Cheeky Pint - Des Traynor on reinventing Intercom twice and the “four horsemen” of good AI companies

Episode Date: September 24, 2025

Des Traynor, cofounder of Intercom, sits down for a Cheeky Pint with John Collison to discuss the growth of Fin (Intercom’s AI customer service agent), why selling AI products is hard, advice for product marketers, and cofounder dynamics.Full transcript on Substack: https://cheekypint.substack.com/p/des-traynor-on-reinventing-intercomTimestamps: (00:00) Intro(02:58) Reinventing Intercom(06:31) Fin(18:06) 1M resolutions a week(24:22) Selling AI(29:34) Product marketing(37:18) Listening to users(44:14) Usage-based billing(45:14) Advice for startups(52:09) AI pricing(01:07:27) Cofounder dynamics(01:11:04) Predictors of company success(01:15:56) How AI-native is Intercom?

Do you ever work in a bar? I've never worked on a bar. I have a Guinness keg in my house. Actually, do you want another pint? Yeah, sure, sure. I was talking to a guy who runs procurement, and I just saying, like, you have to understand, I'm just getting bullshit into all day.

You know, it's just all day, relentless, absolute nonsense in my face. People do not have enough empathy for the procurement person who just has to endure nonstop nonsense. Absolute garbage. Chat GPT launched, I think, on a Thursday. I had a call with Fergal or head of AI on Friday. I made the decision, like, on the Sunday, I think it was,

and we started working on, like, AI version of Intercom on the Monday. It was a lot easier to invest when being a founder was uncool. I blame genuinely the social network. I blame just kind of the entrepreneurial lifestyle. I blame my TikTok. I blame all these things. Soho House.

Yeah, yeah, exactly. You just show me your technique, and I will learn from you because I'm pretty sure I'm doing wrong. This is the first time I've ever poured a pint of Guinness in America. My fellow Irishman, Des Trainer, is the co-founder of Intercom, the customer service giant turned AI company. He's also a prolific blogger and one of the most respected voices on product strategy. Cheers. Okay.

You are my first Irish guest, and so I actually have a critically important question that has been burning this entire time. Whenever we release these episodes, all the YouTube commenters are obsessed with people splitting the G. This was never a thing for me growing up, a thing I never saw in Ireland.

It's like an invasive species, maybe from TikTok. Is this a thing? No. It's not amongst anyone who you would respect. It's very much an actual TikTok thing. It's a slight bit of a tourist thing because of that. But it basically means that you're drinking, I think it's a quarter to point in your first mouthful.

And it's like, I don't know. A waste of good goodness. Yes. Yeah, okay. It's a little like when I first came to America at drinking games. It's like back home, drinking is very serious activity. Exactly. I wouldn't make a game out of it.

Exactly. Yeah, yeah. I was very confused by that in America. Okay. And then my other stout-related question is, I saw you opining on like Beamish, Murphy's, everything like this. I don't know, what is your, what is your, What is your view on the stout landscape in particular?

I probably default to Guinness. There's been moments when I'd go Kilkenny, Beamish, Murphy. Usually it's like when you're every year in their respective hometowns, but for the most part I default to Guinness. And for like one brief day, I tried to Island's Edge. I don't know if you remember when they were Hineken launched a Guinness killer. And it lasted all of like six months or something like that. They were literally, like, I think literally they were giving it away at the end

and still couldn't get rid of it. Have you heard all the Guinness stats about, you know, the Guinness used to be a majority of Ireland's stock market. Obviously, the canal system was built for Guinness distribution, but sometimes when you tell people that Guinness used to be a very significant part of Ireland's economy, you know, they don't believe you, but the stats are really there. And it's weird, like it trickles into modern day, like where I live by Castle Knock, like, a lot chunks of the Phoenix Park are owned still.

Or the Guinness family. Exactly, or the house, but used to be there, and it's like, they don't, and then maybe they donated it to OPW or something like that. But yeah, it's very much still kind of carries forward. Yes. Okay. And we're not actually going to talk about Guinness the whole time. We should also talk about Intercom. And I was thinking in preparing for this. I'm very impressed by businesses that can reinvent themselves or maybe even reinvent themselves multiple times. So you think about Netflix. They started with the original DVD by mail business. And then, oh, my God, the internet's coming. And they had a few abortive attempts at streaming, like remember the whole Quixter debacle, but then really cracked streaming movies. And so, you know, you. you can watch The Godfather or you can watch whatever movie you want on Netflix. And then, of course, as they got more squeezed by the rights holders, you actually can't go watch The Godfather on Netflix anymore.

Or you type any movie into Netflix and it's not there. Because now Netflix is all first-party content that they have developed themselves. And so they've reinvented the platform once again to be, rather than watching other people's content, watching Netflix content. They've twice reinvented the company from DVD by Mail to streaming third-party content to streaming first-party content. Intercom strikes me as a business that has similarly been reinvented twice, where you guys got started with the Intercom feature of, you know, you can talk to your customer through the website, and then you guys became a customer service company, which is actually different for reasons we

can talk about, and now you're becoming an AI customer service company. That's my theory of Intercom. Is that actually an accurate theory? Yeah, that's true. There's a bit of extra context I'd give it. So when we started, it wasn't really, It was like about like this is like literally when we started. And our initial plan was like, hey, like you remember the internet because like Stripe was in its early days back then as well. But like there was no tooling to run a SaaS business. It was like literally nothing. It was like you were using, you were kind of abusing like PayPal for payments and you're using like mailchimp for like talking to your customers.

And so, you know, we had this idea of like talking to your ghost is really important. So someone should work on that, you know. And like there was so much stuff in the early releases of Intercom. Like it was the first live CDP. Like you can actually see who's live. in your product right now and what you're doing and you could store data against them. You could say, show me all my premium customers. And weirdly, like, use cases like that still exist today.

I was in Denmark last week and I was like, oh, I should message all my Copenhagen customers and see you. And like, all that stuff is like, you're still kind of like, who else is doing this? So we started out like with a very, very general purpose idea, which was like that internet businesses talk to their customers. And then we kind of fell in love with this jobs to be done methodology. And like one of the things you do in that is,

you look at how your product is actually used and then you iterate on it from that point of view. And that kind of led us down this path of sales marketing and support. And then I guess to skip a load of years here, let's just say 2020, things were great, 2022 things weren't as great. And then it was like, we need to focus. Concise, pre-C of the period. Let's just cut a lot of the reasons why or whatever, some sort of disease as well along the way.

But yeah, so 2022, like it was like, hey, you know, own returned on the left in 2020, I think. On return, you know, business had been like in declining net near revenue. He said, like, we need to focus. we're in a focus on customer service. And then a short time later, I think maybe like 10 weeks later, AI happened. Chat GPT launched, I think on a Thursday. I think we, I had a call with Fergal or head of AI

and Friday. I spoke with it on all through the weekend. And like we made the decision. Owen made the decision like on the Sunday, I think it was. And we started working on like the AI version of Vitercom on the Monday. And that was like 2022. And I think like weren't enough for that, it's hard to say exactly where things would have gone.

But certainly that's the reason I'm sitting here. And obviously people are naturally wired to be skeptical. you know, when you hear the AI version of Intercom, you have, you know, everyone and their mother out there saying we're an AI company now, but you actually are an AI company now. And so describe what the AI version of Intercom actually means. The biggest thing it means for us is our product,

Finn. So we launched Finn in March, I think, 2023. We launched a few little AI future. We were the first people that actually build anything on, like, the GPT3.5, and then we launched Finn in March GPT4 launch day. And Finn was like basically the first chatbot that worked. It's the best way you can think about it, what that really meant was it could actually have conversations and answer questions. And when we launched it, it was doing like 25% resolution rate.

And that was like crazy numbers. Today it's like 65%. And today, Finn's resolving about over a million conversations a week. It's handled about 40 million actual end-to-end customer service scenarios to date. It's growing over 200% year over year. It's like, we charge a dollar per answer so you can work the revenue out or a 99 cent even. It's becoming like just this, you know, AI sort of growth story inside Intercom, which already like a sort of, you know, a mature SaaS business into hundreds of millions of revenue.

But I think when we think about like what does it mean to be AI, it's like, first of all, what is the future growth of your business? And the answer is AI. And then over the last, say, six months we've been going hard and being like a kind of properly deep AI company. We're now at a point where we're like, you know, we're using our own models inside FIM. We're using custom re-ranker, custom retrieval, summarization, et cetera. And we're doing a lot of this work. We have like an AI lab of 50 people. And we really just kind of have gone all in on the idea of like, you know, like obviously Intercom still has a help desk product. But like, like, The entire future of CS is clearly going to be AI,

and that's what we're all in on. Yes, yes. Maybe there's the repeated pattern in tech where the enthusiasm for technologies comes before the technology being ready. And so people are excited about computer games before the wave of good computer games, or, you know, people are pitching mobile internet

and you'll buy cinema tickets via lap. It's like, you know, J2M.E and all that, yeah, yeah. And we actually had our version of that. Like, we had a product called Resolution Bot. It was originally called AnswerBot, but I think ZendS trend to sue us because they had a competitive product.

But Resolution Mall was actually a good AI product at the time, but it was just AI wasn't there. Right. And so that was your actual reason why we had such a headset, because we actually already had a little AI group ready to go. We'd already built a rag engine ready to go. So we were able to jump a lot quicker than a lot of folks. But yeah, like, I think a lot of these products,

you're right, like, have kind of two or three stabs before they go mainstreaming. Yeah, and there was this whole enthusiasm cycle for bots in 2017, I want to say, and the tech just wasn't there at all. It was a horrible experience for customers. It was also quite clunky to set up for businesses. And at some point, I think everyone looked, you know, there was a genuine question at times where it was just like, It's a web form not just better.

Yeah, I think a lot of cases it was. Yeah, yeah, yeah. Whereas I think now people are starting to have the experience of, you know, the classic thing is, you know, you're talking to a boss. It's like, please, will you please just connect me to a human? Whereas now it's like, can you just connect me to a boss? And can we get... We see that a lot.

We see like, oh, hey, Jenny, sorry to bother you. Can we put back onto Finn. It was like she's doing a great job. It just taught it wasn't, you know, because I asked a few too many questions. But yeah, I think, like, there's a general pattern we're noticing, which is like a lot of experiences are just better digitized, because partially because of human, considerations. Like, one of the reasons people go to like the kiosk in McDonald's, as opposed to, as opposed to their actual counter is because they don't want to think out loud in front of a human. They're like, oh, give me a second, do I want fries? A lot of the reason might people prefer Waymo. For some people, it's like, I just don't want to have the conversation. I know what the awkwardness around tipping or whatever it might be. And I just think what we see a lot is like, once Finn answers won't question well, people are like, oh, this thing's paying out. Now that you're doing not, I'm going to ask you all of the things I was wondering about. Yeah, yeah. Whereas I think they'd feel probably nearly weird when loading all that.

on one per CES rep, you know. Okay, so you're seeing a lot of induced demand where people use interactive customer service much more. Which is interesting because it turns Finn into not just being a kind of a cost takeout, but also it's like, how much better would your business be if everyone knew how to do everything they wanted to do? And like the answer is a lot of times it's a lot better. And it's not just the whole like I don't burn it burden a human.

It's also like people often, one of the biggest fallacies in AI is people compare it with like this perfect human that does not exist. Like the driver that never crashes or like in our case, it's a lot of it. It's like, well, a human artisanal handcrafted answer, and I'm like, yeah, like, let's pretend that would be there in seven seconds. It won't be. It'll probably be 18 minutes. It's also not going to be perfect.

And let's presume you're doing those handcrafted answers, which you're not. You know, someone is like busily trying to close the case before they move on to the next one. So, like, I think, yeah, comparing you're like, I don't know, we have this thing where we expect their AI products to be flawless and we're totally tolerant of like humans, Chonga Pung over, only speaking one language and only work in six errors or whatever. It's just, it's a funny contrast. Yes, yes. That's interesting.

And it's interesting you talk about product onboard. here because I think of Intercom as you guys are very, you guys have a house view that product onboarding should be much better. And I remember a lot of the use cases you would talk about for the original Intercom, talk to your customers through the website, was that you can have personalized nurture tracks. And like it's weird that you drop people into SaaS products and just expect them to be able to use them right. And you should see how people are using the product and then give them kind of specific steers based on their usage. And it sounds like you're coming to this vision again, which is people should have better onboarding support, people should be nurtured

along based on their use case, but now kind of interactively AI-powered? Yeah, I mean, we talk a bit about, like, this idea of, like, what is ultimately a customer agent going to be. That's what Finn will be, as it grows up, it'll just become, like, this way in which customer conversations are handled. And obviously, the most direct attack here is, like, customer service. But, you know, I think every single customer touchpoint can be improved by, like, basically immediate, accurate answers available all the time.

Isn't an obvious limitation? Like, right now you require customer. to come up with a prompt. And if you look at why TikTok is so successful, it's like I would never prompt for, you know, I want to see videos of planes landing low over the beach in St. Martin, but like it turns out that's what I want to see. Yeah, yeah, yeah.

And similarly, people probably have many more things they need and they will actually come up with a prompt for. And I think the product today is still mostly prompt-based. As I said, it's reacting to what customers say. Exactly, a customer has to come along and, like, type things into the box. I mean, today, that's what customer service is. It's still, like, kind of like, here's my problem and it will solve it. I think, you know, for sure, there's obvious directions.

This will go. It's like, hey, what does a good customer look like? And maybe we can honestly infer that as well. But certainly, like, people like you should do things like this is definitely an understandable domain. And then I just think working at the right level of interruptive help. You know, like, you don't want to be too naggy or too pop-upy. Like, you know, it gets kind of quite grating.

But I think if you can get the first message, right, you can sort of say, hey, if you come here, you're always going to get the thing you should do next or like the thing it looks like you're stuck on. Like, if someone's on the, I don't know, the renewal page and they have an error message. We know they're probably going to open the thing, and we know they're probably going to say something that's got a lot of the context already there. So we can work out the right things to say and do.

I think that's pretty doable. It feels like you could do a lot around, yeah, you train a model on what the customer is seeing on that web page at that moment in time and use it to feed the answer and things like that. We already do a lot of that already, like it's in customer context. So like, so knowing that it's John and he's on a premium plan

and he's on the playlist page and there's an error on the screen, there's all useful information when it comes to. Because like, in, people, a lot of like the YC I could build that in a weekend type hacker news crowd, I think one of the things they often, you know, they're thinking every customer support career begins with like, hi there, my name is blah, and my user number is blah, but actually like most support conversations begin with like, this is broken. And you're like, what's broken? And like, so to solve that, you need like a phatic reply engine. It's just like, hey, let's chat about

what's going on here. But like we realize quickly, like, people will kind of disengage. So any amount of extra context that when you say this is broken and if someone says this is broken and there's a big red error box on the screen. We're like, well, it's probably that thing that you're talking about. A lot of people just don't realize how deep you have to go to actually do a great job. We do, say, if you install in today, you get 65% resolution right after 30 days. That's shocking, but like we have had to go really deep to actually get to those numbers. And it involves like all sorts of every single smart thing you can think of we've had to do and then optimize and then find their eye model for it and all that.

But one of them is customer context. And obviously answers a lot of things. Yes. Part of the other smart things. Abstraction. So like, you know, like I guarantee you've got like no. pages on your website that say Stripes works really well for a dentistry office, right? You probably don't have done your docks. A very naive ragbot will be basically like, well, it doesn't say dentist and we're told not to hallucinate. So no, we don't do dentists.

And like the abstraction is like, you know, in that case, is, well, what is a dentist? It's a type of business. Does Stripe work for businesses? Can dentists, can dentists be internet businesses? We'll be say we're great for internet business. You know, so you're kind of working out what's the best, what's the best sort of risk-tolerant way to make grounded inferences without going over the cliff. You know, that's one of like 27 different sort of components of fin. Then you've got obviously your rag, and then you've got like, hey, is this an escalation appropriate at this time?

Like, hey, if they threaten something or if they, you know, like you have every single type of problem, it kind of ends up, but you have to walk through it all to actually recreate customer service. I think a lot of times people will compare it with like, how do I reset my password? Ha, it found it. And you're like, right, cool. That's like 0.4% of the scenario is you deal with it in your end customer service.

Yeah. There's a pattern. Did you ever see the movie? Armageddon where it's like Bruce Willis and Ben Affleck or whatever. But the gist of it is they train a load of, I think it's like oil drillers to become astronauts. And the comedy, the joke at the time that Ben Affleck always says, he got drunk and he recorded the voiceover for the DVD. And he was like, I always said, why didn't we just train the astronauts to drill oil?

Surely that's an easier problem. I think the thing that we're realizing with the AI movement is some version of, what's going to happen sooner? Will AI people learn how to do CS or will CS people learn how to do AI? Thankfully, as I said, we kind of started off with CS and AI in our DNA. I would say people, you mean companies. in this space like, well, open AI get better at customer service faster than Zendesk, it's better at AI.

Exactly, exactly that. I think we were lucky that we kind of had already backed boat horses somewhere along the way. One thing I find interesting about what you do is every company is thinking about AI right now. Every company had a board meeting in 2023 where the board is like, can we do a special deep dive on AI because it just feels like it's a lot happening

and we need to be making sure we're on the leading edge of AI. And then every company was like, oh, we're actually doing a lot in AI. For example, we've seen great automation wins in customer service. And so it's kind of like, you know, the joke about the bike shed, you know, versus the nuclear power plant where everyone has opinions on how to build a bike shed. Similarly, kind of everyone has opinions on how to do AI customer service.

And so I'm curious how you sell, given this, I'm guessing a lot of your customers think, oh, we know how to do that. It's not that hard. We hooked it up to a model. And, you know, we're actually very smart on this topic already, how you sell in that environment, where everyone has opinions. Yeah, there's like, I've never seen the, like, build versus biting play out more often. than we do today, especially where, like, certain, like, a lot of customers are like,

you know that meme on Reddit, I'm not like, or girls or guys, whatever, like, there's a lot of that words. Like, oh, you would never possibly understand as B2C shopping company. And you're like, really, I've never heard of such a thing. Sometimes, honestly, we just be like, hey, like, you know, Godspeed, you go and start building this. P.S., here's a torture test. When you think you've got something good, running these hundred questions to us, let us know.

Oftentimes, that's where they're like, yeah, okay, we think we need to buy your product. But I think there is a Everyone has this idea of like In a move to AI what can we definitely do And we can definitely answer questions like How do I reset my password? And again this is back to the whole That's such a small amount

What they can't do is actually have conversations And all that sort of stuff We're like we're like What is your opinion on the president And how they're performing And like a lot of times Well you don't want You know you don't want anyone to answer that question

On behalf of your company But I think a lot of times people Like they dip their toes It's almost like they fire the trace their bullet, they're like, yep, this seems like we're making great progress. And every AI product has this problem where you make epic progress in the first two weeks. And then you hit this wall, this plateau. And then, like, you know, two years later, you're telling people, oh, Apple Intelligence is coming in 26 or whatever, right?

So, like, in this case, a lot of people start the project, feel like they're definitely, don't need to buy Finn. We just help them understand the difference between a good bot and a bad bot, and then they come back and they buy Finn. So where is the Finn business these days? I'm curious both just how's performing on revenue metrics, and then are you selling it to existing intercom customers, or are you selling it to new accounts? How does it work? We're about 6,000 customers and are growing quickly.

Finn does about a million resolutions a week. We're charging a dollar per resolution so you can do that. So 50 million revenue run, right? Give or take. When we launched initially, we sold just to our own customer base. And then as we kind of progressed, we realized, hang on, moving help desk is a nightmare. Like you've probably done it once or twice, right?

It's a big job. It's a whole ordeal. And Finn is brilliant. So we're like, those people want this product but can't buy it. So we made the decision to launch, like what we internally call Finn standalone or Finn for platforms. So now you can use Finn on top of Zendesk or HubSpot or Salesforce or any of those as well. So basically Finn is available to everyone. And that's a relatively new muscle that we've been growing.

But it's actually, you know, that's kind of where we see a lot of the future growth. And so do you, is Finn, like you can connect your iPod to Windows for iTunes for Windows, but we hope that one day you buy a Mac and it's part of the whole digital hub strategy, or we're actually now all in on Finn the Engine, and whatever customer service platform you use is actually not a topic of huge interest to us. This is such a core question that we kick back and forth quite a lot. This is the offside debate that is currently be happening.

At least it's certainly one of them. The way we think about it first and foremost is the future is AI. So, like, Finn just has to win, kind of, like, at all costs, including our help desk. Weirdly, our customers are, like, they turn Finn on or, like, damn, this thing's good. Hey, net at, like, 65% of our support volume, maybe we don't need X, Y, Z competitor, and maybe we can go all in on your help desk, too. And we're like, okay, cool. That wasn't our game plan, but we're happy to help, if you know what I mean?

Right, I think, like, the actual, the battleground we care most about, genuinely, it has to be the AI agent. That's the one we're, like, we care about most. But it does produce a lot of, like, demand for the actual Help Desk product, too. I'm curious what your AI stack looks like where concretely, you know, what are the models or collection of models and prompts and everything that you are using in production? How do you handle model upgrades, given that, you know, the behavior is changing so much underneath the hoods. How deep do you go in terms of developing the stack yourself? Maybe you can talk about the stack.

First thing I'd say is obviously Finn isn't like one thing. It's like 27 different things or whatever, right? So every one of those is like whether it's the same. summarizer or whether it's like the re-ranker or the retrieval engine or any of these or the direct answer which is where we actually go and formulate the answer. Every one of those is paired with the fastest, cheapest, lightest, most accurate LLM that can actually do the job reliably, like very, very high reliability. So like that means like there's no one particular model. So our primary partner will be anthropic for Claude Sonnet. We've architected it such that like we can plug and

play various different pieces. Whenever a new model comes out or honestly a new idea for for new architectures and hey, we recently launched the ability for Finn to do complex queries, which would be like, say, go and issue to refund and update the name on the utility bill or something like that. Whenever we have to change the architecture, we have this kind of like arduous torture test of like thousands or at least a thousand CS scenarios

where like we have like, here's the question, here's the context we're provided, here's what like the current Finn answer to this question is, here's the best available human answer that we know of, and then basically here's what this new version would offer us. And then so whenever we say like a GPT5 comes out or something like that, we're like, you know, the reason we're not just, a lot of our competitors are kind of quickly, oh, we're never running GPD5.

And I'm like, oh, I'd take a beat on that one. You know, like you shouldn't assume everything's going to be great for your use case always, right? And so we ultimately, we have to run it through this pretty, like, expensive test to work out where the edges are. If it's scoring higher resolution, right, we need to understand why. Because it could be just that it's like trying more stuff. But that could also, the shadow side of that could be like excess hallucinations or whatever. So whenever a model upgrade comes, we have to trigger this whole thing. But when we launch fit, it was like 25% resolution.

Today, it's like 65. We've been increasing it roughly a percentage point a month, give or take. But very little of that is actually because of the upgrades or the bumps from the models. Genuinely, I actually think, and I say this with a lot of respect and love for the CS craft, I actually think we've had enough intelligence for CS for quite a while. In fact, we published some material on this on our research blog repost recently. Like, when you look at, like, you know, people are saying things like, oh, like the latest whatever, you know, GROC can compete a mathematical,

mathematical Olympiad, like level seven or whatever, we're like, right, I think you can probably do most CS, you know? So it's often not a lack of intelligence, is the reason why we're not 100%. It's because they're too distracted by any. Exactly, yeah. A lot of the wins come from, like, honestly, better architecture, better, like, tailored models or, like, changing into UI can change exactly how things work.

And then sometimes you will get an occasional bump here and there from a model spot. It strikes me that a lot of the how you include the amount, the account context, and the amount of account context you include is a big part of the secret sauce. Perhaps, but it varies customer to customer. It really is one of these areas where it's a thousand lead bullets. It's not like a single silver one. If you look at a resolutionary graph, there's no pop, give or take one or two little tweaks. It's mostly just, hey, we ground out through, like, you know, optimizing this prompt and changing this handover.

we ground out another 0.7%. And you see the AI team celebrate that on the balcony on the Friday, being like, yeah, 0.7 up, whatever. It's hard to work out exactly what bits. And then there's obviously multiplicative benefits. You might have a win over here to cost you something over here as well. Yeah. How deep down the stack will you go?

Like what's Intercom's version of Apple Silicon? That I don't know for sure. I mean, like we're going to chase any edge we can get. Right now, I think custom models is definitely where we're going. And that's like a large investment from the AI group, which is like the most contested resource that we have. Every bit of work they're doing is finding a new edge in resolution rate or resolution quality. So right now it's paying out pretty well.

So I think we're going to kind of place all our chips there until something changes. What does selling AI look like? It's quite difficult. It's difficult in marketing and selling because I think... Because it's so crowded and noisy? Well, there's that, but it's also, like, it used to be the case. And for sure, Intercom used to be one of these companies where we are a product looked the nicest. So all we had to do was the age old, you know, blah, blah, blah, reinvented.

in a big sexy screenshot. And you can still get away with that in certain domains. Like, linear can get away with that because their product is the sexiest. I think with AI, everyone's chatbots look the same. Everyone's kind of copied our messenger. Everyone's kind of like roughly like converging on a certain UI paradigm. And so you have to ask like then when we say like, you know, we are the best AI agent, like what do you think all the rest that we're saying?

We're the worst? Like no, of course. So they're all saying this. And then everyone has the same screenshots because it's like, look what we do inside a chat window. So you're like, all right, how do you actually out market and then how do you out sell? And one of the reasons we launched to the Fing guarantee, this idea that we'll pay a million dollars

if you find something about performs us because we're trying to stress to the market this idea that we actually believe in our product to a ludicrous degree such that you should engage with us on any sort of bake-off you're doing. But I think from a marketing perspective, it's really hard to stand out.

So all you can really do is rely on backing up your claims as hard as you can and obviously customer testimonials. Selling is harder. Because I think, again, in the olden days selling SaaS, and the olden days being like three 20-22. It was kind of like,

RUI is nice, theirs is ugly, here's a feature-grade checkbox. We've got 24 checks. They've got 17. D-7 matter, we're in. You know, like that was like, obviously I'm skipping over several steps,

of course, sales and Eval would kill me, but you get the basic idea, right? And I think now, selling AI is closer to selling like infrastructure in a sense. It's more like... Our cloud is better than their cloud. Yeah. And our performance criteria are better. It's like at times it might feel like,

you know, Intel AMD or at times, it's like, you know, it's our response times versus theirs or whatever. But like you're ultimately coming into it like with a battle of metrics and stuff, like our resolution rate and our C-Sat versus theirs. But then people say, well, why? And then you have to then explain what's actually happening beneath the surface a little bit so that people can actually get a bit of conviction. Right.

Other than just like trust us or like, please just go and try our product because it's not that easy to try a Finn, you have to still have to like turn a lot of keys and open a lot of APIs and stuff. So like the challenge genuinely becomes like, how do you have a sales team that's actually able to speak with a good degree from the already about, like, AI. It's funny you mention this. We have this specific problem at Stripe, which is invariably, when people switch to Stripe from a legacy processor, they see a significant revenue uplift. And you think, like, businesses are in the business of, you know, finding ways to get more

revenue. You think they'll be really interested in this. And we have this thing that sounds shockingly good, which is if you just move over to stripe, you start immediately getting more revenue. And it basically comes from two places. One is conversion on the actual point of payment, that if your mobile app or if your web flow is kind of janky or doesn't offer the customer's preferred payment method or something, they will abandon.

And if you just look at the abandonment rates, you know, if you're seeing a kind of only 85% conversion rate on that form, then obviously getting it up to 90% that's a huge deal. And those will be very high numbers. Most businesses would not see anything close to it, a 90% conversion rate on that form. And so there's huge improvement possible there to make the customer, kind of checkout experience as smooth as possible, and obviously things like Link, then where you're not asking people to re-enter their payment details, that delivers a big off-lift. The second one, which is even crazier is after people enter their credit card details, frequently charges are

denied, kind of spurious. And so your bank thinks that it's fraudulent because, you know, they haven't heard of this merchant or whatever, and so they'll deny it, or they'll think it's fraud, or whatever like that. And we, through many, many years of optimization, have gotten good at ensuring that if it is a valid transaction, that that is not too much. What all that adds up to is that we can make the claim and we've seen it play out again and again, we just have Hertz switch for all their e-commerce payments to Stripe,

that when people move to Stripe, they see a significant uplift in revenue. That's surprisingly hard to sell. Yeah. Because everyone is out there saying, you know, we are the thing that gives you more revenue. We've had the exact same thing where, despite you can have all the numbers and all the case studies in the world, it's just, it's hard to sell because it's undifferentiated as a message.

I remember even when we switched back to Stripe, either you or Patrick were saying, like, oh, well, don't forget to do Link. And I was like, really, I was like, is this really a thing that, like, you know, people have, what, some businesses for gotten its credit card or something like that, and you're going to be able to renew it. Right, it feels unlike that. Yeah, it just feels implausible. But, like, at the same time, the data is not, like, not really debatable.

Yeah. I think people like to be able to explain it to themselves. And, like, you know, I think, you average wouldn't, I was talking to a guy who runs procurement and you're saying, like, you have to understand, I'm just getting bullshuted to all day. You know, it's just all day, relentless, absolute nonsense in my face. So, like, if you think that, like, you're like, ooh, 65% thing is going to stick, it's not, it's just like, I take it, I divide it by 10 at this stage. You know, and you tell me, oh, you're going to save me $2 million in CS salaries or whatever. I'm like, yeah, maybe in three years time we'll see $200,000.

You know, that's the kind of the default posture for a lot of these people. I think it is just, it's like they've developed quite an inverse reaction to, like, marketing. People do not have enough empathy for the procurement person who just has to endure nonstop nonsense. Absolutely garbage. That's funny. I mean, this kind of gets to the topic. You and I have discussed a lot, which is product marketing. How do you effectively product market in a world of everyone making claims?

Like, one is the guarantee that you're a guy's a dollar guarantee. Has that worked? It's certainly, it's worked from a point of view of, like, I don't know actually know how many people are in the program right now, but I could say, like, what has worked is like. It's landed the message of we stand behind the problems. Totally. Being able to say, like, here is the reason why you can buy, you can buy it.

I think that's a strong message. I mean, obviously, like, being able to point to real customers or real results, sort of like, and you can say, hey, go talk to Natalie and newly or who, you know, or whatever company you want. Go talk to that person and ask them because, like, that's their name. That's their job title. They work there. Yes, yes.

You know, with 6,000 customers, it's kind of, it gets more believable as the numbers kind of tick up. But I, so, like, I guess either, you know, you can make crazy guarantee claims. You can, like, just point to a lot of successful customers. For us, it might be different depending on your domain, but for us, like, you know, it's not like we can. show you you. We can show you like how you're a beautiful back-in product and you're fancy reporting and all that. But that doesn't speak to the core thing someone's buying when

you're buying AI off you is to some degree a replacement of work that they had to do. And the two things they care about are how much work are you going to do for me and how well are you going to do that work? And you basically need to product market both of those things. And it's very easy to say, we're going to do all the work and we're doing really well. So you have to actually really help them understand how to appraise the scenario. Like sometimes we put time into actually helping people identify when they're being lied to in a sense. So we will say, like, hey, try this type of question or ask them about this. You know, help you almost kind of teach them to be much more conscientious buyers.

Because we know the more informative buyer, like that suits us. It doesn't suit people who are just kind of like jazz handsing their way to an AI product. But like, yeah, it's a difficult one. Ultimately, like five years ago, I would have been like, well, the trick, John, is gifts. You know, have you ever considered using movies on your homepage? You know, that's really engaging. None of that works anymore, right? Because I just think what you're selling is basically,

it's like an iceberg. Like you're saying this little bit of like upfront UI of like, here's what actually happens for your customers. Doesn't that look nice? And you're selling this like gargantuan pile of work beneath the surface that is like, hey, all of the human toil goes away if you make the switch. Yeah, I can see that.

What are your other pet peeves when it comes to product marketing? Actually, do you want another pint? Yeah, sure, sure, sure. See, again, this one, did I not let it settle for long enough and then you have the small head? Like, is the settling... I actually think your one's going to work out perfectly. Is the settling time load bearing?

Okay, so what do you? your pet peeves when it comes to product marketing? I think the thing that still kills me, it's still very common, is marketers that love marketing. So rather than actually saying anything useful or specific, you'll get, like, forget everything you know about email. You're like, okay, what am I buying?

Or like, you know, transformation reinvented. And you're like, cool. Sounds like I'm going to reinvent some transformers, like, but like, what's actually happening here? I think there is a general, still type of thing where my screensaver on my laptop is like literally a typewriter where somebody said, what are you actually trying to say? I keep that there as a reminder of like just

nine times out of ten, the best marketing comes from just writing the thing you want to say. Because like, do you ever get into a Google document? Like, our goal is that by reading this document, the reader will know the following. And I'm like, cool, can we just say that? And so, like, why is the 2,000 more words here? So, like, I think, I guess, like,

speaking in a way that sounds, like, great to marketers is, like, probably the thing that kills me most because they don't marketers, especially in the AI or they don't really necessarily understand the depth of what's actually happening with the AI or whatever. There's a funny stat the og of you used to quote, which would say something like of all the winners of the Cannes awards every year, something like two-thirds of them would lose their contract that year because

the thing they won the award for was not actually effective in market at all. And I think there's such a repetitive pattern there. Like where a lot of people, like, they will look at, say, a stripe or a linear and they'll be like, all right, we should just do that. And you don't really, like, a thing that people don't get is like, everything means something. And this is like where own, our CEO is like so differentiated. It's just like, every single decision we need to. we pick here, what photo, what icon, what typeface, whatever. It all sends a message. Are we conventional or not? Are we futuristic or not? And I think whenever I see folks just copy-paste somebody else's branding, even in a sort of like,

oh, we'll change your homework along the way, I think what they're really doing is saying, we don't really understand what we're doing here. And that's why a classic of this is, you know, whenever an incubator spits it and a new batch of startups and they all basically have right-hand-side screen shot, left-hand-side tree bullets, sign-up button, whatever. You're kind of like, okay, cool, but have you actually thought about what you're trying to save the world. There's also a thing for startups where they probably shouldn't look at what established companies are doing.

Because, like, Stripe for so long we clung to making sure that we had code on the homepage and people who are like, you know, if you want to accept credit card payments for your website, like, we're the place to come. And at a certain point, most of the relevant people come to your page actually know that you could do that. Yeah, yeah. Experiment a little bit more. And, you know, Salesforce doesn't have to hit CRM so hard on the homepage because after

20 years, they've earned the right to talk about Einstein a bit. oftentimes like a startup has a great idea for a great product and they pitch it. And then like six months later, they work on some new feature. And in their heads, the new feature is the big thing that they're so impressed with. Not realizing that 99.4-9s of the world have not even heard about the original thing yet. But there they go, destroying your original pitch by being like, I know, we've got blah, blah. I'm like, dude, no one's even heard of the original thing yet.

And here you're pitching some nuanced take on some extra feature. Yeah, yeah, yeah. Speaking of David Ogilvy, you've read on advertising. Yeah, yeah. What is it? It was just like, that's such a beautiful book where all the marketing copy in it is so good, like the rolls Royce said of, you know, the only sound you'll hear at 60 miles an hour is the ticking of the clock. But somehow that, yeah, it should be mandatory reading for all product marketers.

Absolutely. What kind of person succeeds in product at Intercom? When we set up Intercom originally, like we were kind of like building one thing. Once we forked out to building many different areas like sales marketing and support, I think we gave a lot of freedom to product leaders and sort of say, you own the sales product or the marketing product. And I think the folks who succeed there are like, they have to have, like, decent taste. And I don't mean that in some lofty abstract way, but I mean, they have to, like, use good software,

identify good software, ultimately know how to, like, pick one out of the bunch in a sense, right? Like a very common interview question ask people who are like, what apps are on your phone? What's your favorite app? And the amount of times someone's like, oh, you know, I never really thought about that. And I'm like, oh, so, like, what's your favorite song? Like, you know, like, I'm sure you care about some things. Yeah, yeah, yeah. Certainly if you're interviewing musicians, they should have the favorite stuff.

Yeah, yeah, you'd like to think that, but they also probably have a favorite app, too. So I think like taste is a kind of prerequisite. And then I just think like the confidence to pick a direction and then the, you know, we say at Intercom, we often say shipping is an act of like confidence and humility. And what that means is like, you have to be confident enough to put alive and then humble enough to take the slap in the face when you got it wrong totally and react to that slap. Don't like kind of be like, no, it's not me, it's the customers or don't get it right. So I think like we need like high taste and then like confidence and then like ultimately understanding

that like in the market and recent sense like a product is a conversation. with the market. Your launch is like your opening bit and then you have to basically adapt and react to what gets thrown back at you, which might drag you in different directions and then you need to have the, again, the confidence to prune certain things and be like, no, we're not building an attribution engine. Yes, we'll take on some feedback on the CRM side. But I think, like, the, you know, a lot of product managers who don't work out for us are like a lot more spreadsheety and like, you know, they won't take a bet, they won't take a gamble, they won't take a stance, they'll just be like forever mired and like, well, the data suggests

and they're just trying to hedge their breath through it. It's just not the sort of company we are. I think we kind of believe in having an opinion about a space. Well, and the second part of what you're saying, if I'm hearing you right, is the good product managers actually can listen to the market. They have to be able to, yeah. And hear what.

Yeah. I think about this a lot in the context of tech companies where Stripe's first operating principle is users first. We think that actually paying attention to what users tell us, tell us in every sense, you know, via revealed preferences in the data, via just like when we actually have conversations with them. We start every week with Monday morning meeting. The first thing we do is we actually host, you know, with the intercomplicate there recently,

we host a customer to tell us and give us a report card. And, you know, it's not an A, you know, it's seldom an A. You know, they always have things they want to fix. And they're very pragmatic things that they want us to improve. There's no overcomplicating. And then when we do our weekly, all-hand this fireside, we also bring customers to that. But I feel like there's a problem of over-complexifying things and under-talking to users in Silicon Valley, where, yeah, it's a bit too much celebration of the individual kind of product vision,

or a bit too much, as you say, trying to delay your way out of it. And if you're a product manager and you're not talking to many customers each week, something's probably wrong. I bring that up because the whole original Intercom product was a way to, to talk to customers. Like, this is, this is kind of your guys. Absolutely. But would you agree with that diagnosis that a lot of tech products would be better

if people simply talk to customers more? Yeah. I mean, like, one of the ideas that stuck in me very early on him was like 2009, 2010, I'm going just like a deep cut or whatever. But there's a guy called Jared Spool, who's like a famous UX guy. And I was on this tread of like interaction design association type people. And somebody wrote this really long, like, you know, hey, I've shipped X and I've shipped Y.

I can't work this out. There's anyone have any speculation as to why people aren't doing this thing even though I make it really obvious on the screen. And he just replied on. He's like,

have you tried asking them? And I remember, like, at the time, I was like, right on. Like, it was like, it felt like a revolutionary thing to say. But I find, like, you know, I shared this piece a while ago, which was like the questions I ask

in every single product review. Kind of like, so you can kind of either get ready to meet me or like just ideally other people can replicate. But question one is basically what did our users say about this when you showed it to them.

And everyone has to have an answer of that question when we go in, like, I'm like, okay, well, what did the user say? And I need to, like, understand that. Because if you're not actually asking your users, what are you doing? Like, you know, the only validation we have is the market. I do think in the valid is, and like, well, I'd say the value, but like, that just basically means in the tech industry. I mean, there is this epidemic of, like, hiding behind your data and, like, what can

me instrument and how many different, you know, mixed panel of dashboards can prove to me that this product should be working, just ignore the fact that it isn't or whatever. I think there's something kind of just fundamentally broken there. And interesting, you say like Stripes for value as like users first. I'm just curious. Is that deliberately, the word mean every word you guys say is deliberate, but that's deliberately users as in do you mean like pointy-clicky users or do you mean customers or do you mean prospects or do you mean like...

Yeah, we deliberately chose users because we just meant the people using the product as opposed to customers, you know, if there's a buyer versus user distinction, we want to focus on the people who are actually using the product, the people who are, you know, managing fraud within the business or, actually responsible for increasing conversion or something like that. So that was why we chose that work. Yeah, no. It's not perfect.

It makes sense. Because I just find oftentimes, if you want to perfect a product, you talk to the users, if you want to expand your market, you talk to prospective buyers. But whenever I like, even in my own portfolio, when I talk like, what are you actually doing? Like the businesses that like are, how would you say, prematurely talking to more prospects when they have a load of unhappy users are guaranteed this kind of miles wide inches deep, like, messy product that doesn't actually satisfy anyone.

But they'll get there kind of like one promise at a time. Oh, we'll build that for Johnny and Johnny will sign. And we build this for Jenny and Jenny will sign. And like at no point did they have one happy customer. What they have is like a marauding churn bomb of a user base. It's funny you say that. It feels like many tech companies over-rotate on sales feedback, which will by definition be from the marginal user.

And they're marginal in two senses. So you've all your existing users, you know, that you're dancing with the girl that bring you over here. And then you have this future potential user who, firstly, by virtue of the fact they're not already using you. Maybe they're slightly outside your wheelhouse where the use case isn't perfect or something like that. So maybe they're not quite as good a fit as your existing customers. And then also, by virtue of the fact that they have a whole existing way of doing things, when they migrate over to your product, they'll do so in a bit worse shape of integration, where maybe they'll only use one of the four features or, you know, not everyone in the org we bought in,

versus the people who grew up on your product. And so maybe just restating what you're saying, I'm always struck by people are way too focused on, we tried to win this big new shiny enterprise account, and they didn't have feature X, and so therefore we're going to develop feature X, as opposed to you've all these users who grew up in your product and really like it, but they wish you had fix A, B, and C.

And just the nature of the fact that sales gets more airtime than account management, essentially, It means people really misprioritized where they spend back. Yeah, and people take NOR for granted and think that net new revenue is hard, right? And I think one of the things that we see a lot of is, like, in terms of like working out for your current customers, like we use the phrase permission to innovate and permission to expand in Intercom, which is basically like you have permission to innovate when your product's pretty good. Like, is in the, okay, let's work on V3?

Yes. But like, is V2 in good condition? Like, or, you know, and then permission to expand is like V3 isn't actually that exciting. everyone's happy with V2. Now I think we can try to do something new for customers, like expand our share of wallet or whatever. But I think a lot of people try to solve revenue growth with like aimless product expansion.

They just try and increase the share of wallet for the people who are stuck with you. And then they convince themselves, they got PMF, or like, you know, that they have like some sort of a good product because they're kind of like foie gras style, force-feeding new features down the trots of their trapped users. And they're like, you know, we're doing great, but they don't realize what they're actually doing is making

their current product so messy that they're destroying the hope of future revenue because, yeah, you can force your current customers into whatever upsells you have or whatever but your product marketing along the way is getting really difficult because all these features don't make sense and they're just kind of like, you've tried to do this land and expand thing but you're actually just

expanding and there's no landing happening in the new product and then you end up trying to twisting yourselves and not. And a lot of startups, like, you know, Jason and M can use of this thing out like from zero to one's impossible, from one to ten is hard and from ten to one is inevitable. Like I think a lot of people, I don't think that's proven out to be true

as much as it was back when he said it. I think a lot of people get stuck in some sort of glue around, somewhere around the 10 million mark where they don't know how to get the next 10,000 logos. So they just try and milk the revenue out of the existing customers. It's true, like just forced product adoption of new stuff. Like, you see a log. Here's your co-pilot.

I know he didn't want it. But here you go, like that type of thing. Days is describing here how they've transformed Intercom from a SaaS product to a frontier AI business. And to do so, they had to pivot, not just the product, but the monetization model as well. Because inference costs are so significant, AI-powered companies tend to charge based on usage

rather than just allowing for unlimited plans. It gets complicated and really multidimensional very quickly. Now, fortunately, complicated and multidimensional is what Stripe billing specializes in. Our usage-based billing engine can ingest up to 100,000 events a second, 100,000 events a second. So AI companies can monetize products based on real-time, customer usage. We're powering consumption billing for companies like Figma, Cognition, and

tons of other leading AI applications. Our usage-based billing platform has grown 145% so far this year. So whether you're changing your business model like Intercom or starting a new product from scratch, your business strategy should dictate the billing system and not the other way around. For usage-based billing, check out Stripe billing. As you think about the prototypical $10 million dollar revenue B2B company. Yeah, what are the common mistakes you see and what do you think the actual path that more of them should follow is?

I mean, the biggest problem of mistake is like not aligning your fundraising with your time. I think a lot of folks, like we got a little bit over convinced during the era of cloud that every business had a right to be like a unicorn. And so there's a lot of businesses whose

idea was like totally fine. But actually they should have gone on base camped it more so than they did because they raised on the assumption there's an easy path to like hundreds of millions. There should be more small, profitable $30 million revenue companies? Well, yeah, exactly. And I think a lot of these businesses would be great if only they didn't raise 20 until their investors that you're going to easily be worth a billion or whatever.

So I think there, does a genuine mismatch there where I think people have overstated, like, how big this idea could get? You know, I know all we do is like time tracking for dentists in Delaware, but like, believe me, we're going to be a billion dollar company. and you're like, okay, well, one of your restrictions is going to have to break here. So that's one problem, which is more like kind of business model

and venture ambition. The other stuff I see is like, it is kind of like not focusing enough on the senior, the majority of your customer's value. Like, it's easy to sell you. The best business in the world is like one line of code that all users execute and you sell it to all users, right.

They're like, you know, the sweet spot. It's hard to do it in a differentiated way because, you know, obviously people learn that line of code. And that's where you're getting a lot of these horizontal products, they say something like a loom or whatever, they're like a brilliant, they're a piece in everyone's workflow, but they're no one's like end-to-end workflow.

I think they can do well too. But I think the challenge is like when people, rather than nailing a specific small thing, come back to the earlier point, rather than like saying, hey, let's get really good at X before we go beyond. When they kind of prematurely expand, I think they forego all opportunity of like kind of being the best. And if they picked a really important area first,

then they don't say it out loud. What they're saying is it's okay to not be the best at the most important thing we do. And I remember, like, I remember, I think it was in your office on, you know, in Friday. And I remember at the time, it wasn't, it wasn't obvious to me that you weren't going to expand and do some sort of like, you know, peer-to-peer transfers and people pay-ball. And I remember, like, you guys had the distance. We're like, absolutely not.

We care about helping businesses charge. And, like, there's a real harsh discipline you need to have to, like, just basically say no to all of the surrounding opportunities. I think a lot of people, that discipline is the first thing to go. Yeah. When you hear about competitors, you're going to hear somebody. else encroaching on your space. You're going to have this really weird broad view of all the things you do.

Like I know we just do like whatever it is, Gifts and screenshots. But actually when you think about it, we're a global creativity platform. And there's this premature view of themselves as being massive. And then they feel they need to raise off that and they need to expand into that. But I think like at the core of every great business, every great SaaS business,

but in the future AI business is something that they're just truly world classed. And it's like it's not some sort of 80, 20 tradeoff. They've just basically said, will be better than anyone at this, right? Like, you take it, like, linear. It's basically, like, they have literally the world's most efficient UI for, like, for product management, and they all observe project management.

And they've just gone really deep into, like, all of the surrounding adjacencies you would need to actually do that job really all. Figma is just an amazing creative collaboration machine. Like, everyone who, like, has done really well, they've picked one thing and just gone really hard, really deep, really far on it. They haven't, like, prematurely blown up

and gone in seven different directions. And I also think there's a weird celebration in the valley of act two. Like, the valley is obsessed with finding second acts that are totally unrelated to the first business. Like the number of people who bring up like, you know, oh, and we like invent like an AWS. It's like, okay, you need to use a non-clay example if you're going to make that argument. And the flip side is, you know, you're mentioning Figma, which thinks a great example, where that market proved to be way bigger than people might originally. have thought. You know, my favorite example of this is

Nvidia, where they are the world's largest companies, and they started in the 1990s making GPUs. And if you're an investment banker trying to, you know, make a case for how Nvidia can be a really big company, maybe you'd say, oh, well, and we can expand into maybe we'll actually, you know, make our own gaming rigs, or, you know, because it was all gaming at the time originally. You know, maybe we'll make gaming consoles or, you know, we'll expand to some larger markets, where actually what transpired is, it turns out the GPU

market is quite a lot bigger than people thought and being, you know, the best at GPUs is a really valuable prize. Yeah. And you can't rush it, you know, it'll emerge. But yeah. And they could have killed themselves if they had gone in every other direction, like, right? And they would have lost their edge in some sense. Figma is a great example for me of, like, permission to expand in that.

Like, they literally nailed to a point of like no credible competition, this idea of like just, you know, the Photoshop killer, basically, let's just say. And now they can talk about like, slide. and text to app builders and like every other dimension they want to go. And everyone's like, yeah, that's great because you guys make great software. I think you have to first be known for like, I'm trying to think like, if Stripe launched a payroll product, it would carry the brand of Stripe in the sense of like being, well, it's probably really good, really reliable, really fast.

But maybe it probably has really nice APIs. It probably works really well. You can almost impute like all the ideas that would be carried into it. And I just think like you have to get to that point before you have permission to make that. Like obviously it's a lot easier with some like stable coin or whatever. But what kills me is when I'm like, you know, I don't even want to like name a weak SaaS company, but like pick your favorite, like, mediocre SaaS company and anything. Like, is there any direction you would allow them expand in your head?

No, like it's a short answer. Yeah, yeah, that's interesting. Who are you really excited to adopt new products for versus who are you steering clear of the new products? Like if linear launched a, I don't know, let's just say a source control to them, like, yeah, it's probably going to be really, really good. Yeah, and like, Seth Godin has this hilarious point where he talks about like the value of brand, once it's weaponized. He describes like Nike and Hyatt hotels.

He says, if Nike opened a hotel, you can close your eyes and see it. You know exactly what the corridors are going to look like. You know the vibe of the whole place. You know everything. It's going to be, if Hyatt launched a sneaker, you're like, what? And it's just that's the difference. Because Hyatt has a logo and Nike is a brand. And that's the difference, you know.

A version of this actually maybe quite literally is I don't know. So Equinox launched a hotel. Yeah. It's a pretty good idea because the design center, for the hotel is you just want to be able to get a good night's sleep. And it's funny how that's like a differentiated product hitch in the hotel space. Don't give me any of that other shy. I just want to go to my room and not have like super loud noise outside the window

or like weird light coming into the room. You just want to be able to get sleep. Precisely. Yeah. I thought that's funny. And you're mentioning kind of Stripes expansions. And so this made me a good segue into your pricing model change. You guys are a poster child for the move from per seat,

SaaS pricing, the old way of doing things, to usage-based pricing. Maybe you can describe a little bit about that and then how you implemented it and what you're doing with Stripe. Yeah, sure. Our pricing journey is long and complex. And a lot of your listeners or viewers will know. Indyricom pricing is a charge topic at Instagram.

Not anymore. We've turned a corner. Let me just back up a bit. So when we had like two diverse or product strategy, were trying to do sales software, marketing software, support software. And sales software is typically sell-based and leads created. The marketing was charged by how many contacted people you understand and support were sold-by seats.

So we had this extremely, just to say detailed, but unnecessarily complex pricing setup. And we kind of, we lied to ourselves and said, don't worry because there's always going to be human to help people navigate this because you're never going to have to self-serve this. But ultimately, people are just like, I have been refreshing this for like seven minutes and I can't understand a word of it. And that was just one of the few things we got wrong in our kind of first move-up market. When I own return, one of the decisions he made was just like, hey, we need to sort of our pricing. And we handed it back, like truly handed back, I think I have a 50 million of revenue.

I think it's somewhat controversial, like with the board, with investors? Like, we had support for it. I think it was like people don't really underestimate people massively underestimate what it means of a really happy customer base. It's because word amount doesn't have like an attribution or a UTM code, if you know what I mean? So they don't understand how to think about happy customers. So making the decision to basically like, you know, kind of standardize on an easy-to-understandard pricing that's like fair, transparent, predictable, et cetera. That was the first decision that we made. This was before AI, right?

And that was like us returning to Stripe was a large part of that. In fact, as a small segue, like I think like a couple years prior I had said to you or to Patrick, like, hey, you guys should actually build as part of your product offering, a pricing page creator. I think at the time, I probably got one of those like thumbs up replies or something like that. I was like, yeah, whatever it is. It's on the list. I think you've done it since. We have. Yeah, yeah, yeah.

But like my thinking at the time was basically some version of this, right, you need to not let your customers go wild with pricing, right? You need to like actually put some sort of guardrails onto how they think about pricing. Otherwise, they're going to go and invent stuff that you guys don't support. And then you're going to move all your business logic. Pricing is writing checks. Yes, yeah, exactly. And once, like I remember, like sitting at a stripe mini all hands would ever explain like, hey, now none of our business logic runs true stripe.

And either you were practically was saying like some version of like, that's not a good thing. I think, you know, generally speaking, my advice to any software company is like, don't afford yourself too many degrees of freedom here because you'll actually cripple yourselves in a quagmire of complexity that you'll take you many years and ultimately like many tens of millions of dollars to get out of. It's a weird failure mode that every single company falls into, which is you start signing deals that have some super creative pricing structure, and the customer negotiates ABC, D&E.

And it's like it is built in Microsoft Word, but it is actually, it's just not built practically in codes because it just exists for this one customer. And it may not even be possible to build in code. Like sometimes it's kind of ambiguous or it's like, and if in the subsequent year this happens, then we go back to the prior year and we do an adjustment. There's a guy called Ricky and he decides with the discount.

Exactly, it's like a time travel component to the whole thing. And then they obviously have this, again, we see all customers running into it, these kind of manual billing issues where there is a guy who has to deal with all these like contracts that were agreed during the sales process. And so, as you're saying, an opinionated billing engine is actually pretty important, assuming you believe that billing should be automated. If you're happy, like manually getting out the calculator for every single customer month, then that's fine. And having a large deal desk function and doing all the work behind the scenes. Yeah. So, right, that was like the first piece of our pricing. And then the second piece was obviously when we launched Finn,

and it was like, hey, how do we charge for this? Because we're replacing seats. And like at the time, it hasn't proved it out this way fully, but at the time, Finn looked like it was going to be pretty cannibalistic to Intercom because it was like, hey, if we're automating at the time, what we thought was like 25% of your revenue, we assume that means like 25% less seats in the future. Or at the very least, what it would likely mean is the growth rate

or the NRA of the seats model will be affected by the fact that Finn's doing all the work. And now at 65% you'd expect to be even further true. So it was like, hey, how do we charge in a way that makes sense? And then also, like, how do we be aggressive? Like, as in we really wanted to, like, put a mark on the market. That sort of says, like, we're, like, very AI forward. And I think what Owen and then Darry came up, it was just like, hey, like, let's just charge per literal resolution. Like, every time we do work, we charge everything we don't, we don't.

And this is at a time when, like, AI was, like, you know, margin negative and all that sort of stuff. We're still working out how the whole world plays out. Today, we're really happy with our margins. but at the time it was like, hey, this could. It was a bet. Yes, it was definitely a bet. We made the decision, and I think the market responded really well because I think it was very clear that, like,

the single statement of, like, we only get paid when we do work. We don't get paid when we don't do work. It's from the same vein as the guarantee, which is just like, that's how you know that we believe in our product, and that's how you know our product works. It's been copied a million times since, but I think the actual decisions that we made in the run-up there are really, really important from a point of view of backing up our claims.

And then obviously, for a lot of our competitors, they're like, we don't really have a great way to respond to that. Because either our product doesn't work or we're kind of hooked on these really expensive resolutions. And we were totally throwing cat amongst the pigeons there, which has been like really well received by the market. And our customers generally do love it. It is funny, though, you still get people being like, none in that sense, ridiculously expensive. And you know, you're like, why do you think this?

And the answer is because some version of we don't know how to calculate cogs. Yeah, yeah. Yeah, yeah. How much the human's costing you? Yeah, exactly. And how much is their office costing you and all the other stuff? Yeah, yeah, yeah. But people like certainty. How do you get them okay with the variable components? You know, you can obviously, you can contract out whatever you want, right? Like, but what we offered people is like, hey, like, you know, most of the time people have, like, at least one or two years look back on like what, you know, like we've customers who spike for taxis and customers who spike for Christmas or whatever. And we can basically say, like, hey, let's like, let's contract your base rate, let's talk about overages for the months you need it.

And that's like, that totally works. What we're basically saying is, like, yes, you don't have predictability in the sense of it not being fixed, but you have like you can model it based on what's happened in your history. And it's only really like brand new startups that don't have a clue what's going to happen. But like they're not usually worried about this. Yeah, yeah. So you're using a relatively new product type usage base billing for this. How is that you migrated from Zora for that?

How has that process been? Yeah, I mean, I would say, just to go back to the earlier, like we afforded ourselves too much complexity. And we kind of codified that complexity in Zora. I guess the best way to describe it is we just twisted ourselves in knots, you know. And it got to a place where we actually ended up like Kieran Lee, who is our CTO here. He ended up actually returning to the company one mission, which was like, I am going to un... Fixed better.

Yeah, exactly, to fix this, right? And like, it worked, right? But it was, it was a substantial amount of work to like unwind so much. And then they were like to kind of like deconstruct so many of these like a car Microsoft Word style deals into something that was a go forward, acceptable or whatever. And then obviously moving towards like a clean, transparent seat-based pricing and then just layering on usage base on top was actually pretty simple in the greatest scheme of things. And like all the stuff that we needed, you guys were ahead of us on like, you know, discounts for volume, etc. All the sort of obvious stuff people would push for it. Yeah, yeah.

Is this just where pricing in this new world goes? because obviously no one buys labor on an unlimited basis. And at least for the moment, the inputs of AI do actually scale with usage for a significant basis. And so it feels like you have to have some usage-based pricing. This is certainly the bet we're making, where, again, the reason that billing, kind of the top thing they're thinking about

is making billing work well in the usage-based world is it just feels like many products are becoming much more expensive to serve and therefore have to have a usage-based component. but is this permanent or, I don't know, does the AI get cheap enough that maybe we go back to Unlimited plans or, I don't know. I don't know if unlimited plans will ever, well, I don't know. Here's how I think about it.

I think ultimately all AI has like two vectors. There's like how much work you're doing and how well are you doing it. And the volume of work you're doing, it's almost, well, actually both of them are going to be proportional to how many tokens you're burning, whatever. So you're going to want to factor that in, especially if you're a consumer app as well, we're just going to go nuts.

So I think like you have to like have some, you know, I'm not a fan of like cost plus pricing, but like, but it does place a kind of a lower band on what you can do here, which is just like how, you know, unlike SaaS, you are actually sending money at the back door as well. So I think you have to have something that's proportionate at how much work you're doing. And then I think aside from that, you have to charge consistent with like how much work are you displacing.

I think that's where you can sort of say, hey, like, you know, for us anyway, like if you take an average person who sits in a seat to do customer service, If they do, like, let's just say they do 20 conversations a day, that's what 400 conversations a month. When we were thinking about how we charge, we're like, hey, well, if that person does 400 a month and, you know, fin does 65% of that seat, we're still up because we're only charging, like, whatever, $90 for the seat. So from our point of view, it was like an obvious and easy swap. I think for a lot of businesses, it might not be if your AI doesn't work or it's spurious or like its value can't be articulated. Like, isn't it cool that you can now dynamically summarize a GitHub issue or something like, you're like, cool, I don't know how much people will pay for that. they don't know either.

Or like, hey, you can now generate random graphics in your newsletter tool. It's like vitamins versus painkillers, AI pricing. Yeah, and like specifically, like in this case, the painkillers have a very strict, like, if we don't do it, a human's going to do it, and we know exactly what they cost. And the vitamins doesn't have anything approximating that.

So not only is it a nice to have, it's like, I don't even know what it's worth. I saw a while ago, like someone said, like, when studio Ghibli came out and everyone was like using like that, someone said like how the Fiverr.com equivalent of all these things would have been like trillions of dollars and you're like right but no one was ever going to spend that so there's no sane way to actually talk about what actually happens here I think it was Bern Hobart who said that

you know when you're tied to business outcome that business outcome is usually done by humans I think it's going to be really really easy to join to make a business case for saying swap this over to AI it's better faster cheaper yes I think when your AI is not tied to business impact or is like debatable in quality or whatever I think you know you end up with these people who are just like I was just take a tenor on the seat and see what happens. Yeah.

You know, so it's like, you can have a normal seat or an AI seat. Yeah, yeah, yeah. You're kind of like, I hope no one uses

the AI too much. Yeah, yeah. You're permitting yourself to build weak AI stuff if you do that because you're not pushing yourself to say, hey, we need to articulate the value of each incremental usage here. Well,

when you talk about this AI pricing dynamic, one thing that really strikes me is just how fast AI companies grow from a revenue perspective. So I just saw Mattie from 11 labs. We actually had a great session at our customer event in London, but he tweeted that they've just passed 200 million in ARR, and that's two years after founding on it, maybe three years after founding. But in my day, businesses didn't do that,

and it's really striking for me how somehow they seem to climb the revenue rounds much quicker. I know. I mean, you guys would Finn is another example. Yeah, for sure. We forecast, like Finn will be 100 million probably early next year, whatever, and back at home. Yeah, from when, like starting from...

I don't know, probably about two years, somewhat like... Yeah, yeah, so two years. 100 million in the Iraq. Like, when we started, probably when you guys started, like, that was the threshold to go public. Exactly. Yeah, yeah. It used to take a long time to get to 100 billion in Iraq.

It was like seven years. There used to be a lot of money. Exactly. Back in the day. But yeah, it's the acceleration is more near. There's like, Maddie's, you know, 11's a fantastic product, right? And it's a great. It's a great example of like, there's like four kind of, if you like,

horsemen of AI products that I observe whenever I'm investing. It's rare you see all four. But the things you want in an AI startup, is kind of, one is like, is the revenue backed by usage? Like, and that's why I love usage-based revenue, right, as opposed to like, yeah, you know, shelfware or pilotware. Yeah. You know, okay, we sold it to the two guys in the corner and they're going to put it alive

someday. So, like, you want revenue backed by usage. You want the usage tied to a real business impact. So that's the mission critical, you know, as in like, if you're building a phone product on top of 11, like, if that doesn't work, that's really bad. So they, so it's critical. The third one is, obviously, you want deep AI, deep differentiated AI. It can't be a thin wrapper.

And then the fourth one is like, yes, you actually want positive. unit margins and all this, or at least a clear path deposit of unit margins if you're not there already. And I think when you look at so much of the AI landscape, you'll see so few businesses that evolve for. It's such a rare sort of air to be in, to be like actually, hey, we're doing a real thing, we're real differentiated AI. It really matters to businesses and we're making money off it.

Most of the time, when you hear about these, well, we went from zero to six million overnight. It's kind of like to generate JPEGs over smurf or whatever. And you're like, all right, cool. I'm not sure it's going to renew. Yeah. That's the simplest AI investing framework I've heard. I'll tell you why it's simple, because you're going to basically write no checks.

So, like, I guess I'd say most of the AI companies have invested in there, probably three or four. The only one on my quibble with there, I think that's very good for staying out of trouble. And this is where, you know, I didn't push back when people are saying, oh, it's an AI bubble. It's like, I don't know, I think people are happy with the tokens they're buying, you know? I think, like, there's a lot of tokens happening, and just generally they seem to be delivering useful outcomes of customers because they're actually delivering value on the customer service side or people enjoy their mid-journey adventure. People are getting value from the products.

So it's a pushback that like doesn't... I was going to push back on number four, which is positive unit margins because just aren't the underlying costs... Like, again, when you guys started Finn, it sounds like it was underwater. Right, but then just pretty quickly at right sizes as you optimize it. And so couldn't one be too focused on the current implementation? Yeah, I mean, this is a conversation we have internally

with our CFO quite a bit, actually. Because we're good. You can imagine me the kind of thing of CFO would love it. Hey, Dads, do you have five minutes? Yeah, that's exactly. Money losing AI product. Yeah, hey, quick chat.

I can't help but notice the team have done this preemptive loading or whatever that's called. It's a shitload of money. So, like, what's my counter to that? I guess, like, I prefer it if the path towards profitability isn't just like the, you know, open AI is going to figure this out for me, right? Like, an interesting way, I'd say this, like,

with Finn, for example, Obviously, our profit goes up when we are firing less dead tokens. A dead token being we've generated an answer and it wasn't right, so we can't charge money for it. Like if you're like, say, like, guessing the next line of code, right, or like tab to auto-complete the next line of code, if like five of six of those is wrong, I don't know if you're ever going to get bailed out. Because you're basically five-sixths of your costs is like, you know, it's not something you can resell. Yes. So like there is a question there of like how much of your tokens are actually generating a thing that a user wants,

independent of what you charge. As long as the user wants it, I think you're always in good condition, whereas if you're like burning a million tokens to find one, and that one, you're never going to be able to recoup your cost. Or at least, you know, I'd love to see your telemetry to make sure that you actually have taught this true. I suspect you haven't, you know. I'm curious about the co-founder dynamic you guys have across all the co-founders

where, let me try this on. My sense is that people want to have a subject matter area-based explanation for co-founder, you know, collaboration, where, you know, I'm the technical guy and they're the business guy, whatever. And in my experience, or at least with me and Patrick, it's much more personality attention-based, where I would say he's more visionary and expansionary, and I'm more, well, you know, we have food at home already. You've got to finish the products that you're already doing. Or, you know, I'm more frugal and he always wants to spend all our money, or, you know,

whatever the tension you're describing is. And then there's a useful, well, one, it's useful to have someone to be able to go mad by yourself trying to solve all these fairly naughty problems, but also a good company strategy probably exists at the intersection of those tensions. Does that describe your relationship with your co-founders? And what would you describe as the personality tensions? I mean, we're definitely all different. There's a lot of key things we all agree on. Owen would be like a first and formal.

I mean, he's a very strong CEO. He's very decisive and he's very brave as the best way I could describe it. An interesting thing like when he returned to Intercom, one of the things he did was basically rebuild the culture and one of the things he focused on was like resilience and open mind in this you know we didn't know a I was coming he didn't know I was coming but like to be able to like react to AI requires a lot of manic pivots zero certainty and ultimately conviction bets and I can't think of somebody better to do it that wouldn't have been me like not in a million years I would be like like

even being as AI pilled as I am yeah I still would have like and I can even I even look back at my own performance in that period and like you know I wasn't brave enough. One of the things I'm pushed for was the city of creating the Team Finn, which is like, hey, let's just build a new startup. Let's isolate them for everything else. Different floor, different section in the office. No one else is in there.

It's just their own Slack channels, their own everything. They're entirely secluded. And how do you not push for that? I don't know if we would have the clarity and the focus that we needed. People might be offended. Yeah, yeah, of course. Like all of the things, all of the downsides you'd possibly guess are all there. I just, I also think, like, there's no path to, like, there's no way, you know,

the phrase I've settled on when I look. back in this is like, sometimes you just, you have to go too far to know you've gone far enough. You know, and I think a lot of the mistakes I see in people that are trying to adapt to AI, for an example, and I'll come back to the co-founder here's like, is like, they tell themselves that they've known they've done enough because they, oh, you know, a few sparkly buttons, the merge features AI, and we're happy. We have an AI assistant to the product. Yeah, exactly. And we've updated our homepage as they were air first. So like, we're

good. And I think you need to be willing, genuinely willing to like make brave, hard to undo bets. And I think you need, like, sort of obviously, you know, having this sort of moral authority of a founder and being CEO kind of gives you some of that. But still, it's a huge decision to make. And I think, like, I am much more of an, my default DNA is like, I'm more of an operator in the sense of like, all right, what are we doing? Okay, well, I'll make it work, you know, whatever it is. And I think if it was a company of, like, people like me, what you'd see is probably, like, predictable, reliable, sustainable performance or whatever, but, like, but probably not enough actual like sort of, well definitely not enough, kind of brave big swings, which is actually where

you need to get to. Yes. But I mean, it is a cocktail. Like, somebody needs to go and actually do the thing once we decided what we're doing as well. The way it ended up, like, I was leading team Finn after I undecided it. And like, that was ultimately what led to the creation of like the whole Finn initiative, whatever.

You've now worked with so many different companies externally. You've seen a lot. What is predictive of success and what is predictive of failure? The biggest thing I'll always come back to when I'm talking to anyone who's trying to pitch me to invest or pitch me to induce John to invest is it's always some version of do you have a real product that solves a real problem that really exists and people are really already trying to solve by paying money or time somewhere it sounds so trivial be shocked how many times you'll fail or you'll get some sort of jazz hands type routines somewhere along the way where it's like don't

look too much at this but just trust me the areas that i end up being blind to and that is like you know the extremely market expanding type things like as in if someone said to you hey like all companies are going to have a chat room and they're going to all hang out in it all day and have unproductive conversations, it's going to be big. I'd be like, oh, I don't see it. Like, you know, whereas, like, so you would have missed out in Slack or whatever, right? But I think, like, I can almost, you know, hear from the, like, what are you building and why and who's it for and show me what the product does.

If it's not a real solution to a real problem, I'm kind of already out. And then the other big, I'd say, prediction is just, like, there's one of the things that's happened in the last 10 years. I'm sure you've seen this load is, like, it was a lot easier to invest when a founder was uncool. And I think like combination of like I blame genuinely the social network. I blame just kind of the entrepreneurial lifestyle. I blame like TikTok. I blame all these things. Soho House. Yeah, yeah, exactly. All of that, right, to some degree like remote working, I do intro into the mix as well. But I think the amount of people who are chasing the trinkets of being

a founder of a startup, even if they're quite smart and they can actually go and build something, if their actual motivation isn't the problem or isn't just some deep desire to be quite successful but it is instead to be perceived like the whole kind of I could have been a contender rather than I could have contended.

Yes. Like if you don't really, really want to be like to actually play the game would say you just want to be seen to be playing the game, I think that's probably the single biggest thing that tells me like, you know, you're probably,

your best case scenario you'll sell a 5 million but more likely you'll still be alive in seven years, all your investors will wonder what you're doing and you'll be basically sending one investor update every now and then, you know. Yes.

I have noticed investor updates with metrics don't predict success, but investor updates without metrics that tell a really fancy story, but don't have metrics, are actually quite predictive of failure. Those companies always fail. I basically 100% agree. And honestly, you can even tell where the metrics are in the update. Yeah. Because often I'm like, my favorite updates, I mean,

this company actually probably should be. And no investor updates are fine. There's like a bunch of successful companies that just never buy. We never send investors. updates. Like, I'm sorry for all the investors, but we were bad communicators. I was curious, actually. Yeah, yeah. But if, exactly, but if you go, oh, you an email, and if you go to the trouble of writing an investor update and then make a proactive decision to not say how your business is doing, that's just some deep denial about what running a business

means. So there's one company, I can't say, but we're both an investor in it, but like their updates, one of the most recent ones was just like, here's performance error plus 17%, blah, plus this, blah, plus that. something like, you know, I hope you can see from the numbers we're doing great. Best look, see you next quarter. And I was like, yeah, brilliant. Archive, I'll mark it up, you know, like. Yeah.

There's something like, I think in general, you know, the degree to, I think as Paul Graham said, like the ratio of numbers to words is usually the actual thing you're looking for, which is like, if the numbers speak, then the words, I don't have to. Yes, yes. What else is predictive of success? Numbers is one. I almost kind of want to say the inverse of all the things that I hate seeing. I hate seeing founders who invest massively in their personal brand.

set of their company brand. I hate seeing people who are obsessed about. If the first three or four updates I get are bags for retweets and quote tweets and all that sort of stuff, that's always not a great sign because it sort of says to me you haven't worked out how to market or whatever. Anything around, like, what are the customers saying? That's like, whenever I reply and say,

what the customers think of this feature, they're like, oh, we're gonna ask them. Maybe what you're describing is there's a very boring playbook, boring and glamorous playbook for making products work about writing code, talking to customers, running that iterative loop and avoiding distractions. And people who seem incurious about that playbook or just are failing to execute on it is kind of a warning sign.

Yeah, I would say that's definitely true. So it's basically like if you've got a decent product, decent area, real solution. And are you just willing to work on the boring stuff that needs doing to actually make that whole thing? And then will you get bored near or are you still excited by it? I think to some degree, even a success, best of founders can get distracted by glamorous opportunities,

whether it's like, oh, there's a new wave of whatever, like crypto or like NFTs or whatever, you'll see people get their head turned quite a bit. And I think that if you're like genuinely married to the problem and married to the solution, you'll tend to like sort of not be as distractible. And then like so many of these businesses just need time. You know, like they just need time and execution.

Yeah, totally. Last question, because I've had a lot, in what ways is Intercom itself AI Native? The biggest initiatives we've driven recently has been around how we actually do R&D. So I think we launched this initiative, DARA launched it, I think, about four months ago called 2X, where we basically said, hey, like, we're going to double the productivity of R&D before February 1st. That means the, and we measure this and everyone's going to poke holes in this and that's ground, but it doesn't really matter.

The measurement is, I think, it's deployments to production involving code that has to execute regularly, right? So it's a hard thing to fake. If you fake it, it's like, we should probably fire you. You know, because like, so. Now, interestingly, everyone's just like, is not just the engineers going really hard? No, like, there's like so many different elements to this. But one of the biggest ones that we saw recently, which really has been like awesome, as Emmett, our head of design, he basically said every designer by August 1st needs to be shipping code.

This is like the end to the discussion of should designers code, right? Designers should code. So we basically said, hey, like, all designers can now ship code. weirdly the winder is that like the amount of engineering distraction has just gone away so every paper cut in your UI used to result in a GitHub issue that it'd get filed and triaged and get picked up on a Friday and between breaks or whatever and now all that just goes and now you're like oh I want to fix this button fix that padding fix that thing change that radius change that color all that shit just happens automatically and like it's getting to much meteor stuff like redesign this entire

UI redesign this flow change this wizard all of that's now being managed entirely by a design team And what that has resulted in is like engineers who are now doing far more like, staying in the zone far greater using like whether it's cloud code or codex or any of those or augment or any of those tools to actually just, you know, be far more productive. And there's some real wins here. Like one recent one we had was like Finn works in Slack. But when we were building that, it was built very firmly from like, how do we use AI here? So it was like, let's build one perfect Slack solution.

Let's document all of our principles. And then let's have Claude code, right, the Microsoft teams, the Discord, the Wi. It's every other solution. So we went live to production with Slack, but I think we have everything else now in public beta, and it'll all go live. So we're finding all these, like, it's a lot of like 1.2x wins, but then every now there's like a 50x productivity boost

that we're finding. So I think that's probably the biggest way in which the product has been built from an AI native way. On the go to market side of the house, we've been slower, but like I think we're looking at like, we've trained a GPT, if you like, on like all of our marketing copy, our principles, our content, our visuals, et cetera. And we've been using that to produce a lot of like, you know, stuff like event invites and things like that.

Hmm. Well, does. Thank you. Cheers. Thanks very much.