of Ben & Jerry's, it needs to already be
in the automated system. So right now, when you
order it, it's on the shelf, and then a human has to go and pick that
item, and either they're part of DoorDash and they're going into a
store, they're picking the item, they're going through the line, they are
scanning out the cashier, they're paying with the DoorDash thing, they're getting back in their car, they're pulling
out of their parking lot, they are going to your house. So
much time and so much cost. Same thing if you're ordering it
from like a Walmart, like, okay, someone's now got to go out and into
the aisles and pick that thing and, you know,
put it on the shelf and then the driver comes up, someone takes it up to the driver, like, and
then your other option is like, okay, maybe there's a microfilament place
like, I don't know, wherever there's a warehouse that
all of this is like there are humans in the loop to make sure that that thing gets
into the autonomous system. So that's the
number one speed and cost thing is
that you could already have that in an automated back
of house. automated system, then as soon as
it's ordered, you can deploy it to be
able to be deployed to someone who just drives up and grabs it
and drives off. You could have it ready for a
drone to come in and pick it up. But the
number one thing is make sure that you're able to deploy that object without a human
in the loop. When you're thinking about kind of like five to 10 years from now,
that's going to be the number one most important thing. in
cost. And so all that is, there's
storage density, and the
cheaper you can make the Autonomous System, the bigger you can make it in a
store and still make the ROI, not 30 years.
There's a lot that goes into that, and really, ultimately, it comes down to how cheaply
can you automate the system, and how
simple can it be, because the simpler it is, the more dense it can be, then
it's also the cheaper it is, and you can put it in more places. Interesting.
So I think that's the number one thing. I think
robot speed doesn't matter a ton. Yeah. I
think just having it be able to deploy quickly, the latency of that
So what do you think are the biggest challenges that you
are going to face technically moving forward? Putting
aside trying to get people to let you dig up the tunnels
and selling to customers, which are probably things
that occupy a lot of your attention, but assuming that that is
all taken care of, basically, what sort of technical problems do
you still see yourself needing to solve before this thing is fully
Yeah, there's a lot. I think that's kind
of where we are, not to have a little plug, but the
number one thing, this is so obnoxious to say, but
I think it's like finding great talent is our number one problem right
now. there we
could be doing so much more if you look at like a customer pipeline and
the things we could do that we just we can't get to because we're trying
to fulfill our customer pipeline like all this looks back
down into having great engineers who
can build and manufacture those specialty portals
who can help us accelerate manufacturing be able to deliver more
people be able to scale But there, AutoStore
is 20 years old and Ocado is 25 years old, if I remember that number correctly.
Like, huge companies, but then you look at the amount of deployments they
have, and it's like a few hundred. And
so it's like, oh, these are huge companies. that
have massive teams and they've been around for forever. And their
deployments are, it's just not that much. Automated systems
are really, really hard to solve all the edge cases, to deploy,
to make it easy to deploy, to scale up your deployment, to scale up your,
you know, you have to have third party
technicians. Like, if you have third-party technicians, now
everything has to be designed with third-party technicians in mind, you've got to build out. So there's
a lot of, a lot of that comes down to how simply
and reliably and creatively engineer things so
you're solving those problems ahead of time to allow for that scale. And
ultimately that's, That's our bottleneck, which is, we in Canada always
say it's like the best bottleneck to have, because working with great
engineers is our favorite. And that's, you know, if you have a company, the more
creative engineers you have, the better the company is. So it's a good bottleneck to have,
but ultimately it's still like super tough to find that talent. So currently
And so it sounds, I mean, it sounds like the drone,
the tube, the, what'd you
call the basket? You had a fancy name for the basket. Oh,
the tote. The tote. I gotta remember the tote. I love the tote. So
you have the tote, you got the drone, you got the pipes, you got the
track, you got the, like all of that honestly seems
like, you know, it's like sufficient or whatever. It's good.
Like you guys have figured out those problems and they're like ready. And
it sounds like, The hardest part now is just those terminals,
basically like the portals that get it up
and down. And getting that integrated into these businesses,
it sounds like the SKU count is way higher for that. These are more custom things
for individual customers. It's very
interesting to me that that's the constraint. It seems from the ad, if
you think about, oh, it's hard about making a underground delivery robot.
It's like, oh, it's making the robot and making the track. But no, it actually turns
out that it's the interface. It's like the interfaces with
Yeah, totally. And you're doing it, you know, we have like pretty aggressive COG
limits. So it needs to be like great. It
needs to be a great experience for the end user. And it needs to fit under
COGs and it's got to be weatherproof. And someone's got to be able to drive
a car into it. And it's gotta be a handful, like
all these specifications that companies have for different
SKU sets and some need to be like, there's a temperature control, like
there are a lot of, it's a super fun problem to solve. But
yeah, that is like a lot of the complexities in that. And then on-edge
storage, so being able to, if I'm a picker
at Walmart, I need to be able to put what
I've just picked into a tote. Right now, they
can't store more than an hour's worth of orders because the
orders stack up too big and they can't handle that with
humans. And they've got to schedule people for the hour. The more you're
scheduling people for doing it in the hour, the more
people don't want to use pickup. They want to be able to just pick up any time. Well, you could do that.
If you had more automated storage, now you think like, okay, what if drones start
really scaling? Well, how are you gonna manage that? That's
gonna be way more volume. So it's like all these little things about,
and it all comes down to, yeah, like managing a
store-to-person or a store-to-robot and then on the other side, robot
So the theme of the show is first principles. Are there like other sort of like fundamental
design things that you guys had to account for or like, you know, the
single most important piece of the, you know, getting
it less expensive? Like, are there any sort of storylines like
So originally I went to school for mechanical engineering just
because I didn't have any exposure to entrepreneurship growing
up. So I knew that I wanted to make things and sell things. I loved
that. That was my religion growing up. But
no one told me that you should be in business to do that. So I went to engineering because I thought,
well, if you want to make things so good, that they
sell, which is make them just so good they sell themselves. So I
just need to figure out how to make things super good. So I'm like, yeah, classic. No
one gave me zero to one. So I went to
school. Mechanical
engineering like halfway through found Paul
Grimm's essays and that was like the religious
literature that converted me. I was like oh my gosh there's just a whole other way
I gotta like dig into this and I started talking to people in engineering and
I was like oh man People do not let engineers on their
own go and solve new things. There's some
jobs that exist, but they're so rare. The people who
have the most mobility are the people who can put a business model around an innovation. They're
the ones who actually get to go. do
whatever, build whatever thing they want. And
so I was like, okay, well I messed up, clearly. So coming
out of college I was like, well, if I wanna go and learn how to learn
business and learn how to sell things, I'm just gonna not
get an engineering job. That seems like the worst thing I can do. So I decided not
to get an engineering job and instead I was like, well, if
I need to, if I have to build businesses, enough
to make enough money to pay rent every month, I'm probably just going to
figure it out because I have to. So it's kind of like a little bit of
a push a big bird out of a nest that's going to learn to fly on its way down. That was
my goal. So I figured out how to code. And
like early, early on, I like had these dumb service-based businesses
that just like made money off Craigslist ads, like converting
people's CLA photos. There's
Oh, it's like scanning. Like scanning them into digital. Scanning. Yeah, yeah, yeah.
Making them digital. Yeah, that was... Yeah, you
can make a lot of money from that. But then also, just
a slurred decode, and then I would just go around to small businesses and ask what their biggest problems were,
and just stay up all night building a SaaS platform
So I had a bunch of little ones. You were ChatTPT before ChatTPT, man.
With ChatTPT if it took 24 hours and the outcome
was pretty bad. But yeah,
so I was doing that and learned business that way. But
nothing was like scalable. I learned a lot about what it
takes, but I wasn't building anything
that really had scalability. So I
was like, okay, I need to like, Take time. So
there was a prosthetic startup that asked me to come on full time to run BizDev. I
was doing a little engineering help for them. So I was
like, okay, great opportunity. I'm gonna go do that. I'm gonna learn how to operate a
startup at someone else's startup. I want to take those two years to
not do anything other than find that one opportunity. that
I'll do for the next 10 years of my life, even if it's unsuccessful. So
I just wanted to, you know, I felt like I have a big shot in me. I'm in my
twenties. I need to just like find that thing. And then I just took a lock in
and just like close my eyes and just go for it.
Even if it's nine years of failing, like I was still, I'm still waking up that 10th
year. Like, yeah, I'm ready to go on this. Like let's keep going. So I
looked at a lot of things. Um, and, and Kelly's talking about earlier, what
I was looking for was something, um, where
there's a lot of engineering that went into making that thing better,
but it was pretty obvious what the route was. So
on logistics, you need to make something that is faster. It works in cities. It's
simple. It's reliable. It's cost efficient. There's not
like There might be, but there's no like new paradigm,
right? Like objects are going to start floating and you're gonna be like, oh my gosh, now
I gotta figure out how to handle floating packages, you know? And
then also wanted to be something where even if I failed at
it entirely, but maybe something I did helps
someone else figure it out. that's 10 years
of my life well spent. So, yeah, I
looked at a lot of things and Lost Mile Logistics was just like, that
was the thing. I've been obsessed with it for my whole life. It's
like right on the edge of this huge breakthrough. And
so it just felt like the right time to go into
that industry. And then I figured that out probably like
eight months into the two years and then spent the next like year and a half trying
to figure out what the problems were and what the best space to be in, both
for where would anyone position themselves and then where should I position myself.
And I still think a couple years
later, there should be... 30% of
the people working in AI should just shift over to last mile logistics. There's so
much to build. I
think once we reach automated logistics and then eventually hyper logistics, I
think that will be bigger than the internet from the amount of money being made.
It's a perfect time to get in. Things are shifting, they're moving really
quickly. It's kind of where AI was when
Dolly, GPT-3 came out. Yeah,
maybe a little farther. I don't think we're quite at the Delhi moment. It
was a good time to get started on the
underlying infrastructure. But
ultimately, we decided we're going to lock into that. And
then through interviewing a bunch of people, we realized
that the biggest problems were getting goods in and out of
buildings efficiently into a variety of different
people, and then the bigger, longer stretches in cities, between
cities, doing that efficiently.
And so we were kind of like banging our heads a little, trying to figure out like how to,
like which one of these problems to solve, and started with
drones, and then checked down to ground-based
methods, because we really felt like there needed to be
this really good partner to drones
that can solve the edge cases and help with managing
goods in and out of buildings. And then
we're like banging our heads on the wall and then ultimately we're like, okay, there's gotta be like a
comparable here. Cities already handle mass
distribution of things super well. Is
there a model that we can use and maybe borrow from that? And then ultimately we
got to If you think about, like, water and
sewage are these huge distribution problems. Yes,
you can fit them down into smaller tubes, but for the main part
of the routes, they're in these giant tubes. Can
we borrow from that and
use that to build out. Is that the right medium for
this? And at first we were like, absolutely not. That's
so dumb. That's the dumbest thing. But
we had two, you know, we still had two years of diligence. We're like, all right,
let's just go check it out. Let's figure out why it'd be too hard. And
from talking to people, we realized like city regulations
are super easy compared to other types of permitting, ultimately
because the city owns those easements and because
of franchise contracts and other methods, they make
money off those easements. So if you give them a new
type of infrastructure to make money on, It's
a lot easier than pulling a permit for like an above ground building where
the upside for a city is pretty low, but the downside is like someone gets
hurt. For an agrarian infrastructure, it's almost flipped. The upside is pretty high.
Makes up a big part of their city budget. There's not a
whole bunch of new utilities going in. And then the downside is pretty low.
You're, you know, six feet underground. Not
much can happen that would negatively affect citizens.
So I realized that was a misconception, that
construction methods have gotten so much better in the last two decades in
putting in this underground infrastructure. So if we could stay really close to
the way that utilities are retrofitted into buildings and
are installed and managed and regulated. Today, this was
super doable. We just needed to build a robotic system that used that
same infrastructure, cheaply and efficiently, and
bingo bango bongo. That's the play. So it
still felt like really hard, but it felt like one of those things where it
was too crazy that other people weren't going to go down that road yet. There
was like the sliver of like, yeah, if we like nail this perfectly,
there's a big business. So for us to like, it was perfect. It
was like, okay, let's go after that sliver. It
was fun. Hell yeah. A lot of people told me not to though. I'd
never, I told people, a lot
of people about that two year, like, hey, I'm taking two years, I'm going to find this thing. And
people had seen what I was doing before, and they're like, oh, this is going to be sick. Like,
I'm so excited to hear about what you're going to do. And then I tell people, and they'd
be like, don't do that. Don't do that.
That's so dumb. Yeah, people
I've never thought would were like, hey, like, I'm your friend, but like,
But who's laughing now? I mean, probably still