The Changelog: Software Development, Open Source - Autonomous drone delivery in a Zip (Interview)

Episode Date: December 10, 2025

We're joined by Zipline cofounder / CTO, Keenan Wyrobek. Zipline is on a mission to build the world’s first logistics system that serves all people equally via their fleet of autonomous drones that started in Africa delivering medical supplies and can now deliver packages (up to 8 lbs) directly to your door. They've solved a lot of gnarly technical and regulatory challenges along the way. We go deep with Keenan. We hope you'll find this one fascinating.

Welcome, friends. I'm Jared and you are listening to The ChangeLog, where each week we interview the hackers, the leaders, and the innovators of the software world. On this episode, we are joined by Zipline co-founder, CTO, and product architect, Kenan Wirobeck. Zipline is on a mission to build the world's first logistics system that serves all people equally, via their fleet of autonomous drones that started in Africa delivering medical supplies and can now deliver packages up to 8 pounds directly to your doorstep. They've solved a lot of gnarly technical and regulatory challenges along the way.

We go deep with Keenan. I think you'll find this one fascinating. But first, a big thank you to our partners at fly.io. The public cloud built for developers who ship. We love fly. You might too. Learn more at fly.io. Okay, zip line on the changelog, let's do it. Well, friends, agentic Postgres is here. And it's from our friends over at Tiger Data.

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I saw Zipline and I thought, you know what, this one makes sense. There's a lot of people trying to do delivery. Of course, you have autonomous cars upcoming, you have people that are doing tunneling. They're trying to put tunnels in the ground and, like, ship it kind of Futurama style. but underground Futurama. And then we have drones, which I don't think zip lines, the only one playing the drone game, but you guys are, I think, way ahead of the game.

I've been doing it for a long time. Tell us about the start of this company and where you're coming from. Yeah. So we started almost 12 years ago now. And we started in a niche of a niche of delivering blood to hospitals in Rwanda. That's where we started. Why there? Yeah, so really Rwanda earned this, like we knew we wanted to start in health.

My, my, with the very beginning of this, we started exploring the space based on really just stories from family and friends. My wife's an epidemiologist and she would tell me these stories about health intervention campaigns that would get stuck on logistics, right? These would be like vaccine campaigns where they had the vaccines, they had the doctors, they had, but then like the logistics got in the way and they couldn't be successful. And so yeah, that's how we started. I went deep on that. I'm personally not an early adopter. I'm a very tech skeptic. So went deep in Central America and Africa at the time,

expecting to come away with a thousand reasons why we couldn't possibly make a difference. And the opposite happened. The deeper we went, the more conviction we got that we could make a big difference. And one of those places we were exploring with was Rwanda. And they turned out to be a phenomenal first customer for us and really a partner figuring this out together. Yeah, and in blood, of course, why blood? It's just this rare commodity everywhere, right?

There's never enough of it. It's actually very expensive. We think of it as free because we donate it, right? But the cost of the collection, the testing, the transportation is very expensive. Hundreds of dollars a unit, even in places like Rwanda, way more in places like here. And it has a very short shelf life, right? As little as seven days from the time it's donated to the time it expires if you don't give it to somebody who needs it.

And so it's just by centralizing blood in one place and then delivering it when you know what blood type is needed for what patient and what time, it turns out you can virtually eliminate blood waste, saving a ton of money and a ton of lives for the health system. That's why we started there. What's the tactical nature of that when you went to Rwanda? Was it discovery first and then tech later? How did you come to a technical solution? How did you think about it before you built something?

Yeah. I mean, we had built nothing. I mean, I literally called a friend of mine who was good at drawing, and he drew pencil sketches, and I built a slide, making a slide deck of the concept, and we were using that to talk to people. In early days, it was just talking to, you know, the operators in these health systems that actually run logistics, run this testing, run these labs. But very quickly, we ended up having meetings with the offices of presidents in these

countries. And that was a big sign that we were looking at a problem. that was a really big deal, you know, in the, in these, for, for these health systems. And yeah, no technology whatsoever, you know, a year or two before we were doing this, Amazon was like, hey, drone delivery coming next year. And so, you know, that drone delivery was like an idea that was out there. It wasn't the real thing yet anywhere. And so we kind of thought of ourselves as like, hey, you know, if we're going to do something,

let's find a niche where the value is really high to do this. And yeah, no technology. And then, of course, once the interest was there, we got moving fast. So was there a point that you and your co-founders looked at each other? You had saved countless lives with delivering blood around Africa and thought burritos. You know, burritos are next. Or is that from the start? It was both there and not there, right?

In a lot of the countries, we operate around the world, we start with health systems. That's actually how we started in the United States. We started with health deliveries during COVID and then expanded from there. So in the islands of southeast, eastern Japan, we deliver health care supplies and bento boxes. And in a lot of places in Africa, we operate, we started in human health and then expanded into various agricultural use cases, things like genetic diversity for milk cows, huge impact, but like super obscure. And we've just been layering on other use cases and slowly worked our way into things like e-commerce. and what's what's compelling like and but we think about Zipline I think a lot of we talk about the impact on health which is really exciting we and we started with the impact of like blood right it's

a super visceral you know the high impact but very rare problem right most of us don't need blood transfusions in our life but when you need it you really need it and then we slowly worked our way in health to preventative care which is actually where the real cost savings for health systems is and then we've worked our way into put into other areas like animal health And one of the things that's really magical about this, you know, as we step into new things like auto parts delivery, right? Like, you know, what limits the mechanics' ability to, like, service cars is usually like how fast they can get the parts. And basically, like, the way I think about it is basically for life, home, in the home or professionally, we're in the mission

of getting you what you need when you need it. And we do it in a way that's not just fast, right? We skip over the traffic. We're very reliable in that way. But just, you know, wildly environmentally friendly. We don't talk a lot about that. We can get into that. If that's interesting, like the, you know, we're talking about like a 20x improvement in the overall environmental footprint of the supply chain and the, uh, uh, almost every aspect, including things like bird safety. It's like something we don't talk about a lot. Um, so there's just so many layers to this. Well, even I live here in Texas, we have a lot of wind farms because, you know, here in Texas, we have multiple ways, uh, probably like Nebraska, Jared, you got multiple ways you're

getting electricity and we I'm not so much a fan than they're kind of like big and crazy but I hear people get upset with the bird issue is essentially of that and that you know to maybe to the environmental aspect of it that there's still so much of a cost to produce even wind energy that it's almost not worth it when you compare to you know how you talk about your efficiencies yeah and it's it's you know I care a lot about birds so I pay a lot of attention to it and yeah We estimate that when we displace delivery by car, we reduce bird injuries by something like somewhere between 10x and 100x lower rate. So we study that a lot. And so, you know, there's a lot of aspects to why we do what we do and why we're excited about scaling what we do into all these different verticals.

So let's talk about the design of the drone itself because we mentioned, you know, the tactical approach coming out of the need of delivering these things in Rwanda. When I saw your guys' design, I was very surprised by it. There's a kind of a more typical quadcopter, larger quadcopter looking thing. It almost looks like an airplane with blades on it. And then it doesn't actually do the delivery. It delivers the delivery mechanism, which is a smaller kind of a baby copter that comes down on a zip. That's I presume where you guys get the name. It lowers it down to the ground and then raises it back up again.

Where did that design come from? Yeah. So that sort of double drone, drone inside of a drone design. It came from just an obsession of figuring out what would actually work for our customers. So our first platform does long range delivery has a lot of great attributes, but it requires about two parking spots worth of space to deliver in because it literally just flies over, drops the package with a little paper parachute on it and the package floats to the ground. But so many of our customers in the health space and otherwise we're like, we want home delivery,

we want in metro delivery where you don't have that kind of space. And at the time, we're kind of like, well, we don't do that. And eventually they asked us enough times we started thinking about how would you do this. And we knew from that platform that one of the, one of the things that makes people love our service is you don't hear our drones. And that's way harder than it sounds. And we're like, well, we don't know how to do a super precision delivery without hearing the drone. And we've seen other ways of doing this. It's usually loud and noisy and kicks up a dust storm and takes up, you know, can't deliver very precisely.

And so this two-part architecture enables a bunch of things. One thing it enables is quiet. It lets the drone itself stay up at 100 meters, you know, 300 plus feet up in the air, which is one of the many things we do to make that just silent and even suburban places. And then that little mini drone that comes to the ground, we call it the delivery zip that comes to the ground, you know, they actually carries, delivers the package for you. It has its own little propellers on it so that if in windy days and stuff, It can still be super precise and get into a tight space.

And so really those two things, helping us be really quiet and be super precise, right? We can get into a really tight space with that little drone that comes to the ground while the big drone stays up high that does the, you know, we call it, does the heavy lifting. Like it's literally there to carry the weight, the distance. And yeah, that's why we have the little drone inside of a drone solution. Reminds me of how you see things happen in space. When you see like little jettison engines sort of like pushing it, nudging it. I don't know, I'm a sci-fi guy. So I see these films all the time.

exactly you know it's kind of like a little slight adjustments but you just have is it one single large propeller or is it multiple on the i guess the what do you call the minid drone what is that name for that guy yeah internally we call it the droid delivery zip uh we don't have a great name for it but we just call it the yeah i like the delivery zip but anyway this little thing that's the little thing that's the little thing that's got three little thrusters very similar in concept you like you're saying yeah well it's got one big thruster in the back and that thruster's job is to fight you know big heavy winds and so like point of the wind and just like point of the wind and just just make sure it isn't going to blow it off course. And it's got a little bow thruster and a stern thruster. If you like boats, you kind of think of it that way that help it basically stay oriented and do the sort of side-to-side adjustments as it's coming down and staying precise. But yeah, we actually, a lot of our team comes from space. And, you know, the control theory behind how you stay precise on that little delivery zip

as it comes to the ground is very similar to how you think about, you know, reaction control thrusters on a spacecraft. Because that thing can't spill your coffee. I mean, sure, I can flip a burrito, no problem. But if you're lowering a coffee down, like, that's very, it has to stay oriented very well. I assume blood, they probably want that stuff spinning or something. But there are certain fragile items that can't go. So on the software side, then-fragile items, I love coffee.

Coffee's fragile. It is. On the software side, are those two divergent operating systems then? Because it seems like they have perhaps different concerns, but they probably have a lot of overlap as well. How did you tackle the software side of these two different drones? Oh, yeah, they're very different control problems. Yeah, the drone up, this up high, it has a wing, so it can fly a fixed wing on the wing really efficiently. It can hover in place for takeoff landing and while it's doing deliveries.

Yeah, it's a long story that the controls approach. And really it comes down to just massive amounts of testing. You know, our high-volume test sites have done hundreds of thousands of deliveries. We chase weather with a mobile test rigs. We go chasing like hail and icing conditions and these kinds of things. You know, a ton of simulation, you know, literally half of all the engineering we do at Zipline is test, like just full on half of it. That's how we can do this, is basically building the test systems, the various software platforms for simulation and things like that, the actual test scenarios, all the ground testing we do. We have an entire building down the street from where I am.

That's all it is is just hundreds of ground test systems. to test to take to simulate what we do in the air on the ground uh yeah it's the answer to your question is a long one but it's literally half of what we do is is the sort of all the testing it takes to actually develop the control systems for these things to know that they're going to be both capable but also safe i also think about updating the software i mean you mentioned the test facilities i imagine you do a lot of you know iteration there so you're constantly deploying potentially over the air updates i have no idea how you accomplish that mission, but divergent operating system, but also a truly distributed, you know,

update platform. How do you get new to the individualized? Is it an operating system delivery? Is it an individualized delivery? Can you talk about that at all? Yeah, absolutely. So we think about software and software deployment. There's sort of two worlds for us. One we call it, we think it was flight software and then cloud software. Flight software is all the pieces, some, a few parts of the cloud but mostly things on the actual aircraft that we consider flight critical right um and we that software release process takes us about six weeks so every six weeks we release software uh to that system and and we you know do just in those six weeks we do you know tens of thousands of flight tests uh we do a bunch of hardware in the loop testing so these are like basically think of it is like

the matrix where you take the electronics of the aircraft and basically plug it into a simulation literally and fool it so it thinks it's flying over in dallas somewhere but it's actually, you know, over our basement plugged into the, to the simulation. Plus, of course, software in the loop simulation where you're doing like, you know, millions of flight test. And, yeah, and that whole journey takes us about six weeks to get to the point where we're like, yep, this new software release is good to go. And then we release it. And then we have an over-the-air update system that updates all the process of software on the aircraft and, and deploys. Yeah, we do that. People often ask, do we do that in the air or not. It's like, no, no,

So when our aircraft are docked, they update themselves. That's right. They check themselves. They're like, okay, good software's good to go. And then they'll fly again. How many of these problems are novel to you? I know that the defense systems that we have here in the U.S. probably have these problems and maybe have solved a lot of this,

but maybe you don't have access to the DOD's tech platform or maybe lack thereof. How much of this is invented here and how much of this is, you know, maybe a partner or vendor that you bring in to support like over-the-air updates, for example? Way more of this is done in-house than I would have ever thought we would have to do. Actually, when we started Zipline, I was like, great, you know, I'm going to go find somebody who has a drone, buy it from them, modify it a little bit for deliveries and start serving our first customer. And the best quote I got back then from the companies making drones for defense was a $200,000 drone with a 200 flight warranty if I did not fly it in the rain. And to be clear, most of these countries, it rains pretty much every day. So that wasn't going to work.

Yeah, no, we do a lot in-house. And a lot of that's because we fly in conditions that no one else flies in, right? Stormy weather near the ground over mountains, stuff like that, like, no one flies in that. And so we've had to learn a lot of this stuff ourselves and build our own basically data sets and experience and simulation approaches to actually develop these things. But then the other side of what makes us very unique is just the scale, right? We operate at a very large scale. And so, like, this, you know, over-the-air updates is a good example where,

We need that to be very, very easy and robust in a way where if you're operating at a smaller scale, like a human can do a lot of double checking of that and things like that and it doesn't matter too much. So, yeah, there's a lot of, you know, even over the update system, we've built ourselves. Do you know how many drones are in your fleet roughly, like worldwide to give us an idea of the scale you're currently at? Yeah, so it's a couple hundred. Okay. And you just started the United States recently. Well, you, 2021, I think was the first non-medical flights. This is what I've been told by Ian behind the scenes.

And now you are in Dallas and rolling out. I just saw a video from your CEO and co-founder that there's like a whole bunch of drones getting built right now to just go crazy. But, yeah, 200 worldwide. And how many of those are over there in Rwanda doing their thing? I think it's close to 400 or so. So it's about 300 outside of our first generation. and yeah, well over 100, but I don't think 200 yet of our next, of our precision delivery,

the drone and the drone system. Gotcha. Yeah. So how much of your software is orchestration? Like, I assume that's the cloud side that you reference, the control cloud. I guess maybe tell us more about the cloud side and what all that entails. Oh, there's a lot to it. So there's obviously the pieces for people to place their orders.

Every partner we have, we have basically systems for, to integrate with our partners data systems. Then we have our basically dispatch. I literally think of this as like there's cloud autonomy or fleet level autonomy and then aircraft level autonomy. And at the at the fleet level, you got to decide like which aircraft is going to go on which mission at which time. And some of that is based on which aircraft is capable, right, of that mission. Some of that is based on, you know, making sure if we told someone, hey, we'll deliver to you in this 60 second window that we actually dispatch the right aircraft at the right time, get the order ready at the right time so that we'll hit that window. And some of it is stuff that like people, you know, other cloud stuff for us is like

weather forecasting. We do our own weather forecasting. We can talk about that. That's a really fun problem. But also like, you know, basically we have to design our own highways, right? If you think about autonomous vehicles, you kind of take for granted that if you want autonomous vehicle to drive from here to, you know, over the mountains, that like you can find, if you use the road network that's already been designed, you'll get there. There's no such thing for drones. And so we We have to do a lot of computation in the cloud to basically give enough prior to our aircraft so that when they're flying, they have kind of the equivalent of a highway system. It's not quite that simple so that when they're doing an avoidance maneuver, for example, and planning that in live, that they're doing that with enough sort of prior that they're not going to get off track and not be able to make their delivery. That makes sense.

And they generally fly at 300 meters. Is that what you said? They fly about 100 meters. So 300 feet. 100 feet. 100 feet. Thank you. Yeah.

What kind of stuff do you have to avoid? obviously birds, but at that, I mean, cell towers, air strips, perhaps? Like, what's the kind of stuff that has to be avoided at that height? Yeah, for sure. So, yeah, you can have very tall cranes, cell towers. You can have inaccurate maps. So you may not be at the height you think you are. So there's hill or mountain there.

You, yeah, definitely other aircraft. That's a big part of what we avoid. There's not a ton of passenger aircraft at that altitude, but there are some. And it's really important that we avoid them as well. those are the kinds of things we avoid. Well, friends, I'm here with a good friend of mine. Again, Kyle Galbraith, co-founder and CEO of depot.dev, Kyle, we are in an era of disruption, right?

I would also describe it as rethinking what we thought was true. And I guess that's kind of the definition of disruption. But from your perspective, how are teams, reliability teams, CISD, pipeline teams, how are they all rethinking things? And where does Depot fit into that? In the conversations that I have with customers, a lot of DevOps teams, platform teams, site reliability teams, they're really looking at this new era of software engineering that we're all living in.

And they're starting to question, like, the bottleneck is no longer the act of writing code. The bottleneck is shifting. The most time-consuming part is integrating the code. It's everything that comes after. It's the build. It's the pull request review. It's the deployment. It's the getting it into process.

Once it's in productions, it's scaling up support teams to support it. It's adding documentation, all of these downstream problems. And so through the lens of Depot, what we're really starting to think about is there's a very realistic possibility that within the next two to three years, maybe even sooner, that we're going to enter a world where an engineering team of three people could theoretically have the velocity of an engineering team of 300 people. And what's the consequences of that? What's the consequences of the code velocity spiking up to that level with such a small team?

There's no way three engineers are going to be able to code review all of the code that's being created if there's three engineers and 297 agents also creating features and fixing bugs. So that's just like from a pull request perspective. But then you think about it through a build lens too of if your builds take 20 minutes with three humans and now you're going to have three humans and 297 agents also running. Well, like, you definitely don't want your build. It's taking 20 minutes because now, like, the entire pinch point is the build pipeline. And so we're starting to think a lot about how do we eliminate the bottlenecks that come downstream

and what can we do with Depot that streamlines that. So obviously, friends, we are in an era of disruption. Things are changing. You know it. I know it. That's how it is. And the thing with production and what kind of. I was talking about here is how in the world do you get your bills to be faster?

How you get them to be more reliable, faster, more observability around those deployments. You need it. It's required. And Depot is there to help you. So a good first step is to go to depot.dev, get faster. Try their trial. It's too easy. Again, depot.dev is where to go. It all begins at depot.dev. How much does regulation play into this rollout? I assume every area probably has different rules about how you can go about flying your drones at 300 feet. Yeah, I wish everybody had rules.

I think that everyone we've been... Usually people say they want less rules when they were trying to scale up. Yeah, I mean, when you're a startup and you go to a regulator and you're like, cool, I would like to do this thing. And they're like, well, that's not allowed. And then basically from there, it's like all by exception. And so you have to kind of work it out, the rules of what you operate at the detail.

And as a startup, that's a slow process. And startups need to go fast to survive. And, yeah, that's why I say I wish there was some precedent. In some ways, obviously there's some luxury and getting to help create the precedent. But yeah, it's a lot of working with the regulators. You know, some things about air spaces between countries are very similar, like harmonized. but other things are very different. And so, yeah, like things we have to do here in the U.S.

have been very different than Rwanda. Yeah, it's a big part of what we do. But it's also, we've gone from that being a big challenge, maybe 10 years ago, to now it's something that we've gotten quite good at and quite good at working with these partners and these regulators as partners and working with them proactively enough that we can generally work out what needs to be worked out

before we need it to serve a customer. But it takes a lot of effort. I will say that. Yeah, I was thinking of the luxury of not having rules that are already defined because those can slow you down, but actually not having rules and not having a clear path towards engagement, that means you have to trailblaze. And to trailblaze, you've got to get out a machete and hack away a bunch of stuff, you know. And that can be even slower and more laborious than if somebody else had already cleared the path for you. So that makes sense. There's a great story here in the United States, starting about six years ago, we started working on the center.

system on the aircraft that can sense and avoid other aircraft. This is a system that uses machine learning. And machine learning is a class of software that the regulators have no experience with, literally. And it took us about five years of working with them to go from the beginning of this to them approving us to operate. And that was the first time they've ever approved AI, you know, ML-based software for safety in the airspace. And so it was near daily conversations with their teams figuring that out over that five-year journey. And there's some people at the FAA and at Zipline who I respect a ton for working through the minutia

they had to work through to figure out what would the requirements be and how would you validate the system against those requirements and then actually doing all that work and all that analysis to bring it back to the FAA and be like, okay, we did what we agreed to, like, you know, let's go through this together. And yeah, that was a five-year journey there. And it was a hard, a hard one battle.

When I say battle, I don't mean like Zipline versus the FAA. It was very, very much in it together because they definitely wanted to figure it out, too. Yeah, it was something else. This is an example where the word regulation, which you haven't quite said yet, gets really weird. And I don't want to go into politics, but it seems to be the word that gets thrown around regulation, less regulation, more regulation. But as a developer, you know, I really lean back on what you said there was not a presence of which was specifications, which is really what regulation is. It's an adherence to a specification that everyone's agrees on for obvious reasons.

But you're in this kind of unique high stakes scenario where, you know, maybe regulation could be less, you know, less pressured, so to speak. And in a case, you've got to be, you know, a high stakes scenario where if there's a crash or if there's a, you know, a break of leg situation, which I'm not sure you like to wear crash. I wouldn't like to wear crash if I was in your business personally. But, you know, I just think about the need for that. Can you speak to how that's played as an ally versus a foe? Yeah.

I think there's a couple layers for how we think about this. The first one is because everywhere we've been, everywhere we've gone, there hasn't been some, like you said, specification to follow. We've taken the mantra that like our first job is to convince ourselves and not in like a hand wavy way. It's like, no, no. Like, you know, this is over our house, over our kids. Like, you know, are we convinced that we've taken a rigorous approach before we suggest that approach to a regulator. And that's gone a long way, right? That mindset is attracted some of the

best talent. It's figuring that some of the stuff out is really complicated. It's tracked the talent we need to actually figure this out. And then it's also forced us to do the work, right, to convince ourselves, the analysis, the, you know, all the, all the testing, all that data review to convince ourselves is also what the regulators want to see. So if we've done that to ourselves and we've really been skeptical of our uh internally first um and it helps a ton when when you're then having these in-depth conversations with these folks on the regulatory side who are you know they have the they have the like you know the completely thankless job of like you know okay we got to figure out the specification for this new thing that no one's done before and so right like you know

if they underdo it and someone gets hurt they look really bad and of course like if they overdo the regulation, then everybody in industry complains of like, oh, they, you know, they wrote down these regulations that are completely impractical, right? And so they have, they're stuck between a rock and a hard place. And so by doing that legwork up front and internally proving to ourselves something that we really believe in first, and then bringing it to them, that that's been core from like, from our perspective. And then the only other piece of it that I would say is like, it's all relationships. These are all people on the regulatory side. They've got a job to do. We've got a job to do. And so we spend

a lot of time, you know, basically working together to make sure we understand what they're trying to do. They spend a lot of time working and understand what we're trying to do, be really open-minded, make sure we're hearing each other out like in any relationship and try to make progress every day, even if it's not as fast as you might like. How would you frame, this isn't an exact one-to-one when I say this, but how would you frame test coverage, you know, in terms of a coverage level, confidence level, when you ship something and it's in a regulation standpoint or your specification you've got to adhere to, is there like 95% 98%, like what do you strive towards when it comes to adherence to a spec or defining

the spec? What is what is confidence to you and your team? Oh, great question. So there's a there's a there's a there's a model for thinking about this that was called the swiss cheese model. I did not come up with that name, although I'm known for naming things with really dumb names. It was actually a NASA name. The Swiss cheese model and the way conceptually basically what it is is it's like Every sort of, every approach to testing is like one slice of your Swiss cheese, right? It's going to have good coverage of some aspects. But if you look at it, it's going to have holes, right? For every type of testing you do, you obviously have many different layers of testing that you do.

And the intent is if you stack up those layers of Swiss cheese and look at them, you know, through the stack, then you're not going to see through holes, right, if you're doing it well. And we spend a lot of, so examples of our layers of Swiss cheese, you know, some of them are, going to be familiar of things like unit testing and static testing and things like that that are commonly done in software software in the loop testing so this is where you have like full on physics level simulation running of your full system even your full fleet and you're able to then write test scenarios on top of that we talked about the hardware in the loop testing where you take the hardware itself the brain of the aircraft plug it into a simulator and fool it into thinking it's in the real world that's great for testing you know like the the the actual like

hardware-level components, like if you short out a certain bus, does the actual full software stack detect that short and do the right thing? And then a lot of things in flight test. We do all kinds different flight tests. We do on the order of 10,000 plus flights a week at this point across our flight testing. And almost every single one of those flights is pushing the system to an extreme in some way. We actually have this fully automated software system we call Chaos Monkey, where basically what it's doing as we're dispatching all these flights is that is chaos monkey is literally throwing chaos into the system as as those missions are happening that either will cause the airplane to do something extraordinarily like dynamic against the physics limits of the aircraft or turning

off their subsystems of the software killing various rotors things like that and making sure that the system despite in this given flight having dozens of weird things happen that off nominal events as we call them happen in that flight does the whole system handle a gracefully and safely. And this is just on the software side, right? When we think about hardware, a very similar thing. Tunk and many layers of testing of the hardware to make sure we understand deeply its performance and its reliability. Yeah, and there are entire teams of folks who look at all that testing and basically are constantly questioning, hey, okay, we added it. In this release, we have a new capability we're releasing. Did we add enough testing to all the different

layers of the Swiss cheese such that that's going to be responsible to shift? And there are times we think we're ready and we do that review of everything we did and we're like, nope, this isn't ready. We're pulling this from this release. It's got more work to do just on the testing side to get that confidence. These releases, are they, share as much as you like.

You seem to be very sharing. I like this. I think about releases and I think about, wow, if I released my test level from idea to new capability, as you said, into production. There's probably several layers that are in that middle ground, which is like a true release, but not in a real, real world scenario, so to speak.

How do you plan releases? How do you graduate releases from tests, delivery, observability, test again potentially? You said you do 10,000 flights a week. That's seven days in a week. That's 1,400 flights a day roughly. Gosh, it's a lot of flights. But how do you release and do that in a way that's like, okay, it's in production, but it's not real production.

I'm assuming these things. So walk me through that kind of idea. Yeah. Okay. So depending on the scale of a given feature, I'll talk about one of the biggest features we've ever released. We just released it recently. So we talked about the drone that flies up high.

It has a wing and can hover. Until about a month ago, in our releases, in our operations, we were only hovering. We were not flying on that wing. So we were flying it more like a traditional quadcopter. It's a pentacopter, but flying it like a traditional quadcopter, just hover, which means the range is very limited. But while we were working on, actually being able to fly on the wing, and that's the software in systems to transition from hover onto fixed wing is what's referred to the industry and then back into hover, including when anything could be going wrong, like any of those rotors could not be working and that kind of thing is there's a lot to that. And we've been working on that for, we're working on those features, you know, at some level of development testing for two years to enable this.

And so about two or three months before that release cuts. So when I talk about releasing every six weeks, we cut basically at the beginning of that six weeks. We will look at all the new features that folks think already for a release. And we'll look at like how tested are they? How proven are they? How good is the test coverage and all these layers of Swiss cheese? And then we'll decide, okay, hey, yep, this feature is ready, this feature is ready. No, that feature is not ready.

It's not going to go in this release. And then we'll cut a release. And then once we cut a release, there's a bit of a stabilization that takes us about a week to make sure that release is really stable. And then it goes into this very structured release campaign that takes about five weeks on average, which is, you know, depends on the release, but something like 50,000 flights, a whole bunch of hardware loop tests and software loop tests and all these other tests we will do again as well as a part of that release process. And then all the teams are basically paying a ton of attention to all the data coming out of all. all that testing. And over the years, we've developed all kinds of tooling and dashboards that help all the teams look at that data and look for anything weird, anything that might we consider a near miss. Obviously, the real miss is if we have a parachute landing during

that testing, we're going to know exactly what goes on there. But we're looking for anything that's at all weird. We call it a near miss. And studying it and seeing if it's a, if it needs to be addressed or if it's fine, seeing if it, sometimes when we do, you can kind of think of that flight test is like the last leg. If we find something in flight test, that's a red flag test. Like, hey, the other layers of Swiss cheese aren't good enough. So if we find something in flight test during that campaign, we're immediately investing in those other levels of Swiss cheese

to make them better and improve their coverage. And then only once the data says we've got a, you know, we've got a system that meets or exceeds the overall target level of safety of our last release, do we then say this is ready to actually show? Do you have the idea of a black box in your thing? I mean, I know that airplanes do. imagine you got some version of a black box where if it does, I'm sorry, crash, that you've got some sort of thing in there. And then I've also think about like observability because

you've got all this testing happening. And I think about like traditional software in the cloud, it's kind of easy to orchestrate observability. But you've got over the year, I'm sure you've got some version of Wi-Fi or access to, you know, the thing digitally via a network of sorts, telemetry going. How does a black box? Is there a black box? And how does observability happen in those scenarios. Yeah, so absolutely. So we log a ton of data on the vehicles at all times. And that's, of course, done in all this testing, but also in production.

And that's the philosophy is that like anything that could possibly go wrong or be a near miss, you got to study. And you mentioned crashes. I should mention we have a, we have a parachute system for the aircraft that's kind of the backup to the redundancy. So there's redundancy in the aircraft so it can nominally fly when things don't work. But the backup to the backup is a parachute. So it'll float to the ground, like it's actually made for us by a skydiving parachute company.

So it's like a skydiver coming to the ground. And so, yeah, if we ever have a parachute landing in tests or operations or anything that's even close to a weird data, like we go study that to basically deeply, deeply understand it because quite often it's a new insight. We're so far in the long tail of the problem that many of the problems we see now, they happen one in hundreds of thousands of flights. And so you basically, like, if we didn't log it, think of it as like, oh, no, we like now we, now we're. we have to wait for this to happen again in hundreds of thousands of the flights, which is a total shame. Total shame. Should happen more often. Exactly. No, no, that's not the shame. The shame is not the logging yet. So we log these things. Now, in addition to the logging to enable us to like go through those logs and understand everything that happened, we use those logs not just

for like root causing a specific problem. We use those logs to understand things in aggregate. And so we have tools where you can mine that those logs longitudinally, like across a bunch of, you know, across thousands of thousands of flights to deeply understand the statistics of a certain thing. That's really important as well. And then, of course, during live operations, yeah, the aircraft are reporting over radios like live what's going on. We have a remote operation center that's monitoring all of that. And so during live operations, we have certain things that basically, they are pilots, I think of

them more like an air traffic controller where they can be like, okay, you go back and dock and that kind of thing and understand what's going on at a very sort of fleet level. Have you ever logged a tornado? We've definitely, yeah. So the closest thing we've logged, we've logged some tornado, some very small, I don't think you'd call them a tornado. I think they're like the, you know, basically the things that are too small to be considered tornadoes. And some of our testing, we're actually chasing some tornadoes right now as we look for hail

and more extreme weather events with our mobile test rigs. Yeah. The craziest things we have a lot of log data on is what's called a microburst. So it's the beginning of a thunderhead formation, about nine, first 90 seconds of a thunderhead. Yeah. You have the vertical winds at like 50, 60, 70 miles an hour vertically in the middle of the microbursts. On the sides of the microbursts, the same thing goes down. Those are some of the most extreme weather events that are hard for the drones to handle.

What do they do in those circumstances? Do they turn around and leave or do they land immediately? Or what's their protocol? So it really depends how big it is. This is actually one of the first things we developed AI to forecast. It's because if this is really big, right? If it's kilometers across and really strong, then. And we can't, you know, if we're in it, we're going to end up parachute landing.

And so we know this because in a lot of our operations around the world, when we're doing emergency deliveries for, you know, patient on the table delivering blood situations, we will take, we will basically ignore our weather limits and fly in very extreme weather. So we go through these things. But then for non-emergency deliveries, we rely on our forecasting to keep us out of this stuff in those really extreme events. If they're small enough, yeah, the control system will fight its way through it. But of course, you know, the aircraft has its physics limits, right?

It can only climb so fast. They can only do so much. And so in certain situations, it can't overcome them. And, yeah, that's when the parachute kicks in. I assume there's some sort of wind limit that there's just no chance for anything to fly through successfully. It's got to be around 100 miles per hour or so, maybe a little bit less. I don't know. But there's certain storms where it's just like, you better just parachute out because there's no there.

There's no success as a possibility. regardless of the size of this thing, like, you know, 30 seconds at 150 miles per hour is knocking down massive trees here. And so I'm assuming it's taken a drone off its course quite a bit. There's a certain mountain pass in Rwanda I'm very familiar with because we have to fly through this mountain pass to serve about a third of the country there. And in this mountain pass, it is the winds get whipping. Like the winds can be higher than we fly. We fly that aircraft at like, what is it, 60, 70 miles an hour. and the winds, yeah, get up to 100 miles an hour.

And you'll see our drones flying backwards as it tries to fight through it. Developing the control system and logic to like, because most of those winds are gusty, right? So if you can kind of hang, if you can stay in the air long enough and stay out and then punch through it at the right moment, you can get through the mountain pass. And yeah, it was a big breakthrough when we figured out the like how to make that logic robust. So that even you see the drones just flying backwards for a while, flying backwards for a while, flying backwards for a while, and then floor it at the right second. You know, it's estimating the winds dying down online,

and then it punches through the mountain pass and gets through. Do you have any video feeds? Because you're going to come with some great drama in those moments. If you could capture video, just when it's really gnarly, you know? I got a great video of the logs of that. It's not funny fanaticus video, but you can see the position on the math going backwards and things. I don't think Hollywood's going to call you for the log file. No.

Let's talk more about that wing. So did you guys just put the wing on there because you knew of a Eventually, you were going to use it. And so you just had it, you know, in manufacturing for a long time, but couldn't use it. Yeah, absolutely. We knew we needed the range. You get about 10x more range flying on a wing for the same energy than hovering. And we need, like, our customers need that range.

So many of our use cases need that range. And so, yeah, we always knew we needed the range of flying on a wing. And we decided to launch without having developed that system yet. Really just says how we're wired. We want to get out into the real world fast because we just know when you're in the real world serving customers, you're going to learn a lot of things. just can't learn any other way. And so we wanted to get out there earlier.

Yeah, and that hardware was there. And the teams that spent all this time developing that hardware were like, we want to see a fly on the wing. And, of course, we've been doing the test sites for a long time as we've been developing that capability. It is one of those things where you kind of develop it and then wait. And then once you can get, once you can, yeah, I think one of the things, you know, you're talking about regulations and safety like that is also part of our ethos.

And a difficult thing in a startup is we hire people who have like inherent urgency. because if you set a deadline on safety, you can end up in a really bad situation. If you're like, cool, we must ship this on this date. Some of the stories you hear about of AV companies that have hurt people in the past, they take that mindset and they try to, and then they'll fool themselves into thinking they're ready,

as opposed to saying, no, no, no, we set a safety bar and we decide how we're going to measure ourselves against that safety bar, and that's when we ship. It means your dates aren't quite as predictable, but you still need to move fast, and so you need people, with a very inherent sense of urgency to work through those problems and get there,

as opposed to a more traditional, like, you know, we have a date and we're going for it, management approach. So what was the range prior to the wing and then of a typical drone, like assume good conditions, like how far do they go and how long a time? And then you said 10x, so I can do the math. Yeah. That's a huge win. Yeah, great.

Yeah. So we're doing about a mile and a half hovering. And we'll be able to do, right now we're at about five miles on the wing. we'll be able to take that to about 10 miles over time. So, again, as we continue to validate and sort of work our way up to it, once we feel confident in it. And I assume each drone launches from a location

and then has to return to the same location, at least until you get multiple hubs in a city or something. Yeah, yeah, that's actually a software feature that's coming in a release next year is that ability to go from one dock, go make a delivery, and then dock somewhere else. But yeah, you're exactly right. We don't have the density of docking locations yet to need that feature.

So that cuts your range in half because you have to get out there and you got to get back. Exactly. Okay. So when you say five miles is that if I live five miles from your facility, do I get deliveries or I got to live, I got to be two and a half miles? No, you can live five miles. Yeah. So once we have that, we can dock at a different location nearby the delivery site. Yeah, we can do more than 10 miles.

Right. That's actually an interesting thing. We've learned over the years. It's way better when you're working with these partners. to talk about a conservative range than like where you're going to go in the future because it's just it's so complicated to talk about that when you get into the details of your terrain and your physics and your local weather and all that stuff it's like no no we just talk about this little circle and then they're thrilled and we can do more than that right I was just flying my drone the other day I had a little DJ I flip and I was flying it too far away like slightly too far away to where it was telling me to come back and I'm like yeah I'm coming back so I start flying it back and then the wind picks up up going against it on the way back and i'm sitting there thinking like oh man it's just not going to make it back you know because the the battery percentage continues to go down and it's still 1,200 meters away and it was very dramatic if it did make it back to the house thankfully but

just barely i got to imagine that's a stressful you know we're talking about range anxiety with our new EVs i'm sure you probably have extreme forms of range anxiety with your because these are expensive machines right what is you know what's an all-in cost on one if you can share that to know than manufacturer. What are we talking about? I can't show that specifically, but it's lower than you would think. And this kind of, this is one of the reasons we develop our own drones, both for this range problem you're talking about and for the cost. But for the range, like take our fixed-wing platforms. This is what we do these very long-range deliveries with. There's no hover capability,

it just flies like a plane. We advertise basically a 50-mile service radius. But like on a, if it wasn't windy and there wasn't a mountain in the way, it could easily do 100-mile service radius. So we literally have twice as much energy as you would need nominally so that we can make it back on those windy days reliably. And that's just really important because once you start serving a hospital delivering blood, you can't be like, oh, it's too windy today. Sorry, guys, we don't serve you. We only reach the people closer. It's like, no, we turn you on and we want to serve you all the time. Yeah. Does anybody get underwhelmed by the range when you say five miles? Now, I'm not thrown stones here, but I'm just saying, like, I know you're innovating, but does anyone ever go,

That kind of seems small. It all just depends on the use case, right? Like this is like that, the, the 10 miles was developed going really deep with our health partners and exactly on all the use cases that they want to use the drones in metro areas. And of course, when you're going out of metro areas, that's where the 50 mile range drone comes in handy. And all of this has been developed just, you know, basically technology, second, customer first. So deep with the customers, you know, we even have caught. Well, like for this precision delivery platform, we had contracts with partners, you know, in the while we were still in what we would call like the conceptual phase of that project, right?

Nothing was locked in yet. And having those contracts with the partners gets them to give you, like that gets them invested enough in us to give us to give us the feedback in the data to make sure that we make something that's to be useful for them. And so, yeah, some people get overwhelmed, but we just have that confidence because we spent so much time in these use cases, analyzing them going deep with our partners. to just have confidence we're making a platform that'll that'll serve their use case as well. Well, friends, I'm here with my good friend, Chris Kelly, over at Augment Code. Chris, I'm a fan. I use Augie on the daily. It's one of my daily drivers.

Now I use Claude Code. I use Augment Augie. And I also use Amp Code and others. But Augie, I keep going back to it. And here's where I'm at. I feel like not enough of our audience knows about Augment code. Not enough about Augie, the CLI. It's amazing. I love it.

What can you share? Yeah. We often say Augman is the best coding assistant you've never heard of. And that's both frustrating as to someone that works there. And it's like very proud of the work we've done. But also like inspiring. Like we want to go and sort of punch above our weight. We just like we aren't anthropic and we aren't open AI.

And so the quality of the product itself, you know, with our context engine, once you do touch it, people are like just blown away by that. And so like that keeps me going every day. So not to bear the lead here, but this is a paid spot. You are sponsoring this show to get this awareness. Now, at the same time, we're selective, and I love to use your tool. But there is in the world. So a lot of developers look at the space and they say, okay, well, how long can this work?

How long is this sustainable in the case of cursor or a windsurf? Or you pick the name and you think discounted tokens, help me shape a lens for our audience. I think it's a lot of awareness, right? Like, Cursor got a lot of publicity early on for like fast revenue growth, which well deserved. I think, you know, frankly, some of the media got the, gets the story wrong in that like, if I gave you a $1.50 for every dollar you sent me, I'd be the fastest growing startup in the, in the valley. And so when you're selling discounted tokens, yes, of course you're going to grow very fast, but all that money plus more goes to the model providers. So I think the real story is the story of Anthropic and, you know, being an API provider, I think the market has just moved so fast and there's so many pieces of competition out there that it's just hard to get noticed. So friends, I love augment code and I love using Augie. And I highly recommend you use it. I love using Augie. I can hand Augie a well-defined specification, a well-defined pep, as I call them in my world, an agent flow. And it executes flawlessly.

So the cool thing about Augia that I love most really is that context engine and I can hand it a task and it can just churn away on my well-defined plan and just never bother me and accomplish the mission. It is so cool leveraging the latest models, the context engine, and all the fun things behind the scenes in that awesome CLI. So yes, go try it out, augmentcode.com. Right in the top there is a CLI icon, a terminal icon. Click that. install it, and change your world. It's going to be awesome. Obmancode.com.

And also by our friends at Framer, you know, most design tools, they lock you behind a paywall. Well, Framer flips that script. It is a free, full-feature design tool that does something most site builders cannot. It's actually designed for designers. Framer has already built the fastest way to publish beautiful production-ready websites, but with design pages, they've defined and redefined what it means to design for the web. This isn't a Webflow clone or a WordPress competitor. It is a true design platform, vectors, 3D transforms, gradients, wireframes, all the tools you actually use, and they're all free.

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It's from the end user perspective, but then also as we go, maybe explain the software systems that have to support that because I'm fascinated where software meets the real world and there are all sorts of weird situations that you have to account for. I know there's an app. I assume it's similar to a DoorDash kind of a thing where I'm going to order, let's just say I'm going to get a Chipotle burrito because I already cracked that earlier. And I'm a fan, not a sponsor, but I'm a fan of the old Chipotle burrito. And I know it's under eight pounds, so it's going to fit into my zip. Unless I get the double. I don't know. Can you get a 10-pound burrito from Chipotle?

Maybe not yet. Someday. Someday we can dream. I open up the Zipline app, I assume, or do I open up the Chipotle app? Maybe that's where we start. Do I start in the Chipotle app? Do I start in the Zipline app? Where do I start?

Yeah. So soon you'll be able to start in the Chipotle app. Today you start in the Zipline app. And depending on where you live, if you live in the best place in the Dallas-Forth area, you open that app and you're going to see a bunch of different storefront. You'll see Walmart, very soon Walmart Pharmacy, you'll see Bluebell Ice Cream, you'll see Chipole, you'll see, well, just a whole bunch of great restaurants, Buffalo Wildlings, and others. And, yeah, you pick what you want. Right.

You know, that part of the experience feels a lot like, feels a lot like DoorDash or, you know, someone driving the thing to you. Then, you know, they'll start prepping it. Our partners will prep the food or prep the order. and then we put it in this thing that we call a zipping point, which is this fun little kiosk you put the package into. And that little similar to how we deliver, the drone stays up high and the delivery zip comes down 100 meters, grabs the package out of the kiosk and brings it to you.

And this is where things are very different than like delivery by car. We actually have to warn people, you know, hey, your food may be too hot to eat. So we deliver so fast that like we've had people be like, oh, yeah, I just assume my, my, my hot wings would be soggy and they just stuck them in their mouth and burnt their mouth because they're just like they're so used to how long it takes for deliveries to happen in the old-fashioned way that when it takes only a few minutes it's and it's well insulated and controlled the way

we do it like the food's actually fresh and sometimes very hot still yeah that's a great problem to have so show me the chipotle side like from your integrators your restaurants and i'm just picking on them because i know they're a partner of yours obviously there's going to be a bunch of them. But imagine that I do order a Chipotle burrito out of zip line. I assume an API call kicks off over to the Chipotle and makes the order and then they have to like somehow tell the zip when it's ready. Like how do they do that? With Chipotle, they use their software system the way they use it for any order, right? If you're ordering over the counter or you place an order to the Chipotle app and it shows up on their they call their make line. That's that's the people actually

like put the thing, put the order together. So they're going to make this like any other food they're Our system gets hit over the API, so we know when they started that, and we know when they're done. And then when they're done, we'll put it in that kiosk, dispatch the zip, the drone over to come get it. It'll come pick it up. That's usually about a minute or two after it's ready. And then we deliver it anywhere from one to five minutes later, depending how far you are, away you are. We deliver it in your yard. And, yeah, we have a fun little app that shows you the drone coming.

And it gives you that really super precise ETA. I think one of the things I didn't appreciate about this kind of delivery that's really cool is, like, just how human-centered it is, right? Like it's as opposed to like whenever that driver is going to show up and sometimes it's like, wait, why do they take that crazy route? That's crazy. You know, if my kids are hungry, we tell you like, no, no, within a minute of when we're going to get to actually show up and you can walk outside and pick it up, you know, it's just there. Now, can you hold your hand out and it'll put it in your hand? don't recommend it that can be a cool feature there can you come on put your hand out you know we'll put you can have a third little so you have like the big zip then the little zip and then like

a hand that comes down you know and just drops it a little bit lower and you yeah this is you know the the the way we talk about this is we don't want people to do stuff like that but we test in case people do that kind of thing so i it's delivered into my arms and i love it it felt good didn't it It felt very, it felt special. Do you like pause the delivery then when you detect like anomalies you don't want to be present in? I assume that's probably a phrase or terminology, like a child standing there underneath your target. Yeah, it's actually kind of funny that originally we thought we, so we do a little bit of avoidance. So like if we're coming down and we see the person standing right there, we'll scoot over and deliver next to them.

They keep scooting closer. You keep scooting further. Exactly. If you do that, like you can make a really fun game for kids that we don't want to be a fun game. You know what I mean? Yeah. Like we don't want to make this to be a game of like, oh, it turns out if you chase this thing, it'll become a game and then everybody wants to chase these things and we can't deliver.

And so basically what we found to work really well is just slow down. One of the things we like about that little delivery zip is it's very benign, right? If someone touches it or something, it's not a safety concern. And so, yeah, we just slow down and keep going and make that delivery and get out of there. And basically the way I think we talk about is like we'd be boring. and so so that so that we're not uh creating a fun game for every kid uh as a parent of young kids like i know like i you know i brought them to the test site too and i can see like i know exactly what if you uh if you did that avoidance with my you know my three year old she would have

so much fun and we would never make deliveries right well it might be a consideration for down the road of getting like even more human centric is like allow the orderer to to set like a mode like do i want to have fun with it do i just want my food because not that you always i know you guys want to save energy and battery and all that but like you're already pretty happy to have your food delivered from the sky like i can imagine like that's a moment already but like to have a little bit of a personality with the thing i might take it over the top to where it's like it's the only way we're ever going to get food is to just give us you know that's why i think the handoff would be actually amazing but yeah too dangerous perhaps to for sure today tomorrow

I love that idea. And your head is exactly where my head is. And to me, it's not a question of if it's a question of when. So I look forward to it. Well, someone will always mess around too in those scenarios. But did you mention it all when time of day you can deliver? Is there like danger zones where you can't deliver in the evening or after dusk or is there light concerns?

Do you have lights on these things? Yeah. Yeah. So we can deliver anytime. Yeah, we deliver day night. Any time. So 24-7. Yep.

Yep. Wow. Okay. Right now, that's just. limited by our partner hours. And most of the places we operate in the world, we deliver 24-7 with the health systems. And then dependent, like, and it's always interesting to see, like, you'll work with a restaurant partner. And all of a sudden, they'll realize just how much volume we're adding to their normal business. And they're kind of like, oh, wait a minute.

Like, if we operate with you all, like, and you can go 24-7, you're already operating 24-7 for other people so we could do, be open at night. And, you know, there's a, there's a huge part of our economy that, you know, works at night, right? Night shift workers and things. like that. There's, there's a, there's, uh, yeah, well, we know that because all the health people we work with, they work, you know, 24 hours a day. But obviously, lots of manufacturing operates 24 hours a day. And a lot of our partners are seeing like, wow, there's a, there's a whole part of commerce they can, they can, they can address and a big part of the demand they can address by, by, you know, operating more hours. And, and obviously partnering with us, we can do that in a way

that's people really like. And so, yeah, we're, yeah, it's really cool. I, you know, get whatever you need 24 hours a day. You know, I, you know, I, you know, as a parent, like, just, It's simple things, right? Like a kid spiking with a fever at night and you've ran out of the medication, right, to bring that fever down, right? Like, drag, the only thing worse than having a kid with a fever is taking your kid to, like, a 24-hour pharmacy at night to go grab that stuff you don't have. Yeah, Krupp is a big deal for parents.

I know that we've battled, you know, several late-night ER visits for Krupp. And generally, you know, I don't want to go into like the medical scenario of here. But, like, basically, you have to be seen by some sort of medical professional to get a special medicine that is for croup that sort of helps your vocal cords and things, you know, reduce or whatever. And it's kind of a pain in the butt because you kind of know as a parent, you're like, you know what, I'm Dr. Mom or I'm Dr. Dad. Okay.

I know I've been down this before with my child. I just need that particular prescription. So if you had a relationship where you could do telehealth, which is super popular, you know, we would not have to leave the house at all if, if that were a scenario, we can make a phone calling or telehealth. And, you know, maybe 10 or 15 minutes later, we've got a delivery from Zip that says, hey, here's your recruit medicine. You'd have to leave the house. You can do it efficiently.

You have to be on the roads. I mean, like, you talk about the efficiencies and, you know, environmental effects. Like, we don't have to drive. We have to lose sleep and maybe ruin our day the next day more. So we got the medicine. And there's so many, you know, unintended consequences in that scenario that just make it so interesting to think about how you can reorient the world around this being effective. thing. Oh, totally. I mean, Adam, I'm so excited about this. And we have, we have, we have, we have partnerships now with about a dozen regional U.S. health systems. And, and all of them

have this use case in, in that partnership. They have some other ones as well, but this is, they call it the physical side of telehealth. It's, yeah, telehealth is obviously becoming a really, you know, predominant thing here. And like you said, for so many things, like, there's, there's a physical side, too. And so if you can get that inhaler delivered right away or that, you know, that that crew medication delivered right away, it's huge for the. family. It's huge for, and you're touching on something, too, that I didn't appreciate when starting Zipline that now I appreciate a lot is just how much health affects basically the economy, right? Like you mentioned like just, yeah, the parents not being exhausted the next day, they're going to do,

you know, their work is going to be better. And like, and they're going to be more productive in the economy and just keeping people healthy in that sort of preventative way is something that I've become extremely impassioned about because I've just seen this like cause and effect in my own life and in all all the patients we serve around the world, just how powerful that is when, you know, a parent doesn't have to stay home or a parent doesn't have to, you know, basically be affected in their professional world by, you know, what could be a very preventable sort of health, you know, some of these things kind of feel like inconveniences even, right? Blood, obviously, very acute, big life-threatening, but like a lot of this stuff, it's just a little bit of convenience just

goes a long way for people staying healthy and productive. Have you, I imagine you probably have, but have you imagined a world where Zip is at scale, where Ziplines at scale and you don't have a couple hundred in production. You have, I don't know, half a million. I don't know, a lot, just an astronomical number that you don't even consider today, how the world changes, maybe even how we see the world. Because, like, I can't imagine, having it imagined or experienced a Zipline delivering something to me. I'm sure to be cool once I have it in my own life.

once this kind of technology, whether it's you or just generally like flights isn't only by only owned by United or Southwest, for example, you know, when this kind of delivery or scenario becomes ubiquitous, have you imagined that world and how that changes the world? Yeah. I mean, I'm super excited about it. This is part of the reason we spend so much time on things like making the system silent is, you know, one of the things we know is like I don't want to notice these things, right? Like, you know, just like a bird flying over your house. How many birds flew over your house today? You have no idea. Why? Because we don't hear them. And we want like, we spent a lot of time on things like that because we just know that, like, as these things scale, there's certain things that we've learned from our experience that

just matter a lot, like it being quiet. So there's certain things like that that really, we spent a lot of time on to make sure that this is, when this scales, it's a world we actually want to live in. And then, of course, yeah, the net effects of this kind of instant delivery. I live in a small town here in California. And, yeah, like, there's just two bakeries that are just like, like, They're so excited for when they get their little kiosk and they can just, you know, send out fresh bread in the morning to people.

Yes, I was just thinking about that. Timely deliveries. Exactly. You know, and there's so many things on the personal life side like that, like getting fresh bread delivered. There's so many things on the work side. There's so many jobs that just require stuff. Obviously, doctors and, you know, the medicines, it's so obvious.

And, you know, auto mechanics, it's so obvious. Yesterday, just yesterday, my HVAC system in my house went out. A little blower had failed. and the guy came out, and he's like, I'll be back in two days with the part. And it's like, no, no, no, you'll deliver the part right while he's there. And I looked it up the part he needed. It weighs less than eight pounds. We can deliver it.

Did you deliver it? No, we don't serve that area yet with, with HVAC parts. Oh, that would have been so cool. If you're like, hey, I got a solution for this. Hang on. There's no delay. I got the part. Yeah.

Even just talking to him about his business of like, you know, this is an independent guy who does a lot of these kind of HVAC repairs and, you know, fixing heaters and stuff. And he said, his customers, they hate it when he charges for these visits just to figure out what he needs, right? Like, you know, he could just fix it there on the spot. Like, not only would he be able to serve so many more customers, but those customers would be so much happier. And he has somebody who, like, hates that part of the customer, you know, conversation of like, I got to charge you for the 200 bucks for just to come see, come by and see this thing. He'd love that to go away because he hates that part of his job.

And anyway, there's so many pieces like that. I just can't wait to see what people imagine and how they will use it. Because every country we operate in, people are using it in ways I never expected. And I'll tell you one fun story from Dallas. So a couple, this summer, we were looking at our usage data. And most people would either order one address or order to maybe two addresses. But we saw this one person who was ordering to a different address almost every single day. You're like, what is this?

What's going on here? And so we send this user an email saying, would you share, like, how you're using the service? And so this is a postal delivery carrier. And his New Year's resolution for this year was to eat healthier. And he was getting a salad delivered to him along his route every day for lunch. And I just like, anyway, I just loves that. I would have never guessed. Yeah.

I would have never guessed. We call him the Johnny Apple seed of Zipline. You can see. What about gifting? It's a great way to gift is like, just, hey, call somebody up. Go outside. Why? It's like, I got, there's a delivery coming for you.

And like, this thing just drops a gift out of the sky. Oh, we did this. So we did a really fun thing for Easter this year where we basically loaded up the little delivery zip with a bunch of Easter eggs, no packaging, just Easter eggs. By the way, one cool thing about what we do is it doesn't require packaging. That's another part of the future I'm excited about. None of this, you know, cardboard jungle. We all have in our garage from Amazon boxes.

Oh, my gosh. Save me. And so we put a bunch of Easter eggs. in there. And it was really interesting to see how many, we had grandparents in other states outside of Dallas who we were just delivering in Dallas place orders for their grandkids to deliver like this, you know, pile of Easter eggs into the yard. And the kids loved it and the grandparents loved it. And we just sort of this out of state gifting. It was so cool. And there's so many things like this that I can't wait to try. There's so many places you can go with eight pounds.

But at a certain point, that becomes your limit. I don't think you guys are anywhere near that point and we all know that but at some point have you thought okay what's the next like where's the zip line jumbo like what's the weight that we need to go to like expand to a new set of things and then what do we need to manufacture in terms of drones to actually get that done i know there's a long range one is there like a heavy weight one or is that just too far too far down the line to care about it's a great question you know eight pounds gets us really far as you're living to something like 80% plus of amazon packages are less than eight pounds you're so many of the use cases that we are really focused on, like, you know, meal for family of four

from almost any restaurant is less than eight pounds as an example. So, and then, yeah, if you need more, we just send two deliveries. I mean, back to back. And yeah, it's two little bags of food and it's no boxes, none of this other stuff. So I'll be interesting to see how it evolves. If I was a betting person, I think we will increase our payload over time beyond eight pounds. There's a good chance it won't go a ton past that, maybe 10, maybe 12 pounds. And really what it comes down to is like what doesn't fit right you know once we get to that scale we can deliver a very full bag of groceries uh at that scale and um the advantage of having one platform as opposed to like different variants is we can drive the cost down further and further just from scale and so as the

cost for delivery goes down there's a chance that we'll never be able to compete with like if we made a drone that could deliver like four bags of groceries at once that will always be more expensive then deliver four of the of a smaller drone delivering four bags just you know 30 seconds apart onto your you know picking table in your backyard um yeah and then then there's yeah there's stuff left out right like the flat screen TVs right like it's obviously can't deliver those um i was thinking about the tv i was like can you bring the tv to me i'm just kidding i was not thinking that that's cool yeah and so yeah as we we've been looking at the of the car the partner will be launching within Dallas, you know, we can deliver something like 90% of their car parts, but obviously 10%

we can't do. And yeah, we think about that. And we will, Zipline has always just kind of been like, you know, customer first. So once we get the data, once we get the, once enough customers ask us for the same thing over and over again, and we go deep with them, if we have conviction that there's a thing that will work for them that will make sense for the business, like, yeah, that's how this precision delivery, you know, drone inside of a drone system came from. So, yeah, we'll do more things in the future. Is anybody else doing this? Like, who's who's the southwest to you're united i know that amazon announced the thing like you said years ago about drone deliveries and then that got canceled or sideline or whatever maybe it's happening but

i hope there's other people that are tackling the same problem because we want diverse and unique solutions and learning from each other so who else is working in this space that maybe is either your competition or even that you admire what they're up to yeah so amazon has started doing some deliveries quite limited as far as i understand google has a project called wing I admire a lot of how they're thinking about the problem, and we collaborate with them a lot on some of the projects with the FAA. I really like how they think about some aspects of safety, for example, and things like that. I admire that a lot. There's a fair bit out there.

I think the, you know, I'll be honest, I don't think a lot about the competition. For us, it's just about the customer and just like, what can we do? How can we do better every day and really measure ourselves on our own velocity towards the lighting those customers? Yeah. What's 2026 going to be about scale? Other things? Yeah. What's it going to look like?

It's a lot about scale. So it's our long range platform is scaling around the world. So that will continue in 2026. And yeah, this precision delivery platform is scaling. Yeah, it is scaling really fast. And so a lot of what 2026 is about is building up the supply chain capability to manufacture faster, building all the internal muscles to launch the charging sites and things like that to enable scale. Yeah.

Yeah, and just getting better and better at that user journey you were asking about of like, how do people order it and how does that all work for all the different use cases? We found you can't be super generic there. Different use cases need a tailored user experience for it to really be magical. And so we'll we spend a lot of time there as well. How do you pick your next city and why is it going to be Omaha? It's going to be Omaha because. Yes.

Yeah. Yeah. It's really about the testing and validation story. It's so, you know, I can't announce the next city, but we'll be launching our next cities in the first half of 26. Part of how we choose those cities is they're very similar to the Dallas-Fort Worth area, similar in terms of weather, similar in terms of terrain, that kind of thing. And that's because that's what we validated the system for. In parallel, we're validating the system for, you know, expanded weather, more complex terrain, more complex you know, smaller yards, all those kinds of things. And so, you know, basically once we validate the system to go into metros that aren't like, you know, we refer to like the Sunbelt metros, then we'll move into these other metros as well.

Yeah, it's really fun. We have a test site up in the Cascades where we're doing a lot of testing to validate the system for, you know, for metros that aren't all like Dallas, Fort Worth. But, yeah, it'll be sunbelt metros first, and then we'll keep going from there. Yeah. You've solved a ton of technical problems to get here, and now you're trying to take it in lots of places. What are the big technical problems that are ahead of you? Like if you had a checklist as CTO, like here's the things we need to solve. Like what's unsolved for Zipline?

Almost every front, there's more work to do. You know, I've been thinking a lot recently about weather forecasting. So we spent a lot of time, right, validate the system for certain weather. But then, you know, when you operate, you got to know how, like, how do you not go in that weather? You can't go in. And that's harder than it sounds to do with scale. there's some easy things like wind limits forecasting that is fairly straightforward but there's much more complicated things like icing conditions right now we're testing to

understand exactly what level of icing conditions we can handle and how to handle that well but there will be a limit there that we're going to need to forecast forecasting icing conditions is notoriously very hard to do this is like when you have fog and clouds in cold weather oftentimes you fly through that and just cover your aircraft and ice and another good example is lightning conditions. We are currently chasing lightning with our mobile test rigs right now to really understand how does lightning interact with the system. We think it won't based on analysis, but lightning is one of those things where you don't trust the analysis. You got to go in the real world and get real amounts of data to get confidence to that analysis. So there's a lot

of work both on the capability side to expand the kind of weather we can fly in and on the weather forecasting side. There's a lot of work there. There's a lot of work in the airspace side of just how do you manage this fleet at scale? You were talking about going from one charging point to a delivery, then landing at a different charging point. There are some things there that are just way harder than they sound where you can end up with your fleet kind of like migrating organically in a direction away from where the supply is and you got that can't happen.

Like a beehive. They're swarming. They're going somewhere else. Oh, no. Exactly. So you've got to manage that carefully to make sure you can keep delivering for people. So there's a lot of almost every front. of what we do at Zipline, there's a reimagining happening for the scale, for new feet, new

capabilities. We've talked about some of these health care use cases. There's a lot of new capabilities we need to build both into how we operate the drones and into the tools that the humans use to, on the health care side, system side, and on the patient side to use the system. So there's all kinds of exciting things ahead of us. I think of us as like, we're at the very beginning of this journey, and there's a really exciting roadmap ahead. I love it, man. I'm excited. I think that, I love that there's, like, one of your teams is, like, a group of storm chasers.

And they're just like, our job is to find lightning in the world and then go fly these drones up into it and see what happens. Like, what you do for work. That's what I do. Storm chaser for Zipline. That is, that would be a rad job. Yeah. It's a badass team. And they're hardcore, too, because, like, chasing storms, when you have basically a big old trailer, we have these docks mounted to a trailer that they use.

And, you know, obviously, when storms, it's just hard to get around in these places. And it's really cool. how they work and their dedication. Is there a manual override on those things that you could just take over if you needed to or no? Yeah, but it's very high level, right? It's basically, you basically have three buttons, a button to tell it to go back and dock,

a button to tell it to loiter right where it is, like stay put, and a button to deploy that whole aircraft parachute and land where it is. That third button we've never pushed, but every regulator wants it. And then mostly it's the other two buttons. You can't jump in there and stick fly the thing.

And it'd be extraordinarily hard to. Like, these aircraft fly themselves in a sort of superhuman way. And so like they're, they're, you know, how fast they make adjustments, how fast they can self-diagnose and handle faults and still fly nicely. Yeah, if you try to put a human in a loop of that, it would be extraordinarily hard to do. I was actually just watching a video from Mark Rober. And it was a goalie. It was an AI goalie, essentially.

And I forget the soccer players. name because I'm not a soccer fan to that level where I know the person's name, but I imagine it's probably messy eight, like somebody who's super famous. And they were going against the goalie and they could not beat the goalie because the reaction time was just so uncanny, like how fast they could react. And I take that kind of example, which is sort of a fun experiment, which Mark Rober is a scientist and he's super serious. But at the same time, it's meant to be fun and not really an experiment of seriousness on a large scale and how what to what level your advancements may be well beyond that to to truly say what you say because I'm sure there's a lot of people

say you know can I hear you saying that but you know I don't believe it you know because I can't believe it until they see the truth of the superhuman ability to fly these aircrafts you know I just think back to the maybe the mark rubber thing that soccer goalie that was AI totally demolished the human could not beat the AI goalie. Yeah. It is surreal to see these things handle the, when I saw the first, I mean,

all this fault tolerance we test extensively, right? And you know the fault, like so my face is a whole tolerance, like one rotor fails and the system handles it and goes back in docks. When that is working well, when you're watching it happen, if you don't know what happened,

you won't even notice it, right? Like, you know people like with binoculars. like watching that thing because the only way you're going to see is if you actually see the propeller blade, that one propellate stopped spinning. But the aircraft like handles it so seamlessly, it barely moves. And if it's windy at all, like it doesn't move more than it does normally in the wind. And I think there's, this is one of the exciting things about autonomous systems is they can, they can get super robust, which means we can operate and serve customers and deliver to patients

and hospitals in all kinds of really crazy conditions. again, the conditions that, you know, flying low altitude in these storms, nobody does it. Like, and I want to say nobody, I didn't even realize this when we started Zipline. I thought like at least Medevac helicopters and this kind of things, Coast Guard must do it. And we ended up calling some of them because we were struggling to like figure this out. And we're like, cool, do you have any data? And they were just like, oh, no, we stopped flying those conditions in the 70s, way too many people died. And yeah, you can only do it if you use an autonomous system.

And yeah, it's quite wild to see these systems perform because they're just like they're so fast and so superhuman. And yeah, and then they can get these deliveries through these conditions that like, if you're on the road, you're, you know, some of these conditions are so crazy. If you're on a good road, you're kind of feeling like I should not be on this road, but the drones are all right. Yeah, I used to listen to the Bill Burr podcast quite a bit, don't anymore, but he is a hobbyist, but a trained helicopter pilot. And so he would chronicle some of his, you know, it's just him talking about. talking for an hour. So he needs a funny person to listen to talk. So it's enjoyable. But he would chronicle some of his efforts at just flying a helicopter. And I knew it was like, I mentally understood that it was difficult, but like hearing somebody try to learn it and like the maneuvers

they're going through just to get down the basics of flying a helicopter. It's so fraught and dangerous to fly helicopters that in adverse conditions. I mean, it's a death now. And we know that we've had, you know, famous people like Kobe Bryant dying, helicopter crashes. just because of fog or because of a bad systems. And humans are struggle and have to have extreme training to be able to fly those things. And computers can fly them so much better now that it's like, why even put a human behind the sticks, so to speak. Yeah, absolutely.

And I think there's, yeah, I mean, what our system can do literally in the blink of a human eye is like basically handle, detect decide handle almost everything that can go wrong, but faster than a human blinks. And that's, you know, that's powerful for making autonomy scalable and safe. One last question for you, Keen, what's your tech stack? So if you were to describe, I know you have lots of different tech. So like if you were to pull out all the tools in your CTO, you know, tool belt, programming languages, frameworks. You know, what, what's Zipline built on?

Right. Yeah. I mean, for high performance stuff in the cloud, we like go for almost everything on the aircraft is moving to Rust. you know there's various parts of the tech stack right for almost every part of the tech stack kind of has its own little world a lot of we've built our own in-house simulation system we call Phoenix that was how we do a lot of this basically a lot of the simulation and testing yeah you know we the yeah boy the tech stack is is broad you know I worked a lot on Ross the open source robotics platform back in the day and everybody always

asked me of like, cool, you must run on Ross. And I'm like, oh, man, we don't. If Ross 2 had come along early enough, we would have. But unfortunately, we kind of went down that path before Ross 2 was ready for that. Yeah, we use open source where we can and of course contribute to an resource where we can. I'm a big proponent of open source. And one of the things we actually, on the tech stack fund, we spent a lot of time on is basically the future of autonomous flight, even today in Dallas, we share the airspace with some of these other drone operators we mentioned. And I think of that the no one really knows how autonomous flight's going to scale in the airspace. And I can tell you what we do today in the airspace is not going to

scale. It barely works for the scale we have today, which is very low compared to where the future is going. And we, you know, there's there's a lot of need for the, for folks in industry and academia to like bring the best ideas to the table, make sure the best ideas win so that we are both scalable in the airspace and safe in the airspace as we scale. And so Zipline's work. working on a bunch of projects like that that we have or intend to make open to the community so we can kind of prove it internally as like, hey, this is how our drones, you know, don't collide at scale with each other and make those technologies available so everybody can, you know, share that. That's a big part of the tech stack that we think a lot about because, you know, well, again, I just love the, to me, the open source mindset comes from this thing of like, hey, we're all on this together. And as I think about the future of their space, we're all in this together. It's going to win if it's going to be great for Zipline if all companies that need to use the airspace and all users of the airspace can use the airspace safely.

But, you know, the future of autonomous flight is still to be figured out. And we're spending a lot of time on that. Do you see a world where there's some sort of open orchestration communication channel where you're not just detecting objects and avoiding them, but maybe you're actually publishing your future path? And so other systems can know, like, there's zips going this way and that. And so I can avoid those paths. Yeah, absolutely. So today there's a version of that we use in Dallas. And it's not live.

It's done before you take off. So basically there's a federated cloud-based system where the different operators, systems talk to each other. And basically, it's very rudimentary today. You kind of think of it a little bit like a game of battleship of like, okay, I'm trying to share my intended path in the air. sort of a tube in time, and I share it with the others, and they're kind of like, nope, that collides with something I've already reserved, and then you try to find another tube, and then it finds a tube, and then you're expected to stay in that tube about 95% of the time.

Not very scalable. It's not a very efficient way to use the airspace, which is, you know, plentiful. Internally, we do, we share our aircraft share information live with each other over a point-to-point radio link where they share their intent of where I'm going in the next 10 seconds. or so. And they do that also over the IP network. I can't announce the partner yet, but there's a commercial grown operator in Dallas. We're going to be announcing a partnership later this year where they'll be using that same protocol so we can share the airspace without those big reservations. And that's the net, to kind of explore, hey, is this more scalable? All right. Can we build up the data and then show with the rest of the regulators and

industry to kind of bring everybody along and make the case for what we think is a better idea than what we have today. And then we'll move to that idea. So yeah, I think, I think what you're describing, I think it's going to be the beginning of where we go with this. I think there's going to end up being a fair bit of structure, a lot of real-time sharing to make sure we use the airspace really efficiently and scalably. It's like DNS in the cloud, basically, you know, in the sky, literally the cloud. It's a pluralized, not the Internet cloud, as we know it. But it's kind of like that.

It's like a phone system in a way or a route system or a flight path. You now have to have predefined or known things. And it's like, well, we have, you know, these coordinates and we know where we're at in the world. So maybe they're logistically, you know, like that or something like that. But yeah, but constantly changing, yeah. Exactly. Yeah, we spend a lot of time talking to the original folks who created ICAN, which created the DNS system. So, like, you know, how did that actually come to be?

Because in some ways, it's kind of a miracle, right, how open the Internet is and how undoubtedly it evolves. And like, it's like, all right, cool. We want to learn all the lessons from that because, you know, we really want the future of the airspace to be similarly democratized and open and innovative. involving right so you're studying dns to learn how to do things in the in the sky absolutely yep yeah and not just the technical layer of dns but also like if you believe i can the international is a corporation of names and numbers i think anyway it's basically the people behind sort of the internet that like agree internationally of how it's going to work um just because like they figured out how to how to be a group of people that doesn't make bad decisions you know right and uh it

we want to learn from that as well because I can see if you don't get the right incentives and the right people and the right mindset and the right kind of structure I think it's really clear how this this kind of gets stuck in gridlock and doesn't evolve and innovate right so when you operate on a 2D plane everybody gets one place so like my house address leads to one place now there's many paths to that place so you can alternate routes and that's all well and good but on a 3D plane if you have conflicting paths you How feasible is it to just change the Z-axis and say, well, we're going to fly five feet lower than we were going to, and now we're just completely have free airspace? Is that, like, foolish thought? Is that legit thought? No, that's exactly how our drones don't hit each other. Okay. So they're just like, well, I'll go up or down a little bit. Exactly. They should, they basically, there's distributed algorithm.

They share their 10 seconds out intent with each other. And there's a distributed algorithm based on what they hear from the people around them that they'll adjust their course in a way where we get an immersion and behavior you're talking about of like, okay, great. You end up with that nice passage very efficiently and dynamically. Yeah, I think you're describing exactly how this needs to happen. But the challenge is it has to happen in a very robust way, right? It can't be like, oh, if you can reach a server on the cloud and your cell connection is working and the server is working and everybody's talking at the same time and there's some central orchestration

that doesn't have a problem, then it works. We have a lot of experience to learn the hard way that You just can't scale that way. It's got to be simpler, and the aircraft themselves have to have many layers that they can do without any radio connections to things that will still give you layers of safety. That's really important. When you bring up layers, it makes me think, is there an advantage in formalizing around some kind of layering, vertical layering of lanes, so to speak? So you're not just having the emergent behavior of height, but you're actually pre-planning, like, well, I fly at this altitude. and this other company always flies at that,

and so we're pretty much cool. I think that'll happen, and I think it'll be more than vertical. I think it'll be more like sort of highways or lanes. And the reason in a lot of these, there's a lot of things you do to optimize for safety, but one thing you'll do is you'll avoid certain areas, right? So, like, yeah, if there's a class example is like a stadium, right?

If there's a game happening, you're just not going to fly over that stadium because why would you? Like, it's not that you're going to have a parachute landing there, but like you might, statistically speaking. and flying around it, Sicily speaking, is going to be great advertising. Like, here comes a zip line. Yeah. Yeah, we'll make deliveries there.

What is that thing? Not a crash. That's a parachute. And so everybody in the air, exactly, exactly. And so everybody in the air is avoiding similar things. And so you'll end up with this congestion, kind of going around these keepouts or these soft keepouts, as we call them. And sometimes hard keepouts.

So there's certain government places where the government is like, you cannot fly over this area. We consider that to be something you can't fly over. So these hard keepouts and soft keepouts end up funneling there. traffic into these places or I think you'll have you know you might in the early days vertical separation might be enough but in the long term it may be like yeah if you're going this way stay to the right and up high and if you're going the other way stay down low into the left and you end up with with this kind of literal kind of corridors through um that create more and more

efficiency especially when you have these kind of congestion force congestion um right so there's a lot of cool things that are that are going to be needed to really scale yeah so cool well Well, we've taken enough of your time. We appreciate you answering all of our questions. So much fun. I think this is one of the coolest things there is. So I'm both happy with you and jealous of you that you get to work on Zipline all the time because I just feel like there's so many hard problems.

There's so much benefit on the other side of it. And so congrats and good luck, I guess, on scaling out, scaling up. It's a fun place to work. Just yesterday, I came to work a bit earlier. I was on a call on my car. And I was watching everybody walk into the office. and everybody kind of has like a skip in their step. And I was just like, just, anyway, reminding myself how lucky I am to work in a place that's like that.

Where people are fun, the culture is fun, and the technical challenges are real, the customer challenges are real. And, yeah, and everybody's skipping to work is like a good sign that life is good. So, you're lucky. Yeah, great to talk with both of you, too. Really enjoyed this conversation. It was awesome. There you have it. Zipline. Pretty rad, right? I can't wait to try it out when they come to Omaha, and I'm stoked

that Keenan confirmed Omaha is the company's next destination. Just kidding. He totally didn't confirm that, but he should have, and I hope they do. Thanks again to our partners at Fly.I.O. To our favorite beatmaster in the entire verse, breakmaster cylinder, and to you for listening. We love it that you stick around all the way to the end. That's all for today. But we'll be back in your ear holes on change log and friends on Friday. Bye ya. You know, Yeah,