The Robotics Inflection: Why This Time Is Different (ft. Joe Harris, Alloy)

0:00These robotics companies, they have a big problem. Robotics is incredibly difficult. It's hard to make a robot that works. So we want to just take one of those hard things away. But I think that robotics will not necessarily have to be a consumer hardware business. There is so much opportunity in the enterprise and business space. Help us to imagine how soon and how big the robotics wave will actually be. I'm not sort of here to say, oh, you're going to have a humanoid in your house in one year. I'm not one of those people. I think we're actually massively overstating what that's going to look like in one to two years.

0:31We probably underestimate what it looks like in 10 to 15 years. Every founder begins with a question that won't leave them alone. For Joe Harris, that question was simple but profound. Why do machines still fail in predictable ways? Joe's story is full circle, from an electrical engineer to growth leader at Eucalyptus, and now founder of Alloy, a company building the missing feedback loop for robotics. Alloy helps robots see themselves more clearly. It captures the 1 % of data that truly matters, turning noise into understanding and understanding into reliability. The world of robotics is shifting.

1:15Sensors are cheaper, computers faster, models are smarter. But the real constraint isn't hardware or capital, it's the ability to learn fast enough. That's the moment Alloy exists for. It's the system that helps every robotics company move up the reliability curve. From it works, sometimes, to it works every time. Joe's thinking is rare. He doesn't chase markets. He notices the quiet inflection points before they compound. He left one of Australia's most admired startups, not out of restlessness, but out of curiosity. A curiosity that keeps folding back on itself until it becomes conviction. In this conversation, you'll hear what it sounds like when a founder sees the future coming into focus.

2:01not in hype cycles or headlines but in machines of how something actually works. We talk about finding the truth inside systems, why great teams are built around people who want to learn faster than the world changes and how a company can be both technically audacious and philosophically grounded. Joe also has this rare ability to zoom out. He sees robotics not as automation but as a deflationary force or even a lever of abundance. The idea that by making machines more reliable, we make life itself more affordable, more creative, and more human. If you missed Joe's first appearance as the operator obsessed with growth at Eucalyptus, go back and listen.

2:40It's an absolute masterclass. It's also a wild heart's first, an operator to founder. This episode is the story of someone stepping into the founder seat and building a company that just might accelerate the next industrial revolution. Let's dive in.

3:00First guest to go from operator to founder on Wild Hearts. Welcome back. Are you not just a growth guy? I get that a lot. Do you? Frequently. I mean, that's been what I think a lot of people came to when they met me for the first time. Someone has come to know me. It's knowing of me as the growth guy from Eucalyptus. Say the last time I was on this, being an operator, running the growth team, and then eventually running the product team. That was my identity for some time. What I think a lot of people don't know is I'm actually an electrical engineer. And almost 10 years ago, did my thesis in machine learning for telecommunications, which actually so happens has come back around and that's very similar to what I'm doing now.

3:44And before Eucalyptus, I worked at Atlassian. I was a software engineer working on dev tools. Again, not too dissimilar to where I've ended up back. So I'd say the Eucalyptus experience was more so applying that systems thinking and systems design to a bunch of novel domains where I got to learn so much from, you know, Tim and Charlie and Benny and Alexi and just watching them and helping them build that company that I've now got to bring along with that technical expertise from before into this new company at Alloy. When did you know you wanted to start a company? I think it's always been in my DNA.

4:17I come from a family of, you know, being self-employed, not necessarily in big tech companies or something like that but just generally being normal to start a business employ people make your own money work incredibly hard to pull that off small businesses mostly and so you know I made my first money online when I was about 12. What did you make? I was making html websites for people like small businesses around the area making a couple hundred bucks you know each time and it was this first moment of like wow this is you know quite a lot of money for a 12 year old, teaching myself HTML for dummies out of a textbook.

4:53I also made some YouTube videos back in 2009. No way. Is that channel still up? I've hidden a lot of those squeaky voice videos, but racked up a few million views. Wow. And it was coding tutorials. It was like how to write Python, how to write Java. Yeah, right. Making games, Photoshop tutorials, After Effects, Cinema 4D. I was just dabbling. I was like teaching myself, making tutorials, teaching myself, making tutorials, watching other tutorials, making tutorials. You know, great artist still. as they say and that started to make some money and it was again that that i think was the first time i made money where i wasn't actively doing the work anymore i made the videos and then there was trail every month i just get a check from youtube i was like oh this is quite powerful actually there's some leverage here um i just think that was like a seminal unlock where i was like i'm going to be my own boss that's kind of what i'm going to do also doesn't help i'm a terrible employee i i just what makes you a terrible employee i think i did not believe that for a second uh i mean obviously went well at eucalyptus but i think i got a lot of autonomy there and a lot of trust um i think generally probably my managers at previous roles would probably attest that i'm quite difficult employee just that i want to move quickly um you know i want to test and learn um i don't want the answer of why we can't do something to be something bureaucratic and at a certain scale it becomes hard for that not to be a frequent reason why you can't do something.

6:15And so, yeah, kind of taking, taking no for an answer, not, not, not been my strong suit. And I think when I get told I can't do something, I, I often want to do it more. What businesses have you started after the age of 18? Yeah. Um, a wide variety. Uh, there's been a, there was a yoga studio, um, small one. And, uh, I had a agency that did, a bunch of smart contract development for Ethereum EVM based blockchains around the time, you know, 2021, 2022, lots of NFTs going on. There was lots of projects that had sold NFTs with a promise of building some core technology and then had no way to deliver that core technology.

6:57And so we were the people that they brought in to say, hey, please help us build this thing, this roadmap that we have promised. And I think I just started to get really interested in the technology and the opportunity kind of pulled it, you know, pulled me into it and they built a team out around that, trained them on how to do it. And that was like, you know, quite a moonshot opportunity in that we did over a million dollars of revenue in that first year because there was just so much opportunity and so few people that knew how to do it. Given the wide variety of things you have started, when do you decide to say, actually, I'm going to build something and dedicate a huge amount of time and energy and resources into making this world-class for what it is?

7:36well i always had a creatine gummy brand i remember you telling me that who hasn't you know what's what's some creatine gummies between friends yeah you know it's obviously i don't know a lot of people it was a little side story like they'll they'll have seen that that whole industry has been massively sideswiped recently yeah but that was actually the original insight of why we got into it we saw that some of these big name brands like we got them tested they had no creatine in and you you eat them and you're like, oh, this is delicious. This is such a great experience. I can't believe I can have my creatine this way.

8:07Shock, horror. You can't. It's a scam. So we formulated one that we felt was good, tasted good. It was very challenging balancing the consistency with the dosage. Creatine is a hard thing to suspend in a gelatinous substance because it's quite a low concentration active dose. So I'm getting like really nerdy on creatine gummies. But I think that's always been my mentality, right? Whatever it is, I'm going to go down to brass tacks. I'm going to understand how it works and I'm going to try to make it the best it could be. But I think that I was always stretching myself across so many things that I don't think I ever felt that I did it justice.

8:43I didn't do it to a degree that I felt proud of as a legacy or something that I felt would have a lasting impact. And so I've always had, I think this question in my mind, what could I do if I dedicated myself to one thing? well right there you just shared one curiosity two enthusiasm three get to the bottom of the root cause of something and then three or four see it through and let's take yoga for example like why didn't like what what was holding you back for or even the greeting gummy example like what what held you back from doing that full-time I was doing I was already committed to a lot of other things um i mean i spun down the creatine company and sold it onto a great home and it's still functioning today um it's a lasting business that hopefully people are very happy with but i spun that down to do this um i think it was i think it's the it was the magnitude of the opportunity it wasn't something that like i was passionate about it because i really am passionate about the benefits of creatine and that more people should partake um and that they will partake and it's going to be a big growth industry and is already but it wasn't something that i felt I could work on for 10 or 20 years at least.

9:56And that's what I was seeking. That's what I was really looking for. And that was why I left Eucalyptus. No other reason, right? It was that I wanted my thing that I can go and do, my company that I can start, that's going to be a multi-decade journey. How did you discover what that multi-decade journey would be? That's a big commitment. Yeah. Yeah. And as I've established, I commit myself to so many different things. I seem to not be able to commit to one thing. I didn't know when I left Eucalyptus exactly what it would be. I just knew I needed to burn the ships because it was such a great opportunity at Eucalyptus that if I stayed there, I'd just keep staying there.

10:32Status quo, inertia. And so I actually gave very, very advanced notice, did all of the succession planning, the strategy setting, the execution, make sure that it was in a good spot so that I felt like I could walk away with my head held high, having sort of end-to-end had a great run. I think people really only remember how you start something and how you finish it and so many people finish up a great run just kind of drifting and you know maybe becoming a bit dejected a bit disgruntled and they leave a bad taste and actually that's what people remember that was very important to me but then I allowed myself you know I had a great opportunity I worked with Immutable and helped them build out a sort of a new layer of their strategy built up a team made some hires get that ball rolling on a contract while I was able to sort of spend some time reflecting because it's been four plus very dedicated hardcore years at eucalyptus that I needed some oxygen for my for my creativity and so I just followed my curiosity and that led me to creatine gummies it led me to a variety of things and one of those things was that I was going to be able to finally go back to my kind of original hopes and aspirations graduating as an electrical engineer which is that the timing for robotics was was incredibly ripe and i was going to be able to you know spend the next couple of decades and it would be the right time for that finally share more about the creative process that you went through to surface what became alloy i'm curious like take us into the the bedroom where you're getting creative you're at your best, your own new creatine gummies.

12:11Why is this happening in the bedroom? Well, that's where I get a lot of my work done. I see, I see. All right, putting in work in the bedroom. It was actually born out of, like I believed I was going to be starting a fully end-to-end verticalized robotics company. We're going to build a robot. And as I left Eucalyptus, it was around the time that, you know, reusable rocketry, like we're being able to re-land a rocket that a rocket that we launched was becoming incredibly reliable almost perfunctory it kind of wasn't even newsworthy anymore that we were able to do that which was astounding to me because every time i watch that fly up and land it brings a tear to my eye because it's like it's absolutely crazy that we get to be alive in this moment um this is we've watched it go from sci-fi to reality in our lifetimes but they were continually seeing this cost curve come down so i was infatuated by this idea that every time we have an age of exploration, I think about the East India Trading Company, when we figured out joint stop companies and we were able to send boats across continents.

13:14Immediately after that, you have industry, begin farming, we begin mining, we do all of these things and then we settle because we need people to co-locate with the industry. And so I was seeing things like Vata Space, Fleet Space, all of these companies that were spinning up that were going to be this next wave of industrial revolution in space and logically that followed okay great well that will mean we'll need settlement technologies in space so someone's have to gonna have to be the space habitat business that led me to we're gonna need to be able to grow food in space which led me to how do you grow food in a vacuum and harsh environments which led me to indoor agriculture or controlled environment ag cea indoor farming vertical farming that was around the time that plenty and these other companies that had raised like a vociferous amount of money were then going out of business.

13:59Which are vertical farming companies? Which other ones? Which are vertical farming companies they're going out of business. Right, they're all vertical farming companies. And so it wasn't a great time necessarily to be like, I'm going to go into vertical farming. But that's exactly what I decided I was going to do. And so I sort of just tapped the network. I started asking people like, who knows anyone that's worked in this space who's been one of these engineers at one of these companies or founded one of these companies. And to all of their credits, like the VCs around Australia sort of opened doors and made introductions And I rapidly was able to get in front of some of these experts and learn so much around the cost structure of those businesses and where it had gone wrong.

14:33And a lot around the very large footprint, meaning you needed a large amount of autonomy, a lot of robotics and automation, because the human labor component at that scale just made the economics not work because they were growing lettuces and leafy greens, which had a very low dynamic range. People are not going to pay, you know,$10 for a bag of spinach because it's not noticeably that much better than a$2 bag. But there was one notable company in America called Oishi that was growing Japanese strawberries in New Jersey and selling them for a very premium price because there was a story behind it, a brand, but also it dramatically tasted differently.

15:08So there's a lot around, you know, going for fruits that don't continue to ripen. So they benefit from being picked right by the source of distribution. Growing crops that have that very high price point that they can achieve. they specifically grew leafy greens because it's very easy to predict where it will fruit from like it's going to grow from whereas with strawberries you can't really predict that so trying to automate that is very difficult so they i think the main takeaway here is they went this path of technical lease resistance to get to market but that meant that their unit economic hurdle was so so difficult because they had to get the price point down so low they had to make a huge footprint and then because they built out that huge footprint building automation at that scale was not ready in prime time.

15:50And so they just had a big leaky balance sheet, bleeding money, and the market turned on them. If the market hadn't turned, and they had one more big round, would they figure it out? Maybe. It just felt like the culture was, we'll fix it in the next iteration, the next bigger factory. And they just kept not fixing it because it is quite technically challenging, especially at that large scale. So all of that aside, I think that led me to, well, the automation wasn't there. So if I'm going to do this, I'm going to need to solve that automation problem. well, I'm going to solve that automation problem.

16:19What does it look like? So I then went and spoke to 20 or 30 different robotics founders and their lead robotics engineers, their lead machine learning engineers, and asked them questions about what it took to make their companies work. And there was a very common refrain between them, which was it all came down to the economics of buying a robot versus having a person do the job. And a lot of the time that came down to reliability. How out of 100 times it does the job, how many times does it do it right? Seems obvious, but that is the constant march of these companies is getting from not 99%, but 99.99.

16:55If you're picking strawberries and it takes eight months to get to that level of maturity and you crush one, you have a very unhappy farmer, right? The bar of expectation is incredibly high. And so I just kept asking why. And it got to this place where there are so many different use cases of robotics. And if I'm able to solve this feedback loop problem around gathering data from that edge of how that robot is doing, finding the places where it's not doing well to allow you to fix them. So you can make that continual march to 99.99 to 99.99%. Four nines, five, nine, six nines. This is to anyone who's a system reliability engineer is very common language.

17:32It's the same thing that people at Google and Facebook do about making sure that the app is up, you know, 99.999 % of the time. And you're constantly trying to find these weird edge cases where it comes down that you're going to fix and protect against. And so this was all sort of very, I guess, analogous to me coming from web. Having seen some of these patterns before, even growth is that, right? You're looking for weird experiences on the website, on the app that cause churn. And you're trying to catch those in the analytics. And then you're doing an investigation, you're coming up with a theory, you're deploying the fix and seeing if it improves it.

18:05Ultimately, I think I just came to realize that so much of business is just feedback loops. And there is so much tooling and mature tooling in web and business to drive that and collect it and automate it. there isn't that level of tooling in robotics today and that's what we set out to decide to solve realizing that given this problem exists if i solve it it's probably far better to be the horizontal provider giving them like access to this platform to every other robotics company to accelerate versus become a fruit picking business off the back so what share an example of like what that means in real life what is like maybe share an example of a robotics company where this product can come to life.

18:46Imagine you have a robot that is a very self-contained, beautiful robot. It goes underwater and it scrapes fouling and barnacles off of boats, cleans the bottoms of boats so that they're more efficient. You may have a case where, you know, your autonomy makes an unexpected decision. Maybe the light refracts through the water in a weird way that happens only every so often at a certain time of day. And it causes your models to make a different determination than they normally would. You might not catch that sometimes. because robots will produce upwards of one gigabyte per minute a lot of the time of data.

19:18And that data will be in so many different languages and shapes and sizes. It'll be images. It'll be a series of numbers. It'll be text logs saying error, error, warning, warning. You're trying to pay attention to all of that. And like when you think about something like a web app, it might produce a few kilobytes of data a minute just in these logs or conversion metrics. So you're talking about, you know, many thousands of times, even sometimes millions of times more data coming out of these robotic devices than a web application. So none of the tooling that's built for web really translates over.

19:50So for that company who's dealing with that underwater cleaning, trying to isolate that issue is a lot of custom infrastructure they need to build because there's just nothing they can take off the shelf really. The best solution in the market today is for them to, there are great tools for replaying that data. So they can scrub through it, sort of play like a video and see all the images. They can see the graphs being drawn. They can see the logs coming through. And so they can sort of put themselves in the robot shoes in a way. And they're gathering context and they're trying to reason about what's driving this issue.

20:21And for any of the AI engineers at home going, that sounds like rag. It is, right? It is retrieval augmented generation being done by an engineer looking across different data signals to come to a conclusion themselves. And when I started to talk to all of these different companies, and this was not like one isolated to one company, this was every robotics company I talked to. The operator in the field that runs the robot will observe the fault. They will tell the head office, those engineers will hop on and they'll replay the mission, replay the job. And that is the way that it is done across the industry.

20:56And they may build some custom tooling and that will speed it up. And as companies get mature, like the most mature companies in this space, have built a lot of tooling. So it's not as though it's an unsolvable problem. It's just incredibly expensive. And it doesn't make sense. It's like a web company building its own GitHub, building its own data bricks. Like, why would you do that? It isn't what makes your beer taste better. It isn't your core IP. And that is kind of that core insight of realizing this is going to exist and we should be the ones to build it. How much time is spent in the status quo?

21:27How much time will you save and help us see like, what does that mean for the business once the product is live? I think if you really boil it down, robotics is this fire hose of data where you only really need 1 % of it, but knowing which 1 % is incredibly challenging and time consuming. And so a lot of the time when we do talk to certain companies and we're doing kind of discovery with them about their existing processes, it will be upwards of sort of 90 % of the data can't get looked at because it's just, think about the multiplicative relationship between the operator and the robots. Their goal is to have one operator oversee as many robots as possible.

22:07So if your main debugging solution is replaying in real time, one second per second, the data, that's not going to scale when you have 10 robots with one person. So it becomes the core bottleneck of the business. It's actually the biggest unlock for all of these companies to be able to get the people of like one human to 10 robots, to 20 robots, to 100 robots. that's what defines their unit economics over time. And so we are in the core stream of improvement there. We're trying to accelerate their development. And if you think about the time window that goes into gathering, processing, curating, training the models, or finding and fixing hardware issues, and then QAing that, testing it, and then deploying the new version, about 80 % of that is split between that curation and analysis piece that we've talked about.

22:53and then this QA and quality assurance happens at the end. You make an improvement and you need to now go and test that robot to make sure you haven't regressed anything else. You haven't introduced any other bugs. You have to feel incredibly confident once you're in production and you have 50 of these robots running around the world and you're going to deploy over the air and you update to them. You've got to feel pretty confident that it's going to do what you expect. And again, it's like there's limited tooling today for that kind of thing. Part of it is that there just hasn't been an insanely mature set of companies that have been commercialized to create a huge TAM for people to go, oh, I should go and build this, right?

23:31And I think that's because most people spot opportunities the wrong way. They're looking for where there's this big opportunity today to go and capture 1 % of it, 2 % of it, 3 % of it. But if you look at every single generational company that we have around us, they all came up with the market that they have come to dominate. It didn't exist. If Amazon had gone, oh like what's the tam of selling all of like for aws in the moment when they were originating they would never have been able to pursue it um but it's that belief about the future that turns out to be contrarian and right that grows the market that you come up with you can reflexively accelerate and play a really key role in in in helping to cultivate and nurture how do you earn the right to use the famous words that some listeners will understand to get into the door of these robotics companies where like the stakes are extremely high, the security is extremely high.

24:23I would imagine that the data is unique from one company to the next. If companies are building custom tooling, I would also imagine that people are using different tool sets. How do you begin to sort of like, A, as I said, get in the door of one, get a few design partners, and then think about the product that is being created in a way that unifies all of those customer data sets. What we've observed actually from the cross section of companies that we've been talking to in different stages of development and commercialization and sort of becoming, you know, from research through to companies, the ones who have been most receptive to this are the ones who are the most forward thinking, the most accelerationist, actually the furthest along, because I think they do appreciate what they do and don't do as a company.

25:12Whereas when you're in the early sort of amorphous phases, you're like, okay, well, maybe we'll do that. Maybe we'll pivot and go from making like Slack, like making a game to making a chat thing, right? Like people are concerned, I think, about the flexibility and losing flexibility by partnering with someone like us, right? But the ones who have had the best yield, but best outcome working with us, who have been the most excited about it, the ones who actually have robots out in the field, they're actually seeing this problem in real time, the sort of parallel data coming in for a single person or two people to deal with.

25:39And so part of it is going to them and just asking questions, right? Like we don't go in and go, we know better than you. We're there to learn from them realistically. As you say, like there's so much nuance and difference between the companies. We want to understand how best to serve them. And so that's been a lot of these early conversations and we have learned an enormous amount about the best way for us to serve them. It also has an interesting side effect as members of our team become experts because of the horizontal cross-sectional nature. Like we meet people in different sectors. like we don't really mind which sector your robot is deployed into.

26:12It could be we work with people in maritime, in agriculture, in logistics, in defense. These things all are at the data layer pretty similar. We use a combination of the fact that a lot of robotics is organized around a few, like Pareto distribution, they're organized around a few open source frameworks, which output a similar data format. So those three kind of buckets of perception data, numerical time series from sensors and text logs actually covers a very large amount of the industry. And then we do custom integrations for the edge cases that don't get covered. I think you see that more and more with these AI first companies that are having these forward deployed models to do more of that custom integration at the beginning to help that company get the best out of the product.

26:56It's just the new iteration of customer success. And so we engage in that the same as them. So one half of the question is, why is robotics interesting the second half of the question is you mentioned earlier that a lot of founders or folks have a hard time sort of underwriting markets that don't exist or are small right now how do you think about the two intersecting and feel free to handle that two angled question any way you want sure i mean i think the conventional wisdom is you can follow the cost curves right it's like historically throughout time as humans have brought down a cost curve we have disproportionately leveraged that thing exponentially more and more right it comes down by half we use it 10x and that diffusion has held pretty true and if anything has accelerated as different technologies have stacked on top of each other like the rate at which people came on to the internet or got their pc compared to how the rate at which people got onto mobile uh to the rate at which you know maybe people dabbled in blockchain maybe then we're talking about how quickly they got onto ChatGPT with their 700 million weekly actives, right?