Pod Insights Decoder Notion's CEO wants you to demand better from your tools About this episode This is Casey Newton, founder and editor of Platformer and cohost of the Hard Fork podcast. This is the second episode of my productivity-focused Decoder series I’m doing while Nilay is out on parental leave.
Today, I’m talking with Notion cofounder and CEO Ivan Zhao. I’ve followed Notion for quite some time now — I’m a big fan, and I use Notion as part of my workflow with Platformer. So I was very excited to get Ivan on the show to discuss his philosophy on productivity, how he’s grown his company over the last decade, and where he sees the space going in the future.
Read the full interview transcript on The Verge.
Links:
Introducing Notion AI for Work | Notion
Notion Mail is a minimalist but powerful take on email | Verge
Notion’s new Q&A feature lets you ask an AI about your notes | Verge
Notion takes on AI notetakers with its own transcription feature | TechCrunch
The impossible dream of good workplace software | Decoder
When AI has better taste than you | Julie Zhuo / The Looking Glass
Credits:
Decoder is a production of The Verge and part of the Vox Media Podcast Network.
Our producers are Kate Cox and Nick Statt. This episode was editor by Xander Adams.
The Decoder music is by Breakmaster Cylinder.
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Transcript 10,326 words · 10 speakers
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1:32 Speaker 03 Hello and welcome to Decoder. This is Casey Newton, founder and editor of Platformer and co-host of the Hard Fork Podcast. And this is the second episode of my productivity-focused Decoder series that I'm doing while Neelai is out on parental leave. Today, I'm talking with Notion co-founder and CEO Ivan Zhao. I've known Notion for a long time now. I'm a big fan. And a big part of my workflow for Platformer is actually built on top of Notion's database feature. So I was really excited to get Ivan on the show to discuss his philosophy on productivity, how he's grown the company over the last decade, and where he sees productivity software going in the future.
2:14 Speaker 03 If you've never used Notion, you can think of it as an all-in-one productivity suite. It's comparable to a lot of the collaboration and so-called second brain apps on the market, from the more business-y project management tools like Asana and Airtable, to the more DIY note-taking variants like AnyType and Obsidian. Notion sits pretty comfortably in the middle here, since it can do a lot of what those kind of apps do very well, all in one package. And at the same time, it allows for a really substantial amount of customization, which has made it popular both for individual productivity power users like me and for companies big and small. But Notion started out as a very different piece of software,
2:58 Speaker 03 and its evolution over the last 12 years or so has involved a lot of trial and error, one major reboot, and a lot of big decisions along the way. In my opinion, what really sets Notion apart from so many of its peers is Ivan's obsession with design and craft, and this drive he has to make products that he sees as useful and beautifully aesthetic in equal measure. In this conversation, you're going to hear Ivan talk about Lego blocks a lot. Legos, the toy bricks, are a central inspiration for Notion, which employs its own blocks as a metaphor for configurable templates that let you use Notion in a really diverse set of ways.
3:42 Speaker 03 Everything from simple notes and lists to really complex databases and workflows. But Notion, like so much other software these days, is evolving. Today, the company calls itself "the AI workspace that works for you", and you're going to hear Ivan recount in detail how the launch of OpenAI's GPT-4 proved to be a big turning point for him in Notion. The company launched an OpenAI-powered AI product much sooner than the competition, even before the launch of ChatGPT, and it's added a host of new AI-powered features in the past few years. Ivan himself is also pretty excited about the capabilities of AI. He said he uses it in his free time to learn about new subjects, and you'll hear him talk in depth here about his vision for AI agents
4:27 Speaker 03 that will increasingly do more and more work for you inside of apps like Notion. But a common theme with the AI industry right now is the very large gap between what AI can actually do today and what lots of folks hope it will be able to do down the road. So I really wanted to ask Ivan how we might get to that future that he predicts, how long it's going to take, and what productivity and knowledge work will look like if AI can actually deliver on some of those lofty promises. Okay, Notion CEO Ivan Zhao, here we go.
5:10 Speaker 03 Ivan Zhao, you are the co-founder and CEO of Notion. Welcome to Decoder.
5:14 Speaker 04 Thanks for having me.
5:15 Speaker 03 So at a high level, describe Notion for us. If listeners haven't used it yet, what is it? What does it do?
5:23 Speaker 04 Well, we are an all-in-one productivity software. People use Notion for all kinds of things: taking notes, collaborating on projects, manage your documents, manage your knowledge base, and most recently, we launched a calendar product and a mail product. You use Notion, so you should describe what Notion is.
5:40 Speaker 03 I think you just did a really good job describing it. I do use Notion, which is one of the reasons I want to talk to you, because you know, every time I talk to a CEO whose products I use, I get to give them product feedback, which is exciting for me.
5:51 Speaker 04 Perfect.
5:52 Speaker 03 So do you see Notion today as more for teams than individuals? Is that the direction that it has found?
5:58 Speaker 04 We designed Notion for teams. So another way to describe Notion is we call Lego for software. Maybe it's worth explaining the intent a little bit. If you're a company, if you're a team, you have to use a dozen different tools to get your work done. And our goal is to consolidate those tools into one box and give you the Lego blocks that power all those use cases. Not only you can do all your work in one place, but you can use those Lego to create and customize your own workflows.
6:23 Speaker 03 You and I have talked a fair amount about Legos over the years. What appeals to you about their design? Why is it such a good metaphor for what you're trying to do with Notion?
6:32 Speaker 04 Because it doesn't quite exist with software, right? You think about the last... Fifteen years of SAS. Largely, people are building vertical point solutions. And for each buyer, for each point solution, sort of makes sense. The way we sort of describe it is like a hard-plastic solution for your problem. But once you have twenty different hard-plastic solutions, they sort of don't fit well together. You cannot tinker them. As the end user, you have to jump between half a dozen of them each day. That's not quite right. We're also inspired by the early computing pioneers who in the sixteen seventies thought about computing should be more like Lego-like rather than hard-plastic-like.
7:12 Speaker 04 That's what got me started working on Notion a long time ago during when I was reading their computer science paper back in college.
7:19 Speaker 03 Huh. You wanted to make tools that would snap together the way that Lego blocks do.
7:24 Speaker 04 We want to make tools that amplify human creativity. Legos are creative. Legos are beautiful. And most software probably not as much.
7:34 Speaker 03 Say a little bit more about how you were drawn into this world. Were you always somebody who was interested in productivity tools? Or did that come to you later in life?
7:45 Speaker 04 I think misunderstanding for Notion is like without Notion as a productivity software. That's what we do as a business, as a product. But the easel of this is what I just described is the Legos easel, which is maybe worth to describe the history of the computing industry a little bit, which inspired Notion, right? Like sixties and seventies, sixty, those hippie generation who took acid in San Francisco, saying, oh, holy shit. This like this room-sized calculator, if you put a monitor in front of it, it can be an interactive thing. It can be a new type of medium that help you think better, help you solve problem more collaboratively. That's why the first generation of personal computing, interactive computing were started in the Bay Area.
8:25 Speaker 04 And that generation of thinkers and pioneers thought about computing kind of like reading and writing. Like, we went to school multiple years. Not everybody can read and write English or German, whatever language you are. It's a tool. Yes, you can be a poet, you can be a writing essays, but it's a very valuable medium. So they are set out to make computing valuable and tinkerable and everybody can create their own software. Then, in the eighties, the Bill Gates and Steve Jobs generation took computer into mass market, right? Put a computer on every home and every desk. They sort of freeze computing into this application format. If you think about application, each application, kinda like a mini prison of computing,
9:10 Speaker 04 you cannot change it that much. There's application makers who are engineer programmers and who then their application user, who are the rest of us, the people who use the productivity tool every day. So when I was reading those paper back in of the sixties, seventies people, holy shit, like the world that we're living is like a prison-like world. If anything, the SaaS of the past fifteen years is where even smaller prison cells, like each application can only do a slice of things, right? So that doesn't make right for me. And the customer feel the same way. Like, it doesn't make sense, your daily job, have to jump between twenty different tools to get some work done. The average company, average business, use a hundred-plus different tools, SaaS tools.
9:53 Speaker 04 The fragmentation is obvious even for the IT department. So there's another saying in business, you either bundle or unbundle. So notions squarely in the bundling business. Our job is to bundle SaaS into one-ish productivity tool for your most core use daily needs, so we can unleash the Lego block creativity for you.
10:16 Speaker 03 It's an interesting conversation. It makes me think of kitchen gadgets, because you see the same tension there, where there are some kitchen tools, like, I don't know, a stand mixer or an immersion blender that you can use to make many, many different kinds of recipes. And then there's like the garlic press, which is good for mincing garlic and nothing else. And it sounds like what you're saying is, by the time we got into the 2010s, productivity was just a bunch of garlic presses, and you sort of wanted to come along and say, what if we just had a stand mixer? And you could make a lot of recipes with one thing.
10:52 Speaker 04 You know, a friend of mine used this metaphor, similar to what you said. Have you seen avocado cutters?
10:57 Speaker 03 Yes.
10:57 Speaker 04 Garlic press, you can use press a bunch of different things. Your avocado cutter is made just for freaking avocados. You cannot do anything else. So versus in comparison, a knife, a kitchen knife, is a tool that you can use for hundreds of a thousand different ways. You, as a human amplifies, you have a technique, right? So what is like to create software that's more like a kitchen knife or a Legos? That's what interests me and interests us as a company.
11:26 Speaker 03 Yeah.
11:26 Speaker 04 But the industry, you can't blame the industry, because if you think about it, if you rewind back before SaaS, the world was running on Microsoft.
11:36 Speaker 04 Productive office for like a good solid ten, twenty years. SaaS with Internet as a distribution sort of allow new business to be created. And the natural way to go about distribution of new business is to find really precise point solution. Creating those avocado covers and garlic presses because you can find buyer on the other side.
11:56 Speaker 03 Right. So as we move into today, are you, do you think of yourself as competing directly against a Microsoft Office? A G Suite like is the vision that big or is it something different?
12:09 Speaker 04 We coexist with them like most of our customers still using G Suite or Microsoft Office. It's like they use their identity service, they use their mail and calendar. We have a mail and calendar product currently as a client, mail counter client. Startup can fully run some notion and they don't need to use Microsoft three sixty. Word docs or Google docs, but it's not as mutually exclusive. Their sweet spot is more on the, the thing that you need to put in the database. Another way to think about it is like, what is Microsoft Access but for twenty twenties? An AI native, right? Most SaaS is kind of like relational database storing some kind of system record of your company.
12:54 Speaker 04 And one workflow on top of that. That's the part that Microsoft nor Google touched today. There's spreadsheets, but there's not much database use cases. We want to consolidate and come out of the tight stack and give people the Legos of those database use cases. Such as project management, tracker tickets, some company uses for CRM. Manage your application trackers, reporters, like you can manage all your leads and the stories, right? Those are database use cases.
13:25 Speaker 03 Yeah, and I, and I do do some of that in Notion. Let me ask you about the flip side of building a product that has so much utility baked into it. Which is that sometimes when I talk to people who have tried Notion, they say, I didn't know where to begin. I felt intimidated by the blank page. It seemed like there was a learning curve. How do you think about that challenge and try to bring people along into understanding what, what Notion is meant to do?
13:52 Speaker 04 Yeah. Early Legos, you get bricks. Then later on Lego create system and give boxes. And now Lego work with Marvels and F1s to create like really specialized boxes, right? Uh, in a some sense, Notion as a company were in the middle of adding more boxes. So people, they don't have to start from empty set of bricks, even with no instruction menu. You can imagine like, hey, I want a Formula One race car. I like that Lego box. When you open it, you have your car already made for you. So you can restart driving that, you play that Lego toy right away. But if you don't like certain part of the cars, because they're made from Legos, you can change it. That has always been our philosophy and we're doubling down this approach because it works.
14:36 Speaker 03 I, I feel like a key challenge that some of the other big productivity tools like Office have had over the years is bloat, right? The app has a million features and each individual one is very important to like 0.5% of the user base. So you can't remove it, but also the app just gets harder and harder to use over time because it's so stuffed with buttons and menus and widgets. Can Notion avoid that? And have there been times when you've worried you might be there already?
15:05 Speaker 04 It's definitely tricky. If you want to support more power, you need to have more things. There are two ways to approach it. The classic way is just adding that feature in a hard plastic way. We're taking a more Lego approach. So adding the brick, the brick can be used for different things. In some senses, in my opinion, it's a much better approach.
15:21 Speaker 03 Got it. So trying to offer fewer discreet, very narrow features and more kind of, uh, I don't know, abstract features that can be extended in various different ways.
15:36 Speaker 04 Like Lego system, on one end can be toy cars, the other can, and it could be Barbie dolls. More or less use the same bricks, right? If you look at the most common productivity tool or business tool used every day, if you just put your designer mind on that, there's like 20, 30 pieces there. There's some kind of table, some kind of relational database feature, some kind of charts, right? Some kind of commenting, page editing, collaboration. Those are 20 things are core to all collaboration and knowledge work. So we just, our, we try to do our best job to make them friendly approach, but break them into pieces and give you either as a piece or as a part of package.
16:15 Speaker 03 What bricks inside of Notion are most popular today?
16:19 Speaker 04 We start with bricks about document and knowledge bases. We're famous from our blog-based editors. That's early days, that's like 2019, 2020. And then databases is our most important brick today. Because like I mentioned, most knowledge work, is there just fancy file cabinet, like in the cloud? Knowledge work runs on file cabinet and database are the heart of that.
16:45 Speaker 03 Yeah. Database is my number one Notion brick that I use, so that makes sense to me.
16:51 Speaker 04 People don't discover that. We need to do a better job, get people to understand its power. It's essentially what engineer does every day, is wire together relational database with views on top of that. Like, how do we democratize that? That's our purpose.
17:04 Speaker 03 Well, it's interesting because if I had never heard of Notion and you came to me and you said, "Casey, you should like build a database to solve this problem." That's like, you know, telling me that I should like add another room to my house. Like, I don't know where to begin, you know? I feel like I need to call somebody and ask for help. But in practice, you click a couple buttons and, you know, in my case, install the like Notion web clipper and I'm well on my way to having a database. So, you know, I don't actually think the learning curve is that steep, but I could understand why somebody might be intimidated by it if they had never tried to do that sort of thing.
17:38 Speaker 04 Not every kid grow up liking Legos as their number one toy. I think Notion resonate the best with people who like to build. And they tend to be entrepreneurs, tech people, you know, the spreadsheet groups in each team. They like Notion and then they set it up for the rest of their teammates.
17:56 Speaker 03 Well, that's always helpful when you can get people inside the company doing the sales part for you.
18:01 Speaker 04 And you know what? AI can do this quite well now. Because like what AI is good at is like gluing together the Lego bricks, right? AI can writing code. Writing code is just another way to gluing together your process and workflows. And our latest product essentially get AI to be this success person to help you set up your Notion workspace for you. And That's talking about another way to onboard customer. That's another, that's a brand new way I'll lock in the past year, two years.
18:28 Speaker 03 I will say that has been very powerful for me in a lot of different products. Being able to use like the in-app AI to say, how do I do this? And actually getting an answer, like as somebody who has spent a lot of time in help menus over the years, like digging around and not finding what I was looking for, that has been super useful.
18:45 Speaker 04 Yeah, and it's not just helping you than teach the human to do it. More and more AI can just do it, right? That's the biggest difference is actually if you think about what's happening in software right now. It's like software largely is people providing the tools for human to use. And more and more companies realize, wait a second. We have this new thing called language model. It's like a mini human, mini entering a box. We should design our software to teach AI how to use it. So human can tell, ask AI to do work and using the tools and human can do way more things with it.
19:22 Speaker 03 We need to take a quick break. We'll be right back.
19:30 Speaker 01 New and exclusive holiday decor just launched online at the Home Depot. Check out the viral Grand Duchess collection with smart holiday lights you can control from your phone. Easily customize the twinkle across trees, wreaths and garlands to match your holiday vibe.
19:48 Speaker 01 Create stunning light effects, then switch it up with the tap of your fingers. Even the man in red will be impressed. Shop the holiday decor you want online only at HomeDepot.com.
20:02 Speaker 02 This episode is brought to you by Michelob Ultra. Good times mean competitions between you and your friends. Like seeing who can throw some pigskin the farthest or rush the field the fastest. Winner gets an ultra because it's not just a superior light beer. It's also giving fans superior access to their favorite sporting events. Superior is worth playing for. Visit michelobultra.com/superioraccess to enter. Enjoy responsibly. Copyright 2026 Anheuser-Busch InBev Michelob Ultra Beer, St. Louis, Missouri.
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21:05 Speaker 03 We're back with Notion CEO Ivan Zhao about to get into the core decoder questions about how he's organized the company and the framework he's used to make key decisions about Notion and its future. I want to ask you some of the decoder questions that Neelai would ask if he were here. Notion was last valued at $10 billion nearly four years ago when you raised your last round of funding. What has allowed you to keep growing without raising more funding? Are you guys profitable?
21:33 Speaker 04 We're profitable. So profitable, growing fast, business doing well.
21:39 Speaker 03 Nice. How does that feel?
21:43 Speaker 04 Feels good. I would say the large driver of our everyday activity is like the software industry is completely changing with AI. So it feels like SaaS eras, AI eras of the past two years just make the SaaS era feels like sleeping days. That it's a bigger driver of our execution strategy than just running a profitable business.
22:08 Speaker 03 And I'd like to hear more about how that is working. Is it the case that sort of executives see AI changing various workplaces? They think we need to figure out our version of this and so they come to Notion to help them figure it out? Or is it that your product teams are so excited about the possibilities that you're now seeing them build features and features and features, which are then drawing in new customers?
22:33 Speaker 04 I would say customer are on the lager at the moment. Most people don't know. We can't, it happens with every new technology, right? You don't know what to do with it. The customer not gonna tell you. It's the people who play with this, build things, maybe has imagination few years into the future, right? Or even few month in the future at this point. AI is changing so fast. So a lot is from ourself play with this, realize, holy moly, this is a very different thing. You can't do solving problem that you couldn't solve before with classic software. What are you gonna do with it? There's actually interesting story like we, my co-founder Simon and I got early access to GPT four.
23:16 Speaker 04 So this is like late twenty twenty two, a little bit before everybody else. We thought everybody else get early access to this. So we thought, holy shit, because compared to GPT three, GPT four is a brand new type of thing, right? It's like it has a real intelligent reasoning in it. So we lock ourselves into a hotel room for about a week and just try to rush out the first Notion AI product. We actually launched like a month before ChatGPT happened. It's like, we're excited about what you can do with this new type of material. That's for Notion that energy come from there.
23:47 Speaker 03 How many employees do you have over there? How, how big is Notion today?
23:50 Speaker 04 High three digits, nine hundred, maybe approaching to a thousand, nine-ish hundreds, between there.
23:57 Speaker 03 How do you think about company size? Like, do you see a world where there's five times that many employees? Or do you wanna keep it somewhere around where it is right now?
24:05 Speaker 04 I think there's no right answer for the absolute number, but there's an answer for the density of the talent. The denser is better.
24:13 Speaker 03 You, you like having more talented people as opposed to fewer talented people?
24:16 Speaker 04 If we can do the work with few people and there's less communication overhead, people have more ownership, people can work things across boundaries. That's just better overall. The company move faster, like a small car can turn corners much better than a big car. We always call Notion the small bus. We try to keep the bus as tight as possible.
24:37 Speaker 03 What's your org chart like? How is Notion organized?
24:41 Speaker 04 Certainly classics, myself, my co-founder Simon Akshay. Simon is still coding every day. Akshay, he runs our product and design org, research. Our CTO Fuzzy, art engineer. Our CRO Erica, sales, marketing, CX. Then CFO Rama and General Counsel Hasani.
25:06 Speaker 04 That's our classic work chart.
25:08 Speaker 03 So you didn't feel the need to reinvent the wheel there or do any innovating? Just sort of create classic company divisions and let people go do their thing?
25:16 Speaker 04 Classic company division, high-quality people, keep the bus tight. So allow you to be profitable.
25:23 Speaker 03 How do you make big decisions? Do you have a framework you use or is every decision different?
25:28 Speaker 04 Well, there's a typical things, there's a one-way doors, a two-way doors. One-way doors, try to make it fast. Two-way doors, think a little bit carefully and sleep on it. Those are thinking fast and slow type of thing. I'm pretty detailed. I like to work on the nodes. So there are certain problem I'm good at. And also personally gives me energy I'm interested in. I like to work on the ground in the trenches with everybody. Certain parts, like I can run our finance team. Our CFO, Rama, is really amazing. She take care of that. But certain thing like design, making product trade-off, engineer trade-off, marketing and brand, I like to get involved.
26:07 Speaker 03 Yeah, you've always stuck me as a product CEO. Like, I think from the first time I met you, it seemed to me what was most interesting to you about your company was the tool itself that you were building, as opposed to like the market opportunity or something like that.
26:19 Speaker 04 I build Notion because I want to build Notion, not because I want to start a company or business. I want this thing to exist.
26:27 Speaker 03 Let me ask you one more decision question about one of the bigger decisions you had to make. So in 2015, you decided to shut down the 1.0 version of the app, relocate to Japan, and eventually relaunch Notion 2.0, which is kind of the notion that we think of when we use it today. How did you make that decision?
26:45 Speaker 04 Well, you have to, otherwise you die, right? At that point, it's like we're building on the wrong thing, wrong foundation. And you know what the right thing is, but it's just gonna take you maybe a year, year and a half to build to the right thing. And we're a company of five-ish people, we're gonna run out money. So the only way to do it is shrink back to me and my Simon co-founder. Yeah, we start over. Japan is a good place because like it's it's inexpensive. We've never been, it's interesting and we can just focus on building.
27:17 Speaker 03 I know other founders who have been in that situation and that's the moment where they gave up because they thought, you know what, maybe I could think of another thing to build here, but it seems exhausting. It's gonna take a year. I've already put a year and a half or so into this app. Like I gave it everything I had, it didn't work. What was it that made you say, no, like I, we're going to keep going on this? Like, we think that that there is a vision here that we can actually achieve.
27:42 Speaker 04 The goal is never to start a business, like I mentioned. The goal is to build this thing, right? And the thing doesn't quite exist. Like I mentioned, Notion is like one of the few bundling consolidating software productivity tool out there and doesn't quite exist. Software for Lego doesn't exist. So if I start a company, I'll do the same thing. So why don't I just reset and go back to me and Simon so we can stretch the money a bit longer? Actually, I would just got back from Kyoto last week where there's a tech event there and the Kyoto mayor, we did a fireside chat with the Kyoto mayor about the story because they want, they want to talk about Kyoto with tech and using Notion as an example of how we can blend tech and Kyoto's craft tradition, right?
28:24 Speaker 04 Because we're also inspired really much by the craft people in Kyoto, how they dedicate
28:31 Speaker 04 their time to build something, not just for money, not just for fame.
28:35 Speaker 03 That is so crazy, but I was actually also in Kyoto last week. I, I was on vacation and went there for the first time and had an incredible time. Kyoto is amazing.
28:45 Speaker 04 You got a sense, it's a little bit slower pace. People care about the thing, right? People truly care. That's the thing, it's the main thing. It's not the business, it's not the other surrounding.
28:57 Speaker 03 Oh, absolutely. I mean, like you go to these temples that are, you know, a thousand plus years old and the care and the craftsmanship that they put into them is truly inspiring, right? It's, it's deeply beautiful, it's, you know, very connected to their, their spirituality, their religion, the, the culture, the history. So I could understand why, uh, you know, a founder would go there and, and take a lot of inspiration.
29:22 Speaker 04 It's a bit slower too, so you can focus on that. The thing in the virtual space, computers.
29:28 Speaker 03 Yeah, it's not like San Francisco with our go-go nightlife, our Waymos, the party scene, all of that.
29:34 Speaker 04 Or New York, even more of that.
29:37 Speaker 03 One more of these, this isn't strictly a decoder question, but this, it feels like spiritually decoder question that I wanted to ask you. What is the best productivity tool that you use that is not made by Notion?
29:50 Speaker 04 I like the those chatbot products, ChatGPT, Entropic Cloud. Yeah, it's quite amazing, especially if talking about feature, the conversation mode, right? I love those.
30:02 Speaker 03 You like the voice mode?
30:03 Speaker 04 Voice mode, yeah, the voice mode, like helping learn a lot of different things. I can just, when I'm making coffee, waiting for the water to boil, just talk with this thing for a little, for two minutes, right? Perfect.
30:13 Speaker 03 What do you ask it about? What do you like to learn about?
30:16 Speaker 04 Oof, all kinds. What's most recently? In Japan, I was reading a book about Marshall McLuhan, which is this Canadian.
30:26 Speaker 03 Media theorist.
30:27 Speaker 04 Media theorist, theologian. It's hard to, many of his concepts are hard to interpret. So it's better just to work through with a language model that to help you guide. It's the best tutor. Education should be very different, hopefully be very different a few years from now.
30:45 Speaker 03 I, I think so. This isn't quite a tutoring use case, but I just have to say, you know, I was in Kyoto last week and we were in the neighborhood and kind of had some time to kill. And so I just opened Google Maps and it, you know, sort of opens to where we are. And I took a screenshot and I just sent it to ChatGPT. And I said, tell us a bit about this neighborhood. And it gave me like a history of the neighborhood. It told me the cool restaurants, cool coffee shops, like a museum, places that we could walk to. I mean, like, it truly was as good as I can imagine getting from any guide. And it was as simple as uploading a screenshot. The whole thing took 15 seconds. Like it was, it was wild to me.
31:22 Speaker 04 Especially like one use case I have, like if I go to a famous architectural building and say, hey, I'm at this place. Tell me about it. Oh, I'm looking at this part corner of this building. Tell me more about why is that's the case, right? Because if it's famous enough, it's probably part of the corpus of training. So the language model knows about it and you can just truly a guide tour and you don't need another person. You're just talking with your machine.
31:46 Speaker 03 We need to take another quick break. We'll be right back.
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33:27 Speaker 03 We're back with Notion CEO Ivan Zhao. Before the break, we were discussing a major decision Ivan made to reboot Notion a decade ago, one that helped him keep the company alive and eventually grow it to profitability. But now I wanted to ask him about Notion and AI, and how he sees his productivity platform evolving alongside the new technology. Well, that seems like a good segue into Notion and AI. We've talked about what Notion is, how it's changed. Notion now bills itself as the AI workspace that works for you. So what does an AI workspace mean to you? What do you want it to be for us?
34:04 Speaker 04 If you think about our strategy during the SaaS era, it's bundling, consolidating a bunch of different tools for knowledge work into one place. And what's changing in the past couple of years is now with all those soft knowledge work Lego in Notion, you can not only providing the tool, but you can assemble them as your AI teammates. They can do the work for you. And we're fortunate to have those knowledge work Legos in one place. So you can piece together in a very interesting way. One end can take notes for you. The other end can, you know, help you manage triage projects, you know, writing document. Those are basic things, but more and more with more Legos and smarter models, you're essentially higher notion as your AI teammates.
34:47 Speaker 04 That's the future that we've been building or building more towards.
34:53 Speaker 03 Yeah, I remember one time I was meeting with you and you just launched some of these AI tools. And you were showing me that Notion AI was was taking notes about various meetings. And so you were able to dip into meetings at the company that you did not personally attend and just kind of quickly catch up on what your coworkers were talking about. And I thought, that's super interesting, right? That's like some, that's the kind of feature that I can imagine a lot of CEOs wanting. But before this point, they haven't had that level of visibility into their own company.
35:25 Speaker 04 We just launched the three separate product a couple of months ago. Notion AI for work, including next version of this enterprise search product you talk about. So along with that was a launch AI meeting notes product. So all the meetings you can record and transcribe that. So essentially, your company has a collective brain of what's going on. And you have all the AI knowledge workers on on top of Notion to help you transcribe the meeting notes, answer whatever question you may have. It's it's quite interesting what you can do with the technology now.
35:55 Speaker 03 Of all the AI features that you've added so far, which ones do you personally find the most useful?
36:01 Speaker 04 I use AI meeting notes almost every meeting except this one I record. And I use that for meetings so I can share the notes with other people. I use it for myself as a starting position to dump my thoughts. And I can remember later where I can use this to ask AI to turn the transcription into a writing. English is my second language, so I'm not the fastest writer, but. AI can do a better writing than I can if I just dump out what I on top of my mind through the transcription. AI meeting of future.
36:34 Speaker 03 There's a lot of talk right now about AI and whether it might replace workers or entire workflows or functions within an organization. You've talked today about AI being able to serve as a kind of teammate. Do you think that AI and Notion will get to a point where executives will hire fewer people because Notion will do it for them? Or are you more focused on just helping people do their existing jobs?
37:01 Speaker 04 We're actually doing putting out a campaign about this in the coming weeks or month. We want to push out a more amplifying positive notion about what they can do for you. So imagine the billboard we're putting out. It's you in the center. Then with a tool like Notion or other AI tools, you can have AI teammates. Right? Imagine you and me start a company, we're two co-founders and open Notion, sign up Notion. And all of a sudden we're supplemented by AI or AI teammates, some taking notes for us, some triage, some doing research while we're sleeping. So all of a sudden we're a team of company of 10 people. So then the startup can run much faster.
37:43 Speaker 04 That's the notion, that's the that's the vision we want to push more towards the world, so more of an amplifying force rather than a zero sum force.
37:52 Speaker 03 And like what timeframe do you think that arrives on? Does that feel like it's almost within reach? Or do you think we're going to need to see several more research breakthroughs before that sort of thing becomes possible?
38:06 Speaker 04 From someone who is building with this every day, I think a capability, it's pretty much there for there are different spectrum complexity of knowledge work, right? The model is quite smart. I would say what's lacking are the plummings, the toolings that's unlock the capability of the model. That's essentially what Notion is doing with the Lego blocks, be the plumbing and tooling. So that's one constraint. The other constraint is just how people use it, how people plug into their workforce. Like bureaucracy, sometimes it's a good thing, sometimes a bad thing. In this case, I think it's actually a good thing because it slows things down a little bit. Give people the time to adopt, to learn with this new tool. I think it's good. So capability.
38:50 Speaker 04 It's more or less there and if not, every three months you got a new one. So the trend just keep coming, right? So.
38:57 Speaker 03 You know, a- at the same time, I think the biggest flaw in the AI models that we have today is that they're not reliable. They don't answer the same question the same way a hundred percent of the time. And so if I'm relying on it for mission critical stuff, if it's one of the ten quote unquote people at my company and I tell it to go grab some facts and figures and it just kind of hallucinates the wrong one, that's like really bad. Like I, I, you know, if, if that were a real worker, I would, you know, I don't know, put them on a performance improvement plan or something. So how do you think about reliability as a challenge to what kinds of services you want to offer people?
39:39 Speaker 04 It's definitely an issue and getting, I would say getting better in generally. I would say the best closest mental model is like a trading language model, just like a human, just like an intern. Human make mistakes. You, your trust level, when you tell another human something, you, there's nothing guaranteed this human cannot mess it up or tell another person even till you don't want to. So fundamentally building trust this way. People's expectation for software is higher because software for the longest time is always do exact, if you, there's no bugs, it's always do exactly what you told, right? AI is a new type of software. Our expectation hasn't been set how to deal with this yet.
40:18 Speaker 04 I think as more people getting used to it and as we learn, change our habit around it and company change their workflow around it, I think we'll find an equilibrium that's like amplify the better part of this technology and deal with the short, short, short fall of it.
40:37 Speaker 03 Yeah, I think the, the podcaster, Dorkesh Patel, said something like, an AI today is better than an intern on day one, but worse than an intern on day five. Cause like on day one, they have all knowledge of human history and they can sort of dazzle you with all, with their capabilities. But also they have trouble learning and it's hard to sort of show them how to do something once and then have them do it reliably every single time, whereas a human being could do that. So I'm personally very curious, like what is the point when an AI is better than that day five intern?
41:12 Speaker 04 I think all company are, including Notion, are trying to figure out technique to inject memory and learning into this intern. In the coming quarters, you will see product with this baked in.
41:24 Speaker 03 Okay, now my ears are perking up because it sounds like we're getting a little bit of a preview. Do you want to tell us what you're working on over there?
41:30 Speaker 04 A couple of months ago, we launched this Notion AI for Work has enterprise search, has AI meeting notes, has deep research to help you draft documents. The upcoming product, you can actually not, each one, imagine each one is the AI intern can do specialized thing, right? The upcoming product, you can actually create different flavors AI intern, AI teammates to live with you in your workspace. That's as far as I want to share. And Notion essentially can do everything you can do, a human can do.
42:02 Speaker 03 I like the sound of that. Let me ask you about, this is, this is my product request and you know this request because I've had it for a while now. But basically, when you first started adding AI features in a Notion a few years ago, I put in this request because every link that has ever been in my newsletter platformer is stored in a Notion database. In many cases, that includes the full article text. And what I want is to be able to have a conversation with that particular database, right? It would be so useful for research and brainstorming columns. At the same time, it's, you know, I don't know, hundreds of thousands, millions of words. It's not the sort of thing that you could easily like throw into a context window and just let me have that conversation. So my question, Ivan, is where are we on the stream of mine?
42:46 Speaker 04 To having a conversation with all your thousands of articles in Notion?
42:50 Speaker 03 Yes.
42:51 Speaker 04 It probably already there because there are techniques invented called RAG that you don't have to fit everything into a context window. You can like index everything, embedding everything and piece information out as you need it, right? There's another technique that's been popular in the past year or so called tool use. It's essentially teach the language model, your agent, to know how to use search. So if you have a question that's not in the contact window initially, the agent can go there to, just like a human, can do you find more information about it? Or take a little bit more time round trip, but eventually it will give you what you want. So all technique will make the use cases you're describing better.
43:35 Speaker 03 I like the sound of that. And you do have like an Ask Notion feature already that I imagine can, you know, access some element of what I'm talking about. And, you know, a lot of this stuff is just sort of on the web. So, you know, there are other ways of accessing it. But I just always think, man, if I could have like a lightning fast way of just like chatting with this database, the way I would chat with a coworker, that'd be super cool.
43:57 Speaker 04 Oh, it's it's sure ready be in your Notion workspace. I'm happy to walk you through the new enterprise search, which is large. It's perfect for that.
44:06 Speaker 03 Okay, great. All right. We'll we'll troubleshoot that offline.
44:10 Speaker 03 OpenAI has come up a couple of times today. You work closely with them. Recently, they announced you can use ChatGPT to create presentations and slide decks. All of the big labs are working on these full stack virtual assistants that they say might someday be able to do anything a remote worker might be able to do. Do you think that they'll get there in the next, let's say, five years? And what role do you see Notion playing in a world where AI's capabilities are rapidly expanding that way?
44:40 Speaker 04 One way to think about it on the spectrum of whether it's a more personal B two C flavored or it's like B two B team first flavor. I would say most labs product currently building is more of a personal assistant flavored. It can help you to do work or help you to cheat on your homework. And usually B two C tend to be winner takes all, where there are a few winners. And I think it makes sense for for labs like OpenAI to go really hard towards that direction. Notion squarely is a B two B company. Our product, our business model is for business, other businesses. And inside B two B, there's required making different trade off. There's so many different subcategories and it has to be team first to start.
45:24 Speaker 04 That's why our AI teammates, our AI agent, AI assistant, fundamental live in a team space that you or the rest of your your company employee live in. That's the angle we're taking. There will be. In my opinion, there'll be many different winners in a B two B because B two B usually is not winner takes all. And you need to make very different trade offs.
45:43 Speaker 03 That's interesting. I I'm still not sure I totally understand. Like, say a bit more about like, what does this B two B AI world look like and why is it that that will have many winners whereas B two C maybe doesn't?
45:56 Speaker 04 Well, you you can think about in the professional setting, right? So if you think all knowledge work, there it's lawyers, there's accountants and there it's programmers, right? There is customer support and they're all different. It require you to make a little bit different trade off or a different type of AI agent. You already can see this in the first generation AI agent. They need to be specialized and to plug into different contexts. Versus the consumer side, you just want to chat with your AI chatbot. It's a very universal. That's why in the B two C side, in the previous generation, like there's iPhone and Android. There are two things largely and the B two B is SaaS. There's thousands of different companies, hundreds of different categories.
46:36 Speaker 04 Right? So they force your product to make, and whether it's to be a software or AI product, make very different trade offs. You cannot be airplane and a submarine at the same time. That's why in the professional setting, you see lawyers, accountant. And there's a lawyer agent, there is a financial agent that behave very differently. They need to behave very differently compared to your personal system that you wake up every day you can chat with.
47:00 Speaker 03 Right now, you sell AI tools as an add on in your business and enterprise plans. I'm curious if this hurts your margin at all. We hear a lot about how expensive and compute intensive, resource intensive AI systems can be to operate. Is it a challenge to integrate those sort of like resource hungry tools into your existing subscription?
47:21 Speaker 04 We actually recently merged AI into our main plan because more than half our sales now customer want to buy this product, AI product. So it makes sense to simplify the whole. Planning, um, pricing buckets to just include into everything. It does make the margin uh not as good as as pure SaaS, pure software. But it's so powerful, people appreciate it. And still, our company is cash flow positive, so our CFO loves that despite it's a different margin profile.
47:52 Speaker 03 We we've already seen some companies move toward usage-based pricing for AI, which like as a consumer I hate, I don't want to make like micro payments to ask ChatGPT a question. But it does seem like that is maybe a better business model. How do you think about the trade-offs there?
48:07 Speaker 04 I don't think people figure it out, especially in the um business setting, P two P. The first generation is kind of like customer support. Customer support, you can map to the call outcome resolution-based pricing. That makes sense. Then there's sort of the the second generation, which is saw right now is coding, right? Coding, it's it's uh there's a C base, but if you use a lot, you have to go usage-based. That sort of makes sense because your exchange, it's it's a piece of work. You get your file, you get your software at the end of day, right? So people appreciate that and it's save programmers so much time than actually writing the piece of software themselves. Knowledge work is nebulous. Knowledge work, you can't put a price on the knowledge work. Like it's this chunk of doc, how much is it worth?
48:52 Speaker 04 It's you can't really put that in like it's and how good is a piece of knowledge work? How good is your product spec? You can't put a dollar sign behind it, so much harder for a general purpose knowledgeable product like Notion. That's the thing the whole industry need to figure it out.
49:09 Speaker 03 What do you wish that AI would make possible in Notion that isn't quite yet possible yet?
49:14 Speaker 04 You can always get cheaper and faster and smarter. But you know the train is coming for that direction, right? So it's a very, it it's it does require you build company in a different way. I think this is like the software industry is realizing this right now.
49:32 Speaker 03 Say more about that.
49:33 Speaker 04 First of all, this is kind of like. I never worked during the dot com era. That was a little bit before me. People said during that era, the web standard changes all the time. Every couple, couple month, three month is different, right? And I never worked with into some like hey, this intel. Like Moore's Law era, it's like you can just expect the next eighteen month from now. The next CPU can drive whatever software you do. AI sort of feels that, but even on steroid, like every three months. The next model, it's almost can do what you couldn't do before. So this require you really change how you build software and build product and build a company. Couple of things. One is because it's constant changing.
50:17 Speaker 04 You can, and the model itself doesn't like too much restrictions. You need to build a harness or just around the right places. It's almost like if you build too much around the train track, the next train comes. You, you, you just make what you should build obsolete, right? You should build parallel to the train track. That's number one. Number two is like the language model are, are not deterministic. It's a different from classic software engineer. The metaphor I like to use is that classic software engineer is kind of like a building train track or building bridges. It's, it's Newtonian physics. Everything's predictable, right? And if you can't imagine it, you can build it. Sometimes it takes three months, some six months, but eventually you can build it, right? With this language model thing is squishy. It's organic.
51:01 Speaker 04 It's, it's kind of the analogy I love to use is like brewing beer. Right? You cannot tell the ease, okay, my beer gonna taste this, please. Ferment yourself become like that. You have to channel what's in the model. The best you can do is create environment, massage the data, massage the context. The hope the best, right? So this requires a much more of a iterative approach. You cannot come from your vision or customer need first. You have to come from what the technology give you, what the ease, what the beer give you. So really much allow you, your team to be more empirical, more experiment. Less of this kind of waterfall classic way of like spec to code should be more like incremental iterative.
51:44 Speaker 04 All this add together make force you have designed a different engineer product design work.
51:49 Speaker 03 Does it change the way that you hire? Does it change the way that you structure teams? Like, how does that strangeness that you described translate into a different company?
52:00 Speaker 04 People need to be more okay with ambiguity. People need to love ambiguity. People need to be AI um more experimental, right? The boundary between role to even greater, like I notion we hired designer who can cope. Because if you're engineer and designer in one, you can think a lot more ambiguously, more fluidly, right? AI time even push that even further. Because the design and product you sit side by side with engineers. Oftentimes, what you want, you cannot be built. So you have to really try a bunch of different things. That's why you see a lot of product demos like sixty, seventy percent, but never become real product. That's like because it's good for making demo, but to get to a production B two B software, you need to be really good and to be reliable.
52:46 Speaker 04 Oftentimes, you never get there.
52:48 Speaker 03 I think about this a lot in the context of like these voice based assistants, which today mostly what I use them for is like setting a timer or like asking what the weather is, like these very deterministic things. And the companies that are building them are trying to integrate these new AI based backends. But it it's incredibly hard because if the user is still using the product, they're still going to want to set the timer. And if it goes from doing it correctly a hundred percent of the time to like ninety three percent of the time, that's like a much worse product, right?
53:19 Speaker 04 But you, I think as human, we all learn what's the best, what is this type of technology best at, right? It's when you're having a conversation, like how using the voice mode, you want it to be ambiguous. You want it to go to different places. That's a feature, not a bug. I think us as a whole as industry who making the software with AI and who us as audience who use this, we haven't figured out the stance yet. It will take some time to figure this out, like use the material for the best use.
53:46 Speaker 03 Well, I want to end just by asking what you think Notion looks like a little bit into the future. And I will not ask you about five years from now, because I don't think anybody has five years worth of visibility into anything. But if I could maybe ask for like two years from now, what do you hope Notion is doing that it's maybe not doing today?
54:07 Speaker 04 I think going back to what we just talked about, the nature of software is changing. It's changing, evolving from just a piece of tools.
54:17 Speaker 04 To this organic matter that tool can do some work for you. And the heart of this company in the SaaS software, classic software areas, allow people to build tools, to allow people to use this Lego to create whatever tools they want. Because the nature of software changing, what we care about allows you create AI teammates to help you take some of the most repetitive knowledge work you don't like to do. If we can realize that, there's a lot of implication. The next generation builders is going to run on company very differently. And I care about solving that problem.
54:52 Speaker 03 All right. Well, Ivan, thanks so much for joining me today.
54:55 Speaker 04 Thank you for having me.
54:59 Speaker 03 Thank you to Ivan for taking the time to speak with me and thank you for tuning in. I hope you liked it. If you want to let us know what you thought about this show or what else you'd like us to cover, drop us a line. You can email the team at [email protected] . They really do read every email. Or you can hit me up directly on threads or Blue Sky. I'm at Crumbler on threads and I'm Casey Newton on Blue Sky. Decoder also has a TikTok and an Instagram. You can check those out at DecoderPod. They're a lot of fun. And if you like Decoder, please share it with your friends and subscribe wherever you get your podcasts. Decoder is a production of The Verge and is part of the Vox Media Podcast Network. Decoder is produced by Kate Cox and Nick Statt. This episode was edited by Xander Adams.
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Previous GitHub's CEO says AI coding is ‘here to stay’ Next ChatGPT chief Nick Turley doesn't want you too attached to AI Page updated October 26, 2026 · transcript and summary are machine-generated
