The Freight Pod
The Freight Pod is a deep dive into the journeys of the transportation and logistics industry’s brightest minds and innovators. The show is hosted by Andrew Silver, former founder and CEO of MoLo Solutions, one of the fastest-growing freight brokerages in the industry. His guests will be CEOs, founders, executives, and leaders from some of the most successful freight brokerages, trucking companies, manufacturers, and technology companies that support this great industry. Andrew will interview his guests with a focus on their life and how they got to where they are today, unlocking the key ingredients that helped them develop into the leaders they are now. He will also bring to light the fascinating stories that helped mold and shape his experiences.
The Freight Pod
Ep. #76: Pablo Palafox, CEO & Cofounder, HappyRobot
What if your operations team started each day with every check call completed and only the real exceptions waiting? We sat down with Happy Robot co-founder Pablo Palafox to unpack how an AI workforce is changing the cadence of work in freight—beyond chatbots and into end-to-end execution.
Pablo’s path runs from deep learning research and a Meta internship to YC, a hard pivot, and a clear problem: late deliveries, fines, and interns glued to phones. That pain created an opening for agents that don’t just “assist,” but actually do the work—track and trace, carrier sourcing by phone and email, POD collection, and data updates—while writing everything back into your systems. We dig into the three-layer model his team uses to scale results: execution (agents that act), data (records that get richer with each action), and intelligence (an observability layer where leaders can ask the business direct questions and get grounded answers).
We go inside the enterprise stack: why orchestration and developer-grade tooling matter, how forward-deployed engineers capture tribal knowledge and SOP nuance, and what “manage by exception” looks like for a rep when agents handle the repetitive flow. From reviving dormant LTL accounts to surfacing carriers for real loads, we talk about what to automate, what to avoid for compliance, and where human creativity stays central—especially in customer sales. Pablo shares real outcomes, including dramatic reductions in manual workload and teams redeployed to higher-leverage roles without heavy headcount cuts.
Call it minute one of a much bigger game. As operations interconnect—maintenance signaling brokerage, intelligence spotting margin leaks—agents become the connective tissue and humans become the strategists. If you’re serious about scaling service, protecting scorecards, and growing without linear hiring, this is a blueprint for turning AI from buzzword to advantage.
If this convo sparked ideas for your team, follow the show, share it with a colleague, and drop a review with the one workflow you’d hand to an agent first.
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Thanks to our sponsors:
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Before we get started today, I want to give a quick shout out to our headline sponsor, Stute Technologies. Every week on this show, I talk to operators who are crushing it on the service side but still chasing down payments. That cash flow gap is brutal when you're trying to scale your business. That's why I wanted to tell you about Stute. Stut is the AI platform that does accounts receivable work instead of just assisting with it. Their CEO, Tark, actually came from TQL, so he gets how logistics companies operate. I've known him for years and I truly trust what he's building. What Stute does is simple. Their AI actually collects your receivables for you, not some software that just helps you chase the payments. It literally does the work. It's up and running in days, not months. As an example, Bishop Lifting is using Stut for a 35% reduction in overdue invoices, millions more in working capital, and a reduction of manual work by 50%. If you're tired of your AR eating up time and cash, check out Stute.ai. That's S T U U T.ai. Tell them you heard about it on the freight pod. They'll get you collecting in days, not months, so you can focus on actually running your business. And let's get this episode started. It feels good to say that it's been a minute. I think it's been uh three or four months since I've recorded and uh at least three months since I've released my last episode with Chris O'Brien, which was a great one. You should check it out if you didn't see it. Um but I got the itch again, and you know, some some friends were for bugging me, like you, you know, you're just sitting there playing pickleball all day. Why don't you just at least put an episode out, a couple episodes a month, uh, keep us engaged. And I said, why not? Um, and I got the opportunity to interview someone fascinating who's building a really interesting, unique business in our space. Um, and this is, I think, a great one to come back with, Mr. Pablo Palafox. Did I say your last name right? Yeah, that's perfect. Appreciate it, man. Very excited to be here. Yeah, welcome to the show. Um I I, you know, I I know you've done some podcasts before, and um, I know I remember I watched some of the Freight Caviar one way back when you did that. Um, and I think my goal going into this is a couple, I have a few goals here. One, I want to get deep with you. I want some depth. Um, I want to really understand Pablo the person, and I think that's where we're gonna start. Um and then I, you know, I certainly want to hear the story of Happy Robot, um, the origin of it, and you know, how it's kind of developed over time. Um, certainly some of the accolades or some of the kind of milestones is you guys have raised some serious cash and um had some big moments in your in your um I guess relatively short history. Uh and then I want to talk about like what's really happening in this industry and how companies like yours are changing things, improving things, making an impact, and and what the future might look like. So, um, how does that sound in terms of a game plan for us today?
SPEAKER_02:I love it. I love it. Let's get into it. Awesome. Very excited.
SPEAKER_00:Okay. Well, let's start with Pablo the human then. Um before we get into Happy Robot. So kind of before Happy Robot, like who were you before all of this? Like, talk to me about kind of the experience that shaped you and and how you think and how you how you operate today.
SPEAKER_02:I think if I have to go back to uh a couple people actually, I would probably go back to uh to my mom and on my brother and co-founder, Javi. Obviously, my my sister and my my dad have played also a big part in me growing up, but uh my mom would basically sign me up for anything and everything, like sports, music. Like I would just go like five hours every day after school to like the conservatory, like to play learn how to play piano and stuff. Uh and then my brother would actually inside more of the sport piece and actually sign me up for like all soccer matches ever, like uh just to like basically train a me and him. Like he would basically have like a partner to play soccer with, so or football in Spain. I grew up in in Guadalajara, uh near Madrid. Uh Guadalajara, there's there's a small city in Spain, 70k uh people uh right next to Madrid. So we grew up there. I grew up basically multitasking. Uh I'm like a I'm a doer. I'm uh probably a less of a strategist as my brother Javi is. Uh I'm more of a default to action. No, like I just want to do things.
SPEAKER_00:I'm the same way.
SPEAKER_02:That defines my personality a lot. Uh if there's someone proposing something, I'm like, I like that. Let's do it tomorrow. I'm like, wait, wait, wait, wait, let's think about it. I'm like, no, what is to think about? Uh I like the idea. But uh but yeah, that that definitely shipped me up, we're not a lot of multitasking, a lot of doing different things. Very curious, I would say. Very like um teacher's pet, you know, like I would just like be there, like, yes, I know that answer. And then uh in university, you kind of get like the your in college you get your your uh facing reality, like holy shit, like there's a lot of things that I don't know actually. And like I'm now getting like like uh Fs or like uh like barely passing exams. Like that's not that's not powerful. But then like uh you you learn how to like face reality and and face a failure, if you will, to failure, you're fa you're failing uh an exam that's that's uh probably not that big of a failure, but um, but it it it has shaped me up in that way, you know, like uh thinking that everything should be perfect in my life, no, like I'm like the best student, like doing sports, blah blah blah. Then like you go to college, I then end up doing my PhD, and there's like a lot of uh facing reality again. Like, oh, I I wrote this paper, uh, I've put in like hours and hours of work into these research papers. This was when when I was doing my PhD in Munich back in 2020, and it got rejected. Uh like why? Why did it go reject?
SPEAKER_00:What were you what were you writing about? What were you studying?
SPEAKER_02:I was doing uh at the time deep learning. Uh I was doing 3D computer vision, basically. So you you would have like a depth camera uh looking at a room and you would reconstruct the people in that room moving, the the geometry of it. So it was deep, like what we would say like neural networks, uh like at the time, like just deep learning. We would not even say AI at all. It was like that's like the sacred word. You don't say AI in 2020, 2019, 2020. Uh I ended up doing a research uh internship at uh Meta in 2021. That actually faced or shaped me up also in a way that uh that I realized I didn't want to work in big tech. Uh this was 2021, uh COVID time. I did an internship remotely. I should have been in Sao Salido. Today I'm calling from San Francisco. I should have actually been here in 2021, but COVID did not let that happen. And at that point, I'm like, okay, I'm done. I don't want to write more research papers, I've done enough, I'm gonna quit. So I drop out of the PhD in 2022. Uh, and then I take like a bit of a sabbatical with my with my uh with my one of my best buddies, uh Luis, uh, who's our CTO now. Uh he comes to Munich. We jam for uh months, we kind of do the the the let's think about ideas. Like we get some grants from Germany, we uh we play ping pong every afternoon uh in a small village in Munich, near near Munich in Neufalen, uh tiny village next to Munich. Javi, I was uh at that time like still working as the CFO of this olive oil distributor uh leading North America, is like giving us stipends to like sustain. It's almost like, let's try startups. Like you don't even know what a startup is. And we're out of Germany in Europe, which is not like a it's a decent environment compared to other places, but not like SF in terms of uh VC money and all that stuff. Maybe I'll stop here. I don't know. I've I've probably gone too far.
SPEAKER_00:Yes, uh no, you're not going you're certainly not going too far. Uh I do have questions. Let me ask first, how old are you today? How old is your older brother?
SPEAKER_02:I'm 31. I just focused on uh a few weeks ago. Uh Javi is 10 years older. 41. If you met Javi, you would not make that bid. I mean, he takes good care of himself of himself.
SPEAKER_00:Yeah, I mean to I mean, especially you know, being a C CFO of uh of a North American olive oil company, I assumed he was a little bit older than you. Um and in you know, you certainly have younger vibes um to yourself as well. So I'm curious, like you seem to have been a very good student, uh a learner, and but like it didn't not much of what you talked about screamed entrepreneur founder. And I'm curious, like, was there a point when you decided like I don't want to be a student anymore, I want to be a builder, or was that always the path? Like, talk to me a little bit about when that mindset became what it was.
SPEAKER_02:Actually, I have this question for candidates. I asked them uh what guide me through your light bulb moments in life, and I explained to them the one I'm gonna uh I'm gonna explain here. Um I ended up doing my master's, uh, double degree master's in Munich for um mechanical engineering. Although I had done a lot of robotics uh during um my my bachelor in in Spain. When I ended up in Munich in 2017 doing this double degree in mechanical engineering, um I was not really sure what I wanted to do. I start seeing my colleagues, some of my friends, do these things called uh ML and deep learning. I'm like, what the hell is that? Like I've just been like doing some very basic Python stuff. I don't even know how to code properly. And I see these guys uh building neural networks, I didn't even know what that was back in 2017, um detecting objects, predicting the geometry of things. I'm like, that's pretty cool. I want to learn about that. So I remember one night uh in my my student uh room in in Munich, I'm just gonna drop everything I'm doing with this mechanical engineering thing. I don't even want to do that. Just gonna go to the informatics faculty tomorrow, see what I can sign up for. I won't get the credits, who cares? And I'll just figure it out later. And just like try to get into uh a PhD position there. I actually kind of realized at that point, like I actually want to go deeper into learning all of these deep learning AI stuff at the time, if you will. Um and that that kind of shaped me up uh a little bit. That was my my light bulb moment. Um and that light bulb moment, I think it's connected to the entrepreneurial journey in that I wanted to have something to do with real with the real world. No, like I wanted to see applications of it. I think that was starting to like uh instill in me a little bit of that entrepreneurial mindset. I want to build things that are tangible. I I bought a couple cameras, I set up like a like a rig, and then I could like generate the the geometry of my room. I was just like recorded and like generate the 3D geometry. Like, yeah, I could maybe build like a product out of this, I don't know. Uh and then during the PhD, while I was getting frustrated, a little bit of just simply writing papers, although I was building really cool stuff that actually worked, I really wanted to bring that to reality. And I was very frustrated that even during the P the the internship at Meta, I was not able to truly see that in practice and like come to fruition. It was just like a research project that probably someone took over. Uh fun fact is that I actually waited my entire internship for a certain data set of faces. I went into like face recognition and stuff. Never came. I had to like do other type of geometry, like uh like full body scans or whatever. Uh so that that was like, okay, I know I want to build stuff. I know I don't want to build it in big tech because it takes it takes ages. So I guess my only alternative is to like build something uh myself. And then I uh dig deeper into all these MBAs. Uh I do like find these this online MBA, the power MBA, like some Spanish guys that build like uh like an online MBA, okay. I mean I'll do that. How bad can it be for uh 500 bucks? And it was it was pretty decent actually. And that that stirred me up, you know, like there's something here, I want to do more. So I I at the time I was also doing uh in parallel to the PhD, like uh uh for fun, just looking into buying property in Spain. In Spain, it's uh I mean you can find a place for like 40k uh euros, whatever, rented for uh 500 500 dollars, uh 500 euros a month. So like super, super good ROI, um especially in certain cities around Madrid and especially not in Madrid, no? Like so in my in Guadalajara where I grew up, I'm like, okay, I'm gonna go buy five houses, uh I'm gonna ask for loans, uh like zero interest rate or whatever at the time was like super good interest rates. Uh and I'll just like get rich doing that. And then I I ping my my buddy Luis and and Jali and I'm like, guys, let's let's do this, let's like do this together. And Luis is like, Luis, our CTO is like, dude, no, let's build a software to help us find the best houses, and then we sell the software.
SPEAKER_00:Like fast thinking.
SPEAKER_02:That that that is that's that's my see, like again, like a default to action, no, like I just want to like do stuff, and then like how you lose for more strategic, right? Um uh so that was like a little bit of the of the trigger. We applied to some accelerator in Spain, in Barcelona. Um, I mean this is quite funny. Like we had uh we had one of the advisors, he was like, guys, this is super interesting. Let's build it together. I'll get 20% and I'll advise you. I'm like, that sounds like a lot, but I've never done a startup, so I guess it's right.
SPEAKER_00:I understand that. It's you know, you're the first time around, you're just kind of poking and figuring sh stuff out as best you can, and uh especially when you're looking for like you know, ideally your advisors are the ones who would then tell you that's a bad deal. But when you you're you're finding the first advisor, that that's maybe the one that could uh rake you over the coals a little bit. English is your second language? Is that right? Spanish is when did you when did you sparts start speaking English?
SPEAKER_02:Uh maybe around age five, six.
SPEAKER_00:Oh, very early. Okay.
SPEAKER_02:Relatively early, yeah. My my mom like um found this supposedly bilingual school. Uh and she was like, okay, I'm kicking you out of the current school. I was like five. I'm like, okay, I guess I'm changing schools now. Uh and she put me in this bilingual one. We had like a few teachers that were like either British or American. So I my accent is all over the place. I've after living in Germany for a while, my accent actually got like very Germanized, which was funny. My brother, Javi, would make fun of me.
SPEAKER_00:Is that is it common in Spain that that kids would go through that and be learning English at such a young age? Like, I mean, uh certainly it sets you up. Your mother never could have known that you know, 20 years later you'd be building a business in the US. Yeah. But if you hadn't learned English 25 years ago, I don't know that it'd be as easy for you to be sitting on a podcast right now and having an English conversation uh as fluently as you are, or really just building a business. So I'm curious, like, is that more common where you were, or did your mother have some foresight that others didn't?
SPEAKER_02:She she did have had a lot of foresight there. Uh my my generation and my brother's generation, it's like 10 years uh older, definitely did not have that exposure uh to these opportunities. This was like a bit of a one-off uh in our city, actually. And probably like uh one of the very few in Spain that were part of this British council. Like um like this British council uh would actually find like a few schools and they would give them like access to to teachers that they could send over. So very lucky, very lucky to have had that. Uh I think now it's more common, especially because you have exposure to TV shows. Like my my nephews, uh, they speak almost like native speakers, and they're like five, ten, and twelve. And like, guys, this is crazy. Like I when I was your age, I would just say hell hello, my name is Pablo, I'm here to to work with these uh in this podcast. So I mean and now it's actually it comes really natural to to just actually many times it comes more naturally to speaking, to split explain something in English than in Spanish. I did a podcast in Spain, uh uh it was terrible. It was terrible. Like I would just like not find the words to explain we're building an AI work first for the enterprise. How do you say an AI work first? It was so bad.
SPEAKER_00:Really interesting. I mean, how often do you speak Spanish now? Is it just very rare?
SPEAKER_02:I mean, with my wife at home, um for sure, and then with with Javi and and Luis, uh when we get more into fun stuff or like just talking about anything, we just talk in Spanish. Um But anything work-related, it's harder to explain in in Spanish, for sure.
SPEAKER_00:Do you have any customers that are over there, or it's all everything's US-based, basically?
SPEAKER_02:We have uh quite some customer base, quite a customer base there. We have four offices right now. We have San Francisco, Chicago, and then Madrid and Barcelona. Barcelona is actually more of a, for now, more of a our machine learning hub. We have uh five ML engineers there. Don't ask me how we ended up having that there, but like we just kept finding good guys. Uh Barcelona has attracted uh traditionally a lot of good uh talent from all around Europe. Uh actually, one of the students that I supervised uh during my PhD time, we we uh posted him uh before he started a PhD, we posted him and brought it from brought him back to Barcelona where he's from. He's actually originally Chinese, though. But um so we have that. Uh in Madrid right now, we kind of serve it uh or use it as a main hub for Europe, uh, although we're thinking about other other locations. And we probably have maybe like 20% of our customer base in in Europe. The thing is uh a lot of the freight forwarding and international logistics, if you will, that we're doing today, uh it's 24-7. We have deployments in Brazil, in Australia, uh Singapore, uh starting some in um uh United Arab Emirates uh and uh Middle East, basically, uh France and Denmark. So like it's all over the place in terms of geography, so we have to like cover 24-7, basically.
SPEAKER_00:Got it. Hold up, wait a minute. Let's give a quick shout out to our sponsor, cloneops.ai. Logistics moves fast. There are calls to make, updates to send, documents to track, your customers are always waiting. Cloneops.ai helps teams stay ahead with a platform that can be white labeled and a marketplace of AI agents built for real logistics operations. Inside the Clone Ops marketplace, you'll find agents for tracking, documents, after hour support, finance workflow, fraud prevention, and more. These agents plug into your workflows and existing systems to handle the repetitive tasks, whether it's making calls, sending emails, replying to texts, gathering info, or writing updates. Your team stays in control with real time visibility into every interaction. And because the AI is always turned on, operations keeps moving even when your team can't. A standout is carrier screening plus voice ID, which takes Ties a voice to a DOT number and alerts your team when that same voice appears across different or multiple DOT numbers, helping catch fraudsters before they cause damage. No one else has this. And for companies building a long-term AI strategy, clone ops.ai gives you the ability to white label, build, own, and control every AI use case across your business. And this team is run by David Bell, founder and leader who I've known for years, a good friend of mine, and someone who, frankly, anything he touches in this industry turns to gold. I trust him with what he's building here. If you're ready for automation that supports your people, visit cloneops.ai. Now let's get back to the show. I have questions about that, but I'm not going to ask them yet because we'll get stuck on the business and I'm not ready to go all the way into the business yet. We will get there though. So we're just one more, I guess, culturally. I'm curious, um, because I don't know enough about Spain. So, you know, I'm going to take the opportunity for myself, and I'm sure plenty of listeners will appreciate this too. But um, you know, growing up in Spain, what's kind of as as an American, I don't know much. So like what's your fate, what was your favorite thing culturally about um growing up where you did that's very different from kind of American culture?
SPEAKER_02:Well, I've only been here for two years now. I think the biggest difference, and this probably depends on the city you're comparing. But across the board, I would say that Spain, from an early age, since you're like I'm gonna say nine, you probably just walk alone to school. You just hang out with your friends after school, you go to the park together. It's very it's very walkable. Like all cities are very walkable. And I would say that's pretty much applicable to all of Europe. Now, in Spain, since you have like pretty good weather generally, I mean winters are pretty harsh though, but like in in general you have pretty good weather.
SPEAKER_00:Well, harsh, harsh is relative because it's like five degrees in Chicago right now. Harsh is relative.
SPEAKER_02:I I agree, I agree. That's uh that's a good point. Um and I've lived through that in in Munich, it was also like pretty painful. But um, but yeah, no, growing up in Spain, you get to enjoy the the city more, I I would say. I think that's why we like San Francisco a lot, uh, my wife and I. Um because it's very walkable in certain parts. I mean, obviously, maybe don't you don't want to go to certain places, but in general, it's very walkable, very neighborhood-y. Like there, you can go to a cafe and like just meet your friends there, go play some paddle, uh, learning some pickable as well now. Um you would do a lot of uh a lot of things out there, uh like outside uh with your friends. Um family uh weekends would be like you know, going to the uh going going going to uh to the to the park with friends, going to the uh church with with your family, and then like you go and uh we have the the the the post like the pre-lunch. Uh the pre-lunch like maybe 11 to 2 p.m. 11 a.m. to 2 p.m. you would have like that time range to basically just like have a beer, grab some bites, then at 2 you would have lunch. That's actually a very interesting piece of uh part of Spain. Like you have lunch very late, like pretty late, like two to four is like like lunchtime. Um maybe if you do work in Madrid or something, like you maybe do like one to three, but uh lunch is like a very big part of the day. And then uh another interesting thing in Spain is how how late we uh we have dinner, which actually shapes a lot of the things we do during the day. Like um, if you walk around Madrid at uh 9 p.m., 10 p.m., it's so lively. Like there's so much going on. Uh the city never sleeps on it, really. And it's it's very lively, it's very nice. Uh you feel you feel a good vibe, uh, generally. I liked it a lot.
SPEAKER_00:Do you feel like you'll want to go back, or are you, you know, US for life now?
SPEAKER_02:Man, I wish. I mean, things are not looking good there in terms of the economy, and it's uh they they see I mean I I am I'm positive for the for the future. I think for now, definitely not. Uh although we we do have uh we're very bullish on on serving um European customers, and I think it's uh it's a super interesting market. But personally, um like me going there, it would be pretty, pretty tough um for some for many reasons. But uh the the culture there also is is very slow, which is good if you're maybe retired, but if you're trying to build something, unless you're on very specific hubs in Barcelona, Madrid, uh it's almost consuming, no? Like almost people like judge you for doing the work you do. Like, why do you work so much? You're like putting too much on yourself, versus here, they actually see you as oh, like you're trying to do something cool and like building something that adds value to society. That's that's so awesome. Like kudos to you. There we have a little bit of a stigma. Um there's a lot of, and we don't have to get into politics, but there's a lot of polit uh lot of parties, if you will, that would um like judge you for like building a company just because you're like an entrepreneur or you have a small business. Small businesses, man, like they they treat them as garbage. Like they there's there's there's laws in Spain where you you have to pay taxes, even if you have not generated revenue that year, there's like a pre like a pre-tax on like entrepreneur, like um business owners, basically.
SPEAKER_00:Very anti-business, basically.
SPEAKER_02:You compare that to maybe like a UK where it's pretty simple to get started with a with your own like side hustle, and you get depressed. So that's basically where I said.
SPEAKER_00:Yeah, got it. Understood. So happy robots not going anywhere. Stay in in your stand in uh in San Francisco.
SPEAKER_01:Yeah.
SPEAKER_00:All right, well, let's let's let's transition into the business itself now. Um, I do appreciate the color on your own kind of origin story. Um how did all this come to be? You know, your brother was CFO at this olive oil company, you and your bestie Luis were jamming. You know, how how did we how did we come up with Happy Robot? What was the origin of that business?
SPEAKER_02:2023, we get accepted into IC with some random computer vision platform we had built based on my supposed experience on computer vision. So Pablo knows how to do computer vision. Let's capitalize on that. So we did that, we get into IC, we go through the batch. We don't find more than one more customer than what we had before we entered. We probably had like 70k in ARR when we got in. And we came out with like, I don't know, like 80k, I don't know, like something super tiny. Like, okay, this is not working, guys. And on demo day, there's this this demo day, this presentation to investors, the last day of the batch. Uh, we woke up that morning already knowing, and actually we slacked our partner, knowing that we would pivot, that we would just like not do that uh computer vision platform anymore.
SPEAKER_00:Did you know you're gonna pivot to?
SPEAKER_02:Nope.
SPEAKER_00:You just you just were supposed to present and you're like, hey, we this isn't gonna work.
SPEAKER_02:Exactly. We just we just knew we just felt it in at our core.
SPEAKER_00:Okay. So then pivot hill.
SPEAKER_02:Pivot hill for for three for three months, maybe two months or so. Um that was that was September when we when we decided to like fire all of our customers, and then we go into these search mode to this life quest to understand what we want to do. And um we kind of kept trying to find what experiences we had gathered ourselves.
SPEAKER_00:So is at this point, is it just you, Javi, and Luis?
unknown:Yeah.
SPEAKER_00:And is has Javi has Javi quit his CFO job?
SPEAKER_02:Yeah, yeah. He quit before he actually quit before we knew we got into YC, like around May that year.
SPEAKER_00:Okay.
SPEAKER_02:So he had already quit. Um and then literally the day he was this is funny, the day he was arriving in San Francisco, uh, because we we had decided to move to San Francisco regardless of the outcome of YC. We got the call from our partner Diana Who that we got in. So he was like literally unboxing, and he we got the the call that we got from cutting in, which is uh that was great. That was one of the best moments of our lives.
SPEAKER_00:Um so we go before hold on, was YC worth it? Was it a meaningfully beneficial thing? I mean, you went in with one business and you left with that same business, but it didn't work. Uh so what did you really get out of it?
SPEAKER_02:A really solid business now.
SPEAKER_00:Like uh this came from that, even though you know at the end of it, you still were you, you know, you it's it feels like if I understood you correctly, you get to the end of YC to demo day and you're like, this isn't gonna work. We're done with this whole business that we spent our whole YC term doing. And then you spent three months trying to find the idea for happy robots. So like I'm trying to understand like where the value in YC was. Please help me kind of gauge that.
SPEAKER_02:In knowing that we could aim for bigger, okay, knowing that we could go bigger, I think that was the biggest value, realizing that there's very ambitious people in this in this uh in this country, and in particular in this part of the of the world, trying to build very ambitious businesses just because they know that that even though it's gonna be hard, it's possible. So one of the things that one of our investors, um Are from Baystin, so we have our main two investors are Andrés Norwich and Basedon. We'll talk about that in a minute, I guess. But uh Are he's a Spaniard as well. He co-founded uh the Spanish Facebook uh 20 at the time he sold to Telefonica, uh one of the telecoms in Spain. Um and he tells us that after he sold his business to Telefonica and came to San Francisco to do his MBA and whatnot, and then built another company that he sold to work day. He was always thinking too small. And he urges us every time we talk to to think big and to be ambitious and to know that we can do it. You know, I think we we have a little bit of a stigma in Spain that, you know, like we're not we're not like that smart or we're not that good, like, you know, like the Germans are so organized and so uh so well uh polished and the Americans were so well spoken and they sell so well, and then we have a little bit of that stigma thing in in Spain where we don't value ourselves enough. So I think YC helped us rewire ourselves a little bit and think bigger. So the the cliff was there. Like we just saw how the cliff of having to fire your customers was was scary, but kind of it helped us cross the line, like cross the finish line, if you will, or across that bridge to know that we had that backup or that backing, if you will, that backing from YC as a little bit of a brand, and knowing that other people were also in the same boat, that helps tremendously, knowing that maybe 50% of your batch mates in YC are going through the same or worse. So that that helped a lot. I think that's why we exist today, honestly.
SPEAKER_00:What do you feel like outside of dream bigger? Like or I guess actually, just take me to the point where you realized what happy robots should be. Like, how did you get from you know this this original business isn't gonna work? We're firing our 80k of ARR, you're all gone. Take me from there to we know what we're gonna do.
SPEAKER_02:So after Puritan, we go into introspection and we say, guys, what have you what have we all done? And then we look at Javi because he's the one that he's actually worked at all in the right.
SPEAKER_00:What have we done? And you're like nothing.
SPEAKER_02:Like, does that count? I worked at Meta for six months. I mean, Luis had been working at HBE uh as a cloud like DevOps person. I mean, Luis is extremely smart. He's like the the hacker in the in the team. He like builds whatever you ask him to build in like no time. He he'll just he's also super creative, very, very, very nice guy. Um, extremely nice guy, I should say. Um he he basically wanted to do stuff for a while on on voice, like like basically um like some form of English trainer or some form of like psychologist, the typical like app where you can just like go B2C and and sell uh uh an app that people can use and and and make use of it. So voice at the time was growing bigger, but then we say, like, what are we gonna do there? Like we don't even know, we're not a psychiatrist, we're we're not a uh teacher, uh, we're not teachers, we don't know how to teach English. So then we kill those like B2C companies. Like, like, okay, please forget about that. Like, let's again look at look at Javi. Let's look at Javi. Javi, enlighten us. What do you what do you have? And well, Javi had been uh working for a while in in this company called Diolio, uh, which is um the the biggest olive oil distributor in in the in the world, actually. And he he was leading North America, CFO. So he had gone through a lot of of pains in managing his supply chain. In particular, uh he was working with uh one of the tough time frame brokers, and I must say who other they're they're uh great guys, but he was working in a certain broker, and at the time they didn't have enough bandwidth to basically just track all his loads. So he was uh messing, getting all his score cards from uh like Walmart and Krager would like basically gave give them like bad scores and like some fines for late deliveries, and he ended up hiring interns to call drivers, like essentially bypassing his broker. They were not happy about that. Uh but uh they figured it out. But but yeah, that was how we started digging deeper into okay, there's a problem there. There's you had a pain point, which is you're getting late deliveries to Walmart and Kroger, and you're getting fines, and you had to hire people to call and email drivers and carriers, whatever the carrier was, right? So we started digging deeper there and said, okay, there's actually something here. What if we build a voice agent? He said, I wanted to do LLM stuff. I hadn't really done any LLM stuff. We had done, like, remember, all this computer vision. So it was a mix of hey, there's this cool technology that is unlocking this problem that Javi might have. We don't know if this is a big enough problem. That's the that's the issue. We don't know if it's big enough. It might be that you know, like Javi's uh situation is unique uh when he was working at this company. Maybe, maybe not. We'll explore. So what we do is uh ask this company of his and we dig deeper into the whole broker space. So we go uh and I think uh sign up for freight waves uh November 23. We we send Javi there and he demos uh a terrible voice agent at the time. And it was decent at the time, but like now it would be so terrible. Like basically the latency was super high. And it was like a tracking trace call. Uh and he demos that to folks. And we get some more leads and more leads. And then I ended up in like the uh in the in the tech bro Tuesday with with Reed and these guys. Uh uh actually, thanks to uh to our friend uh Adrian from Gate Go and Mo on the Transport, uh he connected us to Read. And we I present uh in uh in one of these like Tech Bro Tuesdays in January. This is already January. And I do a demo, and they're like, wow, this is so good, man. And it happens to be that one of the um, there was a couple of VP, like one VP from one of the top 15 brokers and uh a data science guy from uh one of the top 40. Uh the top 40 was like both were emailing me like we should talk. The top 41 was like, we should talk, and I want to deploy these tomorrow. It happened to be uh one of our first, actually, our first broker customer uh circle logistics. So uh Andrew Smith, uh who's a great friend of ours, he got this demo from his data science guy. He connected us to his uh CFO. He gets approval for us to work together, and turn uh fast forward to April 2024, we're deploying an inbound carrier sales agent. I didn't even know at the time. I mean, we were just pitching track and trace. Uh so I didn't even know what that was.
SPEAKER_00:I mean, coming to You didn't even know what carrier sales was.
SPEAKER_02:Yes, yeah. I mean, now I think you could put me in a floor and I I would be like top like number one broker. You think so? I I think maybe what like cradle. Like I don't know how it would do with customers, but like just have you sold a load yet? Yeah. Yeah, yeah. Because I I had like the bot messing up at the beginning. So I would actually call the uh like this is April 24, like we were still refining stuff, and maybe the bot would say no to like a decent carrier. I'm like, wait, wait, I'm gonna call that carrier. So I would call them back, hey, this is Pablo, and they were like, what do you mean? I just talked to you. No, no, like the real Pablo.
SPEAKER_00:The non-AI Pablo, my AI screwed up.
SPEAKER_02:AI told you not to uh book this load, but yes, I wouldn't. So uh I I have I've actually uh I've actually booked loads and I've actually uh um yeah, I've I've I've sat down enough with folks to understand how how draining that can be, but how empowering it can be. Like if you if you manage to like create those relationships with with your with your carrier base, that was fascinating. And that's also why we're now pushing a lot uh uh for like our workers to to gather details and insights, our AI workers, if you will, our AI workforce for for the brokerage space, to gather a lot of insights for the carrier base. Actually, have like um what we call bridge, it's one of our brokerage products, uh, which has uh a load view, like uh like a track and trace view, kind of uh alerting and exceptions, like exception management. Then it has a carrier CRM kind of view where you can keep track of, hey, like Pete from ABC trucking, he typically likes running these Dallas to Cancel City loads. Uh and he has a daughter that plays soccer. And he likes calling us to update us on loads, and then he starts talking about soccer. So that that type of those type of insights are really interesting, especially now that we're doing a lot of uh outbound carrier sourcing via email and phone. It's super interesting how we can connect the personal touch and even say that it's a yeah, we we we now say both in tracking trays and and and and carrier sales, we we typically say, especially if it's outbound, like, hey, um I mean this is for the customer to decide. Like we we're very like, if you will, very enterprisey. So like our customers decide what they do with their workforce. We're just providing the the workforce for them. So they decide if they want to say, yeah, um Pablo uh uh from uh XYC logistics, uh the AI assistant to um to Andrew, uh he'd be he would love to call. But like now he's busy. I'm just like calling on on his behalf to see if you guys would have any any capacity for us tomorrow. So I started seeing by by sitting next to these folks how important the the the the relationships were, but also how draining the non-relationship relationship aspects of things were as well. Like a lot of this is just like rings and repeat. So we wanted to position the humans as the guardians of the exception. And that is what really triggered the whole the whole um going from just like a like a certain, like solving for a certain use case with track and trays or carriage sales to actually saying, wow, this is much bigger. We can actually be reimagining how work gets done in supply chain and physical operations. And we want to build a workforce for these enterprises to solve for that pain, to basically position the human as that guardian of exception that manages the 1% or 10% exceptions and edge cases, and have uh bit of that workforce of agents for sales, for customer sales, for carriage sales, for tracking trades, for accounting and back office, just working for the team. Uh and initially it was super interesting to see all of these threps were fearing the agent. The next year, basically this year, uh, and we have some customers that do these sort of uh uh analysis. Like they ask their teams like, how do you value this tool? And how do you position how do you what do you think about this tool or that tool? Last year we were like feared. This year, or loved. It's it's their assistant. It's their e it's almost like they have personal EAs. They can talk to them on Teams, they can say like, hey, uh they get they give it names, they they they call them names, like whatever name they want to call it. Hey, uh Maria or Tracy for tracking trace. Hey, Tracy uh, check on this load, and they text text it on Teams. Like they trigger uh uh uh Tracy to do track and trace for them via Teams or Slack. Uh hey Casey uh for uh care of yourselves. I don't know. Uh can you trigger an album campaign to try to see if we get some some capacity for these can get load? Uh we still haven't won from the customer, but like let's let's see if we can get some some market rate out and market date uh um in in the wild. So that was that was really interesting to see that transition.
SPEAKER_00:Okay, let's take a quick timeout and give a shout out to one of our sponsors, Rappido Solutions Group. Rapido connects logistics and supply chain organizations in North America with the best near shore talent to scale efficiently and deliver superior customer service. Rapido works with businesses from all sides of the logistics industry, which includes brokers, carriers, and logistics software companies. Rapido builds out teams with roles across customer and carrier sales and support, back office administration, and technology services. The team at Rapido knows logistics and people. It's what sets them apart. Rappido is driven by an inside knowledge of how to recruit, hire, and train within the industry, and a passion to build better solutions for success. The team is led by CEO Danny Frisco and COO Roberto ICasa, two guys I've worked with from my earliest days in the industry of coyote. I have a long history with them and I trust them. I've even been a customer of theirs in Molo, and let me tell you, they made our business better. In the current market where everyone's trying to do more with less and save money, solutions like Rappido are a great place to start. To learn more, check them out at goropido.com. That's gorupido.com. Now, let's get back to the show. So it's interesting, because the path I can let you talk and you could fill up the whole podcast. I wouldn't have to even ask a question. I could ask you one question and you could go for an hour. I love that about you.
SPEAKER_02:It's my uh my account.
SPEAKER_00:No, it's it's not a bad thing at all. It's it's it's a challenge as a host because you have to decide like when do I jump in? Because I've got a question here, and then you keep going, and I get a new question and then a new question, and I was like, where do I even go from here? Um But uh it's what I'm hearing is you know, day one, this was a track and trace communication tool. Day two, it became a carrier sales communication tool. Day three, and you know, the days aren't important, it's more timeline, but like eventually it becomes uh a data analytics tool to some extent, um, or or data capture um and then presentation. Um and I'm I'm curious, like, you know, does the evolution from communication to data does it eventually become like an ecosystem? Like, does it replace a TMS or does it live in a TMS? Um, you know what I'm getting at? Like, you know, just we've thought about that a lot. And and I'm curious, like, where do you see answer that when you get a chance and then move morph into like in terms of the maturation of the business? Are we uh are you a baseball or are you a soccer guy? You're a soccer guy. Like, are we at like the 10-minute mark of the first half or are we at halftime? Are we in in extra time? Like, where in if the business is maturation is a soccer match, where are we in the timing of the game of the match? Sorry, I want to stick with that. Yeah, yeah, in terms of like the you know what this business will be.
SPEAKER_02:Super interesting question. Uh, for the first part, the way we started was by building the execution layer. And we see the we see the world in in three layers. We see the execution layer, we see the data layer, and we see the intelligence layer. Kind of that uh dashboard that you talked about, that data piece that you talked about. So the execution layer is basically agents or workers getting things done. It's that track and trace agent, it's that carrier shells, inbound or outbound, either via email or phone, it's that POD collection use case. That's execution. That's where we started. And we built, I would argue, and we don't do it uh we don't do it enough service or uh we don't do enough in putting this out there, that we have probably one of the best orchestration platforms from a workflow builder perspective to build agents. I mean we had to build our own orchestration platform to build agents. Like have have you played with any uh like a Zapier looking tool?
SPEAKER_00:So now explain this to me remedially.
SPEAKER_02:Imagine imagine like basically if these, then that, then send an email, then make an age. So what we've built to scratch our own it's was the ability for our forward-deployed engineers to basically build agents really, really quickly for our customers. So we built our own platform to build agents, and any one of our customers will probably be able to attest to that, that we have a super powerful tool to build agents. I will not maybe name exactly a customer, but it's um it's I'm gonna say one of the top two or three fleets in the US. They had these couple people, like almost like PMs, like data per data people, but like they knew about the business as well, obviously. Just building agents on our platform. So that speaks to the fact that we're not just building on top of some other agent builder provider. We actually are the agent builder provider for these enterprises, and we always knew we had to be that, because uh a CH, uh, an RXO, uh World Word Express, uh um JB Hunt would probably not want to have anything that is not a developer tool of sorts, if that makes sense. They would not want to have a CAN solution. They would wanna they would not want to see a black box. They would want to see uh a developer framework, an orchestration platform for them to collaborate with their different agents because they will maybe build agents elsewhere. They will maybe build systems elsewhere. And they have systems, their own TMS, uh the the whatever sales first instance they have. They have a plethora of systems that we had to connect to. So a Blackbooks would not probably make it a service. That's why we had to build a developer infrastructure, a developer tool, or if you want to phrase it in a different way, um an AI operating system for these companies to build on top of. Because we're remember, we're we're targeting the enterprises. We we today are not serving uh a pre-canned agent for track and trays necessarily. We have that, and we can offer that to customers. We have implemented so many carrier sales and track and trays and POD agents, so we we have those pre-build agents that we that we have templatized over the over the months, uh years now. But we're more than that. So this covers the first the first layer, the execution layer.
SPEAKER_00:Before you go to the next layer, what might be different than let's say my I have a brokerage, XRO brokerage, uh to make some letters around. And I just take your canned template, like your track and trace, your carrier sales, your POD collection, like your three functions and use those. What might be different from my utilization of those three versus versus uh JB Hunt wanting to use the developer tools? What would they build that would be different than the three functions that you the CAN templated ones?
SPEAKER_02:This is super interesting, and it actually connects to that data piece. Because every business will have their own systems of record, they'll have especially at the enterprise level, they'll have their own API connectivity, they'll have their own way of doing things, their own SOPs. This is where if you can connect this execution layer of agents doing work, they can speak, they can write, they can read emails, they can process documents, they can do all of the basic uh agentic stuff. If you can have them do work that then they contribute back to the data sources, that carrier sales agent is putting back all the options it's capturing back into the TMS track and trace agent is actually cross-selling in a track and trace column. Maybe it's proposing another load because it has access to the data layer. We're enriching that data layer in such a way that the action generates information. That information is creating an insight. That insight is actually generating a proposed next action. For example, say that you're calling your vendor to see if your trailer is ready. Uh you have your maintenance team just calling vendors all around. Is it ready? Is it ready? Well, the sooner you know your trailer is ready, the sooner you can put that back into your network. And that's capacity that you you have on the asset side, like that's capacity you have uh to keep your business running. But if you have people just uh execution executing that, it's gonna take a little bit longer. So that's a lot of the value of connecting the data layer, of knowing like this interconnected business, of knowing when a trailer has been repaired, you put it back into the network, and it's improving other parts of the house, maybe the brokerage side of that asset company. So by connecting the agents to the data piece, we're enriching it, and we're generating even more insights and more potential actions for those agents to do. Now, these two layers only cover so much. You still don't know what your agents are doing. You want to have an observability layer on top, like an like uh an intelligence layer, so that you could almost just talk to your data. This is what we call uh uh I mean like it's basically like Chat GPD for your business. You connect by connecting to all of the data sources and by connecting to the work the agents are doing, you can now talk to your data. You can ask, hey, what are what were my margins for these type of for this particular lane uh for carriers that um have more than 10 trucks? Like this particular query, our system, can reason about that query and get it for you versus these folks having to like click everywhere on the TMS, like filter by carrier size, like the lane, blah, blah, blah. It's proposing insights, it's surfacing the edge cases, it's surfacing the insights to the business leaders. We had a we had a one one of our freight broker customers, they wanted to build their own GPT almost. And this is really where the idea came from because they wanted to ask questions. And in one of these questions they asked, they uncovered 3 million of potential savings uh based on some stuff that I kind of talk about, but like they uncovered three million of potential savings just by asking a question to the system that has gathered data from their human teams, but also from the agents putting data back into those data sources. So this combination of the execution, the data layer, and the intelligence layer, or the operability layer, almost like the uh the one glass pane, was really, really powerful, especially at that enterprise level, to to go and be more helpful versus just like a point solution of carrier sales. So that's been that's been really the unlock for us. And I think it connects to the second question: how big can these be, or where are we? Man, this I mean we we're we're really we've grown a lot since we did our series uh B. Um I can share numbers, but um I mean I've shared in all the podcasts, we're over um we're in the eight-figure realm uh in revenue, which is which is fantastic. I I could imagine in less than two years just like uh generating the revenue that they were generating and working with customers like I mean, DHL shared a press release recently uh about their the partnership with S. We're working with eight of the top ten freight brokers today, uh two of the largest, three ocean carriers, um few airlines now on the air cargo piece, uh many of the uh top uh fleets in the country. The sheer amount of work that we are doing today is nothing compared to what's what's coming, you know, to your point. I think we're minute one.
SPEAKER_00:Minute one. I love it. I that makes sense. I was hoping for an early, early, early time. Um and in when you say that, do you mostly mean in terms of I guess answer this two ways. One is is it is it more minute one in the sense of the products that you can build or will build, or is it more minute one in terms of the application of your or or implementation of your products within the, you know, you said eight of ten brokers. You know, is it is it a lot still of, okay, we're trying, let's start with the track and trace, let's do that. Or is it, hey, you know, we've got these three layers that work across multiple functions in the business, and a lot of customers have fully deployed all of that and it's functioning. Um like help me understand that a little bit better.
SPEAKER_02:I think it's mostly on the ladder. It's mostly on the deployment of the products we've already built. We we struggle so much about whether we open up, for example, our our plot our agent builder or not to the world. Because we we don't want to expose our IP, but we know that what we have is best in class. And when we show it to um billion-dollar company eggs that have looked at Palantir, they're like, okay, well, this is this is on par or better, depending on what what type of the equation you're talking about. If you're talking about more of the data piece versus the execution layer. Actually, many times now we're finding ourselves putting the execution layer that we've built on top of uh Palantir's uh foundry uh for very large manufacturers and enterprises we're working with now. If you see it from that perspective, we're definitely more on the ladder. Basically, we it's now more of a go-to-market approach. It's more of a embedding ourselves in the customers and helping them realize the value that they're either paying for or have not even uncovered because they've not even gotten creative enough to work with our teams, uh, with our deployment strategies and with our forward deployed engineers to think about new use cases and new applications. But then it's about connecting them all because you might be doing something again in maintenance that connects to the brokerage side. And then like a lot of lights start uh you know, like blinking, and like, oh boom, this is this is uh a lot of good ideas, and if you connect them all, it's really the interconnected business. So that's what we are really striving for to interconnect uh these businesses.
SPEAKER_00:I'm curious what's the easiest function or element of the business to build, and what's been the most challenging? Like with the most, and by challenging, I mean like the most unique differentiated piece versus the piece that you'll have 50 competitors that can build or have built the same type of thing.
SPEAKER_02:I think our biggest struggle so far has been putting it out there that we are not the tenth or nth. I mean, actually, we're probably one of the first ones really in the space, specifically in freight freight brokerage, but putting it out there that we are more than just another canned agent. I was talking with someone from uh from Gardner, uh the the research uh company. And they're like, okay, so like so you you sell like these pre-packaged agents. Like, no. We're we we are the we can be the functioning workforce, the the AI workforce for these enterprises. I'm not gonna be selling to a 20-person broker. I mean, that's I'll put it out there. No, like we're not there yet. And I don't think we'll ever wanna be, because it takes a lot of takes it takes uh almost like a B2C approach. I mean, like a like it's a B2B approach, but it's very, it's very harsh to sell to a 10, 20 person broker that I'd actually go out of business tomorrow. I mean, I'd love to, but it today our focus is on the top enterprises in brokerage, top fleets, top freight forwarders, ocean carriers, airlines. So we're looking at the enterprise layer of supply chain, also at the uh shipper side, if you will, like tailors, manufacturers, distributors, and how can we make their operations more efficient? How can we build an AI workforce for these enterprises that interconnects the way they do work? Because we want to reimagine how they do work today. So that's been the biggest challenge, no, like getting it out there that we're not just like your nth carrier sales agent. There will be folks that might even build a bit of a load board looking um platform where they maybe like do some offering for for carriers and tra and and brokers and they connect the capacity and they do that load board game. We decided very a long time ago we're built for the enterprise. We're a we're your workforce, we're not sharing your insights with the nth broker because that would that would be messed up. All of the insights I get or you get in your workforce, they should remain in your workforce. And the compound intelligence that you get by having agents working on your data every day, it's exponential. No, the the sooner you uh build an agent on Happy Robot, it's learning every day. It's learning about what it should do, what it shouldn't do. It's getting feedback from the users. It's improving the network. And this is really interesting uh across the agentic space. If you actually improve an agent or a piece of an agent, it actually scales across the board. You don't have to retrain your workforce, your uh your human teams. Now your human team, your human teams are still gonna be uh helping those agents get better. So it's that combination that is really specific to every company. The way broker X works is different from broker Y, and that's their unique ability to grow their business. We're just empowering the way they do day to work. That's been the hardest part. Getting it out there versus, oh, here's just like another carrier sales or truck and trace uh three canned bot.
SPEAKER_00:Holy That is what everyone says when they see Gen Log's truck intelligence platform for the first time. Founded by XCAA operatives and fueled by 15 million daily images across a nationwide camera network. Genlog gives you the power of total market capacity while also defending you against fraudulent carriers. Holy sh is what Gen Log's customers say again when they see the ROI from covering loads faster with fatter margins. Holy shippers. That's right. Genlogs unveils the locations and lanes for all the shippers in America. In the era of artificial intelligence, nothing beats actual intelligence from verified buy video data. See what Genlogs can do for you. Check out a demo at genlogs.io. Again, that is G-E-N-L-O-G-S.io. Tell them Andrew sent you and they'll include their carrier compliance suite for free. And if you haven't already, I interviewed their founder, Ryan Joyce, last year, and it's one of my personal favorite episodes that we've done. Check it out. Now, let's get back to the show. Yeah, because I think the at least my initial understanding of Happy Robot is it's a voice bot. Like that's certainly what I was early on under the impression of it was. And it it sounds like you're telling me it's a lot more than that today. Um, and and I'm really interested in the idea of kind of reimagining your workforce at the enterprise level. So, like, let's just make up an example. Let's say I'm running a brokerage that's got 500 carrier reps and 500 sales, customer sales reps, and 300 customer operations reps doing scheduling and you know, all the other fun stuff that operations folks do. And I come to you and I say, let's go all in together, reimagine my workforce. And I deploy all of your tools, your whole thing. I say, you know, here's the check, you know, reimagine it. What what is that, what changes? Like what is what does the end goal look like? And you can generalize it, obviously, because this is a made-up example, but help me understand like what about each person's role changes? Am I am I repurposing people? Am I going from 500 care reps to 250 and moving these other people to do other things? Like, what does that look like? And and if there's a if there's a change, if you think you know, today versus a future state, I'm curious what those two might look like differently.
SPEAKER_02:Many of our customers paint this super clearly to us. We want to grow. We don't want to we're not gonna fire anyone because we love our people, but we want to grow 2x in the next two years, whatever, you know, whatever the number is. How do you do that without having to scale with with people? And not because it's bad necessarily, but because if you if you don't scale now with with agents, with AI agents, you will not grow 2x next two years. But someone that is leveraging those agents will. So folks are thinking about it the right way, they see that that unfair advantage that uh whoever leverages that AI org first will have versus them. And this is a bit of a of a dilemma that I have. Like if smaller brokers don't get access to this sort of technology, which I I think they will, because there will be players that maybe cater to them and they will be maybe hyperscalers that go from 10 people to uh being uh the next$10 billion broker or five. Um it's a bit of a dilemma that I have now, like if we're only serving the enterprise today, we might be missing out on some uh unicorn. But the way these folks are looking at their workforce is we don't want to fire it, fire folks. Obviously, obviously, if there's like low performers, they're just gonna naturally just like turn themselves. I mean from from a class of a hundred reps, maybe five percent uh are gonna are gonna stay there in the next three years. And uh talking with some folks uh recently were like, man, like uh every every new class is like harder to train. Like they're just like more scared to do stuff, to send that email that to a customer to make that phone call to the carrier, they get shouted at, they're scared, they quit. So, how do you grow uh a business that is inherently messy and complex? And and and my goodness, I kudos like hats off to all of those operators that are like running these businesses every day. And I don't know how how they would um how would I manage that. Like it's amazing. They're thinking about how do we bring this technology to help us accelerate. That's how they should be thinking about it, this transformation, right? Maybe we go from 500 reps to in the care sales rep side to um 400, 300, whatever it is, uh, while people just naturally turn. But we're gonna grow the business 3x, even if we have less people doing the work, because the the the ones that remain will be those uh guardians of exception, which I like calling, managing a bit of a workforce of their own executive assistants, almost like their own reps, their own um assistant reps, if you will. So that that's how I think people should be thinking about it.
SPEAKER_00:And and what does that day-to-day change look like? So if I, you know, before I hire you, my carrier, my 500 reps, each one of them has 25 carriers that are their own carriers. And, you know, I'm Joe Smith. I work in the Chicago office, and I'm responsible for inbound freight to the Midwest. Any loads delivering into Illinois, Indiana, Ohio, Michigan, and Wisconsin. I'm on a team of 20 reps, and we cover all every load coming into those states. I have 25 carriers based in those states. I'm each of them has 20 trucks. I call them every day, or they email me where their trucks are every day. And I'm booking their loads in advance as much as possible. And I book about 20 loads a day. I'm a good rep. I make pretty good money. And there's 499 other guys like me, Joe Smith. And my day is mostly dealing with those carriers. And then I also have to call new carriers every day because we have a bunch of spot loads and different loads that aren't on routing guides, they come in. Uh, my system does some automation, so you know, I've got some primary lanes with some of these carriers that it, you know, when when craft send us the load, I it the system sends it right to the carrier, and I just talk to them about issues. I deploy Happy Robot. How is my life? How's my day changing? What roles and responsibilities are you taking over for me and what am I doing now?
SPEAKER_02:The biggest one is you're managing by exception. You're getting pings from your, let's call it a Tracy agent, telling you, hey, I've already made sure that that 15 loads that you're overseeing today are all good, no worries, like everything's looking uh it's looking good, they're gonna deliver on time. There's this one load that might actually be late. I already called the driver and I let them know that if they have any any trouble, uh they should call us back. So I'll be on the lookout for that. I'll keep you posted. That's the message that that rep gets in the morning. Like, okay, things are looking good. Maybe uh in the in in across the day or along the day, there's an issue. Uh driver breaks breaks down, uh they cannot like uh fulfill that that load. We have to uh they're not gonna make for make it for pickup. We're gonna have to find someone else. The system will tell Joe Smith, hey, I'm Tracy again, Joe. This this driver, he broke broke down. Uh, we have to find someone else for to make the pickup. Uh I'm gonna actually already reschedule with a customer for an hour later so that we have a little bit more map more bandwidth that's possible in this facility. They can they they already confirmed. Uh and now I'm actually uh reaching out to these other 10 carriers that we have uh that have done these loads in the past. So I'm already reaching out to them and see if they have any capacity to make it happen. Obviously, uh I'm asking you for confirmation that we can go a little bit over max pay here. Can you do you agree? And maybe Joe says, hmm, no, actually, I know who to call. Uh go get these uh ABC tracking because they're definitely gonna do it, do this for me. I'll actually text them myself. Then maybe Tracy doesn't have to do anything. Tracy, the agent. So Joe Smith controls that executive assistant of his, that agent of his, they can do 10x more work for him. I mean it's uh it's a question for the broker to see how they commission their brokers now. Um it's a question for for the for the broker to decide how many um how many people they they they they put on on more of the mundane tasks like track and trace. I mean, I don't know who likes doing track and trace, but I mean I I wouldn't. Uh I've done some some some stuff there. Uh it's painful. Who likes calling for pods? My goodness. Uh who likes entering load data. Um so I think the the team that remains in the these companies will be super strategic, will be very uh customer focused or carer focused at the highest level, not at the execution level, not at the getting things done, but rather at the hey, Mr. ABC tracking, you guys have like done this lane for us now like multiple weeks, multiple times these this month. Why don't we do like some more of a of a formal like contract here? We we just have a bit of a longer term commitment here. We have these we have this customer this lane uh happening like multiple times a month. Like let's do something more formal. So at any final, we we actually had these uh multiple uh this identification multiple times of lanes or carriers that could actually be uh contracted carriers, if you will, uh based on the spot loads that we were covering for them via email and phone. I think this is the the how these reps will actually operate by exception and by being a lot more strategic. I don't know if that if that answered the answers the question.
SPEAKER_00:No, it does. It definitely does. It just gets me thinking about a lot of things. Um because like one of the one of the in just in this example, and and this is a minor thing, but you mentioned like, okay, so Tracy says, you know, I called the facility and and got bought us an hour at pickup. So like there's nuance to that where certain facilities, if you were to do that, it it is the right, it's the smartest thing to to you know, logically get yourself the most time to make your pickup. But in some cases, a customer is gonna ding you for missing the appointment and showing up later. And so there is a bit of a balance, and it's like, okay, it's it's 10 a.m. when we got this notification. Our appointment's at noon. We know the facility is open until two. But this specific customer is really strict about the appointments in terms of the scorecard, and our most recent scorecards are just a few percentage points lower than we want them to be. So we really want to hit that noon. And I'm just curious like how that process works, and you know, just how much does how much can I teach Tracy to understand, like, hey, it's probably worth it for us to pay the extra$200 to get a carrier that can actually make the noon versus defaulting to the let's buy the most time possible because that's logically what makes the most sense. Right? You see how there's nuance there.
SPEAKER_02:100%.
SPEAKER_00:Yeah.
SPEAKER_02:100%. The short answer is this is for the comp for the customer to decide. This is their own ASOP. This is the this is in the in the rep's brains, actually. It's it's uh tribal knowledge that that one rep might have. So we don't have we cannot discard that, we cannot discount that piece. So it's gonna be a mix of how much do we know about that facility? Do we know that it's uh like uh strict appointments? Do we know that it's uh first come, first served, uh uh all day long? Do we know that um Pede at that facility can actually typically just buy us an hour or two if we give him some pancakes next time we go there? It's it's that tribal knowledge plus the facility, uh whatever facility know-how you have about that one particular example. But definitely Joe Smith should have a lot to say on that operation because Tracy is working for for Joe Smith. The the way we put it on the Happerwood platform is you see like a bit of an AI org. So you have like um, we don't give it a name, but it's like the AI uh chief of staff, uh, if you will, like managing everything, and then we have like um Tracy, AI head of track and trace operations, have uh uh Casey, AI head of uh carrier sales, have um John, leading sales, customer sales. So you have like these AI org, and then every one of those agents or heads off that I just described, they have like workflows. For for track and trades, you obviously need to do a lot of different different um uh type of uh check calls. You know, like you might have to do like a like a pre-pick, maybe um in transit a couple of them if there's multiple stops, maybe like a pre-delivery uh for the POD, you connected with the with the right after you've delivered, you immediately call, uh, or maybe you wait a day to call for the POD. Those things are in the tribal, our tribal knowledge are in Joe Smith's head. So you have to incorporate that human in the loop. That's where like the guardian of the exception comes in. So I fully agree that there's a lot of nuance, and that's where humans can actually communicate with their with their agents.
SPEAKER_00:Is this where the kind of term of the year in uh tech companies for deployed engineer? Is that where this creates value like in this tribal knowledge understanding? Like you know, it seems like that's all I'm I don't think a year ago we'd ever heard of the term forward deployed engineer, and now and now if you don't say you have one, you're way behind the times. Um am I right? And that's like kind of what's going on with a lot of these companies. Yeah, and and I'm curious, but is is this the application of that where it's you're understanding the um the tribal knowledge of a broker and how to apply your solution in a way that like consumes that and and applies it effectively?
SPEAKER_02:To some degree, to some degree. I would say that part of the beauty of of language models is that it can actually understand the nuance of Joe Smith texting back on Teams. No, don't do that. I know that we can overpay for this one. I have like I have uh I can overwrite this Max Pay here and pay 200 bucks more. So do the opposite, do something else. I think the FD is more so for rethinking maybe the the way we things are done. For example, uh we had a customer where we're doing a lot of these track and trace calls, and one one of our uh one of our of our FDEs working with with their uh reps, one day they're like, hey, I mean we should definitely do like mimic what the reps are doing today, or some of the good reps are doing today, which is see if you can get a backhaul for them. Or see if you can actually get uh another load, the next load for them, and like just keep them in the network. So by having someone that is just listening closely to what's going on in the business and going on sites or going on site uh multiple times uh a month, um you uncover a lot of this tribal knowledge and you can put it back into the agent, but the agent itself will actually learn about your own specific way to do work. Joe Smith saying this facility should not mess it up with these guys, the the shipper will get angry with us and they'll like just find another broker. This can be learned by the system. And next time that Joe Smith is talking to Tracy, Tracy will remember. It's like again, your your EA, a good EA, should remember these new ones. We're trying to implement the same for these companies. We're trying to reimagine the way they they they do the more operational work, and many times some of the sales work, which is super interesting. We have done a few case studies and use cases with um some of the uh of the LTL brokers where we just do campaigns for dormant accounts where we're emailing and calling customers, like smaller, smaller accounts, maybe. Well, some of the accounts they cannot reach uh uh efficiently or in a way that would have ROI. But when we get a lead and we pass it to a human, hey, let me connect you with my pricing expert. You yeah, you guys shipped a pallet of potatoes a month ago. You guys want to ship again? Uh oh, sure, okay. Perfect. Let me connect you with my pricing specialist. Uh wait a minute. Boom, like you have a sale there. So those those type of uh use cases and sales are also super interesting. And it connects to the other operational part of the business, which is again why we realized we cannot just be building siloed agents. It has to be part of a of a broader network of agents, hence the the AI workforce.
SPEAKER_00:Yeah, that's that's that's very interesting. Where do I want to go from here?
SPEAKER_02:Um It's a lot to us. I mean, it's we've been thinking uh uh a lot about these things.
SPEAKER_00:Yeah, I I bet. Um what is there anything that you've kind of refused to automate or that you feel like you don't want the AI to touch, like the agents to touch?
SPEAKER_02:That's an interesting question.
SPEAKER_00:Um And refuse is maybe not the right word, but anything that you've looked at and been like, I don't think we should go down that path. At least not yet, or maybe something like that.
SPEAKER_02:I mean, definitely all. All of the cold outreach, like pure cold outreach, especially via yeah, via phone. Um we just know that it's not gonna fly uh in terms of regulation.
SPEAKER_00:Uh email, it's harder to cold outreach to who? To carriers?
SPEAKER_02:To customers.
SPEAKER_00:To customers.
SPEAKER_02:Yeah. Like that's one that uh I mean we all both our customers and and ourselves, we understand that as much as it'd be interesting to like do that pure cold outreach, uh, if someone has not signed up for a call, especially in certain states, um, it's uh it's trickier to do that uh cold outbound with with AI agents, and we don't want to go down that path.
SPEAKER_00:Why why is it why is that why is that different for a trucking company versus an olive oil company? They're both businesses technically, and both it's technically you're cold outreaching to either of them. I'm curious why that's a difference.
SPEAKER_02:Especially if you've already worked with someone, for example, with with a with a carrier, you've already worked with them in the past, also with a customer. I mean, what I'm saying is for both carrier and customer, if all if you've already worked with them in the past, you have more of a say or you have an excuse to call them.
SPEAKER_00:Yeah, that makes sense.
SPEAKER_02:Hey, Mr. Carrier, you guys shipped uh you guys uh moved this load for us, uh did this lane for us a few uh a few weeks ago. You're gonna do it again? No. Oh, okay. What do you typically run? Now you get an ins an insight from the carrier. Same with the customer. Hey, you guys shipped a pallet of whatever with us last month. You're gonna you want to do it again? That's the excuse that we have. So are like doing the cold outbound piece.
SPEAKER_00:Um But are you guys doing cold outbound for trucking companies?
SPEAKER_02:Mostly if they've worked with the customer.
SPEAKER_00:Well, that so I so I'm saying if if they haven't. If if if I'm a broker and I'm like, I want you to be my carrier sales tool.
SPEAKER_01:Yes, yeah, we do that.
SPEAKER_00:Okay, so you can so like if I said I want you to call any carrier in Illinois for carrier for that's on carrier 411 that has ever been to Ohio with inspections, because maybe they run Illinois to Ohio, you can call some.
SPEAKER_02:Yeah. Customers feel like our customers feel a lot more entitled to make that call because, in a sense, you're giving them potential business. Like if you actually have a load, if it's a can get load, it's it gets a little bit more tricky because then you you get the the carrier angry and it's like you didn't even have a load, you were just like fishing. So it's a little more messy. Um but if it's if if you actually have a load already and you're just like really needing a carrier to do that, like they they feel more legitimate at let how do you put that? Like it's a bit more of a legitimate call versus if it's just like a pure outbound call. Like this is getting into TCPA regulations for for cold outbound uh to sale services. Uh that's for like TCPA regulation gets a little bit more uh strict on that. And this is where we recommend customers to not do a lot of. Um but for for the for the carrier side, you're writing that um we do do that because you you have an you have an offering uh for for work. So it's a little bit it's very interesting, it's a little bit different than selling services, basically. Yeah, no one wants to be sold, people do want to do work.
SPEAKER_00:I get that. It's uh you know, it's it's interesting because I I I'm a sales guy at heart. I love selling more than you know. I've spent my whole career in freight brokerage, and I've run a brokerage. There's no function I enjoy more than reaching out to shippers for new opportunities. And part of it is like the competitive nature of it and the fact that there are you know 30, 40, however many thousands of freight brokers out there doing the same thing. And they're largely undifferentiated, at least in the minds of many shippers, where that cold email, that cold call is generally very unwanted. And something about the chase for me is I just love it. And specifically the creativity, uh I I lead, I lean into creative sales and trying to like come up with you know, leveraging as much research as possible into the individual, the company, um, the market, whatever I can find out about this potential lead to come up with something that I think will be interesting for them. Maybe it's funny for them, maybe it's educational for them, informative, whatever. I enjoy that. Um, and I I it has been successful for for me. And I'm just curious, like I think it would be interesting to leverage AI to help do some of that um preemptive work. Not necessarily doing the outreach itself, but saying, okay, you know, Joe Thompson is the VP of transportation at Kroger, and I want to haul for him, and I want to know everything there is to know about him and his business and Kroger and the market that applies to Kroger. Give me all you got so I can come up with an email or a call that makes sense. Like, are you guys playing in that arena at all?
SPEAKER_02:We started we started looking into some of that uh enriching of the of the data. Uh it's uh I mean I'm gonna say there's a lot of um sales-specific tools for for that alone, like especially on email. Um and they they do a good work. Uh we use ourselves some of that for our own outreach, but uh we have had customers with whom we're already now piloting some access to to LinkedIn uh for the agent, so then the agent can research a little bit on LinkedIn. And the reality is that web search or browser search for agents is getting so accessible that now you can do those things, which is really interesting. But no, I agree. I think the uh honestly, this is where I would still uh as uh if I were like doing a broker, I would probably, as you feel very and invigorated and like uh very excited to like be doing those sales. Like it's the hunt. I think that's where it'll be hard for for humans to to let go of because it's it's fun, no? I mean, similar with killer shells, uh, but um but especially with the customer, like it's you you hit the gong, right? Like, I mean you you uh you feel that uh that energy. So I think that'll probably be the last piece where where we can help. Um I would frame it more from an account management perspective, especially smaller accounts, where the agent can actually be that warmer, like how do you put it? The agent can be warming up the the accounting a little bit again after it's been dormant for a little bit. Like we've we've seen a lot of success on that uh dormant account type of use cases on on the sales fees. Maybe on the coal outreach, I agree. Like it's it's really fun to like research about that person and be like, oh, do I send them like uh like some uh chocolates uh to their office and they then give them a call right after they get the delivery?
SPEAKER_00:Yeah, stuff like that I think is interesting. Um so given time, I want to move to kind of some of the market in general, the the competitive market and the category itself. Like this is where all of the VC money is going right now into AI businesses and you know, trying to find ways to be more efficient and do more with less. Um, our industry itself is is one of the most busy and noisy because our industry has always looked been looked at as like the most antiquated, old school, you know, pen and paper kind of business. I'm curious from your perspective, because there are a lot of companies preaching a lot, like what what are you hearing? What is the biggest BS claim that you're hearing from other AI vendors like that you feel like is misleading or not representative of of what companies are actually doing?
SPEAKER_02:Yeah, that's a good question. I mean, we I have to be honest, and we we just don't instill like any fear of competitors in our company. It's more of a as we have a customer, let's win it over, let's crush it with the customer, let's let's deliver, and let's focus on that. They might like the customer might might may bring up, hey, we have like we're looking at uh a couple of folks, three folks, whatever. Uh let's see what you get. And I mean so far we've been very lucky. Um, and I think we we've we've nailed um I'm gonna say like 99% of the engagements uh that we've had. Um you cannot like do everything right, but like especially as you grow, there's things that fall through the cracks sometimes. And not responding maybe to a to a customer email like gets them angry. What can you do about that? But in general, with the with the enterprises that we have, we've been like really, really wet bluff, and that's gotten us that um that access to their to their different use cases and and and ideas and and operations. Um so I'm gonna say that from our perspective, like the bullshit that we that that the external world might be thinking that AI is doing. I mean, I've just seen folks like let go of a team that was doing uh super, super manual work and put them doing sales. Like uh they went from 82 people to four people, okay? From 82 people to four people. It was a very mundane, repetitive task they were doing. Everyone just like was churning through it. Uh they they were using uh uh a BPO in this case. But um but that that type of like tangible ROI is massive. And and when again, you can actually put the the good performers because who wants to have like low performers in their companies? I mean, the good performers, you're gonna like promote to like maybe customer sales, and they might be like your VP next year. Uh so that's the type of company that you want to run. I remember one of our customers saying, hey, whoever doesn't engage with this bullshit AI at the time is not gonna stay here for long. You have to work with it. Because again, remember, this is what he he was saying to his team. If you don't work with AI, someone will, and they will vote over us. So that's been the the biggest um mind frame or or or uh kind of set of uh set of ideas that we've had. Like always be very practical in your approach to to what we automate first because you want to see ROI. So even if I've been talking a lot about uh a lot about the high-level like uh uh three layers and like coding and work, ultimately where we start many times is just executing for a certain use case. So honestly, no, no, not a lot of bullshit that we see around here, man. I mean, it's it's working, it's crazy. We're busy. Um yeah, if you have good engineers, send them over because we mean we need more to build more product and and and go to market people as well.
SPEAKER_00:So I'm I'm curious, like five years from now, what do you think this business looks like? What is what is the impact look like and what does your team look like? What is how has the industry changed as a result of your business? Like, give me the what your vision looks like down the road.
SPEAKER_02:Five years from now, we are working with the largest enterprises in the world where we've deployed an AI workforce that is doing that 90% of the work, having very smart humans doing the strategic and more important part of the work, and the TAM for that, if you will, the the the market for that, and we're talking about billions of spend in just people like being the interface for the flow of data, like sending emails, making phone calls, entering data from a PDF to a database. That's not gonna be the case in five years or even two years from now. But whoever is serving as an interface to the flow of information is not gonna be doing that job for long. Now, whoever is adding value to the company, strategically getting creative, as you said, thinking creatively around how to win more business, be more efficient, that's who you want to keep in your company. I mean, I tell my my team of engineers uh themselves, like, guys, code is getting really easy to write. You better make use of those tools. You're gonna left behind even faster than the the people for helping uh on our customers, meaning you better learn how to 10x yourself. So what applies to my engineers in Happy Robot applies to uh the reps doing all of the um all of the keeping the the world moving, which is super important, but we're gonna have to uh 10x the efficiency. So that's how I see the world. Both the engineering world, but also like the operational world, is gonna 10x themselves 400x. I mean things are moving so fast.
SPEAKER_00:My concern, and this has nothing to do with this is more macro. When I think about my last when I think about a brokerage, most of the people are not the 10xers, most of the people are not the creative thinkers that are like all day coming up with the strategic solutions. Like most of the people are the ones doing the kind of work that AI should be able to replace in five years. And I don't know that it's just so feasible to turn them all into 10xers, to turn them all into the creative thinkers. And I worry a little bit about where the world will be in five years in terms of opportunities when those just aren't the native skill sets of a lot of people, what the functions will require. So I I don't know if this is even a question or if maybe it is a question of like, do you agree in like what the possible risks are to the world or to the global economy? If like I don't know. I mean, I you hear you hear some people talk about like you know, not even having to work and and universal basic income, and that's a whole different conversation, I think. Um, as we're running out of time. But do you have any thoughts as I'm kind of postulating here?
SPEAKER_02:Uh yeah, I mean, I think first of all, we better learn how to teach our kids to live in this world. We better upgrade our school systems. Right now we're just creating sausage producers. You know what I mean?
SPEAKER_00:Yeah.
SPEAKER_02:It's very like you do this, you study this, you don't do other things. So we better learn how to today like change the way we we we teach our kids. I don't have kids, I don't know how to teach them, but my wife is a teacher. Um and honestly, I still see the same uh uh process, the same manufacturing process of perfectly educated kids that actually don't think out of the box. So I think that's a problem. I don't know how to fix it. Um I think AI might actually help because what I was discussing with my wife is I wish I would have had a more uh personalized education, meaning I spent a lot of time, and my my my wife um verifies this, just waiting for the teacher to calm the class down. It's like Peter, Don Chout, uh Matthew, uh sit down. And you're just like waiting there, like eight hours of your day, just waiting for people to shut down and like try to learn, versus if you could just like learn for two hours what you want to learn about that day, and you get creative, you're like curious about that specific topic, about the history of I was talking to my engineers about the history of their Reconquista in Spain yesterday. Like that's what was gonna get kids like more creative. And then they'll be able to have more time to maybe build stuff on their own and and learn how to go and find new things to do on their own, versus us trying to like put them in buckets. So that that's uh a little bit of how I think about the education system, and it should be a lot more personalized, and I think AI will help do that. Now, how do we fix the the potential um um problem that you brought up? I think we as a society we generally have overcome these problems uh very well. The scale is different. I mean, when my grandfather bought a tractor, uh I mean he didn't need enough, uh he didn't need that many people like going to the field. But they found other things to do. So I don't think we're gonna have a problem. It's gonna be at a different scale, that's true. So it's gonna be we're gonna we're gonna have to adapt faster. But I think something we do well as uh as humans, uh we adapt fast. So even if someone today is like, you think they're actually not like strategic thinkers or like they're like too narrow, give them a carrot. I mean, give them a carrot and and and they say they probably are gonna chase that carrot and they're they'll learn, they're they'll get creative. I think uh necessity uh creates creativity, if you will. I don't know how to put it well, but uh I mean we we for example in our case we we have not raised, I mean we have raised big chunks of money, but we have competitors that have raised uh I don't know, you look at Sierra, for example, uh Sierra AI, this this uh Brad Taylor company, uh it's like valid at a$10 billion. Uh they raised like hundreds of million. I I think, I mean, we're working with some air cargo and airlines and and folks that are telling us like, wow, this just works a lot better. So I think that out of necessity, because we didn't have enough engineers, we've built better products than if someone just has like infinite resources, similar with the government. Like government has infinite resources and it doesn't work. Another another great comparison.
SPEAKER_00:Always compare your competitors to the government and you'll sound like you're making a home run point.
SPEAKER_02:I front up Sarah because it's also like out of the spectrum of of uh freight, if you will. Um, but I mean I don't have anything against them.
SPEAKER_00:But um No, no, I appreciate what you're saying. I think you're I think you're making a very cogent point, and and I agree with it. Is that like just because I can't see the solution today doesn't mean that when push comes to shove and we find ourselves in need of creating a solution that we won't find one.
SPEAKER_02:I think so. I'm very positive about our societies. Uh I think we can always overcome things, even if if if we mess up uh in other in other points, but I I'm positive about finding solutions.
SPEAKER_00:Yeah. I'm with you. Well, listen, man, I've I've had you for over 90 minutes, and I promised I wouldn't go over that. So um this has been a lot of fun. And I feel like I didn't even get to a lot of things that I could ask you about, but uh maybe we'll do this again sometime.
SPEAKER_02:That's true. Really appreciate it. Thank you so much for having me.
SPEAKER_00:To our listeners, I hope you enjoyed the uh enjoyed the ride. Welcome back. We are back officially with our first episode back in a few months, and what a great guest we had. Thank you so much, Pablo. Um Terminal. We'll see you next time.
