The Exchanges

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

A I don't think people want to build more applications. What got me started in Notion, got us started in Notion, it's, um, last year at college, I read a paper by, ah, one of the computing pioneers, Douglas Engelbar, ah, He talked about his papers named Augmenting Human Intellect. So every day we use software today, very much like application. When you go into one application, do one thing. But for that generation of computing people in the sixties, seventies, eighties, computers are a lot more, software are a lot more malleable. You can actually tinker and modify, right? Small talk. You can go into it and change how the operating system works on the fly. Um, 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. Um, the hard lesson for us is like, 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, my project, perfect knowledge base. They both ask for something, they just have to get that work done. Right? Um, so the, in some sense, our learning and pivot is instead of giving people those, um, Software building tool, we have to package the software building blocks together as ready…

AI assessment note: “I don't think people want to build more applications.”

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

A Right. Essentially, everything you put in Notion, Notion can help you remember. Right, and this is not just apply to Notion, it really apply to most RAC systems. Like, why do we use computer? We need to store things and need to recall things. Before language model and RAC, the recall largely happened based on keywords, right? You had the keyword has to be precise, or there's some lexical tech tricks that you can like recall easily, um, uh, imprecisely. What RAC happens, 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, right? That's probably more than 50% knowledge work. Right. We're still perfecting the system. I think we're one of the first on the market that apply at scale. We still have a somewhat a waiting list because it's hard to do this at scale still. Um, but for a company, for a team, before searches to one of a weaker point, but with the Rack, you completely changed that. I changed how I use Notion. I can just ask a question to Notion, like, um, how large, when are we moving out of the SF office to a…

AI assessment note: “I can just ask a question to Notion, like, um, how large, when are we moving”

Q So for someone who thinks on, you know, um, span of, like, decades of, you know, what should computing look like and what were, um, what were the most ambitious plans for personal computing, you know, uh, three, four decades ago, like, what are you most excited about seeing from AI broadly over the next decade?

A I think three, four decades, a bit too long. If AGI happened that time, like, computing might not be necessary. For this decade, I think one sleeper category is the, the drag, the embedding space. Decades might be too long. I was saying that in the next year or two. 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, uh, we use keyword based search where you find your coworker who remember that. That queue, 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 like the agent, the workflow side, that has a lot of buzz already. So that's interesting too.

AI assessment note: “For this decade, I think one sleeper category is the, the drag, the embedding space.”

Q dramatic to think we've been living in a prison of SAS fragmentation for the last two decades, It's actually, um, uh, you know, surprising to hear eight points of view that is so obvious, which is of course we want one tool where the data was interconnected. Why do you think people, um, why do you think more people don't try that to have unified tools and unified data underneath?

A I think people try for different angles, like even fairly recently, there's this thing called no code, right? No code is like coming from this kind of like power user developer angle of wouldn't be nice. Everybody can modify this underlying software they use every day. That's why I go there. 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 the betting space wants to be one place. Wouldn't it be nice in one place, right? And the macro is also come from the, ah, the budget place. Wouldn't it be nice rather than pay for five different vendors and all seed-based business just to pay one vendor and save some money? So there have different angles from different times. Um, 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, you know, English and Chinese. We've spent years to do that. We all know how to do that. The world, the same Mac book for most people are, are very rigid as I'm more like a machine to do typewriting or watching YouTube. Uh, not much more beyond that. It's not very creative, right? Um, wouldn't be more nice than more people can use their software more creatively, right? Because there's a separation between people who can make software and people …

AI assessment note: “I think people try for different angles, like even fairly recently”

Q in terms of like Alan Kay and what he did in terms of simplifying many of those concepts for like a broader audience around computing. Vernal's question was, what lessons in history do you take that, um, inform your point of view of like how to treat AI strategy with notion now? Like from a prior revolution in computing, you know, how does that help you decide what to do?

A Um, a lot of intuition. I think understanding history give you a sense of history doesn't repeat itself by rhymes. So like, okay, which phase are we in? Um, I personally think we're sort of in this kind of bundling phase. Like, um, um, who said this? Like, there's only two way to do business, bundling, unbundling, right? And, uh, actually, there, the during the break I was reading, uh, Uh, Chinese novel, uh, Romance of the Three Kingdoms, and the opening sentence for that is, uh, the empire long divided must unite, long united must divide. That has always been. Business is the same way too, right? Um, we're in the bundling phase. I will say the SAS, it's sort of this unbundling fragmentation phase. If we trace back to SAS, Why is that happening? In the late 2000, mid 2000, before that, everything's running on Microsoft. That was like a bundling phase. Early days of PC, there's so many different applications. The first version of the, the worst are world perfect, different text editors, D-base, different database software. The funny fact of D-base, it's like they start with D-base too, because there's so many company go bust that it sounds like if they start with D-base too, people has more credibility. It feels like it just This product has been around for a while. So that's the eighties. Nineties was this kind of bundling phase because Microsoft has OS layer underlying it, and…

AI assessment note: “I personally think we're sort of in this kind of bundling phase”

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

A Well, um, in some sense, it's kind of a race. There is like the, we're in the notions in the bundling business, where are, um, We are, ah, we're in the bundling and front office business. Front office, my definition, our definition is what's happening in, like, imagine a 19 sixties office, right? What's in a 19 sixties office? On your desk, you have a notepad, you write on something, you maybe have a typewriter, um, then you have your binders on the left and right. That's essentially, the notepad is 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, right? And you have a little push card to put thing into there. Then there's a back office, where it's like the librarians organize all the things and that's snowflake, right? That's the back in the days IBM. We don't touch that. Uh, we largely touch our strengths. Like I mentioned, is software interface, UI, UX, which is largely what's in front of the human. We're trying to bundle in this in one space. At the same time, there's also largely back office power use cases. They tend to be verticalized, specific to healthcare, specific to some kind of workflows. It's very specific, but it's very essential to store somewhere and the vertical integrate that use cases. Uh, that could be AIFI too. And …

AI assessment note: “back office power use cases. They tend to be verticalized, specific to healthcare”