Stop ghosting your friends with Nox's RPLY, plus Alloy Automation and a Shopify flashback | E2209

👉 Register here to join Founder University Japan's kickoff: https://luma.com/cm0x90mk Today's show: Nox's new app RPLY reminds you to text your friends back, getting you to iMessage inbox zero. On today's TWiST, we've got Molly Cantillon of Nox, telling us how she plans to make lackadaisical texters (like our co-host Alex) more effective, even if it means breaking into Apple's walled garden. Hear about how RPLY maps your relationships so that it can understand your messages contextually, and help you stay organized. Then, Gregg Mojica of Alloy Automation swings by the show to dispel some common myths about AI agents. For the most part, these little machine learning helps aren't truly autonomous… Hear how Alloy's agents decide when it's time to bring in a human for help. PLUS is AI in a "lull" right now? Hear why Gregg thinks there's still a LOT of room for these apps to improve. Finally, it's another TWiST Flashback. We're jumping back to 2013 for an eye-opening chat between Jason and Shopify founder/CEO Tobi Lutke. Hear some fascinatingly prescient takes on the rise of SaaS, how early Shopify differentiated itself from other ecommerce and website building solutions, AND why Tobi dreamed of making Ottawa a true tech hub. Timestamps: (02:57) Molly Cantillon of Nox is trying to help you get better at texting (04:01) How RPLY gets even chaotic texters like Alex more organized (05:10) The complexities of entering into Apple's "walled garden" (07:20) Keeping RPLY safe, in case you're using it for work!(09:24) Miro - Help your teams get great done with Miro. Check out miro.com to find out how! (11:59) How RPLY uses relationship mapping to understand and prioritize your messages(19:23) Perspective AI - Real insights, straight from your customers, and your first two months are on us. Just go to getperspective.ai/twist. (21:08) Why Nox wants its AI to become "the Invisible OS."(29:30) Pilot - Visit https://www.pilot.com/twist and get $1,200 off your first year. (30:40) We've got Gregg Mojica of AI agent makers Alloy Automation (31:42) How the rise of AI agents changed the core of Gregg's business (34:03) Why most AI agents still aren't truly autonomous (35:00) How Alloy's agents decide when to bring in a human for help (37:02) Why the rapid acceleration of AI development has made some enterprises pump the brakes (39:00) Is AI in a "lull" right now? Why Gregg thinks there's still room to improve. (40:31) How close are we to AI apps going truly mainstream? (43:41) Why Alloy Automation didn't raise a massive round like so many of its AI peers? (Or are they?!) (46:48) The difficulty of hiring in today's AI landscape (50:21) In today's TWiST Flashback, we're revisiting Tobi Lutke of Shopify's appearance from way back in 2013! (52:11) Why Shopify switched from selling snowboards to storefronts (59:37) Turning Ottawa into a tech hub, and the "secondary market" theory (1:05:32)The constant tension between growing your global footprint and expanding your features (1:08:52)Who were Shopify's actual rivals?

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

• 0:00Speaker 00

  I have more than 800 unread iMessages on my phone.

• 0:03Speaker 01

  Eight hundred is maybe even the lower end of some of the inboxes that we've had to deal with.

• 0:08Speaker 00

  We worked with two services today, iMessage and WhatsApp. I'm curious about the privacy element of.

• 0:12Speaker 01

  What you want to do is not send your messages or at least have them anonymized and never personally identifiable if they're ever going to be sent to a cloud server.

• 0:22Speaker 00

  When I saw you guys built this, my first thought was, hell yes. And my second thought was, will my friends yell at me for using it?

• 0:27Speaker 01

  AI reply generations sound like you.

• 0:29Speaker 00

  I feel like we're like a year or two away though from having enough RAM in every single new Mac computer that we're going to be able to run local models without it being a question.

• 0:37Speaker 01

  People are not as excited as I think they should be about local models. And the reason why I'm excited is because you can have 300 requests in a second if your computer is big and chad.

• 0:47Speaker 00

  And then you also talked about mapping relationships, kind of using people's text messages as a way to sort out who's in their life and when.

• 0:55Speaker 01

  What's interesting is if you take all of this hardcore statistic and you try to weave a story of the tapestry of your life over it.

• 1:04Speaker 00

  This Week in Startups is brought to you by Pilot. Focus on your product. Let Pilot handle your bookkeeping. Pilot provides the most reliable accounting, CFO, and tax services for startups. Head to pilot.com/twist and get $1,200 off your first year. Perspective AI. Surveys, they never capture what customers are really thinking. That's why we use Perspective AI. Real insights straight from your customers. And the first two months are on us. Just go to getperspective.ai/twist. And Miro. Help your teams get great done with Miro. Check out miro.com to find out how.

• 1:45Speaker 00

  Hey, everybody. Welcome back to This Week in Startups. This is Alex and we have an absolute banger of a show today. We have not one but two Twist 500 interviews and then at the end, we're going to rewind that clock all the way to 2013, when Jason sat down with the then much younger and much smaller company CEO Toby Lucky. Of course Shopify has grown tremendously since then, but it's really good fun to go back and look at where the company was and what we were asking Shopify. Shopify back in its relative infancy. All right. So Knox up first, great company. They're building kind of like superhuman, but not email instead for iMessage. It helps folks like myself who are chronically and constantly behind on text messages, stay up to date. And the company has a big vision for a future AI-driven invisible OS. You're going to want to know what that is.

• 2:30Speaker 00

  Then we're going to talk to Alloy Automation, a company that I've covered since its earliest funding rounds. It has matured though. It has gone from being a e-commerce automation platform with a no-code twist to instead today being something akin to the data and integration platform for building AI agents. Trust me, there is a through line there that we explore. Greg's great. I love both of these companies. So Knox, then Alloy, then Shopify. Let's go.

• 2:57Speaker 00

  I'm not very good at texting. I'm actually pretty bad at managing all my inboxes, Twitter DMs, and emails, and LinkedIn messages, and all that. But my SMS folder is always a mess. Happily though, there's a company called Knox. They built a service called Reply that just might save my bacon. So please join me in welcoming to the show. It's Molly Kontiyan, founder of Knox. Hey Molly, how you doing?

• 3:17Speaker 01

  Hey Alex, I'm good. How are you?

• 3:18Speaker 00

  I'm good. It turns out I have more than 800 unread iMessages on my phone, according to my just checking that. Am I like the target for what you're building? Cause I feel like I'm always behind on texts and I feel bad about it. And then I put it off because I feel bad about it. And then I feel worse and you know, it just goes on and on.

• 3:34Speaker 01

  Oh, absolutely. I think 800 is maybe even the lower end of some of the inboxes that we've had to deal with. It's been a really serious amount of people there, but it's a self-selecting thing, right? There's already this bias of people who come towards our solution and they find it and they have 10,000 unread messages. Or in my case, I just read the messages and I don't know how many I have to respond to, but I haven't yet.

• 3:56Speaker 00

  Oh, so you mark them as read, but don't respond. So you have an invisible number of people that are mad at you?

• 4:00Speaker 01

  Yeah, yeah.

• 4:01Speaker 00

  Let's talk about Reply. It's spelled R P L Y. And you guys call it kind of a unified messaging platform to help people survive their text message inbox. How does it work? And really, apart from us complete freaks, for whom is it for?

• 4:13Speaker 01

  So as you said, it's this place where there's one home for all of your messages. So it's iMessage, WhatsApp. We're working on the roadmap towards doing Slack, Discord, Telegram, email. And essentially, we've just embedded this concept of Inbox Zero into your text messages. And so the idea of you having to respond to a person, what it does is it filters on exclusively the conversations where you were the second to last person to reply, right? So I mean, you know, once a week, every Sunday, I would go through literally my text box, my, you know, iMessage and spam Control Tab and just spam that tab until I would see a gray bubble in the bottom left corner, which would mean I need to respond. And I realized, you know, there's, there's an easier way to do this.

• 4:58Speaker 01

  What if I could just have this, you know, one filter, this one query, where I could find all of the people that I haven't responded to, where I have an obligation to respond and just have one home for that. And so that's how it came to be. It's a desktop app because it's actually not distributed through Apple's App Store. It's a direct sort of DMG downloaded app, which is how most desktop files work.

• 5:21Speaker 00

  Can I ask about that? Is that because you couldn't release this through the App Store on iOS? Because I presume that there's privacy rules or Apple not wanting you to mess with iMessage.

• 5:32Speaker 01

  So a few weeks ago, we actually launched our reply for iOS app. And it is not right now on the App Store. We're on TestFlight, which is, you know, Apple's beta software. And the way that it works is you register on your computer and then we relay those messages to your phone. And so, yeah, it's, it's essentially what you're saying. If you tried to do this, Apple would block it. So you have to do it in a different, yeah, different engineered way.

• 5:55Speaker 00

  Do you think the Apple restrictions there are reasonable? Are they actually enforcing intelligent privacy protections for people? Or are they just walled gardening and rinsacking their way to the bank?

• 6:04Speaker 01

  You know what? I think it's the thing that differentiates them and is a large reason why people are buying iPhones.

• 6:11Speaker 00

  iMessage.

• 6:12Speaker 01

  Yeah, iMessage, not having a green bubble, having a blue bubble instead. And so it's completely within their gate to, to reserve this, right?

• 6:20Speaker 00

  Wow, that's the most positive thing I've heard about someone say about Apple in a really long time. Okay, but it does, it works with two services today, iMessage and WhatsApp, probably the two largest non-straight SMS platforms out there. What would it take to get traditional non-iMessage text messages in there too?

• 6:39Speaker 01

  Yeah, so you're talking about what Slack, Discord? Telegram or what types or SMS?

• 6:45Speaker 00

  Maybe this is me about to show my ignorance, but like iMessage is a form of SMS, but not all messages that I send via text message on my iPhone are iMessages. Like, for example, if I text someone with Android, so is all that brought in as well?

• 6:56Speaker 01

  It all works. Yeah, yeah, it's all in one.

• 6:57Speaker 00

  So it is all my text messaging. Okay.

• 6:59Speaker 01

  Exactly.

• 7:00Speaker 00

  I'm curious about the the privacy element of this because if you have got my Slack messages from work, I really don't care. They're coordination, they're boring, they're just talking about what we're working on. My my text messages, though, often include stuff from my friends that is not really mine to share. And so when I saw you guys built this, my first thought was, hell, yes. And my second thought was, will my friends yell at me for using it? So how do I keep my my friends and loved ones' information secure while using Reply?

• 7:24Speaker 01

  There's kind of two separate parts to this answer. The first one is obviously just the privacy policy that we have and the compliance we have. So we're working towards SOC 2 right now because a lot of people are using this, you know, just so happens to be for their work messages, for messages where they're coordinating things, you know, for their actual job. And a lot of their occupation sits inside of their text messaging inbox. But then the tech answer is kind of interesting because what you want to do is, you know, not send your messages or at least have them anonymized and, you know, never personally identifiable if they're ever going to be sent to a cloud server. And so the first thing that we, you know, completely make apparent is that no data is ever sent

• 8:08Speaker 01

  sort of personally identifiable from our servers to any other servers stored anywhere along that process.

• 8:15Speaker 00

  So you're the only place where these things go. So as long as you secure at rest encryption on your end and then in transit, we're pretty much good.

• 8:21Speaker 01

  Yes, so we have zero data retention policies with all of the cloud models. And we also support these local models. And so what that means is you could literally turn off your internet and you would be able to still have the AI reply generations sound like you, albeit, you know, it might turn your battery, you know, go lower and it might have more CPU usage and there might be some other performance issues. But all this would be possible without having to send things to any sort of server.

• 8:50Speaker 00

  What local models can I run, let's say on my MacBook Pro here to use in reply to handle the offline processing? Is it just stuff from Meta? Or have you guys opened the aperture to also, you know, models from Moonshot and so forth?

• 9:03Speaker 01

  So we're using Apple's MLX framework, which does open the ability to have a few different models and to support a few different ones. The best one we've found so far is the Llama, the 7B model. And so that's the one that we're supporting. It works best on obviously the later stage. So M3s, M4s, but also M1s and 2s it works on. It's just going to be slower.

• 9:24Jason Calacanis?

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• 10:07Jason Calacanis?

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• 10:30Speaker 00

  7B is the smaller of the Llama 4 model family. I forget how much bigger the other one is, but how, how much RAM do I need to actually run the 7B?

• 10:38Speaker 01

  I don't have the exact numbers, but it's a manageable amount. And if anything, we have a sort of disclaimer at the top when you don't have enough RAM to be able to support local models. And then we just let you know, hey, this won't work right now.

• 10:49Speaker 00

  I feel like we're like a year or two away, though, from having enough RAM in every single new Mac computer that we're going to be able to run local models without it being a question. It's weird that we're not quite there yet. Brand isn't that expensive.

• 11:01Speaker 01

  The great thing about local models that we all forget, and I had this tweet that, I don't know, I just, I was expressing this frustration because obviously, local models are, you know, not at the place right now where they're widely adopted and even widely discussed or talked about. There's not really just, I guess, potential, um, people are not as excited as I think they should be about local models. And the reason why I'm excited is because people forget they are fast.

• 11:27Speaker 00

  Yep.

• 11:28Speaker 01

  They work without internet.

• 11:29Speaker 00

  Yep.

• 11:29Speaker 01

  And above all, they're free. Like, you can, if you have a strong enough, you know, hardware machine, you can spam as many models as, as many requests as you'd like. So you can have 300 requests in a second if your computer is big and chad.

• 11:43Speaker 00

  So you can run this locally. You have a good privacy setup. That seems to be good. Working towards doctor compliance makes a lot of sense for me. Um, you also have a feature inside of replied that lets you kind of search through all of your messages, which I thought was quite smart because search on iOS is kind of garbage. Uh, and then you also talked about mapping relationships, kind of using people's text messages as a way to, uh, sort out who's in their life and, and when. Tell me about that and why that's an important feature.

• 12:09Speaker 01

  It's really interesting because the app started with just this one SQL query, which was, hey, here are the people that you have to respond to, and you should respond to these people. And here's the draft I've created for you. And then we realized, oh, wait, we're sitting on this treasure trove of information. And there's so much context here about just understanding the relationships you have. You know, the people that motivate you, the people that serve different purposes, the people that are work-related, that are personal-related, that are maybe even service-related, like my cleaner and, you know, different people. And what's interesting is if you take all of this hardcore statistic and you try to weave a story of the tapestry of your life over it. So, you know, in 2020, you were really close to, um, Sam.

• 12:56Speaker 01

  And then in 2024, that relationship plateaued. Um, then in 2025, you got super close to Lola. Um, that's cool. And so the last page of our onboarding, we have this really, I, I would say, hard-hitting and then sort of just world-bending, um, Delineation of who you are through your messages. So it's a closeness graph of the top 10 contacts that you have all time, your messages. And then a graph of how up you're going and sort of how down, you know, certain months or certain periods of time. So you see during COVID, you got your best friends, you see your family, maybe your sisters. You had some valleys and peaks with. And I think the coolest part about having all of this, as well as the ability to run LLM requests,

• 13:41Speaker 01

  is that you can annotate your life. And so obviously, you know, 2021, I moved to Stanford and it says, oh, this was the big move to California. Uh, your friends became, you know, closer in this way and you guys started talking about this. And then this was when you had this huge internship.

• 13:56Speaker 00

  How does it know that I moved or you moved to California? Does it know that just because you started talking about Stanford quite a lot? Or is there any geographic information attached to the messages that you can pick up on?

• 14:05Speaker 01

  There is no geographic information, unfortunately, but it's all just predicated on the relationships that you have and what you're texting those people. So.

• 14:13Speaker 00

  And that's enough to put, to put me into a geographic place. Interesting.

• 14:16Speaker 01

  I mean, a lot of it is, hey, you know, uh, we'll go to the ice cream shop or we'll do this thing that has no geographic context. But when there is geographic context, we have the prompts to, you know, make sure we pick up on that as those are big life changes. Um, and we look for other things like graduation events and, you know, job changes and moves and things like this.

• 14:35Speaker 00

  Wouldn't this, this graph you're describing also provide like a look at how long your personal romantic relationships lasted? And when they.

• 14:42Speaker 01

  Oh, yeah.

• 14:42Speaker 00

  And I don't know if I want this in, in a way, like I've, I've been on iMessage for a long time. And, you know, across different states, different stages of my life, education, careers, relationships, before I got married. Like I, I don't know how far back I want to go. Can I like time bound this? Like, just give me like the last six months. I don't, I don't want to go, I don't want to go too far back here.

• 15:01Speaker 01

  You can skip the slide in, in onboarding that will tell you, uh, this thing that we call EB, which is people that are, uh, just not as close in your life that used to be close. And yeah, a lot of people have somewhat somber experience going through and seeing the people that they sort of lost, um, either symbolically or like literally as, as, you know, partners. And you could just skip ahead and not look at this slide, not take it too seriously. But it is, yeah, it's sort of a part of the.

• 15:27Speaker 00

  This is when I think applying intelligence to our personal lives gets unsettling in a way. And I don't mean to bring up like Black Mirror too much, but like. There are certain things that I just don't mind that have faded, you know, that I've kind of let go of. But I think as we have increasingly digital lives and better search tools and better surfacing tools, we're going to look back more. And I think that's going to be a pretty interesting cultural motif. Okay, clearly the reply is not aimed at people who want to go back and see when they stopped texting their third ago partner. You're charging 30 bucks a month for it for the paid plan. So I presume this is currently aimed at your busy executive, your parents who have seven children that I have to keep track of, people that are just high volume by nature.

• 16:08Speaker 01

  What's interesting is, you know, like a lot of people who are using it are simply people like me and you who are in group chats all the time where they're getting intro to someone. And imagine being the person in the group chat who doesn't respond. Right? So it's, I'm so excited to introduce Molly to Sam. And Sam responds, hey, Mal, I'm so excited to hear amazing things about you. And then me, just because I have this fog in my brain, haven't responded. And then two weeks later, I'm like, oh, my God, this was crazy. And so we're solving that problem, which is just making sure that you're on top of your messages, even from a scheduling standpoint and just from a, just, you know, managing relationship standpoint. And yeah, there's a lot of customer service and there's a lot of sales enablement. There's recruiting, there's consultants, there's freelance people.

• 16:53Speaker 01

  So it's people who live in their inboxes and are texting hundreds of people a day.

• 16:58Speaker 00

  30 bucks a month is an interesting price point. It's a bit higher than most things that I see, not in a bad sense, but I'm kind of curious if there is a lot of processing costs in the background that are leading to this costing as much as it does. Are you essentially covering COGS there? Or are you just charging that much because people are willing to pay for it? So huzzah, great margins.

• 17:15Speaker 01

  It's probably both. It does require quite a bit of compute, especially so if there's a toggle of how long you want to go back. If you go back to the past month or the past six months, there may be hundreds, maybe even thousands of people of threads that you've left unread. And then we're sending all of these requests in parallel. And so that's thousands of requests, you know, in a second, which gets quite expensive. But it's also, I think, just a comparison benchmark. Superhuman who does a great job of this on email. We're sort of, you know, mimicking inbox zero concept from, and they charge the exact same.

• 17:49Speaker 00

  I mean, Superhuman's done quite well. Just sold itself into the Grammarly confab that now has Coda, Grammarly and Superhuman. We've talked to Shere, the CEO. We're gonna put the episode number right here, so you can go find that interview if you want. It was a lot of fun. One more thing before we talk about the future. In February, you told TechCrunch you had about 1,000 paid users. We're now a couple quarters later. How's the company doing?

• 18:10Speaker 01

  Yeah, it's been good. So we had a sort of smaller launch in February where we announced, hey, we're here. We're doing this really exciting thing, sort of nine to five Mac and a lot of Apple enthusiasts picked up on it. And then, yeah, we launched another thing three weeks ago, which was the iOS app, and then announcing that we're supporting WhatsApp and aim to support a few more. And it's just been explosive since then. I think people really like the idea of having everything all in one place where you can see and you can take longitudinal context, right? So I responded to Maria about the Wi-Fi password, and I should take that to the conversation I have with Masha when she asked me about the Wi-Fi password. And so there's just a lot of

• 18:50Speaker 01

  really interesting overlap, dynamic wise, that is going on here. And yeah, we always, I'm a big fan of these launch videos, so that was a ton of fun and just got a bunch of interest.

• 19:01Speaker 00

  How was growth been on the either free or paid user side?

• 19:04Speaker 01

  What's nice is that every time we have one of these big launches, we have, like, my audience is like quite power user heavy, so we have a few thousand people who go and spike. I think that day, we had maybe just short of 10,000 people go and at least download it, try it, check it out. In terms of conversions, I don't have the exact number.

• 19:23Jason Calacanis?

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• 20:08Jason Calacanis?

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• 20:25Speaker 00

  Thousands of paying users now?

• 20:27Speaker 01

  Yeah, yeah, yeah. So what's sort of the most spectacular thing about this product is not not actually the growth number because it's we're not really looking to be this super consumerist, massive adopted thing. I think it's for the loyalist power user that is using it every day. What are their attention numbers? And those numbers are phenomenal because every single person who struggles with this problem comes to this and they're like, this is my holy grail. Like this saves my life. Where have you been? And so that's been something that we take a lot of pride in.

• 20:56Speaker 00

  Again, when I was prepping for this, I was like, oh, this is designed just for me. And it's rare that our product feels so directly tuned in to exactly what I need, frankly. All right now, while all this is cool and replies lovely product, I'm glad it's doing well. You guys have some longer term plans. You actually put out a white paper of sorts entitled the invisible OS and you said that the Trojan horse is building the iMessage assistant that texts like you. I feel like you guys have built that and you've taken it to market and you've shown that you can monetize it very effectively. You also say that you believe in the world or A doesn't replace you, it helps you show up. The next wave of a software will be proactive, yet invisible, seamlessly layering into the tools you already know and love, becoming the unconscious default. Tell me more about the future we're working our way towards because it sounds pretty fluid in a

• 21:41Speaker 00

  really nice way, but I'm curious what that really kind of means.

• 21:43Speaker 01

  I think starting with text messages is so interesting because there is this uniquely deep

• 21:51Speaker 01

  Rich, unfiltered, sort of stream of information about a user that you wouldn't get anywhere else that determine what their intentions are. Uh, you know, just the manner in which they're responding to people, the frequency in which they're responding. Um, it's really good, at least even a base level, like here's what my product does. It's almost one of these mini apps, right? Like one of these wrappers, almost like um a Cal AI would be, or um a, I don't know, there's a bunch of these like random. AI apps that that sort of prints because this is a universal problem and very easily understood. And so that has always been the goal. Like, we have to start somewhere where people download the app. They think it's a phenomenal experience. They find real utility in it. And it doesn't even matter if it's an AI company that's building it or their neighbor, like it's it's providing use to them.

• 22:35Speaker 01

  Um, but I think I've always been really interested in how we can add proactive. Personal intelligence into large language models and how we can create this experience that actually 10x is our lives. That we live on and we depend on every single day. Um, we started uh the company really looking at the voice assistant space. And building things on iOS and thinking, oh, well, if we aggregate all these different streams of context, right? Your emails, your calendar events, your random visits, your random photos, the places that you go. Like all of these intricate little details into one place, then we can create a legible stream of insight.

• 23:15Speaker 01

  Okay, I should help Molly find, you know, an Uber to the next destination she has, or I should help her create some. You know, dossier doc for the next conversations she's going to have and whatever it is. Um, and through that process, we realized that I think building on iOS is a lot more associated with entertainment. And building on Mac is where real utility or value where where sort of people live and create things. Um, and so I've always been more interested in building the utility thing. And I think once I had reply out in the hands of people. Um, I don't know if you've used it, but or seen videos of it, but we do quite interesting things behind the hood. Um, just inside of the iMessage app, right? So we layer a little logo um in the text field.

• 23:59Speaker 01

  Always accessible in every single conversation, so that if you click on it. It starts magically streaming and typing in a response where you can just send. If you don't like it, you delete it, you press it again, it streams another one. And then similarly, if there's a calendar invite, if there's a mention of, hey, me and you are planning something, it's going to be at this restaurant at, you know, noon. There's actually a pop up and it says, hey, do you want me to add it to your calendar? And you can send the ICS file to both parties right then and there by just clicking on that once. And so this idea of just in time help of implicit help of, I don't even have to trigger anything. But it just watching my screen at the same time that I'm doing things and I'm learning and I'm going through my routine and my workflows.

• 24:43Speaker 01

  It should understand how do I format the calendar event?

• 24:45Speaker 00

  Yeah.

• 24:46Speaker 01

  How do I like to send it? Right? All of these things are implicit decisions. And so that's where this idea of invisible OS came from.

• 24:53Speaker 00

  So I feel there's three ways to go about building an AI first OS. You can take, let's say, Windows 11 and just jam AI into it till it bursts. You could delete Windows and start from the ground up or Mac OS, pick your OS, and build something that was AI native. Or you could, as a different company, build the invisible intelligence layer on top of Mac OS and Windows and so forth. And I feel like you're going for option three. I've been thinking a lot about this because it seems very silly to me that my personal chat GPT instance, GPT 5.1 now, knows me, but only exists in this little box and can't touch anything else. It's so siloed, it's almost lobotomized in a way.

• 25:33Speaker 01

  Yeah.

• 25:34Speaker 00

  But I feel like you're describing a much more personally integrated intelligence layer that I take with me that knows me and probably plugs into a whole bunch of things. So you know how we have model context protocol from Anthropic?

• 25:47Speaker 01

  Yeah, of course.

• 25:47Speaker 00

  I feel like you're building like the, the personal context protocol. PCP is not a great acronym. So if you have all this context, are you going to allow other companies to kind of tap into what you've collected about individual people? Or do you see yourself always being the company that uses that information in a product context?

• 26:02Speaker 01

  The thing about building an AI company is that you could kind of make a decision about whether you want to be the infra company, whether you want to be the model layer, the data company, the, the training company, or you want to be the application layer company. At the end of the day, all of them converge and you kind of do everything, right? Like cursor and maybe cognition, wind surf or like meat in the middle.

• 26:20Speaker 00

  Making their own models and now they're powering their own stuff and cutting their cogs and so forth. Yeah.

• 26:24Speaker 01

  Exactly. Yeah. But I think with the background that we have and what we've already launched, it makes sense to start with the application. It also is something that you can be incredibly tasteful and opinionated about. And that's something that has always been, you know, top of mind. Like, how can we create the implicit assumption? And I talk a lot about this actually in the memo, that us as humans, a lot of the times are not asking for choices, right? AI gives us, hey, which response is the best? Or, hey, do you like this one? Do you want a negative one? Do you want one in the middle? It's like, no, there's one right answer here. And whether I accept or reject the suggestion should just qualify and give you the right momentum to tell you, you know, whether the further suggestion should be accepted or not.

• 27:07Speaker 01

  And so that's where I've been thinking about.

• 27:10Speaker 00

  One last thing before I let you go. We're going to allow AI to increasingly intermediate human relationships. If it's just nudging us to respond to something, if it's helping us draft a message. People use AI to write cards and letters and all sorts of things. And we're really kind of allowing AI to sit in between us as humans. Do you have any qualms about that? I'm not asking because I'm trying to set you up here. I'm legitimately not sure how I feel about it. So I'm just curious how you think about AI taking kind of a third wheel in human relationships.

• 27:40Speaker 01

  It's really interesting. I think with emails it already has. So I am an extreme anti-email person, if it isn't clear from me just building an iMessage app. Like, I hate to be an email. I don't email anyone. And it's because of these formalities. It's like, this is so unnecessary. I'm texting best regards and I have to say, you know, hey, dear this person, or hey, how are you? Hope all is well, right? These things that you're just wasting your breath on. And I like the idea of having a extremely curt, straight to the point, this is what I want to say and just help me get. Get there one step closer. And that's what Reply is supposed to be is just come up with exactly the line that you think I would say in the manner and the voice that I would say it in. And I can edit it. I can say where it's wrong, but really, I'm just there to press approve

• 28:25Speaker 01

  or send, interpret the message. And that's, and that's pretty much all. In my sci fi optimistic mind, I think it's a really great thing, because now, you know, this dumb bars number, which is this metric, like you can only have 150 friends in your, or 150 people that you know, and maintain relationships with. I actually do think, since building Reply, I've been having double, triple, you know, just maintaining the same bar, but with more and more people, which has been phenomenal, because now all of the laggard, the logistical, the, you know, brain fog is in, is intermediated by the AI. And I get to do all the interesting work, which is, okay, what are the conversations in which I need to focus, right? What are the ones in which I actually have to get back to this person in a meaningful way? And then just, you know, write those myself.

• 29:10Speaker 00

  I'm excited about your future. And as a sci fi optimist myself, huzzah, Godspeed. And when you hit, I don't know, 10,000 paid users or something, come back on the show and tell me about it. I'm really curious about what you guys are gonna build next. For folks who want to learn more, it's heynox.com and Reply is spelled R P L Y. And Molly is also over on Twitter. Molly, a treat. Thank you very much.

• 29:29Speaker 01

  Thank you for having me.

• 29:30Jason Calacanis?

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• 30:42Speaker 00

  Alloy Automation, a company that I've known about since October of 2019 when they launched on Product Hunt. I had the pleasure of talking to the founders a couple of times as they raised a seed round and an even larger $20 million round. But now down the road, the company has evolved and I want to learn more about what they are doing. I love these founders. I have loved their space. And now we're going to catch up and figure out what they've been working on for the last couple of years. So please join me welcoming to the show. It's Greg Mohica, CEO and co-founder. Greg, how you doing?

• 31:08Speaker 03

  Great to be here. Thanks for having me.

• 31:09Speaker 00

  I feel like I'm just going to keep getting new jobs every couple of years in the podcast game and I'll just keep bringing you on the show wherever I am. How does that sound?

• 31:15Speaker 03

  Sounds great. So that seems like the theme here. I love it.

• 31:19Speaker 00

  So I wasn't kidding. Back in 2019, you guys launched on Product Hunt and the pitch was pretty simple. Complex automation made easy with no code. And as I talked to you around that time, you guys were talking about the e-commerce market and how that was really pulling you in. And so I thought about you guys as a place where I could go to connect applications, get workflows done. But really it was about selling stuff on the internet. Now, clearly, I'm dramatically out of date. So why don't you explain to me how MCP comes into this? And now we're talking about agents. So catch me up.

• 31:49Speaker 03

  So we start our life, like you said, in 2019, kind of beginning of 2020, crazy time with COVID, of course, focused really on the commerce space. It was a very fragmented space at the time, right? So there were a whole bunch of different platforms out there, Shopify, Adobe, Magento, WooCommerce, and many, many others, a very fragmented ecosystem. And our kind of our initial vision was how do we connect all those different platforms together, right? Orchestration, helping them to integrate those systems together. This is really the pre-agentic era, right? So this is the pre-AI era where AI wasn't really a thing. And so APIs were all the rage. As we've expanded as a business, you know, commerce has ultimately become a little more, more, more centralized. And so we've expanded to not just commerce, but also accounting, ERP integrations, which is also a very fragmented

• 32:33Speaker 03

  space, payroll integrations and many others. And what's top mind for a lot of folks these days is well, how of course do we inject AI into this, right? So our business has actually evolved in many ways from being just a integration platform to be more of an orchestration layer for AI. And so some of the things we've done recently is we've expanded to have MCP, add an MCP layer on top of all of our integrations. So if you are a And looking to integrate with a whole bunch of applications like NetSuite or QuickBooks. We have an MCP layer. We're allowing folks to essentially take our technology and build agents quicker.

• 33:07Speaker 00

  I think I now understand the progression pretty clearly. So you had a couple of products. You had alloy embedded in alloy flow. One was your kind of white labeled integration layer. Flow is helping people run workflows using those integrations. And then today, if we think about Anthropic's MCP structure, it's essentially another layer on top of that that allows AI agents to tap into information that you guys are already bringing together in your integration product. So really what you've done is you've made like a series of hooks on top of your previous work. So that way it can itself fit into the agenda.

• 33:40Speaker 03

  Completely. It's exactly correct.

• 33:41Speaker 00

  Is this something that you guys like went out to do because you saw, look, this is where the market's going? Or were you just kind of plowing ahead and then your customers were just like telling you, hey, guys, we need this. We need this. We need this.

• 33:50Speaker 03

  A little bit of both. You know, we certainly saw a pull from the market. Folks were saying, hey, we want to have integrations to things like GPT or like Anthropic Claude and whatnot. And so we added those connectors naturally in our product because the customers were asking for that. And then we also kind of realized that in many ways, agents do require a certain degree of what we call determinism. Right? So there's a lot of talk these days about completely autonomous agents in the space. But there's not that many truly autonomous agents that are actually being deployed in production. And the reasons for that are privacy, security, compliance. It's hard to just to say to an agent, hey, here you go. Go do something and you know, we're not really going to have much oversight. And so we realized that blending the kind of the determinism of our products

• 34:33Speaker 03

  that we've historically built our workflow, built based products with agents and kind of adding AI and infusing it into a workflow creates what we call kind of semi determinism. Right? It essentially creates a an agentic workflow that can think, that can reason, but still works within kind of the constructs of of a deterministic flow. And it behaves relatively consistently across the board. So you're actually able to essentially get the best of both worlds.

• 35:00Speaker 00

  This is why you guys wrote with your quote AI connectivity platform. Agents handle the busy work and humans step in only when needed. So how do you tell when you want to step off of the probabilistic AI side of things and go back into the more deterministic, perhaps even human led part of work? Is there, is there a trigger that comes into play? Is it just a complexity point?

• 35:19Speaker 03

  It's basically a human loop connector, right? How our AI workflows work is, you know, they, someone will define the flow, they'll build it out and it'll have very several agentic tasks in it. And then if the agent doesn't have, if the LLM doesn't have, let's just say confidence, right? To, to address something, maybe the confidence score is less than 80% or 75% or so. It'll actually know then to escalate that to a human. It'll, it'll send an email or a WhatsApp message or a text message and say, hey, you know, can you please approve this?

• 35:44Speaker 00

  When you think about the percentage of confidence, I'm a human and I'm terrible at that. I think I'm either a hundred percent or zero percent, but I'm usually more like 46. How does an AI agent know when it doesn't have enough confidence to proceed and should call in somebody? Cause 75% is a great threshold, but it feels a little synthetic.

• 36:02Speaker 03

  We're always evolving, right? So we're, we're always learning more here. We, we have some built in evals that allow you to kind of test, you know, in the product and to, to help the LLM to kind of generate that confidence. So that's certainly one way. And ultimately it is essentially a judgment called the LLM is making, right? So we are in a certain, to a certain extent, relying on, on the LLM to, to have that judgment. You could, you can still also use just good old fashioned conditionals, right? So if you, if you, you want to be very much more deterministic and say, okay, based on the output that the LLM provides, if it literally just is black and white, does not meet the certain criteria you're looking for, you can build a conditional flow into the workflow that just says, okay, if this, then that. And that's not really agentic, so to speak, but that is a kind of an off ramp to, to be a little more deterministic in an agentic flow.

• 36:47Speaker 00

  I'm glad we're here because I was really curious about just how, how durable, non-fragile and, and useful today AI agents are. Cause if you go back to last year, you know, Sierra was talking about, you know, this was going to be the year of agents and so forth. And I think they've made progress, but I don't see that many companies putting them out there and using them in a way that seems to be entirely free from human intervention. It, it sounds like Greg, that. That's going to be the case for at least another another year or so. It feels like we need a step function change in AI model quality to remove the need for humans in the loop.

• 37:19Speaker 03

  Absolutely. I think there's a number of reasons why. In general, I think what we're seeing is that the technology is still so new and enterprises, of course, take a little bit of time to adapt to this new technology. So they're being a little bit more careful in adopting it. And just in general, the models are also evolving so fast and at such a rapid pace that because of all this change, I think that is driving that little caution in the enterprise saying, hey, we we need to take a take a breather and make sure we're doing this in a safe way.

• 37:46Speaker 00

  But even with that note of caution, it still seems like people really want to move towards a more agentic future. And so I presume that even though the technology may not be as mature as we would like, you guys are probably still seeing quite a lot of demand for this side of your work because folks really want to start at least getting their feet wet in agents?

• 38:06Speaker 03

  Yeah, absolutely. Well, I mean, there's kind of there's two, you know, two, I guess, broad character, broad groupings of agents, right? There's the the more semi deterministic agents that are, you know, requiring human oversight and advice. And then there's completely autonomous agents. And I think what a lot of folks are starting with is that is the former, they're starting with these more semi deterministic workflows, these AI workflows that they are agents, but they may require a little bit more oversight. But I think the gradual shift over the next, you know, probably, let's say, 12 months will be primarily towards the, you know, the truly agentic, completely autonomous future.

• 38:40Speaker 00

  I'm trying to figure out 12 months is a lot of time or not very much time because on one hand, it's an entire year, Greg, in AI. That's but also like 12 months is, you know, that's four quarters. It's four earnings calls. I mean, it's not that bad. Are you content with the pace at which we're seeing the underlying AI models improve? To me, speaking just kind of crassly, it does feel like right now we're in a bit of a lull between major releases and we're not seeing the same kind of like gains in intelligence. So do we need to see an acceleration there to hit your 12 month window?

• 39:09Speaker 03

  Yeah, I mean, I think that that we absolutely do need to see an acceleration. I completely agree with you. There's been a lull, right? I think that there's been a lot of talk about how GPT-5 was not as impressive as everyone thought it would be.

• 39:20Speaker 00

  I've come around to that. I'm kind of now on that page.

• 39:22Speaker 03

  No, absolutely. It's more like, in many ways, I still see myself actually going back sometimes to the previous models and actually using them because they're frankly better sometimes. So I think we are in a lull period. I'm pretty confident that technology is going to continue to evolve pretty rapidly. I mean, there's such investment, obviously, in this space. So I would be surprised if it didn't significantly increase over the next 12 months. But that being said, even I think what we're going to see, even if we don't fully get to autonomous agents, there's so much efficiency gains that you can get from these semi-deterministic agents, right? These agents that are not 100% autonomous, but they're, you know, 50% or 60% autonomous. That's still 50% time-saving that you didn't have before.

• 39:58Speaker 00

  Yeah, and then it's 50, 55, 62, 70, 75. It goes up from there. Okay. So one thing you guys talked about recently that I really liked was the idea of building intelligence systems as simple as prompting a workflow. And to me, that kind of fills with the North Star of where you guys are going, kind of the combination of what you were doing before, and then on top of that, adding agents. So how long until companies that don't have internal tech teams, that don't have the same level of resources to bring to bear that your larger customers, your Amazons have, can really take full advantage of what AWO is offering? And I'm asking this because I'm curious about the state of the market.

• 40:31Speaker 03

  Yeah, well, I think there's still a barrier to entering the market, right? Like, I think the people who are still developing agents or who are primarily deploying agents right now, it's other folks who are, you know, smaller startups, who are on the cutting edge and they're, you know, they're, they're, they're, they have teams internally where they're building agents. And then you obviously conversely also see that in the, in the, you know, the big hyperskellers, like the Amazons and the Googles and whatnot of the world. But I think that the long-term vision, of course, for agents, that the dream of agents is that it becomes mainstream, right? That, that, you know, the mom-pop store on Main Street is also able to, to leverage, you know, AI agents. And so. I think that's coming pretty soon, frankly. The barrier to entry still, I, we believe, obviously, we're biased. We believe is, is by producing a really elegant experience where you can build that. You have all the tools, you have all the technologies in a visual kind of builder.

• 41:15Speaker 03

  So as opposed to requiring someone to write code, you can do it yourself.

• 41:19Speaker 00

  It's almost like you'd want to have a company that had an initial foundation in no code automation as the place to build your future AI agents for mom and pop. So this brings us to customers because we were joking before we started recording about your current logo list and it includes a lot of very impressive, large names and you're not going to put Bob's Pizza Store on there. But when do you think that happens? I mean, when do the, the restaurants near my house that are run by folks who, you know, might have an iPad at most can take advantage of this? Is that five years?

• 41:49Speaker 03

  I think it's less than five years personally. I don't know, I'm not sure that it's one year, but I think it's less than, than five years by all means. I think what's going to happen, like, just like the internet happened, of course, is, you know, it, it, it starts, of course, with people in tech and, and big companies that have the investment budget and the R and D budget to invest in this, but it's going to expand pretty rapidly. And I think what, what we're, we're seeing is we're already seeing kind of pilots of, you know, of, of companies that are doing this and this, who are smaller, they're not just enterprises. So there, there's certainly a lot of interest. It's just, we'll continue to trickle down and there probably will be this like wave crashing moment where there's just this massive, massive splurge of people who are saying, like, all these mom and pop storefronts saying, we have to do this.

• 42:26Speaker 00

  For me, that was when my mom asked me if she'd help me put something on eBay for her. I'm like, oh, okay, this is now become a real thing if my mom's going to ask me about it.

• 42:34Speaker 03

  And the same thing happened with like social media too, right? Like, I mean, like if you look at like Facebook story, for example, the same thing happened, right? So like, I, I think it's inevitable and if you draw comparisons to the past, like it didn't take that long. I mean, it certainly took, it took time, but it wasn't like, it took a decade or so. It, it was much faster.

• 42:50Speaker 00

  Talk to me about the business itself, because the last time I think we spoke was two or three years ago, you guys had raised money or two kind of quick rounds, things were looking pretty good. How has business performance been since we last spoke?

• 43:01Speaker 03

  Yeah, so we've been going more off market, right, over the past few years, right? I think with, with, with the integration space that, that we were kind of previously in, we realized that the, the primary folks who were benefiting from that were these larger companies, right? So today we have companies like Amazon that uses us. Best Buy, Xero, and many others that use our platform. And I think AI is interesting because now AI presents an opportunity to go not just upmarket, but like almost go even more horizontal, right? Like, we're still obviously focused on the middle market and then ultimately the enterprise. But again, to your point before, like, it is going to go more mainstream and there's going to be just this endless, I think, opportunity with everyone just racing the AI agents. So business has been good. It's been really exciting.

• 43:41Speaker 00

  I'm trying to chip away. I'm confused why you haven't done like everyone else has done and go out and raise a 100 million dollar round to reinvent the world of agents. Like, I don't think you guys have raised money in years. And, you know, just given your focus, it feels like you're in a position where if you wanted to, you could go out and raise a pretty large amount of money. So what's your thoughts about raising capital in this market cycle when feast or famine, but you're probably in the feast side of the divide?

• 44:05Speaker 03

  Well, I didn't say we're not going to raise capital, right? It's certainly, certainly, certainly top of mind to a certain extent. But, um, yeah, I think that we are, you know, we're aggressively just growing this AI platform. And I think we'll look to a fundraise in the not so distant future, frankly.

• 44:21Speaker 00

  Are you counting down to a specific like ARR milestone before you do that?

• 44:24Speaker 03

  I think a mix of ARR milestones and also just, you know, certain features that we want to see. But I mean, we're in a very healthy position as a business. You know, we've been very capital efficient, so we've not needed to raise capital, which I think is obviously exciting because, you know, we don't want more dilution than we don't have to take on, so.

• 44:40Speaker 00

  That's actually been a theme of the company since you raised your last round was just not spending too much of it. So I did not presume you weren't raising because you couldn't. I just presumed it was more of a choice. What are you going to invest in when you do raise more? What are the things that you can't do right now that you're, that you would like to unlock? Is it acquisitions or?

• 44:56Speaker 03

  I think honestly, acquisitions might be interesting, but frankly, just scaling up our forward deployment engineering team, right? So I think with AI, what we're seeing is we're seeing a lot of just, you know, like these implementations are very heavy, right? So it's not like you can just press a button and turn on a template and, you know, you're off to the races super quickly. Like, there's a lot of, a lot of configuration required. And so our implementations today are very much like we have to, you know, we're working really kind of in tandem also as an extension of one of these companies' teams, basically. And I think we want to grow that team specifically. So it's just more investment probably in product and frankly, in the forward deploy engineering, kind of go to market motion, like how we get deeper penetration.

• 45:34Speaker 00

  There's probably a seesaw effect here because on one hand, forward deploy engineers is one of the most popular and growing jobs in technology, because I think a lot of companies are realizing, like Alloy, you're going to want to have people to help make everything kind of work. But if we go back to the mainstream conversation, you can't require a small company to need forward deploy engineers, because if that's the is requirement, it's priced, they're priced out. So invested a lot in forward deploy engineers now go after the enterprise, but over time, as technology gets more advanced, you can probably have a lower weight sales motion.

• 46:06Speaker 03

  Completely. I think we're already kind of seeing hints of this with like what Replit is doing, for example, right? Like, you know, the Replit agent, you like, they've reduced the barrier to entry. So like, it's primarily builders now that are able to build websites that like, and formerly that was engineers. I think that's going to go even more and more down market, right? Like, they're going to have anyone who can build a website pretty soon. And like, I think the same technology applies with, exactly with, with here, with here, right? Like, I think that there will be a world where you can just say, hey, here's my process, or maybe you have a JD of some sort, you say, you know, I need a bookkeeper agent, here's my JD, and here's a bunch of the tasks I want to go do. You just, you know, put that into Alloy, and then all of a sudden, you just get an agent, you know, with very, very little configuration. I don't think we're quite there just yet, but we're certainly marching in that direction.

• 46:48Speaker 00

  One thing we have heard, though, is that everyone does want to hire these forward deploy engineers. So I'm curious, how, how hard is it to hire the right talent in the market today? Because it feels like on one hand, you have Meta spending, you know, entire European football clubs with a capital on individual nerds. And then on the other hand, I read all the computer science, you know, subreddits and forums, and everyone's like, I can't get a job for $1. So I'm just curious from your startup CEO chair, how tough is it out there to hire?

• 47:12Speaker 03

  Well, it's not easy to hire, you know? I mean, there's, I think that there's exactly what you described. There's these two kind of very wide spectrums, right? You have a lot of folks who, who are, you know, just being gobbled up by these big labs and infinite capital, and then simultaneously, you have folks who maybe don't have as much work experience and therefore are not the right candidates to hire. So, and we're also trying to be picky, because we started out, you know, really during COVID as a business, and the first years of the business, we were remote, right? So the whole business was just, you know, was not in person, was not, was not an in-person culture. We're trying to change that. So we're like being very, very intentional of like hiring more in person. Now, we're a hybrid company, so we have people, of course, who are remote and we will continue to hire remotely. But we are trying to be more intentional about hiring in person. So that actually makes it even harder, right? Cause you've got to find people within a, you know, certain geographical location.

• 47:56Speaker 00

  What's the maximum commute you think is reasonable for someone to take on? Because I've lived in San Francisco, I'm super familiar with the traffic there. And let me tell you, dear God.

• 48:05Speaker 03

  I, man, probably 30 minutes.

• 48:07Speaker 00

  But that means that you can't even live north of Market Street on bad days. Like if it rains in San Francisco, 30 minutes commute six blocks.

• 48:12Speaker 03

  It depends. We're close to Caltrain. Our office is close to Caltrain.

• 48:15Speaker 00

  You're down in Selma.

• 48:16Speaker 03

  Yeah. So if you're, if you're, you know, if you're in South Bay, you can hop on Caltrain pretty quickly.

• 48:21Speaker 00

  Caltrain, if you're not familiar with the kind of system, is the American Bullet train. Faster than Tokyo's trains, faster than, oh wait, no, it's not. No, it's not. It's slow. It's slow as hell.

• 48:29Speaker 03

  We're still waiting for that upgrade, you know, one of these days.

• 48:31Speaker 00

  Can't some, one of the billionaires in Silicon Valley just buy a new train? Like, why is that? Why, why can't we just get faster cars? Like, come on, people.

• 48:39Speaker 03

  I've been asking myself that question for years, but hey, you know.

• 48:43Speaker 00

  I want to throw one more at you, Greg. Last time we spoke, you were the CTO of the company. Now you're the CEO. I have seen CTOs take on the CEO mantle before. Not unheard of, not super common either. So for folks out there who are either a CTO or CEO today, tips, tricks, things you can kind of share about swapping the roles, handing off certain reins, picking up other ones? I'm just curious about how much it rocked your world to make that pretty dramatic shift in, uh, in position at the company.

• 49:07Speaker 03

  One of the unique things about at least our business was that because the product historically has been very technical, I was doing a lot of implementations myself, right? So obviously we talk about forward to play engineers.

• 49:16Speaker 00

  That was you at the start.

• 49:17Speaker 03

  Yeah, of course. I mean, that's, it's gotta be somebody, right? And so I was doing a lot of that work myself. And what was really exciting was I was also working directly with, you know, many of these customers implementing it as, as the FDA. And I got to see that kind of that sales motion firsthand. So I think it was unique in, in, in that I had that experience and was able to quickly transition that over to, uh, obviously the CEO role, which of course oversees, you know, more of the go to market org historically. But I'm still, you know, I'm still, I have my, my hands dirty in the, in the product by all means. So I think that's been a, been an important thing. And just in general, hiring a leadership team has been really great. We've been focused very heavily on, on growing our, our leadership team over the past few months. So we have a CRO now, um, we have a head of marketing, um, we have a VP engineering. So we've been really building out the leadership team and.

• 50:00Speaker 03

  You know, kind of bringing in obviously domain experts in all the categories as needed. And that's been just super helpful as a, as a CEO now.

• 50:07Speaker 00

  You guys have been really busy, so I'm, I'm really curious how big the business will become. But Greg, a treat as always, when you do hit the next major milestone, whatever it is, come back and tell us about it. We appreciate it, man. Keep the Bay Area cool and we'll talk to you soon.

• 50:18Speaker 03

  Thanks, Alex.

• 50:21Speaker 00

  I absolutely love my job because I get to talk to people when they're absolutely starting off a company, when they have raised their first money, and even when it begins to hit scale. It's an absolute treat. And speaking of founders, we've done that with. It's time to turn to our interview with Shopify's Tobi Lutke, and I want to bring Lon Harris up.

• 50:35Speaker 04

  Yeah, I think it's so funny to go back into these archive clips and see those are, those are always some of the most fun moments where they're talking about like, yeah, well, we just hired 40 people. It brings our total to almost 200. It's like, wow, like to think about Shopify with, well, you know, like a hundred some people trying to make this thing happen in the early days. It's like, it's such a, it's such a huge shift from how we think about them today.

• 50:56Speaker 00

  You can tell in this interview, we're going to play a couple of short clips from it here in a second. How on the ball Toby is, how, how serious he is, how, how deep into the problem he is, and how non kind of buzzworthy the whole chat is. It's so focused on helping people sell stuff on the internet, make companies. I don't know. It just seems very serious compared to the current launch video cycle that we're in.

• 51:17Speaker 04

  Yeah, for sure. And it's also he's got such a, this is the thing Jay said is telling founders like all the time and founder you is like, you really have to have this incredibly deep nuanced understanding of like who your customers are and what the market is and who your competitors are. And you could really see that Toby was super drilled into that. Like Jason throws a lot of other platforms, many of which are still around. Adam, like Etsy, what about Etsy? Are they your competitor? What about Kickstarter? Are they your competitor? What about Amazon Marketplace? Are they your competitor? And Toby has like every one of those. He's like, well, they do this and we do this. So they're aiming for these kind of people. Like he's just got it all very clearly laid out, like what the whole landscape is like in his head. And I think that's probably what made him such a, you know, dangerous competitor in a lot of ways.

• 52:02Speaker 00

  Yes.

• 52:02Speaker 04

  He was able to sort of, he saw so much of what was going to happen over the next decade plus of e-commerce coming.

• 52:08Speaker 00

  But every company starts with an idea and a start. So here is the Shopify origin story from Tobi Lutke.

• 52:14Speaker 05

  In 2004, I co-founded the business and initially we were trying to do an online store ourselves. We, we were selling snowboards online.

• 52:25Speaker 04

  So you were selling snowboards?

• 52:26Speaker 05

  Yeah, right. So we were actually, we were using Yahoo Stores back then.

• 52:30Speaker 04

  Oh yeah, Yahoo had a store product, I forgot.

• 52:32Speaker 05

  That's right, that's right. Program, Sphere Web, they sold that to Yahoo. Yahoo rewrote it a couple of times and then became Yahoo Stores. My background is I'm a programmer. And I apprenticed as a programmer, which is something you can do when you're from Germany. And I wanted to get sort of out of that a bit. I wanted to start a retail business. This was something else I was really interested in. We worked with manufacturers, got some snowboards, wanted to sell them. We wanted to use something off the shelf and realized there was no frigging way we could make, build the business we wanted based on off-the-shelf software that was available back in 2004. So over the course of this first season of sales, we replaced it with software we built ourselves. Which 2004 was right the time when Ruby on Rails came out.

• 53:16Speaker 04

  Yeah.

• 53:17Speaker 05

  So that was fun to play around with. And I got involved very much in the Ruby on Rails community. We had a lot of fun building the technology. So like we invigorated my kind of interest in programming back then. People were saying, you know, it's really, really cool that you guys have this, you know, Snow Devil, the snowboard store, but would you license the software? And then we sort of realized, well, maybe, maybe helping other people go through this and building their stores might actually be a better business than selling snowboards. And this is sort of how we pivoted. In 2006, we launched Shopify, sort of taking a lessons from Basecamp. This was again, even 2006, software as a service wasn't a term yet. Even just putting a price on the website was innovative in 2004, even though that sounds crazy.

• 54:00Speaker 04

  Right, that screen where you have like, here's your three options and this is the best one for you.

• 54:03Speaker 05

  Yeah.

• 54:04Speaker 04

  That was a true innovation by 37signals.

• 54:06Speaker 05

  Absolutely. And it's hard to remember that at this point. But yeah, this was all really, really impressive. And it was so clear that that was the way software should be sold on the internet. And then we wanted to do this for online stores.

• 54:19Speaker 04

  So I love that, I love that they were selling snowboards, which is such a specific thing. You know, like of all, of all the world of products that Shopify could have started with, snowboards would not have been on my bingo card. And that they were using Yahoo Stores, which is, I mean, you could see even in the clip, Jason at the time is like, oh right. Yahoo has a stores. That's great. Like, I totally forgot that Yahoo used to have a like, buy and sell stuff marketplace facing kind of Yahoo stores. So that I thought was really funny. And the other thing that really stood out to me is that when they launched Shopify, SaaS was not even like a term, like was not even a concept yet. We think of that now. Now, if you think of software as a service, it's like such a, that's what companies are.

• 55:03Speaker 04

  And that's how you build a big startup is, you know, you, you sell software. Like to, to think of that as being like a new, fresh on the scene concept. Like I, I, I wouldn't have even thought that was during my lifetime, let alone, you know, like just 20 years ago now where that was like, and they're talking about, you know, the origin, like 37 singles kind of invented this whole thing with Basecamp. And that was the first soft piece of software people were like subscribing to and re-upping on. And it's like, wow, I think of that as like really distant history, but it's not.

• 55:32Speaker 00

  And the SaaS point brings us to the clip that I want to bring up first, Lon, about pricing. One thing that we saw them discuss is how do you charge for this? Do you charge too little? And Jason runs through the exact sort of mental calculation. He still does on the show today, which is, all right, so if you're going to replace and build this yourself, what would it cost to construct this? Can you charge that amount? And it's funny to see how Toby's kind of not thinking along the same lines of replacing the cost with their pricing. It's very interesting. Take a listen to this.

• 56:00Speaker 06

  The one thing I've heard from people is that you charge too little. How do you respond to that? Like, if people say like you're charging 10 bucks or 20 bucks a month, you know, $250 a year to do all your e-commerce in a dedicated site is absurd. It's insane. And people would pay a lot more. If you asked your clients, if this software didn't exist, how much it would cost you, it would, they would say $5,000 or $10,000 to hire somebody to set up a competing service. What do you answer to that?

• 56:26Speaker 05

  I usually just tell them we are bad at pricing and that's the, that's the truth of it. It's, we, we, I regularly talk with people who are converting from like not, not just $5,000. People are often paying $50,000 a month for their systems. That's a, that's a fairly regular price in our industry because you're going through third parties who are building the systems and they are hosting for you and you're being charged and all these kind of things. So converting to that and on a $170 plan and they are, they are, they are serviced much better with that.

• 56:55Speaker 05

  The nice thing about our business is We really want to just make it a lot simpler for people to start these kind of businesses because it's hard. You know, like when we started, there was so much to learn. There was, you know, just how you're dealing with manufacturers, supply chain. How do you get the word out? There was a lot of complexity around technology too. Like we had to get approved for credit card gateway back then. We had to post like $10,000 down payment or bond with the banks to do this kind of stuff. We needed to, you needed to engage for many, many thousands of dollars a year, a company doing PCI scanning for your site, which meant that the site had to be up.

• 57:37Speaker 05

  But then you couldn't get access to the gateway credentials before you had the tests. So it was a huge chicken and egg problem doing development for us. And it was just hard. So there's a lot of these kinds of problems we wanted to make go away. So our business is focused on, hey, let's, let's make it so that everyone who has products to sell, like people with interesting stuff, that there's just nothing in their way to get, to get this out and get them in the hands of people. That's sort of what we care about. And then for us, there's opportunities to monetize, of course, to ask people to pay money for this. But there's also opportunities for us to work with the payment gateways and shipping companies because economies of scale matter in this business. And if you can go to FedEx and say, hey, we have 60,000 people want to probably ship with you. Then that means we can get better rates for everyone.

• 58:22Speaker 05

  And that means there's potentially some, some opportunity for us to make money too.

• 58:25Speaker 00

  I still think we're trying to figure out how to price products today. I mean, we mentioned how SaaS is kind of a dated term. Sure. And now we talk about usage based pricing, but at the time we are two generations in pricing from where we are today. So it's really interesting to see how far back we were still trying to sort out. What should software cost and are we undercharging? Questions we're still asking today.

• 58:43Speaker 04

  If you watch Twist, even in the present day, the idea of like, isn't your product absurdly cheap? Like Jason asks Toby that directly. Like, isn't $10 to $20 a month for everything that you're doing for people absurdly low? Wouldn't people pay a lot more? And this is a topic that still comes up to this day. It's like, well, you do want, you know, that, that is always this sort of like really fundamental tension. It's like you do want to delight your customers. You want people to be so excited to use your product and making it extra cheap is a way to do that. But then like, are you sacrificing? Where you need to go and the ambition and the scope of your project by making things super, super cheap instead of, you know, charging more so that you can get further.

• 59:26Speaker 00

  Let's move on to talk about Ottawa, talk about building in a secondary market. I think right now people are very focused on San Francisco. Again, it is once again become the hub of, you might say, the cutting edge of technology. A lot of AI house parties, I'm told, are in San Francisco. And yet Shopify built a simply world straddling company somewhere far away.

• 59:45Speaker 05

  What we think is one of the things that Shopify became really, really good at is making what we call secondary markets work, like secondary markets is, you know, every city which isn't, everything other than Silicon Valley, maybe New York City. So how a great, big, meaningful, impactful company is being made is like there's a geographical region that somehow realizes there's this one company that all the best people go to and spend a couple of really exciting years of their career together. And then they disperse again to do many other things. And we would like to be this company. So to us, the most important thing is we want people to think of us when they plan their careers. And if they are signing up for lots of interesting, interesting work, but are willing to work

• 1:00:29Speaker 05

  really hard with, you know, really caring and with a lot of passion. And hopefully you come to us. And it turns out there's a lot of these kind of people around in this city.

• 1:00:38Speaker 04

  It is a topic that we're constantly talking about. It's like, you know, like, that's maybe the number one question that we get from founders when they submit questions for Twist is like, I have this great idea for a company. Do I need to move to San Francisco to start my company? And, you know, like, it's always kind of a nuanced answer and it shifts and stuff over time. But I feel like Toby really plugs into this very sort of like romance, what I would consider like, almost like a romantic idea of startups, where it's like, it's like that PayPal mafia idea, like, you're going to bring a group of really brilliant people together under one roof, they're all going to make this great product together, and then they're going to splinter off and become like, you know, like the all-stars, like, they're going to all shoot off and, and start their own great companies. And that's what makes this sort of city a startup hub. And I'm like, I, I, I love that.

• 1:01:22Speaker 04

  I don't know how practical that is or how many companies have been able to like. Set out on that course and actually achieve that. But he and I could tell that he and I share a lot of ideas about like what the ultimate kind of collaboration, the ultimate kind of workplace is because that's what I feel like I'm always trying to find too is like, where's there a group of just really excited, like cool people digging in and working on something interesting and then they're all going to go off and do their own things after that.

• 1:01:48Speaker 00

  Well, you know, just for fun, people do talk about the Shopify mafia. I mean, Business Insider in 2023 wrote a story entitled, meet 38 members of the Shopify mafia. So it does seem to have worked out, but that's how you build entrepreneurial hubs. There have just been enough people, you know, building, exiting, recycling capital in the Bay Area for so long that it is what we call Silicon Valley, but I think you can pull it off in Ottawa. I think you can pull it off in New York City. I think Austin's got a good shot.

• 1:02:12Speaker 04

  I think we've seen a lot of attempts, you know, like, and, and sometimes it takes and, and sometimes I'm, I'm saying, I'm sitting here in Austin. So obviously there was a sort of focus like, let's see if we can go move our companies to Texas and get going there. And it, it worked in Miami, we've seen too, but I also have recalled like, I've had a few of these conversations about places that where it did not take like, I started working in tech companies in Silicon Beach in Los Angeles, if you'll recall, and still today, not the most amazing startup hub in Santa Monica, if you went there today. And then I also recall Vegas, that was going to be a big thing. It was like downtown Vegas is ripe for the picking. We're going to put all of our tech companies there.

• 1:02:53Speaker 00

  Tony, she's vision and I came of age, if you will, in Chicago technology scene back in the era of Groupon. And you know what? Chicago is still about where it was in terms of the ranking of the global startup charts.

• 1:03:03Speaker 04

  Did they have a silicon nickname for Chicago? Silicon?

• 1:03:06Speaker 00

  Silicon fricking cold as hell too much of the year. Dot com is how I describe Chicago. Chicago is the best city in America, except for the weather. Again, like that literally just ruins it.

• 1:03:15Speaker 04

  I did, there was one more thought from, from that discussion that I thought was interesting. He talks about how even great the top people, the A-list people, the people that you desperately want to come with you on your startup journey and help you build your company. Like it's not, it's not so easy to find those people as just scanning a resume and looking for like work experience, you know, like he notes that a lot of people have been fired or have been like poor performance at one job and they just needed to sort of figure that out. Uh, he specifically discusses it while working with a semen. So let's take a look at that clip.

• 1:03:49Speaker 05

  If you pull 10 people, high performing people, um, um, about their, their careers.

• 1:03:56Speaker 05

  Three, four, five of them will tell you, oh, I got, I got fired once. Like people just, people's careers are never these like meteoric races that people think about.

• 1:04:03Speaker 04

  Yeah, they're never perfect.

• 1:04:04Speaker 05

  They are like, I think Cheryl in a book called it sort of a jungle gym. Like that's much more, much better metaphor for what a real career looks like. And, you know, sometimes this is the stuff that has to happen. I worked for Siemens as an apprentice and I got one of those letters from them saying, your performance isn't up to par. And I was like terribly shocked by that because I thought of myself as a really good programmer. But then I realized, you know, like I probably haven't slept in the entire week because I'm, I'm, I'm playing video games at night or I'm programming. Probably my performance wasn't very good. I made some changes and this, this kind of things might end up turning, turning out to be really, really beneficial things. And I think that's worth reminding people of.

• 1:04:40Speaker 04

  And I thought this is such a great point to make that we think of, you know, your career path as being this like straight line, like, you know, up and to the right, like you start at this job and then you move up and then you move up and then you move up and then one day you're Paul Graham or whatever, or you're, one day you're Tobi Lutke. And I think that, you know, it's, it's more, especially in the early days, it's a little bit more chaotic than that. And everybody tries jobs that don't work for them or career paths that weren't the right path and then corrects it. So when you're evaluating somebody or you're looking at maybe hiring someone, you can't necessarily be that rigid. You've got to be able to like, does this feel like the right person and does their experience line up with what we're doing? But it, it, it's more nuanced than, than a lot of people think.

• 1:05:23Speaker 00

  Yeah. You can't really be reduced or boiled down to just your LinkedIn page because that's not going to capture anything like the full context of yourself, your career and what you have learned. All right, Lon, the next segment in this interview we're going to talk about is the question about expanding one's global footprint versus adding features. This is the sort of trade off that founders have to deal with when they don't have a current day Shopify's employee base.

• 1:05:45Speaker 04

  Yeah. I mean, this is, again, it's just fascinating to go way back into the archives and find these amazing companies from years and years ago. And that they were struggling with the exact same problems we hear from founders week in, week out. Even people working on their, you know, MVPs are already sweating this. Like, well, how do I, do I make it more appealing to more people? Or do I make it like extremely robust and like there's tons of useful stuff in here and it takes a while to sort of figure it out. And I just always think it's interesting that, you know, like the same problems persist even at such different levels of scale.

• 1:06:18Speaker 06

  How do you decide between going global?

• 1:06:20Speaker 05

  And adding like killer fun features. We are a very small company, given the size of the problem. We had 200 something people, 200, I think 16 at the latest count. You do that all with just 200 people? I mean. Last month, we added like 40. So it's like. You added 40 people in a month? Yeah. Wow. Like. That's more than, that's two per business day. Right. I had, I give a monthly newbie session. I had to move it into the park because it was nice weather. And there's a lot of Shopify get togethers. And I just recently went to one in New York City. It had 100 people there. People talking, exchanging ideas about how to, you know, you know, take their products to the next level and finding new market channels. But it's powerful. You go around there and you talk to people and say, where were you when you got your first order?

• 1:07:04Speaker 05

  And everyone would be able to answer this because it's a seminar. It's a live event. You have an app. Yeah. And so you get a push notification. I saw somebody who had it and they showed me their Shopify notifications and they were watching sales come in all day long. And they were absolutely raving about the product. People are addicted to that, the metrics, huh? Yes. Yeah, I mean, it's metric business, right? The thing that sucks about online businesses is that you can't watch the person walking into your front door and looking at the various product and taking a path through your store. And then leaving without buying. And then leaving without buying. There's so much information in this that like online stores have like, or just online business have trouble surfacing and creating an equivalent for that. You know, it's just, those are all challenges. If you can figure out what that equivalent is for online,

• 1:07:48Speaker 05

  then we would do a massive job of educating. Eye tracking where their mouse is, whatever. Just what images they swiped on. Right. And then try to do that while being in 100 countries. Try to like, try to deal with the privacy concerns of various different, like continents and so on.

• 1:08:05Speaker 00

  So one question that I had is what's it like to be the CEO of a hyper growth company? Because there's not that many people actually out there long who have done this because a really, really fast growing company is rare. So by definition, there aren't that many people that have experienced it. And so I loved how Toby described his biggest challenge, viz the market.

• 1:08:23Speaker 05

  The hardest part of the job?

• 1:08:28Speaker 06

  Is it the regulation or hiring?

• 1:08:29Speaker 05

  No, it's not. The hardest part of a job is

• 1:08:34Speaker 05

  how to, is that I don't think, like, there's no books for how to build a company that fundamentally needs to be able to, while following a very ambitious roadmap, at the same time, the core competency of our business needs to be how to thrive in chaos and how to react quicker than anyone else. And we are competing on that ground with companies which are very good at this kind of thing, like Amazon, right?

• 1:08:59Speaker 06

  That is the big competitor, though.

• 1:09:00Speaker 05

  Well, yeah, really.

• 1:09:02Speaker 06

  So if I am, if I've made 10,000 iPad cases, what is, should, why should I put them on Shopify instead of just selling them all to Amazon and seeing what happens?

• 1:09:15Speaker 05

  Well, Amazon will be-

• 1:09:16Speaker 06

  Because people have to make that decision, right?

• 1:09:17Speaker 05

  Yeah. No, it's not really a decision. So usually the way it works out is like people need their online shop, which is where they capture all the margin value, and then there are various sales channels. Amazon Marketplace is going to be one of them. So you from Shopify Store, you federate out to eBay, Amazon, all these other channels. If you are in retail stores, you integrate Shopify into that part of the supply chain.

• 1:09:43Speaker 06

  Yeah.

• 1:09:43Speaker 05

  So like, we're not really competing on that. But if you scale up the ambition of the business, like what Shopify is doing fundamentally is trying to make commerce better, right? And trying to disintermediate further, trying to connect the, because what, you know, Amazon has a monopoly on all the products that have barcodes. And what we would like is to have a monopoly on all the products that are actually interesting. So, because the people who actually care about these, the products and make them themselves come to us with them.

• 1:10:09Speaker 06

  Got it.

• 1:10:09Speaker 05

  So we would like to disintermediate further and get them directly in front of people. And that's what we're really trying to accomplish in the long run.

• 1:10:15Speaker 00

  What's funny, Lon, is now there's a bunch of startups out there who are trying to out Shopify Shopify and now view Tobey Lucky, like I'm sure Toby used to view Bezos.

• 1:10:24Speaker 04

  I think it was interesting, too, that Jason, you know, tries to give them like, well, what about Amazon? They're your chief competitor. And the way he thought about it, I think, was pretty productive, where it wasn't like, I'm going to try to- To steal people away from the Amazon marketplace, which like, obviously today, maybe they could, they could have that idea. But back then was like a David versus Goliath scenario. So he was already even thinking about it as like, well, how can I like work side by side with them? So we don't have to beat them like, well, maybe you can sell things through Shopify on Amazon marketplace. So you could use both services. And I think that's like, uh, you know, the sort of clever approach. Like I don't, you don't have to kill Goliath.

• 1:11:06Speaker 04

  You could figure out how to like, hang out with Goliath for a few years until you grow. And then maybe you can take on Goliath.

• 1:11:12Speaker 00

  Yeah, you go hang out with Goliath, learn his workout schedule, his macros, his peptide routines. And then once you're also enormous, you go kick him in the face. Lon, one last segment here about competition and the broad array of it. He was mentioning names like Etsy and Kickstarter as well.

• 1:11:27Speaker 06

  Who's a bigger competitor, Etsy or Amazon for you guys?

• 1:11:30Speaker 05

  I don't think of.

• 1:11:31Speaker 06

  Kickstarter.

• 1:11:32Speaker 05

  I don't think of, I know they're all facets of the same market, having slightly different approaches. I mean, if you, if you really will for like for shopping carts specifically, our competitors like, you know, big commerce, maybe which does something similar.

• 1:11:47Speaker 06

  Jetta.

• 1:11:47Speaker 05

  Maybe, um, but again, we have, we have like, I think fundamentally Shopify is trying to climb a bigger mountain than, than, than the others. And yes, like there are similarities in this, but this is, I mean, like Shopify's market is making websites that make more money than they cost. What's the, you know, what's the market size for that, right?

• 1:12:08Speaker 06

  Yeah.

• 1:12:08Speaker 05

  So, um, it's, this is a big place and, and there needs to be lots of different approaches.

• 1:12:13Speaker 04

  Toby had a great quote in here. Fundamentally Shopify is trying to climb a bigger mountain than the others. And then he reduces it, uh, we, you know, we do one simple sentences all the time, like describe, describe your product as quickly and effectively as you can. And he, he gives a great one. Shopify's business is making websites that make more money than they cost. So when you think about it that way, it like really reframes the whole business like, oh, that's not what Amazon is doing. Amazon is like, we're going to get you that toothbrush cheaper and faster than if you went to CVS. That's like the core promise. This almost makes it sounds more like Squarespace or something like it's about making this website and making this online business.

• 1:12:57Speaker 04

  And we're going to give you all the tools to like, make that happen. So I thought that was, that was really interesting.

• 1:13:02Speaker 00

  Also very focused on individual businesses because if you're thinking only about the cost of the website to build and run, you're not thinking about a large staff. So he's really saying, how can we enable people to build small companies? And I think that's really great because everyone else wants to serve the enterprise. I love seeing someone go after the small guy. And we'll just close with this Shopify today, Lon, worth $190 billion. So it all worked out. A nice, happy ending. All right, everybody, that has been Twist for this lovely day. We'll see you all soon. Lon, you're a peach. We'll see everyone next week. Bye bye.