Notion's CEO Wants You to Demand Better From Your Tools  ## Metadata - Author: [[Decoder with Nilay Patel]] - Full Title: Notion's CEO Wants You to Demand Better From Your Tools - Category: #podcasts - URL: https://share.snipd.com/episode/4d72ad2c-ff43-45ad-9ef2-c368271a051b ## Document Notes ## Highlights - **Lego Blocks Replace Point Tools** - Notion bundles many narrow SaaS tools into Lego-like building blocks. - Teams assemble those bricks to create tailored workflows and reduce tool switching. Transcript: Casey Newton We design Notion for teams. Ivan Zhao So another way to describe Notion is what we call Lego for software. Maybe it's worth explaining the intent a little bit. If you're a company for a team, you have to use a dozen different tools to get your work done. And our goal is to consolidate those tools into one box and give you the Lego blocks that power all those use cases. Not only you can do all your work in one place, but you can use those Lego to create and customize your own workflows. Casey Newton You and I have talked a fair amount about Legos over the years. What appeals to you about their design? Why is it such a good metaphor for what you're trying to do with Notion? Ivan Zhao Because it doesn't quite exist with software. Right? If you think about the last 15 years of SaaS, largely people are building vertical point solutions. And for each buyer, for each point solution sort of makes sense. The way we sort of describe it, 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 them. ([Time 0:06:47](https://share.snipd.com/snip/fe36da68-10a2-4d8a-9ea4-c6b9557acfa7)) - **Computing Should Be Malleable** - Early computing pioneers designed software to be malleable and tinkorable. - Ivan Zhao draws on that ethos to make Notion a creative, customizable medium. Transcript: Ivan Zhao Like 60s and 70s, 60s, those hippie generation who took acid in San Francisco saying, holy shit, this room size calculator, if you put a monitor in front of it, it can be an interactive Thing. It can be a new type of medium to help you think better, help you solve problems more collaboratively. That's why the first generation of personal computing, interact computing, was started in the Bay Area. And that generation of thinkers and pioneers thought about computing kind of like reading and writing. Like we went to school multiple years. Not everybody can read and write English or German, whatever language you are. It's a tool. Yes, you can be a poet, you can be writing essays, but it's a very malleable medium. So they were set out to make computing malleable and tinkorable and everybody can create their own softwares. ([Time 0:08:51](https://share.snipd.com/snip/34ecf183-ed95-42f6-923b-40dbe93e5b06)) - **Solve Fragmentation Not With More Apps** - SaaS fragmentation forces people to juggle dozens of narrow apps each day. - Notion aims to consolidate core workflows into a single, flexible platform to reduce friction. Transcript: Ivan Zhao Your daily job, I have to jump between 20 different tools to get some work done. The average company, average business use a hundred plus different tools, SaaS tools. The fragmentation is obvious, for the IT department. So there's another saying in business, you either bundle or unbundle. So notions squarely in the bundling business, our job is to bundle SaaS into one-ish productivity tool for your most core use daily needs so we can unleash the Lego block creativity For you. Casey Newton It's an interesting conversation. It makes me think of kitchen gadgets, because you see the same tension there, where there are some kitchen tools, like, I don't know, a stand mixer or an immersion blender that you can Use to make many, many different kinds of recipes. And then there's like the garlic press, which is good for mincing garlic and nothing else. And it sounds like what you're saying is by the time we got into the 2010s, productivity was just a bunch of garlic presses. And you sort of wanted to come along and say, what if we just had a stand mixer and you could make a lot of recipes with one thing? Ivan Zhao You know, a friend of mine used this metaphor, similar to what you said. Have you seen the cutters? Yes. Golly press, you can press a bunch of different things. Avocado cutter is made just for freaking avocados. You cannot do anything else. So versus in comparison, a knife, a kitchen knife is a tool that you can use for hundreds of a thousand different ways. ([Time 0:10:34](https://share.snipd.com/snip/5ed263bd-2df8-4b6d-8137-c47043fb4bb0)) - **Start With Boxes Then Tinker** - Ship curated templates so users avoid a blank page and start using your product. - Let users customize those templates so they can tinker and adapt workflows quickly. Transcript: Ivan Zhao Early Legos, you get bricks. Then later on, Lego creates a system and get boxes. And now Lego work with Marvels and F1s to create really specialized boxes, right? In some sense, Notion, as a company, we're in the middle of adding more boxes so people, they don't have to start from empty set of bricks, even with no instruction menu. You can imagine like, hey, I want a Formula One race car. I like that Lego box. When you open it, you have your car ready made for you. So you can start driving that. You play that Lego toy right away. ([Time 0:14:42](https://share.snipd.com/snip/b1800584-2d01-4687-92c1-d6dc5680134d)) - **Let AI Glue Your Workspace** - Use AI to glue building blocks together and automate workspace setup. - Deploy in-app AI to onboard customers by assembling templates and wiring workflows for them. Transcript: Ivan Zhao And then they set it up for the rest of their teammates. Casey Newton Well, that's always helpful when you can get people inside the company doing the sales part for you. Ivan Zhao And you know what? AI can do this quite well now. Because what AI is good at is gluing together the Lego bricks. AI can write in code. Writing code is just another way to gluing together your process and workflows. And our latest product is actually get AI to be this success person to help you set up your Notion workspace for you. And that's talking about another way to onboard a customer. That's a brand new way to unlock in the past year, two years. Casey Newton I will say that 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. ([Time 0:18:42](https://share.snipd.com/snip/7c9046c3-0ba7-4f05-b3eb-7c884a1fa597)) - **Profitable And Growing** - Notion remains profitable and has grown without raising new funding. - Ivan Zhao says AI-driven industry changes accelerated the company's execution strategy. Transcript: Casey Newton What has allowed you to keep growing without raising more funding? Are you guys profitable? We're profitable. Ivan Zhao So profitable, growing fast, business doing well. Nice. How does that feel? Feels good. I would say the large driver of our everyday activity is the software industry completely changing with AI. So it feels like SaaS areas, AI areas of the past two years just make the SaaS area feels like sleeping days. ([Time 0:23:23](https://share.snipd.com/snip/5db0feb3-5e96-471d-b483-cf2def6bb305)) - **Hotel Sprints To Ship Notion AI** - Ivan and his cofounder locked themselves in a hotel to build Notion AI from GPT-4. - They shipped the product roughly a month before ChatGPT published publicly. Transcript: Ivan Zhao What are you going to do with it? There's actually interesting story. My co-founder, Sam, and I got early access to GPT-4. So this is like late 2022, a little bit before everybody else. We thought everybody else get early access to this. So we thought, holy shit, because compared to GPT-3, GPT-4 is a brand new type of thing, right? It's like it has a real intelligent reasoning in it. So we lock ourselves into a hotel room for about a week, and just try to rush out the first Notion AI product. We actually launched like a month before ChaiGPD happened. It's like, we're excited about what you can do with this new type of material. ([Time 0:25:02](https://share.snipd.com/snip/3ed33fc8-6b93-4388-968f-27e39f233ecf)) - **Record Meetings, Then Summarize** - Record and transcribe meetings to create a searchable company knowledge base. - Use AI to convert transcripts into polished writeups and to catch up quickly on missed meetings. Transcript: Ivan Zhao Just launched three separate product a couple months ago, Notion AI for work, including the next version of this enterprise search product you talk about. So along with that was a launch AI meeting notes product. So all the meetings, you can record it and transcribe that. So essentially, your company has a collective brain of what's going on and you have all the AI knowledge workers on top of Notion to help you transcribe the meeting notes, answer whatever Question you may have. It's quite interesting what you can do with the technology now. Casey Newton Of all the AI features that you've added so far, which ones do you personally find the most useful? Ivan Zhao 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 I can remember later where I can use this to ask AI to turn the transcription into a writing. English is my second language, so I'm not the fastest writer. But AI can do a better writing than I can if I just dump out what I'm on top of my mind through the transcription. ([Time 0:37:48](https://share.snipd.com/snip/0f7676f7-f71b-406a-b9bd-d6d45ee3840f)) - **AI Makes Small Teams Act Bigger** - AI teammates can multiply the output of tiny founding teams by handling routine work. - Notion positions AI as an amplifier that helps startups move faster, not as a replacement for people. Transcript: Ivan Zhao So imagine the billboard we're putting out. It's you in the center. Then with a tool like Notion or other AI tools, you can have AI teammates, right? Imagine, hey, you and me start a company. We're two co-founders. And OpenNotion, SignUpNotion, and all of a sudden we're supplemented by AI or AI teammates, some taking notes for us, some triage, some doing research while we're sleeping. So all of a sudden we're a team of a company of 10 people. So then the startup can run much faster. That's the notion, that's the vision we want to push more towards the world. It's more of an amplifying force rather than a zero-sum force. ([Time 0:39:34](https://share.snipd.com/snip/b44d4748-7334-44a0-b281-77a82682441c)) - **Treat Models Like Interns** - Treat language models like fallible interns who need training, memory, and verification. - Build workflows and guardrails to earn trust before relying on AI for mission-critical tasks. Transcript: Casey Newton 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% of the time. And so if I'm relying on it for mission critical stuff, if it's one of the 10 quote unquote people at my company, and I tell it to go grab some facts and figures, and it just kind of hallucinates The wrong one, that's like really bad. Like I, you know, if that were a real worker, I would, you know, I don't know, put them on a performance improvement plan or something. So how do you think about reliability as a challenge to what kinds of services you want to offer people? Ivan Zhao It's definitely an issue and getting, I would say getting better in generally. I would say the best closest mental model is like a treating language model, just like a human, just like an intern. Human made mistakes. Your trust level, when you tell another human something, there's nothing guaranteed this human cannot mess it up or tell another person even until you don't want to. So fundamentally building trust this way, people's expectation for software is higher because software for the longest time, it's always do exactly, if there's no bugs, it's always Do exactly what you told, right? AI is a new type of software. Our expectation hasn't been set how to deal with this yet. ([Time 0:41:20](https://share.snipd.com/snip/8f09e6aa-9eba-472b-a109-de0316d92115)) - **B2B AI Needs Specialized Agents** - B2B AI must be team-first and specialized to different professional roles and workflows. - Unlike B2C, enterprise AI won't be winner-take-all; many specialized vendors will coexist. Transcript: Ivan Zhao One way to think about it on the spectrum of whether it's a more personal B2C flavor, or it's like B2B team-first flavor. I would say most labs product currently building is more of a personal assistant flavored. It can help you to do work or help you to cheat on your homework. And usually B2C, it tend to be winner takes all, or there are a few winners. And I think it makes sense for labs like OpenAI to go really hard towards that direction. Notion squarely is a B2B company. Our product, our business model is for business, other businesses. And inside B2B, there's required making different trade-offs. There's so many different subcategories. And it has to be team first to start. That's why our AI teammates, our Asian AI assistant, fundamentally live in a team space that you or the rest of your company employee live in. That's the angle we're taking. There will be, in my opinion, there will be many different winners in the B2B because B2B usually is not winner takes all. ([Time 0:47:02](https://share.snipd.com/snip/f61f32d8-1c32-4bd0-a926-74b5211b6f3d)) - **Build Software Like Brewing Beer** - AI forces a shift to iterative, experimental product development rather than fixed specs. - Ivan uses the metaphor of brewing beer: you must channel the model and massage the data, not predict outcomes exactly. Transcript: Ivan Zhao You can just expect the next 18 months from now, the next CPU can drive whatever software you do. AI sort of feels that, but even on steroids, like every three months, the next model, it's almost can do what you couldn't do before. So does it require you really change how you build software and build product and build a company? It's a of things. One is because it's constant changing, you can, and the model itself doesn't like too much restrictions. You need to build a harness just around the right places. So almost like if you build too much around the train track, the next train comes, you just make what you just build obsolete, right? You should build parallel to the train track. That's number one. Number two is like the language model are not deterministic. It's different from classic software engineer. The metaphor I like to use is like classic software engineer is kind of like building train track or building bridges. It's Newtonian physics. Everything's predictable, right? And if you can't imagine you can build it. Sometimes it takes three months, sometimes six months, but eventually you can build it, right? With this language model, I think it's squishy. It's organic. It's kind of the analogy I love to use. It's like brewing beer, right? You cannot tell the East, okay, my beer is going to taste 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. The hope the best, right? So this requires a much more of an iterative approach. You cannot come from your vision or customer need first. You have to come from what the technology gives you, what the ease, what the beer gives you. So really much allow your team to be more empirical, more experiment, less of this kind of waterfall class way of like spec to code should be more like incremental iterative. ([Time 0:52:13](https://share.snipd.com/snip/ee2a5bbe-a50c-4da8-949f-ac3fee31620b))