0:00I know what I'm building is a top three priority at Google and Apple like in the next 12 months. Not a top 10 priority, like a top three priorities. The product in this category that will win will have a network effect at the agent level.
0:11Now, the hottest category in Silicon Valley is AI assistance. On the consumer side, you've got Instinct. On the enterprise side, you've got town.com, founded by today's guest, Jean Denise, formerly CTO at Plaid. And this conversation today is probably one of the most pertinent discussions that there is. I think you'll trust your agent to decide what data to share with other people without you intervening in 5 years. You can build now at the speed of machines, but you can only learn at the speed of humans. I don't think Instinct and Town are trying to do the same thing.
0:52JD, dude, I'm so excited for this because in all honesty, I have a lot of founders on the show where I kind of need to pretend to be excited by their product and I'm not really. Um, and I love town. I was saying the team use it here. I'm a DAU and so I was so excited when we agreed to do this. So, thank you so much for joining me today, man.
1:12Yeah, thanks for having me. And honestly, I didn't know that you were a DAU until like 3 minutes ago. So, I'm super happy and uh send me all the feedback about the product cuz you're a DAU, but when you're a founder, you're always embarrassed about your product at all times.
1:24You might regret saying that, but I I will do. For those that don't know, what is count as specifically as possible?
1:33Uh so, we're an AI assistant that lives in your email on your calendar and it tries to help you do work, right? So, what it looks at, it looks at things that you do already, uh, how you organize your day, emails you tend to send out, and it recommends AI automations that try to do some of the things that you would do normally yourself, uh, just do them for you in the background. And yeah, we've been a product, we've been out in the market for about 3 months. I think our ICP is just mainstream users, like mainstream people who, you know, use email,
2:02calendar, text messages to do work. Um, and we've had we've been doing super well.
2:08Can I be blunt, dude? I we obviously did a show a couple of years ago and I remember when you started like your own thing, you were doing some boring [ __ ] in finance and I remember the first round going down I was like I love JD but it was pretty boring. Um what was the pivot?
2:27I mean, we we yeah, so we spent a year building an AI tax company, like business tax prep with AI, and we just we got to some product market fit, but not enough where it was going to be a success. Like that's, you know, there's a thing like the truth is we failed at building a business that would be a great business. And yeah, after a year, we were like, we got a reset and we spent three months kind of in the wilderness trying to figure out what we wanted to do. And one of the one of the areas we just looked at is why has no
2:55one built AI that operates out of email.
2:58Just there's so many people in the world who run their business and their life out of email and calendar. We were like why no one has no one built a great product there. And it was just about the time that like Opus had gone fully agentic, right? This was like November, December last year. And so it was also the same time that models could start to actually do real work, not just do like a few steps, but real agentic work. and the prototype. We built a quick prototype in a couple weeks and it had product market fit almost immediately.
3:26Um so that was the pivot. It was very lucky. There's no you know we didn't go talk to like a hundred customers and take their notes and you know we built for ourselves and um I think it was one of those where the technology was changing so that what we wanted to do was possible at a time um at a time when you know people were very excited about trying AI products. I mean basically you know open cloud was happening like literally as we were building the product like open cloud was blowing up and we were like oh [ __ ] it's the same thing in many ways right they're trying
3:55to do the same thing but it turns out there's a difference between something that's open source and it's amazing but it's only a kind of tinkerer that can use and that would be open claw I think with town we've always been focused on how do you get just about anyone to be able to get value out of the product as an investor today every company in some respects is questioned about how cannibaliz could this be from any of the big providers? Um, this is like right in the [ __ ] sweet spot,
4:24just to be blunt. Like, how do you and we've got Grockbot in the most recent times. How do we think about cannibalization by frontier model providers and Grockbot in recent weeks as a threat? You want to know the the truth is I know what I'm building is a top three priority at Google and Apple like in the next 12 months. Not a top 10 priority, like a top three priority. So, you know, I when I go to sleep, I I fall asleep very quickly. It's one of my
4:52superpowers, but I do wake up at like 3:00 in the morning and immediately usually when I wake up, like some dark thought goes into there. And it's, you know, it's like roulette when you're a founder. Like, which dark thought will stop me from falling asleep again? And definitely the uh this is going to be you're like in the middle of the fairway and everyone's trying to you know is going to try to get you. That's 100% the fear. But I got to I got to say so you won't talk about Moes, right? You're like what's the mode? What's defensible?
5:20I I think h talking about modes is a little bit of a luxury and you have to be more successful than town is today for it to matter. So just like I will answer your question, but like my mindset right now is how do I get 100,000 or a million paying users in a market that has like a TAM of a billion potential, you know, paying users. Step one is like you need we have to have really deep product market fit. And I think none of the products today actually have really deep product market fit yet. Like Grockbot's really cool.
5:50It's awesome, but it's a power user product. It's not a mainstream product.
5:54Town is great, but we have a lot of work to do to make it a true mainstream product. So even before I worry about defensibility, I'm still like what is the right product experience that's going to resonate with a mainstream cuz the big players are not they're not going to innovate their way there. They will copy their way there but they have to copy someone who's been successful in the first place at building a mainstream product. Okay. Then number two like I think the product in this category that will win will have a network effect at the agent level, right? Um, and one of
6:22the features of town that users who figure out how to use it, they love it the most is something called agent to agent. And that's where you ask your assistant, your towny, call them townies, your you ask your towny a question and it realizes that it doesn't have the answer, but that the towny of one of your co-workers has the answer and it just goes and asks it the question and then that towny answers.
6:47And it's it's you to find the feature you have to go like in a subp part of the product to use it. But that is a network effect. Once you have your whole team on that, it's actually really difficult to imagine moving to a different product. And I think no one has figured out multi-user multiplayer AI today. Like I think that's the thing that will be the moat. In the meantime, right, uh you we have lots of theories.
7:09Everyone in the market has lots of theories, right? So people will say like well you'll post train custom models maybe custom models per company or per person and that will allow you to retain your users right people say hey the context about a person that's the mode and people will be less and less willing to connect more data sources so once you have product market fit with a user and they really love your experience and they've connected all the tools and all the connections it's actually really hard for someone else to go in there because you know they won't have the
7:37connections right other people think three actually the moat. There's no new moat in this market and it'll be distribution. And so it's whoever already has the users who will win. So like I think they're for me the the competitor I would worry the most about would be would be probably for personal use cases it would it would be Meta and WhatsApp, right? They're they're going to have a personal assistant that's going to come in WhatsApp. I don't know if they're launching it in a day or in 3 months, but it's coming. They already have the distribution, right? You already everyone's already using WhatsApp for for messaging. If there's an agent in there that can do things for
8:07you, it's going to be extremely powerful, right? So every company right if you you some people think it's a device like they think AI is changing the shape of software so that people will no longer ever go to websites they will never use apps on their phone the entry point for most digital interaction much like the entry point today is either like a phone or a computer or a browser the entry point will be uh an AI and so whoever owns the devices is in the best place to put the AI in front of
8:35the user and they will win but it's you know this is I don't if I think that like way if I think about all of these things I'm like oh my god what do I do like how do I how do I win given all these competitive forces. So what is the future interaction between human and agent? And what I mean by that is do we have like a consumer agent, an enterprise agent and then a hardware agent that does maybe productivity and notes.
9:01How do we think about that multi- aent versus single agent?
9:05Each human will have one, two, maybe three entry points into the into the digital space because I don't think you'll want to be like, oh, I'm doing sales. let me use the Salesforce agent.
9:17Oh, I'm doing project management. Let me use the linear agent. Oh, I'm doing this other thing. You'll want one entry point. You won't want to ask yourself the question. You just push a button and you start speaking. But there are real reasons why it may be more than one and it has to be. So, one of them is just privacy and how your workplace is going to feel about their data being intermingled with your personal data.
9:36Right? So I think you you might still have only one hardware entry point but from a privacy perspective and from a like where your data lives I think you're going to always want to separate on the data layer your personal and your work data and in town we do that for you but I think it could be two different companies that you end up using right uh like one layer one layer below but I think privacy is the main deter will be the main determinant of your data silos and and your company whoever you work for desire to own the data that you
10:06create for them right? They won't want that to intermingle with your personal.
10:09But from a usability perspective, like it's just on my phone, it's annoying that I have 55 apps and I'm clicking everywhere. And so if you move to a world that doesn't have hard interfaces because you don't need them most of the time, you know, why why would you have 50 agents, you know, at at the user layer below it's different, right? So you're an investor, I think, in in Harvey or Lagora. Lora, right? You're an investor in Lagora.
10:31Yeah. So like I think when you're a lawyer and you're talking to your main assistant about legal things in it's immediately just talking to Lora, right?
10:40Because and that might be your work agent, right? If you're a lawyer because there's a bunch of like data privacy and privilege and reasons why your work scenarios need to be handled differently. I just don't know if you're like think of it as talking to your Lorra agent. You just talk to your main agent and it just like talks in the background to Lorra or to Salesforce to whatever it needs to to get things done.
11:01What seems crazy about the relationship between human and agent today that will be incredibly common in 5 years time?
11:10You want a hot take?
11:13Yeah. So, I think you'll trust your agent to decide what data to share with other people without you intervening in 5 years. So, I'll give you I'll give you an example. Like, you put your agent in a room with two friends because you're organizing a trip and they're just asking it like about your eating preferences and they're asking it about like when exactly you can fly out for the trip and they're just asking all those questions of it and it's just your agent and you never told your agent like
11:42these are really good friends and you shouldn't share like my medical history with them. And literally when when one of your friends as a joke wants to ask the agent like, "Oh, tell me about John's medical history." The agent's going to be like, "Yeah, there's no way I'm telling you that." And it wasn't a hard rule that you ever set. Like this this thing which is like taking information that is in silos and deciding how to share it. I think we'll get to a point where we will trust agents to do that. And I know that sounds crazy today, right? Because today
12:10the way the world operates like prei is everyone as a as a human has a data silo underneath them which is their personal data their work data like and I'm not even talking digital like you have information that only you know then when someone asks you a question you are like what can I share with this human and you share it with them right and we trust the human to be the filter for where information goes and I think more and more we will trust AI to do that for us and there will probably be models that are post-trained to make sure you never ever share personal like your family
12:40information and and medical information and certain things for you know like in your work context but but a lot of info that's siloed doesn't need to be to be successful and AI works better and better the less siloed the information is like if you think about it I don't know if this is what you want on your podcast but from an information theory perspective information theory perspective like theoretical world right if you have like an LLM that had access to all the world's information right and it could do you had infinite time so it could just do aent IC search over all
13:10the data, it would be the most what whatever intelligence level you know LLM are at, it would be the most effective because it would always find the right context eventually to answer the question or to do what you needed to do.
13:22But that's not the world we live in, right? We live in a world where information is in different companies and governments and individuals like systems and there's, you know, historically because the humans are the only people who are shuttling the information around, it's kind of inefficient to to to get it from one place to another, right? We have like lots of data controls and privacy and security and blah blah blah, which is great. It's important because privacy is very important. People deserve to control and own their data, right? And so do companies. But what's interesting is what in practice if you're at a
13:51business, you find that if you give your LLM access to more information, it's more more effective at at doing what it needs to. And one way to do that, the old way, the like prei way would be to have like policies about who gets to access what and you classify data. And all this is like very timeconuming and costly. And the end result is often the information that you want the LLM to have access to. Maybe it doesn't have access to. It's stuck in someone's inbox, right? Or it's in a data system that not that's not integrated. And so all I'm saying is like as opposed to having humans in your compliance and
14:21security team over time label data and decide what goes where and what can be accessed. I think we'll just start to trust LLMs to do that. Meaning you will trust your data silo and another co-orker's data silos. you'll be like, well, I'll trust my LLM to decide what can get out of my they decilo. And so then when someone else on your sales team, right? Like very concrete example, someone on your sales team wants an intro to someone at a customer and you're like at a thousand person company. And the person at the sales team knows that there must be someone at a 10,000 person company that knows the
14:51right person at that vendor, right?
14:52Right. That customer, it's somewhere.
14:55And normally now they just go to Slack and they're like, "Hey, who's who's working with client X?" Right? Who's working with them? Who knows? But really what they could do is their agent could just go talk to the agents of everyone else at the company and all those agents have access to each person's inbox and come back and say like, "Oh, well look, like Liz has a personal relationship with a person that you want an intro to." It's not a work one, but you could ask her if she's willing to intro. Bob has a work relationship with the person you want an intro to, and they're due to
15:24have a meeting next week. Do you just want to see if Bob will invite you to the meeting? So you have the convo, and that's like a great business for the company. That's a great business outcome. That's what they want to happen, right? But to do that, right, the individuals have to trust that it's okay for some of the information that lives in and in in your inbox to be made available to other people at the company. And right now, that seems insane. You ask me what I think in 5 years. I think we will be more okay with that because in practice, the LMS will be really good at respecting privacy around things that you don't want to
15:53share. So, you don't want your salary to be shared your co-workers. You don't want your medical history to be shared with friends. There's these things that are sacrosanked and we get that. But you will be able to have an LLM that respects these boundaries.
16:03How much wiggle room do you have on error? And what I mean by that is if you have a mistake for whatever it is, you book the wrong thing, you do do execute a wrong task, how much room for error do you have and how much trust is lost?
16:17Well, my my claim would be like the LLMs will be much more effective at this than humans. I'm going to tell you a story. I once worked at a place where there was a person who uh we just done an acquisition. Okay. And the and there was an email introducing the acquisition to the whole company and this person had been against the acquisition and so they meant to reply to a subset of folks just tell them something like I can't believe we hired these clowns. The words may have been different than that and instead they replied to everyone at the
16:46company. And then that person had a nickname. It was big R like big reply.
16:50Okay. And this this person's like an incredible person. They made a mistake and it's totally fine. and everyone laughed about it and everything was good forever after right but it's a human very smart human top.1% who made a mistake people make mistakes right like Bob from accounting makes a mistake Liz from you know HR makes the spreadsheet with people's salaries available to everyone by mistake this happens all the time I think the LLM will make many fewer of these mistakes than humans pretty quickly my dearest friend is Jason Lanin who says that the biggest
17:19problem with agents is their goal seeking and he talks about his agent going off and trying to buy six AP he watches for him to increase culture in the company. Uh luckily it was prevented because they needed engraving and that was an extra step that the agent couldn't handle. But to what extent is this maniacal goal seeking tendency of agents a feature or a bug? I don't have an answer for you. I think it is I think how much you should be willing to let your agent be goal seeking and
17:48for how long you let it run autonomously is like a very a very interesting question right is it your responsibility to usher people guide them into like what is best hey we find best outcomes if you let them run 4x one way to think about LLMs right is they're just they turn energy into like GDP right into revenue, you know, like really you step way back, right? You know, cuz you power and and silicon and
18:18then you get intelligence and we're applying the intelligence towards business results. So, you know, if they get smart enough, it just creating GDP on the other end. So like do you just say like hey make money for me and then let it run for a long time and it can do whatever it want to or do we want to live in a universe where we think the humans role in this is actually to set the direction and like make sure that the actions that are being taken align with some kind of human value system. So I live in that second universe where I
18:46think it is the human's responsibility to first allocate the resources that means to say how many tokens are we willing to spend to try to get a goal to set the goal right as well. So you you set the goal and the budget and then to monitor right like the the overall shape of the actions that are taken to get to the result and how much as as the intelligence gets smarter you might say well maybe maybe the allocating of resources you're trusting an LLM to like
19:15an analyze ahead of time what it thinks the ROI is on a pretend task and tell you how many tokens you should be willing to allocate before deciding to step away and maybe on like monitoring the actions it's also an agent that's doing that for you I just don't think it's the same agent as the one that put on the course to try to get to the result at the end of the day.
19:30You mentioned the different layers of kind of the value stack there. What does the model infrastructure that you sit on top of look like? How do you think about model rooting for different tasks? Are you locked into one?
19:46Yeah, I think because we're building an application for everyone and we don't think most people care about understanding which model is better at what at a certain point in time, right?
19:55So we view it as like our job is to for what you're asking for find a model that cost effectively get cost effectively gets you the result that you want right and so you know for like concrete examples if we're generating images right we have opinions internally about when we might use like a Gemini model or an open AAI model to generate images right when we're doing voice we have opinions about 11 labs when we would use 11 labs to do voice right and and so I
20:23think it's our job to do that Because as the technology changes every day, like right literally every week or every two weeks, there's a fundamental change.
20:31It's our job to make sure you get the right the right ROI there. But it's, you know, it's it's tough and there's there's things that are just like is it the right result that that's easy for some context to know what the right result is. For others, it's very open-ended. You can't know ahead of time. So, you have to kind of guess like how difficult do I think it is and how close to the frontier do I want to get?
20:50And then the other dimension for us is uh voice. People don't like it when their their townies sound very different, right? And one of the problems when you do model routing is there's some companies like Anthropic spends a lot of time I know we make fun of them online, but they spend a lot of time actually making sure all of their model families roughly don't change too much in terms of their personality. They might be slightly more verbose or less and use different phrases, but they kind of sound similar enough over time. So if you use if you use enthropic to generate
21:19final output for your users, it's kind of hard to suddenly move to like Kimmy because it just sounds different. So people feel like their AI has been loized. So that's like you know the way I think about it for coding it matters less interestingly because for coding you're like does it work? Does the code fulfill its purpose? Right? It's like a yes, you might look at the code and decides the style that I like or not, but not really not anymore, right?
21:41Before when you're talking or speaking to a to to an assistant, if suddenly it's twice as verbose like over text messages, it's writing you eight senses as opposed to four. Like people don't like that. They will literally write tickets. They're like despite my instructions that I gave it 3 weeks ago like my text agent seems to, you know, be capitalizing letters more or stuff like just literally you're like okay. So you know the way I think about our stack is there is the part of the stack that deals with the user interface like the
22:08feel and the personality and there it is harder for me to just route wildly because I need consistency of the experience that is sometimes hard to get from other model families below that when it's just pure reasoning and intelligence and especially when I don't have to show as many of the traces to the users then there yeah I think it's very much a matter of finding using the best model for the task but you We're early in the How do you think about how a diff how different model providers impact
22:37ultimate economics of a user? And what I mean by that is like 11 Labs is notoriously brilliant but also notoriously about you know the cost of a Chanel handbag. Um uh and so my question is how do you think about model selection balanced with cost?
22:56Well, Harry, the answer there for every startup that I know outside of a very few we don't is yeah it's well we're hoping the price we're hoping the cost curve all makes it efficient in 18 to 24 months right in the meantime you're subsidizing in part right because that's what it takes to be at product market fit for these use cases because you need to use Frontier for too much of the work right so the here's I think about it like we so one
23:24of the things that does is we label emails. Okay, label labeling emails does not in any way, shape or form require like opus level intelligence. It does not require sonnet level intelligence, right? And so for that we're already we're already below frontier. And so I think that will trend towards the cost of compute over time, right? And so I'm I'm like how do I use open weight models, right? Uh how might I postrain even my own like smaller models? And so
23:54the the it's easy to say the price of that is going to be much smaller than it is today. And so for that part of my cogs, I don't think I stress out about it. And when I talk to other founders at AI companies, it is always it's also how the thinking goes. The question that no one quite knows is how much of the workload for any particular company stays close to the frontier where you know it's very expensive. And I think no literally nobody knows the answer to that. But for human level tasks, there's a decent amount of stuff like scheduling movies, working with one's calendar,
24:24answering emails that have been answered before, doing research on competitors on a daily basis. Like all these kinds of things I think are trending pretty far from the frontier, right? And you can already use open weight models to do that really, really well. And so as soon as you know that, you can you can you know and you know the price every 9 to 12 months halves. So you know where it's going to be and so that you could price your product today at a point where you'll generate 20 30% margins in 18 months. So that's the way that we mostly
24:52think about it. But the open question is at the end of the day are you left with 10% of your tasks being frontier or 20% or 30%. And we don't know the answer to that and that will change the economics of you know these companies.
25:05What percent of tasks go through open versus frontier today.
25:10For us it's mostly Frontier.
25:11Why is that? With the greatest of respects, the task being asked, I don't imagine are actually that sophisticated. And this is where like, sorry, with the greatest of respects, we talked about instinct earlier. I give instinct hard problems. Like I want Odyssey tickets at the IMAX, continuously monitor it for days by the minute that they're there. For you, in the greatest of respects, I ask like for email tagging and pre-briefs. Much easier.
25:36Yeah. Well, actually, a lot of people ask us to do hard things. So a lot of the custom workflows that people build will be quite complicated and so that's where we will use most frontier I think for we still don't use open weight for things like labeling but we will use much cheaper models from one of the frontier providers but the the main reason is because as a company our focus like imagine I can improve our cogs by moving to open weight but it doesn't
26:05give me much product advantage it doesn't make my product work better So if I have an engineer hour, what is the engineer hour best spent on? Is it taking my current AR making it more efficient? Or is it figuring out a way to grow the product faster by working on a better network effect feature or making the model better and integrating with a new data source that makes its trajectories much better for a set of our users. And we're very focused on growing the PI faster much more so than
26:33getting the ideal economics. And our economics are fine, right? they could be better, right? And I could move down the cost curve faster, but that's not the constraint to success for the business. So that's why we don't do it.
26:45On the network effect side, have there been any interesting lessons or observations? What have you learned on expansion from wall to wall? So first of all interesting aspect for us of network effects is if the company has one person who is a tinkerer and who starts to build things like team skills, team integrations, team routines that is like building those are all building blocks on town that everyone on the team gets for free then we tend to see a lot more adoption faster. And it it's it's
27:15interesting, right? Because I'm we're trying to build a product that doesn't require the tinker, right? Because for the single player experience, we want you to be onboarded and get a ton of value, right? And if you're a real estate agent, you have automations that are real estate agent specific. And if you're a salesperson, you get automations that are salesperson specific. We're trying to give that that experience to you out of the box. But what happens is if there's a power user that's next to other users, they find ways to make those other users much more successful. And I think you'll find that with a lot of AI products, right? So one
27:44of the one of the predictors actually is is there a tinkerer on the team. So one of the questions we ask ourselves a lot is can we identify those folks and can we make it easier for them to create virality for their other team members.
27:55Um and then the second observation is there are a lot of functions that are underserved by AI within companies even enterprises. So I'll give you a very simple one. If you're a sales team at an enterprise you've been sold AI like in every direction now for 3 years. Do you know what I mean? Like literally like if you're a sales ops person and you do not have 10 emails a day from like an AI company, you've you're something you've not on LinkedIn like something's wrong.
28:22There other functions like uh executive assistants, chiefs of staff, uh uh HR team members, finance like some some more junior finance team members that don't there's don't have that much AI in their day-to-day. They like really don't and a lot of their workflows still operate out of email or like recruiters, right? And so a product like town, I think often we find early adoption and growth. And I would say like some functions that seem from the outside like less juicy maybe, but actually that
28:51are really hungry for technology to help make their life easier. And so as soon as they adopt it, there's an interesting effect because they often work with like leaders or execs or people in ops teams and then we get penetration through the op teams. How important is time to wow or time to user delight?
29:11I mean, yeah, I think the only reason our product works today honestly is we have very low in very low time to value for a single user. And so what happens is single users like the product. Even for simp you're talking about like meeting briefings and kind of naysaying, but coming into a meeting really [ __ ] prepared. getting the action items from the meetings like automatically handled for you is for a lot of for a lot of roles like sales, recruiting, small business owners is like magic. So the fact that with us no configuration you get out of the box it gives a magic
29:40moment then the user is like asking questions what else could I do with this technology that's for us all the like our focus is on getting that right can we give you time to value there really quickly and then we play the longer game on all the other integrations and for us that's working really really well since we've had town and again sorry but instinct in the last two to three weeks break out seemingly so I've been pitched four to five European
30:08towns or European instincts. I mean, literally four to five separate ones.
30:12Some, oh, we're enterprise, some we're consumer, some we're both. How should investors be thinking about this space if you could advise us? We were talking about modes, you know, earlier. So, you know, we're making like at town, we make some bets, right, on why we think the product will last. I'll answer your question about Europeans, but we've made some bets. So, like one of the bets that we made is you only get one AI system.
30:35And it has a name. You give it an image. We call it a towny. And we have a whole brand around really building this relationship between the human and the AI. And for a lot of our users, that resonates like they want that. They want something like that they trust and uh that they shape and that they color that's in their image that they name.
30:54They like that a lot. And it's silly, but actually I think that is a form of defensibility. Much like Snapchat structurally in the market is defensible even though it's not nearly as good a business as Tik Tok or as Facebook or Instagram because it's fundamentally different. It has a strong opinion about how it operates. There's some people that are drawn to that opinion. So we have a very strong opinion about the relationship between the user and their town. And for a lot of our users that that really resonates. So we have that.
31:20We have a bet on network effects which we've talked a whole bunch about. And then the third bet that we make is we are big believers that through a lot of pre-processing you can get better outcomes for users. So we spend a lot of compute before you even ask a question to build a mental model of the user like pre pre-creating context in a way that allows us to be really effective at things like uh like work networking right understanding the projects that you're working on understanding your company and and you know those kinds of
31:49building blocks. So there's like three things that we think over time make a difference for a product. So the question if I were an investor is like why does someone deserve to win in Europe and is it a distribution thing?
32:00Is it a GDPR and privacy thing? Is it a like town is not in fact doing any marketing in France and so you could win in France if you're the town of France. And so you have to have some specific reason why some local company will win Endgame because this is these products are expensive to build. Like you said, Grockbot earlier, my R&D, a lot of my R&D is just keeping up with the Joneses.
32:25Do you know it's just like we need to just do well, you have to do your agent has to be as capable at least, right? It forget your distribution strategy, forget all like the fact that you're good at work, forget like the network effect features, but if codeex can do something that you cannot do and that thing is something that matters to users, it's over, right? So you always have to be like at least as good as a harness and capabilities as everyone.
32:51It's very expensive to do that, right?
32:53It's not like I have two engineers of the team trying to keep up with codeex, right? Codex is like a 100 people making that thing better. And so we have to somehow, right, be as effective on a lot of tasks as codeex otherwise the user is going to be like, why would I pay $50 a month for talent? It doesn't make sense.
33:08I'm going to pay $24.99 for OpenAI, right? And so I think that is if I were an investor, I would be like, is this local competitor have enough TAM? Are they going to be able to have a war chest that's big enough to just keep up with capabilities? And then do I believe they have a reason to win in this very horizontal market like where they are?
33:28Is hiring in the valley as insane as everyone says it is.
33:31So I don't find it crazy, honestly. Like I think when I was at Plaid and we were competing with talent for like Stripe, that felt like no harder than what I'm doing now. Can I ask what's been the hardest thing about the product build that you maybe didn't expect?
33:45The speed of the market is insane, Harry. I've never seen anything like it.
33:49Before in in the past, you know, you you you talk to customers, you build a feature, they would use it, and you would be like learning from that feature, and the learnings would go into the next feature and the next feature, and then eventually someone would copy your first feature. But then you had like you're three learnings ahead. Do you know what I mean? you'd been able to like use your product market fit to generate more product market fit. And you know for startups usually you're like milking these the these user
34:19insights for a really long time.
34:20Eventually you run out of user insights but that would take like 10 years right to happen. So you have this entire period where you can you can just because you're number one or number two in a market learn more and iterate right and it's really it's really good. The problem today is it is so much faster to build that as soon as something is working for somebody, everyone notices and is able to get there within like two weeks or four weeks like copy really really fast and learn. You can only learn at the speed of humans. Do you
34:49know what I mean? You can build now at the speed of machines but you can only learn at the speed of humans. And so you're I'm not able to extract quite as many learnings as you know that allows me to get to the next feature. So the way it feels right now is like speed is such a it's so necessary but everyone's moving fast right and and you know when we started the company like I would think first quarter and second quarter of this year my mentality is like there's like 15 competitors in the startup universe that are competing with
35:17us like maybe 15 companies that matter and now I'm probably down to like two or three competitors like I feel like you know it's mostly it's it's going to be like a only a couple companies are going to win this space right and we're like close like from the startup from the startup starting gate there is the there's the like Apple Google Space Grock uh Grockbot cursor you know OpenAI and anthropic starting gates like I'm but you have to at least you have to
35:45clear the clouds right for the startups and usually also the startups would be really fast but the established players wouldn't be that fast but you got to be honest like claude like Enthropic is very fast cursor grobbot they're operating like at a speed that is it's uncanny, you know, and one of my best friends runs engineering over there, so I'm always like, you know, whenever I talk to him, I'm I'm sad that we're competing, you know, we're competing and I'm like, that guy's good. Like, that dude can get [ __ ] done. I got to beat one of the best people in the valley at
36:15a company that has the DNA of a startup, but is operating with huge cost and scale advantages, right? So, you know, that's what's super stressful because I think you can't rest for one minute. You don't have the feeling that the competitors, it'll take them six to 12 months to catch up. Um, and I feel that like never. Yeah. Never before. But it's also the most fun time to build. So, you know what? You know, you can complain.
36:37You mentioned you mentioned the two to three that matter on the startup side.
36:41Who would you say those are and why did you choose them?
36:44No, I'm not going to say that. Not going to give free marketing. Not going to give free marketing to competitors.
36:52Oh dear. You've got You can't blame me for trying. I tried to do the Louis thorough, you know? It's like, hey, how do you think about that? like tell me.
37:02Yeah. I mean, you know, we look, it's a blue ocean market, right? You got to understand like I never when we go to a to most customers, they've not heard of anything. It's blue ocean because people people are using chat GPT as like a Google enhancer. Like that's the market. So, you know, competitors competitors are are great. They put pressure on you.
37:24They make you feel like you have to execute at a really high level. But what's important is you have a different strategy than a potential competitor.
37:31Like you you mentioned instinct earlier like I don't think instinct and town are trying to do the same thing. I don't think we're trying to monetize in the same way. I don't think so. I mean we will see endgame but I think what we do and generate we generate revenue right from companies right that are using us for work with network effects around multi multiple team members working on it. Like their product doesn't do any of that. Maybe that is part of their strategy. I see a strategy that's more
38:00like customer acquisition like with a free product that's fully subsidized right now. That might change, right? But if you look from the outside, the products have similar capabilities, but all harnesses have similar capabilities.
38:10But if you look at the ICPs where the marketing is going, it just feels pretty different to me. So I pay attention to like a Grockbot more than I would to instinct because I think Grockbot is going after a similar market to what we are, right? And so that is for me that is more of the place where I'm like how is our strategy differentiate from Grockbot? How are we going to acquire a different customer? How are capabilities and our harness going to really stand out and feel really different to users?
38:33Like that's more like my mindset than you know.
38:36To what extent is Grockbot's integration into X a feature or a bug? Cuz to to some corporates and to professional usage, it could be concerning actually the integration with the search.
38:48Well, I think they have a I think brand for them. I think some people just won't want to touch it because of brand and it's like that's just inevitable and it's you know that's just a thing that they're going to have to deal with forever. Um but from a distribution perspective uh and I think for some segments I think in early growth it is probably quite useful. I think a person on X that uses these products is not actually product market fit. Meaning that those are not the mainstream users. And you have to keep that in mind. And I I by the way I
39:17think they think about that over at at Grogbot all the time. I don't think they think winning the power user/influencer on X is where the market is. That is not where you win the market. That's the early adopter market. But can you help me understand Apple's agent roadmap? I think the problem for Apple is twofold. One, they're not a cloud company. They're just not. It's just not their DNA. They don't know how to do cloud. And the reason why that matters
39:46is because what we talked about earlier, agents are better the more data they have. And the data is not all on the phone. And and so the fact that they're not cloud is like one big issue. The second issue is they've like contorted themselves for competitive reasons around a privacy and ondevice story that is like absolutely like puts them far away from the frontier. Like local
40:14models on the phone, it's amazing, but they're just not they're just it's just slower and dumber, right, than what's at the frontier. And so as long as they're committed to this like ondevice like privacy preserving stuff, it's the privacy stance is good from a human perspective, but they've tied it too much to the ondevice. So the LA not being good at cloud then being on device and then from the privacy standpoint making it difficult even on the phone to interoperate with all of the data that
40:43they have it just it's those are a lot of disadvantages to play with. Now you know at the same time they do have the devices. So the new Siri, right, is going to be much a much better personal assistant than the I mean that's rumored, but you know, you know, people who've tried it. So when you're in the valley, you've you've you know, and so we all know it's going to be good, but I think it's going to be good, but it's going to feel not nearly as powerful as town or Grockbot. Like it's not even going to be there in terms of its capabilities. But it'll be on your
41:12phone. It'll be convenient. You'll be able to like enable more data with it.
41:17It'll have a cloud component. It's going to be good, but it's going to be like nine months away, I think, capability-wise, compared to, you know, uh, everything that we've been talking about today. And I just I don't know. I mean, they have a new CEO, and we'll see how they take it. But I think they just need to hire somebody that has totally different DNA and be like, you guys, you don't understand. Like, the way people interface with digital data is changing, and we either are figuring this out and we may have to throw a lot of our principles away, or we're just not going
41:45to win this generation of the war. And I I think that is like a a real rest for them.
41:50Are you concerned by the data leakages that we're going to have and the the kind of golden age of cyber threats that we're entering into? It seems like we've all kind of normalized cyber attacks and it's like ah ma had one had one. If you want to build AI that is used in for business use cases, you you must you cannot get it wrong. We've passed the point where humans will read every line of code. That is never happening again.
42:15The most important lines of code around access controls and things like that for systems are still being read by humans.
42:22But overall in the history of humanity, we have passed the point where we will go back to a world where humans are looking at lines of code. It's computers that are building code that is being shipped into production with various guardrails from testing to other models like friendly models attacking you so that unfriendly models can't later find exploitations. That's the world we live in. Obviously, in the history of humanity, in this new world, there's going to be points where there's bad events that happen. That's
42:52just, you know, it's a little bit like chemicals. The way I think about it, like, you know, in like the 20th century, we started to do cool things with chemicals and then we would put the chemicals in rivers and then cities downstream, people got sick. And then we were like, oh yeah, okay, let's pass like regulation like the EPA so that you can't just dump the chemicals in the river. You got to like clean them a little bit before you do. And then later you like label dangerous chemicals not as dangerous where they can go, how you get rid of them. like we learned along the way. There's a set of best practices both like from a regulatory perspective
43:20and just like best practices in industry and right now what's happened is the like cost benefit of attacks is just thrown out of whack and we're trying to figure out what the best practices look like and you can't imagine we're going to get that right every step of the way but I think we will have to because there's no way we're going back to a world where humans are looking at every line of code. Can I ask you when we think about usage, how do you define a successful user?
43:48Oh, um, well, I I just define them as someone who pays me every month. If they keep paying me, no, I'm I'm serious. I'm serious. Right.
43:56If they keep paying me, I've done my job, right? I can't think of them as the most the more tokens they use. It's a dangerous way to think about it because if you think about it as like they use more tokens every month, that's successful. What if they're using the tokens in a way where the ROI is less clear to them? Meaning they don't realize that they're using tokens to do things that they don't value as much. If you do too much of that, then they wake up one day and they're just paying you too much and they get mad and they churn off of the product. So I think you have to take a long-term perspective. The the
44:26problem with token maxing, there's two problems in my opinion. One is like companies told in told people, hey, you can use as much money as you want on AI, which is bad. like you want people to think is the ROI of using AI here worthwhile. So now you know people are not going against employees using AI.
44:43They're going they're like no no we need incentives so that you use AI for good reason. So that's like one aspect you need to think about ROI up front. But the second problem is sometimes it's hard to know the ROI of something like let me be more prepared for a meeting.
44:58How much how worth it is it to be more prepared for a meeting? For people who have back-to-back meetings all day, not having being able to in like one minute before the meeting feel prepared enough to not look like an idiot, it might be worth quite a lot. For people who have like meetings where they have someone else preparing and are presenting in the meeting and they don't have to present anything and they're just sitting there, it's not worth anything, right? So that I'm just using this example like this workflow has totally different value for different folks, but it costs the exact same number of tokens, right? And I
45:28don't think that people think about it that way. So I think of success as paying me because if you're paying me every month, that means I'm mostly doing a job of delivering enough value. When you look at the $49 or the $15 or the $99, whatever plan you're on on town that you pay me, you're getting enough value. But I'm very concerned along the way with informing you about where you're spending money because I think you need to feel like I am doing a good job of avoiding you spending too many tokens. So, one of the most popular features for us over the last month is
45:57we started sending emails when it looked like you had like rogue routines, like routines that were just costing a lot of tokens and then people were like, "Oh, thank you. I trust you now. I feel that you're looking out for me using the product badly." And that's the part for me. I don't know how to measure it, but I want people to success for me is you pay me and you trust that we are the right platform that helps you both use AI, but do so efficiently. And I think if we can do that, we can we can have a pretty decent business.
46:25Yours is $14 a month, $49 a month, and $99 a month.
46:30Yeah. And $1.99. Correct. But the 15- Which which is the most profitable segment and which is the least profitable segment? And the reason I think about that is like my friend Jason Lamin, he obviously pays for like Anthropic Pro or whatever it is, $299. And he spends about $15,000 of tokens. He is the worst customer for Anthropic, but he's on that like Promax individual plan.
46:53Yeah, we don't we don't have a max plan and we have users who ask for it and I've been asking myself like, do we let the whales have a max plan? Because from a marketing perspective, it's useful.
47:01You know, they're just advocating for the product all the time. So, I have thought about that. Um, yeah, the $15 plan is a really good deal, I would say, for users. It's mostly I would say it's like a we use it as a way for people to use the product enough that they realize they should pay pay 49 where the product is really powerful. So 15 has the worst the $15 plan has the worst unit economics is the most subsidized and then I would say probably the $99 plan is the most profitable overall because it's like a power user but it's not a
47:30power user that's like trying to like you know spend on limited numbers of spend but we also have usage based pricing right so what happens for us is once you run into the plan limits mostly you go to usage based and so right like the the we try to adapt the spend to the user there's can you choose one outcome for 100 million consumers paying 20 bucks per month or a million customers paying a h 100 bucks a month.
47:58Not the more more users more users paying less.
48:04Because I think over time in in work in the work setting AI will be used to do more and more and more for people. So I think the long-term potential for growing for like NR driving more revenue per user is extremely large over the long term. So you want to acquire the users in a paying motion because you want them to be for work use cases because you will keep finding more ways for them to use AI to generate business value for themselves. Whereas in the personal sphere it doesn't feel like
48:33that to me like you know I only have so many like restaurant dates I need to book with my wife or or trips I need to organize with my friends. I only have like I only I only have so many like personal like doctor's files that I need to send to a new doctor. Like there's only so many of those things and when I do those things I save time and time is worth money. But on the business side when I create something that generates value for the business they make more money and then they want more of that thing. So like like a clear example for you if you want to like a recruiting
49:02firm on the platform they can take more clients because of town. They've used town to automate enough of their recruiting process that they literally take more clients. And for them taking an incremental and without hiring anyone, you at this recruiting company, one more client is like an extra $3,000 a month, right? And they pay they pay us like, you know, across all their users like $500, $600 a month. And so the like ROI is like super simple for them for a business use case. They're like, "Oh, I
49:30pay $600 a month and I get $3,000 of revenue." And that is like that makes sense. I like that they're making more money. everyone's happy and I think for them if I could show them the way that they could take another client and even if it cost them another $500 on town they would be willing to do that and so I think the elastic like the the growth potential on the on the business side is much larger so I'd rather have lots of users paying us less because I think over time I can show them that I can deliver more and more value and it's worth it for them to spend more and more on town what is town not able to do because of
50:00model capability that you think will be incredible in two to three years I mean voice A voice is so obvious. It's I mean it's happening right now, but it's not voice like you just speak to it. I just mean conversational. Like I like would you be would you be an investor in 11 Labs at a $22 billion price?
50:20I think on 11 Labs like we're users of 11 Labs. I mean I just think it's just they sound the best. I'm not paid. I'm not an investor. It is very expensive.
50:29What I don't know is if it tops out and that's I think the risk for something like 11 Labs. Meaning like we just get voice is good enough and then you can get it. I can put, you know, open weight models on base 10 and get it, but it just doesn't feel like that right now. I just don't know how much runway they have before it reaches that. And so that's why I'm not saying I'm bearish. I really like that company, but like 22 billion is a lot of money. And um and how price sensitive are you in a year or two? With the greatest of respects, right now you can you can burn cash. It's about PMF and growth and
50:58beating others. in a two to three year where you're bluntly trying to make economics work in a much more efficient manner. Ah, if we have two to three million users using voice, dude, that's that's a hit to our margin profile for sure. I mean, I care a lot more about that time. That's why I'm saying like if the voice capability, it'd have to be like maybe twice as good as today, especially tone and expression and like the emotional read. Like once you solve that, I would want to go as cheap as possible because especially for like
51:28once it feels good enough, it's almost there. Like I don't need much better.
51:31But you know on the margin profile stuff, I don't ever think of it as burning money. I don't that's like my mom, my parents would not be okay with me saying words like that. So I think we're being thoughtful in our spend in order to optimize for growth in the short term and gross margin in the long term. The voice is not though where I'm really stressed out about it honestly but the you know there is a what are you really stress why are you really stressed out about it it's just I think it's the percentage of tasks that are frontier because on
52:00everything else I can imagine getting the prices down but you know the thesis that I just said before is over time there are more ways to use AI to generate more revenue for a lot of companies the implication there is it's like there's like things at the frontier that generate more revenue and the problem with the frontier is I have zero pricing power at the frontier and I mean I think this is What happened to cursor right at the end is like you can have huge market share and be customers love you and everything but if you're if you're paying your suppliers and competing with your suppliers at 70%
52:29margin eventually it gets like a little bit difficult and so you know the that that is the part that I'm worried about the endgame if we are but again I have lots of ifs I have to get to tens of millions of users they have to be paying I have to have a lot of scale and then I'm like at a place where I'm still competing with my suppliers I'm still competing with open AAI and anthropic and I'm just giving that money for the 20 or 30% of workloads that are at the frontier for me and that's what makes the economics not work and that's the that's the part where at the end of the
52:57game I need some I need some solve for that by then I don't need it right now the reason that's the only problem is that's the only part of my economics that's different from somebody else's okay so then there's the macro question which is is all AI you know is there not real product market fit for AI products because it's all subsidized right that would be like the other take that some people could have but otherwise as long as you're not competing with your suppliers you have the economics as your competitors and so then your ability to drive margin usually is driven by the competitive landscape more so than anything else right and so the fewer
53:26competitors you have the more margin you can have you are competing with your suppliers I mean like Astra you see you see as a direct competitor correct totally I am today 100% I am today yeah but the percentage the percentage that was a face the I mean I am competing with Astro but there's still the the it's the open box problem you would be shocked at how many people just don't know what AI can do, right? It's like the problem is having a product experience that gets a normal person to
53:56get value out of AI is really hard.
53:57That's why when people use town, they like it and then they start paying for it. like the the the the payment rate for us on acquisition is like more than 15% of users who try the product end up paying for it which is extremely high for PLG because the value delivered relative to what they were getting out of chat GPT is just huge. Yes, I'm competing with what what did you crack that other people didn't to get that 15%. It's the only the really insight behind the
54:25product was if you ask people upfront to connect their email and their calendar, you can know enough about them that you can suggest tasks that AI can do for them. That's like the only insight. And if you're a chat, if you're working at OpenAI, I'm not being I'm sorry. This is where we joke before about me being more mouthy and gobby. Do it. Do it.
54:45Is that that is that that insightful? My chat GPT is always like going here's all the things that we want from you and I'm like no way no way read email abilities no I think well I think their suggestions are I think their suggestions are just like plain bad to be honest but they didn't even have suggestions until a few months ago the delta is this if you want to use chat GPT you don't have to connect your email they just don't force you to do it they ask you a bunch of times to do it now because they realize the value is helpful but the base experience they're trying to show
55:15someone normal hey you can have value in this product just cuz you have a chat box. And that's how most people experience it. Our approach is more like, listen, you have to connect email and calendar. You cannot use our product if you don't do those things. But if you do those things, we can do all this magic for you, right? Here's what we know about you. Here's work that you normally do. We'll recommend automations that automate that part of your work.
55:35That's the that's the part where people are like, "Oh, that's really cool."
55:38I think of it a bit like a hard pay wall. You know, when you land and it's like, "Hey, pay your monthly subscription." You're like, "Hey, connect your calendar and your your email." What percent churn at that moment?
55:5130%. Right off the bat. Yeah. How do you get that down?
55:54You got to be willing to take that hit.
55:55What's the biggest internal product disagreement you guys have today?
55:59We have product market fit for like some purely personal use cases that we didn't expect, you know, and the problem is it's like it's like market like families like parents parents and families. There's like tremendous product market fit for town there because schools you don't have kids, right? You have Yeah. You have a girlfriend, you don't have kids. So, um, schools in America at least send a lot of emails and they have a lot of like portals where things have to happen for
56:28sports leagues and they're like this kids reports and there's a lot of scheduling for kids that has to happen for like haircuts and summer camps and all these things. and our products because it's really good at email and it's really good at the scheduling stuff. It it really has tremendous product market fit for families. Um, and we have like a marketing so it has the product market fit. The question is like do we market to this group and do we spend time on it? Because it's a great group and it has willingness to pay but
56:58it does not have the willingness to pay of a mid-market firm, right? It's just it's a different look. It also doesn't have the like virality and expansion of moving across an org. And yes, you can go across parent groups, but it's not like you get into a Revolute and then Revolute has 7,000 people. That's a big [ __ ] expansion if you can nail it. Yeah. All the people in Sonoma who have kids under five.
57:25Yes. But it jumps. I agree with you. And so I think the discussions that are being had is like it's good growth but it doesn't it's it's not for monetization. You have to believe something like those people will then bring their town to work use cases in places that we wouldn't be accessing as quickly or you have to believe that the word of mouth is incredibly powerful.
57:45And so the the interesting thing about the parents for us is they do talk about the product a lot in like like their WhatsApp parent groups in like Facebook groups and places like that, right?
57:58There there is network virality that I completely especially on the community groups. Yeah. Yeah.
58:01But I think you know we can't do all the things. So you know to your point it's like well we are a monetized platform right and so our metrics are ringing month over month right revenue is what matters to the business. And so, you know, it's why it's an argument because you're when you find product market fit somewhere you don't expect. You have a few choices in life. Like one choice is you're like, I love these users and I love parents. I like love the users, right? I love the use cases. The use cases and the value super clear, but it doesn't it's not fully aligned with how
58:29we've thought about the business growth. But but I think that's why we're having inter interesting thinking internally because we're like is this if we look around enough corners is this worth it or you know should we should should we be more focused on our existing strategy which is fun when you build a company you learn things from users and you got to make the right decisions.
58:50What are you guys at revenue wise today?
58:53Uh no sorry you got to you got to understand it's like it's like ping pong. You give it a go, you sometimes get hit back. Okay.
59:02You know, and and it's like that and we're like fundraising or like it's like I use I will use those moments to create PR and growth for the business. I'm not quite ready with that one. Do it yet, dude. Dude, 100%. And you know what? I would advise you to always separate moments. Too many times I see people like combine a fund raise with a revenue milestone. Do not do that. Those are two separate PR moments that can be made into two big moments, not one. Why would you why would you amalgamate them and lose the ability for two hits?
59:32Yeah. The the the press, I think, is more skeptical of It used to be once upon a time raising at a certain valuation was so rare that like you could get publications to now the publications want more. They don't want to just be So that's one I'm just like, dude, you're see you're seeing a lot of skepticism on the space itself. You know, Instinct raises it $2.5 billion um with no monetization.
59:59Do you think this skepticism around the space is warranted?
1:00:01I mean for us we have the revenue and the growth. I don't know what you know competitors growth is. I think it's if there is a path if you can believe that some of these companies can get to tens of millions of people in the products in an area where the product will be the entryway for people to do digital things right that they're doing in apps on their phone right now. If there is a winner there that comes out of the startup universe, there is like a giant company to be built, right?
1:00:31The billion dollar price for the new round, did it start there or did it get ratcheted up and up and up?
1:00:38I Yeah, I can't I can't deny or I can't confirm or deny.
1:00:45I love I mean, I will not let you take any in any moments for me away from me.
1:00:52You're not commenting anything and I'm not even prying, but like the oh index is doing it. Oh, index not. What's great for you is this all just PR. Like your name's just everywhere. It's pretty good, man. You're you're amazing at trying the uh I'm old, you know? I'm I'm like I'm like 47 years old. I don't even know how old I am. That's how old I am. When you know you're old when you don't remember if you're turning a certain age. So, I'm 47, turning 48 in a few months. And um in I've been around for a while and
1:01:21there are times in my life where publicly I've done things that I'm proud of and publicly I've done things that aren't that I'm not proud of. And um so the reason I mention this is like I I don't think it aligns with my value system on anything to like create PR just for the business. I think I want the PR to be created by my users because they love the product. So if you ever see any news about town that you know good or bad that is it's I'm not out there creating the PR. That's just not and that's not just my way of operating.
1:01:51I think that's I think that's a mistake that respectfully I would push you to change and I Yeah. And I would say like look at a whisper flow as an alternative. Not a hugely dissimilar uh PLG motion. Um in all candid I think they've done a brilliant job at generating PR themselves through their own content through content that their users produce. Sure. Blake content is a hack to customer testimonials.
1:02:17Totally. I I I agree. I just don't think a fundraising story, you know, is part of the universe of things that I would want to like create a PR moment out of. Um, so like not the kind that you're referring to from from, you know, so I I do want to make a point on the on the fund raise because this is as an angel.
1:02:35It's not about right. It's not not about us the fundraising in general is you you kind of mentioned you know if where it started like there are there are these companies out there this goes back to the ethics and who I who I am like I have seen deals where it's like I invest at like 200 and then the announcement is at 500 and then what you learn is that like you know they raise 65 million and like 5 million's at 500 and the other 60 is at like 200 or 300, right? There's a
1:03:03whole lot of that happening for sure in the valley. Personally, I I don't think it's ethical. I don't think it's ethical towards employees. You know, most of all, if you're not I mean, maybe when you hire someone, you tell them for sure because it's like the dilution wasn't that number one. It's not where most of the demand was, right? It's not how you should be pricing people's offers. You can't I don't think you can look at someone in the eyes and say an investor that made 80% of their investment at like a 200 or $250 million valuation,
1:03:32but hey, I'm you know, they they put the last 20% at 500 and that's what I'm going to say. I just feel like I just don't like that. I don't feel like it is right.
1:03:41Uh dude, we're going to do a quick fire round. Okay. What is your best angel investment?
1:03:48Oh, it's either base 10 or modal right now. Those are the first two that come to mind. What's the bullcase for Town being a hundred billion company? What is needed to happen in that world?
1:04:00I think if we can get about 10 million people paying for the product, we we can get to that.
1:04:08I mean our Yeah, we make over 700 $700 per year per user today.
1:04:14How does that compare to Dropbox? Cuz Dropbox must have way more than 10 million users.
1:04:19You have to have the growth, right? It couldn't be I couldn't terminal at 10, right? I'd have to believe that I can keep getting a good rate of growth. The problem I mean I'm pretty far from Dropbox. It's been a long time since I worked there, but I think there was a huge free huge pack of free users that were very costly on the cost side. And then on the paying side, I don't remember if the number was like 10, 20, 30 million, but it did, you know, it did flatten out at some point and there was no way to generate more revenue or growth from the users. I think what's different in the AI space is like I
1:04:48think you should be able to as you do more like once you have a company on a platform using your platform as the core part of where AI works happen you can you you should be able to generate increasing revenue as as the token spend goes up.
1:05:00Who would you most like to add to your board who you do not have?
1:05:05I think for the next board member I I would love someone that's kind of CFO like late stage our business is going to be like the economics are going to have to be really really good. I know this sounds weird, but I think you need if you have a board member with real operational experience on the on the on the finance side, it's going to be very helpful as you scale this kind of company. There's just a there's a bunch of stuff like we're going to have to buy compute at scale. We're going to have to be like very very good about thinking about token spend. So, it's it would be someone with that background. I know you're making faces. You're like I just
1:05:35I'm not a big that was sooner that was sooner than I thought though. I I get that need, but I thought that would come in a couple time maybe. But I think I think we're in growth investor land for the for the next round. So I think once we're in growth investor land, they they will they will ask for me to have they will want for fund raise metrics that you know I can really defend and I think having someone with that background will be helpful.
1:05:57Why don't you subsidize completely? I'm I'm being serious. You could raise another 200 million more and growth is everything.
1:06:04Why don't you just go [ __ ] it, burn the bows? It's a it's a good question and I I think I I would be lying if I said there aren't mornings where I wake up and I think about it. I believe that to prove value on the business side, you must make your customers pay. So I do think there might be a world where our where the PLG part is much more subsidized. But as soon as you get three to five team members, I really want to make money on that side. I really want to make sure I'm delivering value. I'll
1:06:33give you a story. We we when we launched the product initially, right, for the first five months, not launch, but we were like in private beta and then we opened the beta, we didn't have pricing, okay? There were users who were spending, I [ __ ] you not, like $2,000 of compute a month, $4,000 of compute a month. There's someone on the platform who'd spent in five months was like $26,000. Okay? And because there's no push back on the token spend, right?
1:07:00There's no push back at all. So I know I know you're making face. it was one that we would like call them and we'd be like look like you know let's let's figure it out like you know you're using the platform because you could just create like routines to automate more and more stuff but is it really bringing value to them so anyways the reason I I mentioned that is I'm a big believer that getting push back from the market about where you're delivering value and where you're not is really really important there would be ways to subsidize and do that so for example I could make the plans much cheaper I could make them free I
1:07:30could give free tokens to businesses but what I've learned is like on the business side, they also don't like it if you don't charge them because they don't know how much it's going to cost one day. They want to know how much it's going to cost one day. You can't sell to a 500 person company and be like, yeah, just use my product for free internally.
1:07:47So, you get a bunch of usage, but then one day I'm like, I'm going to turn it off and all your business processes are running on it. So we the way we've approached it is on the growth side we may or may not subsidize more and because we're emphasizing growth but I really want a real business when a company is on this product and we have a real business when a company is on the product and I'm very proud of that because I think that is the ultimate test of whether you're building something successful if you're not a pure consumer company and I'm doubtful of pure consumer adbacked for AI for a
1:08:15couple reasons like I think the the tokens are way too expensive to do adback now and then number two there's an incentive problem with ads And I think people are going to want assistance that that are theirs that are not being polluted by outside incentives like ads into the trajectories that they give you, right? So if you ask to book like a flight and you know it uses an airline that is like paying for that flight to be recommended to you, that doesn't feel good, right? So I'm a big
1:08:44believer that actually the economy around assistance will be paid for and so I just want to pay for it as soon as possible. What person if when you open Twitter would you be most thrilled to see love town?
1:08:58Elon Musk cuz he has a competing product and it's Elon Musk.
1:09:05How has your hiring process changed in an AI world?
1:09:08Well, you know, we have a weird hiring process. You want to know a fun thing about our hiring process? If someone on the team has worked very closely with someone else, we don't interview them.
1:09:19Yeah. What? Why? If it's a top person because why would I I just sell. I will just sell. So, it's it's it's very rare that it happens, but it has to be someone that they've worked extremely closely like literally like next to and they're like, "This is one of the best people that I've ever worked with." And for for like an we're just like, "Let's go." Because it's it's I know it sounds odd and people are going to like comment like, "This guy's a total idiot." But a person that I trust that's great on my
1:09:48team, like great on my team, they tell me this other person is like one of the best people that I ever worked with and then I'm going to make that person like spend eight hours doing stupid whiteboard interview or like par makes no sense. So either I don't trust my employee. So there's culture match. So we will be like hey come in spend some time with us you know like you can code with us if you want to. We have to sell because we look you know if you don't interview somebody they're also like what kind of clowns are you? You're not interviewing anyone. So we will like allow them to get signal about us but we are not evaluating whether they can do the core role.
1:10:17Brian Singleman who invests in funds and then invests in the companies beneath those funds has a rule that if the manager is like balls to the wall I am all in on this company he'll automatically write the check. Kind of the same. You trust the person, you trust the layer beneath them. So I totally get you there. Um what percent of developer salary do you spend on tooling? So Mark Beni off said at Salesforce we spend 300 million on anthropic. They spend six billion a year on ange 5%.
1:10:44I mean the run rate's at least 75k per employee per engineer split between core code and cursor.
1:10:52Devon cloud uh codeex and then town. Devon's made like a weird in our we use Devon a lot.
1:11:01I'm like adver advert I'm good advertising for for Devon right now. uh for a lot of bugs that come in for a lot of like simpler little things or little like visual tweaks we are kicking off Devon cuz we just find the team experience and Slack's really really good. We have a few people who use cursor for like more visual the front end. The model's really fast, right?
1:11:21Composer is really fast for front end. And then I would say it's probably 50/50 right now between Codex and Cloud. And that's obviously changed a lot. Like I think 5 months ago I would have said it was mostly Claude. But the new Codex Codex is really good. The mobile experience is really good.
1:11:34What is that in a year? Is that 75K 150 or is it 25 as costs come down?
1:11:40You're just asking an ROI question, right? Think of it this way. People always ask me, are the teams bigger or smaller with AI? And I'm like, hm, okay, imagine you're a normal company and you have a million dollars of revenue. Okay, and 800K of cost. So, you make 200k profit, right? The 200k, you can hire one engineer with it. Okay, if the engineer can't make you more than 200k in revenue, you don't hire the engineer, right? And you take the money in your pocket as the business owner. Now, AI
1:12:10happens. And AI means that suddenly that engineer can generate more than they could have before. So maybe before they could only generate 150k of revenue.
1:12:19Maybe now they can generate 250k of revenue. So suddenly AI makes you hire the incremental person, right? One more person than you would have because there's an extra 50k of profit for you to make by by hiring the engineer, right, in the new world because they're more efficient. So just the the the reason I I I this is how I answer your question is like we're at a stage of the business where like I'm like there's gold littered everywhere in front of me.
1:12:43You know I have like customers they like want integrations in order to like sign the contract. I have people who want audit logs to sign the contract who want like SSO to work with phone numbers to sign the contract to be bigger. I'm like sitting in front of that. I have like a Dex product where people want more exports in order to like use the product more. It's all gold all in front of me everywhere. And my limiters are my ability to hire, right? How much funding I have and the growth rate of my revenue, right? Because I don't want to get too ahead of my revenue. So if you told me that there were better models
1:13:12and I could spend more in that's easier than hiring to do the high ROI stuff that I'm like the money that I'm leaving on the ground, I would do it immediately. So that's like the level at which I think about it today. So I think about our global spend on like compute you know like whatever a million or whatever it is and on an annual basis and I think like roughly like it's four engineers maybe a little less like three engineers all things told with equity maybe it's more like one and a half engineers am I getting one and a half
1:13:41engineers in Silicon Valley at our inflated rates from the yes of course I am so like it's not even close I'm not even close to the place where I'm like are we token maxing wrong it's not even like ballpark there and then I think the other thing that we we don't contemplate enough is like do we see the tipping point in other categories that we've seen in coding, in legal, in sales, in marketing. Final one for you JD. Uh what are you most excited for in the next 10 years? Well, it's definitely my kids. Growing up with my kids and getting to spend time teaching him things like math and
1:14:10playing soccer with my son and that's 100% what I looked forward to the most.
1:14:15But that's not what you meant. You meant what do I look forward to most in the universe? Well, I am a believer that even though people are very skeptical about AI and I understand why it may be scary uh and why any change is hard for humans or anyone to take on, myself included, I do think we are getting closer to a world where um people have more of the things that they want and can do more of the things that they want
1:14:44to. So, I just hope we come out of this with a better better a better universe, like more more money for everybody, more ability for everyone to uh do the things that they want to. I And I I truly believe that like I wouldn't be doing what I'm doing to make money. I'm hoping that I'm I think I'm doing it because I hope we can I'm doing it because I hope that we can remove a lot of the toil uh of people's day-to-day through this technology, not through just town. I think, you know, AI will help us make
1:15:14drugs and will help us build faster in the physical world and well people be able to live further away from cities because they can self-drive in which means they can have bigger houses with pools and be happy. Like I'm very very much an optimist.
1:15:26Dude, I so appreciate you giving the time today. I know it's a very busy time. You've been amazing and I can't thank you enough for putting up with my slightly pressing questions at points.
1:15:36Every every bit of skepticism I would say is something that does keep keep me up at night. But I think there are there are paths through the dark forest and there's a giant treasure with only one or two dragons at the end of it. So got to go for it.
