Hello, and welcome to Decoder! 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 that 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 a major part of my workflow for Platformer is actually built on top of Notion’s database feature. 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.

If you’ve never used Notion, you can think of it as an all-in-one productivity suite 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 what a lot of these kinds of apps do very well, and all in one package. At the same time, it allows for a pretty substantial amount of customization, which has made it popular both for individual productivity power users and for companies large and small.

But Notion started as a very different piece of software, and its evolution over the last 12 years or so has involved a fair amount of trial and error, one major reboot, and a lot of big decisions. In my opinion, what really sets Notion apart from so many of its peers is Ivan’s deep passion for design and an almost relentless drive to make products that he sees as useful and aesthetic in equal measure.

You’ll hear Ivan early on in this conversation reference LEGO: the toy bricks are the central inspiration for Notion, which employs “blocks” as a metaphor for configurable templates that allow you to use Notion in a pretty diverse set of ways. Think everything from simple notes and lists to complex databases and workflows.

But Notion, like so much software these days, is evolving. Now, the company calls itself the “AI workspace that works for you,” and you’ll hear Ivan recount in detail how the launch of OpenAI’s GPT-4 proved to be a big turning point for him and for 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 talk in depth here about his vision for AI agents that 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 so many people hope it can do down the road. So I really wanted to ask Ivan how we might get to this future he predicts, how long that will really take, and what productivity and knowledge work look like if AI delivers on some of these lofty promises.

Okay: Notion CEO Ivan Zhao. Here we go.

This interview has been lightly edited for length and clarity.

Ivan Zhao, you are the co-founder and CEO of Notion. Welcome to Decoder.

So at a high level, describe Notion for us. If listeners haven’t used it yet, what is it? What does it do?

Well, we make all-in-one productivity software. People use Notion for all kinds of things, from taking notes, collaborating on projects, managing documents, managing their knowledge base, and, most recently, we launched a calendar product and mail product. You use Notion, so you should describe what Notion is.

I think you just did a really good job describing it. I do use Notion, which is one of the reasons I wanted to talk to you, because every time I talk to a CEO whose products I use, I get to give them product feedback, which is exciting for me.

So do you see Notion today as more for teams than individuals? Is that the direction it has found?

We designed Notion for teams. So another way to describe Notion is that we call it LEGO for software. Maybe it’s worth explaining the intent a little bit. If you’re a company, for your 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 can you do all your work in one place, but you can also use those LEGO blocks to create and customize your own workflows.

You and I have talked a fair amount about LEGO over the years. What appeals to you about that design? Why is it such a good metaphor for what you’re trying to do with Notion?

Well, because it didn’t quite exist with software. If you think about the last 15 years of [software-as-a-service], it’s largely people building vertical point solutions. For each buyer, for each point, that solution sort of makes sense. The way we describe it is that it’s like a hard plastic solution for your problem, but once you have 20 different hard plastic solutions, they sort of don’t fit well together. You cannot tinker with them. As an end user, you have to jump between half a dozen of them each day.

That’s not quite right, and we’re also inspired by the early computing pioneers who in the ‘60s and ‘70s thought that computing should be more LEGO-like rather than like hard plastic. That’s what got me started working on Notion a long time ago, when I was reading a computer science paper back in college.

You wanted to make tools that would snap together the way that LEGO blocks do.

We want to make tools that amplify human creativity. LEGO are creative. LEGO are beautiful, and most software probably is not as much.

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?

No. I think it’s a misunderstanding about Notion. Notion is productivity software, that’s what we do as a business, as a product. But the ethos of this is what I just described; it’s the LEGO ethos. It’s maybe worth describing the history of the computing industry a little bit, because that inspired Notion.

In the ‘60s and ‘70s, ‘60s, the hippie generation who took acid in San Francisco thought, “Well holy shit, 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 helps you think better, helps you solve problems more collaboratively.” That’s why the first generation of personal computing started in the Bay Area.

That generation of thinkers and pioneers thought about computing kind of like reading and writing. Like we went to school for multiple years, but not everybody can read and write English or German or whatever language you speak. Writing is a tool. Yes, you can be a poet, you can be writing essays, but it’s a very malleable medium.

So, they set out to make computing malleable and tinkerable, and everybody could their own software. Then, in the ‘80s, the Bill Gates and Steve Jobs generation took computers to the mass market and put a computer in every home, on every desk. They sort of froze computing into this application format. If you think about applications, each application is kind of like a mini-prison of computing. You cannot change it that much. There are application makers who are engineer programmers, and then there are application users who are like the rest of us, the people who use productivity tools every day.

So when I was reading those papers about those ‘60s and ‘70s people, I thought, “Holy shit, the world that we’re living in is like a prison-like world.” If anything, the SaaS of the past 15 years has been for even smaller prison cells, as each application can only do a tiny slice of things. So, that doesn’t make it right for me, and the customer feels the same way. It doesn’t make sense that for your daily job, you have to jump between 20 different tools to get some work done. The average company or average business uses 100-plus different SaaS tools. The fragmentation is obvious, even for the IT department.

So, there’s another saying in business: you either bundle or unbundle. So, Notion’s squarely in the bundling business. Our job is to bundle SaaS into a one-ish productivity tool for your core daily needs, so we can unleash LEGO-like creativity for you.

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 the garlic press, which is good for mincing garlic and nothing else.

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?”

A friend of mine used this metaphor, similar to what you said. Have you seen avocado cutters?

An avocado cutter is made just for freaking avocados. You cannot do anything else. In comparison, a kitchen knife is a tool that you can use hundreds or thousands of different ways. You, as a human, amplify it because you have a technique. So, to create software that’s more like a kitchen knife, or LEGO, that’s what interests me, and interests us as a company.

But you can’t blame the industry, because if you think about it — if you rewind back before SaaS — the world was running on Microsoft Office for a good solid 10 to 20 years. SaaS, with the internet as its distribution, allows new businesses to be created. The natural way to go about distribution and new businesses is to find a really precise solution, creating those avocado cutters and garlic presses, and you can find buyers on the other side.

So, as we move into today, do you think of yourself as competing directly against Microsoft Office or Google Workplace? Is the vision that big, or is it something different?

We coexist with them, as most of our customers are still using Google Workplace or Microsoft Office. They use their identity service, they use their mail and calendar apps. We have a mail and calendar product currently as a client. A startup can fully run on Notion. You don’t need to use Microsoft 360 or Google Docs, but it’s not as mutually exclusive.

Our sweet spot is more on the things that you need to put in a database. Another way to think about it is like, what is Microsoft Access but for the 2020s, and AI native? Most SaaS is kind of like a relational database, storing some kind of system record of your company, and one workflow on top of that. That’s the part that neither Microsoft nor Google touches today.

There are spreadsheets, but there are not many database use cases. We want to consolidate and commoditize that, and give people the LEGO of those database use cases, such as project management and ticket tracking. Some companies use them for CRM, or managing application trackers. For reporters, you can manage all your leads and the stories. Those are database use cases.

Right, 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’ve talked 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 Notion is meant to do?

Yeah, like early LEGO, you get bricks. Then later on, LEGO created systems and boxes, and now LEGO works with Marvel and F1 to create really specialized boxes. In some sense, Notion as a company, we’re in the middle of adding more boxes, so people don’t have to start from an empty set of bricks, with no instruction manual.

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 ready-made for you, so you can start driving it. You play with that LEGO toy right away. But if you don’t like certain parts of the cars, because they’re made from LEGOs, you can change them. That has always been our philosophy, and we’re doubling down on this approach because it works.

Interesting. I feel like a key challenge that some of the other big productivity tools like Microsoft 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 percent 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, menus, and widgets. Can Notion avoid that? And have there been times when you’ve worried you might be there already?

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 the hard plastic way. We’re taking a more LEGO approach, so adding the brick, and the brick can be used for different things. In some sense, this is a much better approach.

Got it. So, trying to offer fewer discreet, very narrow features, and more abstract features that can be extended in various different ways.

Like LEGO systems, on one end can be toy cars, and on the other could be Barbie dolls, more or less using the same bricks. If you look at the most common productivity tool, if you just put your designer mind on that, there are 20 or 30 pieces there. There’s some kind of table, some kind of relational database feature, some charts, some commenting, page editing, and collaboration.

Those 20 things are core to all collaboration and knowledge work. So, we try to do our best job to make them friendly, approachable, and break them into pieces, and give them to you, either as a piece or as a part of a package.

What bricks inside of Notion are most popular today?

We start with bricks around documents and knowledge bases. We’re famous for our block-based editors, and that’s from the early days. That’s like 2019 into 2020. And then databases are our most important brick today, because, like I mentioned, most knowledge work is just fancy file cabinets in the cloud. Knowledge work runs on file cabinets, and databases are the heart of that.

Yeah, the database is my number one Notion brick that I use. So that makes sense to me.

People don’t discover that [easily]. We need to do a better job of getting people to understand its power. It’s essentially what an engineer does every day is wire together a relational database with views on top of that. How do we democratize that? That’s our purpose.

Well, it’s interesting, because if I had never heard of Notion, and you came to me and you said, “Casey, you should build a database to solve this problem,” that’s like telling me that I should add another room to my house. I don’t know where to begin. I feel like I need to call somebody and ask for help.

But in practice, you click a couple of buttons, and in my case, install the Notion Web Clipper, and I’m well on my way to having a database. So, 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.

Yeah, not every kid grew up liking LEGO as their number one toy. I think Notion resonates the best with people who like to build, and they tend to be entrepreneurs, tech people, and the spreadsheet gurus in each team. They like Notion, and they set it up for the rest of their teammates.

That’s always helpful when you can get people inside the company doing the sales part for you.

You know what? AI can do this quite well now, because what AI is good at is gluing together LEGO bricks. AI can write code. Writing code is just another way of gluing together your process and workflows, and our latest product essentially gets AI to be this successful person to help set up your Notion workspace for you, and that’s another way to onboard customers. That’s a brand new way to unlock that we’ve added in the past year to two years.

I will say that it has been very powerful for me in a lot of different products. Being able to use the in-app AI to say, “How do I do this?” And actually getting an answer. As somebody who has spent a lot of time in help menus over the years, digging around and not finding what I was looking for, that has been super useful.

And it’s not just helping by teaching the human to do it. More and more, AI can just do it, right?

That’s the biggest difference, actually. If you think about what’s happening in software right now, software is largely people providing the tools for humans to use, and more and more companies are realizing, “Wait a second, we have this new thing called a language model. It’s like a human mini-intern in a box, and we should design our software to teach AI how to use it so humans can ask AI to do the work and use the tools, and humans can do way more things with it.”

I want to ask you some of the Decoder questions that Nilay 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 profitable?

We’re profitable. So, profitable, growing fast; the business is doing well.

Nice. How does that feel?

It feels good. I would say the larger driver of our everyday activity is the fact that the software industry is completely changing with AI. It feels like the AI era of the past two years just makes the SaaS era feel like sleeping days. It’s a bigger driver of our execution strategy than just running a profitable business.

I’d like to hear more about how that is working. Is it the case that executives see AI changing various workplaces, and 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 just now seeing them build features, which are then drawing in new customers?

I would say customers are lagging behind at the moment. Most people don’t know. It happens with every new technology. You don’t know what to do with it. The customer is not going to tell you. It’s the people who play with this, build things, and maybe have an imagination a few years into the future, or even a few months in the future, at this point. AI is changing so fast. So a lot is from ourselves, just playing with AI and realizing, “Holy moly, this is a very different thing. You can solve problems that you couldn’t solve before with classic software.” Now, what are you going to do with it?

There’s actually an interesting story. My co-founder, Simon Last, and I received early access to GPT-4. So this is like late 2022, a little bit before everybody else. We thought everybody else would get early access to this. We thought, “Holy shit,” because compared to GPT-3, GPT-4 is a brand-new thing. It’s like it has real intelligent reasoning in it. So we locked ourselves in a hotel room for about a week, and just tried to rush out the first Notion AI product. We actually launched a month before ChatGPT happened. We were excited about what you can do with this new type of material. That’s for Notion, that energy comes from there.

How many employees do you have over there? How big is Notion today?

High three digits. So, 900, maybe approaching 1,000.

How do you think about company size? Do you see a world where there are five times that many employees? Or do you want to keep it somewhere around where it is right now?

I think there’s no right answer for the absolute number, but there’s an answer for the density of the talent. The denser the better.

You like having fewer, but more talented people as opposed to more people?

I like to have fewer, if we can do the work with fewer people, and there’s less communication overhead. People have more ownership, and people can work things across boundaries. That’s just better overall. The company moves faster. The small car can turn corners much better than a big car, and we always call Notion a small bus. We try to keep the bus as tight as possible.

What’s your org chart? How is Notion organized?

Fairly classic. It’s me and my co-founders, Simon Last and Akshay Kothari. Simon is still coding every day. Akshay runs our product and design org and research. Our chief technology officer, Fuzzy Khosrowshahi, runs all of the engineering. Our chief revenue officer, Erica Anderson, is responsible for sales, marketing, and consumer experience. And we have our chief finance officer, Rama Katkar, and general counsel, Hasani Caraway. That’s our classic org chart.

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.

Classic company divisions and high-quality people keep the bus tight. So that allows you to be profitable.

How do you make big decisions? Do you have a framework you use? Or is every decision different?

Well, there are the typical one-way doors and two-way doors. With a one-way door, you try to move fast, and with a two-way door, you think a little bit more carefully and sleep on it. Those are thinking fast and slow types of things. I’m pretty detailed. I like to work on the notes, so there’s a certain problem I’m good at. Personally, it gives me energy, and I’m interested in working on the ground in the trenches with everybody.

There are certain parts, though, like I cannot run our finance team. Our CFO, Rama Katkar, is really amazing. She takes care of that. But for certain things — like design and product, engineering, marketing, and branding — I like to get involved.

You’ve always struck me as a product CEO. 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 the market opportunity, or something like that.

I built Notion because I wanted to build Notion, not because I wanted to start a company or business. I wanted this thing to exist.

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 Notion, 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?

Well, you have to, otherwise you die, right? At that point, it was like, “We’re building on the wrong thing, the wrong foundation,” and you know what the right thing is, but it’s just going to take you maybe a year to a year and a half to build the right thing. We were a company of about five people, and we were going to run out of money.

The only way to do it was to shrink it back to just me and my co-founder, Simon. So, we started over. Japan is a good place because it is inexpensive, and we have never been there. It was interesting, and we could just focus on building.

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 going to take a year. I’ve already put a year and a half or so into this app. I gave it everything I had. It didn’t work.”

What was it that made you say, “No, we’re going to keep going on this. We think that there is a vision here that we can actually achieve”?

The goal was never to start a business, like I mentioned. The goal was to build this thing, and the thing didn’t quite exist. Notion is one of the few bundling, consolidating software productivity tools out there, and it didn’t quite exist at the time. Software for LEGO doesn’t exist. So if I started a company, I wanted to do the same thing. Why don’t I just reset and go back to Simon and me so we can stretch the money a bit longer?

Actually, I just got back from Kyoto last week, where there was a tech event, and the Kyoto mayor and I did a fireside chat and talked about this story. They wanted to talk about using Notion as an example of how we can blend tech and Kyoto’s craft tradition. Because we’re also inspired a lot by the craft people in Kyoto, how they dedicate their time to building something, and not just for money or fame.

That is so crazy. I was actually in Kyoto last week, too. I was on vacation and went there for the first time, and I had an incredible time. Kyoto’s amazing.

You get the sense that it’s a little bit slower pace. People care about what [they’re making], right? People truly care. That’s the thing. It’s the main thing. It’s not the business, it’s not their other surroundings.

Oh absolutely. I mean, you go to these temples that are 1,000-plus years old, and the care and the craftsmanship that they put into them is truly inspiring. It’s deeply beautiful. It’s very connected to their spirituality, and their religion, culture, and history. So I could understand why a founder would go there and take a lot of inspiration.

Yeah, because it’s a bit slower too, you can focus on virtual spaces, on computers.

Yeah, it’s not like San Francisco, with our go-go nightlife, our Waymos, the party scene, all of that.

Or New York, even, even more of that.

One more of these. This isn’t strictly a Decoder question, but it spiritually feels like a Decoder question that I wanted to ask you. What is the best productivity tool that you use that is not made by Notion?

I like those chatbot products: ChatGPT, Anthropic’s Claude. It’s quite amazing, especially when talking about features, like the conversation mode. I love those. I like to learn from them.

The voice mode, yeah. It helps me learn a lot of different things. When I’m making coffee and waiting for the water to boil, I can just talk with this thing for a little bit, like for two minutes. It’s perfect.

What do you ask it about? What do you like to learn about?

Oh, all kinds. What’s most recent? In Japan, I was reading a book about Marshall McLuhan.

Yeah, media theorist and theologian. Many of his concepts are hard to interpret, so it’s better to just work through them with a language model that will help guide you. It’s the best tutor, truly. Education should be very different. Hopefully, it will be very different a few years from now.

I think so. This isn’t quite a tutoring use case, but I just have to say, when I was in Kyoto last week, we were in the neighborhood and had some time to kill, so I just opened Google Maps, and it sort of opens to where we are, and I took a screenshot. I just sent it to ChatGPT, and I said, “Tell us a bit about this neighborhood.”

It gave me a history of the neighborhood. It told me about the cool restaurants, cool coffee shops, a museum, and places that we could walk to. I mean, 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. It was wild to me.

Yeah. One use case I have, if I go to a famous architectural building, is that I say, “Hey, I’m at this place, tell me about it. I’m looking at this part, a corner of this building. Tell me more about why that is 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.

You can just take a truly guided tour, and you don’t need another person; you’re just talking with your machine.

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?

If you think about our strategy during the SaaS era, it’s bundling and consolidating a bunch of different tools for knowledge work into one place. What’s changed in the past couple of years is that it now has all that soft knowledge of LEGO in Notion; you can not only provide the tools, but you can also assemble them as your AI teammates. They can do the work for you.

We are fortunate to have that knowledge work LEGO in one place so you can piece it together in a very interesting way. Because one end can take notes for you, the other end can help you manage, triage projects, and write documents. Those are basic things, but more and more, with more LEGO and smarter models, you essentially hire Notion as your AI teammate. That’s the future that we’ve been building, or building more toward.

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 taking notes about various meetings. 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.

I thought, “That’s super interesting.” 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.

We just launched three separate products a couple of months ago, like Notion AI for Work, including the next version of this enterprise search product you’re talking about. So, along with that was the launch of our AI Meeting Notes product, so all your meetings can be recorded and transcribed.

So essentially, your company has a collective brain of what’s going on, and you have all the AI knowledge workers on top of Notion to help you transcribe the meeting notes and answer whatever questions you may have. It’s quite interesting what you can do with the technology now.

Of all the AI features that you’ve added so far, which ones do you personally find the most useful?

I use AI meeting notes. Almost every meeting, except this one, I record, and I use that for meetings so I can share notes with other people. I use it for myself, as a starting position to dump my thoughts. And so I can later remember to ask AI to turn the transcription into writing. English is my second language, so I’m not the fastest writer, but AI can do better writing than I can if I just dump out what’s on the top of my mind through the AI transcription feature.

That’s really interesting. 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?

We’re actually putting out a campaign about this, in the coming weeks or months. We want to push out a more amplifying, positive message about what Notion 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. Imagine that you and I start a company. We’re two co-founders, we sign up for Notion, and all of a sudden, we’re supplemented by other AI teammates, some taking notes for us, some triaging, some doing research while we’re sleeping.

So, all of a sudden, we’re a team or a company of 10 people. Then the startup can run much faster. That’s the vision we want to push more towards the world. So, more of an amplifying force, rather than a zero-sum force.

What timeframe do you think that arrives? 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?

From someone who’s building with this every day, I think the capability is pretty much there. There are different spectrum complexities of knowledge work. The model is quite smart. I would say what’s lacking is the plumbing, the toolings that unlock the capability of the model. That’s essentially what Notion is doing, with the LEGO blocks being the plumbing and tooling. So, that’s one constraint.

The other constraint is just how people use it, and how people plug it into their workforce. Bureaucracy is sometimes a good thing, and sometimes it’s a bad thing. In this case, I think it’s actually a good thing, because it slows things down a little bit. It gives people the time to adapt and to learn with this new tool. I think it’s good. So, the capability is more or less there, and if not, every three months you get a new one. The trends just keep coming, right?

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 100 percent of the time. So, if I’m relying on it for mission-critical stuff, if it’s one of the 10 “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 really bad.

If that were a real worker, I would, 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?

Yeah, it’s definitely an issue, and I would say it’s getting better in general. I would say the best, closest mental model is treating the language model just like a human, just like an intern. Humans make mistakes. Your trust level, when you tell another human something, is that there’s no guarantee that this human cannot mess it up or tell another person, even though you don’t want them to, right?

So, we’re finally building trust this way. People’s expectations for software are higher because software, for the longest time, was always exact — there are no bugs. It always does exactly what it’s told. AI is a new type of software. Our expectation hasn’t been set on how to deal with this yet. I think as more people get used to it, as we change our habits around it and companies change their workflows around it, I think we’ll find an equilibrium that’s amplifying the better part of this technology and dealing with its shortcomings.

Yeah, I think the podcaster, Dwarkesh Patel, said something like, “An AI today is better than an intern on day one, but worse than an intern on day five.” Because on day one, they have all the knowledge of human history, and they can sort of dazzle you with their capabilities.

But also, they have trouble learning, and it’s hard to 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, when is the point when an AI is better than that day-five intern?

I think all companies, including Notion, are trying to figure out techniques to inject memory and learning into this “intern.” In the coming quarters, you will see products with this baked in.

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?

Similar to the campaign I just talked about. A couple of months ago, we launched Notion AI for Work. It has AI meeting notes and deep research to help you draft documents. For the upcoming product, you can actually now imagine each one is an AI intern and can do a specialized thing, right? With the upcoming product, you can actually create different flavors of AI interns, AI teammates, that live with you in your workspace. That’s as far as I want to share. Well, you’ll see more soon. And Notion AI can do everything you can do, everything a human can do.

I like the sound of that. Let me ask you about my product request, and you know this request, because I’ve had it for a while now. Basically, when you first started adding AI features into 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. It would be so useful for research and brainstorming columns.

At the same time, it’s hundreds of thousands, maybe millions, of words. It’s not the sort of thing that you could easily throw into a context window and just let me have that conversation. So, my question, Ivan, is where are we on this dream of mine?

To be able to have a conversation with all your thousands of articles in Notion?

It is probably already there, because the techniques have been invented. You’re correct that you don’t have to fit everything into a context window. You can index everything, embed everything, and piece information out as you need it. There’s another technique that’s been popular in the past year or so, called tool use. It essentially teaches the language model, your agent, to know how to use search.

So, if you have a question that’s not in the context window initially, the agent can go there, just like a human can, to find more information about it. It will take a little bit more time round-trip, but eventually, it will give you what you want. So, new techniques will make the use cases you’re describing better.

I like the sound of that. And you do have an Ask Notion feature already that I imagine can access some element of what I’m talking about, and a lot of this stuff is just sort of on the web, so there are other ways of accessing it. But I just always think, “Man, if I could have a lightning fast way of just chatting with this database the way I would chat with a coworker, that’d be super cool.”

Oh, it should already be in your Notion workspace. Happy to walk you through the new enterprise search we just launched. It’s perfect for that.

Okay, great. All right, we’ll troubleshoot that offline. OpenAI has come up a couple of times today. You work closely with the company. Recently, it announced that 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?

Yeah, one way to think about it is on the spectrum, whether it’s more personal, business-to-consumer flavored. Or it’s like business-to-business, team-first flavored.

I would say most AI labs’ products are currently more personal assistant-flavored. It can help you do work or help you cheat on your homework. Usually, B2C tends to be winner-takes-all, or there are few winners, and I think it makes sense for labs like OpenAI to go really hard in that direction. Notion squarely is a B2B company. Our product, our business model, is for other businesses, and inside B2B, you’re required to make different tradeoffs.

There are so many different subcategories, and it has to be team-first to start. That’s why our AI teammates, our AI agent and AI system, fundamentally live in a team space that you or the rest of your company’s employees live in. That’s the angle we’re taking. In my opinion, there will be many different winners in B2B AI, because B2B usually is not winner-takes-all, and you need to make very different tradeoffs.

That’s interesting. I’m still not sure I totally understand. Say a bit more about what this business-to-business AI world looks like, and why it is that it will have many winners, whereas business-to-consumer maybe doesn’t?

Well, you can think about it in the professional setting. So if you think about all knowledge work, it is lawyers, accountants, programmers, and customer support, and they’re all different. They require you to make a little bit of a different trade-off; that’s a different type of AI agent. You can already see this in the first-generation AI agent. They need to be specialized and need to plug into different contexts.

On the consumer side, you just want to chat with your AI chatbot. It’s very universal. That’s why on the B2C side, in the previous generation, there were iPhone and Android. There are two things, largely, and in the B2B SaaS world, there are thousands of different companies and hundreds of different categories. So, whether it’s a software or AI product, you have to make very different trade-offs. You cannot be an airplane and a submarine at the same time, right? That’s why in the professional setting, you see a lawyer agent and a financial agent, and they behave very differently. They need to behave very differently, compared to your personal assistant that you wake up to every day and can chat with.

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 resource-hungry tools into your existing subscription?

We actually recently merged AI into our main plan, because more than half of our sales are now from customers who want to buy our AI product. So, it makes sense to just simplify the pricing buckets, to just include AI into everything. It does make the margin not as good as pure SaaS, but no. It’s so powerful, and people appreciate it. And still, the company is cash flow positive, so our CFO loves that, despite it being a different margin profile.

We’ve already seen some companies move toward usage-based pricing for AI, which, as a consumer, I hate. I don’t want to make micropayments to ask ChatGPT a question, but it does seem like that is maybe a better business model. What do you think about the tradeoffs there?

I don’t think people have figured it out, especially in the business setting. The first generation is kind of like customer support. With customer support, you can try to map what they call outcome resolution-based pricing. That makes sense. Then there’s sort of the second generation, which is out right now, and that’s coding. With coding, there’s a seat base, but if you use a lot, you have to go to usage-based pricing. That sort of makes sense, because through exchange, it is a piece of work. You get your file, you get your software at the end of the day. So people appreciate that, and it saves programmers so much more time than actually writing the piece of software themselves.

Knowledge work is nebulous. With knowledge work, you can’t put a price on it. It’s this chunk of a doc, but how much is it worth? You can’t really quantify that. And how good is a piece of knowledge work? How good is your product spec? You can’t put a dollar sign on it. So, it’s much harder for a general-purpose knowledge work product like Notion. That’s the thing, the whole industry needs to figure it out.

That’s really interesting. What do you wish that AI would make possible in Notion that isn’t quite possible yet?

You can always get cheaper, faster, and smarter, but you know the train is coming in that direction, so it does require you to build a company in a different way. I think this is what the software industry is realizing right now.

I never worked during the dot com era. That was a little bit before me. People say that during that era, the web standard changed all the time, every couple of months, or every three months it’s different. And there was Intel and the Moore’s Law era, where you could just expect that 18 months later, the next CPU would drive whatever software you wanted.

AI feels like that, but on steroids. Like every three months, the next model can do what you couldn’t do before. So it does require you to really change how you build software and build products, and how you build a company. A couple of things: One is because it’s constantly changing, and the model itself doesn’t like too many restrictions; you need to build a harness just around the right places. It’s almost like if you build too much around the train track, the next train comes, and you just made what you just built obsolete, right? You should build parallel to the train track. That’s number one.

Number two is that the language model is not deterministic. It’s different from classic software engineering. The metaphor I like to use is that classic software engineering is like building train tracks or building bridges. It’s Newtonian physics. Everything’s predictable, and if you can imagine it, you can build it. Sometimes it takes three months, sometimes six months, but eventually you can build it, right?

With this language model thing, it’s squishy and it’s organic. The analogy I love to use is like brewing beer, right? You cannot tell the yeast, “Hey, my beer is gonna taste like this. Please ferment yourself. Become like that.” You have to channel what’s in the model. The best you can do is create an environment, massage the data, massage the context, and then hope for the best.

So, this requires a much more iterative approach. You cannot come from your vision or customer needs first. You have to come from what the technology gives you — what the yeast, what the beer, gives you. So, really allow your team to be more empirical, more experimental, less of this kind of waterfall, classic way of specing to code. It should be more like incremental, iterative. All those add together and force you to design, engineer, and develop products differently.

Does it change the way that you hire? Does it change the way that you structure teams? How does that strangeness that you describe translate into a different company?

People need to be more okay with ambiguity. People need to love ambiguity. People need to be more experimental. The boundary between roles is going to be even greater. Like at Notion, we’d hire a designer who can code, because if you’re an engineer and designer in one, you can think a lot more ambiguously, more fluidly, right?

AI time pushed that even further, because the design and product sit side by side with engineers. Oftentimes, what you want cannot be built, so you have to really try a bunch of different things. That’s why you see a lot of product demos get to like 60 to 70 percent, but never become a real product. That’s because it’s good for making demos, but to get to production B2B software, you need to be really good. You need to be reliable. Oftentimes, you never get there.

I think about this a lot in the context of these voice-based assistants. What I mostly use them for is setting a timer or asking what the weather is, these very deterministic things. And the companies that are building [voice-based assistants] are trying to integrate these new AI-based backends. But 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 100 percent of the time to like 93 percent of the time, that’s a much worse product.

But I think as humans, we all learn what this type of technology is best at. It’s when you’re having a conversation, like when using the voice mode, that you want it to be ambiguous. You want it to go to different places. That’s a feature, not a bug. I think we — as a whole industry making software with AI, and we as an audience who use it — haven’t figured out the stance yet. It will take some time to figure this out, like the best material to use.

Well, I want to end just by asking what you think Notion looks like a little bit into the future. 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?

I think, to go back to what we just talked about, that the nature of software is changing. It’s changing and evolving from just a set of tools to this organic matter, to a tool that can do some work for you, right? The heart of this company is in SaaS software. The classic software era allows people to build tools, to allow people to use LEGO to create whatever tools they want.

Because the nature of that software is changing, what we care about allows you to 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 are a lot of implications. The next generation of builders is going to run a company very differently — and I care about solving that problem.

All right, well, Ivan, thanks so much for joining me today.

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