Ep 13 - Set the Mood

[00:00:00] Speaker A: It's interesting what you said about the bar. That AI has changed. We see it and hear it from our users. Six months ago, you could not have an agent answering your phone. Now they're like, can I get it to say this exact thing in this situation? But I don't want them to do this and change. And we're like, you know, it reminds me of the Louis ck Like, you're in a chair in the sky. Can we, like, relax for a second on exactly what entertainment you get while you're in a chair? Welcome to the off site podcast. I am your host, Jordan Gahl. This is where I team up with friends to catch up on our work and just as importantly, what's going on beyond the work. As always, this podcast is brought to you by Rosie, the AI powered phone answering service for small businesses. Welcome back, everybody. Another episode of the off site podcast. I got two friends with me today. Craig Hewitt and Chris Gimmer. Gentlemen, thanks for joining me again. What's up? [00:00:53] Speaker B: Hey, man. [00:00:54] Speaker C: Too much? Just hanging in there. Cool. [00:00:57] Speaker A: I usually do this on Fridays. Today's Thursday. Tomorrow's Halloween. There's gonna be like 50 kids and a bunch of chaos in my house tomorrow. So we're doing this today. I want to start off with a conversation that I was having on Twitter with our friend Aaron Francis about music. So I gather Aaron listens to, like, you know, grown men crying into their beards and is surprised that it affects them in. In like a. In like a negative way. And we had this conversation about music. What kind of music you use to get into the mood for work? I want to ask you guys, what, what do you do? You go right to podcasts. You do music. You do hip hop about, like billions of dollars and Rolls Royces. Do you? What do you do? [00:01:37] Speaker C: To be honest, so I don't know if you knew this about me. I used to be a DJ back in the day and university. That's what I did on the side. [00:01:44] Speaker A: So you know music, but have you kept up with it? [00:01:46] Speaker C: I'm gonna sound like one of those old. Okay, so I would say I kept up with it, but I have to say, like, I don't really play music in the background while I'm working. I just. I just can't do that, you know, But I distinctly remember, and this is going to sound like super corny. When I was working in the government, before I quit full time to go to go on the business, I used to drive into work and at this point, like, I was, you know, doing the side hustle. Thing and trying to get all that going. And I used to listen to, like, Wiz Khalifa, and there was a song. I think it was like, the Race and like, one of the lyrics who talk about, like, making a million dollars and stuff like that. And I used to go into work every day just like, bumping Wiz Khalifa and be like, one of these days, like, I'm gonna make a fucking million dollars and quit this place. And it was like, you know, there was some inspiration there. And so that was. That was kind of my thing back in the day, was like that. That hip hop, that, like, hustle, you know, gonna make it. And so, yeah, I used to love that stuff, but, like, I don't really bump it at 9am While I'm, like, getting. Going to work or while I'm working now. But, yeah, so that was kind of my thing. [00:02:54] Speaker A: You step it up. You need to put the baby aside. Put on a wiz. Put on wiz. Okay, so that's. That's pretty close to, you know, to. To where I'm at on music, but I do listen to it in the background regularly. I know Brian Castle only does music with no lyrics while he works. Craig, how about you? [00:03:14] Speaker B: Yeah, I'm pretty close to Chris. Like, I'll listen to music. I never listen to music when I'm working. Like, it's silent or it's at the coffee shop or something with background noise. If I really, really, really have to hammer on something, like, I don't code, I vibe code. I don't code, but if I had to, like, write a really good landing page or an email or something like that, there's this, like, focus app I have that rebranded to something super shitty, and it's called Suka S U K H A. And they have this, like, electronic vibe kind of track on it that I'll put on. So it's just like, you know, kind of thing. [00:03:53] Speaker A: Repetitive. [00:03:54] Speaker B: Yeah. And I'll just hammer on that, but that's it. I don't listen to music ever when I'm working because I just get distracted. Okay, interesting. [00:04:02] Speaker A: Maybe I. Maybe I like being distracted or I like having half the focus, but I'm also on calls. [00:04:09] Speaker B: More than half the time I'm working, I'm on calls. Okay. Okay. [00:04:13] Speaker C: Yeah, I've been. I have to explain to my wife that, like, I can't multitask. I can only focus on one thing at once. So I'm like, if she tries to talk to me, and I'm like, in the middle of, like, doing something, and and she can tell and focus. I'm like, you have to tell me to stop what I'm doing because otherwise it's just. I just can't process it. So with music, it's kind of the same thing. Like I just, I'll get too distracted and I won't be able to focus. [00:04:36] Speaker A: Okay, so you live the concept of wired in like Mark Zuckerberg in the movie. For me, it changed. It was a New Year's blog post like 15 years ago that I read and it was talking about the author. The guy who wrote the blog post realized how music was impacting his mood. And he, he. I think he was in finance or something. And he was like, all these young guys that I'm competing with, you know, it's a. Trading is like zero sum. Someone's going to win and someone's going to lose on the trade. He's like, they're all like doing bumps of coke and, you know, wired up and trying to like get to the boat in Miami with. With the girls. Like, completely different mindset. And he was like, I think, I think I need to find a way to pump myself up. And he discovered like rap music and how much that changed. And so he wrote about it as a New Year's blog post. Like over the last year, this is how I've been able to kind of tweak and engineer my mindset, my aggression, my competitiveness. And I was like, I think I'm going to try that. And that's basically what got me into hip hop for the first time in my life. Yeah, I think, I think it works. Makes a difference. [00:05:39] Speaker C: Yeah, I resonate with that. But like, not literally while I'm working. Like when I'm in the gym, I want to bump 50 Cent. You know what I mean? I want that, I want that gangster stuff while I'm pushing weight. But when I'm trying to focus on work, I just find music's too distracting. [00:05:56] Speaker B: Okay. [00:05:57] Speaker A: I think I have difficulty focusing on one thing at a time. So a little something with lyrics off to the side actually helps the focus. [00:06:05] Speaker B: I have a related question that I think that it might be interesting to. I want to hear your guys perspective, but for everybody else is. I think we're all at home right now, right? [00:06:13] Speaker A: Yes. [00:06:14] Speaker B: I am actively looking for an office to go to three days a week. I have a whole room here at home and it's got all my stuff. But I want to leave and go do a thing and then come home and have home time. How do you guys view this how long you. [00:06:30] Speaker A: I want to like dig into this a bit because I. I have a lot of the. It's been bubbling up for me more over the last six months. [00:06:36] Speaker C: Right. [00:06:37] Speaker B: We. [00:06:37] Speaker A: We just moved here three years ago and I have this great home office and I'm up on the third floor. There's a bath. Like I got everything I need, but it's so comfortable. I often find myself like I've been meaning to write this investor update for five days. Let me go to the coffee shop and then I finish it and then I come home and I think that's funny. That works every time. So how long have you been working from home that this is bubbling up for you to the point of basically justifying it? [00:07:04] Speaker B: Forever. [00:07:05] Speaker A: Okay. It's like the cost is part of the friction. How do I justify it? So that's on one side of the scale. The other side is, well, productivity, happiness, focus, all this other stuff. So at this point, that weight on that side is overwhelming the 1500 bucks a month, 2000 bucks a month. I don't know if you can do a wework thing for 500amonth. Like, how do you think, how do you think about it? What do you want out of it? [00:07:28] Speaker B: Yeah, no, I mean the cost is minimal. Like here in our little town, there's a place that like a. Just little private, little. It's a house they converted. It has like eight offices and they're like 700 bucks a month. Okay. [00:07:38] Speaker C: Right. [00:07:39] Speaker A: A couple of bills, some lunch, it's an extra thousand bucks a month. 1500 bucks a month at most. [00:07:43] Speaker B: Yeah, but figure like what you're worth per hour, that's like two hours a month. Like can I get two extra hours worth of work done? Yeah, sure as shit. Like each week. Probably. The only downside is like the dad cab scenario where like yesterday my son texts me at like 15 minutes after school started. Hey, I left my computer at home. Can you bring it to me? If I'm at the office and it's like 10 minutes to get back and then 10 minutes to the school and then 10 minutes to get back to the office. [00:08:06] Speaker A: Sure. [00:08:07] Speaker B: Whereas if I'm home, like I'm literally on a call with the team, I grab the computer, walk out the door, go to the school and come back and it's all like all good. I think that's the biggest reason not to do it is it's. It's not as convenient for all the non work stuff. [00:08:21] Speaker A: Yes. And I love hearing the kids come home at whatever it is, three o' Clock. I hear them out the window. I open the window, I yell for them, I go downstairs and meet them and then I come back up for like the final hour or so of the day. So that, that, that for me, same thing. That's actually what I would miss. But you're saying not five days a week, nine to five, few days a week, just a second place. Yeah. [00:08:43] Speaker B: Or even most days, nine to three. Because my kids get home at three too. [00:08:47] Speaker A: Okay. Chris, are you productive at home? [00:08:49] Speaker C: Yeah, I think so. I mean, so back in the really early days of Snappa when I think it was like four of us, I thought, oh yeah, maybe we can do this like hybrid thing and get a shared workspace. And there was like a really cheap. It was through like Invest Ottawa where used to live at the time. And so we, so we did that. And you know, the first week or two it's kind of cool. Like, oh yeah, we got our office space or whatever. And then by like the third month, no one went in anymore, including myself. [00:09:16] Speaker A: It was optional and it turned into the option that was taken was I'm not going to go. [00:09:20] Speaker C: Yeah, exactly. And, and so it's kind of same thing. I have a really awesome home set up here. It's great. You know, my wife's stay at home mom, so we have breakfast and lunch with, with our son every single day. And then I go to the gym, you know, four days a week at like 1:30 kind of thing, which I. [00:09:40] Speaker A: Find like middle of the, middle of the day gym guy. [00:09:42] Speaker C: I'm a middle of the day gym guy. And it's great. So I don't feel like, you know, slaving away in this office like all day. It's like I get enough breaks. I see my wife and my kid, I go to the gym. You know, I walk to the gym, which is, which I like. So yeah, I feel like I'm super productive when I'm here and I don't feel that I really need to get out and get into an office kind of thing. So that's, that's just me. But I know there's like, I have friends that do the wework thing and they're like, there's no freaking way I can work from home all day. Like it's just not going to happen. So I think it's just totally like a personality thing. [00:10:16] Speaker A: Yes. No, no. Right or wrong. Yeah, I would like to find a balance. And I do. You guys get office envy when you see some people's offices or like the offices of famous entrepreneurs or I don't know. You see Albert Einstein's office, you see Steve Jobs office. You see, like, these people that you admire. I do fantasize about creating, like, what is my interpretation of an ideal office? And I have that in mind now much more than over the last few years. I'm like, I don't want to go anywhere. This is great. Now I'm starting to think, like, oh, actually, it would be nice to take a walk. And I. If I'm honest, I look when I'm driving around town and when I see empty storefronts, I'm like, that's kind of a fun little idea. We'll see. Craig, update us if you end up doing it. [00:11:02] Speaker B: Yeah, I'll. I'll probably try it because I've. I've literally never done it. I mean, this is 10 years since I quit my job. 10 or 12 years. And, like, I've always worked from home, and, yeah, I'm ready to do something else. [00:11:14] Speaker A: Yeah. I talk about this with my younger brother, who's now in between things. He sold his business, like, six months ago, and he's looking for the next thing, and he's in Manhattan, and he goes out and meets friends and networks and gets connected to friends of friends. And his big thing is, as. He's just coming across people from different, like, parts of the stack, you know, from operators to investors to family, off all this other stuff. What's. What seems to really be rubbing off on him and his ambition and his understanding of how big to think is getting out of the house and talking to people and going to visit them in their businesses and meeting with them at, you know, at a lunch spot. And I feel like that's. That's missing. Yep. At least for me. I get worried when I focus too much online and on and on Twitter because it's such a specific, narrow view of things. [00:12:09] Speaker C: But I think you can still get that without having to have an office. Right. Like, you can kind of carve some time out once a week to, like, meet up with people, or you can take a business trip every month. Right. So I don't think that's, like, predicated on having an office. [00:12:23] Speaker A: I think you're right. I think the office is an excuse or a very easy way to default into going out into the world and talking to people, meeting people, and getting out of your house, basically. [00:12:32] Speaker B: Yeah. [00:12:32] Speaker A: Speaking of getting out of your house and thinking bigger, I think it's super interesting, this news about OpenAI. I don't know if it's a rumor. I don't know if it's like a, like a trial balloon, but at some point yesterday, the rumor came out that OpenAI is considering going public, and they're considering going public at a trillion dollars. And my first reaction is, well, that's a good way to get news. My second reaction is, is that going to keep the bubble going or is that going to pop the bubble? I don't know. What do you guys think it would do to have OpenAI go from basically a nonprofit foundation to a startup to one of the most valuable companies in the world in, like, that step. Step. Do you guys think about this? Craig, you're, you're deep into AI right now. I think about this and what it'll do to the market. Yeah. [00:13:18] Speaker B: I mean, I just saw the news this morning, and I guess, like, fundamentally, if you look at going public, it's a fundraising activity as much as anything, right? Like, going public liquidates the private shareholders, or it can, and then lets other people kind of invest and infuses capital into the business. They need that. [00:13:34] Speaker C: Right. [00:13:35] Speaker B: They sure as shit aren't going to be profitable for, like, a very long time. I think about a different problem or opportunity maybe with them going public, which is owning the chip manufacturing because. Because that, that's the big linchpin right now, you know? Right. And everybody's like, oh, Nvidia. Nvidia makes all the chips. Nvidia doesn't make anything. They design the chips. And then tsmc, Taiwan Semiconductor makes the chips. It's the only company in the world that makes the chips for both Apple and all the Nvidia chips. So if they go public, can they go, cool, we're going to do this now? That's the bigger opportunity because they'll have. [00:14:11] Speaker A: The access to capital. [00:14:12] Speaker B: Bajillion dollars. [00:14:13] Speaker A: Yeah, right, right. And lists and the market by that. [00:14:17] Speaker B: Company, maybe, or whatever. Right. Like, right. I guess the reason I think about that is I don't know why they would go public to raise a bajillion more dollars. I don't know. Like, I don't have the product vision. [00:14:29] Speaker A: Right. It's. It's to be more ambitious, not less. Yeah, yeah, yeah, yeah, yeah, yeah. That's interesting. Coincidentally, this week on the timeline, multiple related startups made announcements. So Xtropic made their announcement around their new thermodynamic chip. I'm saying those words without any understanding of what it means. And at the same time, another, like, manufacturing startup came out with a new process to, to, to create semiconductor chips. I'm saying more words. I don't fully understand, but it's all aimed, aimed in that same direction. And I think at the same time, isn't there a massive investment in the US to start building chips here, to start to diversify away from the risk of, you know, China invading Taiwan any day now? [00:15:13] Speaker B: Yeah, yeah. Well, you know, chips, but also like data centers. [00:15:16] Speaker A: Yes. Yeah, I, I guess I, I end up thinking about this a lot. You know, it's interesting as an exercise, sure, but, but mostly selfishly, I just think, okay, what is this going to do? Because everyone seems to think we're in a bubble and it's going to burst and it's, you know, people aren't going to be raising money and everyone's going to be laughed at that they raised at absurd valuations. And I am not sure. I already talked to friends who are outside of the software industry and we laugh at the multiples of software and especially AI companies. It's ridiculous. But I don't know if it's going to end anytime soon. [00:15:49] Speaker C: I think bubbles, quote unquote, can last for a lot longer than anyone can imagine. And the problem with, with them is you can make money in a bubble a lot, hanging on a lot later than you can. The people that, that are shorting are typically have the worst time because they're almost always too early. Right. So it's really hard to make money shorting a bubble. It's a lot easier to ride it even if you're coming in in the 8th or even 9th inning sometimes. [00:16:15] Speaker A: So, yeah, I have this Slack group that I'm in with the Portland guys, Ruben Gomez and a bunch of others. And yesterday I posted a screenshot of our MRR growth and, but I went back far enough to show where we pivoted. So you see like some revenue and then it craters to zero and then it just zips up from our growth with Rosie over the last year and they started asking me like, okay, can you trace back, like, what were the key factors? I'm like, by far the key factor was just going into a market that's just ripping and roaring and there's a bunch of demand for it. They're like, how much is execution and idea? I was like, I think actually idea mattered because just the idea to go into a market that was just going crazy was actually the most important thing. And then executing well enough is what led to it. So, yeah, I see, I still see just a ton of opportunity. Even now with everything that feels ridiculous, I still think there's just a lot of room to go yeah. [00:17:13] Speaker C: The other thing too is like, I don't know how much you guys pay attention to like, finance and macro and stuff, but I like listening to a lot of the macro podcasts and as you know, I'm into bitcoin and stuff. And the rhetoric from like the administration. Well, initially it was, you know, they came in with doge, they were going to do some austerity and cut the spending. And then I think that lasted like two months. And now if you hear them, yeah, they tried and hit a wall. Yeah. And so now if you listen to Besant and Trump and whatever, it's like, essentially what they're saying is we're going to grow our, grow our way out of it, which is synonymous with, you know, liquidity and money printing. And, you know, they're trying to get stakes companies and stuff. So to me, they're really telegraphing that they want to fucking, you know, add fuel to the fire here. Right. They want, they want this thing to rip in the hopes that, you know, there's such a productivity boom that we can finally offset, you know, some of the, the growth and, you know, the debt and the deficit. So that's kind of what I'm seeing, at least from a, from a macro point of view. [00:18:13] Speaker A: Yeah. And they, they cut yesterday, right? I think it was 20, 25 yesterday. [00:18:17] Speaker C: Yeah. [00:18:17] Speaker A: And I just look at the midterms, I'm like, they're going to want to rip into the midterms. No one's going to be overly concerned with inflation, I guess, like, if you. [00:18:24] Speaker B: Look at, you know, OpenAI going public at a trillion dollars, like, what is the downside there? Like, what's the opportunity for that to go bad? Like, they go public and it's a bubble and they massively devalue, like after that, or they can't, they can't go public at that price point. Like, what would happen to make that reality? [00:18:43] Speaker A: Yeah, I guess it would come back from the institutional investors saying, no, we're not willing to pay that price. But I think the psychological trillion dollar barrier has been broken. Everyone thought a trillion dollar company is ridiculous. Now we're just waiting for the trillion dollar person, which is what, around the corner a few years. I don't know what Elon's stake is in all these different businesses, but as they grow and Jensen and so all these psychological barriers seem to be falling apart and OpenAI just seems like the leader by far. So, yeah, I'm not that familiar. I don't have a great sense of what would happen if it failed. But there's appetite, man. People want to invest. I won't invest. [00:19:25] Speaker B: You know what's interesting is like, I think the institutional investors have to say it's not worth it because AI just isn't that good. Like the value at the end of the day to businesses isn't substantial enough to justify this kind of valuation. That would be hard. [00:19:40] Speaker A: How dare you. [00:19:41] Speaker B: That would be hard to prove. I think that's definitely not what we're seeing. But I think what's so interesting, and this is where we get into our little micro bubble. ChatGPT is the worst AI tool in the market for me. [00:19:53] Speaker A: Okay. I like a lot there's like, there's blasphemy coming out from your screen at this point in time. Okay. So first of all, I think Chat GPT is a consumer product and consumer products run on brand as much as they run on quality. But you've gone super deep. What, what day are you on here? [00:20:09] Speaker B: 90 of your 90s tomorrow. [00:20:11] Speaker A: Yeah. Okay, so you've done. Can you explain what you're in the middle, not in the middle of the tail end of. [00:20:16] Speaker B: Yeah, so I'm doing a video every day about AI for 100 days. So 100 days of AI and I published video 89 today. [00:20:25] Speaker A: So just describing ChatGPT as the worst AI product is hyperbole. Can you explain what, what you mean? [00:20:31] Speaker B: Yeah, so I mean, I guess, like, I agree it's consumer product. I think we talked about this last time. Last time that Chris and I were here is like each AI product or company is going to have its lane AI OpenAI. And ChatGPT is a consumer product. Anthropic is mostly for tech and developers. Gemini is for general kind of old school work, probably Copilot's for ancient, you know, and Microsoft's for ancient companies running them. So. So like that. That's kind of where it is. I guess when I say it's the worst product, it's for the kind of work I do. It's not very useful. [00:21:02] Speaker A: Too general. [00:21:03] Speaker B: Too general. Doesn't have the context, doesn't integrate with all the other stuff that I do. Doesn't help me achieve the things that I want. [00:21:10] Speaker A: It does feel like a. It's a great first place to go get some like a. That's where I go when I have a contract and I'm like, what are the actual termination clause? What are my options on how to terminate this early? I throw that into ChatGPT and I get responses and I'm like, okay, it kind of sets me Toward the right track. You're talking about. You're talking about deeper work, more complicated development work, design work. Yeah, yeah. [00:21:32] Speaker B: I mean, I think like the, you know, the few paths would be like, development work, Claude code. Amazing. Like super amazing. Any kind of like one off power move. Like you need to do a whole bunch of shit on a very specific one. Off topic, I would use Manus. Manus has Claude under the hood, but it kind of agentifies Claude. Really amazing tool. And then like, a lot of, like, stuff that is integrated with, you know, we use Gmail and Google Suite and all that kind of stuff. Anything there. I would use Gemini to, like, talk to Documents and my email and stuff like that. That's kind of the short. And then. Yeah. ChatGPT for like, we have this plant in the backyard. What is this plant? Oh, it's Wisteria. Cool, thanks. That's kind of like the value that I associate with each of those tools. [00:22:15] Speaker C: Okay, Chris, I'll take the other side of the bat. [00:22:17] Speaker A: Yeah. On a scale of 0 to 100 days of AI, where are you on the scale? [00:22:23] Speaker C: Maybe. Let's say 25. Yeah. So for me, I like, ChatGPT has basically become like a. Like a virtual assistant for me kind of thing. I've been writing a lot as so with good metrics and stuff. I've been working a lot on like, you know, documentation and that kind of stuff. And so even just little things like, this is what I want to say. Here's the. Read the rest of our docs. Like, how can I say this better? And it's like hiring, you know, instead of hiring thousands of. Or spending thousands of dollars for a copywriter, I can get, you know, feedback instantly. And it's been great for that kind of stuff. To your point about contracts and whatever, any sort of like, PDFs I feed it, you know, what. What are the red flags to watch out for? I've been writing a lot of like, just like basic Python scripts. Like, there's a few accounting stuff that, you know, I would do manually that would take. It would only take a couple minutes per month. And it. So it was. It wasn't enough to like, get a dev involved, but now I'm just like, fuck it. Like, now I can, you know, get us. So now I'm like automating scripts and stuff like that. So I guess. I guess because I'm not at day 89, maybe. Maybe that's the. That that's the issue. Right. [00:23:34] Speaker A: Craig's gone three years deep in a hundred days, and we are going to go through a similar path of. [00:23:40] Speaker C: Now, that being said, like, I started like, I, I, I've started like Vibe quoting some side projects. So I built like a workout tracker app that feeds into like Google Sheets because I work with like a, an online trainer and so I use Claude code for that. So I agree there's probably like some context where, like, you want a specialized tool, but I guess, like, I'm maybe lazier than Craig and so I don't want to be flipping back and forth between like 50 tools, which is why I kind of like, all right, chatgpt is what I use it, I have all the projects, it has context, it has memory, and so far it seems to do the, to do the job pretty well. [00:24:15] Speaker A: I talk about this with investors, about Rosie, where a lot of the conversation is, you know, who's going to win, who's going to win the market. And that doesn't mean who's going to be the best product, period. It means who is going to get out in front and get the word of mouth and become a default. And then the market will shake itself out to the, number one, owning 50% of the market, number two, owning 30% of the market, and then a smattering of hundreds and hundreds of options. So I could see from that sense, OpenAI already has the lead in branding and recognition. And if you go public and you invest even more money and you push things even further and you lower the price more and you block out even more competition, the potential of becoming the default AI tool for general billions of consumers, that is worth a lot more than we think it's worth, right? Over the next 10 years, 20 years, 30 years. So maybe that's kind of the race there. Chris, while we're on the topic, how are things going with good metrics? Last time we spoke, you were early on in your launch. [00:25:21] Speaker C: So if I remember correctly, the last time I was on, I thought that we were basically a week away from kind of releasing early access and we have unfortunately ran into some infrastructure issues with some of the bigger sites that were using us. They started to get like, the reports started getting like, pretty slow. And so we spent some time, like trying to optimize it and inevitably we realized that, like, the current database structure just wasn't going to work. So we essentially migrated off of, we were using single store at the time, migrate to Clickhouse. So that was a pain, that was painful because, like, I was, we were right there. And so that set us back like several months. But the good news is the dashboard's ripping fast now. All the kind of current users that we had on it were pretty happy with it. So now we officially launched early access literally last week or, yeah, this week. So I'm finally starting to invite people onto the platform, seeing people starting to use it. So, so yeah, it's where I think we're finally in a good spot now. [00:26:29] Speaker A: Congrats on the, on the launch of first users. [00:26:32] Speaker C: Yeah, so the, the, I guess the, the challenge right now is we, I think we have a really good like baseline product for basic, you know, the page views, like basic event tracking, all that stuff. We're still missing a few key features mainly like filtering, like global filtering, like date comparisons, that kind of stuff. So curious to hear your thoughts on the strategy. I, I like we've been at this for too long now and I'm like, we need to get some revenue in the door and like we need to like really validate this thing. So ultimately what we decide on is rather than like dragging out this like early access beta period, whatever you want to call it, we said, okay, this is, this is early access. You get, you get to use it for 30 days free. And after that we're offering 50% discount if you become a customer. And that 50% discount will stay with you for the lifetime of the product to basically incentivize people. Like, we know we're missing a few key things, but you're getting a killer deal and that will stay with you going forward. [00:27:34] Speaker A: Right. And crossing over the line of not paying to paying is bigger than exactly how much you're paying. What I'm really curious about, and Craig, you may have gone through this experience also that decision process around do we just launch this thing even though I'm not happy, or do we, you know, swallow another month, two months of work before doing it? How you handle that individual decision is, I think it says a lot about your approach in general. Sometimes, you know, there's caveats and there's unique situations. I know for us, we defaulted because rally was so painful and slow and payment oriented and enterprise sales process with Rosie. We defaulted to just ship the damn thing. And about a year in now it's caught up to us and we, we had to call time out on that mindset and basically say, okay, we, we got it. We gotta get professional here. We can't do that because all the band aids and all the technical debt. So how did you think about it? How'd you go through that decision process to say, no, I'm not releasing it like this? I'M not happy about it. I don't care how long we've been working on it, I'm gonna go back to development. [00:28:43] Speaker C: Well, for me it was like, there's a difference between having a shitty first experience and this is a pretty great starting product, but there's just a few key features missing. And so when we kind of ran into those like, infrastructure issues, I'm like, it's pretty shitty if someone logs into a dashboard and it takes like 3 seconds to load the first page. I'm just like, I just, I couldn't get around that. And you know, we were like, we can't. It's just not a great first impression. Whereas now I feel like if you install good metrics, you load the dashboard, it looks awesome. Obviously I'm biased. I think it looks awesome. It's super fast. It gives you all like the basic metrics at a glance. And so I think it, I think we're giving a good first impression. But like I said, the only issue is like, yeah, we recognize there's some of these key features that are missing, but I don't know if I'm willing to wait out another two, three, four months, however long it takes to build. And then it's also like, where do you draw the line? Right? There's always one more feature that you need to build. So that's kind of how I think about it is, yeah, just the difference between offering a good experience versus just like, yeah, there's a couple of features missing. [00:29:56] Speaker A: Okay, so you emphasize the first impression. Is it a self serve product? [00:30:00] Speaker C: Yeah. So right now, essentially what we're doing is like, if you go to like GoodMetrics IO, you have to request an invite and then I'm basically like personally onboarding and sending out those invites. Right. But ultimately, yeah, in the future it'll be completely self serve. [00:30:17] Speaker A: Yeah. In that case, I think that first impression is make a break. That's it. [00:30:22] Speaker B: Yeah. [00:30:22] Speaker A: And then if you get into it and you like it and you say, oh, I want this feature. Not the worst thing in the world at all to hear that from users. [00:30:29] Speaker C: Yeah, exactly. Like, to me, there it, to me, hey, this is, this is a great product. Like, you know, can you build like XYZ feature or like, oh, I wish it had this feature. That, that to me is a lot better than like, wow, this thing is, this thing is slow, you know? [00:30:44] Speaker A: Yeah, yeah, Yep. [00:30:45] Speaker C: Yeah, it's hard to come back from that. Yeah, yeah. [00:30:48] Speaker A: Craig, do you have any of these issues? Your product is mature. [00:30:50] Speaker B: Yeah, our product's Pretty mature. And I would just say like we probably did the, like, let's just ship ugly early. And I mean one that was eight years ago. So like it's different. I think that's important to say is like AI has transformed all of our perspective on what value is with software. So like the bar of like for not even mvp, but like first good product is quite different than it was. Yeah. And I think that especially with a self serve product, like it has to be the core of what it has to do, has to be really good. So yeah, Chris, I think you're, I think you're taking the right tack. That's what I would do. Even though that's not, that's not my nature. I would be like, fuck it, let's just get this thing out there and see what happens. What you do is you burn a lot of your initial audience with a bad first product. And we definitely did that. [00:31:37] Speaker A: Yeah. And then reputation is very hard to reestablish. Yeah, it's, it's, I hear you. It's very tricky. And it's interesting what you said about the bar, that AI has changed. We see it and hear it from our users. Six months ago you could not have an agent answering your phone. Now they're like, can I get it to say this exact thing in this situation? But I don't want them to do this and change. And we're like, you know, it reminds me of the Louis ck like you're in a chair in the sky. Can we like relax for a second on exactly what entertainment you get while you're in the chair? [00:32:09] Speaker C: I think even before AI, if you just think about, like Craig said, like when we first launched our products eight years ago, the bar, even back then, even pre AI was a lot different. And then AI just put that on steroids in terms of expectations. So, you know, I still kind of like this idea of trying to ship early but, but this whole like Lean Startup thing where you're, I think the concept of Lean, of Lean Startup makes sense, but I think now there's only so far that you can take that. You know, you need somewhat of a developed product, I think, to, to showcase. [00:32:47] Speaker A: I think one of the things like missing from this conversation that, that is right. Normal conversation. To have this outside factor of this conversation is people's impressions. And I think that a lot of us get wrong because we look at it like egocentrically. We're like, well, this is the one time people get to know our product. And what I see other companies doing a better job at is basically ignoring those limitations and just launching their product over and over and over again. So you get multiple shots at a first impression. And I talked about this internally last night. I actually pinged the team and said, maybe let's. Maybe we should just launch. Rosie, who cares if it's been a year and we have a thousand customers? 99.9999% of people have no idea what it is and when. What we see out in the market. I think maybe this week on Twitter impacted me. These companies are launching and announcing themselves, but they've been working for two years, three years sometimes. Whether it's a robot in your house. Right. Or some crazy thermodynamic chip or something else. It's almost like, don't think about yourself, think about the market. The market has no idea who you are and what you are. And you can inject into this conversation that you do have more time than you think, you have more shots on goal than you assume, and you can just make up your own narrative and you could suck for a while and get better and then announce that you're new in how amazing it is. So I do think about that. Instead of limiting, you know, what. What people think about us or the impression the market has or something else, I think that's missing. [00:34:19] Speaker C: Yeah. That reminds me of. I don't know how. How popular Product Hunt still is, but I remember there was a time where everyone kept launching on Product Hunt and adding like, 2.0 and 3.0. They would just, like, tweak something with the product. They're like, oh, we're launching, like, 2.0 today and made, like, a big deal out of it. [00:34:36] Speaker A: Yes. [00:34:37] Speaker C: And I'm like, that's kind of smart. Like, you know, they're just getting, like, repeat exposure for essentially the same product, just with the new feature. [00:34:44] Speaker A: Yeah. And then once you do that, you can also launch features as products. [00:34:48] Speaker C: Yeah, right. [00:34:49] Speaker A: You're like, here's this new thing. Let's make a whole, you know, bunch of marketing around it. [00:34:55] Speaker C: Yeah, for sure. [00:34:56] Speaker A: Speaking of robots in your house. [00:34:57] Speaker C: Yes. [00:34:58] Speaker A: Are you going to have one? [00:34:59] Speaker B: 100%. [00:34:59] Speaker C: Yeah. [00:35:00] Speaker A: 100%, yeah. [00:35:01] Speaker B: 100%. Yeah. Not the one I saw this week. That looks kind of creepy. It looks like style, but. But, like, I think the price tag for Optimus is less as well, and it arguably can do more. [00:35:13] Speaker C: Yeah. [00:35:13] Speaker B: Like, I would definitely be on the list. Yeah. [00:35:16] Speaker C: I'm going to be a late adopter for sure. But, yeah, I think inevitably the time will come where it makes sense. [00:35:24] Speaker B: Yeah. [00:35:24] Speaker A: I think it's five years. Five years and everyone just a robot. [00:35:28] Speaker C: Yep. [00:35:29] Speaker A: Craig, I have on my list here you're doing a case study. Is that day 100? [00:35:33] Speaker B: Yeah. [00:35:34] Speaker A: So I want to hear about this and how you think about agents, how you, how you even define an agent, and how you compare them. [00:35:40] Speaker B: Yeah, it's a good question, I think, like, for like, context and like one of my, one of our mutual, mutual friends text me yesterday. They're like, what, what's the deal with the AI stuff? Like, where are you going with this? [00:35:52] Speaker A: With your content, you mean? [00:35:53] Speaker B: Yeah, with the content. Like, I've put an enormous amount of effort and money into this. Like, you know, an editor for 100 videos and all this kind of stuff. Like, what's the plan? I didn't really have a plan, I guess. And then somewhere along the way I was like, you know, this cohort based, like, program course kind of thing, mentorship is a pretty good model. You know, you look at some of these guys making a whole ton of money doing this, and I was like, cool. Like, I could just do that for AI. Like, it's what I know. I know more than a lot of people, which I think is like, whatever, a potential kind of qualification for this. And like, I'd been building the email list decently, and it was a big old dud is the short version. So I, I emailed that list. I was like, hey, I'm putting together this case study thing, which is kind of like a veil for like, do you want to pay me some money to help. For me to help you build an agent? [00:36:41] Speaker A: Okay, so you're like alluding to the value of, of what it would be, but can you trace it back to case study? What, what do you mean by that? [00:36:49] Speaker B: Yeah, so case study, like the way I phrased it in the email was I'm putting together a case study group. So it was going to be like a small cohort of people I was going to work with to build an AI agent and then, you know, do a case study with them. So I think part of it is like the wording of the case study. Email was a little misleading, if I'm honest, because it really was like, hey, do you want to pay me a thousand bucks for me to help you make an agent? [00:37:09] Speaker C: When I read that email, I thought you were just looking for people to feature in a case study. I wouldn't have even known that there was like an upsell at the end of that. [00:37:19] Speaker B: Yeah, yeah. So I sent the email, a bunch of people said, you're Saying, Chris, yeah, like, sounds great. I email them like a doc and it's like, hey, this is what we're going to do. It's going to be like six weeks and it's a thousand bucks and zero people were up for it. [00:37:31] Speaker A: So like some like expectation misalignment there. [00:37:35] Speaker B: Yeah, but you would think like they were probably sent the doc to like 50 people. You would think, like, if I'd had five people who were like, cool, like, totally worth it. I'm in. But I think the lesson for me is a bunch of people on that list are not people who have a deep problem and a lot of money to spend to solve that problem. And I think that's kind of the situation with AI, maybe all the way back to like OpenAI being consumer product. Like, not a lot of people are going to pay $200 a month for Claude Pro Max 20x or whatever. The pricing power at the kind of consumer ish level I think is very low in AI because so much of it's free. [00:38:13] Speaker A: Agree. And 20 bucks a month does not feel like a lot. But 50 bucks a month for a consumer product is a lot. Yeah, yeah. I think this stuff is going to be paid for by companies. And companies are willing to pay 5,000 bucks for you to train their team on the newest AI products in a completely different way than one individual person's willing to pay 500 bucks to learn themselves. [00:38:36] Speaker B: And that's like the lesson for me is like, solve really expensive problems in a very specific way to people with a massive pain. And I kind of missed on all those. And that was like, I should be fucking smarter than that, but I'm not. [00:38:49] Speaker C: Yeah, I wouldn't think that your list would be all consumers though, right? Like, surely you must have some legit founders on your list that follow your content. [00:38:57] Speaker B: Yeah, totally. [00:38:58] Speaker A: Yeah. [00:38:58] Speaker B: It's a lot of folks like you and I, a lot of developer tech folks. And I think that's like, they're super. [00:39:04] Speaker A: Hard to sell to and they know everything. They know what's going on. They know what the options are. It's almost. It's almost like they know what you're doing. And you're better off selling magic. You're better off selling to companies that want benefit from AI but don't know what Manus is. Have never heard of Manuscript, may not have even heard of Claude. But the way I saw someone phrase it was that you want to sell business outcomes and use AI to deliver them. You don't want to sell AI solutions, you want to sell the business outcome. You just want to build a system that uses AI to deliver those results. And that's the arbitrage. The arbitrage is we'll get you, I don't know, 10 leads this month for your personal injury and then go behind, you know, under the hood and set up this chain of AI tools that does the outreach and the qualification and writes the email and personalizes it and follows up and sends a text message. And the person that's buying the result does not care that it once cost you $2,000 worth of effort and expense to get that $5,000, and now it costs you $50 to get that $5,000 worth of value. And that's where the arbitrage is. It's almost like you need to sell to a less educated or aware audience. [00:40:20] Speaker B: Yeah, I think the application is more ubiquitous. I don't even know if that's the right word. You know, it's not, it's a, it's not AI you're selling. It's like the business outcome. I think, coincidentally, Andrew Lieberman is doing the best job at going straight head on into like super enterprise, massive pain point. You know, he's like, we're going to be the McKenzie of AI. Like, if you want to sell AI solutions, like, seeing what he's doing is not surprisingly, he's a, he's a baller. [00:40:45] Speaker A: Great. Yeah. This is the. One of the morning brew founders, Michigan guy, go blue. And I, I totally agree. And I, I think he has the audience and just enough clout to come all the way right at the top. Just go right to the big companies that have the biggest problems. And I think that, I agree that's just a gigantic opportunity. [00:41:01] Speaker B: But, but otherwise, like, the thing I learned is like, you can either do that or don't sell AI at all and sell the, you know, sell the algorithm that AI helps you get. [00:41:11] Speaker A: Chris, my assumption is you still use a lot of AI without selling an AI tool, but do you feel the need to inject AI into your marketing and into your features? And you can do this and you can talk to your analytics and like. [00:41:24] Speaker C: How much pressure do you so right now? No, but I know that in a year from now, I think there's going to be a lot more AI baked into the product, which makes total sense. Right? Like, the whole point of using an analytics tool in the first place is to figure out, you know, where's my traffic coming from, what's converting, what pages aren't converting. Well, why segmenting it to see the difference between Desktop and mobile in this country versus that country. AI can, can surface all that for you. Right. So I think a year from now I could see a, I could definitely see a world where you log into good metrics and rather than clicking around to all the different reports, it's just telling you, you know, three key insights. You can query that data. And the thing that's awesome about this is like OpenAI is never going to build a web analytics tool. Right. But we can leverage the AI. So, so I'm pretty like bullish on this long term for, for our standpoint, right? [00:42:21] Speaker A: It's like if you build a solid enough product that gets the job done on analytics, then the layer on top of that becomes more useful and it still doesn't mean that your product is very easily replicable. You can't just copy your product because what's underneath it is actually driving whatever that conversation. At the top layer, the hardest stuff. [00:42:41] Speaker C: To build is all the fricking backend stuff and the infrastructure and how to handle a gazillion events coming through. Like that's, that's the hard stuff. That you ain't going to be vibe coding that. [00:42:50] Speaker A: No. [00:42:52] Speaker C: So, yeah, we're not terribly worried about that. [00:42:54] Speaker A: Yeah. I admire your bravery in your product selection because I have so little confidence in all of our analytics. I've given up and I'm like, I'm vibe running my company at this point because everything is directional with zero precision. So at some point I would love to try your product. Let's get into this for a second. I am not overly numbers driven and I have always, I've always been that way. I don't really want to go by the numbers. I want to go much more with what I think and feel and what I think is right and directional and so on. And my journey with Rosie has been really painful. Early on I got to the conclusion of this is going to be an optimization challenge because it's self serve and it is an AI product for non technical people. And what that means is we're going to need to get really good at onboarding. And the only way to get good at customer acquisition at the top of the funnel and then onboarding and then activation and then conversion is to get really good at understanding what's happening inside of our funnel and to go at each individual friction point one by one and improve it one by one. And in order to do that, you have to understand your numbers. So early on I thought this is an optimization challenge, so we have to have good analytics that drove us toward a series of mistakes in over reliance on bad data that led to bad decisions. And it got so painful that I came to terms with not having precise data and accepting everything is fuzzy. And so the data is a part of my decision process and informs my gut. But I am specifically no longer data driven in the challenge because of the mistakes that it led me to. Does that sound typical? When you hear that you're building an analytics product, like, what's your reaction? [00:44:54] Speaker C: So when I think of analytics, I, I kind of separated into two. I think there's product analytics and I think there's like marketing analytics. And so even when we were building Snappa in the early days, like we had a lot of, a lot of free users and a lot of traffic. And so I was the same thing as you. It's like, okay, we can, like I had Mixpanel and we tracked every fricking click and everything. And, and you know, I'm looking at these reverse funnel reports and you know, and, and eventually you come to that same conclusion, which is like you either need like millions and millions of data points and having like almost like a data science to and interpret all this, where it's actually going to be meaningful and doing all these split tests, or you kind of come to the realization that like, it's so hard to instrument this in a way that is foolproof, that you can actually rely on this data. So I, I think product analytics specifically is like that, that's a, like a, a whole challenging beast. Then, then you have, you know, what I would call marketing analytics, which I think is more what we're doing. What, you know, people, what Google Analytics is, which is more along the lines of understanding traffic. You know, what your best traffic sources are, what are the, you know, top pages on your site, what are the conversion rates of those pages? Basically anything before they get into the, to the product itself. And I think those can be much more relied upon than, you know, the whole post, you know, funnel inside the product and created whether account. Yeah. Whether we should do, you know, this onboarding screen versus that onboarding screen. I mean that just gets like very complicated. [00:46:37] Speaker A: So my biggest challenge is, is when it crosses over. So on the marketing side, you're right. We do feel more comfortable and confident in the data there. The challenge is when that user turns into a paying customer and then tracing back that that paying customer came from this blog post that, that is kind of like, it gets fuzzier as you go along. [00:47:01] Speaker C: Yeah. So the way that we handle that is basically we, we create Like a visitor signature, the first, the first time someone site. So if they, let's say someone comes to your site for the very first time and they read a blog post, you can then create custom events, you know, for, for trials or purchases or what have you. So if that visitor comes back, you know, four weeks later, signs up and converts, we can tie that back to that original blog post, which I again, I think is one of the, it's like the easy things that you can do with analytics that, that really move the needle and I think gives you good data and good feedback to go off of. Right? Like if you realize this one blog post is actually driving trials and conversions, well, you better make sure that you keep that blog post updated. You know, make sure you. It's still ranking. Maybe that indicates other blog posts that you should be creating similar to that. And so I think that's a lot easier data to go off of than trying to, you know, ab test five different onboarding sequences and figuring out the optimal one purely based on data. [00:48:10] Speaker A: We're 50, 50 at this point. So over the last few weeks, we're 50, 50 between new customers coming from advertising versus not advertising. The challenge is we have multiple marketing programs up and I've kind of thrown my. Thrown in the towel on understanding what's happening where. So for example, we have a cold email campaign going right now with pretty sizable numbers and we have improved. We have been improving the response rates through offers and headlines and everything else, targeting, whatever, but I really don't know. Yesterday I think we had 40 signups. 20 came from paid. So literally legit 50, 50. Yesterday, those other 20, I really, I'm relying on UTM parameters and those, those are not reliable. So I'm looking at the analytics and I'm seeing, okay, I see, I see four came in from cold email, but that's only if they clicked on the link in the cold email. I don't know if they just saw the cold email and googled it. I don't know if they saw the cold email, googled it, clicked on the brand keyword that we bid on because then it looks like it came from that campaign. So I guess this. How fuzzy. All of these, these efforts that all go into the same effort to just get someone to the site to sign up. There's so many things happening at once that I end up being like, well, how much money did we spend in advertising? How many signups did we get this month? That's how much we're spending per signup. And that's kind of like, okay, and then what did that lead into? In MRR growth. Those are my ratios. The problem with that is it's so fuzzy that you don't know what to do the next month. Do you go deeper into this campaign, spend more money in this direction or not? So it's not great. It has improved because I'm not demanding of exact precision, but it's not great. And I guess that's kind of where your tool is supposed to come in and just give more clarity on where signups are coming from, where people, where traffic is coming from. [00:50:14] Speaker C: Yeah. But I also can, even as the, you know, co founder of an analytics company, I can still re acknowledge the fact that it is never going to be perfect. And, and I would never tell someone like, oh, yeah, using our tool, you'll be able to track every single thing. No matter what. There, there's always going to be limitations. And like you said, if like a lot of people's buying behavior is, you know, they'll hear about something, they'll Google it, they won't, they'll forget about it, then they'll see it on social media. So it's, it's, you know, I think it's hard to just rely entirely on, you know, any attribution method really. And I think the important thing is just to look at things directionally and just understand that like maybe 70 to 80% of this is going to be accurate, but you're never going to get to 100%. [00:51:05] Speaker A: Right. As soon as someone can watch your ad on Instagram and then decide that this is a business decision. So they're going to get on their laptop. [00:51:13] Speaker C: Yes, yes. [00:51:14] Speaker A: As soon, as long as that's the reality. Right. And the, that's the one of the key reasons why a company like Meta is so valuable because they're on both of those devices and they're the only ones that have that insight. Yeah, but cool. So that's it. Congrats on getting it out that 0 to 1 first phase. Congrats on getting over the line. [00:51:34] Speaker C: Yeah. So now they, now the fun part begins. Yes. [00:51:38] Speaker A: Now you, you make contact with the enemy, let's say. [00:51:42] Speaker C: Yeah, for sure. [00:51:42] Speaker A: Cool. Chris, thank you very much for joining. We said goodbye to Craig earlier. Come back again. [00:51:48] Speaker C: Sounds good. Will do. [00:51:50] Speaker A: Appreciate you. Thanks, everybody. [00:51:51] Speaker C: All right, have a good Halloween. Sam.