How Founders Are Building the Next Great Startups | Paid.ai, iTruckr & Tenax AI | E2175

Today's show: In this TWiST founder triple-shot, Alex digs into the real-world rollout of AI agents: Paid.ai's Manny Medina explains agent economics and value-based pricing, iTruckr's Camilo Ramirez shows agents booking loads and coordinating drivers, and Tenax's Elise Myrans demos computer vision + drones that score a single home's wildfire/flood risk for smarter underwriting—plus live office-hours on winning enterprise pilots without getting stuck in PoC purgatory. Timestamps: (00:00) Brainstorming hacks for sales cycles in regulated industries — castles, moats & alligators! (03:50) Meet Paid.ai: tracking costs & monetization for AI agents (04:35) Paid.ai's Manny Medina on the "year of agents" & early enterprise traction (09:04) Netsuite - Download the ebook CFO's Guide to AI and Machine Learning for free at https://www.netsuite.com/twist (11:06) The tough economics of AI agents vs SaaS — margins squeezed by tokens (18:20) How Paid.ai gets granular: tracking signals & agent activity with OpenTelemetry (21:20) Coda - Empower your startup with Coda's Team plan for free—get 6 months at https://www. Coda.io/twist (29:16) Enter iTruckr: Camilo Ramirez brings AI dispatch to the freight industry (31:43) . TECH: Say it without saying it. Head to get.tech/twist or your favorite registrar to get a clean, sharp .tech domain today. (39:02) Scaling from small fleets to mid-sized trucking companies — lessons from AI Trucker (55:59) Tenax ai helps homeowners & insurers manage wildfire, flood & climate risk Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp Follow Lon: X: https://x.com/lons Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Thank you to our partners: (09:04) Netsuite - Download the ebook CFO's Guide to AI and Machine Learning for free at https://www.netsuite.com/twist (21:20) Coda - Empower your startup with Coda's Team plan for free—get 6 months at https://www. Coda.io/twist (31:43) . TECH: Say it without saying it. Head to get.tech/twist or your favorite registrar to get a clean, sharp .tech domain today. Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland Check out Jason's suite of newsletters: https://substack.com/@calacanis Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com Subscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Jason Calacanis?

  So we need some Vanguard here. We need some early adopters who want to get early access. So great. Let's get some of those going.

• 0:07Speaker 01

  And then the question I would put, this is something I'm loving brainstorming around right now. Are different ways to hack sales cycles in really regulated industries that are slow moving? Right? So in that B to B space, I love talking about this and I'd love, I don't think you and I have talked about it. I would love to hear your thoughts on that.

• 0:27Jason Calacanis?

  You know, it's a tough one. You know, whenever you go into education, let's say, or you go into housing, as you are, healthcare, these are some of the giant castles that are hard to scale. We've got moats around them. They've got drawbridge, they've got alligators in there, got arrow slits. It's not fun.

• 0:48Speaker 02

  This week in startups is brought to you by .tech. Say it without saying it. Head to get dot tech slash twist or your favorite registrar to get a clean, sharp .tech domain today. Coda. Coda empowers your startup by bringing words, tables, and teams together. Strategize, plan, and track goals effectively with all your valuable data in one place. Go to coda.io slash twist to get started for free and get six free months of the team plan. And NetSuite. The business landscape is very chaotic right now. That's why you need NetSuite by Oracle. Download the CFO's Guide to AI and Machine Learning for free at netsuite.com/twist.

• 1:32Speaker 02

  Hey everybody. Welcome back to Twist. This is Alex and today's episode is all about founders. We are talking to three different startups that are each taking a very interesting tack on the world. We're going to dig into what they're building, why, and how it's going to move the needle. First up, we're talking to Paid AI, or just Paid if you want. They're a Twist 500 company working in the world of AI agents. But unlike your Sierra's or other companies that want to build an agent for you and deploy into your company, this is all about helping the companies doing the actual building. So what Paid does is help companies track how much money their AI agents cost by checking their number of prompts and which models they're using to get a good idea of what they're spending. And then also helps them with AI agent billing. This is the kind of picks and shovels work that often doesn't get quite as much press as

• 2:16Speaker 02

  the OpenAI is and Anthropic's of the world. But if we are going to bring AI agents into the enterprise, into the world of small business, well, paid could have an absolutely huge business. Think of it a bit like, I don't know, Twilio, but for AI agents to make a very loose comparison. An absolute treat of a chat. You're going to love it. Then we're talking to the founders from iTrucker. Now, the world of trucking, you may not know much about. You may not drive an 18 wheeler. If you do, shout out, but most people here, I don't think are doing that. So why do we care about trucking? Well, what iTrucker learned is that the world of truck dispatch, freight management, and all the relationships between individual truck drivers, truck owners, dispatchers, and loads is kind of run by phones. It's not very efficient. So what they've done is built an AI tool that helps all the communications be done

• 2:58Speaker 02

  simply, easily, and quickly from devices and services people already own and use. I love this company. I love seeing technology applied to kind of like flesh and blood industries. You're going to love it. Then to wrap up the day, 10x AI. Now, if you think about climate change from a risk perspective, what does that mean? Well, you might be worried about increased wildfire risk, increased flooding risk, extreme weather in general. And what 10x AI wants to do is help people both make their homes more resilient and also provide good information to insurance companies to make sure that they're doing intelligent underwriting. You don't want to underprice risk and then get your face ripped off. And also, if you own a house, well, you probably want to know what your risk is so you can go about mitigating it. 10x AI is super interesting. It's a company that I'm paying a lot of attention to.

• 3:43Speaker 02

  I think you're going to dig it. So with all that said, let's dive in and we're going to start with paid.ai. Let's go. AI agents. 2025 is supposed to be the year of agents, or at least the year that kicks off agents as a common tool for companies to help automate their work. While companies are working to integrate agents into their workflow to try and make more money themselves, what about the companies building AI agents? Are they making money? We know that major foundation model companies like OpenAI and Anthropic are seeing the revenues soar, but at the cost of huge burn. So the question really does matter. One startup has its eyes fixed on the question of AI. AI agent economics. That company, Paid AI, wants to better track AI agent costs and help with monetization

• 4:26Speaker 02

  so that the work of making autonomous AI tools can prove profitable for both the provider and the customer. To tell us more about Paid and the state of the agentic economy, please welcome to the show, it's Manny Medina, co-founder and CEO of Paid and former co-founder and CEO of Outreach. Manny, hey, how you doing?

• 4:42Speaker 03

  I'm awesome. Good to see you. Thanks for having me.

• 4:44Speaker 02

  You get 10 points for having your logo behind you in neon signage. That is fantastic. I have to ask, how, how long after the company was founded, did you guys get that made for your podcast studio?

• 4:57Speaker 03

  So the company was founded around January this year. We broke code in, you know, towards the end of January, February. And, you know, we've been rocking since. We have, you know, we started with pilot customers and that we now have close to 20 of them. And we just landed our first enterprise customer last week, so we're super excited about that. And the neon, the neon sign was a detail that the team brought together. It turns out they're very easy to make. I didn't know how easy work to make, but they're, they're fantastic.

• 5:30Speaker 02

  Turns out there's actually just a bunch of services that'll make them for you, but it does make you appear to be incredibly legit. I want to get into customer growth and the exact thing you're building in a second, but I want to just set some foundations here for folks. People have said, like I said in the intro, that it's the year of agents. What I'm curious from your end, Manny, is how many companies are really in the market today that are building AI agentic tools that they're taking to customers and therefore, you know, need what you guys have built. But how many companies have reached that level of maturity, if that makes sense?

• 6:02Speaker 03

  So the, the, the agent market is incredibly early and it's incredibly early in that anyone can build an agent, but very few can build an agent that is solving a problem for somebody that is willing to pay for it. That said, because agents are actually being sold, the majority of the agents that we're seeing are being sold into non-tech spaces. You're not going to hear about them. You're not, you're gonna hear about them when, you know, when, when your plumber tells you that it was the agent that they scheduled their appointment and it was the agent that told him that he needed a part. Or whenever your architect uses, you know, an agent to figure out the cost of the house you're about to build.

• 6:39Speaker 02

  Sure.

• 6:39Speaker 03

  Or, you know, the, you know, mortgages are gonna be performed completely by agents over the next, you know, in the next year or so. So it's a little bit like taking the red pill that once you take it, you can't unsee what's happening out there. And we all here took the red pill and their agents in every single nook and cranny of the economy, they're just getting started. Some of them are not yet quite monetizing. Some of them are just, you know, out there, you know, getting market share. But the great majority of them are fine tuning the agents to work precisely well in the industry in which they're deployed. Which is incredibly exciting because it's opening an opportunity for people who are not traditionally in tech to be in tech and make money.

• 7:16Speaker 02

  To use technology tools. Yeah, no, that makes good sense to me. Do you think we're going to see then agents make their way into technology companies more generally this year, next year? When does the other part of the economy come onto the agent side of things?

• 7:29Speaker 03

  I, I, I think that the, usually the way the economic cycles work with innovation is that, you know, software startups buy from other software startups and you go up and down one on one and that's the majority of your market and you try to expand from there. And that's when you cross the chasm. I'm seeing it all the way around. I'm seeing, you know, real American, you know, real business companies that are already jumping directly into agents or bypassing the whole cloud thing and going directly into agentic purchases. And companies that you will think have no business being an agent, such as freight forwarding or, or, or supply chain or fleet management or mortgages or insurances, they're all going directly to agencies. And there's two reasons why this is happening.

• 8:13Speaker 03

  One is because their workforce is aging out.

• 8:18Speaker 03

  And they found agents as a way to to not have to go and retrain you know new kids to become actually who they may not want to be. The other one is the fact that the the comparison of an agent is not against other agents or human beings, it's against BPOs, which are human beings, but they

• 8:35Speaker 02

  BPOs are business process, outsourcing, just people that will do the busy work for you off seas.

• 8:40Speaker 03

  A hundred percent. Exactly, exactly. And and an agent compared to a BPO is incredibly more efficient, more effective and higher performing. So that's sort of like the the table stakes right now of what's going on with agents. And that's a very rich market to go after. And we're going to see that for the next five years until we start seeing other effects of agents in the marketplace.

• 9:05Jason Calacanis?

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• 9:46Jason Calacanis?

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• 10:26Speaker 02

  So agents are here today, often in places where you can't quite see them. You're optimistic about their ability to improve and expand their market share. So this is the year of agents, year one, I guess, I should think of it not that we're going to get to the end this year, but certainly we are accelerating towards an agentic future. Fair enough?

• 10:43Speaker 03

  A hundred percent. You just planted your asparagus field and they're all sprouting. So all you're gonna see is sprouts. Next year is gonna be a nice, bountiful harvest.

• 10:53Speaker 02

  Okay, let's talk about where paid fits into this because everyone knows in a traditional SaaS context, software is very margin efficient. You can have gross margins in the seventies, eighties, some cases even low nineties. One reason why everyone loves it. AI, on the other hand, is often more expensive to run. And I presume that when you build an agent that has a foundation model from a third party inside the core, that it's expensive to run as well. So can you just tell me what the economics look like for the average company selling agents for those products? How much do they cost to run? And if you can, before a paid given, how are they tracking those costs?

• 11:32Speaker 03

  So the, the difference between a normal SaaS company, like a SaaS company of the, you know, seventy to eighty percent gross margins and an agentic company is exactly what you talked about. I said, the cost of inference and the cost of tokens that are paying to the L, to the foundation model provider. And those go on top of your cloud cost. So now you have your eighty percent cost and you have the additional cost of, of, you know, pretty much the human replacement. So whereas a SaaS company will have, you know, seventy to eighty percent of gross margins,

• 12:06Speaker 03

  an agent company would have somewhere between forty and sixty percent gross margins. And that will significantly, and then that's problem number one, or sort of situation number one. Situation number two, and that is incredibly variable depending on the type of customer. So for instance, you can have a customer, if you're in customer service, you can have a customer that, that you call in and you quickly, you know, tell them the answer to what they're looking for and on they move. Or you can have a customer that calls in and they tell you the story of their lives. They ask you a bunch of questions that are not relevant. into what they're trying to get resolved. And then they ask you the question about they're trying to get resolved. And you just got a free chat session with that person.

• 12:43Speaker 02

  And you're paying for all the tokens.

• 12:45Speaker 03

  Yeah, exactly. For all the tokens, you're paying for all the tokens. Exactly.

• 12:48Speaker 02

  So really, the more terse versus verbose your customers are if they're chatting with your agentic product, the more money you can make. So really, that does imply that you want to get to value very quickly in those interactions to prevent excess token generation.

• 13:03Speaker 03

  A hundred percent, but there's no, no way for you to predict it. The customer, the service is out there and it's performing. I mean, the same thing is, is for agents that do document reviews. So there are some people who have short histories and some other have very long histories. And for the very long histories, that's just going to consume a lot of tokens. The same thing for people who are, you know, performing complicated tasks. The more agentic the behavior is, the more autonomous, the more agency an agent has, the more likely it is to run off the rails and go to something that you are not expecting it to do. And it may be for good reasons, but you just don't know. And, and that's sort of the trade offs that we're living in right now, which is a fascinating thing because you're giving them the ability to decide. And that's very exciting.

• 13:46Speaker 02

  It's very exciting that they can decide, but you don't want them to decide to spend your entire checking account on, you know, anthropic credits or whatever.

• 13:52Speaker 03

  A hundred percent.

• 13:53Speaker 02

  Okay, now, a question that I have is, do some agentic systems use multiple AI model providers? Because when I was thinking about the problem you guys are solving, it seems like it would get even more complicated if I sometimes lean on GPT-5, sometimes on GROK-4 and sometimes on, I don't know, Claude Opus 4.1.

• 14:11Speaker 03

  They, they do, but they don't do it for economic reasons. So if you think about every single model from every single provider, they have different behaviors. They have different tendencies. They are, they may answer the question completely differently, even if they're provided by the same vendor. So you don't know, because it's all a black box, you know, whether you can, you know, hard replace, you know, Sonnet with, you know, any of the versions of GPT. And whether that's going to work for you or, you know, Gemini, et cetera. So they, so there are definitely ways for you to arbitrage the token cost, but you have, but the task. Need to be relatively simple and relatively swappable. In which case you may not even be solving the right problem because it will be an agent company out there that will take your problem,

• 14:55Speaker 03

  bundle it into a bigger basket of problems that are solving it and make you irrelevant. So it's a very dynamic environment right now where there is no free lunch for anybody, right? Like if you're making a ton of money, you can rest assured that there is four Y C startups that are going to come after you with a much better model that is going to solve a bigger problem you're solving in your roadkill.

• 15:14Speaker 02

  So it's the old Bezos quote, your margin is my opportunity.

• 15:18Speaker 03

  Oh, 100%, 100%. At Amazon, you know, people used to live with like somewhere between, you know, 6% and 20% operating margins. And it was a good day when you hit 20% because people want a lot of books. But on the day that they bought a lot of electronics, you could be upside down. So you have to be really careful how you operate. This is why, you know, most of the companies give you free coffee at Amazon. You gotta put your 25 cents in the little jar before you put yourself a cup of coffee.

• 15:45Speaker 02

  I, I didn't know that, but that was my experience at the headquarters of State Farm. Once I got there after going to a lot of Silicon Valley offices and I went to the little cafe and they're like, that's a dollar. I'm like, what?

• 15:59Speaker 03

  There you are where your, where your Silicon Valley entitlement, we're hoping for a free latte. And that's a use how to say.

• 16:05Speaker 02

  It wasn't even a latte, man. It was just a black coffee, but that's what you get for going to Southern Illinois. Okay, so clearly you don't want to undercharge for your agentic work because then you're upside down and that's terrible. So talk to me about how paid helps people actually sort out the discrete costs per, I'm not sure the phrase here, agentic interaction, agentic use case, the, the, where the rubber meets the road, if you will.

• 16:31Speaker 03

  Yeah, so the, if you think about the dynamics of pricing, pricing has roughly three components. One is your cost, so you clearly want to be above that. The other one is what is the equivalent of the service that you're providing? And how much would that cost? And in the iteration that we're living right now, that equivalent for the agentic cost is a human being. So you can easily compare, you know, what would a human do, take to do the same work? And the third one, of course. Is a competition like there if somebody is doing the same thing that you're doing and they have a different cost, you have to be solely in the same ballpark of that. So what we hope everyone see is the fact that, you know, A, we help you see your cost, but B, we help you understand what is that the agent is doing so that when you pitch it to your customer,

• 17:14Speaker 03

  the customer can figure out out of all these activities the agent is performing, which ones do they attach the most value to and you can charge for those. And this is the, the, the, the, the change in, in, in mentality that we are embracing. We're actually asking our customers to embrace is that you don't need a consistent price sheet for all your customers. What you do need is to make sure that your value aligns to the customer perceived value receive. Once those things match, that's where you should price. You shouldn't price in a way that is simple to you. You should price in a way that is consumable by your customer in a way that your customer perceives they're getting value. And that's what we offer is a flexible platform that understands what the agent is doing.

• 17:59Speaker 03

  And allows you to capture the value in a way that the customer wants the value to be captured.

• 18:03Speaker 02

  Okay. So that's, that's two parts. Let's stick with the cost tracking. I've, I was going through some of your developer docs and you guys talked about signals as a concept of like breaking down work. I guess what I wanted to know is how granular can you get on tracking either an agent for a customer or an agent doing a task for a customer? Can you get down to the cents that it costs?

• 18:29Speaker 03

  So we, what we do is just to get technical here for a minute. So we, we, we found out that the entirety of what you need to understand of what the agent is performing is in the runtime code of the agent. So once the agent executes this code, there is this egress that comes out of the code that is the runtime. And that could be captured by a technology that is open source called Open Telemetry. Open Telemetry allows you to decorate the code and then see the entire egress of the, of the execution. The egress of the execution is like, imagine somebody's walking around right next to you, clocking every activity that you do and taking a note. Every time you drink coffee, I clock it. Every time you do a podcast, I clock. You go take the kids a clock it. And now you have a catalog of everything that you did today. And now you can choose what are you going to charge for?

• 19:14Speaker 03

  And what are you going to show? Right? And that's what other technology does. And once you do that, then you can go around and buy customer. So if a customer bought your agent, because it saves in time. If a customer bought your agents, because it shortened times to value to their customers. If a customer brought your agent, because it delivers higher NPS, you can charge for those things, because you can see it.

• 19:35Speaker 02

  Okay, so you can get very, very granular and you can decide what to charge for. Are you pushing us towards a world in which each customer not only pays a different price for what they're getting in an agent context, but it could also vary based on the specific task that are put into it in that moment? Is that responsive to the customer asks of the service?

• 19:57Speaker 03

  Absolutely. So let me tell you an actual exact example.

• 20:00Speaker 02

  Okay.

• 20:02Speaker 03

  We're working with customer service agents for car dealers. And it turns out that this car dealer customer service agent is blowing up in the Middle East. And the work performed is the same. So they take an inbound lead, they convince it to come into the showroom. They get more information about the kind of car they want. And once they become a customer, they sort of try to get them in for services and for up sales. Right? So it turns out that the same customer, the same activity, sorry, not the same customer, same activity the agent does. If that person, if that activity is performed in South Dubai, and you get a customer in into the Beamer dealership, the likelihood of they walking out with a car is in the 90 some percent.

• 20:47Speaker 03

  Why? Because they have a lot of money. If they like the Beamer, they walk off with it. Versus North Dubai, where the likelihood of they walking out with a Beamer is a lot lower, because they tend to be a lot cheaper, a lot more price conscious, and then go from dealer to dealer to find the right price. So driving a lead into the store at the South Dubai dealer is worth significantly more to the dealer than it is driving a lead to the North Dubai car dealer. And how do you capture that value? Even though the work is the same, the value is significantly different. You want to capture that.

• 21:21Jason Calacanis?

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• 22:06Jason Calacanis?

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• 22:25Speaker 02

  But if I'm the dealership, I want to pay as little for this as possible because I want to make the most money that I can. Am I going to be content with you coming to me and saying, "All right, listen, Manny, if it's a South Dubai IP address, then we're going to charge you X dollars. If it's a North Dubai address, we're going to charge you Z dollars." And I'm going to be like, "Wait a minute, it's the same work. Why do I have to pay more for it? Am I not just padding your margins?" This feels like search pricing in the micro sense for each customer interaction, which feels almost egregious to me in a way. Maybe I'm just being too cheap here, but Manny, I feel... Are people complaining about that at all or are they fine with it?

• 23:07Speaker 03

  No, I think that it drives a conversation around value again. So if you're a dealer, let's take a step back. If you're a dealer, not a influencer, a podcaster, host, like if you're an actual dealer, your job is to move cars off the lot.

• 23:23Speaker 02

  Yeah.

• 23:24Speaker 03

  Full stop, right? And you make money by moving certain cars of cars off the lot. So whether the agent charges you more for because you happen to be the South Dubai one versus the North Dubai one, it may come into play in the conversation, but at the end of the day, if this agent moves cars off the lot, we're having a conversation and it's going to be a productive conversation.

• 23:50Speaker 02

  Okay, so I was really thinking two small things. I was thinking about SaaS pricing, you know, recurring per seat, whatever. People moved into in the Twilio era, you know, pay for what you use. In this case, though, we're kind of moving to a new iteration, which is pay for demonstrated value, I suppose.

• 24:08Speaker 03

  Exactly.

• 24:09Speaker 02

  Okay.

• 24:09Speaker 03

  Exactly. And just think about that. Like if you are charging for the fact that you moved the car off the lot and you're not charging for the 20 other conversations that didn't result in moving a car off the lot, there's a lot of economic unlock in that kind of pricing. I'm not suggesting that that's the way you go, but I am suggesting that that is well more aligned to both parties and how both parties can realize value than some kind of seat pricing, in which, you know, you may have a person using the tool that may or may not move cars off the lot.

• 24:41Speaker 02

  So you just said that when you manage a transaction, when you pull off a transaction via an agent, it's a success, but you might not get paid if it doesn't lead to a sale. So are we going to see a world in which some agentic products only derive revenue when a customer completes a transaction on the other end and then otherwise it'll be provided for for free?

• 25:04Speaker 03

  Yeah, that's entirely in the cards.

• 25:07Speaker 02

  Wow, that's super aligned, but also it sounds very complicated, given you'd have to have so much information about, you'd have to know that you're, you know, there's a split in Dubai, you've drawn the line here and you'd have to probably define in sort of some billing system. So has all of that technology been built that we'll need? Or are we still working on building this scaffolding up to provide the granular information you would need to be so detailed on your pricing?

• 25:32Speaker 03

  No, so that's what we do. That's exactly what we do. So we eliminated, so we built paid from the principles of what are the future integrations going to be like? And once you decide what the future interaction is going to be like, then you need that kind of flexibility. You need to be able to provide, like, again, I'm not saying anything new here. Like, you should be able to provide the value and deliver the value that your customer scares about and then charge for it. But as it turns out, every customer is in a different, is in a different path, is in a different value perception curve. And they should be able to pay in the way they want. And like what we have done in the last 20 years is convince the software vendors that because we're so powerful and so magical

• 26:13Speaker 03

  that we can charge this arbitrary per seat thing, because it's really hard for us to like otherwise scale the pricing. And I think that's a big bag of lies. I think that in the end of the world, software is very cheap to build and you should be able to build exactly what your customers need. And like your inability to scale custom pricing doesn't seem like it's your customer's problem. That seems like your problem. You should really fix it.

• 26:37Speaker 02

  Yeah. Okay. So in the future world, then, let's say that I'm selling an agentic product to a Dubai dealership. Do I have like a forward deployed engineer that's helping them, you know, dig deep into their granular business to define the right pricing setup for them? Or is this something that's automated enough that a dealership could set up a relationship with an AI agent vendor without having to do a lot of custom coding work to make their iteration function? Because I feel like if it's the latter case, your business is going to be much bigger. If it's the former case, it's going to be slower growing.

• 27:10Speaker 03

  I think that a lot of these rules are going to be baked in. So like as one of the things that is beautiful about this agentic world is that is that we are truly embracing services because we're replacing services. But as you embrace services and replace them, the kind of services you provide is higher level. You see what I mean? So instead of like doing forward deployed for, you know, hooking up the agentic workflow that is going to do discriminatory pricing based on your location. I think you will do some other kind of services around, you know, you know, where car dealers actually make money is on the trim. It's on the services. It's on the app sale. So like the idea, then you're going to really have your juices flowing more into like, okay, so what kind of marketing program can I run to get people backing here? You see what I mean? Like, how can I elevate the trim?

• 27:55Speaker 03

  The moment you fall in love with that red Beamer, how can I sell you the one with the spoiler? And they want with like, you know, more horsepower? So those are the kinds of things that you're thinking about that that this kind of like, you know, pricing unlocks.

• 28:08Speaker 02

  Well, I was really excited to talk to you because I feel like you were attacking a really interesting problem point in the AI economy today. Figured out what it costs to run an agent and also how much to charge for it. I didn't realize, though, Manny, and this is so glad you came on, just how detailed where you're going to need to get and also how good that's going to be for the end customers. But what this does do is put a lot of pressure on the AI agent companies. Because if we're going to charge only for really defined value, they have to build high quality products that really get there. So I guess, I guess, good luck, everybody building, because there's going to be no, you have to get signed up for 1,000 seats to get the enterprise, you know, you know, SSO or whatever, you're going to have to really be good everywhere.

• 28:50Speaker 03

  100%, 100%, but like, isn't that the way it's supposed to work?

• 28:54Speaker 02

  All right, wait. I mean, I'm not saying this is bad. I'm saying it's exciting.

• 28:58Speaker 03

  Why will you go to a doctor that is okay versus a doctor who actually fixes your problem?

• 29:03Speaker 02

  The website is paid.ai. Manny, thank you so much for coming on. We really appreciate it. And when you hit 100 million ARR in like 40 months, just call me up and we'll talk again.

• 29:11Speaker 03

  I'll dial you right up. Good to see you.

• 29:18Speaker 02

  All right, Jason, speaking of founders, we have one literally waiting in the wings. I'm incredibly excited to bring Camilo Ramirez. He's the co-founder and CEO of iTrucker. Now, you know this company, Jason. It's based in Pittsburgh. It was in Launch Accelerator 34, and it's working on helping trucking companies do more using AI agents. And what's cool is Camilo is not just another Stanford graduate out there trying to sling code to a market. No, he's actually driven trucks on a cross-country basis, both dry and, as he says, reefer, which means refrigerated. Camilo, welcome to the show.

• 29:48Speaker 04

  Hey guys, thank you, appreciate it.

• 29:50Jason Calacanis?

  Yeah, nice to see you. I was absolutely in awe of your performance. You did a great job of presenting in the accelerator. And yeah, sometimes domain expertise is great. Sometimes domain expertise can ankle you, but sometimes it can give you an unfair advantage in the space. So what have you learned in that aspect? And maybe start with telling us what your insight was as an insider of what needed to be built here. That'd be a good place to start.

• 30:19Speaker 04

  Sure, yeah. Well, thank you guys for having me here. Appreciate it. Yep, former truck driver a couple of years ago, where I understood the pain points of the driver when you're driving over 600 miles per day. Then you're stuck with a flat tire at the midnight and no one is there to help you, right? So then we had the opportunity to own our fleet. We ended up with around like 15 trucks, where we saw the problem from the other side. So at the time, we had 15 drivers calling us, asking for pickup number. Then we have 15 customers asking like, "Where's my load?" You know, like, "Is it gonna be on time?" And it's a 24/7 business. So we understood that in order to build something

• 31:01Speaker 04

  to improve this kind of like activities, coordination on a single basis, we needed to build something that is able to be part of the operations team. So basically that is able to talk to the drivers, to talk to the customers, to brokers, forward information. We have a ton of paperwork going around. So, you know, reading those documents and forwarding the right information to the right party. So we learned that we needed to build this bottoms up in order to get to the trucking companies and put our service within their operations.

• 31:45Jason Calacanis?

  Y'all know I'm obsessive about a good domain name and I'm so proud of my exclusive collection of single-word, easy-to-spell .coms from begin.com, inside.com, mahalo.com, a day.com, but the truth is, the supply is dwindling. You could spend your whole life brainstorming ideas, but 99.99% of the best .coms are taken by rich guys like me, or they're sitting there wasting away unused. But fear not, founders, there's a simple solution: .tech domains. A .tech domain means you don't have to compromise or give your company an awkward name you hate. .tech instantly lets everyone, from customers to potential

• 32:26Jason Calacanis?

  investors, know you're a tech company building something innovative. It's in the domain. That's why over 500,000 founders have collectively raised over $5 billion in investment using their .tech domain. Even CS, the world's largest electronics show, is using a .tech domain now for a reason. It's time to move over to .tech, so head over to get.tech/twist, G-E-T dot tech slash twist. So when this was done prior to your product, iTrucker, which is I-T-R-U-C-K-R, drop the

• 33:02Jason Calacanis?

  E for elite, you found there are dispatchers. Dispatchers are curmudgeonly humans who have to get on the phone with all these parties and yell at the drivers and manage the people who are, you know, sending a load across the country and they're chain-smoking Marlboro Lights in some boiler room somewhere, and they're getting paid a large amount of money to do this, essentially, air traffic control for trucks, yeah? Where do they get paid?

• 33:43Speaker 04

  Yep. So there are like two different ways on how that operates. So we have like some fleets, they are able to like bring those dispatchers like in-house team of people. So it's a little bit cheaper for them because you're hiring like a full-time employee. But then there's a lot of trucking companies that use like dispatching services. So those fleets are able to, well, they're not able to, you know, bring a full-time employee. So they're paying like a portion of the revenue of the

• 34:13Jason Calacanis?

  Oh, that sounds expensive.

• 34:15Speaker 04

  Yeah, it's pretty much expensive. If you have like 10 trucks, you know, you're making a hundred K.

• 34:19Jason Calacanis?

  So what was your solution then? You, I know you had an AI-first solution to this. So what did you build and how has it worked?

• 34:28Speaker 04

  Yep. So we are deploying A workers, A fleets within those operations. So basically we are automating the communication. So now a trucking company, instead of having like three dispatchers to dispatch a fleet of 15, 20 trucks, they're probably just gonna need one because we help them with like booking loads, right? So now our agents are able to go to different load boards, find different option of loads, make the phone call, send email, book the load, then

• 34:57Jason Calacanis?

  And that's being done by an AI agent that's calling on the phone using voice or text to voice, I guess. And you've, you've built all these sophisticated AI agents and they occur as a co-pilot, where they're supervised? Or are they stable enough to deploy them and not have a human in the loop or a human checking them? How does that work? Because we've heard a lot with this MIT study, oh my God, you know, AI doesn't work. Obviously co-pilots work really well. Agents, people do have concerns. So yeah, unpack that piece.

• 35:33Speaker 04

  Yep, so we right now have, well, they have a dashboard where they can see like the whole operation. So they can see like how the AI is talking to the drivers through text messages. They can see like how the email is replying on a on lifetime. Then they also have the option to to like stop whatever the AI is doing, or the AI suggests a few things. So let's say, just to to give you like a specific workload. So they have a truck idling for six hours. So the AI notified the dispatcher or the fleet manager saying, hey, we have these drivers in this location. It's idling his truck for five hours. You want me to find a load? So they just approve the the the option, and then the AI go find the load, book the load, and notify the driver, and notify the dispatcher saying like, hey, I found this,

• 36:19Speaker 04

  based on the metrics that we already have set up.

• 36:22Speaker 02

  Camilo, how do you get that information? Is it IOT that lets you know that this truck is idle for five hours? Because that's a very specific actionable data point, but you can't, you know, have a human looking at GPS data. So how do you get that that nugget?

• 36:34Speaker 04

  Yep. So in trucking, there's a system called ELD, which is an electronic logging device, where every single truck needs to put a hardware into their trucks to see where they are to for this hour of service that the driver can drive. They can just drive 11 hours per day. So they have this GPS tracking kind of thing. So they have all these telematics, like, you know, fuel consumption and all that. So we are integrating those ELDs into our system. So we are able to see where the truck is, how fast they drive, if they have, you know, enough fuel to get to the delivery location.

• 37:08Jason Calacanis?

  Truck drivers have no privacy. They can't stop and like, have a couple of beers and drink, or, you know, have a hamburger and take a nap and then go 75 miles an hour the next morning to make up for it. They're monitored, like, very granularly? Is that correct?

• 37:25Speaker 04

  Yeah, exactly. So

• 37:26Jason Calacanis?

  Are they required to have cameras in the in the cabin, too?

• 37:30Speaker 04

  Right, yes. Some of them, they're putting like cameras in in front of the dashboard.

• 37:34Jason Calacanis?

  Is that required now? Or is that like your trucking company decides? Is that like a federal mandate?

• 37:38Speaker 04

  No, no, no, no. That depends on the on the fleet, and then depends on the insurance company. Some insurance are like, hey, you gotta record every single, you know, piece of the of the journey of the driver. But some of them, they're just, you know, fleet.

• 37:52Jason Calacanis?

  Which is why we now have this video tragically. I don't, you must have seen this of this, did you see this last week, Alex? To have video. Of a lunatic truck driver who decides to make a U-turn on the freeway and I think he had a double cab. I'm not sure if it was a, it was a double cab.

• 38:10Speaker 04

  Yep, it was the same way.

• 38:11Jason Calacanis?

  It's so tragic. He decides, oh, I missed my exit, so I'm going to use the U-turn, which is like the police U-turn.

• 38:18Speaker 02

  Yeah, in between the dual carriageway, the gravel bit in between, yeah.

• 38:21Jason Calacanis?

  Yeah. And then he, because he decides to do this, a car can't stop and smashes into the side of him. And I think tragically, two people were killed.

• 38:29Speaker 02

  I'm not going to play it because of that, but

• 38:31Jason Calacanis?

  No, we don't need to play it, but it's awful. It's awful. And there's a video of his perspective on it because you have not only video of the driver, not only video of the road and everything and the rearview mirror, you have video of the driver and their reaction to it. Oh, yeah, yoi.

• 38:48Speaker 02

  Yeah.

• 38:49Speaker 04

  Yeah, must be tough.

• 38:51Speaker 02

  What's your average trucker? How many trucks are the average customer of you guys have? Because what I learned prepping for our chat today is that trucking companies come in size from absolute pipsqueaks to absolute behemoths.

• 39:01Speaker 04

  Yeah. So we started with smaller fleets, like one, three, four trucks operations. Once we like fully deployed the product, we now are targeting like midsize fleets. So anywhere from like three trucks to 100 trucks. Those are the ones that are feeling the pain that they're having, you know, like four or five dispatchers, working 24/7, talking to drivers, talking to brokers. So those are the fleets that we're targeting right now and we are focusing.

• 39:27Speaker 02

  How many, how many of those companies are there in the US? I don't think a lot of folks that are listening to us right now have a good feel for how many midsize trucking companies there are out there. I presume it's a lot.

• 39:36Speaker 04

  Yeah. So let's, let's say that in total, we have over like 2 million fleets. That includes like box trucks and all kind of like fleets. Then within the trucking, we have around like 800,000, right? And then within those 100,000, we have around, around like 300,000 for midsize, like three to 100 trucks. So there's like a, a plenty of, a room for us to play here.

• 40:00Jason Calacanis?

  Awesome. Well, it's office hours. Company's doing well. You got through the accelerator. You got customers. You're growing nicely. You're using AI to the fullest of its current abilities. You're one of these companies that's like the tip of the spear in using this technology. But you know, we're here and there must be some things you're either struggling with or challenged with. Any questions for me that, or anything you want to discuss?

• 40:27Speaker 04

  Well, now we are seeing a lot of opportunities like in enterprises accounts, like larger fleets, even like out of the country opportunities.

• 40:39Jason Calacanis?

  Great.

• 40:40Speaker 04

  So in order for us, you know, to stay focused on how we're growing, because we're growing pretty fast, any tips on like how to handle both things, like, you know, like how we handle enterprises?

• 40:54Jason Calacanis?

  Yeah, so the great thing about enterprise customers is that they will spend more money. And if they love your product or service, they're probably less price sensitive. The great thing about the small boutique, you know, smaller customers is they might be more scrappy and willing to try something, right? Because they don't have the budgets. And, you know, that's why a lot of people will use startups as their first customers, because startups will actually use the product. Whereas if you go after the big enterprise clients, they take a long time to sell, they're going to need SOC 2, you know, so you're going to need to get in touch with Vanta, make sure your SOC 2 is compliant, all that good stuff.

• 41:37Jason Calacanis?

  And they just take forever, right? They might have a six-month sales cycle, they may want you to build custom software, so they can be a bit of a headache. What's important is to study your customer base. And if you're in a highly fragmented market, there can be many customers. What's a highly fragmented market startup that's done incredibly well? Spotify. They went after small merchants. There was Magento and other big products, you know, going after the large enterprises, going after Target, or, you know, I don't know, Walmart. Maybe those companies are even too big, they build their own it because it's so critical for the user experience. But they went after the long tail. HubSpot.

• 42:18Jason Calacanis?

  They wanted, you know, small firms' Squarespace. There are big companies that use it, there are small companies that use it. So then you have to make a decision. Do you want to have a sales team? Do you want to deal with custom software? Do you want to deal with approval processes? And both can work. Obviously, there are Salesforce and other tools for large enterprises for sales and marketing functions, and then there's HubSpot. And this will inform a lot of product decisions and a lot of go-to-market decisions. Your go-to right now, I'm assuming, is founder-led sales. You email a small trucking company, or they hear about it from another small trucking

• 43:00Jason Calacanis?

  company, you get on the phone with them, and the person you're talking to owns the business, gives you their credit card, fills out a form, and you're done. Okay, so you get a nice, quick hit. But it might only be $1,000 or $3,000 a year. And you might start to say, you know what? I want the $10,000 a year customer. I want the $30,000 a year customer. So it really is going to determine how you staff and fund your company. You may need more runway to go after that. So what does your gut tell you, or what does your knowledge tell you about what type of market you're in? Are there a small number of large flyers and a long tail of small ones?

• 43:45Jason Calacanis?

  Are there plenty of both, so both business models will work? I don't know enough about trucking to know the answer to that.

• 43:50Speaker 04

  Yep, yep. That's pretty good advice. And right now, we're seeing our product into this mid-size level, which is the, you know, sales cycle much faster because, like you said, the owner is involved. So it's really easy to show them the product, like, hey, here's the solution. They're scaling their operations. So it's really working right now. But then, you know, those enterprises comes and they're like, hey, I want to use your technology, not your product, but your technology to put into our current systems. So, but it's a different game, like you just said. So we will...

• 44:22Jason Calacanis?

  You might need to price differently for them. And you then have one group that is easy breezy, they'll just use your solution. Like I said, the other group is, oh my God, I need... You know, this custom thing, I need that custom thing. Can you get into our accounting system? And a way to do that is to say, yes, we can do it. It's going to require a $250,000 activation fee for us to build that. And we need you to pay upfront. If you're willing to do that, we're happy to work on the project. And then you can hire two developers or a product manager and a developer. And you tell them, I will embed ourselves. You may have heard me talk in the accelerator or founding university. Did you go to founding university too, or just accelerator?

• 45:07Speaker 04

  No, just the accelerator.

• 45:08Jason Calacanis?

  Great. And so I've told the story before about bear hugging a client, which is when you embed yourself at their company. So you could say to one of the big ones, I'll put a product manager in your office for six months to sit with your team and to outline all these features. We just need 250K in advance. And that's for the first six months of this trial. And then afterwards, this is what the pricing would be. So you're kind of challenging them to not waste your time. The biggest problem founders get into is that, oh, my God, this is such an incredible lighthouse customer. And then some mid person there wants to get points. They drag you through different specs and documents and meetings.

• 45:53Jason Calacanis?

  And then they try to sell it to their boss. And then that person decides they're going to leave the company. They get fired and you lost your contact there. So you gotta kind of let them have skin in the game. You gotta say, listen, we're a small company. We're eight people. In order to do this, I need two more people. In order to do this, you know, I'm adding five new customers a month right now for the existing product. I just need you to, you know, make a commitment upfront. And so how do you feel about a 250K pilot for six months? And the person might say, I can't authorize that. And say, oh, who in the organization can? Maybe we should have a meeting with them. And you just challenge them, you challenge them, you challenge them. And if they're not serious, you say, you know what? We're just resource constrained. We'd love to work with you, but we need to stay focused on this. Can we check in in six months? And boom.

• 46:37Jason Calacanis?

  Does that make sense?

• 46:38Speaker 04

  Yep, a lot of sense.

• 46:39Jason Calacanis?

  Yeah.

• 46:40Speaker 04

  Thank you, thank you.

• 46:40Jason Calacanis?

  So don't be scared of these customers. Look at how many employees they have and times that number by $200,000. So what's the biggest of the customers you've talked to who are the big fish? How many employees do they have? Do you even know?

• 46:54Speaker 04

  Uh, with a thousand, they're like.

• 46:56Jason Calacanis?

  A thousand.

• 46:57Speaker 04

  Yeah.

• 46:57Jason Calacanis?

  So a thousand times 200,000 is $200 million. They're probably spending all in about $200 million running that operation if they have a thousand employees. And if it's a public company, you can go find that out. But, you know, it's not that every employee is getting paid 200,000. It's that, you know, maybe on average, the employees cost 100,000 with their benefits, but they have to have office space. They have HR, they have turnover, they've got to recruit people. And you start, just as a back of the envelope number, for a mid-sized company, that. And then for a Google or for a Facebook, maybe it's 500,000 per employee. You can estimate what they spend.

• 47:37Jason Calacanis?

  Alex, if you were to look up how much money Meta spends a quarter and how many employees they have ballpark, and you were to divide those two numbers, and he'll go do that in real time because he's awesome at these kind of things, you'll get a certain expense base per employee. It might be 500, 750K in total spend because they build signature office space. They have other kinds of infrastructure. They have consultants. Free food. Free food, all this stuff. You know what the free food bill is at those big companies? It's like 10, 20K per employee.

• 48:09Speaker 04

  Wow.

• 48:09Jason Calacanis?

  The free food is so expensive that the IRS felt the need to investigate if they were end running compensation by using their pre-tax dollars and giving an employee benefit, to which point the IRS said, hey, if you're going to spend $20,000 on perjury employees, we need you to pay. Tax on that because that would be the same as like paying for a corporate apartment, paying for a corporate car that's used personally. Like they have to eat. That's on you to give that perk. And I don't know where that IRS investigations wound up, but you know, that's how crazy the spending they have per employee is. So I would-

• 48:51Speaker 02

  So far as we can tell, Jason, you were very much close to dead on. 2024, which is the latest full year employee data, they don't drop it every quarter, about 550,000 in expenses per employee against revenue of 2.22 million per employee last year. And that's why Met is a good business.

• 49:11Jason Calacanis?

  And that's why when they keep the team size the same and grow revenue 10 or 20% per year, the earnings increase, which is why people keep betting more and more money on the mag seven. Listen, continued success. Camilla, hopefully we did a good job for you in the accelerator. Did my team work hard and support you?

• 49:29Speaker 04

  Absolutely. Yanka was great. We met a lot of connections, great connections, a lot of BCS interest. So it was really good, really good.

• 49:39Jason Calacanis?

  What was the best part of the accelerator for you as a founder that you got the most value from? And then after that, what do you wish we would add to the program that would make it better for you as a founder, if anything?

• 49:52Speaker 04

  Yeah.

• 49:52Jason Calacanis?

  Take a second to think about that. Yeah.

• 49:53Speaker 04

  The best thing definitely is the pitch sessions, you know, like practicing this pitch, these two minutes pitch like every single week. So after that, like every time I have a meeting and I'm pitching and they're like, you're done? Like, wow, you just covered everything because you know, we covered the issue, what's the solution, his product revenue, and that's it. So that's definitely really, really-

• 50:21Jason Calacanis?

  Pitching really helped you.

• 50:22Speaker 04

  Yeah.

• 50:23Jason Calacanis?

  And Alex, well, we originally were at like five minutes of pitch, then it went to three minutes, then we made it two minutes.

• 50:28Speaker 02

  Two!

• 50:29Jason Calacanis?

  A dozen companies.

• 50:30Speaker 02

  That's only 120 seconds, man.

• 50:31Jason Calacanis?

  Yeah. Well, here's the thing. You are making a trailer of your startup is what we tell the founders. Now, the trailer for Star Wars doesn't tell you, spoiler alert, that Darth Vader is Luke's father. It just tells you like this is an epic thing happening in space and there's lasers and there's ships and it's, there's a Wookiee and you're like, oh, I want to know more about this movie. That's what we try to accomplish, which is, oh, wow. This is a interesting founder or interesting founders. And they found it's a really interesting market. Oh, and this is a really interesting solution. Oh, and this is a really interesting TAM. Oh, and the competitive set is, you know, Marge, smoking those Marlboro Lights, two packs a day, you know, yelling into a landline.

• 51:16Jason Calacanis?

  Uh, and who tells you to get the hell out of our office and throws the ashtray at you when it's filled with 20 cigarette butts if the boss comes in there and tries to give her a hard time.

• 51:26Speaker 02

  Two packs a day is excessive smoking. If you're smoking two packs a day, man, what's the side of you?

• 51:31Jason Calacanis?

  I mean, I know these dispatchers. They're, they're, these are curmudgeonly hardcore individuals. I love them. I knew them from the dispatch at Harbor Car Service in Bay Ridge, Brooklyn, where I grew up. Uh, cause yeah, there, there was like a large Marge there too, who would yell and scream at people. And get the hell over there, pick up John to be its kids. It's the middle one, Jason. He's, he's gotta get to school. He's late. Uh, they give him a hard time. Okay, what can we do better? Is there anything that you would have liked to add to it? Sometimes people ask for mentors. I always felt the mentor thing was kinda garbage because they had these mid mentors. But you, you tell me, is there something that we could have added to the program that would have helped you more?

• 52:10Speaker 04

  I mean, well, yeah, the thing with mentors is the, that really depends like who's the one that is gonna help us, you know? Uh, if it's gonna be like, you know, founder, maybe, uh, could be a good advice. Um, but what else can I say?

• 52:28Speaker 02

  More money.

• 52:29Speaker 04

  Could be more money.

• 52:30Jason Calacanis?

  Okay, sure, we'll double it. Sure. Great. And more money to the program. Thanks, Alex. You just cost me more money.

• 52:37Speaker 04

  That would be a, a great opportunity to double the money. Yep. And, um, but no, for real, it's a really full program. Uh, we really love the, the pitches, the introductions. I mean, we haven't seen, um, well, programs like this one where you see every single week, five, six, seven different VCs. And just not like associates, but also like, you know, the managing partner and then he's the owner of the, of the fund. So that, that adds a lot of value.

• 53:09Jason Calacanis?

  To unpack that, Alex, you know, some firms do like this big demo day and they advise you, "Hey, don't do meetings with investors before then. Just get your startup nice and tight." I took a different approach. I'm not saying the other approach doesn't work. It does to create like a bit of a marketplace at the end. What I'd said was, "Let's pick our favorite investors who we have deep relationships with, who give great advice and who are willing to give up an hour and a half of their time." And then we say to those ones we like best, "Here's the calendar. Pick a date you want to come." And then it becomes competitive. They're like, "I want to get these companies in the first, second, third week because I want to pick them off before other people see them." And so then what happens is, you know, Camilla will get some

• 53:53Jason Calacanis?

  great piece of advice, you know, three or four times where people are like, "Hey, this TAM is, you're charging too little for the value you're creating." And when a founder hears that, not from us, not from their customers, but from three or four VCs in three or four weeks, and then they just try raising their prices and then they present, "Oh yeah, we have three pricing models. There's the introduction for, you know, one truck company or two, three and under companies and we charge them, you know, a hundred bucks a month. But then these ones, we charge 750 a month and 1500 a month. And when we changed that pricing, we saw people, half our customers moved up. And when we deprecated the free product, we got rid of 20%

• 54:35Jason Calacanis?

  of our annoying customers and the 80% said, "No problem." And they just, you know, agreed and checked a box to pay the higher rate. So we record every piece of feedback, Alex. We normalize it and we say, "Okay, you keep getting this question about your pricing. Should we have a discussion about that? And do you want to read a module we've written on pricing? Or would you like to talk to an expert about pricing?" And I find this model works better with great founders where we're not dictating to them how to run their company. They're just collecting lots of feedback, lots of feedback, and then they themselves normalize it and make their own decisions. And we help them by normalizing it and taking out all that work. If you had to set up those seven meetings,

• 55:20Jason Calacanis?

  Each week for 12 weeks, it would be a full-time job to get half of that done with the associates at the firm. There's nothing wrong with associates. We have plenty of them. But, you know, like you said, we try to get more senior folks. The associates, though, I will say, can be sneaky influential in some firms where you have lazy VCs who are like, they just send all the associates. I can't meet with all these companies. We do 100 meetings per week at our firm, introductory meetings. I could never do more than 20 of those. You know, back in the day, I could do 100, but, man, that becomes like, hard. Your brain will melt. All right, listen, great job. Very excited for you. Thank you for letting us invest and thanks for the kind words about the program.

• 55:57Speaker 04

  All right. Thank you, guys. Appreciate for the time.

• 56:02Speaker 02

  All right. Next up on the show, we have Elise Myrans. She is the CEO and co-founder of Tenax. It's Tenax AI. Jason, this is a company that wants to get more information about potential risks, help homeowners harden their houses to prevent wildfire damage, and also ensure that insurance companies can properly underwrite potential risk. It's an enormously important business because we've seen more natural disasters, higher repair costs. The entire US insurance market seems to be a little bit upside down, so I'm very excited to hear more from her. And here she is. Elise, how you doing?

• 56:34Speaker 01

  Hi, I'm great. Thank you. How are you?

• 56:36Jason Calacanis?

  Nice to see you again. You were from the Launch Accelerator 35th Class, if I'm remembering correctly?

• 56:44Speaker 01

  34.

• 56:44Jason Calacanis?

  34. Okay, so I'm not remembering correctly, but I was close. I was in the ballpark. And we had the chance to partner with you on your new company. Maybe you could tell us a little bit about what you're building and why it's important?

• 56:59Speaker 01

  Yeah, happy to. So, Tenax AI protects homes and their insurability from extreme weather. So I'm talking about things like flood, wildfire, storms. And essentially, what we have built is software that uses computer vision and AI to assess risk at the individual property level, so at a home level. And what that does is it gives insurers a granular view that helps them understand the true risk of that property, which enables them to underwrite and insure that property more accurately. And what it also does is it enables the homeowner, so the people who live there, to understand their exposure to risk and to take actions that could actually reduce that risk as well.

• 57:42Jason Calacanis?

  So AI is the better way to do this? How is it currently done? And why is AI a better solution? And maybe you can show us because you had some really interesting demos in your deck. And when you, I remember when you presented to Sequoia, I was there and they were fascinated by your approach.

• 58:01Speaker 01

  Yeah, absolutely. So to date, what has been done is insurers would normally make a regional sweeping decision based on regional models about the exposure of a property. So they might say this entire zip code or neighborhood is this general level of exposure. And then they use that to inform how exposed that home is to a particular peril such as wildfire, or flood, or hail, or winds. Now there's the introduction of some manual inspections where a person, a professional, would be booked and organized and they would go to the property on behalf of the insurer and they would do an inspection that could take a couple hours.

• 58:43Speaker 01

  They got to write up a report, ingest all of their written and verbal notes to put together a report to explain that exposure and then hand it over to the insurer who then has to ingest it into their underwriting process. What we do is about 80% more efficient than that process because we have built, as I mentioned, AI and computer vision models that essentially enable images which can be collected in up to 30 minutes max on a mobile phone. So we can just take their cell phone, walk around the property with our app. Very, very simply, you need zero expertise whatsoever. The average homeowner can do it. And we can upload those images and run it through our proprietary models to be able to diagnose the exposure of that property.

• 59:28Speaker 01

  The other thing we're doing that is quite unique is we are now starting to send drones to properties as well. And this is really important because in some cases insurers would actually prefer that the homeowner not be the one collecting the data. It just offers another level of verifiability.

• 59:46Jason Calacanis?

  Sure, yeah. We've, as we've seen, homeowners can value their homes and maybe get into shenanigans on the margins. And you know, this is very interesting to me, this company specifically, Alex, because when we had the tragedy in the Pacific Palisades. You know, I'm just playing a quick video here on YouTube without the sound. I'm assuming you two can see it, yeah? Yes. So, this home was made to be fire resistant. It has a number of features and if I were to zoom in on this for a second, let me pause it there, perfect. Now, when you look at this home, what you'll notice is it doesn't have overhangs of the roof.

• 1:00:30Jason Calacanis?

  You'll also notice it's fire retardant material everywhere. And around the home is a giant stone fence with landscaping with a lot of gravel and metal and not a bunch of trees around the home. You can build homes today that in a wildfire would be resistant to them, but this home, Elise, would have been bundled with all homes in Pacific Palisades, correct?

• 1:01:01Speaker 01

  Spot on, and that's because of the way that risk has been being calculated by insurers, as I said, in these sweeping regional models. And so what happens is even if your home was lower risk, so in that case, that home's insurance actually is probably higher because they're technically compensating or paying for their neighbors' regional risk, right?

• 1:01:21Jason Calacanis?

  Now, Elise, if I understand, this is not because the insurance companies are lazy, but because there's actually a regulatory barrier they can't cross or couldn't cross until recently?

• 1:01:30Speaker 01

  Yeah, there's a couple crazy forces at work which are kind of unexpected. And so one of them is actually in California, until about a month ago, insurers literally did not have regulatory-approved catastrophe models that they were allowed to use that were forward-looking, that enabled them to calculate the exposure to true and up-to-date wildfire risk, which is bananas. You would think that that would be very obvious, but it hasn't been the case. And so as a result, of course, they would be pulling out. They literally haven't been able to measure risk accurately. And so there are now three catastrophe models that have just been approved in the last about four weeks, Varesque and Moody's among them.

• 1:02:18Speaker 01

  And what is really cool about these, if you are nerd like me and get into the weeds and looking at these models, is that they have placeholders within them where you can insert data about specific secondary factors related to the home. So we're talking about characteristics like what material is the fence made of? Is it combustible? And does it link up to a large patch of vegetation? Because you may think you have defensible space around your home, but say you have a wooden fence and it connects, you literally have a wick to a combustible source. Or what type of windows do you have? Are your vents covered with the right mesh? And what's really cool and what we factor in mathematically to our algorithm, so we can actually tell a homeowner, tell insurance, tell a community

• 1:03:01Speaker 01

  how exposed they are, is we have risk factors with each of those characteristics of a home. So if you have the right type of roof, you're reducing your risk by six times. If you have the right porch material, you could be reducing it by three times. If you have vents that are covered by the right size mesh, so embers can't fly in, you could be reducing it by 1.5 times. And it goes on and on. And a lot of these things are not things that people think about every day. And so that's what we're able to offer people really simply.

• 1:03:28Speaker 02

  This goes to the question that I really have for you, which is who is the customer here? Because I can imagine the insurance company being the customer, or it might be the individual who wants to get a better rate, so they might pay for what you guys put on. So who do you sell to in the market?

• 1:03:39Speaker 01

  Yeah. So insurance carriers are our ICP. So those insurers who have exposure to perils like flood, wind, hail, storm, wildfire, which increasingly is kind of everywhere, as we all know, if anyone picks up the news. The homeowners themselves are the users. And so they would be prompted by their insurance provider, either if they are at a point where they're looking for a new coverage. So if an insurer is deciding how to price the risk and they need this kind of data, so that a homeowner could actually get rewarded with discounts, which is now there's new regulation that helps enforce that in California, for example. And then they would be able to access that software, basically, through their insurer.

• 1:04:24Jason Calacanis?

  Yeah, this is, I am obsessed with this. And because we had a, we had an investment, it didn't work out in a company called Blockable. They were making prefab homes. Now, you might think, oh, prefab home, oh, that's just going to burn up. No, au contraire, mon frère. What they were doing was the gaps in these homes and the materials that you can build in a factory as opposed to onsite, because cutting certain types of materials is, cutting certain types of materials is impossible in the field, Alex. And so, Dwell did an interesting series on this. Especially in Australia, this is a big deal because of the wildfires in Australia are,

• 1:05:07Jason Calacanis?

  I think they make some of the wildfires we have look like, you know, campfires. Not to make light of anything here, but as you can see here, this is a fire resistant structure. This is a Dwell story, great magazine, dwell.com. And you can see they're using steel for the roof, etc. But at least the gaps is a key, because if there are tiny, even the tiniest of gaps, the air gets sucked in. You have all kinds of suction kind of situations that happen with heat that you've all experienced when you open an oven, etc. And what that does is suck embers into the home, or it sucks embers into, you know, a pile of leaves in the gutter. All this kind of stuff contributes.

• 1:05:50Jason Calacanis?

  And they have been working on this specifically to do fire resistant timber. Here's an example of a timber that has fire resistance. And then other folks are making what some people might consider ugly, you know, made out of iron, but you don't have to go that far. And then, as you see here, the distance of the trees to the home, also critical. So it is completely possible that if you clear the brush around your home, the chances of it burning down go way up. If you look at flood resistance home, that was another thing that happened in the wake of Katrina. And Breezy Point, where I used to summer as a kid in Brooklyn and the Rockaways, they started building homes that are four feet above the water, yes, Elise? And have these really interesting panels on the side of them.

• 1:06:35Jason Calacanis?

  My brother was a firefighter, my grandfather as well. And what these panels do is when the water comes rushing in, you know, so you don't see under the house, but when the water comes rushing in, it just blows the panels out. The pressure from the water just blows them out. And then you just have, you know, whatever you have in your basement is like, you know, you keep surfboards there or whatever things, you know, you're not putting a full-on, you know, theater in your basement. These panels blow out, allowing the water to flow through. So aesthetically, it doesn't look like you're living on stilts, but essentially you are because the panels just are made to break away. So flooding is the other big, high-order bit here, Elise, I guess?

• 1:07:13Speaker 01

  Yes, flooding is going to be second for us. And I think you're touching on something, Jason, that's really important. And we hear this so often, we talk to homeowners who say, "Well, what can I really do? I live in an area that, you know, I'm told is prone to, in this case wildfires." The reality is there are so many things that people can do, but they don't know. And it's not only a roof, you know, and then people, you know, say it might be the roof. They're like, "Well, that's so expensive." Well, the reality is the numbers have been run and we know without a shot of a doubt that at the very minimum, $1 invested in the right retrofits or controls on a property saves at least at a minimum six in recovery cost, right? And then if you can do these types of retrofits and then get insurance as well, so you're

• 1:07:58Speaker 01

  insurable and you're not having to pay for, you know, an insurer of last resort that is insanely expensive, well, then you're in a really good position. And so we're trying to give people advice on those things that they can do to help maintain their insurability.

• 1:08:10Speaker 02

  Elise, I have a kind of annoying question here, but if we make it so that people who are very proactive about hardening their house from either fire or flooding or whatever, can be insured on a one, a single house basis? And is that going to leave a lot of homeowners who may not be able to harden their homes out in the cold, essentially? Because they'll become uninsurable because the risk pool will be narrowed from a neighborhood size to an individual home? What's the other side of the good news that we can have more information, I guess?

• 1:08:40Speaker 01

  Yeah, okay, so there's a few aspects of that. One is actually something that we are seeing is interest from communities themselves. Like so from HOA's, uh, local and regional governments who actually want to take a community-wide approach to risk reduction. And so the idea here is that, you know, when you can harden multiple homes in a neighborhood, you can actually improve the survivability of the entire neighborhood. And we also see from a behavioral lens, when one person in a neighborhood starts to take action, it does spread. I was gonna say like wildfire, it's a wrong pun, um, but it does. There is a contagion, you know, in a certain aspect of.

• 1:09:21Speaker 02

  These are terrible, terrible analogies.

• 1:09:24Jason Calacanis?

  Terrible analogies.

• 1:09:25Speaker 02

  It spreads like a smile.

• 1:09:26Jason Calacanis?

  I could have used, that would have been even worse, Alex. But in some ways, those homes at least become a firewall. And there would be an argument in my mind, Alex, to, um, even make the disparity between the safe homes and the unsafe ones even greater.

• 1:09:45Speaker 02

  To incentivize.

• 1:09:46Jason Calacanis?

  To incentivize it because if, let's say, we lived in a, you know, a thousand home plant, you know, planned community, that entire community could save the three communities next to it. When the embers start flying, they, they just are natural blockage. And you might look at it in a community and, you know, the, um, the, the floral arrangements and the, and the, and the parks and everything, uh, and the structures that are not homes, you know, those are kind of a tragedy of the commons, like who's gonna change those? But you could say, you know what? These trees are no bueno. There, there are some trees in California that are literally like, I mean, you, you, you could put Duraflame logs around your house and it would be more fire resistant than some of these, like the, are they the palm fronds?

• 1:10:31Jason Calacanis?

  That, what are the things that fall off of the palm trees? These giant things, I don't know what they're called.

• 1:10:37Speaker 01

  Yeah.

• 1:10:38Jason Calacanis?

  Palm somethings, anyway.

• 1:10:39Speaker 01

  And those light up like tinder, tinder, yeah.

• 1:10:41Jason Calacanis?

  Oh my God. And then they break off and they fly like a, like a, literally like a missile and land on somebody's roof. And then that person's got, you know, a shake roof and okay, game on now, so.

• 1:10:54Speaker 01

  Yeah.

• 1:10:55Jason Calacanis?

  So we're here for a little office hours. How's the company going? Is there anything we can help with?

• 1:11:01Speaker 01

  I love that question. Thank you. Yeah, things are going well. We're working with a handful of insurers that are helping feed into our product development, which is very exciting. My question for, well, there's a couple of things. One is actually an offer that I'm going to make, which is for any insurers, brokers, and even homeowners who might be listening to this, who are really interested in figuring out how to protect their home and understand their risk. We're currently working with some partners in California. And essentially, if there are people who would like to get an early version, a test of their property, contact me at [email protected]. That's at T-N-A-X-A-I dot com.

• 1:11:46Speaker 01

  And I'd be happy to put you in the queue for some of that.

• 1:11:49Jason Calacanis?

  Great. So we need some vanguard here. We need some early adopters who want to get early access. So great, let's get some of those going.

• 1:11:57Speaker 01

  And then the question I would put, this is something I'm loving brainstorming around right now, are different ways to hack sales cycles in really regulated industries that are slow moving, right? So in that B to B space. I love talking about this and I'd love, I don't think you and I have talked about it. I would love to hear your thoughts on that.

• 1:12:17Jason Calacanis?

  You know, it's a tough one. You know, whenever you go into education, let's say, or you go into housing, as you are, healthcare, these are some of the giant castles that are hard to scale. We've got moats around them, they've got drawbrows, they've got alligators in there, got arrow slits. It's not fun to scale those. One thing I've seen is companies like brilliant.org, and Alex will pull it up. You know, they thought, hey, we can help educators, right? Teach kids math more efficiently, et cetera. But I think one of the lessons Sue learned over there very early was

• 1:12:56Jason Calacanis?

  We can actually sell into the top parents and have those parents, you know, use these tools to make their kids superhuman, to use a term in another startup that we're investors in. And then those people bring it to their schools. Or it becomes, you know, oh, the kids who are doing really good in the class are using brilliant.org and their STEM stuff. And then they say, hey, can we get this for our school? And so I wonder if you find high-end homeowners where you can consult with them or build some product or service that helps them navigate lowering their insurance and

• 1:13:40Jason Calacanis?

  also just lowering their risk and advising them. So if there was an audit of my home and you told me for $500, $1,000, $2,000, $5,000, you know, I have some expensive homes that cost a lot of money. And somebody said, hey, we can audit your home for $500 and give you recommendations right now of how to lower your insurance, or we can go call your insurance company and tell them you've done these things and whatever we lower your insurance by, we'll take half of the gain. You know, there could be something there. Now, I don't know enough about the insurance business and lowering insurance based on

• 1:14:19Jason Calacanis?

  these remediations, but that could create a way for you to integrate yourself into the industry to just raise awareness. And I think I spoke to you a little bit about you're so passionate and you're so great at communicating this and you have that just natural enthusiasm, a YouTube channel just about this issue, where you have homeowners, you have builders, you have the person who makes the roofs, you have the person who is a contractor who you met in Santa Rosa, you know, up by Napa where they've had some terrible fires and does this kind of retrofitting and just short videos, even TikToks, hey, my name is Elise, I'm from 10x AI. We help fortify your home from floods and fire and

• 1:15:02Jason Calacanis?

  lower your insurance. Today on the program, I'm going to show you this tip, or here's a tip for, you know, stopping wildfires and dealing with floods. Those kind of things could just make you, you know, the queen of this topic. And that would naturally start you off on second or third base with partners. I know this because people, when I had This Week in Startups and I started my angel syndicate on Angel List and then moved it to the Syndicate.com, were like, "Oh yeah, I watched This Week in Startups. I'd love to be part of your syndicate." Or, "I saw 10x AI. Are you going to syndicate that company?" So, we inserted ourselves into the discussion and then we became the host of the discussion. We became the place where the discussion about startups

• 1:15:47Jason Calacanis?

  was happening. The discussion about angel investing was happening, which is why I wrote the book on angel investing, literally called angel, you know, now in 12 languages. And so, I had that calling card that just made, you know, any meeting request happen very quickly. And now with All In, it kind of moved over into pop culture. So, when I go to another city now and I want to talk to people about bringing Founder University to their region, or, you know, I want to record an episode of This Week in Startups with a founder. We just had a founder on the pod from Neuro and he was referencing Alex and I's conversation from previous episodes about self-driving. And so, that means their

• 1:16:30Jason Calacanis?

  chance of coming on the pod goes up, the chance of me investing in the company goes up. You get the idea. All right. Everybody go to 10xai.com, T-E-N-A-X-A-I, T-E-N-A-X-A-I dot com. And if you are a homeowner, or in your insurance, and you want to help a founder out just with some conversations and maybe some tips and advice, [email protected], E-L-Y-S-E, at. Great job. Thank you for letting us invest in your company and we will see you all next time on This Week in Startups.