Inside Zipline's Autonomous System: 140M Miles, Zero Incidents

[00:00] I remember being in Rwanda early days and going out and meeting with some of the doctors and lab techs that we were serving and asking for them, like, you know, how's it going? What do you think? What's your feedback? Here I am kind of, you know, up and coming learning engineer thinking they're going to say something about. [00:15] the drone or some of these things. And the main piece of feedback that I received was, people get sick 24/7, why are you guys only open 12 hours a day? - Hmm. - Right? - Especially when you're delivering life-saving blood. - Yeah, exactly. And so that was a really key insight for me where it's like, man, [00:31] We found product market fit in a market where, yeah, our product wasn't great yet, but it was solving a real need. And so having that really beachhead market where there's a real problem being solved. And when your customer is telling you that their main feedback is they want more of your service, it's like that's a good sign. [00:47] Thank you. [01:03] Welcome, Keller and Eric, to the show. You guys have been working at Zipline for a long period of time. Keller is the co-founder, and Eric, you are in charge of systems engineering and safety, and we got... [01:15] Lots of things to talk about in this whole world of drones, drone systems, and how you guys started in this hardware space before LLMs even started. So we have lots of questions. Awesome. But you don't like Zipline being described as a drone company, even though you're probably the largest autonomous drone company in the world right now.

[01:35] I mean, we've always wanted to be an extremely customer-obsessed company, and the reality is none of our customers care at all about drones. [01:45] Our goal was always to build an automated logistics system for Earth. [01:50] and to approximate teleportation. [01:52] And all the customers who are living on Zipline today, they really don't care how... [01:58] If they don't care about the technology operating behind the curtain, what they care about is their ability to like download an app, open it up. [02:04] I, you know, see a huge number of different brands and amazing restaurants that they want to shop with and then click a button and have it delivered to them five minutes later. So we've always really tried to focus on the experience rather than on like the specific technology. Well, this show is about technology. [02:22] We're excited about that. What is the underlying technology behind ZipLine? You started in 2011. You pivoted in 2014. [02:34] before anything related to AI, robotics, foundation models, anything related to that. But you were before all of that and you're riding the wave of all of the things that have come afterward as well. Yeah, this was when starting a robotics company was the dumbest thing you could possibly do. You're talking to an investor in that time about... I mean, it wasn't easy and it was particularly hard because so many of those conversations... [03:01] I was 23, 24. Eric joined the company around that time. And we were starting to describe this vision of an autonomous logistics system for Earth that would be 10 times as fast, half the cost, zero emission.

[03:15] One of the biggest problems when we're trying to raise money for that vision was investors would say, isn't this illegal in the US? In fact, I think that that's a question you asked me when we started talking about this. We weren't allowed to fly beyond a visual line of sight. [03:45] value of the service would be extremely high. Zipline decided to launch in Rwanda in 2016, delivering blood transfusions directly to hospitals and primary care facilities. [03:54] This enabled us to have a use case that was so powerful that [03:59] A government would work very closely with us to make it happen. Make it legal. And to make it legal. [04:05] or at least make an exemption to their existing kind of regulatory framework. [04:10] And, you know, and then the other thing, you know, when it comes to how to think about ZipLine as a company, you know, when we launched in 2016, we were like, we have this really cool drone. We put all this work into designing this really cool aircraft that, you know, and it's it has all these great fundamental features. And when we launched, it was a total disaster. [04:26] Uh, because the reality, what we, what we learned in that first year for the first eight, we'd signed a contract to sign 21, to serve 21 hospitals. And we serve one hospital for the first nine months. And Eric in particular, like how much did you sleep during those? I spent a lot of time in Rwanda and sleep a lot. And then when you're in the U S like we'd get woken up at like midnight. Cause that's when the distribution center was turning on and it would, everything would be broken. Nothing was working. It was totally desperate, constant all nighters and working through the weekends because we'd

[04:56] that like the cool vehicle was the majority of the solution. What we learned during that first year is that the drone is 15% of the complexity of the solution. The physical drone, the hardware of it is only 15%. We had to build so many auxiliary software systems, maintenance systems. How do we hold the inventory and do inventory management? How do we integrate with a national civil aviation authority, which we'll talk more about? How do we integrate with a national healthcare system? How [05:26] We had to build out all of these other parts of the overall logistics system. So this is the reason I think a lot of people might look at ZipLine and be like, wow, it's a cool drone company. They build a cool aircraft. The reality is the aircraft is like 15% of the solution that's required to build something that just feels like magical, reliable teleportation 24-7, 365 to the... [05:47] Now, you know, hundreds of millions of people who depend on the service. [05:50] Speaking of 24-7, I remember being in Rwanda early days and going out and meeting with some of the doctors and lab techs that we were serving and asking for them, like, you know, how's it going? What do you think? What's your feedback? Just really being customer obsessed and wanting to optimize the product. [06:05] And, you know, here I am kind of, you know, up and coming, you know, learning engineer thinking they're going to say something about, [06:11] the drone or some of these things. And the main piece of feedback that I received was, people get sick 24-7. Why are you guys only open 12 hours a day? Right? And so- Especially when you're delivering life-saving blood. Yeah, exactly. And so that was our, you know, you got to start somewhere, right? So we started being open 12 hours a day and trying to expand and grow from there. And so that was a really key insight for me where it's like, man-

[06:34] we've found product market fit. [06:36] in a market where our product wasn't great yet, but it was solving a real need. And so having that that really beachhead market where there's a real problem being solved. And when your customer is telling you that their main feedback is they want more of your service, [06:48] It's like, that's a good sign. Yeah, we were 24-7 within the first year. So we went 24-7. We're now 24-7, 365. I mean, on Christmas Day, I usually call all of our different distribution centers to thank them and check in with them. So there is no day when these facilities don't depend on – we went from serving 1 to 20 to 500, now to 5,000 hospitals and health facilities across the world, across eight countries that are served by the system. It's become the largest commercial autonomous system on earth. Can you size that for us, the largest – [07:18] system on earth just crossed 140 million commercial autonomous miles which i mean how many times i think that that's like over the sun and back or one of the one of the things that i like is every road in the united states there's a lot of roads in the united states driving on every single road more than 30 times [07:32] Wow. That's a lot. That's a lot, just to put it in perspective. Seeing the impact that that system is now having across all these eight countries. I mean, University of Pennsylvania just published a study showing a 51% reduction in maternal mortality. [07:48] thanks to Zipline. So half as many moms losing their lives in childbirth. We have, you know, across all the different use cases that Zipline serves, some of our partners estimate that we're saving between 10 and 12,000 lives a year. And that impact is growing exponentially as we're now expanding, especially as a result of this new partnership we have with the U.S. State Department. What is that partnership with the State Department? In December, we announced a $550 million partnership with the U.S. State Department to expand the impact of Zipline's life-saving service across a lot of the countries where we're already

[08:18] With USAID being shut down, the U.S. was really seeking new ways of engaging in these countries and helping save lives in these countries, but they wanted to do it in a way that would [08:28] that would accelerate the economies of these countries and help the U.S. economically. And so the new strategy they're calling commercial diplomacy. The idea is that we want all of the developing world should be built on top of U.S. AI and robotics technology. [08:41] We should be going and economically helping. We should be bringing the best that the U.S. has to offer. Interesting thing is when you talk to these countries about what they want, [08:49] they'll tell you they are sick of... [08:52] you know, low quality aid provided by NGOs for free because these services and gender dependence and prevent economic growth in the countries. What they want is high paying jobs. [09:02] entrepreneurship technology. And so the U.S. is [09:06] is going through a big strategic shift where it's like, well, we have that. We have those things. So let's basically go out and incentivize these countries to adopt that kind of infrastructure, make sure that [09:17] As these countries are accelerating, they're doing it using U.S. robotics and AI technology. And this is something that will be great for those countries. It saves lives. It saves them money. But it also means that it will make it possible for the U.S. to secure our lead in manufacturing and robotics over the decade to come. I'm curious about you guys, because you now run the largest autonomous system in the world, and you launched it 10 years ago at this point. So you've been in production for 10 years. [09:47] lot of stuff that your average engineer sitting behind a computer screen has no idea they're going to run into when they try to deploy AI into the real world. And so I'm curious what some of those lessons learned are. And maybe one way to ask the question is, what popped up over the last 10 years that you never would have guessed you needed to be good at when you first started launching these systems in 2016? Yeah. You know, we started off delivering life-saving products, right? And our customers need...

[10:15] need life-saving products all the time in all weather conditions. And you would think it's, you know, wind, these things, but one of the weirdest things is actually solar weather. So there's solar flares that happen on the sun. So they're basically big explosions that send radiation to the earth. They can mess with the ionosphere and that can cause basically the RF signals coming from GPS satellites to be faster, slower than you expect. And that can lead to degradation and challenges in navigation systems. And so here's one example that when we were [10:45] We didn't think that this was going to be something we have to figure out. But we actually have gone pretty deep in this space. And really, it's two things. One is, [10:53] designing our navigation system and our GNSS systems to be robust to these conditions, to ensure that we can still know where aircraft are with centimeter level precision in those conditions, in those challenging solar flare times, as well as designing the system to have redundancy beyond GNSS, such that if things get really bad, we can still safely operate. Eric, you're in charge of safety. Tell us about what you've learned about safety today, [11:23] system that you have [11:24] Yeah, yeah, absolutely. I mean, there's so many things that we've learned over the last decade of operating, you know, the system in the real world. One of the things that we're proud of is how we've developed, to your point, compute failover. So there's a flight computer, flies the aircraft, lots of sensors come into this, into this computer, and that basically does a lot of math and sends commands to actuators, right? So motors, control services, these things. So this is the brain that flies the aircraft, right?

[11:54] learned is you need to assume that any part of the system [11:58] can have a fault, can have a hiccup, something can go wrong. And that's how you really design something to be robust, reliable, and safe. So... [12:05] What do we do if this flight computer has a challenge? It could be a software challenge. It could be a connector challenge. It could be these different things. Bitflip due to solar radiation. All kinds of things, right? And so what we've done is we have two flight computers. [12:17] And both of these flight computers think that they're flying the aircraft at any given point in time. They all are receiving all the information from the sensors. They're all sending commands to the actuators. And there's like a kind of a third arbiter, a little computer that is monitoring the health of those two and telling everyone every other node on the on the aircraft who to listen to. Who's actually in charge? What if the arbiter fails? If the arbiter fails, then the primary computer that was flying just keeps flying. [12:47] then now we say, okay, like, you know, now we're just going to keep flying on the thing that was good and we're going to keep flying the mission. Um, so two heads are better than one. [12:56] Yeah. So something I'm really proud of. Um, we had actually had one of these events happen, uh, a couple of weeks ago. Yeah. Where we had after a delivery, we delivered the package to the customer and then we had a hiccup on the main flight computer and we'd switched over to the backup. The aircraft flew itself home, landed, everything was totally fine. So just, you know,

[13:17] through and through is, you know, how you get the two and a half million deliveries and 140 million miles flown with no safety incidents. And a lot of what Zipline is doing, it's not like, oh, this is totally revolutionary. No one has ever thought about having a secondary flight computer. That's how Boeing 777 works. But the cost of a flight computer on a Boeing 777 is in the millions of dollars. And so a lot of what Zipline is having to do is take a lot of the best ideas that you can [13:47] And then you've got to figure out how to build that using components coming out of the [13:50] smartphone supply chain. Yeah. You can do it for, you know, tens of dollars or hundreds of dollars. You can achieve similar levels of safety, uh, [13:57] to traditional aerospace, but you can move 100 times as fast at 1/100th of the cost. Yeah. So you mentioned that the aircraft is only 15%. Describe the other 85% in layers and maybe go down deep in some of your systems that are really, really sophisticated. I know this because of being a board member and the detect and avoid systems. So how do we test? Why do we test? [14:24] Really, the way I think about it is, first of all, we're not a software company, right? We're a real-world AI robotics company. And so there's electromechanical systems out in the real world. So there's hardware test aspects, there's software test aspects, and there's integrated system test aspects. We have a lot of different environments that we test, a lot of different approaches. [14:44] I'll name a few of them. You know, on the hardware side, we do a lot of component level testing, halt testing, highly accelerated lifetime testing where we're taking components. Maybe it's a motor, these kinds of things. And we're putting them through, you know, through hell. Right. We're putting them through all kinds of challenging conditions, making it rain, making it hot, making it humid, making it corrosive. All these things while we're exercising, you know, while we're spinning the motor, while we're moving things, all of the things.

[15:14] We are designing not just the flight computer from scratch, the power distribution board, the motor controllers, the battery, the battery management system. The pod is the smaller robot that we're using to actually make deliveries to people's homes. There's an entire NVIDIA GPU powered flight computer on the pod. We're building the electronics that go into the docking station where the zip is flying in and out of. We... [15:39] You know, all of that, even the electric motor being designed from scratch by Zipline because we need a, you know, a thrust to weight ratio that is not available in off-the-shelf electric motors. So you have to design something from scratch. So, you know, 700 unique components, 43 major sub-assemblies on the aircraft, all then coming together on the manufacturing line that you both have gotten to visit. [15:58] and getting assembled into one overall aircraft. But anyway, that's the, so for each of those components. Yeah, right. Going through this type of testing and, you know, thinking about other industries, oftentimes when I talk to people from maybe automotive or aerospace and some of these, [16:10] "Hey, how do you think about reliability challenges?" And a common answer is like, "Well, I asked the supplier what the reliability of the part is." - Yeah. - And I'm like, "Okay, cool. Like, what if we're the supplier?" So anyway, so we're that vertical integration, where we have component testing on the ground, we have system testing on the ground, where we're taking full aircraft, as well as other parts of the system, and putting them through vibration tables, wind tunnels, thermal chambers that you can walk into, like all of these things, in order to understand [16:37] is how is this going to break right more than just is it good enough like we want to know how it's going to break and then we can understand okay cool like let's make it better or maybe it's like oh

[16:46] That's not too worrisome. Like, [16:47] Great. You know, we didn't break any of the ways we're worried about. It broke in that way. Fantastic. So we don't just want to say we ran the test campaign and nothing failed. We're done. Like, no, no, let's take this thing to failure. Right. Let's see where the limits are. 49 degrees Celsius, which is very hot. Hot. Down to negative 25 degrees Celsius, which is very cold. All the things. Yeah. So you don't fly anywhere at 40. [17:07] nine degrees we do you do that's what we wouldn't test at 49 if we're not where are you flying at 49 i think phoenix during the summer phoenix during the summer yeah and then where's minus 25 [17:16] to northern parts northern parts of the united states actually can i ask you guys how you think about that like [17:21] I could imagine a different version of the world where you guys are like, hey, look, if it's too hot, we're just not going to fly. And if it's too cold, we're just not going to fly. And if it's raining too hard, we're just not going to fly. And there are tradeoffs to be made, and obviously your customers would prefer that you fly at all times. But how do you think about those tradeoffs? The easiest way to think about the tradeoff was because of the use cases that Zipline started with. That's right. That makes sense. Which was basically like saving lives.

[17:51] shining. [17:53] It's not super compelling. You develop the capability because you had to for the initial use case. And in fact, for the first [18:02] couple years, we took [18:04] a lot of risk. I mean, we would basically fly. We were like, look, if it's a lifesaving [18:09] delivery happening and there's someone whose life is on the line yeah we're gonna go for it and we had a civilization authority that was you know generally great partner with us on that front we took a lot of risk we learned a lot and you know almost always it worked out in favor of like we saved the person's life and you know the worst thing that could happen was you know we had a para land which is the kind of like [18:29] zip line safety mechanism of last resort is we can pull a parachute on the aircraft and bring it gently to the ground. But we learned a lot. It happened very often in the first few years. Like, yeah, very, very rare today. I mean, to put it into perspective, you know, our original goal was to be 10 times safer than cars. Actually, Alfred was the one pushing in our last board meeting. He's like, that's a BS goal. We need to be two times safer than Waymo. And so Eric literally went and reset the goal. The zip line's target for the end of this year is to be two times safer [18:59] technology. [19:00] Waymo, I think, is about 10x, right? No, they're about 10x. 10x cars. 10x, 12x. So our goal is to be 2x safer than Waymo. Yeah. It's not the right comparison. You're flying. You have to be safe in the air, not safe on the ground. I think it depends. We're substituting something that's typically going in cars, so it's debatable. But suffice it to say, we now have 140 million commercial autonomous miles and zero safety incidents. Zero.

[19:30] depending on what country you're talking about. And [19:33] This is why we really pride ourselves on picking the right use cases. It's life-saving, and it really makes a lot of sense to go do it. And also, by God, we're going to be as safe as humanly possible from an engineering and testing and validation perspective. We really take that. That's a deep part of the DNA of the company. [19:49] One last point, what is the outcome of all of that testing that [19:53] Eric is talking about the outcome of all that testing is we have individual aircraft in the commercial fleet that have flown more than a million commercial autonomous miles. [20:02] And so I think people, you know, that's just from an intuition perspective. A lot of people look at this and they're like, wow, it kind of seems maybe exquisite or fragile, probably very sensitive to like. [20:12] extreme conditions or weather. I mean, you know, raise your hand if you have a [20:16] car that has a million miles on it. It's pretty impressive. These systems are already like way more rugged and durable and robust than people necessarily think. Can I ask you about the [20:26] Like one of the things that blew my mind when I saw some of the, I haven't had a chance to experience in person, you know, a delivery. Gotta come, Pat. I know. I gotta go experience it. But just in watching the videos. [20:36] The drone's 100 feet up. [20:39] And it drops the package. It lowers the package to a, I don't know, a circle that's got a 18 inch radius or whatever it is. Right. Like, how do you guys achieve such precision in. [20:50] Even when it's windy, even when it's raining. Yeah. How do you pull that off? First of all, the aircraft's about 100 meters up. 100 meters up. Okay. Yeah. There you go. It makes it harder. And, you know, the multiple layers, there's the delivery pod that comes down. Yeah. Right. So the delivery pod comes down. That's really the delivery and pickup like precision part of it. Right. So the drone is hovering above it. You know, it knows where the target is. Maybe let's say it's this coffee table, for example. There wasn't a roof above us. So this coffee table.

[21:20] And so the aircraft is going to hover above, but it actually needs to consider what the wind conditions are. Yeah. Right. So if the wind's blowing in one direction, then the aircraft is going to kind of be shifted upwind. It's going to shift in the direction to help with those wind conditions. And it's going to lower that delivery pod down. As Keller mentioned, we do take advantage of GNSS. So real time connection GNSS. That gives you centimeter level confidence of where you are. [21:50] the GPS coordinates of this table, right? It's not like someone came and surveyed the middle of the table and sent us the coordinates, right? No one wants to do that. So what we have to do is we kind of, that we use that to kind of get close, right? We're like, okay, here's the backyard. Here's where we kind of know things, the things roughly are. And then the job of this delivery pod is to be lowered down, you know, fight the wind conditions, fight these different things, and be able to use its onboard perception autonomy systems to identify the [22:15] where's the best place for me to leave the package right like if there's a little table and there's a whole bunch of drinks [22:20] probably I shouldn't try and drop down on top of these drinks and make a mess. Maybe I should go to the ground right next to the table, right? And so it has these autonomous onboard real-time compute to be able to identify what am I looking at? What am I seeing? And how can I find the best place to leave the package? And then come down, touch the ground, opens its doors, gets retracted back up. And there you go. The package is left on the ground and the delivery pod comes back up, stows, and the aircraft flies back home. A couple of big advantages. I mean, just to be specific.

[22:50] has its own NVIDIA GPU, running its own AI autonomy stack. So it can survey and like know exactly where it's delivering even at night. Yeah. But it's also controlling its own position. That's right. In the X and Y axis. So it can not just know, but then move. And the advantage of that architecture is, [23:10] which you can probably guess, but there are two huge advantages of doing it in this way. One is it's quiet. People have this perception of, I mean, first of all, most drones are really freaking annoying. Like the sound is just, it's basically the most grating annoying sound that you could possibly subject a human to. And so, you know, like we, Zipline has a big team of aerodynamics, aeroacoustics, and controls experts. Every part of the vehicle is designed with sound in mind for the vehicle to be as quiet as humanly possible. We want it to be no louder than the [23:40] sound of like gentle... [23:42] leaves moving in trees. And when the pod is delivering, we're keeping the main aircraft 100 meters in the air. So it's like the thing that is creating noise is really far away. That's also a huge benefit from a safety perspective, because the only thing that is coming anywhere close [23:58] to you, your family, your pets, your kids, is something that is super cute and safe. It's really like a styrofoam, kind of like a cute anthropomorphic styrofoam... Tub? Tub. Yeah. [24:11] How long was the... [24:12] technology tested outside the United States before he came to the United States? And what's the path to getting into the U.S.? [24:19] now that you're flying in Dallas and delivering packages there.

[24:22] We spent eight years, I think, right? About eight years. I mean, depending how you measure it, maybe like six to eight years. And then it was... [24:30] I mean, we launched in Rwanda in 2016 our commercial service, and we really launched this kind of next generation home delivery service, the thing that's now like in sort of insane hyperscaling mode. That only launched January of last year. So depending on how you measured it, you could even say it was like almost nine years. [24:47] And then when you got to the U.S., was it just smooth sailing? What was the sort of regulatory path that you had to go through? Yeah, I mean, we really started, I would say, like meaningfully engaging with U.S., with FAA and other regulators in the U.S., [25:02] around 2020 or so. [25:04] Um, so it doesn't, you know, we didn't show up in 2025 and everything was smooth sailing. It was really a partnership of working through, um, as you mentioned in kind of 2016, all of this stuff was, there was no pathways, kind of illegal as we, as we joked earlier. And so, um, yeah, so it really was a partnership to identify, Hey, you know, [25:21] We have shared goals, right? Our shared goals are safe and efficient airspace integration. And so while we have experience doing that successfully in different countries, we can bring some of that experience in. We have opinions on how this should work. The regulators had opinions on maybe how they thought it should work. And so it was a partnership over the course of a couple of years to identify what those paths look like and how we could kind of converge and align before we were able to execute on that. And you had to show your ability to manage all these aircrafts that are flying. [25:51] systems? Yeah, I think it's a huge part of, you know, Keller's mentioning that the drone is only a part of the overall system, the overall complexity. What we're really building is an infrastructure layer, right? We're building an infrastructure layer that can enable instant access to products. And you don't do that with one aircraft flying from one place to another place. You do that with a network of charging locations, hundreds of aircraft spread across an area that

[26:21] having demand? Where do I have supply? Where do I have aircraft? What's coming up is about to be the dinner rush? What's the weather at these different locations? How can I kind of self-balance these things? As well as, [26:32] how do I efficiently... [26:35] pull in people when needed, right? So these aircraft are autonomous, they're operating, they don't require human intervention through these flights. But there are times in which it makes sense to alert a person that, hey, maybe there's an issue here, or the weather's a little bit, the wind is climbing in this area, right? So there are humans, trained aviation professionals that are monitoring our network, I would call it. They're fleet commanders. Fleet commanders, that's right. We used to call them pilots, because when we originally launched in the US, [27:05] permission we got was to fly one-to-one. So that meant that we had one pilot sitting in an office, remote pilot in command, who was sitting in an office basically just observing an aircraft do its thing. And again, it's exceedingly rare that a human should ever have to issue any kind of a command to a vehicle, but we would have one human watching one aircraft. Not great for unit economics, but as Zipline proved out these systems, we went from one-to-one to one-to-three, [27:35] 100 and have plans to go well beyond that. Well, one fleet commander now. So yeah, we technically changed the name because I think pilots confusing. So we're inspired by Ender's game. We now call this group of this team of people at ZipLine, we call them fleet commanders. And it actually says that in the FAA documentation, we say fleet commanders shall do the following. And yeah, they are overseeing a group of 100 aircraft. And to me, this is like the exciting, cool thing about technology, because people think about like, well, you know,

[28:03] I... [28:04] what about how humans used to solve this problem? It's like it's not, you know, the [28:09] And it's cool how robots enable humans to like up level, right? Like the human is still getting to like strategically manage the system. It's just the human is now maintaining and commanding robots rather than like doing the actual work. [28:21] herself now that you guys are kind of in hyper scale mode you've solved so many problems in the last 10 or 15 years what new problems are you running into [28:29] Yeah, I mean, what I would say thematically... [28:32] I mentioned earlier that getting to two and a half million deliveries is [28:35] the, you know, the only happens every couple of years, it's like kind of a one in a million chances. Yeah. These things start to matter, right? We're we're on the path towards a million deliveries every day. [28:46] And if you have a one in a million situation, it's going to happen every single day. Yeah. Can I just just to really make that clear? [28:52] It took Zipline from... [28:54] 2014, when we started building the original version of the technology, to 2021. [29:01] to do our first million deliveries. Was it the end of 2024? Maybe it was even early 2025, actually, that we had done a million deliveries. [29:08] in the cumulative history of the company. Yeah. [29:11] So it was almost a decade, maybe say about a decade to do a million deliveries. Zipline is now in the very near future. [29:18] going to be doing a million deliveries a day. And so that is definitely [29:23] humbling it's like wow okay [29:25] everything about the way we've been solving the problem is going to break. The bar goes way, way up. And I mean, one specific example, maintenance becomes really hard. Like the scale of the problems, the number of vehicles that you're managing in the fleet, the cost of a screw up or if a certain process is operating in very inefficient ways becomes extremely high. And so there's just high degree of criticality for all these systems. One interesting point, though, there are a lot of ways that these systems operate.

[29:55] I think people don't yet appreciate the advantages of autonomy. One good example is that like the system wants to operate 24 seven. It does operate 24 seven. So I think people are used to like logistics is generally being like, well, here are the hours when humans are driving trucks. [30:10] That's not how these systems... [30:11] operate. They want to operate 24-7. They can be fully utilized. They can be as happily delivering at 2 a.m. and 3 a.m., delivering something so it's ready for you on your doorstep or in your backyard when you wake up at 6 a.m. before you go to work, as they are delivering at 2 p.m. They can deliver in five minutes. They are available 100% of the time. We are soon going to be flying vehicles straight out of our factory in South San Francisco into commercial operation. If you've seen Tesla Model 3s and Model Ys delivering themselves to customers, [30:41] the factory into operation. It's a huge advantage from a maintenance perspective that as soon as a vehicle needs to go through some kind of proactive maintenance, it will fly itself to the maintenance depot. So the human can then quickly make, you know, do whatever process necessary and then the vehicle flies itself back into operations. We can also dynamically assign capacity in a metro. [31:00] based on what the system is seeing. There's no like set home for a vehicle. It can go to wherever it's needed. [31:06] Yeah, I think to your question about, you know, getting to a million a day and what are the new challenges, I think, you know, Keller hit on some of them to the previous thought about the drone is only 15% of the problem. [31:16] Really, it's the way that we currently manufacture aircraft, maintain aircraft, support all these things, troubleshoot problems. [31:24] like the way that we do it today isn't going to work when we're at a million deliveries a day

[31:28] And so there's like, okay, we need better tools. We need better software systems. We need better processes. We need better, you know, all these things. So it's like, you know, Elon talks about designing the machine that builds the machine. And so, you know, this is really one of the... [31:42] things that I see Zipline tackling over the coming couple of years is we are going to be investing much more in the machines that build and run the machines. [31:52] I mean, from a scale perspective, I think the largest airline in the U.S. is doing about 5,000 flights a day. Yeah. Yeah. [31:58] The plan is going to surpass that in the next month. [32:01] And when we get to a million deliveries a day, Zipline will be doing like... [32:06] Somewhere between... [32:07] I don't know, 40 and 80 times as many... [32:10] flights in the U.S. and commercial airspace as all other airlines combined. Yeah. [32:15] And so it's obviously a different class. It's a completely different class of aircraft. It's a totally different kind of problem. But the reality is when you look at air traffic control. [32:23] They don't make a distinction. And so there's also, when you talk about all the auxiliary systems that have to be built, there is a huge transformation that's going to have to happen in air traffic control as we start to realize that – [32:34] People are really excited about electrification of vehicles. People are excited about autonomous vehicles. The reality is, [32:40] As those transformations occur, there are going to be 10 times as many autonomous vehicles in the air as there are using these teeny, archaic, constrained things that we call roads. [32:50] And so... [32:51] Like the sky is a big place. It makes sense to utilize it. You can give earth back to humans. You can make neighborhoods quieter, safer, less pollution, less traffic. You know, you can make huge improvements to earth if we can more effectively utilize the sky. This is going to

[33:06] require huge transformation of how we think about air traffic control in the US. And it means that we need to design it with AI and autonomy in mind rather than the way it was designed, which was in 1950 using pencils and paper and note cards and like a human looking out trying to watch the airplane. Are you helping the FAA design that? It's really, yeah, I mean, what needs to happen is like collaborative innovation is one way to put it, right? It's like that one company solving this problem for themselves is not going to solve the problem [33:36] industry. [33:37] And so we are heavily involved in, I mean, first of all, [33:40] What a key part of the solution, we believe, is [33:43] aircraft should be talking to each other. They should be telling each other where they are. They should be automatically detecting that, hey, there's a conflict on the horizon here. And so therefore, we're going to, you know, you go up, I go down, right? These kinds of these kinds of things. And our aircraft do that. [33:58] And we're working with other kind of, you know, other new entrants into the airspace, autonomous aircraft and autonomous drones to do the same thing, to make sure that our systems can talk to their systems and we can all collaborate. [34:09] to make sure it's efficient and safe usage of the airspace. We're also, to your point, Alfred, working with regulators, working with standards bodies to take some of these best practice and innovations that we and others have developed and try and make them broadly accepted and utilized so that we can all collaborate and we can all safely and efficiently use the airspace. Because you guys have developed a really sophisticated detector of the right system. Yeah, because when we were launching in all these other countries, we had to build something from scratch. And so we built the thing from scratch.

[34:39] so that they could use it to monitor this entirely new class of autonomous vehicles in the airspace. Interestingly, there are multiple public companies in the United States that build air traffic control software that are worth more than $10 billion, right? So it's like I often look at that. I mean, I think there are many companies inside ZipLine that are likely... [34:57] It's like, oh, that's like a public company inside Zipline. It's just having to get built from scratch. We're building it because... [35:03] every part of the ecosystem we sort of had to build from scratch to enable the overall technology to flourish. [35:09] You know, air traffic control is an interesting, like the more you learn, the more disturbing it is. I mean, we're starting to see the impact. You know, you read about like a plane crashing into a helicopter in D.C. a few months ago. You read about like two planes colliding on, I think, on a taxiway in an airport. I don't remember where that was a month ago. You're like, wow, why are all these accidents happening? Turns out like 50 percent of air traffic controllers are over the age of 45. Twenty percent are not. [35:35] are about to retire. And nobody is going into air traffic control. [35:40] as a career path right now in the US. And so there's actually a huge labor crisis around these kinds of jobs. [35:48] So you have pressure coming from different angles for like transformation is required. We cannot use a system that was designed for airspace in the 1950s. The labor isn't available to do it even if we wanted to. And also there is this like giant influx of new technology, AI and autonomous vehicles that are going to require us to transform how these systems work. [36:08] So you're a hardware company and a software company. You design your own questions? Operations, manufacturing. Yeah.

[36:13] You design your own parts, you build your own aircraft, you write your own software, you [36:19] You do your own operations. It's a pretty vertically integrated company. Talk about the benefits of complete vertical integration versus buying component parts or buying component software and putting it all together. [36:33] And how you get people who come from such different disciplines and domains to see eye to eye and work together collaboratively. Yeah. I mean, I think that interestingly, you know, this is. [36:44] doing it is such an incredible pain in the butt that you would never do it. Like if you, you know, I have this flag over my desk that says we do this not because it is easy. [36:55] but because we thought that it would be easy. And this is definitely like the definition of Zipline, you know, and it's such a pain in the butt actually that it's almost, if you look at the history of all these hardware companies, they all try to not do it first. You can look at the Roadster, right? They're like, we're going to use a Lotus Elise chassis. We're going to buy the battery pack from a secondary supplier. And we're just going to put the two together and it's going to be awesome. You know, kind of Roadster, you lost a lot of money and wasn't very reliable, right? But like it was an important part of getting to the Model S. [37:25] And Eric knows well, we were buying everything from suppliers. We were paying people to design different parts of the system for us or trying to buy off-the-shelf stuff. And we crashed airplanes at test sites. And we just crashed and we crashed. And we realized, wow, this stuff is super expensive. And it's also totally unreliable. And so part by part, you're like, all right, well, rip that out. We'll design the motor controller from scratch. OK, rip that out. We're going to have to design the GPS module from scratch, navigation system.

[37:55] apart, you sort of like rip it out. And I think there's a fundamental realization, probably similar to the realization that happened that made the Model S possible is like, hey, if we want to build a really great [38:04] specific product in this totally new area of technology, we're going to have to design every single one of these components from scratch to meet the specific requirements of this new area. You know, [38:14] You might think, oh, like drones. I mean, there are already lots of drones because DJI makes, you know, plastic quadcopters and they make millions of them. And like the U.S. buys 20 million dollar Predator aircraft that can fly 100 miles. The reality is actually both of these systems are very unreliable and nothing is in a level of like reliability anymore. [38:33] and safety at unit economics that would work for this new [38:38] industry that Zipline was trying to kind of like pioneer. And so we realized we had to go build like an automotive grade solution. It has to be super reliable and it has to be extremely cost effective because you're competing against cars and motorcycles, which are actually [38:51] really cost effective and we've had a hundred years to make them reliable and cheap. So [38:55] You never do it. [38:57] I think intentionally... [38:59] Maybe just like slowly freak out and through desperation realize like, wow, we got to tear all this shit out and we got to build it all from scratch. The advantage of doing it from scratch is like is speed and integration. And so, you know, our offices, you guys know because you've been, but like when you visit Zipline's offices, I mean, we are all like absolutely packed into like, you know, sardines into this small building where you have firmware engineers sitting next to mechanical engineers sitting next to autonomy engineers sitting next to, you know, cloud infra sitting next to, you know, cloud infrastructure.

[39:29] to [39:30] Aero, Aero Acoustics, Guidance Navigation Controls, Systems Engineering, Manufacturing, everything, all everywhere in one place. And then our factory is a three-minute drive away. [39:41] And so our team is like on the factory floor working, seeing parts get integrated into the overall system. And then we have our test sites, which are just a short drive away. So you can go to the test sites, watch the vehicles flying, observe how the system is performing. [39:56] Combining all these things together means that [39:59] You know, stuff is always breaking stuff's always going wrong. As Erica described, the advantage is when the thing goes wrong, we can basically go straight to the person's desk and be like you and I are pulling an all nighter tonight. Hmm. [40:10] Whereas if you're Boeing and something's going wrong with the battery on the 787, you're [40:16] You're like going and suing a supplier and taking, you know, two years to try to figure out whose fault it is. And like it's three layers deep in the rat's nest, you know. [40:25] cluster of like how these procurement deals and supply chains work for aerospace is why it's so broken. Yeah. I think Pat, to your kind of question there about getting these different discipline folks to work together. Yeah. I honestly think it's quite easy. [40:39] It's easy to [40:41] when you have set up the way that Keller just mentioned, right? Like, first of all, everyone's rowing in the same direction. We all have the same goals. And when you can ground it in reality and it's tangible, then we're all just here to solve the same problems, right? So we actually, with the vertical integration, with having a very diverse team, we actually cut through a lot of the stuff, right? A lot of the things that happen where, oh, you know, that engineer won't tell me what the actual source code does because they said it's IP. And so we don't actually know what the fault

[41:11] next to the person's desk and be like, hey, [41:13] We failed that test. Tell me about how this part of the system works. Oh, cool. Pull up the code. Great. Let's look through it. Oh, interesting. You're making that assumption. That's not how I designed it. [41:21] right cool let's get to the bottom of it right and so this idea of just rapid collaboration where you're just you know the manufacturing team the operations team the engineering team are all just like really together is the way to solve these problems and [41:33] I have found that it's actually not that hard, right? When you have those ingredients, it actually makes it, you know, makes it pretty fast and efficient. And, you know, too, I mean, [41:42] Eric's saying that it really makes you realize when you build these complex... [41:46] AI and robotic systems that combine hardware and software, you really appreciate the deep religious truth of how [41:54] dumb requirements usually are question every requirement which is you know the number one part of like elon's algorithm they talk about at spacex like question every requirement is like this is like so profoundly and deeply true you must have every team question every requirement the requirement is always stupid when you and you're like well you know it's but that you go to this team that team you like often you have to dig like two levels deep to realize like this but um [42:19] questioning every requirement is a fundamental part of like getting through this and then you know the other thing is um delete the part the most reliable [42:27] part on an aircraft is the part that is not on the aircraft at all because you deleted it in the last design. That part will never fail. [42:34] And... [42:35] You take a lot of inspiration from looking at the Raptor 1, Raptor 2, Raptor 3. I'm sure you've seen those engines next to each other. Actually, a lot of people who come to the factory now and get to see the EV3 aircraft, you can see the EV2 aircraft, the EV1 aircraft, plus the 10 different hardware versions that we built on the first version of Ziplines.

[42:52] technology, you would just delete, delete, delete. There's a huge amount of [42:59] it's really hard to delete things. It's an act of courage. [43:02] No one wants to delete the thing. You look like an idiot if you delete the thing and then the system can't perform or doesn't work because you deleted the thing. But true confidence in the physics and the performance of the system enables you to start deleting things. It's a big advantage of having full stack, integrated control of all of these systems. It makes it possible to question every requirement. It makes it possible to delete parts. Yeah, I think first principles thinking is a huge part of that. I remember the... [43:31] platform one aircraft early days it had a deployable tail hook is how it landed so had this big hooks like a meter long that would come down from the aircraft and we had a line that would catch that and slow the airplane down is this kind of complicated contraption and we had this idea that we should be able to move that complexity to the ground systems yeah and have the recovery system the landing system more like an aircraft carrier like [43:54] crab the airplane right we can you know put the actuation on basically a robot that goes up and grabs the airplane and we're like man that's going to make the aircraft so much simpler so much lighter so much more reliable um [44:04] We didn't have it working yet, and it was time to build that next generation of the aircraft. [44:09] and we're like so do we're building these next week do we build them with the meter long tail hook or do we delete the tail hook and put the two centimeter long tail hook on the back and bet that we can get this thing working [44:20] We got a rumor like, [44:21] delete it right like let's do this thing and so like from first principles

[44:25] It should work. We can make it work. We haven't done it yet, but we can do it. And the next couple of weeks looked like. [44:30] myself included, a lot of people pulling a lot of late nights, getting that thing working. And sure enough, those first aircraft came and we caught them and landed them. So it's a lot of courage. [44:39] But that really being grounded in first principles thinking with a tight, integrated team is how you do that. Is there a version of the future in which instead of delivering life-saving medicine and cheeseburgers, [44:50] You're delivering human beings. Uh-oh. Hey, I'm the board member that has to control their costs. [44:59] I mean, you know, safe, reliable, battle-tested. I don't know. It seems like... [45:04] Seems like if we're going to liberate ourselves from the tyranny of streets, it's a pretty decent solution. Gosh, I think I agree with you. I think that, you know, come to you and ask for another billion dollars. [45:19] I think, you know, a couple of thoughts like one is that. [45:23] I think Alfred knows I'm measured in the way I answer that question because to be clear, [45:29] You know, building a new infrastructure layer for the planet that can deliver packages as efficiently as the Internet moves information is going to be one of the biggest companies on Earth. [45:37] It's a huge opportunity and we definitely want to stay humble and paranoid about how super hard that's going to be. The level of execution for us to scale the way we want to scale over the next couple of years. And... [45:50] To put into perspective, I described this goal of getting to a million deliveries a day in the very near future.

[45:56] We now have many partners who are at each asking to buy a million deliveries a day of capacity from Zipline in the last few months. [46:04] And so our operating plan has now become our unit of sale. [46:08] That's a pretty crazy... [46:10] realization and it's leading us you know we had originally built the we we'd sized the entire factory to build [46:16] 20,000 aircraft a year. That was about what was required for a million deliveries a day. [46:21] all of this is kind of being thrown, we're realizing the market is way bigger. [46:25] And one one thing, you know, [46:27] When you look at this totally hyperbolic curve that I think I showed you only a few months ago of what our total daily flight volumes have done over the last – [46:38] 16 months, the level of complexity of all the different systems that are required to basically like stay on that track is quite high. Yeah. But. [46:47] You know, there are five and a half billion instant deliveries being done. [46:52] by humans. [46:53] in the United States every year. [46:56] And that's, you know, we're using a 4000 pound gas combustion vehicle. It's not really instant. It's like half an hour to an hour. Exactly. It's good marketing that it's called instant. But yeah, exactly. And, you know, 30 minutes, 45 minutes, an hour. [47:08] you know, [47:09] A significant percentage of the driver's report eating some of the food that they've delivered in the last month, like more than 50 percent. There are significant safety concerns associated with these kinds of delivery. But five and a half billion instant deliveries, what we're realizing when you look, you know, ZipLine is now at massive scale in Dallas and we're now launching four more metros in the next four months.

[47:30] When you just look at Dallas, if you were to extend the buying behavior that we're observing from Zipline customers in Dallas to the rest of the United States, there would be $55 billion instant deliveries happening, not $5 billion. $55 billion. Yeah. There's a huge market expansion. I think it's similar to how people looked at Uber when they were launching in San Francisco. And they're like, oh, even if Uber gets to be 33% of the taxi market, it's only going to be a $15 billion company. And obviously what they missed is like Uber is now 10 times the size of the taxi market. [48:00] If you make something [48:02] more convenient, [48:04] and less expensive and a better product experience. [48:07] people are going to consume a lot more of it. We are clearly seeing customer behavior where customers order every day rather than a couple of times a month. I mean, I met a grandma the other day who's ordered 350 times from Zipline in the last year. She was 80 years old. Amazing. Actually, nursing homes are like big Zipline. They're like big demand centers for Zipline. It's probably pretty fun if you're in a nursing home. It makes sense. And actually, it's funny. People perceive, I think, old people as maybe being not capable of using technology. They're all living on their iPhones. They're probably doom [48:37] be not a good thing, but like, um, they are very comfortable using like, um, [48:41] you know, Apple ID, Apple Pay or Face ID, Apple Pay and just ordering and having it delivered directly to them. So there are definitely not enough humans in the United States. [48:53] to do 55 billion deliveries. The only way we're going to be able to serve this kind of demand is with automated systems. And there's definitely not enough roads.

[49:03] When you look at traffic in most of our major cities, you're like, oh, can we just like maybe double the number of cars on the road so that we can do way more deliveries? [49:10] It obviously doesn't work. We actually need to be taking cars off the roads if we want to, like, enable human growth and flourishing. And so I think, you know, this change is inevitable. [49:21] So how many flights are you doing a day now and how many will you do in a month? So Bunny is now doing almost 5,000 flights a day. [49:29] And we're anticipating exiting this year at above 30,000 flights a day. And our goal is to get to a million flights a day as fast as humanly possible, which we expect to achieve in the very near future. Like all of the supply chain manufacturing capacity decisions we're making right now are designed not just to get us a million deliveries a day, but also accelerate. [49:51] past that. The things that are interesting to think about on the unit economics front is like whenever we meet hardware companies and you always talk about like how much do you think the system is going to cost? [49:59] And they're always like, it's going to cost X. [50:01] And you're like, cool, it's going to cost 10x. Just so you know, like when you build it, it's going to cost 10x. That's your advice to founders. That's my advice to founders is like for hardware companies, like because, you know, I'm like [50:10] try to be a good seed investor and pay it forward and stuff. And like, you're always meeting these founders and always like, it's going to cost this much. I'm like, cool. It's just like, assume it's going to cost 10 times that. And like, does it work? And what would you do if it costs 10 times that we're speaking from experience? Like when we launched our system in 2016, we were charging $30 delivery to deliver a blood transfusion over a

[50:30] 80 to 100 miles. And that was like cost comparable. And so we that's what we signed the contract for. And we thought that we're going to launch a system that cost about $30 of delivery. How much do you think it costs when we launched? Yeah, $300 of delivery. And Alfred was surprisingly chill about it. And, you know, we were like, all right, we got work to do. And so, you know, the next year we got it to like 120. And then the next year we got it to 75. Then the next year we got to 40. And then we got it to 28. Then we got it to 18. It's now 12. [50:58] for the long range technology that we operate outside the US. [51:02] Right now, what's happening this summer is the fully burdened unit economics of these systems is just now in the process of falling below the cost of using cars to deliver things. And so I think it is a cool moment that I think most people don't really realize. It's happening quietly. Like, you're not reading about this in The New York Times or whatever. But, you know... [51:22] I think that this thing is happening now. [51:26] in the next month or two that is going to have a big impact on the world and how the world looks and how people, how most normal people even live their lives because it is now more cost effective to use a robot. [51:36] in logistics. [51:38] than it is to use a human. And that's really good news for the environment. [51:42] It's really good news for neighborhoods that are going to get quieter and safer and less traffic. [51:46] less pollution and it's really good news for customers because you can get things way faster and more reliably. [51:52] and I [51:53] for less expensive. You know, our customers love [51:56] There are obviously so many cool things about the system that you can talk about and that you see customers taking advantage of, but no tip, exclamation point, exclamation point, exclamation point is a big – that's probably the number one comment. I think that customers love –

[52:12] not having to feel guilty and being able to just have a system that they know how much it's going to cost well thank you keller and eric for being here with us i thought you were going to say it takes longer than you thought not 10x more than it costs but anyway yeah that's a great great way to end it does also take a lot longer i mean i think you know [52:32] the memo that [52:34] Sean wrote here at Sequoia a few years ago, I think is like, is deeply true. [52:38] I don't know if he'll ever publish that publicly or if it'll be allowed, but I do think, you know, suffice it to say, there is an internal Sequoia memo that has had a big impact on me talking about, A, why hardware companies are going to be some of the most impactful companies for humanity's progress over the coming decades, and B, why it's super hard to get those companies off the ground and fundraise for them, and C, like how, you know, investors should think about funding those kinds of companies. It's interesting, like when you look at the world today to see, you know, [53:06] I mean, wow, how fast the world changes. Because think about it, we spent 10 years being the freaking black sheep, like a hardware company. No, thank you. Like, let's invest in, you know, SaaS, let's invest in margins. Like, this is where the whole future was. And like, you know, iPhone apps, blah, blah, blah. So, [53:23] I don't know. I guess I feel like now you're Bane. Remember Bane and Batman? What does he say? [53:28] Like you adopted the darkness. I was born in it. Like, and we built a robotics company for 10 years before building a robotics company was a cool thing to do. But, you know, I do think that especially important for like US competitiveness and just for our ability to like build the future that we'd be really proud to hand to our kids and to our grandkids and to build the sci-fi version of the future that we were all promised. Like we got to get good at building stuff again.

[53:53] And we got to get good at building not just, you know, vehicles and hardware. We got to get good at building infrastructure. Like we're depending on the crumbling infrastructure that our grandparents built for us. [54:03] I read the other day, [54:05] We just installed these anti-suicide nets on the Golden Gate Bridge, if you guys heard about that project. It cost more to install those nets... [54:13] than it costs our grandparents to build that bridge. [54:16] I believe it. So anyway, we get really excited just like, we think the future, like [54:21] promising future is like we should be able to build infrastructure. You know, we got it. We have to be interested in it. And I think people have to have the stomach for it. [54:29] And we have to learn how to manufacture and run complex supply chains again. And we have to be bold and believe in sci-fi versions of the future if we're going to build them. Awesome. Let's end it at that. Believe in the sci-fi future. Thank you guys for being with us. Thank you. Thank you for inviting us. [54:47] Thank you.