Granola CEO: How to Build in a Crowded AI Market Without Marketing | Christopher Pedregal

📌 Head to https://granola.ai/marina and enter the code MARINA for 3 months off. Chris Pedregal built a $1.5 billion AI app in 3 years, in a category where Zoom and Google already had similar features before he launched. In this conversation he hands over the exact playbook for breaking out of a crowded market with a tiny team and a small marketing budget — a playbook anyone can use to win in the AI era. We cover: Why Chris kept Granola in closed beta for a full year before launching — and how 150 users taught him more than any public launch wouldThe 2x2 matrix he uses to decide if a startup idea can survive in a market with big competitorsHow Granola grew virally with zero built-in growth loops — no automated emails, no forced sharingThe dot plot: the early-stage retention tool that replaced usage graphs for Chris's teamWhy he doesn't use AI for product decisions — and what he uses it for insteadHow to turn 2,500 meeting recordings into a virtual chief of staffThe one thing small teams can do that Google and Zoom structurally can'tLinks: Subscribe to my newsletter: ⁠⁠⁠https://siliconvalleygirl.beehiiv.com/subscribe?utm_source=spotify&utm_medium=video&utm_campaign=futureproof-sub&utm_content=ChrisPedregal ⁠⁠⁠⁠https://siliconvalleygirl.beehiiv.com/subscribe?utm_source=spotify&utm_medium=video&utm_campaign=futureproof-sub&utm_content=⁠ChrisPedregal⁠ Instagram: ⁠⁠⁠⁠⁠https://www.instagram.com/siliconvalleygirl/ ⁠⁠⁠⁠⁠ https://www.instagram.com/siliconvalleygirl/ X: ⁠https://x.com/siliconvalleymm⁠ https://x.com/siliconvalleymm LinkedIn: ⁠https://www.linkedin.com/in/marinamogilko⁠ https://www.linkedin.com/in/marinamogilko My Companies & Products: ⁠⁠⁠⁠⁠https://Marinamogilko.co⁠⁠ https://Marinamogilko.co

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

• 0:01Speaker 00

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• 0:55Speaker 02

  If you believe AI is going to have a big impact, then you should try to stay close to it. Think about the core things that you are good at and figure out how you could augment those with AI.

• 1:04Marina Mogilko?

  This is Chris Pedrigal, CEO and co-founder of Granola. The AI notepad valued at $1.5 billion. He built it in three years and turned it into a standout product in a crowded AI market. When it comes to competing with big corporations, there's still opportunity to build something major in 2026.

• 1:24Speaker 02

  There are a lot of products out there. A lot of people trying to do things. It's like, can you care more than everyone else? There's so much advertising that's happening that I think that if you don't have a product that itself can like pop out and get noticed and loved, it just feels like a losing proposition.

• 1:38Marina Mogilko?

  If you had to start from scratch today, what would be your playbook?

• 1:41Speaker 02

  I would definitely build.

• 1:44Marina Mogilko?

  Welcome to Silicon Valley, girl. I am so excited to be chatting with you because we've been using Granola for, I think, over six months now. I know you launched earlier, but when we discovered it and started using it, it's an amazing product for our team. And what I'm going to do, I'm going to launch a task right now. So it starts recording so that at the end of the conversation, we'll be able to see.

• 2:08Speaker 02

  To see now.

• 2:09Marina Mogilko?

  To see. How it actually works.

• 2:10Speaker 02

  Yeah, perfect.

• 2:11Marina Mogilko?

  Back in two thousand twenty four, you said it's so much easier now to build very specialized workflows for a small group of people versus earlier because now you can use AI. Your bet was that with current AI tools, we can build something for a small group of people because we don't have to use so many resources, right? Because we can vibe code all this stuff, we can ship faster. Versus like ten years ago, if you wanted to build something, you would need a huge team. So serving small group of people wouldn't really make sense. Do you think it's still the case in two thousand twenty six? Or we moved to a world where anyone can vibe code anything? So that you don't really need to build a very specialized tool? What is your sense of the market right now?

• 2:52Speaker 02

  The one thing I know is that everything's changing and it's it's hard to predict the future. Just because people can vibe code things doesn't mean that we're only going to use vibe coded software all the time. I think vibe coding, building tools from scratch is incredibly powerful. If you're building like an internal tool that your team is going to use. I still think that there are certain areas where you want to have the best possible tool. And that takes tons of time and effort and care and continued investment. So I do think there will be lots of software out there that exists. But it's hard to predict exactly where the line of what will be vibe coded versus what will we pay for?

• 3:28Marina Mogilko?

  Do you feel like it's much harder to build now? Because you have experience building in pre-AI era, comparing that to building granola.

• 3:35Speaker 02

  Harder now?

• 3:36Marina Mogilko?

  Yeah, just because I feel like the market is so crowded. Like you see, because anyone can become an entrepreneur. If ten years ago, in order to build something, if you were not a coder yourself, you needed to find an engineer. If you were an engineer, you needed to find a product person. So you needed those resources. It feels like now there are so many solo founders and the market is really crowded.

• 3:59Speaker 02

  It's two sides of the same coin, right? I think it's so much easier to build now. You don't need as many people, as many resources, which means more people are trying it. It's kind of like when digital photography became common. It used to be really hard to get a camera, right? And then only a few people had cameras, there were photographers. And then digital photography made it easy for everyone to take photos, right? It doesn't mean that professional photographers aren't still needed and way better than your average person. So I think it's the same thing with starting products today. There are a lot of products out there, a lot of people trying to do things. A lot of them aren't that good, right? And I think that's what it's all about. It's like, can you, can you care more than everyone else? And can you create something better?

• 4:44Speaker 02

  Like, what I have seen in terms of the one thing that seems to help an AI company break out from a crowded marketplace is just that the product actually works and is the experience of using it is better than than the alternatives. We see people are more willing to switch for slight improvements in product now. So it's like, people are very, very attuned to the quality of the products that they're using. And in that sense, I think it's no different than before. It's like you still, like, it's just you have to fight for that. And you have to, you have to be really, really focused on it.

• 5:15Marina Mogilko?

  I really like how you said you have to care more. I feel like that applies to any niche where you're competing, anything that you're doing. If you care more than others, then this is kind of, this helps you stand apart. Talk to me about launching a product in the AI era. Cause you didn't do like a public launch. You started with a few users, saw their reaction. If you had to start from scratch today, what would be your playbook?

• 5:39Speaker 02

  Yeah, I think the, the conventional startup wisdom before was launch as soon as possible, get feedback from real users and then iterate your way to something great. And I think because of precisely what you said before, there's so many people putting out slop, like putting out crappy products, that it is actually a differentiating factor, a differentiating approach. If when you launch, when you come out into the world, your product is better. And so we, we didn't have this whole strategy about building an AI. We were just like, our philosophy when we were building Granola was basically, we'll do whatever it takes to learn as quickly as possible, what we need to do to make our product better.

• 6:19Speaker 02

  And for the first year, the way we learned the most was literally by sitting next to someone, watching them try to, you know, install it and use it, figure out everything that was wrong, go home, try to fix that, do it again the next day with a new person and do that over and over and over. And we didn't need to launch publicly to learn what was wrong with the product, because every day we would see exactly what was wrong with the product by just watching one or two people use it. After about a year, it got to the point where it was like, it was actually pretty good for those folks. And we said, okay, it's, it's now time to, to launch publicly, because then we'll learn at scale what's wrong with it, how we can make it better. So that was the approach we took. I think that really, really made the difference. But like in a world where anybody can make

• 7:02Speaker 02

  software, the only thing that really matters is like how good of the is the software that you're trying to use. So I would, if you said if I was starting it from scratch, I would definitely build in private or close beta until I felt really, really secure that the product was meaningfully better than than the competition.

• 7:19Marina Mogilko?

  Yeah. And when it comes to picking out idea, was that your initial idea? Smart notes? Or did you have to iterate through ideas as well?

• 7:26Speaker 02

  Yeah, ideas are tricky, right? Because it's like, on one hand, you want to be thoughtful from a strategic standpoint. Like, if I build in this space, is it a dead end? Or is there a big opportunity there? Right? And that's kind of high level thinking. And then, on the other hand, really, a lot of building is it's better not to think. And it's better to just put something in front of people and learn how they react to it and kind of follow that, you know? And and I think when you're, if you're trying to think about a startup idea, you want to do both of those things. You want to make sure you're building in a space where there's there, you know, there's legs.

• 7:59Marina Mogilko?

  Future.

• 7:59Speaker 02

  Yeah, there's a future. Exactly. But then it's sometimes better not to think too deep. Like, once you make that bet, it's almost better not to think at a high level and an abstract level, and really just to like, follow the scent in terms of what people like. And in 2022, I came across LLMs for the first time. This was about eight, nine months before ChatGPT launched. And I was immediately, I was like convinced, I was like, okay, this, I don't know what this new technology is, but it's gonna, it's gonna change everything. It's gonna change all the the tools we we use for work, for productivity. I felt that very strongly. And I knew, I knew that was a space I wanted to build in and be excited about. But then, when we had to figure out where to start, that's where

• 8:41Speaker 02

  we put some prototypes in front of users, in front of people. And they didn't care about most of them. But this idea of like, a real time notepad that would take notes for me and that I can interact with, people's eyes really lit up when we put that in front of them.

• 8:55Marina Mogilko?

  Was it like a just word by word description of what you want to build? Or did you vibe codes?

• 8:59Speaker 02

  Well, vibe coding wasn't quite a thing, but it was more the vibe code. It was, I'm a big believer in prototypes. So like, like, cheap, basic. Prototypes that let people actually mess around with a thing. I feel like you're going to learn a lot from that. So Mike Ovan and I built a few different prototypes. And the the notes one was just, it was just some JavaScript on an HTML page that that we threw together manually. But it was enough to give you a flavor of what it would be like if it if it worked properly.

• 9:26Marina Mogilko?

  How did you select those first people who were evaluating your idea?

• 9:29Speaker 02

  Friends, friends of friends. It was just people we had access to.

• 9:32Marina Mogilko?

  Was there any qualification criteria? Because now that I'm thinking about it, if I'm trying to build something, I also wanted to put in front of the right people, like people who are maybe paying for a lot of tools, people who are working in a big corporation. So they have access to, you know, some budget because just randomly asking.

• 9:47Speaker 02

  Yeah, no, that's a good point. Maybe we're a little bit more thoughtful about it than that. Like, we built Granola for ourselves. And by ourselves, we mean people who are like knowledge workers, tech savvy, are using different types of tools, like live in tools like Slack and Linear and Superhuman and Gmail. So the folks that we would talk to were oftentimes folks working at startups of different sizes, just because that was kind of the the environment that we were in.

• 10:13Marina Mogilko?

  What was your criteria of deciding whether to drop idea or continue working on it? It was just like, somebody said yes, or were you tracking something? I know I was talking to Josh Woodward from Gemini, and he said the way they test products at Google, they watch how eyes light up.

• 10:27Speaker 02

  Yeah.

• 10:27Marina Mogilko?

  When the users start testing it. So they don't really have a metric. They're like, they're relying on this intuition that you're seeing this. Kind of surprising for a company like Google, right? Where you expect like a metric after metric.

• 10:38Speaker 02

  Yeah, it was very, very intuition and qualitative. And in the early days, it was the opposite. It was watching a lot of people being frustrated and unable to actually like use the thing the way they we wanted them to.

• 10:51Marina Mogilko?

  When it comes to competing with big corporations, right? Because we have Zoom, who has AI, like every.

• 11:01Marina Mogilko?

  Product now has AI notes. Can you walk me through your mindset, entrepreneurial mindset? Cause when I'm building something and I see a large company releasing something similar, like my first thought is, oh, I'm done. But then I'm like, okay, we're gonna make it through.

• 11:16Speaker 02

  Things are moving so quickly and companies are launching things all the time. And I think now we've all gotten a bit more used to it. But maybe a year, year and a half ago, it would just felt like, oh, the world's like just, like the sky is falling and the world's changing every five minutes. Uh, when we launched Granola, AI note takers, uh, had already been around, like, the earliest ones had been around for like seven or eight years. So there were tons of AI note takers, the Zooms and the Googles of the world. They already had AI note takers, not as advanced as the ones they have now, but they, they already existed. And when we would go and we'd interview people and try and understand, like, were they using them, uh, were they being useful or whatnot?

• 11:58Speaker 02

  It became really clear that, uh, they were only like marginally useful. Um, and they weren't actually kind of doing the job that people wanted from a tool like that. I guess what I'm saying is like, we kind of did it to ourselves because we entered this like crazy saturated, uh, space. And I think we were able to break out because even though Zoom or Google create notes and Granola creates notes, the, the, the way we've designed Granola, the, the way we think about it is just very, very different from those tools. And Granola is very much a, it is your personal tool. It's like your personal notepad that you are in control of. And you, you can put notes in there. I can go into Granola and I can basically chat with all my meetings from the past two years.

• 12:43Speaker 02

  Um, and as the AI models get smarter, the level of like insights or the level of, uh, conversations I can have across that corpus gets, uh, smarter and smarter.

• 12:52Marina Mogilko?

  Yeah, I would love to talk to you about that later in this interview. Cause, uh, this is like, if a company is not recording their meetings, I think they're losing. Of fifty percent of what they can build later with all of these insights that they're getting, because this is their employees' taste. This is the way they make decisions. This is the way they move. And the only way to teach AI how to mimic or enhance that is to record all the Yeah, exactly. Yeah, it's the context, exactly, all the data. I want to thank the sponsor of this video, Granola. Granola is one of the apps I use every single day. There is a rule that I made for myself. If a task repeats, and it's not the work that actually makes me money, I automate it. Cleaning up meeting notes was one of the first tasks I actually automated with AI.

• 13:37Marina Mogilko?

  Every call I take, strategy partnerships, team syncs, intro chats, gets recorded and sorted. And because I've been doing this for a long time now, at the start of every new call with the same person, I have a clean list ready. What we agreed on last time, what I still owe them, what they still owe me. It's not a bot that joins your call. Nothing is really visible to the other side. You stay fully in the conversation, and after the meeting, Granola transcribes everything and turns it into a clean summary you can work with. And of course, at the beginning of the call, you disclose that you will be recording this with Granola. So here's my real example. Last week, I was in a partnership call. We were going through financials, timelines, deliverables. There were a lot of moving pieces, and my manager was not part of that call, but I really wanted to send her a follow-up email.

• 14:21Marina Mogilko?

  I felt really engaged in the conversation. I could focus on the person I was talking to without having to take notes of every detail, because I knew every number and every date would get captured. After the call, I opened the transcript, and I just asked Granola to create that follow-up email, pull a list of deadlines. Drafting the email part took me about twenty-five seconds, and I copied and pasted. That's it. As if my manager was on the same call with us. My team and I have been using this for a few months. We miss fewer things, which really matters, because with AI, the number of tasks we're tracking has actually gone up a lot. If you want to try it, use the code MARINA and get three months free. The link is in the description. And now, let's get back to a conversation with Christopher.

• 15:04Marina Mogilko?

  For an entrepreneur who's starting today and thinking, okay, I really want to build this tool, but I'm afraid that a big company is going to release a similar I don't know if you watched Google I O, but they released a very similar tool to Whisperflow.

• 15:15Speaker 02

  Oh, did they?

• 15:16Marina Mogilko?

  It looks the same, the small bar appears, has the, but the, the difference is, while you're talking to it, it also references all the files you have in Google Drive and Gmail. So you can say like, oh, by the way, insert a table using this data and it's going to do it. So it's not only transcribing, it's also adding context. And I'm like, I can see how I'm still using Whisperflow because I'm, I want just the transcription, but also see how I'll be using more of that as well. Like, can you give advice to an entrepreneur who's building something, but again, constantly in this era when everyone's competing with everyone?

• 15:51Speaker 02

  It's a great question, right? And it's one of those things where it's, I think if anyone had a crystal ball and could say like, okay, there's, there's an extreme world where we are only using like, there's only one tool in the future, right? And we use it for everything. And there's a, a different version of the future where we use even more tools than we have today. And I think we'll end up somewhere in the middle, but it, you know, it's hard to know exactly where we'll be. The way I would think about it is, so it's basically, it's a two by two matrix. It's basically how frequent is the use case that you're going after? And how important is it for the user? It's like, if it's an infrequent use case, then I think it'll be really tough to compete with the, the larger companies or the larger tools that are more established.

• 16:31Speaker 02

  I think the, if it's an infrequent use case, people will go to the chat GPTs or the logs most likely, right? In the same way that you didn't see a lot of verticalized search engines in like the two thousands, because people are just going to Google and it's easier, they have a habit and that's where they would go. So I think you have to choose a, a use case that's very common. Because if it's common, you have, you have an opportunity to build a habit around it. And there, the question is like, is it a common use case that the user doesn't really matter if you do a much better job at? Or is it a, is it a use case that's really, really important to people, right? And it's, and I think you want to be in that corner where it's basically, it's very important to people where

• 17:12Speaker 02

  if the product experience is even just like 10% better, like that's, that's reason enough for people to switch to you and use it. And if you're in that quadrant, then I think it goes back to the. If you care more, and that's the one thing you can do over the big companies is like you can just care more because they have to care about a lot of things, right? Then you can build that better product and I think you can, you can compete.

• 17:32Marina Mogilko?

  Do you think we should add a niche to whatever you just said?

• 17:35Speaker 02

  Yeah.

• 17:36Marina Mogilko?

  Because I feel like if you're just going after a frequent use case for billions of people, then it's a big corporation kind of playfield.

• 17:42Speaker 02

  Yeah.

• 17:42Marina Mogilko?

  But if it's a niche, like for your product, it's like people who are fixing their productivity and want to record, want to be more effective with their notes.

• 17:51Speaker 02

  Yeah, or you become a really big company one day.

• 17:53Marina Mogilko?

  Or that.

• 17:54Speaker 02

  We definitely want to have billions of people using granola.

• 17:57Marina Mogilko?

  And and you're moving into B two B. You started as B two C company and now you moved into B two B. How is how is that shift?

• 18:03Speaker 02

  Well, yeah, it's a good point. Our strategy was to mimic like a Slack or Dropbox, like those types of bottom bottoms up companies. So it's basically a product led growth. So the idea that someone inside of a company discovers granola, they fall in love with it. They tell their their colleagues, we kind of grow organically inside of the company. And then at some point, someone in a position of authority, maybe it's like the founder, maybe it's the the chief compliance officer, what have you, legal officer, security officer says, whoa, everyone's using the software. We should, we should probably like pay for it, have control over it, make sure we know where our data is going and all that stuff. And that was always the plan. We always knew that we would be selling to companies.

• 18:45Speaker 02

  But at the beginning, we were just worried, not worried, we just focused on just trying to build something people actually wanted and liked. And that that worked. So granola did spread like virally, organically throughout companies. And now we have some very, very large companies who are on enterprise plans with granola. But it all started either bottoms up where it kind of it spread through the company virally, or the founder or CEO was using, like heard about it, was using it themselves and found it valuable and said, actually, everybody should should be using it.

• 19:16Marina Mogilko?

  I think it's a great B two B marketing plan when you start with a consumer. How did you get to those initial customers?

• 19:22Speaker 02

  We posted on Twitter, like that was basically.

• 19:25Marina Mogilko?

  By yourself, like the founding team or?

• 19:27Speaker 02

  Yeah, yeah, I think we posted it for my account and I didn't really have a.

• 19:31Speaker 02

  Twitter following at all. And I think we just, we got really lucky. It was this idea, the way granola works is like, it, it looks like Apple Notes, it's a notepad. And then at the end of the meeting, it'll take whatever notes you wrote and it'll flush it out. And there's this really nice animation where you see your, your notes get like filled in. And we had a GIF of that. And at the time, I think a lot of the, like the startup founders or leaders out there were really interested in new UIs or interactions around AI. And so we had a few famous, like Guillermo from Vercel retweeted my tweet and then, and then Nat Friedman also retweeted. So it's basically there somehow. And I don't, there's like the universe, you know, this happened, like, it just caught a few people's eyes and, and they tweeted about us.

• 20:17Speaker 02

  And then we just started growing, like the first day, I think we got 500 installs, you know? So it's like,

• 20:23Marina Mogilko?

  That's pretty decent.

• 20:25Speaker 02

  It's not bad. I mean, it was, it's more than I expected, but it's also a drop in the bucket, right? And, and then it just started growing like little by little by little. Cause we, we weren't doing any marketing. We, the crazy thing about granola is all, all the like old school AI note takers, they're all super optimized for like growth hacking. They'll like, the end of the meeting, they'll send notes to everybody who was in the meeting, whether they want it or not, whether you want it or not. And granola doesn't do anything like that. It's like granola is like, our only job is to serve the user and, and give the user wings. The fact that granola was entering a space that was super crowded and had zero growth loops built into it. And it still grew virally, organically and kind of was able to, to pop out and become really visible in that space.

• 21:11Speaker 02

  I think is a really, there's something going on there. I think it's a really strong testament that people are hungry for just better software and better software.

• 21:20Marina Mogilko?

  Good product.

• 21:20Speaker 02

  Yeah, yeah.

• 21:21Marina Mogilko?

  Interesting. So basically all your marketing is based on.

• 21:25Speaker 02

  People loving it.

• 21:26Marina Mogilko?

  Great product.

• 21:26Speaker 02

  Yeah.

• 21:26Marina Mogilko?

  Exactly.

• 21:27Speaker 02

  The whole company is based on that.

• 21:29Marina Mogilko?

  Yeah. That's amazing. So would it be your advice for any entrepreneur building something? Don't think about marketing yet. Just think about the product and people sharing it.

• 21:37Speaker 02

  I think so, because I think, to your point earlier, it's so noisy out there right now. There's so many people doing so many things and there's so much investment, right? So there's so much advertising that's happening that I think that if you don't have a product that itself can like pop out and get noticed and loved, it just feels like a losing proposition. By default, I always think about very user facing products. I think it's very different if you're going after customer support there. It's, I think, all about having the right sales motion and, and marketing is a part of that. But, um, but generally, I think if you don't have a good product, you're like, it's the one thing that you can go and make better with a small team, right? And I think you should do that upfront rather than do, do that later.

• 22:19Marina Mogilko?

  I have one final follow up question here. How many initial users did you have? So how much feedback were you collecting before pushing it out?

• 22:26Speaker 02

  Yeah, we had about a hundred and fifty active users after, after that.

• 22:30Marina Mogilko?

  That's your friends and that's like your inner circle.

• 22:33Speaker 02

  Yeah, yeah, yeah. Friends and friends of friends and.

• 22:35Marina Mogilko?

  Well, were you tracking when you gave it out? Like, because you couldn't see their eyes, right? But who were you tracking with the frequency of use?

• 22:42Speaker 02

  Yeah. So what we would do is we would, um, we would set up a first call. We, we, we do it in person if we could. Otherwise, we do a video call where we would ask them to share their screen and then we would watch them try to install granola and try to use it without us saying anything. And then we would schedule a call in three days. Again, share their screen and walk through the, the meetings they use granola for and talk about what was good or not. And that, that was the highest signal. That's like the super qualitative, um, uh, that's where you learn the most. But then, once the product started getting good enough that people would actually use it, then we track usage. And, um, there's this, uh, there's this thing, I'd never heard about it before, uh, before granola, but one of our mentors told us about it and it's a thing called a dot plot.

• 23:24Speaker 02

  And a dot plot, basically, it's, um, think of it like a, like a, like a spreadsheet and every row is a user and every column is a day, right? So. The default dot plot we had would show the last thirty days. And then in each cell, you basically put, for our case, like, how many meetings did they use granola for on that day? And and then you change the color of the cell. So if they use it for like ten meetings, you should make it like dark green. If they use it for zero, you should make it white. And then you can, at a glance, very easily see like the patterns. And and the idea is that you start with a dot plot when the product's not very good. And then you iterate and you iterate and you're it. And what you should see happen, you should see it light up.

• 24:05Speaker 02

  Because normally, when you do analytics, you get, you you group all the usage together and you just get like a usage graph, right? Which, you know, like cumulatively, are people doing more meetings or not? But that's not actually very helpful in teaching you what's wrong with your product and is it working? And then a dot plot, you can see things where it's like, oh, okay, like, this person was using it a lot. And then they stopped using it. And then they like clearly remembered it existed and started using it again. Or like, maybe they went on vacation, or you could be like, oh, actually, there's a few people who started a little bit. And then they had like one day where they they did like five meetings. And from then on, it became a habit, it became hooked. And you can be like, oh, how do we get people to get to have that kind of day?

• 24:44Speaker 02

  So it becomes like a very easy visual way to to get a to stay on on top of the pulse of what's happening with your users.

• 24:52Marina Mogilko?

  Amazing. All right. Talk to me about your AI stack. What are you using apart from granola?

• 24:58Speaker 02

  So I struggle with this question because I try to use granola for as many things as possible. And I use, we haven't launched it yet, but I just got this Apple Watch. And that is a, that's a really nice feeling because it's just here all the time.

• 25:11Marina Mogilko?

  This is how I take my notes when I go to conferences.

• 25:15Speaker 02

  What do you, what do you?

• 25:16Marina Mogilko?

  Just voice notes. And they go to my phone and then I use whatever we're using to transcribe. So it's it's a journey.

• 25:23Speaker 02

  It's a few steps. Yeah, but in terms of form factor, I think the the Apple Watches, it just feels, it feels very.

• 25:29Marina Mogilko?

  Oh, one hundred percent.

• 25:30Speaker 02

  Yeah.

• 25:30Marina Mogilko?

  It it should be the form factor for all the conferences and everything.

• 25:33Speaker 02

  Yeah, yeah, yeah. And then, next, I mean, I use Claude, right? Claude's probably my second one. And then one of the engineers at granola set up this internal. Agent, we call it Nacho. I actually don't know why we call it Nacho. It has like a little Nacho as the icon. And we've connected basically all of our internal tools to this one agent. So literally every single data source that we have is accessible to this agent. And there's like an internal portal, but we also interact with it in Slack. And that one's really interesting. So for example, I will, oftentimes it will happen is like, I will notice something kind of weird in the product because you know, that's my job. And I'll post about it in Slack and then someone will ask Nacho to like,

• 26:17Speaker 02

  be like, hey, can you look at the analytics for the last couple of months? And see if that supports like Chris's, you know, annoyance or whatnot. And then that'll come back and then someone will be like, okay. Here, what if we change the way this worked and put, uh, put a button here instead? And then you ask Nacho and Nacho goes and talks to cursor and like prepares like a change. So it still kind of goes off the rails all the time. So we have to be like, no Nacho, like, like that's not what I wanted. Or you think harder, you know, you made some assumptions here that aren't right. So there's still a ton of human back and forth. But it's, it definitely changed the way we've worked internally.

• 26:54Speaker 00

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• 27:20Speaker 01

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• 27:49Marina Mogilko?

  So it's basically, I'm trying to describe this role. Well, what is, he's not like a C, like a chief of staff. He's more like, goes to analytic, does, does he help him with strategic decisions? Or it's mostly like, pull me data?

• 28:04Speaker 02

  It's, it's a lot of like, pull me data. Do this thing that would have been like thirty clicks before, you know? Or like opening up three tools and saving data into a file and uploading it somewhere else. Just do all of that for me. So it's, it's in some ways, it's like, maybe an intern would be the right, you know? It's like, we're not, we're not outsourcing big decisions. We're gonna be like, hey, go pull up the data, go pull up this thing. Look at how those two connect. Okay, here's what we want to do. So it's very much the ideas are coming from us, not, not from Nacho, but Nacho's executing on it.

• 28:35Marina Mogilko?

  Did you use a tool for that? Or was it like built from scratch? I wonder like, cause if you, you can totally build this with perplexity computer or like.

• 28:43Speaker 02

  Yeah, we didn't, so I, I actually have to ask, we didn't use anything like that. It's something like Claudebot, but it's not Claudebot. I can't remember what it's called. Um, and we run it, we run it ourselves. So that's why we're comfortable with all that data, you know, going through this agent, because we, we run it and control it.

• 28:58Marina Mogilko?

  Okay, what, what haven't you delegated to AI yet? Or what are you doing without AI?

• 29:03Speaker 02

  I think a lot of building great product, it's all about how does this make me feel? Right? And a lot of it is human intuition based. It's trying to put myself in the shoes of another person and, and imagining how they, how they'd experienced that. I just don't use AI for that.

• 29:21Marina Mogilko?

  And you can't. What you're describing is something so uniquely human.

• 29:25Speaker 02

  We have some really young people on the team and they, they just naturally default to using AI for everything. It's, it's just like the, like default behavior. And more often than not, I look at them, I'm like, oh, that's clever. I wouldn't have done that, but that's actually really smart and I should do it. I think the, the product stuff is probably, it's probably one of the last things, at least in, in our immediate work, that I think will get, um, I don't actually know if AI will ever kind of fully, fully get in there. Cause I think, uh, I don't know, the lived human experience is actually the one thing that we have.

• 29:59Marina Mogilko?

  Totally.

• 30:01Speaker 02

  What it can help do though is so we'll get lots of feedback from users, right? And then grouping, classifying that, basically making that feedback, putting it into a form that's really easy for us to like build intuitions on top of and making decisions, super useful for that. But then actually, what do you do with those intuitions? What changes do you want to make? That that's still very, very.

• 30:21Marina Mogilko?

  And it's a very founder driven thing because you're like the soul of the product has your vibes. So it has to have your feelings. I don't know if you can even. Uh, put it into a product, but I love that. Do you have any, I don't know, I call them magic prompts that totally change how you interact with AI? For example, I just asked my granola, can you identify bottlenecks in my company? And it went and analyzed my conversations like number one, and you know it, you're the bottleneck. That was my number one. And then it came up with a few more things that we're currently fixing. Do you have any other prompts that anyone can use with their AI that's going to change their work?

• 31:00Speaker 02

  It all comes down to the AI needs to have enough context. So if you use granola in all your meetings, then it does. And then you can ask it some pretty incredible things. So let's, let's just assume that the person's doing that. The, the things that really opened up my eyes and I was surprised at how good they were, were um, coaching level things like that really, there's a, there's one recipe in granola, which is called Coach Me Mat. What's kind of great about coaching is that harsh, if you ask an AI for feedback, an AI can give you harsh feedback. And there's no person like, it's not worried about hurting your feelings, right? So that, and it's, and AI can say something to me and I think I can hear it better than if like, let's say my wife said something to me. I might be a little bit more defensive, if that makes sense.

• 31:45Speaker 02

  So uh, anything around like deep coaching, hey, what are these like patterns you observe? And how I do things that maybe I'm not aware of that are not helping or that I could, that I can improve. That's a really big one. Oftentimes I'll go into. Other tools, if I use ChatGPT or Claude, they feel quite dumb to me compared to granola because they don't have all that context baked in.

• 32:08Marina Mogilko?

  But you can connect now. I mean.

• 32:09Speaker 02

  No, no, I can. But what I mean by that is, so I have two thousand meetings in granola, two thousand five hundred meetings, right?

• 32:16Marina Mogilko?

  Wow.

• 32:17Speaker 02

  So when I ask Claude a question, it doesn't read two thousand five hundred meetings, right? It'll it'll read ten and it'll try to form a picture about me from those ten meetings, right? So I have a recipe in granola, which basically says, look at my last month of meetings and write me five pages about who I am, what granola is, what's the granola product?

• 32:37Marina Mogilko?

  Can we try that? Can you give me my granola? Let's do it. I really like this problem. Let me let me see what it tells me.

• 32:44Speaker 02

  Perfect. So if I go here and then we just say, I'm going to use ChatGPT to do some work and I want ChatGPT to understand who I am, what I'm working on and what I'm trying to achieve. So it'll have better context about me. So please look at all my meetings from the last month and write three pages that I can paste into ChatGPT. So I'll have all the context on what I'm trying to achieve.

• 33:12Marina Mogilko?

  Wow. Oh, nice. It even extracted some stats, pushing cadence.

• 33:21Marina Mogilko?

  Yeah, nice.

• 33:23Speaker 02

  So what I find is now if you take this and you can go to any AI out there, you can go to ChatGPT, you can go to Claude, you can go to any, anything. And if you if you just say, here's some context about me and you paste this in, and then you ask whatever you're gonna ask, the AI will do such a better job answering your questions because it understands so much more about you. Exactly.

• 33:44Marina Mogilko?

  So because it's connected to my Claude.

• 33:46Speaker 02

  Yeah.

• 33:46Marina Mogilko?

  How can I ask Claude to self-update using this? To like add context to all my projects?

• 33:53Speaker 02

  Yeah, well, I mean, there's probably some way where you could set a trigger where it does it every day or something like that, or you could just wait for us to launch that soon. Because that would be kind of cool, right? If this thing, basically, we're building a version of this, we're all auto-update every day. And then you could just use that context.

• 34:09Marina Mogilko?

  Yeah, yeah, that's, this is fascinating. So I feel like you are building something like a virtual chief of staff based on

• 34:17Speaker 02

  Moving towards it.

• 34:17Marina Mogilko?

  Based on this data that you have. I also write a newsletter where I go deeper on AI tools that I use, career strategies, and things I can't fit into a thirty minute podcast. It's free. Link is in the description. We've been talking for almost an hour, right? And I'm remembering some things, but there is some details that I might be missing that are important to me. How does Granola work in terms of picking out those details? Uh, how does it decide what to surface?

• 34:45Speaker 02

  In the, in the notes, you mean?

• 34:46Marina Mogilko?

  Yeah, yeah.

• 34:47Speaker 02

  Yeah, so.

• 34:49Marina Mogilko?

  Oh, and I say it gave me product strategy and crowded markets. I really like it. Building in the AI era market dynamic, dynamics, product strategy.

• 34:56Speaker 02

  What we realized early on is that what are good notes for you would be very different than what are good notes for me. Right? So like the point of notes is really dependent on who the person is and what they're trying to achieve.

• 35:08Marina Mogilko?

  Yeah.

• 35:09Speaker 02

  I think we might have been the first to do this. It's basically notes are generated for each person and they're different for each person. And what we do is we take as much about the person into account as possible. So I don't know if this was a calendar event, but let's say you, you join a Zoom meeting and use Granola. Granola will go and try to do research and figure out who everyone in that meeting is and what their roles are. And then we'll use that to figure out what is, what the meeting's about and like what should be highlighted in those notes.

• 35:37Marina Mogilko?

  If I tell Granola, my goal for the next few calls is to, I don't know, make sure we follow up with everyone if we had agreed on a to do list.

• 35:47Speaker 02

  Yeah.

• 35:47Marina Mogilko?

  Would it be highlighting that for me in every meeting? Does it have like a universal memory of how I want my notes to be presented?

• 35:54Speaker 02

  Not an automatic one yet. Yeah. So that's something you can go and set up a template and Granola, you can basically say. You can have different templates and so you can kind of say, I want notes in this structure during a call or during a meeting and be like, hey, good luck. Make sure to say, include this in the notes and it'll do that. But it won't, it doesn't have like a memory about you said this in the last call, so I'm gonna do it in the next call, which is um, you have to be careful with memory, I think. Like, memory is super powerful, but with explicit instructions like that, the reality is like, um, we underestimate how much things change, right? What you don't want is you don't want an instruction that like

• 36:28Marina Mogilko?

  From last month.

• 36:28Speaker 02

  You said something last month and like, Granola still thinks it's really important.

• 36:31Marina Mogilko?

  Oh, yeah. Like my chat GPT still thinks I want to be an actress.

• 36:34Speaker 02

  Yeah.

• 36:35Marina Mogilko?

  Which is like, three years ago.

• 36:36Speaker 02

  There's a guy on my team, which is like, I mentioned, uh, muffins, you know, like he, like, he had one question about muffins that ChatGPT wants. And like now, like ChatGPT just keeps bringing up muffins all the time. It's like, as a muffin connoisseur, you know, it's like, no, I just, I just asked about muffins. And that's why you have to be a little bit careful with, and that's the difference. If you use Granola a lot, the, the thing is, is like, there's just so much richness and context in, in, in our conversations. It's a little bit like, um, I don't know, think about your best friend and think how many hours you've talked to your best friend and like how well they know you. It's like very, very different than like, if you're just chatting with something like ChatGPT or Claude, it's like a very, very superficial.

• 37:16Marina Mogilko?

  Very granular. Yeah, it's, but once we fix that, if we can make this dynamic memory based on, like, asking AI to identify my priorities on a certain day, then this can become my chief of staff.

• 37:30Speaker 02

  Mm hmm. Yeah.

• 37:31Marina Mogilko?

  If it can just pull those things, like, oh, now Marina's focused on that.

• 37:35Speaker 02

  Yeah, yeah.

• 37:36Marina Mogilko?

  I'm gonna help her in this meeting by suggesting these questions. I'm gonna identify this process that's broken in her team clearly, because I've heard in another calls within her company.

• 37:46Speaker 02

  Yeah.

• 37:47Marina Mogilko?

  Because for me, like, recording my calls is the way, is a way to build a virtual chief of staff, which we're trying to achieve.

• 37:54Speaker 02

  Yeah. And, and I think almost, almost what everybody in AI is trying to achieve, really, right? Like, like, that's, that's, that's, I think.

• 38:00Marina Mogilko?

  Some level of autonomy. Because for now, I feel like AI has made us much more productive, but it only means we're, we're working more. Because we see all this productivity game. We see how much better it is and we just work more. What I want the next step to be is like, give us some more free time in summer.

• 38:18Marina Mogilko?

  I can't.

• 38:19Speaker 02

  I, I, yeah, I think we kind of do that to ourselves, though, a little bit.

• 38:23Marina Mogilko?

  Oh, true, but this is our nature.

• 38:24Speaker 02

  Yeah.

• 38:25Marina Mogilko?

  And it's interesting, like, whether we're gonna cross this period in time where AI is helping us with strategic decisions. So we intentionally take more time off.

• 38:35Speaker 02

  Yeah, yeah.

• 38:35Marina Mogilko?

  I don't see this happening now.

• 38:38Speaker 02

  On the, the point you were talking about a second ago, which is, uh, there's this interesting question of how are you going to, um, interact with this chief of staff or this AI? And how directive are you gonna be? Like, basically, you're gonna be like, oh, always do this, or give it instructions and it always follows that? Or I think there's a different model, which is like the AI is almost a little bit in invisible. And it just observes what you do and then tries to infer from that, like what it should be doing.

• 39:08Marina Mogilko?

  Yeah, exactly. That's what I wanted to do.

• 39:09Speaker 02

  Exactly.

• 39:10Marina Mogilko?

  What will Marina bring up in the next meeting, based on her previous?

• 39:13Speaker 02

  Exactly, yeah. So, cause we, a good example here, months ago, I tried building a version of, uh, Granola generating, um, follow-up emails. So like, you'll connect your Gmail and it will just learn from your previous messages.

• 39:27Marina Mogilko?

  With that person?

• 39:28Speaker 02

  Yeah, no, both, both. Uh, and so, so like, an example there that's really important is, for example, let's say, um, oftentimes people will need to send a link to like, an important doc. Like, for example, before this, you sent me a doc saying, here's some instructions, right? That doc might change, like, next month, you might decide to use a different doc.

• 39:46Marina Mogilko?

  Yeah.

• 39:46Speaker 02

  And if it, if you had to tell Granola that you changed the doc, you might forget. Whereas if it has access to your emails and it notices that, oh, you now use this new doc, I'm gonna start using this new doc, you don't have to think about it at all. So I think this, I think a, a great model for AI is one where the best designed things become invisible, right? And, and I, and I think the, like, the best AI is gonna be stuff that you don't even realize is there.

• 40:11Marina Mogilko?

  Self-learning, self-updating, learning from what's changing. This is exactly what you're describing.

• 40:17Speaker 02

  Try to get everyone at, at Granola to think about product in the, the. Same way. And when someone new joins the company, I basically paint them this picture where I want granola to feel like a handrail. You know, when you have stairs, there's that that railing and and people always look at me like, like, what do you mean by that? It's like such a weird thing. And I'm saying, well, handrails are basically invisible, right? They're on every staircase. You never notice them, right? You don't pay attention to them until you trip, right? And then your hand shoots out and it needs to be like right there. And it needs to like hold your weight. And it's a really, really important thing. And it needs to be like super intuitive. But then you go back to living your life and going up and down the stairs. And and that's, that's how I want granola to feel like I want granola to have your back.

• 41:03Speaker 02

  To to in any moment of need, like if you're tired, if you're tripping or whatever, it's like, we're right there for you. But otherwise, you're the star of the show, you know, you're out there doing things here, you're living your life.

• 41:13Marina Mogilko?

  You know, whenever I post, like, I'm excited. This company just launched this and I've been using this company for so long now I can do this. Oh, why are you happy? I stealing your data. Oh, AI is gonna replace you in three months. All like corporations are just eating, eating us, whatever. What would you say to those people?

• 41:32Speaker 02

  I think the world's gonna change a lot over the next couple of years. And I think whenever there's a period of a lot of change, there's gonna be turbulence. That is just a reality. And I don't think we're, I don't think anyone knows exactly where we're gonna end up. I'm excited about AI as a tool that augments us and enables us to do more and better things than ever before. And I think there's a lot of areas where where that's the case, where actually

• 42:02Speaker 02

  AI is not gonna replace people, it's actually gonna let people do more. And there are all these examples in history where all of a sudden, if something becomes more accessible, the demand for it goes up because now people can use it. That's a Jevon's paradox, I think it's called. It's not gonna be everywhere, though, right? Like, there's definitely gonna be. Uh pockets of society where it's gonna be very disruptive, right? And I think um that's happened lots of times in history as well, but it's like change can changes can be exciting, but it can also be really hard. I think it's important to hold the excitement, but also the the reality of the downsides uh in our minds at the same time.

• 42:40Marina Mogilko?

  Yeah.

• 42:41Speaker 02

  Cause I I think that's what's gonna happen.

• 42:42Marina Mogilko?

  What do you tell yourself when you have fears about AI? If you ever have them?

• 42:46Speaker 02

  Uh I so my my view there is I think about what I can control generally. This is my like philosophy in life. I think about what I can control and things I can't control, and I don't worry about the things I can't control. And I think about the things you can control is if you believe AI is gonna have a big impact, then you should try to stay close to it. And by that, I I think you should you should try to use it. And I think that's really the only thing you can do.

• 43:11Marina Mogilko?

  Totally, one hundred percent.

• 43:13Speaker 02

  And I think that um and I've seen this, I've seen, cause I think what's happening with uh engineering is it's like you can kind of see what happens in engineering and the same thing that's gonna happen with coding and engineering is gonna happen in other sectors later. And I see, again, we have a guy on our team, he's twenty and he's uh the way he uses AI is incredible and he's just able to do all kinds of incredible things that I never would have expected. And so like, I think the only advice I have to people is like, don't shy away from it and and and lean into it. And that doesn't mean you need to, there's a lot of like AI theater, productivity theater. It's like, I think that there's a lot of people, there's almost like more talk about how AI has helped them than it's actually helping them be more productive, right?

• 43:54Speaker 02

  I think we're, I think we're in the productivity, AI productivity theater phase, but I think we're gonna come out on the other end of that where it just really does augment your productivity tremendously, but it doesn't mean you have to spend twenty four seven, you know, like following every single launch, like I that's that's not what I mean. What I mean is um, think about the core things that you are good at, that you need to achieve in your job and figure out how you could augment those uh with with AI. And like we were talking about for product, for me, it's not, oh, how do I get, how do I get chat GPT to make product decisions? But it's maybe, how do I get AI to uh?

• 44:33Speaker 00

  This episode is brought to you by Google Chrome. You think you know a browser, but Gemini and Chrome? That's new. It can help you with practically anything on the web, like restoring a vintage motorcycle from a 50-page restoration block, or finally break down that long article you've had open for weeks. Gemini and Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses set up required. Compatibility and availability varies 18 plus.

• 44:58Speaker 01

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• 45:28Marina Mogilko?

  Get all the data.

• 45:29Speaker 02

  Get all the data so I can be better informed to make better product decisions. So that's how I would think about it. I have a six-year-old and an eight-year-old. And I think about what's the world going to look like when they're older? And I don't know, right? But it's perhaps going to be a little bit easier for them because the world's going to change a lot over the next few years. So, well, I don't, I mean, again, I don't know, but it's, they're going to, they're already growing up in a world where chat GPT is normal. Whereas I think if you are maybe in your mid twenties right now, like early in your career and now there's all this change that's happening. I think that's a, that's perhaps a harder time. But again, maybe it's easier than if you're in your 40s. I don't know, you know, like it's hard to tell.

• 46:10Marina Mogilko?

  Yeah. Okay. And last advice for founders building in the AI era? What should they be avoiding?

• 46:16Speaker 02

  I think this has always been the case, but it's so much more extreme with AI. There's so much noise. There's so much FOMO. There's so much imposter syndrome. Like if you were just, if you just look at Twitter, you'd, you'd assume that everything is just solved.

• 46:31Marina Mogilko?

  Companies that run by agents, everyone's a millionaire.

• 46:34Speaker 02

  And, and I think the reality is very far from that. And I think ultimately the thing you can do, again, what can you control is you can understand a problem and a user better than anybody else in the world if you really wanted to. And you can just care more about building a really great solution for those folks. And You can have a peripheral awareness of of other stuff that's happening. I think it's good to understand directionally where things are going. But do not let it mess with your head because it's so easy to obsess and to look at those things and to assume that they haven't figured out. And they're shiny objects and it's like the what's the the fashion of this week versus that week or what have you.

• 47:18Speaker 02

  But the underlying problem that you're trying to solve, that probably hasn't changed at all in the last like two weeks, right? Or even the last two years, probably. And so like that's that's what you need to work on, right? That's your job. It's exciting, but it's also you have to you have to manage that mentally because otherwise you'll you'll.

• 47:34Marina Mogilko?

  You'll be too distracted and you have to care more about your particular problem.

• 47:38Speaker 02

  Yeah.

• 47:38Marina Mogilko?

  Love it. Thank you so much.

• 47:41Speaker 02

  Thank you so much for having me.

• 47:42Marina Mogilko?

  Thank you.