Incumbents beat AI startups on data, domain, and distribution
“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.”
“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.”
Don't be the founder who gives up when there's no API
“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.”
The Axial Age teaches us how to handle technology shocks
“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.”
Flexport's machine learning saved 2% on freight while improving transit 20%
“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.”
“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.”
“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.”
Companies exist to deliver goods, not employ people
“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 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.”
