RAG is the key for smarter productivity tools with Notion CEO Ivan Zhao

Hi listeners, welcome to No Priors. Today we have Ivan Zhao, co-founder and CEO of Notion, the beloved productivity application for notes, tasks, and knowledge base. They recently launched an AI Q&A interface as well as a calendar application. We're super excited to have Ivan. Thanks for being here again, Ivan. Uh, we are going to start with, uh, the hardest question, which is what is Notion?

Notion is always pretty hard to define because it can do so many different things. But that's also our goal. We want to give people one tool that they can do their most work with. For a personal user, that means all your personal notes, all the planning for a trip or for your wedding. For business, for enterprise, for a company, that means all your documents, all your tasks, all your issues, calendaring, knowledge base in one tool. The reason we want to do that, because there's just so much fragmentation. In the market today. We wish, like, it wouldn't be nice as one place to do your most work. And our approach here is rather than try to cram all different use cases into one product, what are the underlying software building blocks? What are the Legos that power those use cases? Can we give users those Legos so they can be creative with software themselves? They can create and tinker their perfect workflow for their personal life. Or for their company. And none of this is new, by the way. Like, people back in the '80s, even '70s, tried this kind of building blocks approach to software. We're just trying to take a modern spin with cloud and with AI to what it's like to break the prison of application-based software.

It's dramatic to think we've been living in a prison of SaaS fragmentation the last 2 decades. But I do think it's actually surprising to hear a point of view that is so obvious, which is like, of course we'd want one tool where the data was interconnected. Why do you think people— why do you think more people don't try that to have unified tools and unified data underneath?

I think people try for different angles. Even fairly recently, there's this thing called no-code. No-code is coming from this kind of power user developer angle of wouldn't it be nice everybody can modify this underlying software they use every day? That's one angle. It wasn't coming from the angle of the knowledge and data wants to be in one place, right? And language models sort of give another angle is the underlying knowledge in embedding space wants to be one place. Wouldn't it be nice in one place, right? And the macro is also coming from the budget place. Wouldn't it be nice rather than pay for 5 different vendors And all sea-based business just pay one vendor and save some money. So they have different angles from different times. I would say we are more come from this kind of computing and medium and literacy angle. Like you and me go through school to learn how to read and write English and Chinese. We've spent years to do that. We all know how to do that. The world, the same MacBook for most people are very rigid. It's more like a machine to do typewriting or watching YouTube, not much more beyond that. It's not very creative. Wouldn't it be more nice that more people can use their software more creatively? Because there's a separation between people who can make software and people who use software, That's why SF rent is so expensive because we're the modern-day Detroit or Manchester. We're the factory of the world. Notions largely come from that angle, which is the original angle. We were inspired by early computing pioneers. They thought about that angle. They thought about computing could just be like literacy. One day everybody can do it. I guess they didn't expect AI might make that even give a really interesting twist to it because now language model AI can not only create software but also do a lot of thinking and working for you. So the future is pretty interesting.

So for someone who thinks on span of decades of what should computing look like and what were the most ambitious plans for personal computing, 3, 4 decades ago? What are you most excited about seeing from AI broadly over the next decade?

I think 3, 4 decades is a bit too long. If AGI happened that time, computing might not be necessary. For this decade, I think one sleeper category is the RAG embedding space. Decades might be too long. I would say in the next year or 2. Now the language model can understand what you put into a computer understanding. So rather than you to the organization to make you retrieval, retrieve the understanding more easily, machine can do that better than anybody else can.

Right.

So before that, we use keyword-based search where you find your coworker who remembered that, that cue. Where does that information sit? Now just ask Notion AI and you get that in seconds. So that's one I'm personally really excited about. I think not enough people talk about it. And of course the other one is the agent, the workflow side that has a lot of buzz already. So that's interesting too.

You and Simon said bet the company on AI and have real conviction. And as you are building out the team, what does the talent look like? Have or need to make Notion an AI-first company?

I kind of argue you folks are one of the earliest adopters of AI at scale as an application. So part of the question in some sense is you've built so many interesting things, what are the people that you now need to build the next level stuff in addition to what you already have on the team?

In the early days, kind of just brute force. Simon's really good thing. I built a lot of things and learned really quickly. I would say Notion as a company, we're largely people interested in interface and design, a lot of full stack. Frontend heavy folks and backend people who scale. We have somewhat a small team of search, but we don't have too many ML folks, almost nothing. And in at least my learning, our learning in the past year or so building for AI is, okay, ML folks are important. It's kind of like you no longer do this deterministic thing that you can see how it works. It's almost like a— I don't bake, but feels like baking, right? You have to do something, get the ingredients ready, run through, rinse, press the button, and wait for a while and see, does it come up? Or it's a different way, a different sense of patience, and different type of personality to do that well. A lot of massaging, a lot of preparing.

Some of my friends call that probabilistic software engineering.

Kind of like—

I think it's morphed into this sort of stochastic world, or at least partially stochastic.

Yeah. So one is like Maybe gardening feels like that way. I don't garden either. So that category of people are, to me, is pretty necessary. The other category is people who are curious and learn really fast. It's like, okay, like the group of prompt engineer language models sort of make everybody like a real-time machine learning engineer. You just prompt right, then you can get your stuff.

Mm-hmm.

And there's a lot of trick and techniques And how does that plug into user interface? I think this category of people called AI engineer or something, there's some terminology for them. They tend to be pretty young. They tend to be like, we have someone under drinking age working at Notion. They fit into that bucket and I think both seems to work quite well. We don't have too many researchers at Notion. That's another one I think will be important, but we fundamentally sit in the application layer. So it's more about apply side of things.

So more manipulating the models and making sure you can scale them to user outcomes and think about that.

And another part is the scaling part. How do you scale to tens of millions, 100 million users? It's a problem on its own too. It's beyond just a demo on Twitter. Right. It's tricky. Yeah.

So you have often said that Notion is less a productivity company than an application building company. How do you think about the initial use case and what makes you believe people want to build more applications?

I don't think people want to build more applications. What got me started in Notion, got us started in Notion, it's last year college. I read a paper by one of the computing pioneers, Douglas Engelbart. He talked about— his paper's name, Augmenting Human Intellect. So every day we use software today, very much like application. You go into one application, do one thing. But for that generation of computing people in the '60s, '70s, '80s, computers are a lot more— software are a lot more malleable. You can actually tinker and modify. Smalltalk, you can go into it and change how the operating system works on the fly. That really inspired me. It's like today people's software is so rigid. Can we create a new breed of software that people can modify, can change and customize and bring back some original ethos of those early computing pioneers? That's why we started Notion. The hard lesson for us is like you mentioned, most people don't want to create software. They don't wake up and say, hey, I want to create my perfect project management tool or my perfect knowledge base. Their boss asks for something, they just have to get that work So in some sense, our learning and pivot is instead of giving people those software building tools, we have to package the software building blocks together as ready-to-use templates, as ready-to-use use cases that people can adopt really quickly.

So you were one of the earliest adopters of AI in terms of application with any real scale. And I think it's impressive how quickly Notion ended up starting to work in this area. How do you think about how that impacts different aspects of what you built and what you're building going forward? And how does that impact that vision of saying, okay, we have this effective platform that allows people to both interact with documents or core use cases in simple ways, add things like calendar, but then also go in very interesting directions in terms of both the set of applications and templates they can use?

Yeah, I think we're lucky. Like I mentioned, we're not trying to build specific use cases. We're trying to build the Lego bricks that power those use cases. What are those Lego bricks? Text editing is one fundamental Lego brick. Most software have that piece. Relational database, a table, is one fundamental Lego brick, right? Different form of permission, commenting. So we've been spending 5+ years building those Lego bricks and feels like, boom, AI just jumps in almost like a brand new car engine and can power those Lego bricks in brand new ways. So it feels very lucky in that way. And that, because we've been building those Lego bricks and refining those, allow us to ship features Plug in with AI really quickly. We're one of the earliest ones to launch AI writing for productivity software at scale because we've been spending years building a text editor. We can do AI-powered database table features really quickly because we've been building relational databases. We've been building a knowledge base for a long time, so we launched AI Q&A really quickly, fairly quickly. The RAG system on top of Notion Because we have those Lego bricks. So in some sense, it's kind of like just the right moment, right time for us.

How did you begin to resource and prioritize this effort? Because you're like, ah, magic, we have this engine, it applies to our Lego bricks, and then you start shipping pretty quickly. But I think there are a lot of organizations right now trying to figure out what to do with AI. And so in terms of designing the features, prioritizing that effort versus everything you're already doing in a rapidly growing software company.

I think I had the conviction. My co-founder Simon, actually they all had the conviction. Funny because we all live in the mission and OpenAI initially still is in the mission. And some of my friends, especially Simon's friends, work at OpenAI. I remember we'd go to their office during the Dota days. They were like, what is this company doing? Kind of interesting. And Simon and some people at Notion saw early demos of GPT. It's like, what is this thing? Spitting out text. Sometimes gibberish, sometimes useful. I personally, I have to admit I slept on it. On GPT-3, even saw GPT-3, feels like, what is this thing useful for? It's like, yes, for marketing, for content writing, create a first draft. Didn't really click for me personally. For me, was fortunate enough to start early preview GPT-4 and that's like, oh wow, this thing can think, it can reason, it can know how to do things, has this little bit of workflow power to it. That's a big aha for me and it just personally gave me so much conviction. This is going to change everything. If you think about what knowledge work is in, why do we use software? Fundamentally, SaaS software, this is all— we're all in the same information, people, paper pushing activity. It's like a piece of paper coming in front of you, a human changes a couple bits, push to another human. Language model can do some form of this now. So that just gave me the conviction, this is going to completely change everything we do with a computer. And after that, we sort of just bet the company on it. We're lucky enough to have those Lego bricks and then which Lego bricks can work well with AI, which doesn't. We're trying to figure that out. Who inside the company are good with this technology? We have search, but it's not like— we don't have a lot of ML folks, so need to hire more ML folks. Need to get people inside the company to have similar convictions so we can move in the same direction. It's quite interesting. It's kind of like— So it must have felt— dinosaur feels like when asteroid hit the Earth and it's like, what do they do?

Yeah, yeah, there's a lot of change coming for sure.

It's a lot of change. Yeah.

What do you think is missing from the capability set? Because to your point, I think a lot of people weren't really thinking about AI too much until ChatGPT and GPT-4 came out. And there was a period of time where 3 and then 3.5, and you started to see the capabilities incrementing up and entirely new businesses are suddenly enabled with each sort of step with the next GPT level. model, GPT-5, or to your point, RAG adds a lot of capabilities. What are the biggest missing gaps for you to take full advantage of this technology? Is it future reasoning? Is it better thinking and knowledge? What's the—

Yeah, I think all of that above to me feels like technology is fundamental. We're in the tech business. Technology is fundamentally about trade-offs. The plastic can do things that wood cannot do. And we discover plastic and then we figure out new things. We can bottle water like this. Before, you cannot bottle water with a wood table.

Right.

So all of a sudden we have this thing called language model. You have a new characteristic that deterministic software cannot do in the past. And we don't really know how it's made fully. So every month, every week, if you're on Twitter, people discover new techniques to get more out of this? And for companies, entrepreneurs, they're also making trade-offs, discover how the market reacts to these capabilities of this new what, this new language model. And so it's a constant evolutionary cycle happening really, really fast right now. I think with that mindset, what are the dimensions? On the technical side, on the technology side itself, yes, the model gets larger context windows, more reasoning, better speed, smaller footprint. Those are all great. For Notion to power the workflows that we really need, we learn GPT-4 is smart, a Claude 2 is smart. We need that intelligence to do reasoning or for the text summarization cheap. Fast is better. That's the technology side. And in my opinion, there's so much about human behavior as well, just like inertia in our personal behavior, companies' risk tolerance, and that's slowly evolving as well. Like what Steve Jobs always talked about, you cannot make something too new. You have to be largely the same and change one thing and two things.

Right.

Virtual Abloh, the Off-White guys, like 3% difference. Just push the boundaries so people can accept it, but still also new. To me, it feels like language model-powered applications are kind of in the same phase. If it's too different, people are like, what do they do with it? Such alien behavior. It has to— the RAG is pretty nice because largely existing behavior but better output.

Can you describe the AI Q&A product? For people who haven't experienced it.

Right. Essentially everything you put in Notion, Notion can help you remember. And this is not just applied to Notion, it pretty much applies to most RAG systems. Why do we use computer? We need to store things and need to recall things. Before language model and RAG, the recall largely happened based on keywords. The keyword has to be precise or there's some lexical tech tricks that you can recall easily, imprecisely. What RAG happens, the language model can actually understand what you're putting into there. So you no longer need to organize your information in Notion. Whatever you throw in there, you can find it later. What that means is for a person or for a company, for a team, you can have perfect memory. And not only have perfect memory, the right piece of information If we design our software right, can push to the right person at the right time. That's probably more than 50% knowledge work. We're still perfecting the system. I think we're one of the first on the market that apply at scale. We still have somewhat a waiting list because it's hard to do this at scale still. But for a company, for a team, before search is one of our weaker point, but with RAG you completely change that. It changed how I use Notion. I can just ask a question to Notion like, How large? When are we moving out of the SF office to a new office? And someone in the company wrote in some documents, I don't have to ping 3 different people to find the answers. If it's in Notion, go find it for me. Everyday engineers, designers, operation people just keep asking each other on Slack or in email such a question. Each question is 10 minutes, Writing the answers, 20 minutes to find the answers, and there's the delay in the middle. With Notion Q&A, you can completely cut that into seconds. We're just at the beginning of what RAG can do for work.

It's pretty amazing. I feel like RAG and embeddings are very underdiscussed or underappreciated in some sense relative to the impact that they really seem to be having or starting to have. And I think Notion Q&A is a great example of that. I guess the other thing that you folks just launched is calendaring. And if you can't talk about it or if there's nothing to talk about, that's fine too. But I feel like one of the really interesting things that people are talking increasingly about is agents and sort of the agentic world. And there's a lot of capabilities missing to really make those valuable. But in the context of a calendaring application, you could think of all sorts of ways that having AI act on your behalf or help understand things can be incredibly valuable. And so I was just curious how you think about the application of AI relative to calendar versus— Some of the core information-related things that you just talked about.

Maybe we can group AI stuff into, at least in my mental model, it's the RAG, the knowledge information retrieval is one bucket, knowledge bucket. Then there's this workflow bucket. I use the word agent, that's in that bucket. Calendar is somewhat in that bucket. Why do we need to meet? Why do we need calendar? Because we need to meet and we need to schedule time. We need to Figure out, exchange some kind of bits between my brain to your brain. Can that exchange be done by a language model? Maybe. And can the meeting time be done by scheduling be done? That's like a baby step. And most things we do has this kind of time dimension to it. Can language model help us shuffling our schedule?

Yeah, it feels like there's also the information retrieval piece of it because if my calendar auto-populated everything I need to know about the meeting or the people attending or other things that's incredibly valuable as a user of a calendar. And so I just feel like there's a lot of these things that kind of tie in together both in terms of the coordination, which you mentioned, and the workflow. And then separate from that, there's just, what do I know about this person?

Yeah, I think the calendar part is the simpler part of the workflow. Like the holy grail is kind of like, can just the agents, robots do our knowledge work for us, right?

It's a really interesting framing that I didn't have before of a bunch of the work you're doing at Notion actually eating into Communication. It's sort of obvious in retrospect, but if you look at what you describe of, am I really going to Slack back and forth about this thing about when we're moving? If I can just know, I'm in Notion, help me know. Or with calendaring, the most intelligent version of it is, well, do I need to have that meeting or can you tell me what Ivan was going to tell me?

I know. Why do you need to communicate? Because there's something, the work cannot be done asynchronously or by the software itself. Then that's why you talk. Yeah, it's interesting. Maybe it's an interesting question, are we going to communicate more or less with language model? I probably feel it's probably less. The agent side essentially bet on language model does the communication.

One question I have for you, just going back to the implication of RAG and you can be my brain and do my organization for me. Like, what if my brain is really disorganized? Like, do you think that this changes the amount of work people should do in systems like Notion at input, right? Like, you know, should I be designing my knowledge base in the same structured way, or can I just dump it all in stream of consciousness?

I think organization might be— we might be moving away from the organizational world. world. Why do you need to organize? Because you can retrieve. Why do you have index? Index initially are file cabinets and the little index are sitting on top of so you can find things quickly. And they're indexed based on certain names or certain dimensions. But embedding and RAG, you have semantically connection of all the things you throw into this file bag. And you can bring it out however you like. So I think we might be moving past the need for organization. That's really liberating. That means on my phone, imagine this experience. I'll have a new idea where I see a whiteboard behind me. I just take a picture or write something, dump it, and Notion is going to organize for you. Right. So then that's become my perfect memory to start. Later it could be my perfect assistant to help me do something with this knowledge. That's the vision we're moving towards. That's super exciting to me.

So you are— this is a question from Mike Verbal. We've been longtime friends with. You are a student of history. You mentioned Doug Engelbart earlier. I know you think about the transition in terms of Alan Kay and what he did in terms of simplifying many of those concepts for a broader audience around computing. Vernon's question was, what lessons in history do you take that inform your point of view of how to treat AI strategy with Notion now? From a prior revolution in computing, how does that help you decide what to do?

A lot is intuition. I think understanding history gives you a sense of history doesn't repeat itself but rhymes. So which phase are we in? I personally think we're sort of in this kind of bundling phase. Who said this? There's only 2 ways to do business, bundling and unbundling. And actually during the break I was reading a Chinese novel, Romance of the Three Kingdoms. And the opening sentence for that, it's The empire, land divided must unite, land united must divide. That's how it's always been. Business is the same way too. We're in the bundling phase. I would say the SaaS, it's sort of this unbundling fragmentation phase. If we trace back to SaaS, why is SaaS happening? In the late 2000s, mid-2000s, before that, Everything's running on Microsoft. That was like a bundling phase. Early days of PC, there are so many different applications. The first version of the WordStar, WordPerfect, different text editors, dBASE, different database software. The funny fact of dBASE, it's like they start with dBASE II because there are so many companies go bust that it sounds like if they start with dBASE II, people has more credibility. It feels like this product has been around for a while. So that's the '80s. '90s was this kind of bundling phase because Microsoft has OS layer underlying it. And the SaaS is because the web becomes good enough to run software.

Right.

Then we have this unbundling phase, a fragmentation phase. And then with the last 10, 15 years, really the money is cheap, easy to create company. There's so much, too much now feels like. There's like information so fragmented. And now the new technology happening is AI language model. And if you build more with it or just think more with it, language model wants information to be one place, wants the endpoints to be connected so it's easier to— is it hard enough to like a current version of language model to do what you want? But imagine talk with different endpoints. That's even harder, right? So, and so we're in the bundling phase because the macro, but we're also in the bundling phase because language model. I believe wants the things to be together.

I think that makes sense. I also feel like we're in the bundling phase because the nature of how founders think about their businesses shifted.

How so?

I think that it's interesting because I remember, I don't know, 10 years ago I used to argue with people about, oh, you should really buy other companies or integrate or sort of pull all these things together. And in consumer, that actually happened, right? Like Facebook bought Instagram and WhatsApp and other things, and they effectively created like a bundle of social products that they could cross-use in different ways for distribution or other things. I feel like what happened is we had a series of highly technical founders because we shifted in the Facebook era from Sheryl becoming CEO to COO. And you went from business-centric CEOs in the '90s in some cases, although there's people like Bill Gates who learned and adopted as technologists, to very technology and product-driven founders who often thought, no matter what product I build, it always has to be better. And so I can't just think of distribution as my wedge. I need to think of every product as being superior. And so I'm not going to build certain things. And now I feel like people are both building great products as well as bundling them, but also they're much more aggressive about saying it can be 80% as good, it could be 50% as good, but I'm going to have a bundle. And that's HubSpot and that's Rippling, and they have very high quality to their products. It's just they realize they don't need every single edge case and every feature as long as they're able to cross-sell.

Yeah, I think the YC school of philosophy of build one thing, use internet to find the distribution, That was, I think, overlapped quite a bit with the rise of internet and feels like there's a value to create on the other dimension, which is like you mentioned, it doesn't have to be as good, 90% as good, but because the synergy of things just make a lot easier, a lot cheaper, less tabs you open in your browser.

Yeah, it's all integrated. You have the information flow or the system of record for whatever thing that you're dealing with.

I think a lot of people also just Perhaps lack that sort of historical context, right? If you look at the strategy of companies like Oracle, right, it was very much for a decade and a half, like a dominant, at least commercially, attitude of like, okay, we're going to buy the second best product in this additional software category we want to be in, and then sell the heck out of it.

Mm-hmm.

Or trade, right? Actually, because it was very hard for customers to deploy these things, or there's just advantages to everything being attached to the same database at some point. And I do think there is some analogy to, as you said, language models because having things in the same embedding space is very useful.

Very useful. Yeah. I think there's bundling of distribution and bundling of information. What you're describing to me is more of Microsoft, more like bundling of distribution. Language model wants the bundling of data, bundling information.

So I remember hearing from Dylan at Figma early on that there was One crazy user who was in the product like 14 hours a day. It was you early on in the Notion journey being really design obsessed. I think the company has a reputation for that. Do you think of Notion as a design-centric company and is it important? How do you scale it?

I think it depends on what you mean by design. Design is to us, at least to me, it's less about how it looks. It's how the system plugs together. And then in that case, the trade-off you make, do you centralize that thing or do you decentralize that thing? Certain companies work well where certain business or product work well being decentralized, like operation-heavy company could work that way. And Notion, like I mentioned, we're sort of in the bundling business. Our value provider having this one information space, one workspace for people to do all different kinds of things. So things need to work well together. It's almost building Notion, it feels like building an operating system, building a programming language. You don't farm out to 50 people to design a programming language. Usually programming languages are done by one person. So that means the design here is very much centralized energy. So kind of like Apple, how they build OS integrated with their hardware. What is the Apple for software? doesn't quite exist today. It truly doesn't quite exist. So that's what I'm interested in, what we're interested in. So in that case means to build a good product, a good customer user experience, we need to think things more horizontally, more holistically. That means the decision-making tend to be centralized in our design team or tend to be centralized. So more Apple-like, less Amazon-like.

It's funny because when I first met you, it was just you starting Notion, and it was before you brought on Simon, and you talked about things that way even then. And I felt that one of the reasons I was lucky enough to invest or I came on board was because you had such a cohesive view of how you wanted to build software and you had such a cohesive design aesthetic. And it was your mocks, but it was also how you were dressed and how that reflected into the product. I felt like it was extremely striking. You're one of a very small number of people I've ever seen where that design aesthetic has just permeated everything in a very cohesive way. And so that's one of the things that got me excited at the time. I was like, wow, this is capturing an aesthetic that could be an incredible product platform. But you also talked about things even then, I remember, in terms of like, okay, what's the cohesive Apple-like thing that you can do for software and things?

Yeah, I think—

It's kind of amazing to see that consistent thread. So I was just stricken while you were talking by that.

Thank you. Yeah, I studied cognitive systems, cognitive science, which is kind of just like a degree for everything in some sense. It's like a little bit of philosophy, philosophy a little bit, linguistic computer science. I learned how to code when I was a kid and I did a lot of art and also in school. So try not to— there's so many things you can steal from all the different places.

Yeah.

And it's like the boundaries are sort of manmade. Then in Notion, most of our designers can code, majority of our designers, 80% of our designers can code because The moment you can, as a designer or as an engineer, you can code or you can design, you can make really interesting trade-offs. At the end of the day, technology is, at least in my opinion, it's about trade-offs. What kind of trade-off you can make that unlock new user behaviors that's valuable? But if you can do more things, you can make more interesting trade-offs that other people cannot make. As a designer, if you can code, you know how to change your design to make it easier to build. As an engineer, if you can design, you can do the same thing, almost squeeze the air bubble to whichever direction is easier to squeeze. And therefore I think being more holistic help, at least Notion as a company energy, we're trying to be holistic. It also help keep our company team very small. We're usually one of the smallest relative to our business scale because people can think, can do more, can be more holistic. And people enjoy that too because they can do more things.

Right.

It doesn't feel like They have one role, they have to be doing that repeatedly. Has a lot of different benefits, but it's much harder to find such people.

I have an important question here.

Please.

So if I think about the first office, and this may or may not be true still, Notion is a no-shoes— was a no-shoes place. Did this contribute to the company energy?

I'm Asian, so when you go home, you take off your shoes. Our first office, no shoes. It lasts us to 10-ish people. Second office, 20-ish people, no shoes. Third office, no shoes. It actually has heated floors, so even better.

Oh, very nice.

So it was all in the Mission. The fourth office, we tried to do no shoes, still in the Mission. I think I made a wrong choice in the rug. The rug kind of hard. It's a hemp-based rug, so when you step on it without shoes, With socks only, it hurts. So we decided not to do no shoes at 4th office, and so far has been stuck that way.

Yeah, Applied Intuition has socks and slippers at the front, so that way if you need the padding—

I know, but then where do you— then the question is like, where do you store your slippers? Like, it becomes stinky.

And they have to stay aesthetic.

Yes. If you come to our office, it's like we still try to be Not corporate. It's like they were trying to use the furniture that people use for homes. I'm pretty picky about what kind of furniture's in the office, ideally design classics that last 50+ years. So inspire us to build software that way. So they also made trade-offs. People who design a chair make trade-offs. They made really interesting trade-offs to solve certain problems if you know the history of it. So we try to In the office, use good software, good chairs, good lighting.

So this is back to the aesthetic point that I made earlier. I actually felt that in the offices as well, there's that ongoing cohesion. Even the music, I remember, I think it was in the second office, it was always jazz in the background and I just felt like it all kind of was this consistent vibe. So it's pretty cool. Within Notion, are you using a singular underlying LLM or are you at this point using multiple different things for different use cases? You mentioned sort of the high-level reasoning versus the Fast, cheap synthesis?

We try everything. OpenAI and Tropic are the high-end model. We want reasoning, which is we work with a high-end model. Yeah, it's kind of like everybody building different flavors of this.

Yeah, makes sense. And then as you look at it, it feels like with Notion there's a set of core templates or use cases There's things around project management. There's other types of almost applications that people have built to use. There's knowledge base related stuff. There's the things that you mentioned. Are any of those you feel differentially impacted in terms of how you think about future AI roadmap or things that will really change the game dramatically in terms of some of these areas?

Yeah, I would say RAG changes all the knowledge side fundamentally. you no longer need to organize. So the notion, one of the things people love, it's the left sidebar. The left sidebar, you can organize your knowledge base, organize your personal workspace. Maybe the future doesn't have to have that. What it's like to not fall into your own innovative dilemma to double down that UX paradigm.

Wow.

But just having a notion that you can just dump things and retrieve. That's knowledge side.

That's actually really interesting at a high level to think that everything sort of moves to a form of search over time.

Move over to search over time?

Yeah.

You don't need to self-organize information anymore in this new world. You can just create a mechanism to interrogate it.

Yeah. At least you don't organize your brain. You just dump into it. Then you wake up, oh, you remember that thing.

Yeah, it's interesting.

Oh, some people do. The art of loci, the art of memory is actually visualize your brain, but for most people it just works without any organization and magically, right? What it's like for software, we're getting there. Yeah, it's kind of fun.

Are there areas of software more broadly that you think are outside of Notion scope that you think are going to change a great deal from AI?

Wow. In some sense it's kind of a race. There is like the— we're in the— Notion is in the bundling business. We are in the bundling and front office business. Front office, my definition, our definition is what's happening in front. Imagine a 1960s office. What's in a 1960s office? On your desk you have a notepad, you write down something, maybe you have a typewriter. Then you have your binders on the left and right. That's essentially the notepad. That's your documents, your notes in Notion. Your binders of things are like your wiki knowledge base in Notion. And behind you will be the file cabinets. That's your relational database in Notion. And you have a little pushcart to put things into there. Then there's a back office where it's like the librarians organize all the things. That's Snowflake. That's the back in the days IBM. We don't touch that. We largely touch— our strength, like I mentioned, is software interface, UI/UX, which is largely what's in front of the human. We're trying to bundle this in one space. At the same time, there's also largely back-office-powered use cases. They tend to be verticalized, specific to healthcare, specific to some kind of workflows.

Manufacturing.

Very specific, but very essential to store somewhere and vertically integrate that use cases, that could be AI-fied too. And people, in fact, we see this in law, we see this in a bunch of very specialized things that people have that domain knowledge and trying to figure out how do you, instead of humans shuffling this, let language model help a lot of that. The front office type of things, it's kind of open-ended. The back office power things tend to be specific. So I think it will be a race. But the market is just so large and it doesn't, it's not zero sum necessarily.

Maybe you can talk about the market as you see it for Notion. So, you know, when you guys began, I think early adopters, startups were the first to get onto Notion for knowledge base. You're a much bigger company now. We're also in a different macro where, you know, startup budgets are less robust. Like, how do you think about the enterprise and helping the enterprise adopt AI or Or do knowledge management?

Yeah, we're still very early, not at scale yet. I would say bundling intrinsically do a lot of good things. One is you don't have to jump between different tabs to do things. Second is save your cost. We save a lot of customers' bills for their project management tool around their issue tracking tool. And that's enterprise really care about that. It's very CFO friendly today with this macro. So yeah, bundling has many good benefits besides information. There is also money.

Well, Ivan, I mean, this conversation has spanned so many interesting topics. Thanks so much for joining us today.

Thank you.

Yeah. Great to see you.

Good to see you.

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