AUTOMATE LOGISTICS

“When our backs were against the wall and we had, I think, less than two weeks of cash runway. And we had a terrible night where every single order was late. This was a Stanford football game in 2013 and I had trouble raising the seed round. We made the decision to refund everyone. That cost us over 40% of the bank accounts. So when you have two weeks of runway, 40% of the bank accounts. And we baked everyone cookies and deliver them at 5 a.m. before everybody woke up.”

“One of the first big differences is the eating out culture in China is very, very high and very, very affordable. Eating out in China is about as affordable as cooking at home. And as a result, nobody cooks. And there are a lot of reasons for this, but we can go super deep on retail history and grocery history in China. But anyways, but that's a huge phenomenon. I think second, because of labor market dynamics, both the availability as well as the cost of labor in the Chinese market, that's allowed a lot of these businesses to make this activity almost as affordable, as if you were to pick up the orders yourself.”

“Drones obviously can do a lot of these longer distance orders. And so we've been doing drone deliveries actually for a couple years now, mostly outside of the United States. Outside of the US. Places like Australia, we're going to bring them to Europe, bring them to the United States as well. But again, you have all of those problems you have to solve. The autonomy is a little bit easier. You still have a routing problem, you have hardware problems. Obviously, you still have permits and regulation, set up, loading inside different stores, things like that.”

“From the product perspective, yes, because at the end of the day, any consumer product is judged very simply by its retention and its usage. That's how you know whether you have a differentiated product. I think it's very easy to have differences in opinion about whose app do you like more or whether or not certain apps look similar or different. At the end of the day, though, if our app is performing at a higher retention, much higher retention and frequency of use than others, that's how we know whether or not the things that we say actually are making a difference to customers.”

“It just turns out it's extraordinarily difficult, however, unless you're a large brand or a house of brands, someone like DoorDash, to be able to attract enough customers to make that math work. ... For businesses like Chipotle, who tend to identify real estate in fairly expensive areas, there's high opportunity costs of what you do with that space. Yes, you're right. One choice is to turn it into a delivery-only kitchen, and sometimes that happens. But there's also a massive opportunity to recoup the expense.”

“It just turns out it's extraordinarily difficult, however, unless you're a large brand or a house of brands, someone like DoorDash, to be able to attract enough customers to make that math work. ... For businesses like Chipotle, who tend to identify real estate in fairly expensive areas, there's high opportunity costs of what you do with that space. Yes, you're right. One choice is to turn it into a delivery-only kitchen, and sometimes that happens. But there's also a massive opportunity to recoup the expense.”

“Everyone's so worried about automating away the jobs. And I just think that misunderstands the role of companies in society. Like the role of companies is not to employ people. It's to deliver goods and services. And in fact, whoever employs the least number of people will have the lowest cost and win. And that's how they benefit society, is lowering costs and making things more available for us to buy and sell.”

“I add Laird. Laird is Laird Hamilton. And I literally just tell Laird at the beginning, like, here's where our boat's at. Here's what we like to do. We got to be out before sunset. Make sure you look at sunset. Make sure you look at the weather. I don't want a boat in the rain. I only have six seats, and we always need people to bring waters and food or whatever. So that's like, it's just simple. And you just talk to it, and it goes and builds that agent for you, just from texting it.”

“We have our own mapping system, for example, that we built. Why do we build our own? Well, it's because we care much more than any third-party mapping system of exactly where the last two feet, forget 20 or 200 feet, of some apartment unit door is, for example. And we know if we reliably deliver to that door, and that we saw that the pin actually hit exactly where, we have a little bit more fidelity in whether something was dropped off. We build profiles of customers, I'm sure you do too, of their behavior and what they tend to say.”

“One of the most difficult things is how do you actually staff your restaurant? This is the number one challenge, this has always been the number one challenge. And I think there's no easy ways around this really. And I think because the cost of labor only goes in one direction, only goes up, restaurants are increasingly making this choice of on the continuum of service to manufacturing, where do I want to sit on that spectrum? I think that is one very big trend, that more and more restaurants feel like they have to go towards the ends of the spectrum.”

“It usually takes a couple of seconds. It goes and builds everything in the background. So it's provisioning an email address for this, a phone number, a web browsing capabilities, everything. And then it just joins like a member in a chat. All right. I just opened Convos. I hit start a Convo. I can choose whether or not I want to share my name with the agent. So I'll throw it out. I need to swipe up and then it joins.”

“This is true of all incumbents in an industry. They have some real advantages when it comes to AI and benefiting from it. And one is the scale of the data. Two is the domain experience to know, okay, which problems should we be solving? And third is distribution. Like when we build or any large company builds a great AI product, the next day it can be used by thousands of companies. Whereas a startup doing that has to go beg people for their data to train the model and earn their trust to have that data from a security compliance standpoint.”

“If you look at the country, a lot of this growth is happening in the south of the country. And that's been true for a couple of decades now. And they tend to be correlated, meaning if it's easy for me to build apartment units and to build just construction in general, it tends to be a bit easier to also get the licenses to open up a restaurant. That's good. There's some bright spots and it's a nationwide maybe negative trend when it comes to permitting.”

“One of the other things that we've done is create a program for non-engineers to learn AI skills and kind of formalize programs. So your manager has to agree, but you get one day a week for 90 days. It's a 90 day program, one day a week, where we teach you kind of a AI bootcamp, vibe coding and different ways to apply. The promise of the leader who created this and convinced the managers to give up someone for 20% of their time to go into it was, I will return them to you as 10 times more productive than their peers.”

“Those agents can protect us, protect our attention while coordinating, and they can negotiate, they can find times together, they can do briefings. It has access to your calendar, mine has access to my calendar, but we don't want to share, I don't want to give you my whole calendar, I don't want to give you my whole workspace. Those agents can protect us, protect our attention while coordinating, and they can negotiate, they can find times together, they can do briefings.”

“I just screenshot the app in the app store and throw it in a thing and go code the app, and then it just builds a personalized version of the app that I want. And I was like, that's interesting. I wonder if I can make that so anyone in the world could do it. And so we made it where you can literally just take a photo and I was looking at this app. I have my phone. I pay $29.99 a year for Cal AI. It's so simple. I drop photos. It analyzes the photos. It tells you the calories in it. And I was like, can you build this app into an agent?”

“From the product perspective, yes, because at the end of the day, any consumer product is judged very simply by its retention and its usage. That's how you know whether you have a differentiated product. I think it's very easy to have differences in opinion about whose app do you like more or whether or not certain apps look similar or different. At the end of the day, though, if our app is performing at a higher retention, much higher retention and frequency of use than others, that's how we know whether or not the things that we say actually are making a difference to customers.”

“One of the most difficult things is how do you actually staff your restaurant? This is the number one challenge, this has always been the number one challenge. And I think there's no easy ways around this really. And I think because the cost of labor only goes in one direction, only goes up, restaurants are increasingly making this choice of on the continuum of service to manufacturing, where do I want to sit on that spectrum? I think that is one very big trend, that more and more restaurants feel like they have to go towards the ends of the spectrum.”

“I took all my messaging logs of Kai from iMessage, put it, I just dropped it in there. I copied and pasted it in the chat. And then I said the mybodytutor.com blog has all their philosophy. And I love that company for what it's worth. I dropped the link in and said, go read everything about MyBodyTutor. Here's all my chat logs from Kai. And what he did is he's a psychology coach about how you feel about food. So I just built Kai.”

“Drones obviously can do a lot of these longer distance orders. And so we've been doing drone deliveries actually for a couple years now, mostly outside of the United States. Outside of the US. Places like Australia, we're going to bring them to Europe, bring them to the United States as well. But again, you have all of those problems you have to solve. The autonomy is a little bit easier. You still have a routing problem, you have hardware problems. Obviously, you still have permits and regulation, set up, loading inside different stores, things like that.”

“I tell founders, friends of mine who raise a large round, sure, go raise a big round. As long as you're up round, you're doing good, great. Raise a large round, then do a hiring freeze for 90 days. The next day, to tell your team culturally, no, the money's not going to solve our problems. We're going to solve our problems and keep that. And then, sure, go higher. But it's because it's super, it happened to us over and over again, where you just like headcount, got out of control.”

“There's a period in history called the Axial Age. It's about 500 years BC. And that's when coins really started to spread. What you had with... You think about it with coins is taking transactions between two people and really making them very impersonal. And simultaneously, across the world, you had four major profits that emerged. Well, profits of sort, you had Buddha, you had Laozi, Confucius, and Socrates. They all lived at the exact same moment in time, right, as coins were taking hold.”

“One of the first big differences is the eating out culture in China is very, very high and very, very affordable. Eating out in China is about as affordable as cooking at home. And as a result, nobody cooks. And there are a lot of reasons for this, but we can go super deep on retail history and grocery history in China. But anyways, but that's a huge phenomenon. I think second, because of labor market dynamics, both the availability as well as the cost of labor in the Chinese market, that's allowed a lot of these businesses to make this activity almost as affordable, as if you were to pick up the orders yourself.”

“When our backs were against the wall and we had, I think, less than two weeks of cash runway. And we had a terrible night where every single order was late. This was a Stanford football game in 2013 and I had trouble raising the seed round. We made the decision to refund everyone. That cost us over 40% of the bank accounts. So when you have two weeks of runway, 40% of the bank accounts. And we baked everyone cookies and deliver them at 5 a.m. before everybody woke up.”

“Our take is that we can make the price of shipping anything by ocean container shipping cheaper by between 8 and 10 percent cheaper over the next few years. And AI is a big, not the only part of that, but a big part of that. As our business model, the way we think about it is as I call it, scale economies shared, which is the bigger you get, the cheaper you get, the more automation is a form of scale.”

“The things that Flexport did really well compared to all the other tech companies who have tried and failed in our space, both before we came along and in parallel, is we didn't look at ourselves as a pure technology company. We're willing to pick up the phone and solve problems with humans, drive down to the port, still to this day. And I think that's the mistake that a lot of tech people in traditional markets will fail at, because they're like, oh, if there's no API, I can't do it. If my agent is unable to do this task, I guess the task can't be done.”

“If you look now at the last two hackathons we've done, it would have been like 90% LLM based projects. I haven't studied it, but it's just my feeling and my gut. Whereas probably 18 months ago, there were like four or five. There's probably 50, 60 teams that do a hackathon project each time. I remember thinking afterwards, I'm like, you know what, we could just only do that stuff and we'll also win.”

“I think when you have high volumes of activity, I think keeping the reliability as reliable as the electricity we have or the water inside of our buildings, that is extraordinarily difficult. ... One of the biggest things that we're going to have to do before we can just fulfill the items, which is what we'll get to, is where are the items and what are the items? There's tens of millions of items literally inside these cities, whether it's in the US or different countries within Europe, other parts of the world, they're not catalogued.”

“I took Patrick Collison, the CEO of Stripe, has a list on his website of his 89 favorite people that has links to all their sites. And I said, build me a reminder, if any of his favorite people write any articles about tech, AI, or the future of technology. And so now it just goes and builds that, and it's now monitoring all of his site. Then it's monitoring my favorite writers. And then I said, every morning, send me a summary, and I want you to tell me if a website's updated.”

“It's not that we just started using AI with LLMs. We've had a machine learning model for doing planning, and planning in the sense of logistics means let's say on a containerized basis, I've got a container, which ship should it go on? So our AI for that saved us 2% of our ocean freight spend while improving transit time 20%. Usually, that's a trade-off. It's either faster or cheaper, but not both.”

“I think when you have high volumes of activity, I think keeping the reliability as reliable as the electricity we have or the water inside of our buildings, that is extraordinarily difficult. ... One of the biggest things that we're going to have to do before we can just fulfill the items, which is what we'll get to, is where are the items and what are the items? There's tens of millions of items literally inside these cities, whether it's in the US or different countries within Europe, other parts of the world, they're not catalogued.”

“If you look at the country, a lot of this growth is happening in the south of the country. And that's been true for a couple of decades now. And they tend to be correlated, meaning if it's easy for me to build apartment units and to build just construction in general, it tends to be a bit easier to also get the licenses to open up a restaurant. That's good. There's some bright spots and it's a nationwide maybe negative trend when it comes to permitting.”

“We have our own mapping system, for example, that we built. Why do we build our own? Well, it's because we care much more than any third-party mapping system of exactly where the last two feet, forget 20 or 200 feet, of some apartment unit door is, for example. And we know if we reliably deliver to that door, and that we saw that the pin actually hit exactly where, we have a little bit more fidelity in whether something was dropped off. We build profiles of customers, I'm sure you do too, of their behavior and what they tend to say.”