Why AI Coding Will Never be 100% Autonomous, How Engineering Teams Are Actually Adopting AI, Inside the 996 Discourse, How to do Creative Marketing | Daksh Gupta, Co-founder and CEO of Greptile

21:14Turner Novak:I think that people should just be using whatever they want. And some companies, they like build their own, like they have their own whole entire stack too, right? Yeah. Yeah. A lot of companies do. I think there's some, you know, if you're Google and like, I think, I think as far as the last I've heard, people like the Google stack internally, like they like the internal developer tooling stack there, but it's just like, there is value in the centralization of it. Like there's probably some ramp up time for Google hires where they're trying to figure out how the internal tooling works. Whereas like your startups, including hours and also a lot of the more recent sort of, you know, that you're sort of newly large companies that are maybe founded in the late 2000s or early 2010s and later on in that.

21:56They pretty much have converged around GitLab or GitHub as their source code manager, Git as the version control. Very likely, there's like a small number of editors that they have all converged on. There's a lot of value in that consistency because it means that people can move around a lot more easily. Like a developer that's really, really used to Uber and moves to Airbnb is like, they're both, I think they're both GitHub users. So like, you know, it's like they have, they can kind of easily, obviously there'll be internal tooling that things will be different, but like the amount of time it'll take to adopt to the new place will be like a lot easier.

22:31Turner Novak:And you were going to kind of get into this whole second element of I think I kind of cut you off. What was the, what was kind of the second layer of it? Everyone has the tests for their code base on their computers. It's in the repo. And yet companies spend like all this money on CI runners, running the tests sort of in the CI CD pipeline. Like they're spending all this extra compute. And it's probably a very meaningful spend for most software companies is running these tests in the cloud when people open pull requests. And the reason is actually quite simple is that you don't want to rely on individual agency if you don't have to.

23:04Like as a CTO, you can just say, hey, it doesn't cost us anything for everyone to just, everyone just remember to run the tests before you open a pull request. If you successfully convinced everyone to do that, you wouldn't need the CI runner anymore. Like you could just make everyone run the tests and then it's their, you know, obviously people using their computers for incrementally more compute is free. And you don't have to pay for these like runners in the cloud. But one, you know, that's slow. Like these computers aren't very optimized for that type of workflow. And second, you just don't know if everyone's going to do it and people not doing it is very bad.

23:35And so being able to do it for sure every time, you know, before this code is merged, it's very valuable. The same thing is true for code review. Theoretically, you could ask, there could be a local version of Greptile, which has all the tools and everything. And you could rely on everyone going into their CLI and going like Greptile review, and then current commit or whatever. And it'll just review your current commit. And that would be fine. Functionally, it would be the same product, except the main difference being you can't enforce that. And the enforcement is useful. I think that's where...

24:06Developers are excited by Greptile. CTOs, VPs of engineering, engineering managers, are very excited about GrubTile. This type of form factor is much more exciting to team leads, tech leads. It's very exciting to staff engineers. The more senior folks are more excited by this. One, they spend a lot of their time doing code review. And second, one of their mandates is they have to figure out how to get their team to produce really high quality code and to build processes and systems that make that be as low effort as possible.

24:33Turner Novak:How have you seen engineering teams just adopting and using AI? Is there a certain... If I'm like a forward-thinking top 1 % engineering org, what does my stack maybe look like? It has changed a lot over time. Last year, the state-of-the-art was the startups and the very cool companies, they had adopted Copilot really early. And then most of the team around that point had moved on and started using Cursor for coding. So there was like an enterprise contract with Copilot, but no one was necessarily using it? Over time, they just sort of slowly bleed the cursor because cursor is a superior product at the time, at least, and might still be a superior product today.

25:19And this year, it seems to me that like, and so last year, the frontiest company, the people that absolutely, the fringes, the ones that were most sophisticated, they were former co-pilots and had mostly transitioned to cursor. Some of the ones that were like a little bit slower, they had some cursor adoption, but still mostly were co-pilot. And then there were ones that were just co-pilot, but we didn't talk to them much because if they were still on co-pilot, they were definitely not reaching out to like a seed state startup to do code review. Like there was just, that's not the type of thing you'd do.

25:48So everyone we talked to, they were usually, if not on Cursor, they were on Windsurf and they were on all these sort of, on these tools. And then this year, it's been very interesting. The early adopters of every, so now Cursor is like most companies we talk to, everyone uses Cursor. And then to varying degrees, there's cloud-coded option. So the companies that were like at the front of the cursor adoption curve have now become mostly cloud-coded companies. And in some cases, Codex companies. And then the ones that were co-pilot companies last year are mostly cursor companies today. So it's just like this moving transition from tool to tool.

26:26And if cursor builds a equally good long-running agent as cloud-coded, I'm sure people start switching back. The really great thing about coding agents great thing for developers probably bad for the coding agents themselves it's very very easy to switch between them and you can just kind of decide that you you can use this both on the same day like you know you can use like cloud code and you can use them at the same time like you can have one terminal open with cloud code you can have one terminal open with codex you can have one terminal one sort of cloud cursor window open give all three of them three separate tickets that you think they're uniquely suited to solve because the prices for these things are so low for what they are like cloud code is the most expensive one it's$200 a month it produces like an order of magnitude more value than that at the very least like it probably like a hundred times more value than that at the very least like it it's just like there's no question about how that whether or not it's worth it and and like you just buy all you pay for all of them doesn't matter like if you're like you know there's some there i use cursor for for some things i use cloud code for other i don't even code that much and i still pay for both because i use them enough that it's worth it there's more than worth it i use cursor for things times and i need like surgical edits and i use cloud code for like most of the difficult things and i'm like very happy with that pair.

27:36Turner Novak:Yeah, it's always interesting to me when you see all these people, you should like, it's interesting to me when you see a lot of these people kind of like saying these companies, like, you know, they have bad margins or whatever. I'm like, okay, just like step back and think about this. If I'm Facebook, just like the all in cost to employ a good engineer is like a million dollars, right? Like I'm paying them whatever, 400, 600, 800 K. I'm probably giving them a bunch of stock, I'm probably paying them seven figures. It's an insane deal,$200 a month. They're paying $1 ,000 a year for their million-dollar engineer.

28:09Turner Novak:So you could probably raise prices over time. I'm not sure how they're going to do that. You probably incorporate new capabilities and new features that you charge for, or you can just naturally raise prices like Spotify or Netflix did over time. But I just think it's crazy to say that they won't. I don't know. I don't know. I just like, I feel like people have just forgotten. I mean, we were using GPT-4 when it came out. I had to look up the price recently because it used to be like prices used to be listed per a thousand tokens. That's how you listed prices. It was like 50 bucks per thousand tokens or like five bucks per thousand tokens, whatever.

28:43And like, oh, sorry. I think it was 50 cents or something. So it's 50 cents a thousand tokens. It's$50 per million tokens. GPT-4 equivalent intelligent today is like free. It's like GPT-5 nano is free. Like it's, it's functionally free. The frontier has also gotten cheaper. Obviously, equal intelligence has gone to zero. Like the same IQ level that we got two years ago for very, very high cost is basically free now. But whatever the frontier is, is also cheaper. Like the frontier, like no model today, no matter how good, is as expensive as GPT-4 was when it came out. All of the models have gotten cheaper.

29:15And I just, I can't picture a world where that doesn't keep happening. I mean, it's like a stated goal from OpenAI, the intelligence that's too cheap to meter. Like I believe them that they're working on that. And to some degree, they have to. And I think the model is just keep getting cheaper over time. Like, whatever indictment people have of Cursor's business, I think margins should not be one of them at all. I think they're going to be totally fine. And they can easily raise prices. I think the product is much more worth, like worth way more than like 40 bucks a month or whatever they charge now.

29:44Turner Novak:So why do you think it's such a big, like maybe this is like a multi-pronged question, but I guess, and you can answer whatever you think makes the most sense. but I guess there's like an element of why do people care so much about like, why is this such a big deal? Why is nobody kind of internalize this? Cause I think if you look at those like cost curves, it's like, you know, they drop like 99 % every 18 months or whatever the time is. I probably said the wrong numbers there, but it's like coming down significantly. Is it like what's been going on where people haven't quite internalized this yet about the costs coming down?

30:17I think it's just the Occam's razor explanation is that it's like cool and edgy to point out when something is wrong with something. Especially when the thing is so good in all of these external regards. Cloud Code, incredible product, goes from zero to hundreds of millions of dollars in revenue in a matter of a few months. It's not cool to glaze it. I'm doing it right now. It's a fantastic product. Cloud Code is AGI. I think that it is unsurprising to me that it makes as much money as it does. And they're like, well, clearly if I'm cool, I have to find something wrong with it. And I'm like, margins, that's the one that's like, the margins are the problem.

30:58But it's like, it'll be fine. The margins will be fine. Uber was like two bucks, like a ride in San Francisco. And they just like raised their price because the value Uber creates is just a lot larger. Like how much would I pay to be moved for free? Like the actual thing Uber does for you, I don't have to own a car, like because Uber and Waymo, like owning a car in San Francisco is like a thousand dollars a month. I don't own a car. I don't foresee myself owning a car because between Uber and Waymo, I just like, I can, like, I'm definitely spending less than$1 ,000 a month on those. And, you know, maybe it's not$1 ,000, it's like$600 a month to own a car or whatever, like including parking and insurance and gas and everything.

31:30And like, you totally, like, you know, the value you create is just so much larger. I think, I think just Occam's razor, just, you need something to criticize. And like, this is the only available thing. Like what access would you criticize it on? People love the product. It makes a lot of money. Like, it creates a clear, like a very measurable ROI. Like, what do you hate? What could you possibly hate about it? Yeah, and I think it's like, we're literally barely, I mean, by the time this comes out,

31:56Turner Novak:we'll be like barely three years post ChatTPT launched. Like, it's like, we're still figuring out what this stuff can do. And it's not unlike, you look at the pricing models, how people price these things, like, that's been changing. Like every year, there's like a new way to price this. I mean, initially, ChatTPT didn't have a, there was no revenue, like, there's no price. There's no product you could even pay for originally, like back when it first started. So we've really only been, like, I think, I think in like for a while, I think like Intercom came out with Finn. There was like outcome-based pricing, right?

32:30Turner Novak:It was just like, I was just thinking about that, the outcome-based pricing. It's like, I've recently just been like really interested in like pricing in general. And it's, there's this, this book, I think it's a very popular book called Monetizing Innovation. It's like, I think it's pretty old, but a lot of the stuff applies today. And it says that like pricing models are like two axes as autonomy and attribution. And the more autonomy you have, the less useful. So if you have very low autonomy, then you should probably price by seat versus if you have high autonomy. And then if you have low attribution, like low attribution, low autonomy, seat-based pricing works the best.

33:10And this is like Slack, where like hard to attribute the value created by Slack. You know, it's there, you enjoy using it and it makes communication better, but it's really hard to measure it. And so it's very low attribution. And then it's also very low autonomy in that it's only as useful as the number of people on it. Like it's very directly related to how many people are using it. And so low attribution, low autonomy, like seed-based pricing makes sense. And then you have FIN, which is the exact opposite, which is like very high attribution. You can literally say, here's how many support tickets that we resolved without human intervention.

33:36And then it's also very high autonomy. It doesn't literally need a person using it. Like unlike something like Zendesk where it was useful and more people used it. And so that's the perfect candidate for like outcome-based pricing. obviously like i really like this this framework for thinking about it the thing that it ignores is that like your pricing should be compelling for customers and if customers kind of expect seed-based pricing for your type of product then there's like you have to price that in to factor in the fact that people just like seed-based pricing like in our case like our product is fairly high like it's fairly high attribution in that you can see how many bugs it caught and then it's also fairly high autonomy in that it doesn't really need people you can just I mean, literally, Devin's writing PRs and got help reviewing it.

34:16So I don't think there's much of an autonomy question. And it's doing its work independently.

34:20Turner Novak:You have AI reviewing AI. Yeah. And even without it, it's not a co-pilot. Cursor is a co-pilot. It works with you. It works independently of you. It corrects your things. It looks at your code and helps you. So it's not really a co-pilot. It's essentially autonomous. And yet repriced based on seed instead of outcomes because our customers expect seed-based pricing. It's easier to understand. And we're not really interested right now in like value capture. The stage of the company we're at is we want to create really incredible products that create enormous value for everyone. And like how much of it we capture is just like very much a second thought.

34:54Like maybe later. And hopefully we'll be at a point soon where like that'll become one of our core problems. And like all of our focus right now is just how do we create something like really incredible that creates like huge amounts of value for our users. And we should capture some of it, like as much as we can. But like we just don't stress too much on like exact. We probably capture much more if we're doing outcome-based pricing. but I think there's I think it's like for now just create as much value as possible

35:17Turner Novak:so this book it's called monetizing innovation it's a yellow book yeah I'll throw a link in the description for people to check it out if they want so if there's an engineering leader that's like that's like out there and they're like what should I do to just like get more people to use AI I know that's kind of like a top-down directive at a lot of companies like a lot of founders a lot of CEOs like we need to use AI because of X, Y, and Z and I'm like fuck how do I do this what would you kind of recommend? Is it like a process you found that generally tends to work? So there's some stuff where like with Reptile where you don't really need people to adopt it in the sense you just turn it on, you attach it to your GitHub or your GitLab and then it just is automatically reviewing everyone's code every time they open a pull request.

35:57So there are products like this which are, they just work and you don't have to do anything. Like meeting recorders are kind of like this where if you have a good meeting recorder, it'll just create notes for your meetings and you'll be like, oh, wait, what did that person say in that meeting? And then you go and seek it out. So there are these types of, And when we started out thinking about kind of products we wanted to build, one of our things was we needed something that's an automation. And so it doesn't require people to choose to use it every day. It should just work and should just automatically be part of your workflow.

36:23And the reason for that was we don't want this extra challenge of also having to evangelize a product after we've created value in it. We wanted that part to be essentially automatic. And the aspect of sort of like courting agents, for instance, I think they had a, like something in an adoption curve that like companies actually had to like push their people to use them more. What I found very interesting was like the person that we talk to at every company, the person that reaches out to us is always, there's a couple of characteristics. Like one, they're usually pretty senior. They're a staff engineer or a principal engineer, an EM or a VP.

36:57That's usually who reaches out. And second, they were usually an early person at the company, or at least a very important person at the company, that has decided that the highest leverage thing they can do, instead of writing code and producing software, is to get more of the team to use AI. That is the highest leverage thing they can do. For instance, at Brex, we work with someone called Jared, and Jared was a very early engineer at Brex. And I think from what I can tell from folks that work at Brex, they're very widely respected across the company. Spends a very large percentage of his time getting more people to adopt AI.

37:28And the way he does essentially just like to show people the value. Like the thing about these AI products is it doesn't take like a week of using it to start seeing value. Like I think of like the whoop as like, oh, I'm not wearing my whoop right now. But I was thinking like whoop as the obvious example where like you kind of have to use it for a while for it to generate value for you. Same or like Superhuman is a product I love. And like Superhuman, I thought it was like dumb to pay 30 bucks a month for email because email is free. And then I started using it and I was like, I can't go back.

37:56But it took like a month for me to really understand that, like for the keyboard shortcuts to get fast enough that I was really getting the speed value. With Cloud Code or like a cursor, I think within 10 seconds of using it, you'll know how powerful it is. Like it is just the initial hump of like using it in the first place. And if you just get more people to just use it once, it's very likely it'll stick.

38:16Turner Novak:Interesting, okay. A slightly different topic, but you people might be familiar with your name if they're, or maybe your face too, if they're pretty online, You had, I think, a tweet that, or I think you were quoted in an article. I forget exactly what happened, but you kind of started this whole 996 discourse that has kind of picked up a bit. Can you sort of explain what 996 is for you who don't know? And also, what exactly happened? So the context of this was Raya, who is a journalist at the SF Standard. And I think she's great. Her stuff is really good. She writes, I think it's something I said earlier, she writes about Silicon Valley the the way David Attenborough writes about the rainforest.

38:58It's just with genuine curiosity around this strange place. I thought that was really interesting. But so she wrote this article about Burning Man. And what she asked me was, hey, are people your age going to Burning Man? People in their 20s in Silicon Valley, do they go to Burning Man? And I said, no, actually, I think everyone that I know who goes to Burning Man is in their 30s and has been in Silicon Valley for a while. They're a deeper part of the culture here. And they've been around for longer. And I don't think the, as she called it, the AI kids are going to Burning Man. And then she asked me, what is the general vibe if not that?

39:33Because it seemed like the hippie, medicated aspects of Burning Man were such an important part of, I'm assuming, 15 years ago, Silicon Valley. And I said that the current vibe, as far as I could tell, was like 996, lifting heavy, not drinking, not doing any drugs, running. eating steak and eggs, marrying early. Like, it's like all these, like, things which are, like, as I could tell were the vibe. And then a screenshot of that part got, like, got tweeted. And then that tweet blew up. And I think people's interpretation of that was, like, this company 996s, instead of, like, that's the general vibe of 996.

40:19Like, I wrote later on, sort of, you know, like, to me, like, there's obviously, like, a lot of, like, hate messages or whatever. And, like, I don't, I just don't really care. Like, if, like, the, I think it's a very bad way to live if you care, like, what regular, like, just, like, everyone thinks of you, just, like, people you don't know. So, like, and my team understands what we, obviously, they live it. So, they know what, so, they know, like, what our culture is. And, you know, like, my friends and family, that they understand. And the only part of it where I was worried was I don't want potential hires that would have had a really, really fulfilling career here to mistake our culture for something it isn't.

41:01And then choose not to work here. So I did write about it. I wrote about what our work culture really is. So what is it? It's not literally 996. We work a lot. Usually people come in at nine, I think. The earliest people start leaving is like probably like seven, but I think people are pretty regular. Like, you know, most like my co-founders and I are always here until like nine, nine 30. Usually there's at least like a handful of other people that are, that are around at that time as well. And, and then like weekends, like at least of the three of us, me and my co-founders, at least like two of us are here, like most on Saturday and Sunday afternoons.

41:42And so like, it's not, I think the problem with 996 to some degree isn't the number of total hours you're working, but like it implies enforcement. Like it gives like 2008 factory in like a third world country. Like that's what it sounds like. I think that's what people don't like about it. But I think there's two things. Extraordinary outcomes require extraordinary effort. I think that's just like people, people understand that intuitively. And then I think people also understand And recruitment is a sales funnel. But there's a second-order effect of that which people don't recognize, which is that means the roles at your company are a product.

42:19Roles at your company are a product. Sponsor in your team are a product. And our product is like our compensation is very high. And our stock is like unusually high, like unusually generous for our stage and base compensation is high. The work is very interesting. The problems are hard. And the team is relatively small. and the signal is strong where, you know, the good investors have funded us. We work with some good customers and people like the product. That signal is strong. And like, we want to build a really enormous company that takes the entire market. Like, that is the product. Like, if that sounds like, and then you have to work really hard for it and that's the product.

42:59Like, if it's compelling to you, you know, then you should join us. Like, I'm going to be very transparent about what it is. And... The other aspect of it is like the decision to spend like your 20s, your 30s, like working at a company and then spending like the majority of your waking hours, at least during a Monday to Thursday on it, is like a very big ask. You ask them for a lot out of a very talented person that can do anything with their time to do this. And the sort of the thing that you're trading for is like the possibility of asymmetric upside from the stock. And obviously that means they need to evaluate the stock.

43:34And so during the interview process, we're like, look, we give you even more information than we give to investors when they're deciding whether or not to invest in us. Here's our last 12 months of growth rate. Here's where our revenue's at. Here's where our customers are. Here is customer feedback data. You can look at our NPS score. We're going to give you a free account to go use the product. You can talk to people on the team. You can talk to our investors. Many of our investors have been kind enough to take time out of their day to talk to potential hires about their thesis around investing or where their conviction comes from.

44:06We're going to give you all the information you need. Like we're going to treat you as like a very important investor who's going to invest like a lot of their time into this company. And I want, before you decide that it's going to buy the stock with your time, like I want you to have all of the possible information you could possibly have. And then the sort of the ideal customer profile of this product, all products have one, of the product, which is the role of of working at Reptile is that you're most likely at a large company right now. And the thing that you want is higher pace and you want a smaller team and you want something smaller so that you can have more upside, the potential for more upside.

44:49And, and like, if that's what you're looking for, this is great. Like you, you can always go and work at a company that works like, you can always work at a 934 type company. That's how it's very much available to you. It's just like, that's not the product here. like this product is different. And it's also, it's not unique. Like the most high velocity startups kind of operate this way. So it's not like we're sort of this like strange way of operating.

45:12Turner Novak:Yeah. And you kind of mentioned talking about hiring, how has your kind of process changed over time? I know you kind of described it. It's sort of like a go-to-market motion in a way, like how you think about different things. Yeah, we treat it very much like a go-to-market motion. So what do you do when you try to make a really, really good sales process? You have really good prospecting. You have very good qualification. I think that part people intuitively understand recruiting is to have good prospecting and good qualification. Qualification, in this case, being sort of the interview process.

45:43I think the part of sales processes that people forget to translate is it should be very easy to go through. It should be the minimum amount of effort from the buyer or the potential hire in this case. There should be as little effort as possible. We move extremely fast on it. When we know that we're interested in someone after an intro call, like they will get an email from us 30 minutes later saying like, let's get an interview. Let's fly you out here. We'll fly you out tomorrow. Like we can get you on the next plane and come out here. And like we'll interview on a Saturday or Sunday if you have work during the week.

46:15We can do like a Saturday. You can meet the team for lunch if you're coming in on a weekday. And like we'll do this two hour interview. Before you leave, we're going to ask you for references. We're going to call them the same day. By midnight that night, you will have made me an offer. The first call to offer is like, we'll do a ton of work. And we invest heavily in references, especially with engineering. I think references tend to be very good. Engineers are very honest people and they'll tell you genuinely how they feel about their former coworkers. And we found that you just need to move really fast.

46:47People have a strong bias toward the first offer that they get when they start a hiring process. You move extremely fast. I think that those are the scaffolding of the process. The actual evaluation portion is like, we're always iterating it. The important aspects of that are standardized. You can't use AI for the engineering parts. And so we have our own thoughts on this. It's like a long internal debate that led us to this point. But I think the high bit is move extremely fast, make it extremely friendly. And then like after you've made an offer, like we're just like, here's all of the information you could possibly need to evaluate us.

47:18You can talk to anyone from the team. You can talk to our investors. I'm sure that we wouldn't talk to you. And like, I want you to have all the information you need before you invest time with this. This is an important decision. and by now you've talked to the team, you know what our work culture is like, you know what it's like to work here, you know the types of problems you'll be working on. I want you to evaluate this place like you're an investor that's investing their time and then figure out if this is the right place for you.

47:41Turner Novak:And you mentioned reference is a big piece of it that you really lean hard on. How do you generally recommend doing a good reference process? Like what kind of questions you ask? Like who do you ask? How do you approach it? Honestly, I don't think we are very sophisticated in how we do references. We make it very simple. We just text the person or email them the references that they shared. And we say, hey, can we get five minutes of your time on a phone call? Or if you prefer to just tell me your thoughts on email, that's fine too. Often, especially if they're very positive thoughts, people will just write an email.

48:13But on the phone, we'll just say, how was it? How was this person? How was it working with them? Are they good at their jobs? Are they pleasant to work with? And then there's kind of just... We just seek glowing recommendations. like if they're glowing, that's a very good sign. And be like, yeah, they'll offer up, you know, we did one recently for someone who we were fortunate enough joined our team where, you know, their former employer said, this was like one of the greatest engineers that I've ever worked with. And like, what was funny was that they sounded upset on the phone that this person was leaving.

48:43Like that was like palpable in their voice. There was like, we're happy with this person moving on, but like we were all worried that they were leaving our team. Like just from the future of the team perspective. And I think like that's the type of references you're looking for. we're so risk averse around hiring. And I think like everyone is, obviously if your engineering team is like 10 people, then the next hire is like 9 % of your engineering team. You're hiring all at once. And we take it very seriously.

49:06Turner Novak:Yeah. And maybe you'd kind of characterize the whole 996 publicity that you got sort of as like, I mean, I guess it was kind of marketing for Reptile in a way. You've done a lot of different like marketing stunts over time. How have you kind of like, what are some of those for people who aren't familiar? and like, how do you approach them? I think one I thought was kind of interesting was like the energy drink one. I don't know if that was the first one. That might be one of the early ones. We made a custom energy drink brand, like a private label energy drink, which was like energy drink for coders.

49:38Cause there's this like whole world of energy drinks for athletes, there's energy drinks for gamers. And then there wasn't a brand that was like for programmers. There are coffee, there's the, you know, there's terminal coffee, which is like coffee for developers. I think that's like really brilliant. And I think that came around the same time. And we want to do like an energy drink. Everyone we know that's a good engineer is a white monster enthusiast. And we were like, this white monster's aesthetic isn't for you though. Like we want to build one that's an aesthetic that's for you. And so that's what we built.

50:08Turner Novak:It's like, you know, this energy drink helps you ship faster. We shipped it to a bunch of customers. We put hundreds of them in the YC office. I think the one stunt that we did that I personally enjoyed a lot, and I use the word enjoyed because I don't know how attributable this stuff is. I don't know if it helps. I don't know if it's useful, but it's fun. And, you know, like we don't like, you know, I think I'm kind of, I forget this a lot. And thankfully my co-founder, Suhun is very good about remembering this. It's, you kind of have to, you have to have fun. You just have to, you know, it's supposed to be fun.

50:40Like building this thing is supposed to be fun. And this one was, we built a box. We filled it up with cookies and it had a light-activated speaker inside. And when you opened it, on the inside flap was a sweaty picture of Steve Ballmer and it would start playing the developers, developers, developers speech. And people would open it and a bunch of our customers that got it, like put it in their fridge so that every time they'd open the door, the lights would come on and it would start saying developers, developers, developers. I thought that was brilliant. Probably annoying within a day or two.

51:09But that's another one. We're always thinking of crazy things to do. Honestly, I'm hoping they're useful because we've just been doing them because they're fun. We just do one every few months.

51:18Turner Novak:So how do you come up with an idea? And how do you know if it could potentially work or not? How do you pick? What's the creative process look like? And then how do you decide, this is the one we're going to do? I think they come up organically. Our entire team eats lunch together because the lunch order arrives all at once. And then all 15 of us sit around a table, like a tiny table and eat lunch together. And it's just like, I do not know this is unusual. I thought this is how all companies did. because I've never had an actual job before. But they're like, I thought this was all coming together.

51:50But like we used to sit together for lunch. And actually it's really, really good for coming up with like crazy ideas like this. Because we have one half, which is like the go-to-market side of people, which are pretty technical. And then the other half is engineers, which is their ICP basically. And so like to some extent, like we sort of have the perfect balance of people to come up with crazy ideas. We just come up with a bunch of them. And then whatever sounds like crazy enough that we can see like going viral and then we just decided to do those. And ones where, and part of it is going viral.

52:20And the other thing is like, it sends the right message about us. Like the thing I want people to know about us, like when we really care about this specific thing, which is like, we really care about catching bugs. We really care about creating a lot of really good software. And like, we like, we're like, we like having fun, which is like, we're like a fun company. And like, there is this, I might be getting his name wrong. It was like Rick Ross, who's a music producer. and someone asked him, how do you make a hit party song or a hit pop song? And he was like, you have two or three people in a studio and they're having a blast.

52:52And if you can capture the energy of that room and put it into a song, that's a hit song. If you can capture the fun that the artists are having while making the song, then it's going to be a hit song. And I think that's how we think about evaluating this stuff.

53:05Turner Novak:So how do you measure if it worked? Because you kind of said you don't know if it worked. Like, do you not do a lot of attribution? Or are you just like, hey, it looks like some more people came to the website or like scanned the QR code on the cookie box or like, how do you measure this stuff? So I think this is advice we got from CKey at Runway. They said all marketing channels that are attributable are priced in. And they're usually, and usually anything that's underpriced is unattributable. And this made total sense. I think anything that's like high effort, so people don't do it. and then it's like attribution is very hard, usually we'll have better outcomes.

53:43Like the total amount of effort and cost of getting this cookie box thing, for instance, is not very high. Like I think like cookies don't cost that much and like boxes don't cost that much either. And then getting custom speakers was like, I think it was like$2 a speaker or something from China. I think with terrorism, maybe like$4 per speaker. And it's like, it's very, very cheap to do this at even a decently high scale. And it's just like, if you saw a LinkedIn banner ad for a company, like you can send that to like a million people for not that much, but you won't remember that.

54:16Turner Novak:Your eyes like skip over, like you subconsciously see that it's an ad and you just don't notice it. Even if it's relevant to you, you might have higher attention if it happened to be that like earlier that day, you had a quarterly meeting about how like you guys need to get an AI code review. You probably have a higher chance of clicking on it. but if you get a box like it to your office and it has steve balmer's sweaty face on it you will remember that forever like you're not going to forget like the the cookie box that that talks to you like that you're not going to forget that one and so like i think the the total when you think of like marketing things i think of them like well obviously they're a funnel and so the way to evaluate them is like how many people can you reach and how long will they remember you for, I think is like a good way of like the area under the curve is like basically the total value that you can produce with the marketing activity.

55:07As you have stuff that's like very, very wide, but not very deep, which is I think canonical example would be Google ads. And then there's stuff like this, which is you do this. I mean, I think we did like a hundred boxes because I think it's difficult to fill up boxes of cookies. We were like a five or six person team at the time. And it's just like a lot of, there's only so much you can do. It takes like hours to do that. but I think those 100 of the 100 cookie box we sent out I think like at least a third of them are like paying customers now and like everyone else they definitely remember us like at whatever point they're looking for an AI code review or within the next few months like they will probably reach out to us and be like hey like at the very least we want to talk to you because you sent us this crazy cookie box earlier like it's still sitting in our office somewhere yeah I think like

55:47Turner Novak:I see people do pizzas a decent amount those are maybe like a little bit easier to scale up because like you can probably just put it in order with a pizza shop and be like, hey, slap a sticker on the box or something. Like, that might be a little bit easier. And the other aspect is like, it only works once and never works again. Like, we can do the cookie box again. Well, maybe that one we might be able to do again because I don't think that many people heard about it. And so we could do it because it'll be new to some people. But like, Antimetal did the custom pizza boxes. I don't think anyone can do it anymore.

56:18Like, Antimetal captured all the alpha on that one. I think you've just come up with a whole entirely new thing.

56:23Turner Novak:Yeah, I was going to say, you almost have to come up with like new, new food or something. Food seems to be pretty good. I feel like because people will eat it and they'll like spend time a couple minutes, literally. Hot sauce is my favorite one, especially if you sell to startups. The hot sauce sits for a long time on the kitchen like counter or like in the... And I think of all of the things in very long shelf life, coffee, like 12 ounces of coffee in our office would last like a week. But like a eight ounce hot sauce is like could last a year. like that could be the whole lease like it would just be sitting there the entire time okay you can't it's not easy to get through and the funny thing is the hotter you make the sauce the longer it'll last and the longer you have like like true like mental space for people yeah and you almost need to get like a magnet just like have them slapping on the fridge you're like every single person sees it every day when they open the fridge yeah there's there's something there too and it's like how do you get in front of like more people and this stuff is great but i think like you know we waited a long time to do any of these things we're like we need a product that people are just telling their friends about because they love the product.

57:27And then the fire is already going and then we're like, what jet fuel can we throw on this? Like, where do we find? Like, what can we throw on this? That's like this thing that's already working. To some people, you think,

57:37Turner Novak:tried to do this too quickly? Yeah. Really? How do you know when it's ready? Like, is it like, quote unquote, you need PMF to like do this or? I think so. I think you need like at least like relatively early signs of PMF. Like some people, like I think we were at a place when we did this where we were like, if you start a free trial with Greptile and you're like a real software company, you will sign up. Like you will become a paying user. It was like 70 % conversion rate. Like it was like very, very high. And the other 30 probably like largely explained by just being out of ICP. And at that point it was like, okay, like clearly the next thing we need to do is just get many people to try the product as possible and get in front of them as possible.

58:16And it's like, what are some fun ways in which we can do it? And the cookie box came up, the energy rings came up. And we did a hackathon where we gave out Venus flytraps because they catch bugs. And we had a shirt to go along with it with a big Venus flytrap on it. And we have Everett, who's on our team, who does a lot of growth-type things, like figured out how to get...

58:38Turner Novak:Because it's not actually... They're very tropical plants. So getting them into California in the dry weather and keeping them alive is not that easy, actually. They're not really for this weather. So getting 100 carnivorous plants, keeping them alive for a few days ahead of the hackathon, and giving them out and also creating a website where you have like care instructions for the plans so like people can keep them alive for long. And the other thing that happens is you'd think that they'd catch the bugs in your office, but they actually did pheromones that attract bugs. And so we had more bugs at the end of it.

59:07Like we had like way more bugs inside the end. And it was like a strangely poetic thing where like maybe GrubTel also causes the company to have more bugs. It's like, oh, GrubTel will catch it. Let me just like sloppily write some stuff. It's fine. And I'm sure that happens. Like a number of bugs go up at some point because people are like, whatever. just like we have like a failsafe for this we'll be fine interesting okay well so i know one thing

59:26Turner Novak:you mentioned was you had to you waited a while to do this like it was a long process to get here i want to kind of talk a little bit about just like that general journey and i know it starts probably like a lot earlier than people would think one thing i thought was super interesting back in high school you were a musician and you had a song you had a couple songs that like they charted on Spotify. What's like the story with that? So I grew up playing guitar. I was in choir in middle and high school and I was singing a little bit. A friend taught me how to use Ableton when I was, I think maybe like in sophomore year.

59:59So I started writing songs, recording them. And then I started to really enjoy it. I think the process of producing music is really fun. And you start to listen to music differently. I think a lot of people that start writing, for instance, it might be like writing a substack. You just start reading differently when you start writing. So you start listening to music differently

1:00:15Turner Novak:when you start producing music. And it's like, I think people look at me and they're like, oh, Tech Bro, like probably made like techno or whatever, like made like, like was like a DJ, made like electronic music or ambient music. I actually made like sad indie folk music. That's what I was, that's the kind of music I was doing. I made like sad indie folk songs. And then like, I think the second or third song I put out like kind of spent semi-viral. I think so Spotify was, I was living in India. Spotify was new to India at the time. And so I think they wanted to promote like new independent Indian artists.

1:00:45And so it got on like the Indian indie, like editorial playlist. It was like one of the first songs on a playlist. And so it got like tens of thousands of views. I think it might've ended up with like low hundreds of thousands. And then the song I put out after that got on the viral 50 on Spotify. And I think it was like at the 14th place or something. And there's like a precipitous drop off in streams after the first 10. So it wasn't like a ton of streams, might've been like half a million or so. But this is like senior year of high school. and I'm like, wait, should I do music full time instead of like, you know, maybe there's something here.

1:01:19And you're still in India. I was still in India, yeah. So I went, and this was around the time I was applying to school. I knew I wanted to go to engineering school. I had grown up like really liking math and science and my sort of dream was I wanted to build cool things with my friends. Like when people would ask me when I was like 15, 16, I was like, what do you want to do? I was like, I want to learn how to program or build robots or something. And then I want to like, I want to build cool things with my friends. That's what I want to do. and then this music thing was sort of like potential potential side like side quest where I was like maybe I should do this instead and you were in a band too right I was in a band in college so got to college I I think the so the band we would basically play like house shows there's this neighborhood in Atlanta called Home Park and it was for these single family houses in the city formerly constructed for people that were working in the textile industry and in Midtown Atlanta, they were set up.

1:02:13They were sort of like post-Civil War, I think early 20th century. I think it was like around when that must have been. And so that, because it was next to Georgia Tech's campus, became student housing because obviously you don't really manufacture stuff in Atlanta anymore. The textile industry moved out and that area all became retail and commercial. And then that place where the houses were for the workers became like sort of where the artsy Georgia Tech students lived. So it was like a lot of bands and a lot of like music people and they were doing shows in backyards and like people would come and they'd be like a keg.

1:02:47And so we started playing those shows. and it was like this so the first thing i learned is like i really like programming and i like building things i think that's really fun for me and then while running this band it was like five people and it was like this is actually like it's really fun to one because you're perfecting this product you usually like rehearse like like two or three times a week in in like you know either the music room or like one of our friends garages and and just like practice and that's the you know set list is the product and you're like refining this product you're trying to make it the music better you're trying to pick the right songs that are like fun at these parties and and then you're doing the go-to-market trying to book shows trying to book shows at frats because the frats pay you to play at like their formals whatever and frats for a big thing at jordatech and then and then you play like these house shows which is really fun and and like the the thing of like you and like and like just like it's a group of five people and you're trying to like make this thing work is like so fun and in some sense it was like okay the two things i learned about myself i like programming and I like being in a five person team trying to make a thing get off the ground and like that seemed like I was like okay I'm starting to realize that there's like I maybe I was very sure I did not want to start a startup in college I was like this looks like way too much work like why would I not why would I do this when I could just be like an Amazon or something and then I think the the band experience was kind of like this is actually like it's really fun to be like a small group of people trying to figure something out and like trying to take something from Simjira one.

1:04:12And then I happened to meet Suhun around that time, who's now my co-founder. And he was very, he very much wanted to start a startup. He was like, he used to listen to Gary Tan's YouTube channel growing up in the Philippines. And we sort of decided to go down this path afterwards. But I think the one part of, I don't really miss college overall, but being in a band was great. That was a really, really fun thing to do.

1:04:37Turner Novak:Yeah, it's so funny. like people I think I saw a tweet it was like you know if you could go back to college doing everything you know and like you know either be cool or like not mess up like make better decisions I was like I don't know if I would go back like I'm kind of it just kind of happened it's done it's like I'm happy now I mean I would have done something differently I guess but like also I don't really care that much like it's like it's like high school like high school honestly I wasn't I wasn't the coolest kid in high school it's like it's done would I change things yeah sure but like I don't really care.

1:05:09Turner Novak:Like, I'm happy where I'm at today. It's like, it is what it is. I do wish you'd learn to program better in college. Like, I think that actually, I think like Soon got like really, really good at programming in college. And then my third co-founder, Dyshanth, got really, really good at programming. I just didn't learn it as well. It's like, I'm actually like not a good programmer now. I think that would have been a really good time to learn how to program really well. Yeah, that's fair. I probably played too many video games. Like, I, do you know, have you ever heard of major league gaming? Yeah, yeah, yeah, yeah, yeah.

1:05:33Turner Novak:Yeah, so I like went to these like MLG tournaments. It's literally like a team. we competed Halo 3s. I was going to ask, yeah. Yeah, so when you're playing Halo or Call of Duty Online, you just show up in matchmaking and you match with random people. It's literally a team that's playing against another team. And some people take the extent of you have a coach. Some people, they will literally have practices. And they'll like each map in each game setting, you'll have different plays that you'll run, how you'll open, who goes where. There's even levels of where you stand on the map will influence where the other team spawn.

1:06:07Turner Novak:So you're always looking to control the map based on where people are setting up. Based on a new weapon might spawn in 30 seconds, you have to try to shift so you can get back Mac control, all that kind of stuff. Anyways, I went to a couple of those tournaments and we ended up... I was probably top 1%, but not top 0.1%. And you're like, I'm not going to be a pro video gamer. But it was fun. like something i've noticed with like startup people and like startup founders investors etc it's like i think one obviously they're very often we're like very good gamers but i think they're more more abstractly really into learning the meta for some type of winnable game which is like kind of what you do when you start a startup is you learn the meta and like there's like old scripture on the meta which is like old paul graham essays and then like you just start the meta for like how to be really good at this um and it just seems like like it well we're all hill climbers we're just climbing hills we're like we're just like rl machines we're climbing hills like like i have a friend who's one of the co-founders of of a company called gumloop and and his like i think we were in the same yc batch and i think like a few days into the batch we were talking about geoguessers like oh you want to come over and play geoguesser i got after like after work one of these nights and he was like wait you guys play geoguesser and i was like yeah why he's like what and he's like what rank are you i was like i don't think i play geoguesser like you play geoguesser i'm like hi i don't know and then this guy like he like the first like image comes on and he plays a mode of geoguesser called nmpz which is no move pan or zoom which is the setting you can set which means it's a picture because you can't move or put or pan or zoom it's just like just a picture you just have to like the single shot you got like one shot the guess it's it's crazy and like he'll and you know the thing will come on and he'll be like that street lights is in southern Nairobi and I was like what it's like we've been to Nairobi and he's like nope I just know that they just there's like entire routes of meta it's like oh these bollocks are like only in Barcelona or whatever and they just learn like what the different things are there and and like oh and then car itself is meta on its own we're like the the type of google car that took the that took the the the images there's like a certain one they use in Ghana which looks like different from the one they use in South Africa.

1:08:24And you just learn what they look like for every country.

1:08:27Turner Novak:It's like hill climbing. There's a game, there's an objective, and you just learn everything you can about how to get good at it. So what do you think is sort of the current meta around startups? There's obviously the Paul Graham classics, like build something people want, talk to customers or whatever. What do you think is something that's kind of emerged over the past year or so-ish that people maybe have not picked up on yet that maybe you have? This one, I think, might be too specific But I've been thinking about this increasingly now. But when you're building AI products, there's this thing where if you're building, especially for the enterprise or for B2B, people will use the product and they will determine based on their first 10 minutes of use whether the product is good or not.

1:09:17That was totally fine for deterministic products, I think. like they work the same all the time like they're deterministic but like l &m products are different they're stochastic they will hallucinate sometimes they will be bad sometimes we were trying to predict at some point like what can we like we just you know we had 70 percent of people that tried grub how they become paying users i think the question go well what is different about the other 30 percent like what's going wrong there are they just like what's what is it about them that mean and we had some theories we're like oh it looks like fintech teams really like grub time.

1:09:49Like Brex was one of our early customers, for instance. And maybe it's because they care a lot more about details. Like fintech bugs are a lot worse. Like a bug in Zendesk is not as horrible as a bug that causes a transaction to fail in Brex. That's really, really bad. Maybe culturally, these companies are just more attentive to detail. But honestly, none of these things held up. They're always good counterexamples. The thing that held up was people that had a great first experience with the product. It just so happened that the first day that they were using it, it caught this crazy bug. It barely mattered what happened over the next two weeks.

1:10:23They just had this belief that this can do things. And whether or not it catches a bug the first day is just, it's kind of the actual question is, well, did you create a bug that day? Because if you caught no bugs that day and you got one of those hallucinating comments the first day, you're like, this is a product that hallucinates. And I've written it off in my head. And so your first impression matters a lot. I think that was not maybe true pre-AI as much. Now it really matters to make a good first impression. And to some degree, you can't like control hallucination to you. You kind of can, but you can't really completely eliminate it.

1:10:54And, but what you should probably do though is make your product lovable. I think that that's like, that's the new meta. It's like invest in design earlier, make the experience using the product delightful. Make it so that by the time the person is experiencing the product's core value, they are already on your side because they just like, they have experienced joy through using your product. So we like obsess over the landing page design and the onboarding flow. We want you to root for the product before you ever even start using it. You go through this entire onboarding process and you say, wow, that was like really delightful.

1:11:26Like everything just worked. And like, it was interesting and it was visually compelling. The design is beautiful. And like, I'm not rooting for this product. And so when I see a hallucination, I will not punish too heavily for it. And when I see it work really well, I will like reward it very strongly versus someone who just has like kind of a broken or uninspiring onboarding. and uninspiring means they'll be fair and then broken means they'll be like heavily punish the hallucinations and not very strongly reward the positive aspects of the product. I think people's mood really, like you have to really control it early.

1:11:59I think, and the sort of tactical advice there is invest heavily in the ancillary aspects of your product. Eliminate the paper cuts, invest in design early. I think that's like kind of, I think newly important or much more important than it used to be.

1:12:12Turner Novak:Yeah, it sounds like it's like, Because you can't necessarily always control what their first experience is, just like in the actual product. So it's like design scaffolding around how they'll use the product. So you can create a moment of delight that isn't necessarily the product, but it is because you designed it that way, if that makes sense. Yeah, I think there's a lot of that. And so you kind of met your co-founder. Did you guys meet in college? Yeah, I went to college. and he kind of convinced you, it sounds like, we should start a startup. What was that whole journey like from, I'm in a band, just kind of like a startup, even though I don't know what a startup is because I'm at Georgia Tech, it's not really a thing.

1:12:54Turner Novak:What was that arc like? So yeah, Georgia Tech, not very common to start startups. I think it is now, but it wasn't even a few years ago. There were not many Georgia Tech alum in the YC batches, for instance. Now they're very well represented. But at the time, it was uncommon. My friends didn't really understand what I was doing when I started doing it. And I didn't really know. I didn't really know what venture capital was, for instance. The concept of it wasn't... My idea of venture capital was what a Shark Tank viewer's idea of venture capital would be, which is you have this business that is a high likelihood of working, and then you sell some percentage of it.

1:13:25I took this class my junior year fall semester, and it's called the Startup Capstone Class. For engineering and computer science degrees at Georgia Tech, you have to do some type of project class. And all of the other project classes were three semesters, but there was a startup class that was two semesters. One semester you do the startup thing and then there was like a semester of, I think like technical writing or something that's unrelated. And so like, this looks like the lowest effort one. And the more, like the more I do this, like to take like the easiest possible classes, the more time there is for me to work on my band, which is like what I really want to do in college.

1:13:58And so I was like, I'm going to take this class because it's like very easy. And like the A rate was like 90 % or something. It was basically like a free A. Suhoon took that class because like he earnestly wanted to start a company. And he was like, I'm going to learn how to start a startup here. It's like, obviously, you take the resources you have available at university. And so we met in the first day of the class. The professor, Dr. Craig Forrest, said something along the lines of that a third of the projects that started in this class continue working on it after the class ends. Like, they turn it into, like, companies.

1:14:28And I was like, then I think I laughed out loud in that classroom. Like, I was like, why would I keep working on the group project on the semester end? That's insane. Like, you stop working on it the moment it's been submitted for grading. And, like, why would you, Like in what world would you continue? We started doing it and it was like really, it was like really fun. Like I was, I had, I was having a lot of fun working with Suhoon and like we became close friends with that experience. And then we like, it just, I think like we're solving a problem, which was, and actually the problem we were solving at the time was to find a problem that we could solve in a way that would like make us money.

1:15:03Okay, okay. And so, because we came up with all these like, And so we were just smart enough in not to do a B2C idea. Because we're like, oh, you know, B2C is like what people do and they're like not sophisticated. B2B is what the cool kids are doing. Obviously that's changed now. But I think this is like the, you know, like late 2000s, like pre-AI is what people are thinking. And so we build like, but we were smart enough to come up with an actually good B2B idea because we'd never been a B. And so that's kind of hard to figure out like what a good B2B idea would be. So we came up with like a series of plausible sounding B2B ideas.

1:15:31So one of the ones we came up with was a customer feedback a text bot. So it would text message you after a... Maybe you just took a JetBlue flight and it would text you after you took the flight from JetBlue being like, how are you experiencing? It was a conversation to get your feedback. That was a brilliant idea. Obviously, no one actually wants this. It turns out companies already have too much customer feedback that they just don't know what to do with anyway. So it's not like a quantity problem.

1:15:59Turner Novak:Yeah, it sounds a good idea though as a college student who's buying a flight. It's like, oh, I should... I bet a business wants my feedback. Yeah, exactly. You land and like, it's kind of hilarious. It's just like, you know, I bet JetBlue would really use my like insights and how they could make their flights better. It's like, free Wi-Fi, like better snacks. Yeah, like the seats are a little hard. I feel like my lumbar is not being supported right now. Yeah, you guys should upgrade the seats on all the planes. And in my head, I'm thinking like JetBlue gets this feedback and they're like, wow, this brilliant college student has figured out how we can fix JetBlue.

1:16:31It's time to get new seats, fellas. Bring this to the CEO. We need to hire this kid immediately. Yeah, like maybe this should be our head of product. I don't know if Jepo is the head of product. So we do this like, we do this like plausible sound and startup idea. And like the semester ends and we're like, oh, maybe we should keep working on this. Like there was this like competition thing that we got into, which you like, I think you're auto enrolled in this competition when you do the class. And so we got enrolled into it. It's called the InVenture Prize. We became a finalist. We're like, okay, let's just keep working on it until the competition.

1:17:03It's like three months away. And so we keep working on it until the competition. And this is now like three months after the semester has ended. And we're like, okay, why am I still, like, what is it? Why are we working on this thing? It's like semester is done. And then the competition happens. We don't win. And we're like, okay, we can finally stop working on this now. But then we actually did keep working on it for like a few more weeks. And during that time, we signed up for like another competition. And this one was hosted by Chris Klaus, who was one of the inventors of network scanning in the 90s.

1:17:32and he dropped out of Georgia Tech and sold that company for like over a billion dollars to IBM. And he then donated the computer science building to Georgia Tech. So it was called the Klaus Building. At this point, I didn't even know this was like a living person. He's not even old. Like he's like a young person. And I just, obviously you assume like whoever names buildings, like everyone else who's named a building was like, like died in the mid 20th century.

1:17:54Turner Novak:Yeah, like Vanderbilt, Rockefeller, whatever, like some like oil baron or whatever. But this person, like Chris is just he's like a pretty young person he's like in his 40s or something he's like a pretty young person and obviously extremely intelligent and he was hosting this competition and like the winner would get like$100 ,000 and so we did the competition we won and we're like okay so like I guess we should keep working on this at least until we run out of this money and then obviously$100 ,000 when you're in college is like infinity money yeah that could last like 10 years yeah I think I think over the next year we spent like$8 ,000 total because like, I think I got a computer for a little bit because I was like, my computer doesn't really work.

1:18:34And then like, we had like basically like trickling AWS bills. We didn't have any credits yet. And I said, that was like, that was all our expenses for the next year. And we're like, we're trying to find something that works. We're trying to sell this thing. We're like learning because you have to do sales. They have to like, and we're now sort of reading a program essays and like learning, okay, we have to like, we have to do things that don't scale. We have to like email like a thousand people a day and like find someone like, like just get in contact, talk to as many users as possible, a potential user as possible.

1:18:59And like, just like nothing is working.

1:19:01Turner Novak:And this was still the surveys. Yeah. We're still doing like text-based customer surveys. And like, it's like, in what world would like two college students have never been in the consumer goods business be like the right people to build this? It's just like such a, it just makes no sense. Like that, this is like, why would this be the right? And, but the semester ended and we were graduating, you know, like about a year after that. And we decided, hey, like, let's, let's just go full time. Like, just let's try something. So we were already working with like the DaVinci 2, DaVinci 3 era of opening high APIs.

1:19:31And they were really, really good. And then ChatGPT came out, it's conversational, like, well, this seems very relevant to what we're doing because we're doing this text-based thing. And they used RL to make these things more conversational. Post-training seems to have been working really well for this type of conversational chat-based use case. And so it seems sort of like this crazy coincidence that we would graduate with computer science degrees right as one of the biggest transformations in history of technology is happening. This is like 2023. And so we should at least attempt going out to San Francisco and like building things there.

1:20:04We managed to raise a little bit more money, convinced my college roommate of four years, who's one of the smartest people I knew. She's like, hey, you should become our third co-founder. We should, all three of us should go to San Francisco. It's like this crazy thing that's happening there and we should be part of it. We should build something.

1:20:20Turner Novak:So had you decided that you were going to do code review or like, were you still kind of like, we think we probably need to try something else, but we don't know yet what it is? At that time, I think we actually were, we still hadn't lost conviction in the text-based customer feedback thing. And the funny thing was we didn't lose conviction because investors funded us. And we were like, well, investors funded us, it must be a good idea. And what we didn't intuitively understand is investors were funding us partly because it was like the potential of us to find a good idea. And it was not really validation for the idea.

1:20:49That can only come from customers. And so like that was not the correct thing to, and I think it's like sort of a canonical young founder mistake is like you, misattribute investor validation as customer validation. And those serve very different purposes. And so we came out to San Francisco. So I was sending investor update emails. We have one investor. So I would send this person an email. I would send Chris an email every month about what happened that month. And I still send monthly investor updates, but obviously now to more investors. And I think someone told me, we should start putting our numbers on top of the letter.

1:21:24So the letter was just like this narrative. It was like a story every month. It was like not very compelling, but it was like, start putting numbers on top, like put your revenue, put your cash, put your runaway. And we moved to San Francisco, suddenly we have real costs because we just really underestimated how expensive it is to live in San Francisco. And we were all living in the same room in this like horrible Airbnb in the South end of San Francisco. We didn't have that much money. It was starting to run out and our revenue was zero. So we had like month one, arrive in May, zero revenue. Month two, June, zero revenue.

1:21:52And we're like, oh, this is gonna be a problem very soon. We should probably, And it creates this very strong urgency that we just didn't have when we were in college. And we're like, okay, we need to reset ourselves. We went to this hackathon, Scaliad did a hackathon mid-July of 2023. And we're like, we should just build stuff that like, because we're clearly not the right people to build this consumer feedback type product, which is not the right people for it. But we are programmers and we're like early adopters of these LM APIs. And so maybe there's something here that we can build. and we decided to build a code-based chat product.

1:22:25That was our first idea. We were like, it would be really interesting if you could put a GitHub link in and start chatting with the code base. We have struggled with operating on large code bases and finding where stuff is and so on and so forth. And so like building that would sound like really, really compelling to us. So we built that. And that day is when YC, for the first time ever, did early applications. And so at the hackathon, we're like wrapping up. I've just finished my bits and I think we have like an hour left and I'd see this tweet. saying that YC is doing early applications. And so I was like, it'd be pretty funny.

1:22:56We just applied with this hackathon project that we're not even completely done with. And so we applied to YC with this. The next day, we didn't think much of it. We were probably not going to get in. We just applied with a hackathon project. The next day, we put it out. We put a Stripe link on it. And we were like, let's monetize this thing. I think within a few days, because early users seemed to like it, the first couple of people we showed it to. And then it started growing, just kind of automatically, like grew like a few hundred and a thousand and then two thousand five thousand dollars a month like it just the revenue just kept kind of growing and by the time we did our yc interview we had a hundred paying users and and like this is like i think we got interviewed maybe like two months after the uh the application and and we got in and we did we did yc during yc we realized code based chat is actually maybe like not the correct startup idea because it doesn't actually seem like people, like companies want this thing.

1:23:51Maybe individual developers do, but companies don't. So we should find something companies want.

1:23:55Turner Novak:Yeah, the true B, the true B2B. The true B, yeah. And again, the funny thing is like, we were still not equipped because we've not even had actual software jobs before. So it's not like we knew how, like what a software company might want. But at least we were a little closer because we were programmers. And so we knew what programmers wanted. How'd you figure that out? Like, how'd you figure out, maybe no one gives a shit about chatting with the code base, but they want to be able to see it in some sense or see the reviews? So the, once we tried a bunch of stuff, so we're like, okay, so we've taught, the thing with the hard part of our code-based chat is getting a large language model that has a very small context window relative to the size of the code-based, how to make it understand a large code-based and reason over it.

1:24:34That's the hard part. And that's what we built all this tech to do. Like I had a background in semantic embeddings. I'd done that stuff in college. And then a Soon and Beshambra were both programming languages nerds. Soon was in the programming languages club at Jorah Tech. So he had this sort of like sophisticated understanding of syntax trees and call graphs and whatnot. And so what we were good at was creating a sort of, you know, teaching these models to understand large code bases. And then chat was the obvious thing to do. If you've taught an LLM how to understand the code base, the obvious thing is you build a chatbot so you can talk to the LLM about the code base and it understands what's happening.

1:25:08So we were looking for other things to do. We said, okay, maybe it would be compelling to make this like an on-call assistant. Like maybe you're trying, there's like an outage and the engineer's trying to figure out what went wrong. And so you're trying to quickly figure out through a code base, like where the issue is coming from. That's one potential path that would be helpful in. But then that just wasn't like, none of these things, like we talked to QA engineers and SDETs and SREs and everything. And it's like, no one just really found it that compelling, like whatever ideas we're coming up with.

1:25:36So we just decided to build an API because people were asking us for an API.

1:25:39Turner Novak:They're like, can you build an API, which is just like the OpenAI API, but then like you add this parameter, which is your GitHub link. And it just allows you to talk to the, to essentially have context-aware LLM APIs. And so we built the API. And then a lot of our customers started using it to build some version of a code review bot in 2024. So this is like summer 2024, we put out this API, API understands your code base. And then people are using it to build a code reviewer to review their pull requests in GitHub and GitLab. We talked to them. We're trying to understand why they were doing that.

1:26:13And they said, we adopted Copilot and Cursor really early. And now we have too many pull requests. We just have too much code to review. And so we have to build these automations for it. And there isn't really an AI code review type product that exists. And that was at the moment where, again, I can pretend to be really smart and say we figured out that everyone was going to need this at some point. But in reality, this is a product. And we found three people that want it. and like that means we can get three people worth of revenue. We can get like three customers over there and we can make three people happy and we can capture some of that value.

1:26:46Turner Novak:Because you were like wandering through the desert and like found water basically. And you're like, we got a drink. Like this is something. We found like just like a glass of water and like a lot of people find glasses and they're able to extrapolate that there must be a well nearby. And then like we just, we weren't doing that. We just wanted a glass of water. And so we picked up the glass of water and we just started drinking out of it. And it was still months later that the takeoff actually started, which is like, so now this is July. We decided to do a code review. We kept it in beta until December.

1:27:18So like four or five months, I think we had maybe like 70 or 80 teams using it by that point. And then from there, it just exploded from there. Like in December, we put it out. And then in like nine months, there were like a thousand companies using it. And it was just like this crazy, like large companies that we work with now that I would like, would have never imagined being able to work with, be able to work with in the first year. I think like it was just this, it just felt like just like dumb luck that we were just like, we found the glass of water that happened to be like from a Mnoshin or something.

1:27:52It was like, it was not like a, like we could not have predicted that this thing would have like the intensity, like this category of product would have the intensive product market fit that it does.

1:28:02Turner Novak:So why did the adoption take off? Were you limiting it when it was in beta? You couldn't sign up and suddenly you're just like, self-serve, you can just start using it if you want and it kind of spread? You could always self-serve. So the only thing that changed is, I think this is kind of the crazy thing. Industries have very strong memetic desire. So around this time, we were now about 18 months. I think the adoption curve for AI Code Review lags behind about 18 months. the adoption curve for coding agents. So people started using coding IDEs. And about 18 months later, every team that adopted it, about 18 months later, they were like, we need an AI code reviewer.

1:28:37It's just how much time it took for it to permeate through the entire company. And it took about a quarter or two for people to realize this has killed our time to merge. We have too much code review now. And we need something to fix this. And I think people couldn't picture that. And this is like, when we started selling an AI code reviewer, people couldn't picture what that looks like. They would ask us how it's different from Copilot. And we were like, Like, well, Copilot generates code. We review code in a pull request. And they're like, I don't get it. Like, why is that different? And people couldn't picture this thing.

1:29:07And then some companies started using it because they had this real problem. And everyone had this problem. And some companies started using it and everyone starts using it. I think a lot of it is just mimetic. There are a lot of rational things that everyone should be using that they don't. There are products that exist that solve people's problems and then people just still don't want them. And then there are some products of those that get to some critical mass of early adoption, some spark. And through mimetic desire, it just spreads and then everyone wants it. I think that's kind of what's happening here.

1:29:37Turner Novak:Yeah, there's probably some element of you just probably ask a couple of friends and a couple of people, I'll give you the same answer. You're like, cool, I'll try this one. Seems like the best one. How did you figure out the pricing? I know we talked about this a little bit earlier. We're like, what was the process generally of figuring out what to charge for it? Honestly, with pricing, we've kind of been very unsophisticated. we just said, we want pricing that is very customer friendly. Customers understand it very easily. They look at it and they're like, okay, this makes sense. I can predict how much it's going to cost.

1:30:08I can kind of compare it to other things I pay for and see how much better or worse it does. It just makes sense to have seed-based pricing with this type of product. Like people are used to paying for GitHub per seed. People are used to paying for Cursor per seed. It just made sense to price it this way. I think what was sort of unusual about this wave is, again, like pre-AI software, you used to just help you do the thing and then AI software does the thing. I think that's like the big difference. I mean, you do the thing, you can charge for the job, not for like assisting the job. And charging for the job is better because it's more attributable.

1:30:43And so you can have, like we say about marketing, marketing that's attributable is priced in. Marketing that's not attributable is usually underpriced. And the same thing is true for software where software that is not attributable, the value is not attributable, is usually significantly less expensive. Like Slack is a good example. Honest to God, Slack is worth more than$7.5 a month per person. Like it creates more value than that in a month. It's just hard to attribute it. And so that's why it's cheap. And the other end of the spectrum, you have like Datadog. Pretty easy to figure out an attribution for Datadog.

1:31:19And so they're able to charge for like the outcome. They're able to have the scaling charge. The easiest one is Stripe, where it's like, we help you facilitate that transaction. And so we take a cut from that transaction. And it's like the perfect, it's a perfect amount of, it's extremely attributable. And so they can create, they can basically take 3 % of your revenue from you, which is like really crazy when you think about it. Like 3 % of your revenue goes Stripe. And yeah, whatever, part of it goes to interchange or whatever, but like, you are kind of giving it a Stripe to begin with. And so I think that like, Like I have, I was feeling that over time, this industry will kind of move towards outcome-based pricing.

1:31:56But for the time being, it's like, it just, you keep it easy. Like you make it easy to buy, like let customers buy it easily and spread first. I think like for now, it's okay to leave a bunch of value on the table that you don't capture. As long as we're creating enormous value for customers and they're paying us an amount of money they see as non-trivial. We can, we can get investment in single and other forms. Like we're talking to a large public crypto company and like they're, like we're doing this like sort of trial with them. And it's like palpable how much they care. Like they're like going really deep into making sure they're getting as much value from it as possible.

1:32:30They're building all these integrations, they're changing their like life cycle around how they do code reviews for this. And like that is the PMF signal I need. Like we're sort of at the final point of the stage where revenue to us isn't intrinsically valuable. It is valuable to the extent that it signals to us what it's worth and not worth building. It is an information-seeking activity to collect revenue. And as time goes on, yeah, I think all companies sort of move from an expanded stage to an extract stage. And I think there it starts to matter more and more how much pricing, exactly how you price.

1:33:04And it's possible that we're sort of close to getting to that place, but I don't think we're there yet. So right now, just keep it easy. Just don't worry too much about creating too much value. So then how did you kind of get that first big enterprise customer? Every customer we've had just came inbound. And they usually heard about us from a different customer. And then sometimes they heard about us from like a blog post. Like there are blog posts where people have talked about comparing Greptile to other products. Or there's blog posts where people have just done like a review of the product.

1:33:33And there's like someone, some developer's blog. Or like someone tweeted about us that's a customer. And like Brex's CTO recently tweeted that like this was the best code reviewer they tried. and like that's where all the like a bunch of traffic came from that yeah i actually dm'd him

1:33:47Turner Novak:i think when i i saw that tweet i dm'd him yeah he didn't get back to me but i was like hey what do you think of this i'm i'm having dutch on the podcast like what do you think brex is a phenomenal company we're brex customers and like they're just working with our engineering team i've gotten like just so bullish on them they're they're so sophisticated with how they do ai just they're I think they're when you talk to the people there it doesn't seem like it's hundreds of engineers it seems like a 10 % engineering team is extremely locked in and they've been able to do this at the scale of hundreds of engineers and I fully believe based on the people I've met there that they'll be able to do this at 10 ,000 engineers if they ever need to Wow, okay So it's just a function of people a lot of self-serve customers discovering the product organically through word of mouth socials, blog posts, etc.

1:34:39Turner Novak:Did you do any influencer marketing or not really? We're starting to do it now, but historically we haven't. We did technical blogs, so we'd solve hard problems or at least interesting problems. And there are sometimes that surprising results. So like one of the early problems that we faced with building an AI code we bought is that they're very nitpicky because LLM is very verbose. So they, common things are technically true, but they're just like kind of a nitpick. And like no one likes nitpicky like coworkers either. Like no one likes the person that's like, Like, oh, actually, you're missing this very specific way of doing login.

1:35:12There are log formats a little bit. It's like little things like this. So like, oh, don't use any in TypeScript. It's like, it's whatever. Sometimes it's fine. And people found that to be very annoying. I think one thing about LLMs is the lack of saying something smart does not tell you a person is stupid. But saying something stupid tells you a person is definitely stupid. And so when in doubt, you should just not say anything. And I think that applying that to LLMs is hard because they're paid by the token. And so they will, they're like incentivized just keep saying stuff. And there's like this paper recently from, I think from OpenAI from Anthropik, which is like, why do LLMs hallucinate?

1:35:47And it's because like, if the reward function is likelihood of being right, then guessing anything at all confidently is like a higher, is like a better on that test than saying, I don't know. Like there are no points for saying, I don't know. But there are some points for being potentially correct. And so like teaching the code review bot to not make picky comments was like a surprisingly difficult problem. We were like a blog post about how we did it. And like that went viral. That was on the front page of Hacker News. A lot of customers came from that. I think with developers, our simple thing is like, developers don't like being sold to, but they like trying new stuff.

1:36:24They like trying interesting things and they like reading and learning. And so we just produce content that is like things we're learning. We're solving interesting problems and like we learn stuff while solving those problems. and we write about them. That ended up being the most powerful way to reach customers. Just create value, write interesting stuff. We've been on the front page of Hacker News probably a dozen times by now.

1:36:46Turner Novak:Interesting. Yeah, I feel like Hacker News is one of those beasts that's just hard to figure out. But when Hacker News likes you, you just got to ride the tiger, I guess, and just love it. Just write things that are surprising to you. I probably spend too much time on Hacker News and I have... And then once you start writing and you start wanting to be in the front page, you start noticing what stuff you click on. And you're like, what are the patterns here? What are? It peaks your curiosity. That's the main one. I think curiosity is the currency of Hacker News. If you can peak someone's curiosity, they'll click on it.

1:37:20And so going into technical detail about pulling back the curtain on the types of problems we're solving. Most people aren't working on building B2B AI agents. Most engineers are not working on that, obviously. Most people are working on different things. But there are interesting insights that come from working on this. Weird problems you face, things that break in interesting ways that are interesting stories to share. And I think those things end up doing the best.

1:37:49Turner Novak:Because people are just curious to know what all is out there, how other people are solving problems, all that stuff. Yeah, yeah, exactly. If I were to see a post that was about Shopify breaks when people do drops, I was listening to, I think it might have been either a podcast or maybe a Hacker News post, which is about the hardest technical challenge Shopify had to solve was that there became a trend in e-commerce to do drops. And drops are the enemy of a company that's trying to scale an e-commerce store. That's the opposite of what you want. You want even predictable traffic, not enormous out-of-pattern spikes and scaling to support those.

1:38:30And it's like, that's not interesting. I wonder how they did that. I wonder how they made it so Supreme could drop something in a Shopify store and it didn't crash the entire website. That's not a really, really interesting problem to read about.

1:38:39Turner Novak:Yeah, interesting. Do you remember how they did it? I don't know. Well, actually, there was a handful of things that separately break, like DB connections break and so on. So they went into detail of that, how that stuff breaks. It actually ended up not being as interesting as I thought. It was like a lot of boring problems to solve. But I clicked on it and I read it and I was like, and the thing I gleaned from it, my conclusion was, wow, Shopify has very high quality engineering talent. So if I was a really smart engineer, I would be like, I should work at Shopify. I could probably learn so much.

1:39:10So if that was the purpose, which is engineering blocks to some degree are part of the recruiting mechanism. And so it did that. I was like, if I was a smart engineer and I want to be better at engineering, I probably want to go work at Shopify. It seems like a really interesting place to work.

1:39:22Turner Novak:Yeah, that's fair. One thing I kind of want to hit on before we jump off. So I know you've kind of had like a little bit of an interesting fundraising journey just from Georgia all the way to San Francisco, all the way up to today. My friend Suds was, I think, one of the people who met you when you were still in Georgia. Right when we moved to San Francisco. So I think he was one of the first people I met in San Francisco. Yeah. Okay. And then how did you kind of raise the first little bit of money when it was just, hey, we've got this survey thing? What was generally like that whole process? We honestly just told people about it and then they wanted to fund us.

1:39:59And I think, I don't know what it was. I think all three of us are just very high energy. And I think people respond well to that when they're funding something that early. There's like the product, I think a lot of people are like, well, this is obviously not going to work. But these people seem so high energy. I'm sure they'll figure something out eventually. And they seem like they course correct when they receive new information. and they're like, and they're, and, and like, so Paul Graham was one of our investors and, and he said something about us and more broadly founders that went to Georgia Tech, which is they have a very high effectiveness to entitlement ratio, where it's like a public school in the South.

1:40:36It's like, you don't become entitled from going there. Like you, you become entitled when you go to a school that's like prestigious, like Stanford or something. He's like, I'm entitled because I went to Stanford. And then I understand, like, it's very hard to get in. It's a, it's one of the best institutions in the world. I think it's like not crazy to come out of it a little bit entitled but and you also like snapper people also very effective at the same time i think jorda tech because it has become a good school before it become a prestigious school and also by being by virtue of being sort of a public school far away from silicon valley far away from new york and like its own isolated corner ends up having like a high ratio i'm guessing that's what people gleaned i'm not entirely sure what it was getting into yc was just i think was just like the slope like when we applied we were like this is a hackathon project we're almost done with it And then we were like, update, we have 100 paying users now.

1:41:22And like, it's growing like 20 % week on week. I think that was like, and I think they could probably also figure out that the code-based chat thing was not going to work. But I think there's just the point was that like, we'd probably do something else if this didn't work. And like, I think there's like, you know, we're, I think we're decently smart, but we're just, we work harder than anyone. And I think that that's like, I think that's what people gleaned early on.

1:41:44Turner Novak:I think you raise money from a pickleball game. Is that true? I didn't, but one of our, like a couple of our early angel investors were like huge pickleball people. And so the first time I played pickleball was here. I'd never heard of it. Like this is how like out of, like this is like out of it, like the rest of America, it's not like what's happening on the coast. I'd never heard of pickleball. I fully thought that it was like, I genuinely remember thinking this. I was like, this must be like, it must be a food. You make a ball of pickles or something. like that's probably what this is and it was like no it's like a game it's like and then and then the it was i think someone described me in such a cryptic way they were like oh pickleball is for like you're like uh too poor for uh golf and and too unathletic for tennis that's who pickleball is for and i was like well why don't i play this game i played it i was like this is a lot of fun this is a really fun game and then and then i so i got into it because of an investor i think it's more accurate oh got it okay that makes sense and that i think you guys had like an interesting story with dilution in YC.

1:42:47Turner Novak:I don't actually know what happened, but when I was talking to Sudsy, mentioned to have you talk about that, what is the significance there? So we raised a little bit of money before YC, and then we raised money after YC as well. And then the question was, should you do YC if you already raised money? You clearly can raise money, why would you do YC? And we're very diligent about not over-diluting. and and you know we we spent sort of a lot of time at our series a we didn't fully like it was not the first thing we optimized for but it's one of the important things to us was to like minimize the amount of dilution we're taking on and so we raised less than we could have like people offered us much more money than we ended up raising in the series a and and we wanted to like suppress that amount as much as possible but i think the and maybe this is helpful for people that are like why would i why would i take the seven percent of actually dilution when i could just like do something else and just raise the money outside of it.

1:43:41I think it's hard to overstate how valuable it ends up being in the long term. I have a cousin that works at a... He's a phenomenal engineer. I had, I think, a 10 or 12-year career across different companies. Recently started as a staff engineer and then later an engineering manager at Coinbase. And he was talking about, I was like, Coinbase is the largest company I've ever worked at and is the one that feels most like a startup, like extremely high velocity. And everyone is so locked in. And then every interaction he's had with Brian, Brian Armstrong there has been like, this guy's got his eyes around the ball.

1:44:23It's nuts how locked in he is. And I think that there, and you hear the same thing about Tony at DoorDash and so on. And I have a feeling from what I can tell, there's like a reprogramming of the brain that happens when you do YC, if you do it correctly, and if you do it in an engaged way, that just like serves you forever. And that's sort of like the intangible benefit. I think the dilution pays for itself when you raise like a high valuation. Like people complain about YC companies, like rounds being too expensive. And like as a founder, the 7%, you just get back when you raise that evaluation that's like two, two and a half times higher than what you would have ordinarily raised at.

1:45:01But I think the better way to think about it, like what do you get in return for the dilution? I think what you get for YC is worth it. I think it's very hard to justify like increasing your dilution usually, but I think the specific one, like with hindsight, now I can say with confidence that it's like, it's good.

1:45:18Turner Novak:Do you think the way to kind of get around YC dilution is you just sell less of the company and in a following round, like you don't have to sell 20 % of the company in a specific round. It's generally just like the, yeah, people generally do, but you don't have to. Yeah, you don't have to. I think you can raise less. I mean, we said no to almost all, again, the seed round, we said no to most checks. We initialized, invested in us at the time. And the only other ones, we said no to every other angel. We only took two other ones, which were JJ and Fleelman and Rich Abramman. And just because we just liked them both, I think we're awesome.

1:45:55And they've been incredibly helpful over the last years. I think it was like 100 % worth it. But every other firm, they were really, really great investors. that we just was like, I'm sorry, we just like, we don't have room and we don't want to, we don't need more money than this. And I think to some degree, we probably still ended up raising too much, but, but obviously like, I like to be on the safer side. I think the idea of having like 18 months of runway as the standard is insane to me. I think we definitely should have more than that,

1:46:20Turner Novak:like possible. Oh yeah. Fair. Yeah. I think I just like, I don't need the extra stress beyond everything. I was just like, we also might run out of money. Like, I think that I'm okay diluting a little bit more if I can just kind of know that we're safe on that front. Yeah. You had a pretty interesting way of framing how you just think about fundraising in general. You kind of think about it as like dating and building a credit score. I was going to ask, what does that mean? Because you mentioned, I don't actually know. So it's like an interesting way of thinking about it. A lot of this is just like sort of received wisdom around seed and series A and stuff.

1:46:56But like, I think early on raising money, there's investors that are just like good people. And you'll probably like through references, figure out who they are. And obviously YC has this, one of the advantages of it, you have this network and you can figure out who the good people are. And I think just raise a little bit of money from them, just enough that you can survive off of it. If you think you should raise less because you want to create urgency and pressure, I really think you should find another source for that that's less catastrophic like another source for the urgency I think running out of money as a source of urgency seems like a crazy thing to play with like it's like maybe like I don't know find a different

1:47:36Turner Novak:place to get urgency from you literally like you run out of money like you just die like you can't yeah that can't be the thing there has to be like a less insane way to be urgent and for us it's like we'll lose the market to someone else like that's the urgency like we don't need the urgency of like running out of money like we have we're totally fine on on on runway. And like, we, we, we have sort of, we're very prudent with our spending and, and like we we've been, we've kept a very limited head count and everything. I think it's a series A, the advice that I received from, from Brad, who's a partner of IC was just like, you might, if things go well, you're going to work with your board partner very closely for like a decade or more.

1:48:15And, and that is like, it's a 10 year permanent relationship, essentially, Like over that course of time, you can't change your mind on it. Like this person is going to be on your board forever. You should treat it with that level of gravity. It's like a marriage in some sense. And so I was like, well, what would I do if I was getting married? It's probably go on like dates and like meet people, get to know people. And so I just spent the next few weeks just meeting all of the great investors that invest in like dev tools and infrastructure type things. I got introduced to Eric at Benchmark through Mike at SV Angel.

1:48:48and he, within our first meeting, it was like, it was extremely obvious to me that this was like exactly the right person. And thankfully he felt similarly. And so I think that ended up working really well. But I think like, obviously, you know, it's increasingly less common for people to do board seats at Series A. But I think they're still frequent enough. And it's like, I think it really matters to getting that right. Like Eric and I, obviously it was really early days. We've only been working together for like a couple of months, but the conversations are just fruitful. Like I come out of those, like in the 30 and 40, 30, 45 minute conversations.

1:49:26And I'm like, there's like a new thing for me to think about that I think is really compelling. And there's like more clarity than we had, than we had when the call started. And, and obviously like references there matter to everyone who'd worked with him, whether it was Spencer at Amplitude or Saji at Benchling and everyone else I talked to was just like, this is the greatest investor of all time. they've created enormous value over the course of the last 10 years of working together.

1:49:48Turner Novak:Yeah. Spencer's a big Eric fan. Actually, you mentioned you listened to the episode we did together. Spencer's actually the one who told me to have him on. He's just like, you got to have Eric on the podcast. I was like, all right. I really liked that episode. Oh, yeah. Thank you. Yeah. One thing I've been trying to weigh is founders versus investors. Personally, I think it's more interesting to just talk to people who built stuff. so I've been kind of leaning if I'm talking to an investor it's like you kind of like created something there's a there's a long list of investors who are like hey I want to come on the podcast so you're kind of I'm kind of like always fighting them off of like you know so I've been trying to figure out like what is the most interesting things to get investors to talk about like so what did you like about that episode just just curious I think part of it is just Eric's been a founder before in the internet era I think the thing I enjoy most about talking to investors is just that they're like, because they're older, they were around the internet era and then the mobile era.

1:50:44And so there's just like stories from them that I think are so interesting. Like, I think we could learn so much from that era of time. Like the internet companies came, they had, there was this frenzy and then like 90 % of them died. But like Amazon and Google did not die. What did they do? And how do I do that? Like whatever, like what can I learn from what they did? And like, how can I not be one of the 10 ,000 companies that died? And instead be one of the companies that became like really large, important and influential. And like, I feel like we don't pay enough attention to that. And like, I was not around that.

1:51:11Like the inner bubble burst before I was born. And like, all these companies predate my time, obviously. But like, Eric was there. Like, we have office hours at Paul Graham every now and then since he invested in us shortly after the batch. And like, he was there. He was in the middle of all of it. He was at Yahoo. He sold his company at Yahoo at the time. And like, there's just wisdom from that era that comes. And with Eric, it's like the, I don't know if he was the one that said this or someone else, but the sort of the thing that investor adds to your company is that like, they're not in the trench with you, but they're like at the surface level so they can see the other trenches and they can like point say your trench, I know sucks, but like, I'm looking at the next one over there and that one's, that was also pretty bad.

1:51:52So like, you know, but this third one looks fine. Like maybe try that one. And it's just like stuff like this. It's like the wisdom you get from like, from a top down view and the perspective you get from like working with all these different companies. I would actually argue that I think like investors actually are good podcast guests sometimes or maybe even often for one, they're just like better at talking. It's like such a much larger part of their job.

1:52:11Turner Novak:I think they're like, it's like, they're talking about more abstract things. Like I can talk, I can talk about like code review for like four hours and it's just like, who acts like the total time for people that are interested in that type of thing is not that large. And I think investors have an easier time talking more abstractly about things that are more broadly interesting. Yeah, that's fair. And then generally speaking, They're also better at talking about things that are more trendy. Like, I guess, in your case, you know, if I'm like thinking about what the title, I actually have no idea what we're going to call this.

1:52:42Turner Novak:But I'm sure there's like AI in the title. I'm sure the thumbnail, there was like some AI thing. So it's like, it's like kind of trendy. But generally, as a founder, like, you might not even know what's cool, because you're just not paying attention. You're just focusing on whatever you're doing versus, you know, like most VCs could recite why Web3 is going to be a thing. Like why every code review should have an NFT because NFT is like, you know, everything should be on the blockchain or whatever. Like you'd probably be like, you know, that sounds stupid. But like an investor could tell you the pitch of like why everything's going to be on the blockchain in the future.

1:53:17And just like, I don't know, your investors have been right for like 12, 13 years. like, you know, the best investors did see the future. Like, you know, like, I don't know. Like there's, there's this, there's one side, which is just like, like, I think over obsession around investors. And then I think that there's this other subculture of just like, oh, investors are dumb. And I think that's not true either. Like, I think the truth is that like, like all people, there's some of those just like genuinely brilliant people. And like, they, and like, and there are others that aren't, but like, that's just like, that's true for every category of person.

1:53:50and this is what founders do. I've met a lot of terrible founders, but also a lot of really, really incredible founders. I think that's just true for everyone. And I think the discourse around it is just like, I think, like feudalistic and tribalistic to some degree.

1:54:03Turner Novak:Yeah, you basically can't say that things are gray. They have to be black and white. Like you basically, there must be a heuristic. And so anyways, well, this is a lot of fun. Thanks for doing this. Yeah, thanks for having me. This is great. and thank you for listening. A quick thanks again to Numeral and Hanover Park for supporting this episode. Head to numeralhq.com for the fastest, easiest way to stay compliant with US sales tax and global VAT. Head to hanoverpark.com slash Turner to upgrade your fund admin to the 21st century. If you missed it, make sure to check out last week's episode with Adit Abraham on everything he learned scaling Reducto from YC batch to a series B in 18 months.

1:54:43Turner Novak:If you like conversation, please comment, subscribe, share with a friend and name your next PR review after me. If you don't want to miss a future episode, subscribe to my newsletter, The Split, linked in the description to get each episode plus a transcript email directly to your inbox every week. Thanks again for listening. See you next time.