[Music] Hey everyone and welcome to Generative Now. I am Michael Mcnano. I'm a partner at Lightseed. This week on the show, I spoke with the co-founders of Granola, Chris Pedrical and Sam Stevenson. Granola is a powerful note-taking app that uses AI to compile and summarize meeting notes. Chris and Sam and I talked about their journey as co-founders, how they have quickly become a must-have tool for many companies in tech, sales, recruiting, and beyond, and the areas where Granola might be trying to grow next. We spoke in front of a live audience at the Granola headquarters in London, and it was a lot of fun. So, let's get into it. Hey guys. Thanks, Mike. Thanks for hosting us in uh your amazing office. Thanks for coming. Yeah. This office is like brand new for you guys, right? Couple months. Something like that. Yeah. Yeah. Sam just carried all the plants in himself. Is that true? We're going quiet. Almost a few other people. Like actually you went to you went to the plant market at like 4 a.m. with like We did do that. Yeah. People sold us a truck and like carried it up all the stuff. That's like a great example of building a startup, right? Yeah. That was like the least hard thing he did that day. All right. Obviously, everyone I I would hope most people in this room are familiar with Granola and we want to get into the app layer and what it means to build at the app layer, but tell us about the product. Tell us about the company. How'd you guys get started? How'd you end up doing what you're doing right now? Give us a little bit of the the origin story. So, this was three years ago. I quit Google. I knew I wanted to do a startup in London. I didn't know what I was going to do. and um like within a week of quitting Google I started playing with uh GPT3 the instruct version of of it that had just come out and was blown away as I'm sure everyone here at some point in the last 5 years has been with all and I was like okay this is this is new this is different I don't know what it is exactly so I started messing around with it I knew I wanted to start a startup so I started looking for a potential co-founder and I basically was like convinced there's two things at the time I'm like okay maybe if I need a technical co-founder it should be someone who knows to train models. Um, which I changed my mind on later. And then the other really hard thing I was like, "Oh man, there's a bunch of new UI that's going to have to be designed like that's AI native." So like I need a someone who's really thoughtful at that. And I started exploring these like tools for thought forums and I stumbled ac across uh this online meetup called like tools for thinking rocks. What are tools for thought? Just to help us all understand what that means. All right. All right. You're going have to cut me off. Tools for thought are basically like like humans are tool makers, right? Like my friend Paul was here like taught me this like humans are toolmakers. one of the things that sets us apart from animals and basically what we are able to do is really limited by the tools we have available to us right so classic Steve Jobs uh bicycle for the mind right but like the the original tool thought it's language it's like written language right then you can look at like mathematical notation right like the if you're using like Roman numerals you can only do so much math in your head whereas if you use what are Arabic nu like whatever we use today like you can do much more complicated stuff with paper and pencil and basically like every development of like um human tool making has meant that humans can do more and more and more and um I think AI is like the ultimate tippercharger of tools for thinking. Anyway, so I found this guy online in a tools for thinking meetup group. Uh I didn't even meet him. I just saw I just saw his profile and I sent him an email being like, "Hey, do you want to grab a beer sometime?" And somehow uh he said yes. Yeah, we uh so I think yeah, we were we basically like both were very aligned from the beginning on like we AI is going to change the landscape of like the tools we use and either the tools that exist right now are going to have to change everything about what they do or new people are going to come in and and take over and and so that felt like an exciting place to be starting a startup from like it's a it's a opportunity that's just opened from both of our prior experiences where you know Chris talked about how we think um building a really good product experience is going to be a lot of what matters in making something successful in this space. And I think to do that, we were both very keen to have a very specific like and painful user problem that we could be designing around. Um like you want to have us you want to be able to picture a person in your head and picture them struggling with a thing so that you can kind of like make the tool that that solves the struggle. Um, and so we spent a while just just like open-mindedly kind of wandering around looking for that struggle, talking to people about their days, like trying to figure out where are the pain points, what what sucks about people's jobs that we could possibly make easier. Um, and like I think a thing that came up again and again was like people whose whose job revolves around meetings and talking to people, every time you have a meeting uh with somebody, that meeting tends to create a kind of pile of follow-up work. Whether it's simple stuff like just um writing up notes that you care about or uh sending a follow-up email to the person you met or whether it's complicated stuff like updating 20 different fields in a CRM and triggering a workflow and and an email campaign to somebody, you know, things like that. A lot of people who have calls have a version of those kind of things after a meeting and they all universally hated doing them. Uh it's all kind of menial work that isn't isn't what you get energy from in your job. Um, and it felt like the kind of stuff that AI was like primed to be able to help with, uh, if not then when we were doing it, at least in a few years time. Um, and so we started pushing on on that on like how can we how can we kind of make a tool that is in your meeting that eventually will be able to help you do a lot of this kind of menial work that happens around meetings. Chris said that it's going to be so important with AI to build a great product experience. So I totally agree. Um, but I would say that for a lot of people in the AI community, in tech, in VC, in startups, that was not obvious to many people a year ago. I'm sure you guys remember a year a year year and a half ago, there was all this talk about, oh, if you're building at the app layer of AI, you're just a rapper on GPT4 or GPT4, you know, what whatever anthropic claude. Um, now it feels like we've done a 180. There's so much excitement about the app layer and again you know granola is an example that's often cited as as being you know one of the one of the potential winners. What changed? Why is there been Why do you think I know you guys haven't changed but why do you think everyone else has sort of changed their mind about this opportunity? I think a few things happened. One is these models just kept getting fa better and better faster and faster and it became very clear that it was just it made way more sense to just use the best like frontier model out there than try to train your own thing. You're always going to be slower, right? Um that's one. Two, super hard and expensive to train your own model. So it's going to be a couple big shops that are going to do that. And then three, man, you get all the benefits from those models. So like if you can apply it to the right use case, it's really powerful and I think our view of that from the beginning has always been low frequency use cases that are maybe non-critical are going to be eaten up by the general agents. So I think if if it's like a consumer use case that you do like twice a month, it's definitely going to go to catch PT or anthropic. If you are uh doing something that like really matters like it's like professional tooling where your performance really matters and you want to optimize for that use case then bespoke tools that are optimized for that are going to be way better and I think that's what you're starting to see things like um like cursors valuation like windsurf just got acquired I think it's like prototypical like they're just like rappers on on summit 3.7 or whatever right um but actually they're like amazing and there's so it's hard to build great software and the delta of if you're using one of those products is how much more productive you can be really matters. Um and I think now the market's kind of I think this thing is like a pendulum, right? We get really excited about one thing and then it's like oh there's a glimmer of the future might be different and people get very excited about that. We think that has sticking power, right? Because we think the tools you use matter and we think the like profession professional tooling has always been a thing, right? Um and uh if it makes you 10 20 30% 50% better at your job like that's going to always have a lot of value and economic value. It does mean we have to be quite selective about the things like the the challenges that we choose to bite off and which we choose to like leave alone. When we started which was like GPT3 time and um real-time transcription had kind of just become a thing that was available by an API. Uh, but it wasn't great. You know, like transcription was obviously bad in a bunch of ways. Like it would kind of miss things. The notes that we wrote weren't amazing just because the models weren't amazing. We had tons and tons of conversations about like, yeah, you know, like should we, you know, what should we be investing our time in because like the um some stuff is just going to keep getting better without without us doing anything. Um, you know, the quality of the AI output, the speed, the cheapness, all of those things. Um, and some things are not going to get better unless we like push really hard on it and try to figure out what a good solution is. And so I think a lot of the game for us has been like picking our battles and like knowing what to innovate on and what to just like wait for it to get better, you know? Give us some examples of some things, you know, real-time transcription is one of them, but like what are some other things that you, you know, very intentionally decided not to work on? And maybe what are one or two things that that you did you're like, "Oh, this is our job to solve. Granola can be the best at this." The obvious one to me was um language support. Like when we launched it immediately was like the most requested thing for granola was to support multiple languages. Um I think it still is and we spent like a week working on it like um trying to figure out a good interface. Uh it was like kind of available on one of the transcription providers. I guess it wasn't great the the what the language situation now which meant that we would have had to it was looking like it was going to be like a few weeks to a month long project to make a good interface to help you pick the right language for the right time that the meeting that you're in. Um which is a huge investment like a month of time, right? And that to me feels like a thing that there are dozens of companies out there really incentivized to figure out multi- language real-time transcription models. And um if we just wait like it's going to happen and and the experience will be way better in that world than anything we can kind of think up to like hack around the fact that it's not good right now. Yeah. Another example is like context uh window length. It was too small when we launched. You could only do like 30 minute meetings. Um and we could have done a bunch of work to like okay try to chunk that or we just just wait a little bit and the context windows got bigger. Yeah, exactly. Yeah. Another one's rag actually. Can you explain to people? Retrieval augmented generation. Basically the idea is like so context window most people here probably know this but uh uh a model can only take so many tokens so much context into its like memory. Um, and if you have uh more, let's say you have like in our case a repository of meetings that are larger than a context window, you have to figure out like which of those do you put into the memory. And um, like there's all these naive approaches where you basically kind of do a search across those and you choose a subset. Doing that well is hard, right? Doing it doing it not well is super easy. Doing that well is really hard. Um, but context windows keep getting bigger. So you can get away with by just sticking a lot of stuff in there. uh which is like and and in some ways it's like an unintuitive I think if you put your engineering hat on you're like a that's wrong you know we should we should engineer this throwing more stuff but it but it it unstructured it it like AI breaks intuitions man it's like um sometimes you're like oh it's like it's very imprecise we're putting all this stuff in there but like I think these models are smarter and more intuitive than we expect and sometimes they'll the moments where I'm like oh  are usually where it picks up on something I wouldn't have expected a machine to pick up on. You know, it'll be like actually in that meeting 6 months ago, you said this thing and uh and then now you said this and like we wouldn't put that in the rag if you stick it all in the context window. Like sometimes magic comes out, right? Let's talk about the business model of building at the app layer. It feels like so many companies right now are basically just just charging for prints, right? We see all these products that charge for credits. Yeah. And really what what those credits go to are just just hitting the model, right? How do you guys and Granola think about the business model? Like is that the type of business model these companies should be pursuing? Should they not be pursuing? What's the opportunity to to build like a huge business at the app layer on top of the models? I think a lot of the way we think about it is probably not too like our business model is probably not too different like pre or post AI. Like I think ultimately we're trying to make a tool that's like valuable enough that a company will give us money for it. And um there are things that we want to push on to to kind of make the thing feel more valuable which are not really to do with AI but to do with like app team app building I guess like if we can if we can unlock network effects in granola where like there's a the granola gets better the more people in your team are using it and it becomes like this valuable repository in and of itself. I I think that's a thing that we have a lot of signal that companies will will pay good money for and um it's kind of independent from AI, I guess. Although the enables you to do cool stuff with that. If you're just monetizing the AI, you're you're effectively just like a reseller, right, for Open AI, whereas like if you charge for the repository, you're charging for granola, something only that granola can provide, right? Yeah. I I do think we're like an interesting moment in history because it's kind of a land grab right now. there's like new products that are possible that couldn't couldn't exist before and we know that the cost of running these products 2 years from now will be vastly cheaper than they are today. So there's like and maybe that will always be the case but it's kind of easier for me to just think about the next few years. So, we're in this world where um it's going to be cheap to run granola, I don't know, PA or whatever you want um 2 years from now, but it's quite expensive to run now, but there's a lot of user demand. So, like what do you do in that kind of situation? And I I think it's the kind of thing where you have to have I think you have to build for the future, right? And you have to you have to figure out how to make that work for your company because if you build for today, I think you'll make all the wrong optimizations. Uh which does mean it's a capital intensive play right now. when we uh forecast our finances, you know, into the future, like uh if you don't account for things getting cheaper, then then it gets like really expensive really quickly. Exponential with like 10% we can regrow. Yeah. Yeah. Yeah. And so and so I mean part of part of the company's bet I guess is that is that this stuff is going to get cheaper and you know and there's going to be ways some things we'll always want to be on the frontier of. I think like I could see like um uh being able to do chat and document creation on top of the huge body of all of your company's meetings is like the kind of thing where just the more power the better. But like transcription I could see hitting a ceiling where where there's a point where it's good enough and then and then like and then again be it's just like cool let's now get that transcription for like as little money as we can so that so that you know that's our main running cost like that can that can kind of go away. Lightseed, you know, was one of the first investors a couple years ago. And I will say it it was so fun for me and I know everyone else in the team watching you guys build from day one just like from zero lines of code to what it is today. And you know, I remember the launch moment 22nd. May 22nd. We're coming up on a year. That launch moment, it was amazing. It felt like almost instant product market fit, which is so rare, never happens. Yeah. I got to ask like tell us about the process of building the first version of Granola so that so that you could have that day you launched which again it's it's it's nearly impossible to do. I don't know you know we try and be deliberate about things but something can happen by accident too but I think the things that we uh we're like deliberate about were the hard thing about granola was probably going to be figuring out what's like an interaction or what's that lets a user get the stuff they care about out of a meeting in a way that feels really natural and really effortless. um like figuring out that is like is just a huge part of what we have to do to make the product successful. And so I think the first I don't know six nine months of Granola were like just experiment after experiment after experiment like trying things to figure out what that might be. You know we'd build a thing put it out in the world uh be constantly talking to new users and watching how they react to it and how they use it. And um and over time we we you know threw away a lot of the things we tried and were able to hone in on something that felt like it could work. The first 6 months was was like a gradual growing of complexity in the thing as we like threw more ideas into it. You know, trying this and that and this and that. And at some point I think we found we felt like we maybe found a thing that could work. Um this like you know type your notes at the end Granola fleshes it out on the same piece of paper that that kind of thing. Um and then we kind of went through this process of like cutting back and streamlining everything until it was really just that feature. Um and that's what we launched with throughout this we were kind of like the goal was to build a daily habit for our users like can we make this a daily use product in the small number of beta use beta testers that we had and um we had this uh this this chart called the dot plot which is like uh you can see each individual user that uses granola um day by day and how many meetings they did on a given day and uh that helped us be really honest with ourselves about like is someone reliably picking this up and using this in their meetings or are they just kind of dipping in and out or you know is it kind of random? So yeah, we we were in closed beta for a year and uh we had about 150 people that we had onboarded by the by the time we decided to launch and we had manually onboarded all of them at that point. Uh and I guess looking back on it it's so funny we never like the dos only connect back but I didn't really think was ready when we launched it like Mike pushed us to launch. No, really. And like typical VC actually been pushing us to launch for about nine months before that. We held them off for nine months. But I, you know, it's like at that point all we could see were the things that were that were wrong with it. Um, which is like an interesting lesson, right? Because uh once we put it out in the world, it it just kind of it actually hit a bunch of quarters. Uh but we didn't necessarily appreciate the depth of that until we we put it out there. Sam, I've heard you talk a little bit about your design process and about how the team really thinks about designing for what people actually need, not what they think they need. I've heard you use the term lizard brain. Um, explain. In building software, it's really easy to um I speak as someone who's done this over and over and over again on things I've worked on. Um, like it's really easy to get theoretical about like what a user might want and like um this thing would be cool. I've got such a good feeling about this. I'm going to, you know, I think this is how it how the app should be. Um, and when you interview users, you know, they can tell you all of their great ideas for the product and and it's really easy to just build what they want because they're asking for it. One thing that we were kind of paranoid about from the start was um I guess especially in our use case like meetings are a super high stress uh situation in that when you're in a meeting especially like a backto-back meeting where you know where you're you're maybe it's 2 minutes past the hour you're already late for your next meeting you're like  you know trying to make excuses to get off the call um and then you get off the call and then you got to rapidly get into the next one as quick as you can and then you're like oh my god who am I talking to why are we doing this you know all that stuff you have so little brain space for for a piece of software at that moment to try and help you like you you're just trying to deal with the basics of getting the next person in front of you. We just have like this this I don't know 1% of your brain to play with you know as like as a people designing a product. Um and I think keeping that in mind like keeping the kind of stressed out backtoback kind of moment in in our heads as we were designing it like helped keep us honest to what's going to fly what's going to work in this. I think people often talk about how simple granola is and how how it's feels nice because of that. I think that's just a a function of like we really can't put many buns in front of you when you're in that in that situation. You don't have the head space for it. That's really cool. Chris, uh you built and scaled and sold another company before this Socratic. I had the pleasure of watching you do that as well because the company that I was building was on a street block right behind you. Yep. Um in New York. That was a while ago. And you know, one thing I often think about is especially with you guys building this is is wondering like what's it like to build a company now with AI versus building a company that didn't have AI? Like how what's the difference in building companies across these two eras? Ask me that in two or three years. I think I'll have a much better answer. Well, I I guess one is uh so boss, our CTO, who um who's not here right now, like he's like I look to him because I think he's the best at this in the team, but he really really pushes us internally to use AI as much as possible. So, it's like an active goal to reduce the number of lines our engineers write every day. Um and I think that you like you actually do need to push people for that because we all have habits. We've been working we've been doing stuff for a while and the world's changing very quickly. So if like the org isn't doing that um then you're missing out. The other thing is I think people ask a lot about like okay what's the makeup of a company going to look like in this post AI world? How big does it have to be? My my view there is that like I don't know what it'll be like in five years but but for us the product is core. So we need a really we need a bunch of really thoughtful you know best best-in-class people working on the product. There are other functions where I like in the past we might have built a really big customer success function where I don't expect us to do that. I expect us to use like whatever the best and greatest like AI tooling is and we'll still have a great team there. It's just like how that team spends their time and like they might look more like um like engineers in a way um in terms of like building systems even though they might not be writing code. And the last one is the world is changing and everyone's watching and interested and wanting to try stuff out and that wasn't the case uh with my last startup. I'm used to startups being like a slog of you like you fighting so hard to get people to care about what you're doing and um I kind of feel like the rug got pulled under me out from under me with granola because we put it out there and we're like all right. So I'm like I'm like no one's going to care about this you know we have to like keep working on it keep working keep working on it and all of a sudden I'm like it just started growing and then and then stuff just started breaking internally because we weren't like mentally prepared for that. Um, so I that's like macro environment questions like those things change quickly. But that's that's been a defining defining part of this journey is just trying to keep up with the change and keep up with the growth. And I think that inevitably forces you guys and really any team building an AI right now to just move so freaking fast, which inevitably creates a different type of challenge for the company. It's like how do you maintain quality? How do you maintain uh taste, right? Like taste has been this thing. I feel like it's like become this really annoying word actually. Gotta have taste. Uh but but I think again granola gets cited as one of these products that just like oh it's beautiful, great design, amazing taste. Like how do you think about maintaining that when you're moving so fast and when you're building a team? Uh it it becomes so important I imagine with with each and every person you bring on. I think we do all right at this but I think we we like there's there's much more we can do to make this better. Um but I think things that I think we do well or that of WordPress um we screen engineers as part of the interview process um for like product thinking I guess like can you can you think from the point of view of a user and like uh you know when there's a technical problem put in front of you like get to the why of like why is this a problem for the user and you know that helps you make the right trade-offs in cutting the scope and really just building the thing that's going to solve the person's problem not like this beautiful uh technical masterpiece of an execution. There are there are types of features where you can where like um once we have good systems set up like you know the UI of Granola is kind of figured out you can just kind of like ship and iterate and push stuff out very quickly there and and we don't need to kind of be so cautious about about that stuff. Um you can can always roll it back you know a couple days later. Um, and and then that way we can kind of like help like reserve our judgment and the taking the time to kind of pour over the details on the things that really matter or kind of like in the core flow of of someone using Granola. New primitives in the app. The basic we're trying to get better at the one-way door versus two-way door, right? So, it's like if it's two-way door, can we just ship changes quickly, see how what people think and go from go from there. That said, I think what people love about granola is that it's simple, minimals, and gets out of your way and you add 50 buttons in there with new features, you kind of kill the the golden goose, right? And I think we're figuring out how to find that balance because we do have to move quickly, but we also need to keep the soul of the product like intact. I want to talk a little bit about building a team here in London. Um, Granola, I will tell you in the States, I mean, you guys know this in New York in Silicon Valley, I mean, people are obsessed. It's kind of like you're building a Silicon Valley startup in London. Is is that intentional? And what is that like? It is intentional. Hopefully you guys can meet some of our team. And I think what you'll you'll find when you meet them is everyone on the team kind of wants to have that like really ambitious like classic startup journey. Uh and we just happen to be in London. And that's like a pretty I think it's a pretty beautiful twist on it because um you know get to you get to be in London but you also kind of get to live the Silicon Valley dream and and that's pretty rare. Um but I I think there's like like the reality is there's like a most successful tech companies come out of Silicon Valley, right? And there's like there's a culture and like learnings and best practices about how to build a hypers scale tech startup that were kind of invented over there. And I'm not saying we wholesale copy all of that, but I think our our DNA and you can hear my accent. Our DNA is kind of comes from the valley. That said, there's amazing talent in London, right? And it's an incredible it's a a pretty fantastic group of people and perspectives that are here. So, I think there's like a real big opportunity like for us to build a Silicon Valley South startup, but like in London with the talent that's here. Um, and I think something that kind of benefits us is at the app layer, there aren't that many kind of like buzzy AI app companies in London. There are some pretty impressive ones the foundation layer, right? Like if the 11 labs all the way back to like deep mind, right, where u so there's incredible like AI talent in London, but at the app layer, we're kind of like a bigger fish in a smaller pond compared if we were in Silicon Valley. There's just so much stuff going on there. So we're kind of a magnet for type of person. So it's probably like a bit of a strategic advantage when it comes to hiring, building the team, being in a different market is actually helpful. Yeah, there are trade-offs with everything, right? Um I I feel like we definitely get uh access to incredible people here. Uh that those people will be lots of different companies be trying to hire those people in Silicon Valley whereas here they would kind of get like first first dibs on them. You know there's also a lot of stuff happening in Silicon Valley, right? So it's like it's important for us to stay current, understand what's going on there. Um can also be a full-time job to keep up with what's going on in AI, right? So you want to strike the right balance of like keeping your finger on the pulse but don't get distracted, right? because there's so much noise and so much trash. At the end of the day, all that really matters is building something that's useful that's going to grow. What other like are there other London based companies or products or teams that that you guys take inspiration from? When you think about that, when you think about building a team here in London, I think the AIO folks have done a a great job at attracting a bunch of good talent. Uh people from 11 Labs I've met um plane I think at building like a really great user experience, you know, on a product category. listed for a long time. Yeah, I think that like Monzo's wise card, all the fintech ones are like I think my view is basically like it's too easy if you're in London to think about the UK and to think about Europe. And like my my general view is that in this AI space that's so competitive, you need to be competitive in the US because otherwise someone will win the US and then you're going to have to fight them in Europe. Whereas there's no reason why you can't go after the US market from here, right? Like most people don't know granola. like users don't care. Like they all think it's an SF company. Um so it's like I think it's a question of ambition, right? And I think in AI the the prize is so big, there's going to be so much competition, you have to have that high ambition level or just, you know, you're going to get eaten anyway. So we're taking a very like world view from the get-go. Uh and we just happen to be base here, but we're not like doing all all our user interviews with folks in London. We're doing them all over the place. Uh maybe last question for me and then I want to open up to everyone in the room. Um what what is what is the ultimate ambition of granola? We we know it as the the notetaker for people in backto-back meetings. You said you want to build you're building with Silicon Valley type ambition. What does it become? What is the you know what is the massive Silicon Valley like success version of granola. Other professional categories have already figured out their like power tools that people spend their day in and it kind of helps them get their best work done. Um uh designers have Figma or Photoshop back in the day. engineers have IDs like cursor or VS code. If you if you're an engineer or designer for example like seven or eight hours of your day is spent in those tools and they amplify what you can do by a huge multiplier. up until now like people uh folks who work in like I don't know doing like people stuff I guess you know talking to people whether that's like sales or customerf facing stuff or managing or investing like uh you've not really been able to have one of these workspaces because like the the kind of fundamental unit of your work is natural language and conversation and that's just too squishy for like uh traditional software to deal with. It's not it's not code and it's not pixels. But I think we are at this exciting point where like we can fin like computers can finally make sense of natural language and organize it and so I think we have a shot at creating that kind of workspace that that people who do people stuff kind of live in and and it amplifies them makes them work better work faster. I agree with all of that. Uh, but if I zoom out even more, I think we're like we're so lucky to be alive at a moment in history where we talked about humans as toolmakers. Like the tools that humans use to think and to do work are being reinvented. And I really do think AI is is like if computers were a bicycle for the mind. Like AI has a potential to be a jetack for the mind. So like my ambition is can we build tools that help people actually think smarter, work better, do better things. It's like be a multiplier on on human capability. um kind of hearkens back to I don't know how much of you have like studied like Douglas Anglebar but there are all these ideas that the uh birth of computing basically of like what impact is going to have on you know society and our ability to do great things that we could never do before I think computers did do that and I think now it's like the second chapter of that like what what are the new heights that we can reach to. Awesome. I I could ask questions all night but I know people here probably have lots of questions. Go right here. Hi, I'm Emily. I'm working on something new and um I'm really curious cuz I'm very early days on how you guys approached when you were early your feedback loops in your early iterations. I think something I'm trying to think through is like how do I know when I have enough data to move forward? And also if I don't have enough data to move forward, what kind of data am I looking for? Is it qual? Is it quant? How much do I need? So I would love your guys' thoughts. I I have like a philosoph philosophical view on this. Ba basically it's all qualitative. Like my my view is like in the early days it's actually not even that. It's like you need to go off of your intuitions. I I I believe that deeply. If you don't fundamentally like feel like the product or the need in like deep down inside, then that's a real problem. Uh I'm not saying go off in a in a closet and like just work in isolation for six months. I think talking to users and people is paramount. You should do it every day basically. But you shouldn't, it's not the like ask people if they want to build faster horses thing. It's you by spending time with users and watching them try to do stuff and fail. You are honing your you're giving your mental context like your your brain all the all this uh really relevant context so that your intuitions are better honed. I think if you're looking for anything qualitative um it's it's almost impossible in the early days. I think everyone here would love for Granola not to become a CRM. So my question would be about to create the sort of jetpack of the mind. What does the future of actually design look like for the jetpack of the mind? I hear you with the CRM thing. Yeah. Uh uh I think the way we think about it is um one the thing that has served us really well so far is like putting the individual user and the particular moment that they're in when they're using granola like above everything else and designing a great experience around that. And so you know when we're talking about how to spend our time and what things to build that user has come first and and like and yeah companies pay for us but it's not kind of the the thing that's driving every kind of product and feature decision. It's like make granola great for for the user. I guess there's kind of two directions we we I think of this pushing in like um we've seen when teams use granola together. There is like a lot of value in um having the kind of shared context in one place that where you can you can kind of look at not just the one meeting you had then but every meeting that your team has had around a specific subject and do stuff with that. If you're a sales person trying to get better at your job, uh then then being able to like look back at every call the sales team has had for the last week and query like why are we losing deals and what what things that people said that helped us win when we thought we were going to lose and things like that. It's it's super helpful to the individual. Yeah, I guess just adding to that it's in my mind it's all about AI is as good as the context as it has, right? And then the UI that lets you do useful things on top of that context. And right now AI like granola looks like it generates meeting notes and that's that's what it does for people. That's what people like for it. You saw the versions we had internally. Um AI sorry granola is all about using all this context we have about you to help you do work. I don't know. I think Sam and I were both like okay meetings are going to be a good wedge because you know there's a lot of information in meetings whatnot. Um so I think we get a little bit of credit for it but actually looking back meetings are freaking incredible because the amount of data in transcripts is nuts. And meetings are really just to start like we'll have to add emails, we have to add Slack, we have to add all this context for you to be able to do useful stuff. But I think meetings are a really powerful training ground because for example, if like you're you're a VC like I want every VC in the world writing the first draft of their investment memo in Granola, right? Because we have all the we should be the best tool for that. Full stop. Every follow-up email, every strategy document. If you're going to reorg your company, like you should do that in Granola because we know the most about what's going on in your company. Jim, who maybe is here, he built this demo the other day, and it blew my mind. Again, like I've been working on granola for two years. There's so much data in these meetings where he built like a self-writing wiki for granola. Like it it writes itself and it's always up to date, which is nuts, right? And it was, have you guys seen like web uh websim web? It's like basically what it'll do is like it'll generate an HTML page. You give it a URL and it'll have an LLM hallucinate an HTML page. So this wiki work the same way. So I could be like what's our work from home policy and it wrote it based on all the meetings that we have internally right which so it's like it's just this crazy new world that it's hard to imagine all the value that's going to come out of it until you you start playing but you should come by we'll show you some demos. Hi, I'm Sundep. Uh I'm with Automation Anywhere. I used to work in financial services and one of the things you observe about meetings with potential customers is hey I don't want to share this information and that to be recorded. So just out of curiosity in engaging with users what have you found about human preferences about having information stored transcribed that lets you put the tools for thought in action? tools like granola are already useful and will be so useful in the future that they will be expected in work situations right I think the private like social fear sphere is is a different question that one's a big question mark to me but in the work sphere I think it's going to be uh normal I do think like for the companies in the space rest of society there's a conversation around what are the specifics and how invasive are those tools right so granola from the get-go never stored the audio. It only stores the transcripts, right? Which limits how useful we can be, but it makes it way less invasive than like the other AI meeting bots out there. And I think the conversation is going to shift from whether or not something is transcribed to who has access to that transcript, right? Is it just me? Because lots of meetings, I don't want anybody else to have access to that transcript. Is it my team? Is it my company? Is it the world? Is it I think that that will really really matter. And I think the the defaults companies build there will have a lot of down like downstream consequences. It's like someone's discovered fire, you know, like no one's putting like no one's going to be like we're not going to use fire. It's like we're not going to heat ourselves or like cook food. It's so damn useful. We're going to use it, but how do we use it in a thoughtful way with good norms that actually, you know, minimize like potential bad situations for the for the most upside? Let's have a big round of applause for Chris and Sam. If you like this episode, please do us a favor and rate and review the show on Spotify and Apple Podcasts. This really does help. And if you want to learn more, follow Lightseed at LightseedVP on YouTube X, LinkedIn, and everywhere else. Generative Now is produced by Lightseed in partnership with Pod People. I am Michael McDano, and we will be back next week with another conversation. See you then.