$1.5B AI Founder: The Mindset Shift That Separates Winners in 2026

0:00 If you believe AI's 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. >> This is Chris Pedregal, CEO and co-founder of Grain Note, the AI notepad valued at $1.5 billion. He built it in 3 years and turned it into a standout product in a crowded AI market. >> When it comes to competing with big corporations, is there still opportunity to build something major in 2026?

0:28 >> 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 a losing proposition. >> If you had to start from scratch today, what would be your playbook? >> I would definitely build >> Welcome to Silicon Valley Girl. I am so excited to be chatting with you because we've been using Grain Note for, I think, over 6 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 notes.

1:13 >> to see how it actually works. >> Yeah, perfect. >> Back in 2024, you said it's so much easier now to build very specialized workflows for a small group of people versus earlier cuz now you can use AI. >> Yeah. >> 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? Cuz we can vibe code all stuff, we can ship faster versus like 10 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 2026 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 me a of the market right now?

1:56 >> 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's 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 it's hard to predict exactly where the line of what will be vibe coded versus what will we pay for.

2:32 >> Do you feel like it's much harder to build now cuz you have experience building in pre-AI era comparing that to building granola? >> Harder now? >> Yeah. Just because I feel like the market is so crowded. Like you see cuz everyone can become an entrepreneur. If 10 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 product person. So you needed those resources. Feels like now there are so many solo founders and the market is really crowded.

3:03 >> Yeah, 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 a when digital photography became common. It used to be really hard to get a camera, right? And then only a few people had cameras, they were photographers and then um 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.

3:37 A lot of them aren't that good, right? And I 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? Like I What I've 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 products 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 it's no different than before. It's like you you still you like it's just you have to fight for that and you have to you have to be really really focused on it.

4:19 >> 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 cuz 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?

4:43 >> 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 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, differentiating approach if when you launch, when you come out into the world, your product is better. >> Yeah. >> Uh and so we 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. And um for the first year, uh 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 uh 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." Um so that was the approach we took and I think that really really made the difference. Well, like in in a world where anybody can make 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 uh build in private or closed beta until I felt really really secure that the product was meaningfully better than than the competition.

6:24 >> Yeah, and when when it comes to picking out idea, was that your initial idea, smart notes, or did you have to iterate through ideas as well? >> Yeah, ideas are are tricky, right? Because it's like on one hand you want to be thoughtful from uh 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. Um and then on the other hand, really a lot of building is it's it's it's better not to think and it's better to just put something in front of people and and and learn how they react to it and and kind of uh follow that, you know? And um and I think when you're if you're trying to think about a startup idea, you you want to do both of those things. You want to make sure you're building in a space where there's uh there you know, there's legs. Yeah, there's a future, exactly. But then it's sometimes better not to think too deep. Like once you make that bet, uh 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 um in 2022, I I came across LLMs for the first time. This was about um 8-9 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 going to it's going to change everything. It's going to change all the the tools we we we use for work, for productivity." I felt that very strongly and I knew um I knew that was in 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 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.

7:59 >> Was it like a just word by word description of what you want to build or did you vibe codes? >> Well, vibe coding wasn't a thing. Yeah, vibe coding wasn't wasn't quite a thing, but it was more the vibe code. It was I'm a big believer in prototypes, so 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, my co-founder 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 a flavor of what it would be like if it if it worked properly.

8:30 >> How did you select those first people who were evaluating your idea? >> Friends, friends of friends. It was just people we had access to. >> Was there any qualification criteria? Cuz now that I'm thinking about it, if I'm trying to build something, I also want it 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 people >> Yeah, no, that's that's a good point.

8:53 Maybe we were 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 often times folks working at startups of different sizes just because that was kind of the the environment that we were in.

9:17 >> What was your criteria of deciding whether to drop idea or continue working on 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 when users start testing it. So, they don't really have a metric, they're like they're relying on this intuition that they're seeing this. >> Kind of surprising for a company like Google, right? Where you expect like a metric after metric.

9:43 >> Yeah, it was very very intuition and and qualitative. And in the early days it was the opposite. It was watching a lot of people being frustrated and and and unable to actually like use the thing the way they we wanted them to. >> When it comes to competing with big corporations, right? Cuz we have Zoom who has AI like every product now has AI notes. Can you walk me through your mindset, entrepreneurial mindset? Cuz when I'm building something and I see a large company releasing something similar, like my first thought is always, "Oh, I'm done." But then I'm like, "Okay, we're going to make it through."

10:20 >> 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 and the world's changing every 5 minutes." When we launched Granola, AI note-takers had already been around like the earliest ones have been around for like 7 or 8 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 to understand like were they using them, were they being useful or whatnot. It became really clear that uh they were only like marginally useful.

11:06 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 cuz we entered this like crazy saturated 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.

11:36 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 2 years. Um and as the AI models get smarter, the level of like insights or the level of conversations I can have across that corpus gets smarter and smarter. >> Yeah, I would love to talk to you about that later in this interview cuz uh is like if a company's not recording their meetings, I think they're losing uh 50% of what they can build later with all of these insights they're getting cuz 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 it. Yeah, it's it's just yeah, it's the context. Exactly. All the data.

12:24 >> 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. 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.

13:00 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. 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 Gornola to create that follow-up email, pull out a list of deadlines. Drafting the email part took me about 25 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.

13:54 >> 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 3 months free. The link is in the description and now let's get back to our conversation with Christopher. >> 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's going to release a similar I don't know if you watched Google I/O, but they released a very similar tool to WhisperFlow.

14:19 >> Oh, really? >> It looks the same, the small bar appears, has the but the the difference is >> Yeah. >> 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 cuz 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 >> Yeah, yeah.

14:55 >> 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? We use it for everything and there's 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 that 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. I think the if it's an infrequent use case, people will go to the chat GPTs or the clouds most likely, right? In the same way that you didn't see a lot of verticalized search engines in like the 2000s because people were 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 uh a use case that's very common. Um because if it's common, you have a 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 if And I think you want to be in that corner where it's basically it's very important to people where 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 this if you care more and that's the one thing you can do over the big companies is like you can just care more cuz they have to care about a lot of things, right? Um then you can build that better product and I think you can you can compete.

16:36 >> Do you think we should add a niche to whatever you just said? Cuz 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 play field. 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. >> Yeah, or you become a really big company one day. I think that's the Yeah.

16:58 We definitely want to have billions of people using goodnotes at some point. >> That's And and you're moving into B2B. You started as B2C company and now you moved into B2B. How's How's that shift? >> Well, yeah, it's a it's a good point. Our strategy was to mimic uh like a Slack or Dropbox, like those types of bottom bottoms-up company. So, it's basically a uh product-led growth. So, the idea that someone inside of a company discovers Grainola, 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's going, and all that stuff." And that was always the plan. We always knew that we would be selling to companies. Um but at the beginning we were just worried of now we just focused on just trying to build something people actually wanted and and and liked.

17:57 And that that worked. So, Grainola did spread like virally organically throughout companies. And now we have some very very large companies who are on enterprise plans with Grainola. 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. >> I think it's a great B2B marketing plan when you start with a consumer. How did you get to those initial customers?

18:26 >> We posted on Twitter. Like that was basically >> just like the founding team or >> Yeah, yeah, I think we posted it from my account and I I didn't really have a Twitter following at all and I think we just we got really lucky. It was this idea the way Grainola 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.

19:14 So, it's basically there somehow, and I don't know it's like the universe made this happen. Like, it just caught a few people's eyes, and and they tweeted about us, and then we just started growing. Like, the first day I think we got 500 installs, you know? So, it's like >> That's pretty decent. >> 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 cuz we we weren't doing any marketing. We The crazy thing about Granola is all all the like old-school yeah, I know tickers, they're all super optimized for like growth hacking.

19:46 They'll like at the end of the meeting they'll send notes to everybody who was in the meeting whether they wanted it or not, whether you wanted it or not. And Granola doesn't do anything like that. It's like Granola's 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, 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 experiences.

20:25 >> Yeah, yeah. >> Interesting. So, basically all your marketing is based on >> people loving it. >> Great product. >> Yeah. Exactly. The whole company is based on that. 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? >> so cuz I think um 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 a losing proposition. By default, I always think about very user-facing products. I think it's very different if you're going after a customer support.

21:08 There it it's I think all about having the right sales motion and and marketing is a part of that. But 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 up front rather than doing do that later. >> I have one final follow-up question here. How many initially users did you have? So, how much feedback were you collecting before pushing it out >> Yeah, we had about 150 active users after after that.

21:34 >> That's your friends and that's like your inner circle. >> Yeah. Yeah, yeah, friends and friends of friends and >> What were you tracking when you gave it out like cuz you couldn't see their eyes, right? But who were you tracking with the frequency of use? >> Yeah, so what we would do is we would 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 >> Mhm.

21:58 >> and try to use it without us saying anything. And then we would schedule a call in 3 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 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 there's this there's this thing I'd never heard about it before before Granola, but one of our mentors told us about it and it's a thing called a dot plot. And a dot plot basically it's a think of it like a like a like a spreadsheet and every row is a user >> Mhm.

22:35 >> and every column is a day, right? So, the default dot plot we had would show the last 30 days and then in each cell you basically put for our case like how many meetings did they use Granola for on that day. >> Mhm. >> And and then you change the color of the cell. So, if they use it for like 10 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 start with a dot dot plot when the product's not very good and then you iterate and you iterate and you iterate and what you should see happen you should see it light up. Cuz 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're 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?

23:23 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 never did exist 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 did like five meetings and from then on it became a habit and became hooked and you can be like oh how do we get people to get to have that kind of day? 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.

23:56 >> Amazing. All right, talk to me about your AI stack. What are you using apart from Granola? >> 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. >> This is how I take my notes when I go to conferences. Either I What do you What do you use?

24:20 >> 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. It's a few steps. >> For Granola, yeah. >> Yeah but in terms of form factor I think the the Apple Watch is it just feels it feels very nice. >> Oh 100%. Yeah. It it should be the form factor for all the conferences and everything. >> Yeah. Yeah yeah yeah. And then next I mean I use Claude, right?

24:42 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 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 often times what 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 be like, "Hey, can you look at the analytics for the last couple months and see if that's support torch 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 put a a button here instead?" And then you ask Nacho and Nacho goes and talks to Cursor and like prepares like a change. So it's 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 a still a ton of human back and forth.

25:54 But it's it definitely changed the way we've worked internally. >> So it's basically I'm trying to describe this role. What what is he's not like a C like a chief of staff. He's more like goes to Does does he help with strategic decisions or is mostly like >> Yeah, it's it's it's a lot of like pull me data. Do this thing that would have been like 30 clicks before, you know, or like opening up three tools and saving data onto 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 or going to 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.

26:44 >> Did you use a tool for that or did was it like built from scratch? I wonder like cuz if you you can totally build this with Perplexity computer or like Google or whatever. >> I I actually have to ask. We didn't use anything like that. It's something like Cloud Bot, but it's not Cloud Bot. 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.

27:07 >> Okay. What what have you delegated to AI or what are you doing without AI? >> I think a lot of building great product, it's all about how does this make me feel? >> Mhm. >> Right? And a lot of it is human intuition base. It's trying to put myself in the shoes of another person and and imagining how they'd how they'd experience that. I just don't use AI for that. >> And you can't. What you're describing is something so uniquely human.

27:33 >> 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 their like default behavior. And more often than not, I look at that and I'm like, "Oh, that's clever. I wouldn't have done that, but that's actually really smart and I should do it." But, 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 we'll get um I don't actually know if AI will ever kind of fully fully get in there cuz I think uh I don't know.

28:04 The lived human experience is actually the one thing that we have. >> Totally. Totally. >> Um what 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 you want to make? That that's still very very manual.

28:29 >> it's a very founder driven thing because you're like the soul of the product has your vibe, so it has to have your feelings. I don't know if you can >> Yeah. >> 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 the app. 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.

28:59 That was 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? >> 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. Um the the things that really opened up my eyes, the way 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 Matt. 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. So, uh anything about like deep coaching, "Hey, what are these like patterns you observe in 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. Often times 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.

30:16 >> connect now. I mean, >> No, no, I again but but what I mean by that is So, I have 2,000 meetings in in Granola, or 2,500 meetings, right? So, >> Wow. >> when I ask Claude a question, it doesn't read 2,500 meetings, right? It'll It'll read 10. And it'll try to form a picture about me from those 10 meetings, right? So, I have a 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 strategy.

30:46 >> try that? Can you give me my granola? Can we Let's do it. >> Yeah. >> I really like this problem. Let me Let me see what it what it tells me. >> Perfect. So, if I go here, and then we just say, I'm going to use Chat GPT to do some work, and I want Chat GPT to understand who I who I am, what I'm working on, and what I try to what I'm trying to achieve, so it'll have better context about me. So, please look at um all my meetings from the last month, and write three pages that I can paste into Chat GPT, so I'll have all the context on what I'm trying to achieve.

31:20 >> Wow. Oh, nice. It even extracted some stats. Pushing cadence. Yeah. Nice. >> So, what I find is now, if you take this, >> Mhm. >> and you can go to any AI out there. You can go to Chat GPT, 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, >> Mhm. >> and then you ask whatever you're going to ask, the AI will do such a better job answering your questions, because it understands so much more about >> in my life.

31:52 >> Exactly. >> So, because it's connected to my Claude, >> Yeah. >> how can I ask Claude to self-update using this? To like add context to all my projects. >> Yeah. Well, I mean, there's probably some way we 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. That would be kind of cool, right? If this thing Basically, we're building a version of this where it'll auto-update every day.

32:15 >> Mhm. >> Um and then you could just use that context anyway. >> Yeah. Yeah. That's This is fascinating. So, I feel like you are building something like a virtual chief of staff based on >> Moving towards it. >> 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 30-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 foreign to me. How does Granola work in terms of picking out those details? Uh how does it decide what to surface? Cuz >> In the notes, you mean?

32:55 >> Yeah. Yeah, yeah. >> Yeah, so >> Oh, nice. It gave me product strategy and crowd of markets. I really like it. Building in the AI era market dynamic dynamics, product strategy. >> What we realized early on is that what are good notes for you would be very different than what are good notes for me. >> Mhm. >> Right? So, like the point of notes is really uh dependent on who the person is and what they're trying to achieve. I think we might have been the first to do this.

33:19 So, 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 um 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 isn't what the meeting's about and like what should be highlighted in those notes.

33:45 >> 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. >> Yeah. >> Would it be highlighting that for me in every meeting? Does it have like a universal memory of how I want my notes to present to be presented? >> Not an automatic one yet. >> Mhm. >> Yeah, so that's something you can go and set up a template in Granola. You can basically say you can have different templates and and so you can kind of say, I want notes in this structure. During a call or during a meeting, you can be like, "Hey Granola, make sure to say include this in the notes." And it will do that. But, it won't It doesn't have like a a memory about you said this in the last call, so I'm going to do it in the next call.

34:24 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 you said you said something last month and like Granola still thinks it's really important and like keeps doing that. >> Like just like 3 years ago. >> There's a guy in my team which was like I mentioned muffins, you know, like you like he had one question about muffins to chat GPT once and like now like chat GPT 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 thing is it's like there's just so much richness and context in in in our conversations.

35:11 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 chat GPT or Claude. It's like a very very superficial. >> Yeah, 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.

35:38 >> Mhm. Yeah. >> If it can just pull those things like oh now Marina's focused on that. I'm going to help her in this meeting by suggesting these questions. I'm going to identify this process that's broken in her team clearly cuz I've heard in another calls within her company. >> Yeah. >> Cuz for me like recording my calls is the way is the way to build a virtual chief of staff which we're trying to achieve. >> yeah, I I think almost almost what everybody in AI is trying to achieve really, right? Like like that's that's that's I think >> Some level of autonomy cuz for now I feel like AI has made us much more productive but it only means we're working more. Cuz we see all this productivity gains, 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. I want to take a few weeks off. I can't.

36:27 >> I I yeah, I think we kind of do that to ourselves though, a little bit. >> Oh, true. But this is our nature. >> Yeah. >> And it's interesting like whether we're going to cross this period in time where AI is helping us with strategic decisions, so we uh intentionally take more time off. I don't see this happening now. Um >> On the the point you were talking about a second ago, which is a there's this interesting question of how are you going to um interact with this chief of staff or the this AI and how directive are you going to be? Like basically you're going to 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's 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.

37:16 >> Yeah, exactly. That's what I wanted to do. >> Exactly. >> What will Marina bring up in the next meeting based on her previous meetings? >> Exactly. Yeah, so cuz we A good example here, months ago I tried building a version of Granola generating um follow-up emails. So like you'll connect your Gmail and it will just learn from your previous messages. >> With that person or in general? >> Yeah, no, both. Both. 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.

37:54 >> Yeah. >> 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 going to 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 design things become invisible, right? And And I And I think the like the best AI is going to be stuff that you don't even realize is there and that you >> Self-learning, self-updating, learning from what's changing. This is exactly what you're describing.

38:25 >> to get everyone 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?

38:49 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.

39:11 To to at any moment of need. It 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 They're doing things. You're you're living your life. >> 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 AI's going to replace you in 3 months? Oh, like corporations are just eating eating us, whatever.

39:39 What would you say to those people? >> I think the world's going to change a lot over the next couple years. And I think whenever there's a period of a lot of change, there's going to be turbulence. That is just a reality. And I I don't think we're I don't think anyone knows exactly where we're going to 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 AI's not going to replace people. It's actually going to let people do more.

40:13 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 like Jevons paradox, I think it's called. >> Yeah. >> It's not going to be everywhere though, right? Like there's definitely going to be pockets of society where it's going to be very disruptive, right? And I think 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 in our minds at the same time.

40:48 >> Yeah. >> Cuz I I think that's what's going to happen. >> What do you tell yourself when you have fears about AI? If you ever have them. >> I So, my my view there is I think about what I can control. Generally, this is my my 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 going to 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.

41:19 >> Totally. 100%. >> And I think that and I've seen this. I've seen cuz I think what's happening with engineering is it's like you can kind of see what happens in engineering and the same thing that's going to happen with coding and engineering is going to happen in other sectors later. And I see again, we have a guy in our team, he's 20 and he's 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? I think we're I think we're in the productivity AI productivity theater phase. But I think we're going to 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 24/7, 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 uh how do I get how do I get ChatGPT to make product decisions, but it's maybe how do I get AI to uh >> Get all the data.

42:41 >> the data so I can better better inform to make better product decisions. And so that that's how I would think about it. I've you know, I have a 6-year-old and an 8-year-old, and and I think about what's the world going to look like when they're older, and and I I I don't know, right? But um it's perhaps going to be a little bit easier for them because it 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 ChatGPT is normal, right?

43:08 Whereas I think if you are maybe in your mid-20s right now, uh 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. >> Yeah. Okay, and last advice for founders building in the AI era. What should they be avoiding? >> I think this has always been the case, but it's it's so much more extreme with AI. There's so much noise. Um there's so much FOMO, there's so much imposter syndrome. Like if if you were just if you just look at Twitter, you'd you'd assume that everything is just like solved. And oh yeah.

43:47 And um and I think the real 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.

44:16 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 have it figured out. And the shiny objects and it's like the what's the the fashion of this week versus that week or what have you. 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?

44:41 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 >> You'll be too distracted. And you have to care more about your particular problem. Yeah. Love it. Thank you so much. It was Thank you.