n8n CEO Jan Oberhauser on Building the Universal AI Automation Layer

When the AI wave hit, n8n founder Jan Oberhauser faced a critical choice: become irrelevant or become indispensable. He chose the latter, transforming n8n from a simple workflow tool into a comprehensive AI automation platform that lets users connect any LLM to any application. The result? Four times the revenue growth in eight months compared to the previous six years. Jan explains how n8n’s “connect everything to anything” philosophy, combined with a thriving open source community, positioned the company to ride the AI automation wave while avoiding vendor lock-in that plagues enterprise software. Hosted by George Robson and Pat Grady, Sequoia Capital Mentioned in this episode: Model Context Protocol (MCP): Open protocol that lets AI models safely use external tools and data that is used extensively by n8n for orchestration. Vector database: A database optimized for storing and searching embeddings. These “vector stores” can pair with LLMs for retrieval-augmented workflows. Granola: AI productivity tool mentioned by Jan as a recent favorite. Her: A film that Jan says, “a few years ago, it was sci fi, and it’s now suddenly this thing that is just around the corner.”

• 0:00Speaker 00

  What is the stack that you see people using with N8N? Actually, quite diverse. I think it's actually obvious makes sense because the nice thing about that system like N8N is you can actually connect everything to anything. Means like, there is probably not kind of this default stack people are using, like, they use literally any LLM, they use any kind of memory or vector store, or any kind of applications, etc. That's the thing that makes anything great, because I don't know what LLM is going to win the race. In the end, who's going to be the best one? If it's going to be one of, it's going to be a million different ones, it's going to be a small one, a big one, I have no idea. But that's the great thing about N8N is like, we don't have to care, because the nice thing is you can use whatever is best for your use case. And I think that is what makes it so powerful.

• 1:00Speaker 01

  Today, we're joined by Jan Oberhauser, founder and CEO of N8N, who is one of the most remarkable growth stories in the automation era, quadrupling revenue in eight months after six years of steady building. What makes this breakthrough particularly compelling isn't just the explosive numbers, but the strategic pivot that made it possible, transforming from a workflow automation tool into an orchestration layer for AI-powered applications. Jan discusses the counterintuitive marketing strategy that abandoned lead generation to focus on community adoption, the delicate balance between serving free users and enterprise customers, and why he believes horizontal platforms will ultimately win over vertical AI applications. He also shared how their open source ethos informs how they prioritize

• 1:45Speaker 01

  what to build and how to package it, and the importance of fair code usage in commercializing their technology. Jan's vision for N8N is to become the Excel of AI, the default tool people think of when building anything AI-related. He reveals why empowering builders at the bottom of the market may be the key to capturing enterprise customers at the top, and why the future belongs to those who can connect everything to anything in an increasingly fragmented AI ecosystem. Enjoy the show.

• 2:14Speaker 01

  So Yan, hello and welcome. Thank you for joining us. We've been in business together for a long time. I think as far back as 2020, so the early days of N8N. So we're grateful for you, you know, being with us and sharing some of the perspectives. I thought maybe a good question to kick off with is just to share a little bit about the last eight months of really N8N's history. It's been incredible run. You added, I think, four times the revenue in the last eight months. And it took the first five or six years to really achieve in the company. So the business is really ripping. What happened? What changed?

• 2:44Speaker 00

  First, thanks for welcoming me here. Great to be here. To answer your question, what happened? I think it's, and it comes down to things that we actually did quite a few years ago, actually almost true by now. And I think it's, there's been two things. One was obviously our focus in AI. It's like when this whole AI wave started, we kind of, honestly, we were worried a little bit at the beginning. And we weren't sure what does it really mean for us. And we knew it's probably gonna be one of two things. It's either it's gonna be a huge opportunity or actually the demise of the company. We obviously want to be very sure it's gonna be one and not the other. Then we kind of looked at the market as like, what are other companies doing?

• 3:27Speaker 00

  And what the most companies did is they kind of added nice AI features to the application. And we kind of realized that's probably not the kind of thing that makes sure we're gonna stay around long term. What is really important is to kind of become actually part of the value chain. So what we did is exactly that. It's kind of, we not just added AI features. We actually allowed people to build AI-powered applications with N8N. It's obviously nothing that the user base or people kind of realize overnight, like what N8N has become back then. And it's obviously takes some time to kind of catch on. And that's where also the second piece comes in. Historically, we kind of focused on many two things internally at N8N. Especially in the marketing department, they always had like this dual focus.

• 4:11Speaker 00

  And obviously kind of creating leads, but also kind of making sure like the inbound that kind of we get more adoption. It can always cause a problem in the sense of we were always very good in adoption, but at the same time, leads normally fall short. So what happened is that the marketing department put everything from adoption in leads to make sure that we can make that go as well. And that was obviously problematic because all the long-term planning went away. They couldn't really have the impact they could have had. We realized, hey, we have this amazing community. We have this amazing bottom-up adoption. So instead of actually kind of forcing something that's not really true to us, we just really focus on what was already working. This is really focusing on this kind of top of the pile. That's what we did.

• 4:55Speaker 00

  We kind of removed the lead goal. We actually exchanged with adoption of large organizations. That's when all in the community, as many people as possible are using N N. And also is another thing that you can decide and you make the change. But it's nothing is kind of happens overnight. You actually have to fight, you have to have trust in that. You have to kind of really double down and kind of wait because these things kind of take some time to mature. And that's actually the thing that actually happened. Like it matured, it kind of really doubled down. We kind of empowered our community more. We created more events, created more content. And that is then in the end, this thing that materialized, especially in the beginning and the end of last year in December,

• 5:37Speaker 00

  is where the market finally realized that we have become this AI tool. But also the community, especially around on YouTube, where more people created more and more content. Obviously, more content people create, the more other people want to create content, the better it gets ranked. And then everything kind of started to explode.

• 5:54Speaker 01

  I had an amazing story at our board meeting a couple of weeks ago, Jan, that you have Jan-focused time on long flights. And you actually coded the first version of that AI nodes product flying back from San Francisco. Is that true?

• 6:05Speaker 00

  No, actually, I created quite a few things on planes in the past. That thing I didn't create on planes or trains. I think I always loved the time. Honestly, right now, I always loved that, to be honest. But now I always feel like destroying more than actually helpful. So I kind of create more like MVPs or something that play around rather than actually adding production code on planes or trains anymore, which is sad.

• 6:27Speaker 01

  On dodgy wifi. Yeah. Maybe, Jan, if you can take us back to 2019. I think it was just you sort of founder entrepreneur when you went out and raised your pre-seed round. What was kind of the aspects, the origin story that really stands out to you? What has really stayed the same from day one of N N? What has really changed over that timeframe?

• 6:45Speaker 00

  I think what always stayed true is for sure the kind of focus on the community like actually the first people, like in the first week in, in, in April, a few people started. And one of the first people that started was at Eiffel, because I always knew like, if, if we want to make sure that N N N becomes meaningful and kind of becomes the company like I wanted to build, I really have to kind of make sure kind of I, I, I invest in the community very early on. I think that kind of always stayed true. I think another thing is probably something around values. We always, especially I always try to be as honest and upfront about things as possible. We also see that, for example, in our license.

• 7:28Speaker 00

  We probably have seen like, we never call ourselves open source, because we don't have an OC approved open source license. So what does it mean? It means our source code is available, everybody can use it totally for free. They can even use it in, in production, that they, it's no matter if it's a, somebody home privately or somebody in a large organization, everybody can use it. What's however different in our license is that people cannot commercialize our code. It means nobody can just take our code and often like a hosted version of N N N, for example, or kind of create X Y Z automator in the product. Why is it important? Because I saw a lot of organizations in the past, like open source organizations kind of changing license.

• 8:12Speaker 00

  And people obviously got very angry and they really hated that. And what I thought was quite interesting is people didn't hate it because of the license that the company chose. People were mainly angry because people like this company changed the rules and it's never nice. And so what I thought, hey, I, I think it's a very reasonable thing. So I'm just very honest and upfront about it from the very beginning. I said, hey, I'm not building N N N and giving it away for free because I'm a good person. Like I actually want to build a business around it. I want to make sure I can get paid. I can be, I want to make sure all the other people can get paid as well because I actually think it's in the interest of everybody. So that is why I chose the license. I think that's we, we always had stayed very true around that. Again, knocking the second part of your question is like, what changed? I think it's definitely like.

• 8:57Speaker 00

  Around like what what we started at is like I said, as mentioned before, like we started this kind of automation tool. Obviously, I never have thought that we would AI ever like it's never even crossed my mind that we would go into the AI space. But I think in the end, it's like sometimes you see opportunities out there and you have to take them and else I think it's the mix difference between building some big sustainable company that really matters and or probably building a kind of a startup at some point and that's because of the business.

• 9:29Speaker 02

  Yeah, and you've done a masterful job on the community building aspect of N8N. And you mentioned the values, which I'm sure were really critical to earning the trust of your community. Can you also talk a bit about the tactics? It's kind of the constant push and pull of trying to kind of shape or curate the community while also really trying to listen and, you know, and see where they want to go. How tactically, how have you managed the community over the years?

• 9:56Speaker 00

  I think for the very beginning, it was very important for me just to kind of include people. For example, we in the beginning, we didn't have any not not telemetry data at all. We didn't collect any telemetry. It's also obviously fine in the very beginning, but obviously, as the company grows, you kind of need data, kind of improve the product very fast. Again, it's going to make the difference between a company that survives or one that doesn't. So we had to add telemetry data. Another thing we had to add was at some point, we obviously added paid features. And every time we made a bigger change, we kind of kind of posted it to the community forum first. We kind of like we shared it with them what we wanted to do, gave them the reason why we wanted to do it. And then kind of listen to their feedback. I think that is just kind of taking them with you

• 10:40Speaker 00

  when you're doing something. I think that's just a very important thing. Another thing is definitely kind of trying to kind of empower them. Actually, like one of the earliest N8N employees was Ricardo. Ricardo, see, he's this amazing guy working in Florida, and he was the first, one of the first contributors to N8N. He discovered a product and product hunt. This started to kind of create one node. Then he created two nodes, created three nodes. And every time he contributed something, I said, hey, that's great. Thank you very much. And then I kind of. Give feedback, I improved things and he learned and he was excited and created more notes. And at some point, he created like fifty or sixty notes, like integrations for N N. Um, then obviously, as soon as I had the first Money Banker, I hired him.

• 11:25Speaker 00

  I think it's really just very important to kind of show people that you care and take them with you and can kind of show how how much you value them. I think really hope the community really knows how much we value them. We try to give back a lot. I think that's certainly, I think, is kind of even though we're not open source, we have to set this open source ethos where you kind of really give a lot first. And I think you normally get so much more back than you actually receive. We see the same thing again also with our community today, where we just say, like, we empower you and then they create all of this amazing content, no matter if it's on YouTube or LinkedIn. They create tutorials. I think that that worked out very well. That's something they're still doing to this day.

• 12:05Speaker 01

  Yeah. And has there ever been a shift in, I mean, given the scale of the community today, right, it's hundreds of thousands of members in size. Has there been a change in how you try and surface the right information or the right ideas and how you choose which to prioritize coming from that community base?

• 12:21Speaker 00

  Yeah, and the beginning was definitely easier, like, which ended in the beginning, like, I didn't really worry about monetization at all. So I just wanted to make sure I built the best product and I just built things that people really wanted. So I could literally, from the very beginning, we had a community forum where people could add feature requests and people could upload the ones they wanted to have the most. That is literally kind of how we chose very early on what to build. Unless that was something totally out of bag, we normally build it because we knew people really valued it very much. And that works, but actually for quite a while. Um, at some point, you have to be a bit more opinionated, but you're not just kind of building what the community wants, but we actually have to kind of think about like

• 13:04Speaker 00

  where the market is going, also how you kind of build something, again, that's sustainable, that again, especially also something what honestly is also kind of larger organizations use as well. And also just generally where you see the market going. And I think that's what we're doing right now. We try to find a good mix between what are people really asking for? And what do we think we have to build to be successful in the long term? Both because like something like AI, but also again, what, for example, enterprise organizations need.

• 13:31Speaker 02

  You mentioned earlier toward the start of the conversation that you had this sort of make or break moment in the early days of AI where you realized that AI was either going to be the future of N8N, or I think the word you used was the demise, the demise of N8N. Can you take us back to that moment? Like, what did you see that made you realize how important an inflection point in the trajectory of the company this is going to be? And then what did you do to figure out how to position N8N so well with respect to these AI tailwinds?

• 14:04Speaker 00

  One thing I actually saw is I saw it was the funding announcement of Pinecone. So I think they raised like a hundred million dollar round or something like that. I also saw that they kind of raised around a year before, like some point before, and I was wondering like what changed? It's like, why, why a company suddenly cares so much about them? And then I realized again, it was exactly that. It's like, what they were in the past is they were the vector database. What they've become, they became deep database for AI. This is what I say, we have to do something very similar with N8N as well. That's exactly what we did. What we also did on this in the past and what the most of our competitors

• 14:45Speaker 00

  did is they kind of created an OpenAI node, a node that kind of connected via HTTP, did requests to OpenAI. You could do quite some nice things with it. You can still do it up to this point in time. But what we have realized is that this is only not enough. Like, you can do quite nice these cases, but the really powerful things are not possible. You really have to be able to kind of create proper agents, like change auto prompts, add tools, add a vector database, and output passes and all of these things. And that is when we then kind of built out our advanced AI functionality, where we allowed people to do the things in N8N in this kind of low code, low code way. That was, we were the only positive writing Python scripts.

• 15:30Speaker 00

  So we kind of drastically reduced the entry barrier for people to build things and also reduced the speed because the stuff has historically also been quite finicky, honestly. Like, connected A with B and it didn't work and it's taking away all of those pain points and it takes care of it underneath the hood and you just click a few times, add an agent, add a model, add the memory and so on, and it is working magically.

• 15:54Speaker 01

  Yeah, and talking about, you know, companies that share, I guess, an open source ethos across AI, obviously, the role of open source, I think, is changing across the industry at large. We've seen, obviously, a lot of headlines coming out of Meta, out of Mistral. OpenAI released their GPT, you know, open source version, et cetera. What are just some perspectives you can share on how you perceive the state of open source in AI more generally? And maybe how do you see its role changing in the future?

• 16:18Speaker 00

  I think the great thing was we always had a bug with open source is it's like, it's kind of, it's driving very rapid innovation at the end, like, because you have like this kind of huge army of people that really, really care very deeply. They're very smart and very often have a lot of time. And they kind of do things that organizations can very often not do. Because again, they have very different incentives or have very different timelines or have.

• 16:51Speaker 00

  It simply doesn't work. And I think the nice thing about open source is like, you can do whatever you want. And you can explore things that maybe wouldn't even make sense in a company setting. So I actually think like, open source is like really this amazing thing that they kind of open up the world to very many different possibilities. And the end, like, some of them bins, and a lot of open source projects never make it to anything. Obviously, this is the ones nobody talks about. But some of them, they kind of hit something. And that those are the kind of the ones that really kind of matter and kind of really shape kind of very often the whole industry in the end.

• 17:21Speaker 01

  Maybe a follow up question to that, Jan. I mean, do you see a shift in the role of open source? I mean, do you see that companies, I mean, today might be using some of these open source technologies to save money, to save costs. But maybe actually having more control inside of organizations over the performance of models might be a value proposition that evolves in the future.

• 17:38Speaker 00

  Definitely, very, very much. I think like, first, I'm not sure, like, first, if open source is that is very often it's the cheapest thing. I think this is kind of misconception, it's actually very often not true. I think you get even a lot of things like being able to kind of self host, knowing where data is stored and what's happening with it. I think there's a lot of value there. But very often, it's actually the cheapest thing. Very often, it's actually the more expensive thing because you have hardware that's probably idle for 99%. Of the time and it's actually kind of turns out to be more expensive. So actually, I I'm not sure if if that's actually true. But the the second part I think is true and people care about it more and more. Like we actually work now with a few organizations. And that's actually the main reason why they wanted to use open source.

• 18:21Speaker 00

  It's not because it's free, it's because they actually they care about the data privacy and data security angle. And I think that's also what we are always historically seeing with N N very often is like. People want to kind of self host and want to know um where the data stored. Um and admit themselves, obviously don't mean they run it on their computer, need to test, they still run it on the cloud. But obviously in their own private cloud.

• 18:42Speaker 01

  Yeah, and one, I think noticeable shift over the last couple of years, something that of course N A N I'm sure has been a beneficiary of. It's just improvements in the communication protocols between different systems and different models. And obviously M C P is a, you know, high profile candidate that has really driven the industry forwards. Can you talk a little bit about that, kind of, kind of how you see the changing role of some of these protocols in the future? And where you think they might evolve?

• 19:03Speaker 00

  I think that if you kind of standardize, you kind of in the end, you kind of accelerate things. I think that's very important. Even interestingly, if the standard is maybe not perfect, I think it's still. It's so much value and I think if M C P is gonna be the the one we're gonna use in a few years, I have no idea. But I think it is great to have like a starting point and kind of you kind of can build on top. Um in the end, this M C P is like the H D P of the A I of A I workflows. I think that's really amazing. I think it's kind of will enable, it already enables now things like agent to agent and it kind of is a kind of building blocks you actually need. For this kind of more powerful um use cases like for example, the marketplaces or like.

• 19:44Speaker 00

  Plug the play automations and I think N N can act as the kind of the orchestration layer between this kind of service M C P. Agents and and tools and also obviously N N is also the best kind of platform to build also tools that you can um access with M C P as well.

• 20:00Speaker 02

  Actually, on that, Jan, we haven't, we haven't really done the straightforward, what is N A D N? So for somebody listening who has a passing knowledge of N A D N, but wasn't sure exactly what it is, what is N A D N? And when should people think about it when building N A I?

• 20:17Speaker 00

  I think N A D N is by now probably the easiest to use, most powerful way to build A I agents right now. I think it allows you kind of, again, build things you previously never even thought you were able, you could build. I think the nice thing about it can go very fast from a first idea you have to a first prototype and then bring that prototype into into production.

• 20:42Speaker 02

  What is the stack that you see people using with N A D N?

• 20:46Speaker 00

  Actually, quite diverse. The, the nice thing about that system like N A D N is you can actually connect everything to anything. There is probably not kind of this default stack people are using, like they use literally any L L M, they use any kind of memory or vector store, any kind of applications, etc. That's the thing that makes anything great because, like, honestly, like, I don't know what L L M is going to be in the race. In the end, who's going to need the best one? If it's going to be one of, it's going to be a million different ones, it's going to be a small one, a big one? I have no idea. But that's the great thing about N A D N is like, we don't have to care because the nice thing is you can use whatever is best for your use case. And I think that is what makes it so powerful.

• 21:23Speaker 02

  Any interesting observations on what's been trending, positive or negative, in the N A D N universe?

• 21:30Speaker 00

  What people definitely use quite a lot is honestly still like all the kind of Google tools. Google is definitely still, I think, the one, the, the kind of application you can use, that everybody, like, people use the private in large organizations. I think that's the amazing thing. That's why we definitely see that's probably one of the, the strongest ones. We definitely also see a lot of this kind of communication platforms, if it's a Slack or Telegram or anything like that. It also kind of makes sense, especially in this kind of A I world, because you obviously need like an interface, how you kind of interact with, with the agency built. And I think that is probably a few to call out. And apart from that, obviously, also things like just databases, any kind of, again, the nice thing about N A D N, you can connect literally anything. So it's not just kind of applications, also kind of low, low level things as well.

• 22:16Speaker 00

  And also honestly, very often also internal tools as well.

• 22:18Speaker 02

  One of the nice things about N8N is you struck a good balance between the sort of flexibility, customization, control that a developer might want with the ease of use that somebody who's less technical might want. Has your user base changed? Kind of the complexion of the N8N user base? Has it changed as you've gotten more and more AI adoption?

• 22:42Speaker 00

  It's quite interesting. Like when actually our user base started to explode, like since the last eight months, you were really wondering if if those people are really gonna be the most successful. Like if if the quality actually dropped and quality doesn't mean obviously this bad people is just like the kind of people that are successful with N8N. And they didn't, which was quite surprising. Like brilliant people that are quite either are already quite technical or people that really like have a use case and they care very deeply about what they're building and they're just willing to put in their work. Like maybe they're not as technical when they're really kind of enter, but they have a problem they really want to solve. We have actually quite a few users that actually started to learn to code because of N8N. And why do they do that?

• 23:27Speaker 00

  Because they can realize, hey, I can do S that much. Like if I if I'm technical, but I cannot code, but I can't code, but again, it can literally go anywhere if I can code, it kind of this whole new world opens up. That is actually, they didn't change that much. And I think that's just really amazing. There's so many technical people out there and people are really interesting. I think our our community is really amazing. It's just the ideas they're having, how driven they are and how much they also want to help each other out. I think that's just great.

• 23:56Speaker 01

  Jan, do you think with the proliferation of adoption of many of these different AI technologies, the pressures are different on being a founder in 2025? I mean, you've lived it over the last eight months.

• 24:08Speaker 00

  Yeah, I think that it definitely changed things. I think the main thing is like the past, it was easier to plan and know where you're going. And right now, you're always living in this constant.

• 24:22Speaker 00

  I wouldn't call it fear, but kind of kind of state of uncertainty where the world is moving. You have to be really willing to kind of like, you have to find that you have to strike a very good balance between not missing anything important, but it's not jumping on anything that comes up your way. And I think that is definitely much harder, it feels like than it was in the past.

• 24:44Speaker 01

  Given that, how do you think the signals that you get as a CEO have changed in terms of how you weight them? I mean, even things like, you know, you see, you see across the business or the revenue being generated, you know, in different parts of the company. How do you sort of assess the sort of durability of that and make sure you're investing behind the right things?

• 25:01Speaker 00

  That's actually probably talks about something I think is generally quite important. It's definitely harder in kind of this open source world we are having as we have like, if obviously we have some use cases that generate revenues, like with enterprises. And we have a lot of people that that use the product for free and we never generate revenues with them. But honestly, none of them is more important than the other one. Because like one is obviously is going to help us directly, but the other one is the thing that drives all of it. To me, it's like, you have to strike a very good balance between both of them. And honestly, normally I'm leaning much more heavily into kind of, for example, I guess,

• 25:43Speaker 00

  you obviously asked about Chris, what signals, I think it's an important point is like, I normally lean much more heavily in kind of giving away more for free. Because again, everything we give away for free kind of makes the product better for literally everybody. And twice more adoption and also twice more revenues in the long term versus everything we build for the enterprise organizations. Obviously, that's kind of up the subset of the users. Thing is, we think it's still important to do both and I think you have to listen to both very closely. But also I think it's around timing in the end. It's like right now, I think it's really about capturing the markets. And we have to listen, what do people really want to build? And I think what is important is to really capture the market generally and literally capture like the smallest builder out there.

• 26:27Speaker 00

  Because we obviously, what we obviously see is that through the smallest builders, we get into the largest organizations out there. What I think is impossible is if you now focus very heavily on enterprise only. And I think you can never go then downwards again. I think nobody like nobody went from enterprise to to kind of owning a space. And I think that is again, also Google started the same way as well. They maybe own quite a quite quite a lot. The same with Microsoft as well, but you have to start in in the right direction there.

• 26:55Speaker 02

  You know, right now, we're seeing this explosion of people building with AI capabilities. Over the last few years, we've seen an explosion in the AI capabilities themselves. And so the question is, is that technological foundation, the AI capabilities themselves? Do you think that that is still innovating at the same rate it has over the last few years? Or are we finally asymptoting in terms of the capabilities coming out of foundation models or out of the open source world? Do you have a point of view on that?

• 27:27Speaker 00

  I think probably looking at GPT five, I think it definitely feels like it's slowing down. This kind of makes sense. I think it's not very often what what happens is like this. There's more low hanging fruits in the beginning than than the later point in time. And you can again, you can throw more compute power and more data for quite a while. But at some point, you kind of max out there and and at some point, it just becomes too much. So I think definitely kind of, please kind of slowing down. However, just think that's more as a kind of a temporary thing, because there's so much money in the market right now. Where people explore a lot of different things. And some of them are still very early, early. And I think they're not at the right stage yet. But I think as as some of them were coming to this kind of to the right stage, I think you're gonna see probably another acceleration.

• 28:12Speaker 01

  I mean, I'm maybe building on that to Pat's question. I mean, we're seeing more code being written by machines, right? And more end to end, agent to agent automation. How does that change the positioning of N A N? How do you think about areas you'll invest, maybe given that future?

• 28:26Speaker 00

  I think one thing is, I think it's probably talks a bit to the kind of role as as a developer. Like in the in the past, a developer was somebody that kind of built something for you. It's like, you said, hey, I need X, and they built X for you. Now with tools like N A N and all of the white coding tools, that's changing. See developers. More as the the people that kind of generate, that kind of create the guardrails for you, the people that empower you to build the things you actually want and need. And I think that is really amazing. And honestly, it also plays exactly what N N was always about. It was always about empowering people.

• 29:02Speaker 00

  And I think it's great. I think literally every developer is kind of going into the role of empowering other people to to build the things they actually want and need. Yes, developers obviously still have the the vibe quarters and other people like that. They're not going to build everything. They're still going to roll for the classical engineer. But I really love that kind of world where people are empowered and the people that have the problems are the best equipped to kind of solve them themselves. And I think that's the kind of world where we're going. And I think that's the engineers and developers are definitely a very important part for that.

• 29:35Speaker 01

  I mean, Jan, something I think we'd love to know your opinion on. I'm sure a lot of people listening are struggling between building, you know, verticalized applications that solve a very acute use case versus kind of having broader platform visions, right, for their companies. N A N is the horizontal of horizontal tools, right, in many ways. How do you see the positioning changing, given some of those dynamics of some of these very vertical applications and then some of the more horizontal tools coming out of the labs and the like?

• 29:58Speaker 00

  Yeah, I think like vertical is obviously amazing. If you had like one very specific use case, that do this one thing perfectly and they can do it much better than than every horizontal tool. And obviously, that's exactly what happened with with SaaS. Like the SaaS world, it's like they have a vertical application for literally everything. That is again why we had the need for something like N N, because you have to kind of pick it all of them together again. I think there's also a little bit, but also probably happens more and more in the I right now where people build this kind of very vertical tools as well. But as this happening, there again, the complexity increases again. And you either need kind of another orchestration tool or like you need a horizontal tool that kind of built everything for you again.

• 30:42Speaker 00

  So either kind of again, you bring all those tools together or use a more horizontal tool to kind of and build this thing in this one tool rather than kind of a million different ones. And again, I think that's again why we obviously feels like in a very good position there because again, we, I think we, no matter which way it's going to turn out, I think we are very well positioned for this world.

• 31:02Speaker 02

  If everything goes right. What will N8N be in five or 10 years? What role will N8N play in the world?

• 31:11Speaker 00

  The idea is always like, for very many different reasons, that I was compared N8N to Excel. They always thought about, hey, if people 15 years ago, they heard spreadsheet, they thought about Excel. And if if people in a few years think about, hey, I have to build AI, I have to do anything with AI. The only thing that should come to mind is N8N. This is more like kind of this kind of default orchestration layer, like what is kind of platform from everything to building, to deploying and and where you find your agents, um, things like that. And I think that is is where I think it's going to naturally evolve. I think we are very, very well positioned as we already kind of starting to be like the default building tool already.

• 31:49Speaker 01

  So Yan, you know, you build a remote first company, obviously centered in Europe, but but with global ambitions. Um, just talk a little bit about, you know, thinking about going into the US and kind of building the team and scaling the organization over the last year.

• 32:02Speaker 00

  Like obviously we started in Europe and the whole team was based here. But what we always was quite interesting, like even though we were based in Europe, like our user base was always very global. Like for quite a long time, Europe and the US had the same size, even though we only didn't provide our US customers the best experience. It definitely shows us like a very, very big need in the US. This is why we are also right now expanding to the US and actually just right now opening our um office in New York. And this also why we are having quite a lot, especially in the US, but literally like also also as we can say worldwide, literally everything from engineers to people in support and and and especially a lot of people in the go to market org. I think it's also the kind of the thing that really gets me excited is like, I think

• 32:46Speaker 00

  not many European organizations kind of have the possibility to really build something really global and something really matters. I think N8N is probably one of the orgs. I think that has quite a lot of potential. It's nice to see that we are now finally kind of going in that direction and then kind of also kind of capture the US and take that market over as well.

• 33:04Speaker 01

  And and maybe to wrap, um, we love to ask some kind of rapid fire questions just to get your your take on a couple of key themes. Um, I think one, just through your reflections of the last six years, what's maybe one of the hardest truths you've learned about Yan as a founder CEO?

• 33:19Speaker 00

  One thing is probably.

• 33:22Speaker 00

  I really don't like to say no. There's so many different things out there and I think that is I think very often it turned out to be okay, like to kind of do a lot of stuff in parallel. Standards and hindsight is actually didn't turn out that well. Interestingly, I think the most things very luckily turned out to be quite well. So I'm very lucky there, but I think also it has turned out very differently. And I think for the most companies, it actually turns out very differently.

• 33:46Speaker 01

  We want you to keep taking those big swings.

• 33:48Speaker 02

  Yeah. What is one must read or must watch piece of content in AI? Blog, book, show?

• 33:57Speaker 00

  I guess I still love her. It's just a movie. I think it's just. Yeah, I think it's just this thing is that I think what I think is especially amazing about it is like a few years ago, it was sci fi and it's now suddenly this thing that is that's around the corner. That's why I just love it. I think it's also a great movie.

• 34:14Speaker 01

  Is there a tool or a product, Jan, you've been playing with in AI that you would recommend? Or that really interested you?

• 34:21Speaker 00

  I think I just very recently and probably very late I came there, but I started using Granola. I think it's just an amazing tool. It's so great. So send them to use. That's such an amazing job. So I think that would probably be the one that comes to mind right now.

• 34:33Speaker 02

  What AI application or application category do you think is most likely to break out in the next six to 12 months?

• 34:41Speaker 00

  I think it's kind of probably more this kind of AI powered internal tooling. I think this obviously like this external part, I think it's gonna, it's a little bit hard. You have to be very careful there, but internally you can take much more risks. We also see that already at End and End quite a lot. That's obviously that's obviously why I'm also excited about it.

• 34:59Speaker 01

  Yeah, needless to say, we appreciate you, you know, sharing some of your story, looking into your crystal ball for us and kind of sharing some of the perspectives over the last six years. It's been a privilege for Sequoia to be a part of it. So thank you for having us on the journey. We look forward to the future.

• 35:12Speaker 00

  Thank you very much. Thanks for having me.