Ryan Petersen: How Flexport Uses AI to Cut Freight Costs

1. 0:00 – 0:51

   Intro

   1. RPRyan Petersen0:00

      Logistics are a very scale-driven industry. And so the bigger you get, the cheaper you get. Our take is that we can make the price of shipping anything by ocean container shipping between eight and 10% cheaper over the next few years, and AI is a big part of that. So our AI for that saved us 2% of our ocean f- freight spend while improving transit time 20%. Usually, that's a trade-off. It's like it's either faster or cheaper-

   2. JFJared Friedman0:24

      Yeah.

   3. RPRyan Petersen0:24

      ... but not both.

   4. JFJared Friedman0:25

      And you're at two billion dollars a year revenue and just getting started. (instrumental music plays) Welcome back to another episode of The Light Cone. We've got a real treat today, we have Ryan Peterson of Flexport with us, he went through YC in 2014 and he is easily one of the most awesome founders I've ever met. (laughs) Ryan, thanks a lot

2. 0:51 – 3:17

   What is Flexport and what are they doing with AI?

   1. JFJared Friedman0:51

      for joining.

   2. RPRyan Petersen0:51

      Thank you.

   3. JFJared Friedman0:52

      To start, Ryan, uh, what is Flexport and what are some of the things in AI you're actually implementing right now?

   4. RPRyan Petersen0:58

      So Flexport is a global logistics company built around a modern tech stack. And that means we help companies ship cargo from point A to point B across any mode of transport, so air, ocean, truck, and rail, and get that cargo delivered hopefully on time and in full at a lower cost thanks to the tech. What we're doing with AI is, uh, may, it's an exhaus- I have to make an exhaustive way to extend the length of the podcast to pull that off. But it starts with customer user experience, what can we do with their data, getting them better access, how do we load containers in the optimal way, how do we, uh, put that container onto the right ship at the lowest cost while maintaining or beating transit time expectations? Automating just tons of work that's done in email or that you d- or phone, or work that you wouldn't even do because the cost is too high for a human but actually does create some value that's worth it with AI. So most contracts in logistics come in giant Excel files, thousands of rows and, you know, a dozen tabs. You can't just feed that to OpenAI and get an ans- get a structured JSON file back. It needs intelligence. But writing code and then having AI write the code, you write a parser that ingests it and then have AI that can write those parsers for you learning. There's an endless list and we feel like we don't even know all the things that it can do, it's still pretty new.

   5. JFJared Friedman2:16

      So basically one of the most, uh, human-intensive things now can be streamlined to the point where actually it might, uh, affect GDP in the world.

   6. RPRyan Petersen2:25

      Our, our take is that we can make the price of shipping anything by ocean container shipping cheaper by between eight and 10% 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, 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 au- automation is a form of scale, and the bigger you get or the cheaper you get, you lower your, the lower your cost, you give that, share that with your customer which will make them do even more volume with you. There's scale benefits that come, logistics are a very scale-driven industry, uh, and so the bigger you get, the cheaper you get. Like the Costco model, I like, I like, I love Costco, even though I don't shop there, I just love the business. Uh, you keep driving down the price, that makes you more attractive, more competitive and, and just keep going. Yeah.

   7. JFJared Friedman3:12

      And you're at two billion dollars a year revenue and just getting started.

   8. RPRyan Petersen3:15

      Just getting started. Yes.

   9. SPSpeaker3:16

      Something

3. 3:17 – 6:27

   When did AI tools become serious at the company

   1. SPSpeaker3:17

      I'm curious about, so from our perspective, we work with all the startups and we've seen, like, AI over the last couple of years go from like when ChatGPT launched and then, like, some startups in the batch started playing around with it and it's become, like, progressively more serious.

   2. RPRyan Petersen3:28

      Mm-hmm.

   3. SPSpeaker3:28

      Um, I think you're the first person we've had on the show who's, like, running a company at scale that was founded pre-AI.

   4. RPRyan Petersen3:34

      Mm-hmm.

   5. SPSpeaker3:35

      What's, like, what have the last few years been like for you from that perspective, from like ChatGPT launch, like at what point did it start becoming like a thing you were paying more attention to?

   6. RPRyan Petersen3:44

      Like so many other people is on November of 20, was it 2022? It's already been-

   7. SPSpeaker3:49

      Yeah.

   8. RPRyan Petersen3:49

      ... a few years since the ChatGPT launch, been personally obsessed ever, ever since then. It's interesting to watch it take hold at the company, and in some cases not take hold and you then saying like, "Come on guys, we can't be this boomer company."

   9. SPSpeaker4:02

      (laughs) Yeah.

   10. RPRyan Petersen4:03

       Like, everybody needs to be using this. We're trying to drive that sense of paranoia from the, from the top, from me but, but many others in the company may be even more paranoid than me or more enthusiastic, excited than me as well, uh, to say that story that we say of like, "Well, we're the only large logistics company founded since the web browser." And I know there's a kid in the next YC batch who'll say, "Hey, we're the only freight forwarder founded since ChatGPT November 2022." Like-

   11. SPSpeaker4:30

       (laughs)

   12. RPRyan Petersen4:30

       ... and he's got a point. Um, so we, we have to be leading on this. This is true of all incumbents in an industry, they have some real advantages when it comes to AI and benefiting from it. And, and one is the scale of the data, two is the domain experience to know, okay, which problems should we be solving? Uh, and some of those problems are small enough that you shouldn't start a whole company around the problem. It's maybe a feature, not a company. Uh, but for them it's great, it's a valuable feature that they could add. 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 trust, ga- earn their trust to have that data from a security compliance standpoint. And then third, get the customer, get, you know? So that's the huge advantage that any incumbent will have and we think, we, we definitely feel that we have that advantage at our scale. Um, but the flip side where I think we also have an advantage is that we are still a young company relative to our industry, but young in terms of our tech stack. Like we build our own tech, therefore we can implement and integrate AI and just add it wherever we want. Most of our competitors treat AI or tre- treat technology period as IT, as a service that they pay for. Uh, many ............................ a desktop app or like Windows Remote Desktop is very common in our industry. Uh, but still it's, it's something they buy and therefore you don't control the code base. If you wanted to add AI to automate something or do something you're like, "Ah, it's not really... it's hard." You know?

   13. SPSpeaker5:59

       Has there been a specific moment since ChatGPT launched where you started as a company, sort-

   14. SPSpeaker6:04

       ... taking it more seriously, or, or... 'Cause, uh, my impression is, like, the first version was a toy. Even within the YC batches, like, we would sort of see some founders playing around with things, but it wasn't clear that they'd actually be, like, companies founded on it. Mm-hmm. So I'm just curious what's, like, founder running large-scale company... You start out, you're like, "This is really interesting to me personally." Like, was there some moment where you're like, "Oh, like, we should probably try and, like, build something or do something internally with this"?

4. 6:27 – 12:03

   The benefit of internal hackathons

   1. RPRyan Petersen6:27

      Yeah. I think a lot of it has come through i- in our hackathons. But there could be an interesting metric here is like, what percentage of hackathon projects, first of all, used AI? Like, we're building something with large language models. Uh, and which percent of the projects actually you decided to fund and push into, like, h- "Let's actually make this thing real, it's not just a hack," um?

   2. SPSpeaker6:44

      I- is hackathon something you've done for a while? Is that like a-

   3. RPRyan Petersen6:46

      Yeah. We usually do two a year.

   4. SPSpeaker6:48

      Okay.

   5. RPRyan Petersen6:48

      Uh, I think now we're, like, p- kind of religious about two every year. But, um, but s- d- one to two a year, uh, where... And for us, it's, uh, uh, uh, very much a free-for-all. You can build anything you want. If you look now at the last two hackathons we've done, they've been like 90% LLM-based projects.

   6. SPSpeaker7:04

      Nice.

   7. RPRyan Petersen7:04

      I- in my int- I haven't s- studied it, but it's just like feeling, my feeling in my gut. Whereas probably 18 months ago, there were like four or five, on a-

   8. SPSpeaker7:11

      Interesting.

   9. RPRyan Petersen7:11

      ... we- there's probably 50, 60 teams that do a hackathon project each time. In the beginning of, of Flexport, I was very much of this idea that, like, you just let, let the peop- get smart people and get out of their way and go execute. Uh, and-

   10. SPSpeaker7:25

       Oh, that sounds like manager mode.

   11. RPRyan Petersen7:26

       Yeah.

   12. SPSpeaker7:26

       (laughs)

   13. RPRyan Petersen7:26

       I- I- it was- I, I had way too much manager mode and I had this idea of, like, human beings are gonna flourish, if only they could be set free.

   14. SPSpeaker7:33

       (laughs)

   15. RPRyan Petersen7:33

       They don't wanna be told what to do by the man. That's why I started the company. I don't wanna be told what to do. And I went through my own Chesky moment of founder mode and recognizing, oh, you've got to be way more tops down and directive and tell people what to do and get people aligned and rowing in the right direction. And that's been my evolution the last two years at Flexport. I've been pretty, way more hands-on and hardcore in directing the business. But then, as I see these hackathons, I'm like, "I never would have come up with that idea in a million years." And I, I gotta let these guys build what they wanna build and flourish. And so I'm starting to now come back on myself and say, "Where's the room in our product roadmap for bottoms-up innovation?" Uh, uh, certainly you see it in these hackathons. And trying to maybe even start making sure I do the hackathon timing before we s- we do our kind of roadmap exercise every six months or so. We, we should probably do the hackathon right before that, so that when you see a great idea, you can budget it, instead of after the budgeting-

   16. SPSpeaker8:26

       I mean, there's a noteworthy change here that's happening for you, that, um... I mean, I think most, uh, companies might throw a hackathon and then in most hackathons the pro- 90% of the projects are just like toys and you never return to them again. Like, you know, someone gets a nice participation trophy and that's it.

   17. RPRyan Petersen8:43

       Yeah.

   18. SPSpeaker8:43

       But, like, it sounds like the difference right now in the age of LLMs and the age of intelligence is that these hackathon things are actually turning into real product lines and features for you.

   19. RPRyan Petersen8:54

       Yes. And, and at the very least, into debates in my head of being like, "Man, uh, I've got to do that." But I also, I lost... We're gonna, we're gonna crush everybody with just our regular roadmap. Uh, but I had this, after the very la- uh, I think our last ... Our next hackathon's in two weeks. So the last one was six months ago. It... I remember thinking afterwards, I'm like, "You know what? We could just only do that stuff and we'll also win."

   20. SPSpeaker9:13

       Huh.

   21. RPRyan Petersen9:14

       Uh...

   22. SPSpeaker9:14

       Maybe win faster? Maybe.

   23. RPRyan Petersen9:16

       It's highly unlikely that the person at the top now knows best what the best implications are, applications are. That it's, i- it's just as likely that someone on the front line who's closer to the problem is gonna go, "Hey, look, watch. It can do this." You go, "Oh, man. I ne- wouldn't have guessed it could do that." Uh...

   24. SPSpeaker9:30

       You kind of need engineers who are just really into it and have been playing around with it and just, like, understand how to, like, build the products in the first place to come up with the ideas properly.

   25. RPRyan Petersen9:37

       Yeah. Engineers, and engineers being really close to the business is something we've always prided ourselves on. Like, really being in the weeds. And one of the other things that we've done, uh, is create a program for non-engineers to learn AI skills. Uh, and it f- kind of formalized the program. 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, uh, different ways to apply. And it's, it's a new program, so we're only about six months into this. We'll see how it works out. But people love it and you are seeing gains. But the, 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." W- I'm sure we haven't have achieved that or it would show up in the metrics. (laughs) But that is the, the, you know, that's the idea.

   26. GTGarry Tan10:28

       How are you training all these folks to up-level skill in AI? What are, what are the sorts of things they're learning?

   27. RPRyan Petersen10:34

       Certainly, it's, it's Cursor and a set of related products like that, that like... I think we're using something called Streamlit, but probably a good YC company... I don't know, maybe we should use Replit or something-

   28. SPSpeaker10:43

       (laughs)

   29. RPRyan Petersen10:43

       ... with similar ideas. You can spin up, uh... build your own little apps. Um, build workflow automation tools to say... Okay, 'cause a lot of what Flexport is, we call it freight forwarding. Uh, I've often joked it should be called freight email forwarding, where you're like taking docs and sending it on. So, how do you look at a person's job and there's no one better to look at it than the person doing the job and saying, "Oh, man. I'm doing the same thing over and over again. What if I instead..." It's like if everybody was an engineer, they would... And I've thought about this in the past and saying, "Hey, what if I took one group of engineers and, and s- hire them as engineers as a big bait and switch and then tell them, 'Actually, you're just moving freight, sorry.'" And watch them automate their way out of a job, right? And you sort of say, "Okay." I- I never really wanted to do that to an engineer, 'cause I feel like I'd just have a revolt of...

   30. SPSpeaker11:31

       (laughs)
5. 12:03 – 14:40

   What internal AI projects have been most impactful at Flexport

   1. SPSpeaker12:03

      I wonder if you could share some examples of the AI projects that you have rolled out that have been most impactful over the last couple years. Both customer-facing features, but also, like, any internal operational things that you guys have automated that maybe the customers have no idea about.

   2. RPRyan Petersen12:17

      Yeah. Um, the customer-facing were probably the most impactful. Like, a lot of what you care about from a logistics company is your data.... what's going on with my supply chain, where, uh, the- the- the types of data that people are looking at. So the way Flexport works, you- you place orders through your factories through Flexport. So I'm replenishing my inventory, I'm buying things, I'm placing purchase orders. So those flow out to the factory, factory becomes a user. There's a nice network effect there. Once the cargo's ready, they place a booking, uh, and then we execute that, uh, booking to move the freight, come pick it up on this date, uh, and we'll execute it by air, ocean, truck, rail, whatever, and move it across the world for you. So that's kind of the, the loop that we're trying to run. So you care a lot about the data for on-time performance, SKU-level performance, cost, you care a lot about that. There's customs attributes here that are super important with tariffs and everything that's happening. So being able to get that data is one of the core areas that Flexport shines already, historically. With AI, and this did start as a hackathon project, we just built like natural language ability so that you don't need to know SQL, you don't need to build dashboards. You just type your question and it generates those graphs, charts, tables. Don't think it does maps yet, but it should. And it works, and that has done a wonder- w- won- customers love it, but two is, uh, it's about 25% of our account management time is spent helping people generate reports.

   3. SPSpeaker13:40

      Mm-hmm. Got it. Yep.

   4. RPRyan Petersen13:40

      That's the, another huge metric for us, is we're cheaper, we'll ... more people will choose us. It's not that we just started using AI with, uh, LLMs. Um, we've had a machine learning model for doing planning for ... 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? Therefore, you need all the contracts with their price, you need the sailing schedules, like how long is it gonna take, which route, variability, all the, around those, both those things. So our AI for that saved us 2% of our ocean f- freight spend while improving transit time 20%. Usually that's a trade-off. It's like it's either faster or cheaper.

   5. SPSpeaker14:23

      Yeah.

   6. RPRyan Petersen14:23

      But not both. Uh, so huge win there. Customers don't, they care a lot about those metrics. They don't care how we did it.

   7. SPSpeaker14:29

      And for that one, was the unlock parsing a bunch of unstructured, like, emails and data that you get from the shipping companies that have this, but it's all, like, in, like, a big paragraph where, like, you couldn't-

   8. RPRyan Petersen14:39

      The-

   9. SPSpeaker14:39

      ... just, like, run a simple query

6. 14:40 – 19:08

   What software can do better and faster in logistics

   1. SPSpeaker14:40

      on it before?

   2. RPRyan Petersen14:40

      Sort of, yeah. The way to think about it is, um, you've got ... if you just p- put a container on the cheapest contract, you, you've made a, it's an optimization, okay, which one's the cheapest, but also the fast ... you know, I'm, I'm trading off. So that, that's one thing that machines are better at. Uh, and then it's the scale of that. So on a given week, we have about 2,000 containers that get canceled by our customers. They place the booking and then they say, "Oh, actually, the cargo's not ready. The factory's late." It's just inevitable. It's gonna happen. What software does that humans could never do is go through 10 times a day and taking each one of those containers and saying, "Okay, I lost this container. It's been canceled. Is there another container that was meant to depart one week from now? And I'll grab that and move it forward." That's how you get the 20% transit time increase. And then the optimization piece of find- is just find the cheapest contract, like a solver al- you know, algorithm to go find the cheapest one.

   3. SPSpeaker15:27

      And the humans can't do that because it has to happen really quickly?

   4. RPRyan Petersen15:29

      'Cause it's happening 10 times a day for every container in the system.

   5. SPSpeaker15:32

      Okay. Okay.

   6. RPRyan Petersen15:32

      You know?

   7. SPSpeaker15:32

      Ah, yeah.

   8. RPRyan Petersen15:32

      It's just like you wouldn't ... maybe you could, but you wouldn't, right?

   9. SPSpeaker15:34

      You have to hire, like, an army of people doing it.

   10. RPRyan Petersen15:36

       The labor costs would be crazy.

   11. SPSpeaker15:37

       Yeah.

   12. GTGarry Tan15:37

       If you calculate this first principle, sounded like that first version was using classical optimization problems, and you had certain data about all these shipments, inputs, outputs, and schedules. What do you think is the delta that you could get with AI now that you can harness all the unstructured data?

   13. RPRyan Petersen15:52

       So-

   14. GTGarry Tan15:53

       What kind of efficiencies could you get?

   15. RPRyan Petersen15:54

       You may be able to get a lot more now that you're starting to see tool use, because the tool itself is incredibly powerful. And I don't think an L- LLM will outperform that. But the LMM can use that tool, and it can do other things outside of that. So you can, uh, we'll see. We haven't started to do that yet. So we're actually still using that.

   16. SPSpeaker16:09

       I can actually email people or call them up and-

   17. RPRyan Petersen16:12

       Yeah. But it, it could, it- it, you assign the LLM the same solver problem, but it is gonna default to use this tool. And then it'll also say, "Yes, maybe this container, I'm not sure if I could move it forward. I should ask the customer, would be a good idea, actually."

   18. SPSpeaker16:25

       Yeah.

   19. RPRyan Petersen16:25

       Email that, "Hey, is it okay if I bring you this container early?" Some-

   20. JFJared Friedman16:27

       Like the solver's still there, but then, uh, basically the agent is the user.

   21. RPRyan Petersen16:32

       Yes. Instead of right now there's not really a user or there's a, there's someone who's approving the plan and so you could make that person upstream of the solver, uh, choose the solver as one of many tools. So that'd be interesting. We haven't done that yet, but ... And then the other thing is sort of just routine work. Uh, for example, you've got a lot of email communication with your customer base. So how do you take this? You- you say, "Hey, I want to place a booking for a container." Translate that into a booking.

   22. SPSpeaker17:00

       Mm-hmm.

   23. RPRyan Petersen17:00

       Uh, LLMs are quite good at that. Or, um, a big use case today is verifying warehouse addresses and, and other information and getting appointments. I've got to deliver it to a warehouse, quite costly to call the warehouse and be like, "Do I have the right address?" Look, you're not gonna do it every time and then you have a lot of misses where your address data was bad and your truck got lo- you know, it's pain in the ass. Um, so LLMs now before we deliver, we, if we haven't delivered to the site in the last three months, there's an LLM agent, it does email and voice.

   24. SPSpeaker17:31

       Interesting. Wow. So if necessary, it'll actually call the warehouse and be like, "Hey, can you confirm that 2:00 PM tomorrow is a okay time to deliver this?"

   25. RPRyan Petersen17:39

       Yes. Yes.

   26. SPSpeaker17:40

       Oh, very cool.

   27. GTGarry Tan17:40

       Which is great because you're turning this previous communication protocol, which is very much, um, I suppose very lossy, to work sort of like the internet, like TCP fully, uh, acknowledge and you can-

   28. RPRyan Petersen17:52

       And-

   29. GTGarry Tan17:53

       ... get guarantees.

   30. RPRyan Petersen17:54

       And sometimes it's not replacing work, although I'm very happy to do so. But like in some cases the work would have been too expensive so you just didn't do the work.
7. 19:08 – 21:18

   Do goods get cheaper if more logistics get automated?

   1. JFJared Friedman19:08

      affect, like, the total cost of ocean freight? Like, if all the human work gets automated, does stuff actually get materially cheaper?

   2. RPRyan Petersen19:15

      Yeah. Uh, it's 10% of the end cost that the b- uh, the importer/exporter pays for their freight. 10%, uh, if you look at the full PnL, about 10% is the labor cost in the freight forwarding layer of logistics.

   3. JFJared Friedman19:29

      Wow.

   4. RPRyan Petersen19:29

      So-

   5. JFJared Friedman19:29

      So, so when AI is, like, fully rolled out, like, stuff will actually get 10% cheaper. Just 'cause you've got automated-

   6. RPRyan Petersen19:35

      Well, the freight of moving the stuff.

   7. JFJared Friedman19:36

      Yeah, r- okay.

   8. RPRyan Petersen19:36

      The cost of moving it, right?

   9. JFJared Friedman19:37

      Got it. Got it.

   10. RPRyan Petersen19:37

       The stuff itself depends on-

   11. JFJared Friedman19:39

       Got it. Got it.

   12. RPRyan Petersen19:39

       ... on what, what the ratio is-

   13. JFJared Friedman19:40

       The-

   14. RPRyan Petersen19:40

       ... but yeah.

   15. JFJared Friedman19:40

       ... the, but, like, the transportation costs of, like, international freight is actually, like, 10% auto- like, wow.

   16. RPRyan Petersen19:45

       On containerized ocean freight, that's our, that's our view, is that we can drop the price of everything by around 8%, and maybe it goes to 9%, uh, over the next few years by doing this.

   17. GTGarry Tan19:55

       That has some, uh, big economic ripples in terms of if it's becoming cheaper to ship things across the ocean, is it gonna create just more trade? I mean, there's also trade wars, but...

   18. RPRyan Petersen20:04

       It's, exactly, it's very hard to control for that in the mir-

   19. GTGarry Tan20:06

       (laughs)

   20. RPRyan Petersen20:06

       ... in the world where tariffs just made everything-

   21. JFJared Friedman20:08

       Yeah. (laughs)

   22. GTGarry Tan20:08

       (laughs)

   23. RPRyan Petersen20:08

       ... like, 10 times more expensive, but it, we, we're doing our part. (laughs)

   24. JFJared Friedman20:11

       I mean, the white pill on AI right now is, you know, this hope and sort of possibility that, uh, AI rolled out properly across society would increase GDP 7% a year. (laughs) So this would be maybe 50%.

   25. RPRyan Petersen20:24

       7% a year will double you in 10 years is the, the law of 72.

   26. JFJared Friedman20:27

       Yeah, yeah.

   27. RPRyan Petersen20:28

       That is the hope, right? And I think more people should talk about that and, uh, and everyone's so worried about automating away the jobs, and I just think that misunderstands the role of companies in the, 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. And then there's this idea, "Well, how are people gonna make money if AI's doing all the work?" And I, I, I think that that very much misunderstands human nature that we'll, we'll just want more things. Like, there's an infinite desire inside the h- the, the human soul can never be satisfied w- without God. (laughs) Uh, we need m- more stuff. Like, we gotta have more, we gotta have more. And so...

   28. JFJared Friedman21:14

       We're trying to return to, uh, the garden.

   29. RPRyan Petersen21:16

       We may get a return to some

8. 21:18 – 23:51

   The spiritual/philosophical implications of AI in society

   1. RPRyan Petersen21:18

      ch- I, I think that actually the internet first, we haven't quite reconciled this on like a spiritual, philosophical level, the, the emergence of these technologies and, uh, and AI we're not even beginning to, of what it means for us. But there's a period in history called the Axial Age, it's, uh, about 500 years BC, and that's when, um, coins really started to spread. What you had with, if you think about it with coins is taking transactions between two people and make, and really, uh, making them very in- impersonal. You no longer care who you're doing business with. "I don't need a, the ledger, does this guy owe me money? What's my relationship? Do I trust him?" Just like, "Here, take this thing." So you, and it, it actually led to this breakdown in societies because, uh, we just stopped being so knowing your neighbor, like you used to only do business with your neighbors, now you can just do business with any old person. The internet kind of does that at scale. What happened in the Axial Age, you had this breakdown of ability for, of trust, and d- you started to get degeneracy and all kinds of, like, things that start to break down in society. And simultaneously across the world, you had four pr- major prophets that emerged, uh, yeah, well, prophets as of sort. You had Buddha, you had Lao Tzu, Confucius, and Socrates. They all lived at the exact same moment in time, right as coins were taking hold.

   2. JFJared Friedman22:33

      Fascinating.

   3. RPRyan Petersen22:34

      It's like a, "Hey, we need to..."

   4. GTGarry Tan22:36

      (laughs)

   5. RPRyan Petersen22:36

      "... we need to kinda, like, get our hands around how d- how do we behave in this new world." Uh, and so it, I did think there, there's an opportunity here, maybe it could be you, Gary, at YC, uh...

   6. GTGarry Tan22:44

      (laughs)

   7. JFJared Friedman22:44

      (laughs)

   8. RPRyan Petersen22:45

      ... to, to be the next, uh, the next Socrates.

   9. GTGarry Tan22:47

      No.

   10. RPRyan Petersen22:47

       Yes, Buddha.

   11. JFJared Friedman22:49

       I, I'm in, but I-

   12. RPRyan Petersen22:50

       (laughs)

   13. JFJared Friedman22:50

       ... might not be the right person.

   14. RPRyan Petersen22:51

       (laughs)

   15. JFJared Friedman22:52

       But I mean, I particularly like this idea that, like, the idea that what are humans going to do is a little bit invalid in that, you know, that's a little bit like going back 500, 800 years and saying, like, "Oh my God, all of us are farmers, and then what are we gonna do when modern agriculture comes?" (laughs)

   16. RPRyan Petersen23:10

       Yeah.

   17. JFJared Friedman23:10

       And it's like, we figured it out. Like, we... You know?

   18. RPRyan Petersen23:12

       Or, or take the, the printing press.

   19. JFJared Friedman23:13

       Yeah.

   20. RPRyan Petersen23:13

       Right? What are the, what are the monks gonna do? They're transcribing words all day. There's no more jobs for transcripts. You're like-

   21. JFJared Friedman23:18

       So there will be implications for society and morality and how people relate to one another, and obviously, like, we're, we're seeing it right now.

   22. RPRyan Petersen23:25

       And w- we have no idea what this will... It's early days, but history does kinda repeat, and there's lessons there and figure out, "Okay, how does this..." But the human nature doesn't change much, right? And we... You can't satisfy humans, they're just gonna want more stuff. The more money you have, the more... Classically, right? Cliche, like, the more you have, the more you want. That's not gonna go away. So if you give people a lot more stuff, it's not like, "Oh, I'm gonna quit working." Most people aren't like that. "I'm gonna get a lot of stuff, I'll just quit working." You find out you're miserable, you wanna keep producing, keep contributing.

9. 23:51 – 26:38

   How does AI change the model structure for companies?

   1. JFJared Friedman23:51

      One of the interesting things that has been percolating around the YC community among young founders and, like, AI researchers that we've been talking to is this idea that, like, there are going to be humans in the loop. The humans in the loop may well be, uh, some, some might be, like, government mandated, right? You know, in fintech there's a lot around, uh, you cannot have an AI algorithm, like, approve loans, for instance.

   2. RPRyan Petersen24:14

      Mm.

   3. JFJared Friedman24:14

      There are, like, requirements from the government-

   4. RPRyan Petersen24:16

      Mm.

   5. JFJared Friedman24:16

      ... in these high r- highly regulated industries to have humans in the loop. Uh, and then-

   6. RPRyan Petersen24:21

      In customs brokerage as well, we have to have a human that's approving the transaction befo- before we clear customs.

   7. JFJared Friedman24:25

      Yeah. And so vibe coding's happening. There's this idea of you enter a prompt, it comes back with a bunch of stuff, and then you just...... click Accept All Changes without reading any of it.

   8. SPSpeaker24:36

      Mm-hmm.

   9. RPRyan Petersen24:37

      Hmm.

   10. JFJared Friedman24:37

       Right? Do you think this might happen, that- would this happen at Flexport or would this happen, uh, writ- more broadly across all businesses? Like, what if businesses are, at the core, like, hyper-intelligent AI that, uh, has access to all your systems of record, knows what to do, optimizes constantly, and then you have sort of, like, government-mandated liability sinks that are humans in the loop? Ideally, the organizations still actually serve human needs. In which case, like, the decision to use, you know, vendor A or vendor B sometimes boils down to who brought me to the nicest steakhouse last.

   11. RPRyan Petersen25:12

       (laughs)

   12. JFJared Friedman25:12

       So then, like, the model for companies ends up being ASI of some sort, like some sort of AI process at the core of each company. But then, you know, humans attached to it as either, like, decision-makers in, like, you know, accepting or preventing liability and/or holding relationships with other relationship holders at other companies.

   13. RPRyan Petersen25:34

       Yeah. And presumably, you're still relating with- you're still s- here to serve humans.

   14. JFJared Friedman25:39

       Yeah.

   15. RPRyan Petersen25:40

       You know, once we get to a world where AI is serving AI, then fair enough, you don't need to learn that much from the, uh, h- record of human history (laughs) 'cause there's no more humans involved in the loop. And I- I don't have a lot to say about that. But as long as there's humans there, there's gonna- humans are gonna want to relate with other humans and have a relationship. And I think we're pretty, pretty, pretty far from humans preferring to work with AI than to work with other humans. We're seeing where AI is doing more and more work. Uh, you know, another good example is, uh, uh and- just that you made me think of with your bank, uh, you know, you have to have an approveler- approver, is that even our- our humans in customs brokerage across the industry, we benchmark and make about 2% mistakes, and they file the entry with 2%. And we built this sort of, like, AI spellchecker. The two-digit code for Australia versus Austria, you could easily get that wrong.

   16. JFJared Friedman26:33

       You can, yeah.

   17. RPRyan Petersen26:33

       Uh, and the AI will figure out, like, "Oh, this thing is not made in Australia, it's made in Austria."

10. 26:38 – 30:22

    Would Ryan have built Flexport differently today?

    1. SPSpeaker26:38

       I guess one question for you, Ryan, is if you were to start Flexport today-

    2. RPRyan Petersen26:42

       Hmm.

    3. SPSpeaker26:42

       ... how would the company be different?

    4. RPRyan Petersen26:44

       Not that different, I hope. 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, um, 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, like I- we've got a new customer who's asking us to do something really weird. We need a crane on the truck to unload this thing, and we don't have that. It's not typical of what we do, and I just said, "Take the customer, and I need you to drive there and follow the truck and make sure this goes well." (laughs)

    5. SPSpeaker27:20

       (laughs)

    6. RPRyan Petersen27:20

       So I- I would not change that at all. And I think that's the- that's the mistake that a lot of tech, uh, people wil- in traditional markets will fail at 'cause 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."

    7. SPSpeaker27:36

       No tool use for cranes.

    8. RPRyan Petersen27:37

       Yeah, a- and it might take you a long time, and you should not try to automate that last- that tail of things.

    9. SPSpeaker27:43

       You started and grew Flexport, like, especially in the first few years, during an era where it's just, like, more money coming into- like, there's more venture capital each year-

    10. RPRyan Petersen27:50

        Yeah.

    11. SPSpeaker27:50

        ... coming into startups. And then you had- you had, like, multiple fundraising rounds. Like, in- in what ways was, like, that capital, like, an advantage? And I feel like now, we're sort of somewhat back there in the AI world now. Like, the rounds are heating up-

    12. RPRyan Petersen28:02

        Mm-hmm.

    13. SPSpeaker28:02

        ... there's more money flowing in. It just sort of, like, post, like, the 2022 crash. Yeah, what- what's your advice to the founders now who are in these, like, companies that are growing and have options to raise, like, huge funding rounds? Like, how should they think about it?

    14. RPRyan Petersen28:13

        Every company's super unique, so don't listen-

    15. SPSpeaker28:15

        Yeah. (laughs)

    16. RPRyan Petersen28:15

        ... to advice on a podcast. Like, uh, get someone who's-

    17. SPSpeaker28:18

        (laughs)

    18. JFJared Friedman28:18

        (laughs)

    19. RPRyan Petersen28:18

        ... like, paying attention, you know, knows the details of your business, which no one will know better than you. Generally, capital is a beautiful thing. Having it in your bank account gives you a lot of advantages. Uh, all you really need to care about at the end of the day is price per share 'cause if you issue more stock, like, the num- as long as your price per share goes up, you- you are richer. Uh, doesn't matter how many- what percent you own until it comes to control. So there's two things that matter. Do you control your company legally or otherwise? Culturally also works. But do you really have control over what's gonna- over the decisions that are getting made? And do you have a job and, and price per share? And that all- that's all that matters. And I think- I still think that's true. That's always how I thought about it is there's been a lot of dilution to our investors, but the price per share went up. And everybody's made better off. I didn't take away anybody's shares, so you're better off. The part that I underappreciated and that- and now I'm ve- take very, very seriously is the degree to which money just wants to spend itself. And you will end up making a lot of mistakes where... And the biggest mistake is believing y- for sure, every company has a lot of problems. And you start to default to, like, "Oh, we'll just use money to solve this problem." And the way that that manifests itself is, "Oh, I got this thing that we need to do. Okay, hire someone to do it." And you feel like you just end up very bloated, we had too many people, you start to really slow down. And it's just a super bad cultural approach to problem-solving. Like, you're gonna solve the problems, not the new people that are go- you're gonna hire. So I- I give this advice. Only one founder's ever listened to me. But I tell founders who- who- friends of mine who raise a large round is, "Sure, go raise a big round. As long as you're up a round, like, you're doing good, great. Raise a large round. Then do a hiring freeze for 90 days-"

    20. SPSpeaker29:52

        Hmm.

    21. RPRyan Petersen29:53

        "... the next day to tell your team culturally, like, 'Nope, the money's not gonna solve our problems. We're gonna solve our problems and keep that...' And then, sure, go hire, but it's- 'cause it's super: it- it happened to us over and over again where you just, like, headcount got out of control. So all the plans look good. I want to fund all the..." We're- uh, we're doing budgeting for next year, and I'm like, "God, I get- it's so painful not to-"

    22. SPSpeaker30:14

        Yeah.

    23. RPRyan Petersen30:14

        "... add OpEx, add engineers, whatever," but you gotta stay disciplined, and the money will easily make that stop.

    24. JFJared Friedman30:21

        So

11. 30:22 – 33:40

    Outro

    1. JFJared Friedman30:22

       I'm really psyched to hear about this idea that AI is actually transforming your business in pretty fundamental ways. It's, like, coming bottom-up. What does Flexport look like in 2035?

    2. RPRyan Petersen30:32

       One cool thing about Flexport is the way our vision has evolved. I mentioned we started as a customs broker.

    3. SPSpeaker30:35

       Yeah.

    4. RPRyan Petersen30:36

       Now we do all, end-to-end, all the way from factory floor to consumers' doors. Like, we have an e-commerce business that does fulfillment, retail store distribution, et cetera. So we want to take that globally to where you can really ship anything anywhere by any means, any mode, in any quantity, and do it all-... via code, like all available via APIs or voice or it's just, like, easy to ta- execute transactions at the lowest cost, automate away the cost. And so that brands, companies of all kinds don't spend time thinking about logistics. Logistics should be this utility that just works, just like you don't spend time thinking about the electrical grid. You flip the light switch, you get power. Uh, you go back to doing your thing, which is making something people want and talking to users, right? That's what I think r- companies should do. Our customers should be doing that all day. Like, make great products, make a great brand to sell those products. And we'll take care of everything in between in the most automated, efficiable- efficient, reliable ways possible, uh, on a global basis. So today, and we have a long ways to go to actually make all that true. First off, the automation stuff I talked about, making progress, but I got to keep going. And then the global aspect. So we have employee... We shipped cargo to and from, uh, 147 countries last year. But we only have employees in 22 countries. And therefore, people on the ground that can do the work, yes, we are automating that work, and in fact, it's easier for us to automate our own employees' work than it is some third-party company that's doing work. You know, even though they're in our software, it's very hard to automate. We don't know what they're doing. Um, so we want to be in every country by 2035 certainly. Uh, in fact, our roadmap has us covering 95% of all container trade with our own people doing all the work in the country, uh, in 2028. So by 2035, I think we could realistically say, "Look, we'll be everywhere that's- that's legal." And that is a big extension of our original vision, and I didn't have all that in mind when I did YC Demo Day. My pitch was like, "We'll do customs and then we'll add some other stuff," but it wasn't like, "We will cover the earth, any two places on earth, whatever you want to move, we'll move it." Uh, and so yeah, it's a very ambitious goal. The good thing is I d- we really, genuinely... We're gonna win on tech. We're winning, we're going to extend our lead there relative to our peers, our competitors. We're behind them on the global side, and that's super fun. If you told 25-year-old me that like, "Oh, Ryan, your job this year is we got to launch Flexport in Indonesia, Australia, Japan, Philippines, Turkey, and Poland and France." I'd be like, "Oh my, really? I get to go to all those places and talk to the locals and stuff?" So it's a, it's a pretty fun moment in our history, but also really challenging. But fun kind of challenging, you know.

    5. JFJared Friedman33:19

       No better kind. (laughs) Ryan, thank you so much for joining us, man. It's always a pleasure. All right, we'll see you guys next time. (instrumental music)

Episode duration: 33:40