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

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-intercom Timestamps: (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?

• 0:00Speaker 00

  Do you ever work in a bar?

• 0:01Speaker 01

  I've never worked in a bar. I have a Guinness keg in my house.

• 0:03Speaker 00

  Actually, do you want another pint?

• 0:04Speaker 01

  Yeah, sure, sure. I was talking to a guy who runs procurement and I was just saying like, you have to understand, I'm just getting bullshitted to all day. You know, it's just all day relentless, absolute nonsense in my face.

• 0:14Speaker 00

  People do not have enough empathy for the procurement person who just has to endure non-stop nonsense.

• 0:19Speaker 01

  Absolute garbage. Chat GPT launched, I think on a Thursday. I had a call with Fergal, our head of AI on a Friday. Owen made the decision like on the Sunday, I think it was, and we started working on like the 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.

• 0:42Speaker 00

  Soho House.

• 0:42Speaker 01

  Yeah, yeah, exactly.

• 0:45Speaker 00

  You just show me your technique and I will learn from you because I'm pretty sure I'm being wrong.

• 0:49Speaker 01

  Ever poured a pint of Guinness in America?

• 0:51Speaker 00

  My fellow Irishman, Dez 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.

• 0:59Speaker 01

  Cheers.

• 1:03Speaker 00

  Okay.

• 1:05Speaker 00

  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?

• 1:26Speaker 01

  No, it's not amongst anyone who you would respect. It's very, it's very much an actual TikTok thing. It's a slight bit of a tourist thing because of that.

• 1:34Speaker 00

  Yeah.

• 1:35Speaker 01

  But it basically means like you're drinking, I think it's a quarter of a pint in your first mouthful. And it's like, I don't know.

• 1:39Speaker 00

  A waste of good Guinness.

• 1:40Speaker 01

  Yes.

• 1:41Speaker 00

  Yeah, okay. It's a little like when I first came to America, drinking games. It's like back home, drinking is very serious. I couldn't do it.

• 1:46Speaker 01

  Exactly.

• 1:46Speaker 00

  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 that I saw you pining on like Beamish, Murphy's, everything like this. I don't know. What is your, what is your view on the stout landscape in particular?

• 2:02Speaker 01

  I probably default to Guinness. There's been moments where I'd go kill Kenny, Beamish, Murphy. Usually it's like when you're every year in their respective hometowns. But for the most part, I default to Guinness.

• 2:12Speaker 00

  Yeah.

• 2:12Speaker 01

  For like one brief day, I tried Ireland's Edge. I don't know if you remember when they, Heineken, I think it was Heineken.

• 2:18Speaker 00

  Heineken.

• 2:19Speaker 01

  Launched the Guinness killer and it lasted all of like six months or something like that. They were literally, I think literally they were giving it away at the end and still couldn't get rid of it.

• 2:26Speaker 00

  Have you heard all the Guinness stats about, you know, 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.

• 2:41Speaker 01

  And it's weird, like it trickles into modern day, like where I live, by Castle Lock, like a lot of chunks of the Phoenix Park are owned still.

• 2:49Speaker 00

  By the Guinness family.

• 2:50Speaker 01

  Exactly where the houses 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.

• 2:57Speaker 00

  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. 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 Quickster debacle? But then really cracked streaming movies. And so, you know, 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.

• 3:40Speaker 00

  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?

• 4:16Speaker 01

  Yeah, it's it's that's true. It's a bit of like extra context I 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, you remember the attack, 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're using, you were kind of abusing like PayPal for payments and you're using like Mailchimp for like talking to your customers and stuff. You know, we had this idea of like talking to your customers 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 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.

• 4:57Speaker 01

  And where do like use cases like that still exist today? Like 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?

• 5:05Speaker 00

  Yes, yes.

• 5:06Speaker 01

  So we started out like with a very, very general purpose idea, which was like that internet business is talk to their customers. And then we kind of fell in love with this jobs to be done methodology. And like as one of the things you do 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 and then it was like, well, you need to focus.

• 5:33Speaker 00

  Concise prece of the period.

• 5:35Speaker 01

  Exactly. That's just quite 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, Owen returned on the left in 2020, I think. Owen returned, you know, business had been like in declining net new 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, ChatGPT launched, I think on a Thursday. I think we, I had a call with Fergal, our head of AI on Friday, spoke with Owen 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 Intercom on the Monday. And that was like 2022. And I think like where and not for that, it's hard to say exactly where things would have gone, but certainly that's the reason I'm sitting here, you know.

• 6:18Speaker 00

  And obviously people are naturally wired to be skeptical, you know, when they 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.

• 6:32Speaker 01

  The biggest thing it means to us is our product Finn. So we launched Finn in March, I think, twenty twenty three. We launched a few little AI features. We were the first people to actually build anything on like the G P T three point five. And then we launched Finn in March, G P T four launch day. And Finn was like basically the first chatbot that worked. It's the best way you could think about it. What that really meant was it could actually have conversations and answer questions. And when we launched it, it was doing, I think, twenty five percent resolution rate. And that was like crazy numbers. Today, it's like sixty five percent. And today, Finn's resolving about, I think, it's over a million conversations a week. It's handled about forty million actual end to end customer service scenarios to date. It's, you know, growing like over two hundred percent year over year. It's like, you know, it's, we recharge a dollar per answer. So you can work the revenue out.

• 7:15Speaker 01

  Or a ninety nine cent even. It's becoming like just this, you know, AI sort of growth story inside Intercom, which is already like a sort of, you know, 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 on 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 Finn. We're using custom re-rank or custom retrieval, summarization, et cetera. And we're doing a lot of this work. We have like an AI lab of fifty 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 the entire future of C S is clearly going to be AI. And that's what we're all in on.

• 7:54Speaker 00

  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 like good computer games. Or, you know, people are pitching a mobile internet and, you know, you'll buy cinema tickets via a app. It's like.

• 8:10Speaker 01

  And J two M E and all that.

• 8:11Speaker 00

  Exactly. Yeah, yeah.

• 8:12Speaker 01

  And, you know, we actually had a version of that. Like, we had a product called Resolution Bot. It was originally called Answer Bot, but I think Zendesk tried to sue us because they had a competitive product. But like Resolution Bot was actually a good AI product at the time, but it's just AI wasn't there.

• 8:22Speaker 00

  Right.

• 8:23Speaker 01

  And so that was the actual reason why we had such a head start, because we actually already had a little AI group ready to go. We'd already built a rag engine ready to go.

• 8:29Speaker 00

  Yeah.

• 8:29Speaker 01

  So we were able to jump a lot quicker than a lot of folks. But yeah, like it's, I think a lot of these products, you're right, like have a kind of two or three stabs before they go mainstreaming.

• 8:36Speaker 00

  Yeah. And there was this whole enthusiasm cycle for bots in twenty seventeen, I want to say, and the. Tech just wasn't there at all.

• 8:42Speaker 01

  It was a horrible experience for customers. It was also quite clunky to set up for businesses.

• 8:46Speaker 00

  Yeah, yeah.

• 8:47Speaker 01

  And at some point, I think everyone looked, you know, there was a genuine question at times where it was just like, is a web form not just better?

• 8:52Speaker 00

  Yeah.

• 8:52Speaker 01

  Like, I think a lot of cases it was.

• 8:54Speaker 00

  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, would you please just connect me to a human? Whereas now it's like, can you just connect me to a boss?

• 9:05Speaker 01

  We see that a lot. We see like, oh, hey Jenny, sorry to bother you. Can you put me back onto Finn? It was actually doing a great job, but it just thought 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. Cause partially because like human considerations, like one of the reasons people go to like the kiosk in McDonald's, I suppose. Cause as opposed to their, their actual counter is because they don't want to have to think out loud in front of a human. They're like, oh, give me a second. Do I want fries?

• 9:30Speaker 00

  Yeah.

• 9:31Speaker 01

  A lot of the reason why people like 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 one question, well, people are like, oh, this thing's paying out. Let me, now that you're doing, now I'm going to ask you all of the things I was wondering about.

• 9:47Speaker 00

  Yeah, yeah, yeah.

• 9:47Speaker 01

  Whereas I think they'd feel probably nearly weird unloading all that on one per CS rep, you know?

• 9:51Speaker 00

  Uh, okay. So you're seeing a lot of induced demand where people use interactive customer service much more.

• 9:57Speaker 01

  Which is interesting because it turns Finn into not just being a kind of a, you know, 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?

• 10:06Speaker 00

  Yes.

• 10:06Speaker 01

  And like the answer is all, you know, a lot of times it's a lot better. And it's not just the whole, like, I don't want to burden a human. It's also like people often, one of the biggest fallacies in AI is people compare it with like, with this perfect human that does not exist. Like the, the driver that never crashes. Or like, in our case, it's like, well, a human artisanal handcrafted answer. And I'm like, yeah, like, let's pretend that will be there in seven seconds. It won't be. It'll probably be 18 minutes. It's also not going to be perfect.

• 10:29Speaker 00

  And let's presume you're doing those handcrafted answers, which you're not. Yes. Someone is like, busy trying to close the case before they move on to the next one.

• 10:35Speaker 01

  So like, I think, yeah, comparing or like, I don't know, we have this thing where we expect our AI products to be flawless. And we're totally tolerant of like humans jumping over, only speaking one language and only working six errors or whatever, you know? It's just, it's a funny contrast.

• 10:45Speaker 00

  Yes, yes. That's interesting. And it's interesting you talk about product onboarding 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.

• 11:22Speaker 01

  Yeah, I mean, we, we talk a bit about like this idea of, of like, what is ultimately a customer agent going to be like? That's what film will be when it, 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, by the basically immediate accurate answers available all the time.

• 11:45Speaker 00

  Isn't obvious limitation, like right now you require customers 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.

• 12:10Speaker 01

  As if it's reacting to what customers say.

• 12:11Speaker 00

  Exactly. A customer has to come along and like type things into the box.

• 12:14Speaker 01

  I mean, today, that's what customer service is. It's still like, kind of like, here's my problem and then we'll solve it. I think, you know, for sure, there's obvious directions this will go with, like, you know, hey, what does a good customer look like? And maybe we can honestly infer that as well, but, but certainly like people like you should do things like this is definitely an understandable domain. And, 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 uppy. 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. 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, you know, a lot of the context is already there. So we can work out the right things to say and do. I think that's pretty doable.

• 12:56Speaker 00

  It feels like you could do a lot around, yeah, you train a model on what's. The customer is seeing on that webpage at that moment in time and use it to feed the answer and things like that.

• 13:06Speaker 01

  We already do a lot of that already, like as a customer context. So like, so knowing that, 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, it's all useful information when it comes to. Cause I like, I think people, a lot of like the, you know, Y C, I could build that in a weekend type Hacker News crowd. I think one of the things they often, you know, they're, they're thinking every customer support career begins with like, hi there, my name is blah, my username 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 fatig reply engine. That's just like, hey, let's chat about what's going on here. But like, we realized 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 they're talking about.

• 13:50Speaker 01

  A lot of people just don't realize how deep you have to go to actually do a great job. And like we're, like we do, like say if you install Finn today, you get like 65% resolution rate after 30 days. Like 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 the right model for it and all that. But one of them is customer context and that obviously answers a lot of things.

• 14:12Speaker 00

  Yes. What are the other smart things?

• 14:14Speaker 01

  Abstraction. So like, you know, like I guarantee you, 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 that in your docs. A very naive rag bot will be basically like, well, it doesn't say dentist and we're told not to hallucinate. So no, we don't do dentists, sorry. And like the abstraction is like, you know, in that case as well, what is a dentist? It's a type of business, the Stripe work for businesses. Can dentists, can dentists be internet businesses? Well, we 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 Finn. Then you've got obviously your rag and then you've got like, you're like, hey, is this, is an escalation appropriate at this time?

• 14:55Speaker 01

  Like, hey, have they threatened something or have they, you know, like you have every single type of problem. It kind of ends up, 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, I found it. And you're like, right, cool. That's like 0.4% of the scenarios you deal with and you're in customer service. There's like the, there's a pattern. Did you ever see the movie Armageddon where like, 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, well, 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 gonna happen sooner? Will AI people learn how to do CS or will CS people learn how to do AI?

• 15:40Speaker 01

  Thankfully, as I said, we kind of started off with CS and AI in our DNA.

• 15:44Speaker 00

  I would say people, you mean companies in this space, like OpenAI get better at customer service faster than Zendesk gets better at AI.

• 15:50Speaker 01

  Exactly, exactly that. I think we just, we were lucky in that we kind of had already backed both horses somewhere along the way, so.

• 15:55Speaker 00

  One thing I find interesting about what you do is every company is thinking about AI right now. You know, every company had a board meeting in 2023 where the board is like, can we do a special deep dive on AI? Cause 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 that, 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.

• 16:40Speaker 01

  Yeah, there's like, I've never seen the like build versus biting play out more often than we do today, especially what like. Certainly, like a lot of customers are like, you know, that meme on Reddit, I'm not like with her girls or guys, whatever. Like, there's a lot of that where it's like, oh, you would never possibly understand is B2C shopping company. And you're like, really? I've never heard of such a thing. Sometimes honestly, we just be like, hey, look, you know, Godspeed, you go and start building this. P S, here's a torture test. When you think you've got something good, run 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 like, 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 the back to the hole. That's such a small amount.

• 17:25Speaker 01

  What they can't do is actually have conversations and all that sort of stuff. 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 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 fired a tracer 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 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.

• 18:07Speaker 00

  So where is the Finn business these days? I'm curious both just how it's performing on revenue metrics. And then are you selling it to existing intercom customers? Are you selling it to new accounts? Just how does the whole thing work?

• 18:18Speaker 01

  We're about 6,000 customers and growing quickly. Finn does about a million resolutions a week. We're charging a dollar per resolution, so you can do that.

• 18:27Speaker 00

  So 50 million revenue run rate?

• 18:28Speaker 01

  Give or take. When we launched initially, we sold to 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? If we've done.

• 18:41Speaker 00

  It's a big job.

• 18:42Speaker 01

  A month or two, right? It's a whole ordeal. And Finn is brilliant. So we're like, loads of 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 we 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.

• 19:05Speaker 00

  And so do you? Is Fin like you can connect your iPods 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 Fin the engine and whatever customer service platform you use is actually not a topic of huge interest to us?

• 19:27Speaker 01

  This is such a core question that we kick back and forth quite a lot.

• 19:30Speaker 00

  This is the offsite debate that's just currently being held.

• 19:32Speaker 01

  Yeah, genuinely, or at least it's certainly one of them. The way we think about it first and foremost is the future is AI. So like Fin just has to win, kind of like at all costs, including our help desk. Weirdly, our customers are like, they turn Fin on, they're like, damn, this thing's good. Hey, now like 65% of our support volume, maybe we don't need XYZ 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 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, you know, demand for the actual help desk product too.

• 20:10Speaker 00

  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.

• 20:30Speaker 01

  First thing I'd say is obviously Fin 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 summarizer or whether it's like the rerank 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 a new architecture is in, hey, like we recently launched the ability for Fin to do complex queries, which would be like, say, go and issue the refund and update the name on the utility bill or something like that.

• 21:14Speaker 01

  Whenever like 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 fin 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 like, whenever we say like a GPT five 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 never run a GPT five. 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?

• 21:58Speaker 01

  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, whatever. So whenever a model upgrade comes, we have to trigger this whole thing. But when we launched, 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 like, 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 most recently. Like, when you look at like, you know, people are saying things like, oh, like the latest, whatever, you know, Grok can compete a mathematical Olympiad like level seven or whatever. We're like, right, I think you can probably do

• 22:42Speaker 01

  most CS, you know, like, so it's not, it's often not a lack of intelligence is the reason why we're not 100%.

• 22:48Speaker 00

  It's because they're too distracted by any.

• 22:50Speaker 01

  Exactly. A lot of the wins come from like honestly, better architecture, better 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 swap.

• 23:03Speaker 00

  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.

• 23:14Speaker 01

  Perhaps, but there are like a kind of a various customer to customer. It really is one of these areas where like it's a thousand lead bullets. It's not like a single silver one. Like it's not, if you look at our resolutionary graph, there's no pop, like, give or take one or two little tweaks. Like 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%, like, you know, and you see the AI team celebrate that on the balcony on the Friday, being like, yay, 0.7 up, whatever. It's hard to work out exactly what bits. And then there's obviously multiplicative benefits. Like 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 gonna chase any edge we can get. Right now, I think customer models is definitely where we're going. And that's like a large

• 23:59Speaker 01

  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 gonna 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 like- 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, our product looked the nicest. So all we had to do was the age old, you know, blah, blah, blah, reinvented and in a big sexy screenshot. And you can still get away with that in certain domains. A cleaner can get away with that because their product is the sexiest, right? I think with AI, everyone's chatbots look the same. Everyone's kind of copied our messenger.

• 24:42Speaker 01

  Everyone, you know, 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 of them are 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 outmarket and then how do you outsell? And one of the reasons we launched like the thing guarantee, this idea that we'll like, we'll pay you a million dollars if you find somebody that performs this, because like, we're trying to stress to the market this idea that, that like, we actually believe in our product to a ludicrous degree, such that you should engage with us on any, on any sort of bake off you're doing. Yes. But I think from a marketing perspective, it's really hard to stand out. So all you can really do is like rely on, on like backing up your claims as hard as you can. And obviously

• 25:25Speaker 01

  customer testimonials. Selling is harder, because I think, again, in the olden days, like selling SaaS, and the olden days being like pre 2022. It was kind of like, our UI is nice, theirs is ugly. Here's a feature grid checkbox, we've got 24 checks, they've got 17. These seven matter, we're in. You know, like, and that was like that, like, obviously, I'm skipping over several steps. Of course, sales enable will kill me, but you get the the basic idea, right? And I think now selling AI is closer to selling like infrastructure in a sense. It's more like.

• 25:54Speaker 00

  Our cloud is better than their cloud.

• 25:55Speaker 01

  And our 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 CSAT versus theirs.

• 26:09Speaker 00

  Yeah.

• 26:09Speaker 01

  But then people say, well, why? And then you have to then explain what's actually happening beneath the surface a little bit.

• 26:15Speaker 00

  Yes.

• 26:15Speaker 01

  So that people can actually get a bit of conviction.

• 26:17Speaker 00

  Right.

• 26:17Speaker 01

  And other than just like, trust us or like, please just go and try our product. Because it's not that easy to try a fan. You have to still have to like turn a lot of keys and open a lot of APIs and stuff. And so like, the challenge genuinely becomes like, how do you have a sales team that's actually able to like, speak with a good degree of familiarity about like AI?

• 26:34Speaker 00

  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'd 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

• 27:17Speaker 00

  85% conversion rate on that form, then obviously getting it up to 90%, that's, you know, that's a huge deal. And those will be very high numbers. Most businesses would not see anything close to 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.

• 27:33Speaker 01

  Yeah.

• 27:33Speaker 00

  Then where you're not asking people to re-enter the payment details that delivers a big offload. The second one is even crazier is after people enter their credit card details. Frequently, charges are denied, kind of spurious.

• 27:46Speaker 01

  Yeah.

• 27:46Speaker 00

  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 denied. So what all that adds up to is that we can make the claim and we've seen it play out again and again. You know, 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.

• 28:17Speaker 01

  Yeah.

• 28:17Speaker 00

  Because everyone is out there saying, you know, we are the thing that gives you more revenue. And we've had the exact same thing where despite you can have all the numbers and all the case studies in the world.

• 28:24Speaker 01

  Yeah.

• 28:25Speaker 00

  It's just, it's hard to sell because it's undifferentiated as a message.

• 28:29Speaker 01

  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 business has forgotten its credit card or something like that and you're going to be able to renew it?

• 28:41Speaker 00

  Right. It feels unlikely.

• 28:42Speaker 01

  Yeah, it just feels implausible, but like at the same time, the data is not like, not really debatable.

• 28:46Speaker 00

  Yeah.

• 28:47Speaker 01

  I think people like to be able to explain it to themselves and like not like, you know. I think you have really, I was talking to a guy who runs procurement and he was saying like, you have to understand, I'm just getting bullshitted 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, sixty five percent thing is going to stick, it's not. It's just like, I take it, I divide it by ten at this stage, you know, and you tell me, oh, you're going to save me two million in CS salaries or whatever. I'm like, yeah, maybe in three years' time we'll see two hundred grand, you know?

• 29:16Speaker 00

  Yeah.

• 29:16Speaker 01

  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 adverse reaction to like marketing.

• 29:23Speaker 00

  People do not have enough empathy for the procurement person who just has to endure nonstop nonsense.

• 29:28Speaker 01

  Absolute garbage.

• 29:30Speaker 00

  That's funny. I mean, this kind of gets to a 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 million dollar guarantee. Has that worked?

• 29:44Speaker 01

  It certainly, it's worked from a point of view of like, I don't actually know how many people are in the program right now, but I could say what has worked is like.

• 29:50Speaker 00

  It's landed the message of we stand behind the product.

• 29:52Speaker 01

  Being able to say like, here is the reason why you can buy, you can buy from us. 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 at Newly or whoever, 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. They're saying this, you know, with six thousand customers, it's kind of gets, 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, hey, here's a beautiful backend product, here's fancy reporting and all that. But that doesn't speak to the core thing someone's buying when they're buying AI off you is to some degree,

• 30:36Speaker 01

  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, helping people identify when they're being lied to in a sense. So you, we will say like, hey, try this type of question or ask them about this, you know, help, you're almost kind of teach them to be much more conscientious buyers. Cause we know the more informed 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, it's a difficult one. Ultimately, like five years ago, I would be like, well, the trick, John, is GIFs.

• 31:19Speaker 01

  You know, have you ever considered using movies on your homepage? You know, that's really engaging. None of that works anymore, right? Cause I just think like 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.

• 31:39Speaker 00

  Yeah, I can see that. Well, what are your other pet peeves when it comes to product marketing? Actually, do you want another pint?

• 31:44Speaker 01

  Yeah, sure, sure, sure.

• 31:45Speaker 00

  See again, this one, did I not let it settle for long enough? And then you have the small head, like, is the settling-

• 31:49Speaker 01

  I actually think everyone's gonna work out perfectly.

• 31:51Speaker 00

  Is the settling time load-bearing? Okay, so what are your pet peeves when it comes to product marketing?

• 31:55Speaker 01

  I think the thing that still kills me, and it's still very common, is marketers that love marketing. So like, rather than actually saying anything useful or specific, you'll get like, you know, "Forget everything you know about email." And you're like, "Okay, what am I buying?" Or like, you know, "Transformation reinvented." And you're like, "Cool, sounds like I'm gonna reinvent some transformers." Like, but like, what's actually happening here?

• 32:14Speaker 00

  Yes.

• 32:14Speaker 01

  I think there is a general, still type of thing where my screensaver on my laptop is like literally a typewriter, where someone has said, "What are you actually trying to say?" I keep that there as a reminder of like, just nine times out of 10, the best marketing comes from just writing the thing you want to say. Because like, do you know the docs, 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 say this?" Like, "Why is there 2,000 more words here?" And 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, especially in the AI era, they don't really necessarily understand the depth of what's actually happening with the AI or whatever. There's a funny stat that I'll go use to quote, which would say, something like,

• 32:56Speaker 01

  "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, you, 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, the thing that people don't get is like, everything means something. And this is like where our CEO is like so differentiated, he's just like, "Every single decision 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 like copy paste somebody else's branding, even in the sort of like, "Oh, we'll change your homework along the way."

• 33:39Speaker 01

  I think what they're really doing is saying, "We don't really understand what we're doing here."

• 33:42Speaker 00

  Yes, yes.

• 33:43Speaker 01

  And like, that's why, a classic of this is, you know, whenever an incubator spits out a new batch of startups, and they all basically have right-hand side screenshot, left-hand side tree bullets, signup button, or whatever. You're kind of like, "Okay, cool, but have you actually thought about what you're trying to say to the world?"

• 33:55Speaker 00

  Also thing for startups where they probably shouldn't look at what established companies are doing.

• 33:59Speaker 01

  Yeah.

• 33:59Speaker 00

  Because like Stripe for so long, we clung to making sure that we had code in the homepage. And people were 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.

• 34:13Speaker 01

  Yeah.

• 34:13Speaker 00

  Experiment a little bit more. And you know, Salesforce doesn't have to hit CRM so hard on the homepage. Cause after 20 years, they've earned the right to talk about Einstein a bit.

• 34:22Speaker 01

  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.

• 34:30Speaker 00

  Yes.

• 34:31Speaker 01

  Not realising that 99.49s of the world have not even heard about the original thing yet.

• 34:35Speaker 00

  Yes.

• 34:35Speaker 01

  But there they go destroying your original pitch by being like, oh no, 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.

• 34:43Speaker 00

  Yeah, yeah, yeah. Speaking of David Ogilvie, you've read on advertising, I presume.

• 34:47Speaker 01

  Yeah, yeah.

• 34:47Speaker 00

  What is this? It was just like, that's such a beautiful book where all the marketing copy is so good. Like the Rolls Royce ad of, you know, the only sound you'll hear at 60 miles an hour is the ticking of the clock. And but somehow that's, yeah, it should be mandatory reading for all product marketers.

• 35:01Speaker 01

  Absolutely.

• 35:02Speaker 00

  What kind of person succeeds in product at Intercom?

• 35:05Speaker 01

  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, you know, 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 I ask people is like, what apps are on your phone? What's your favourite app? And the amount of times someone's like, oh, you know, I never really thought about that. I'm like, ooh, so like, like, what's your favourite song? Like, you know, like, I'm sure you care about some things.

• 35:44Speaker 00

  Yeah, yeah, yeah. Certainly if you're interviewing musicians, they should have a favourite song.

• 35:47Speaker 01

  You'd like to think that, but they also probably have a favourite 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 like at Intercom, we often say shipping is an act of like confidence and humility. And what that means is like, you know, you have to be confident enough to put it live and then humble enough to take the slap. 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 in 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 like, no, we're not building an attribution engine.

• 36:32Speaker 01

  Yes, we'll take on some feedback in 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 in like, well, the data suggests. And they're just trying to hedge their bets where it's just not the sort of company we are. I think we kind of believe in having an opinion about a space.

• 36:54Speaker 00

  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.

• 37:03Speaker 01

  They have to be able to, yeah.

• 37:04Speaker 00

  And hear what?

• 37:07Speaker 01

  Yeah.

• 37:07Speaker 00

  Like, 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. 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 intercom guys 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 to improve. There's no overcomplicating. And then when we do our weekly all hands fireside, we also bring customers to that.

• 37:48Speaker 00

  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 data your way out of this. And if you're a product manager and you're not talking to many customers each week, something is probably wrong. I bring that up because like the whole original intercom product was a way to talk to customers. Like this is, this is kind of your guys.

• 38:20Speaker 01

  Absolutely.

• 38:20Speaker 00

  But would you agree that diagnosis that a lot of tech products would be better if people simply talk to customers more?

• 38:28Speaker 01

  Yeah, I mean, like one of the. Ideas that like still can be very early on, it 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. And 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 like 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.

• 39:11Speaker 01

  But question one is basically, what did our users say about this when you showed it to them?

• 39:14Speaker 00

  Yes, yes.

• 39:15Speaker 01

  And everyone has to have an answer to that question when, when like when we go in, like, I'm like, hey, well, what did the user say? And like, 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 valley does, and like, well, I'd say the valley, but like, that just basically means in the tech industry. There is this epidemic of like hiding behind your data. And like, you know, what can we instrument and how many different, you know, mixed panel 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.

• 39:44Speaker 00

  Yes.

• 39:45Speaker 01

  And interestingly, you say like stripes for value is like users first. I'm just curious, was I, is that deliberately, I 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?

• 39:59Speaker 00

  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.

• 40:08Speaker 01

  Yeah, that's what I was gonna say.

• 40:09Speaker 00

  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 word.

• 40:19Speaker 01

  Yeah, no.

• 40:19Speaker 00

  It's not perfect.

• 40:20Speaker 01

  It makes sense. I often, because I just, I find oftentimes, and if you want to perfect a product, you talk to the users. If you want to expand your market, you talk to like prospective buyers. But whenever I like, even in my own portfolio, when I talk to 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. Kind of miles wide, inches deep, like messy product that doesn't actually satisfy anyone.

• 40:45Speaker 00

  Yes.

• 40:45Speaker 01

  But like they'll get there kind of like one promise at a time. Oh, we'll build that for Johnny and Johnny will sign it. 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 of a user base.

• 40:58Speaker 00

  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 have all your existing users, you know, that you're dancing with the girl that brought you over here.

• 41:13Speaker 01

  Yeah, yeah.

• 41:14Speaker 00

  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 or like 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 will be brought

• 41:45Speaker 01

  Yeah.

• 41:45Speaker 00

  Bought in versus the people who grew up in 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, you know, we 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 fixed A, B and C.

• 42:07Speaker 01

  Yeah.

• 42:07Speaker 00

  And just the nature of the fact that sales gets more airtime than account management essentially.

• 42:12Speaker 01

  Absolutely.

• 42:13Speaker 00

  Means people really misprioritize where they spend.

• 42:15Speaker 01

  Yeah, it's and people take NRR for granted and think that like the net new revenue is that is hard, right? Like and I think one of the things that we see a lot of is like in terms like, you know, you know, 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 as in, yeah, okay, let's work on V three.

• 42:36Speaker 00

  Yes.

• 42:37Speaker 01

  But like is V two in good condition? Like or, you know, and then permission to expand is like V three is not actually that exciting. Everyone's happy with V two. Now I think we can try and 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 with like aimless product expansion to just try and increase the share of wallet for the people who are stuck with you. Yes. 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 throats of their 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 like they're destroying the hope of future revenue because like, yeah, you can force your current customers into whatever upsells you have or whatever.

• 43:20Speaker 01

  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 like land and expand thing, but you're actually just expanding and there's no landing happening in the new product. And and then you end up trying to twist yourselves in knots. And a lot of startups like, you know, Jason Mckinney said this thing of like from zero to one is impossible, from one to 10 is hard and from 10 to 100 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 like get the next 10,000 logos. So they just try and milk the revenue out of the existing customers. Yes. True, like just forced product adoption of new stuff like, you know, you see like, here's your co-pilot, I know he didn't want it, you know, but here you go, like that type of thing.

• 44:05Speaker 00

  Dez 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 multi-dimensional very quickly. Now, fortunately, complicated and multi-dimensional 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.

• 44:48Speaker 00

  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.

• 45:04Speaker 00

  As you think about the prototypical $10 million 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?

• 45:15Speaker 01

  I mean, the biggest problem mistake is like not aligning your fundraising with your TAM. 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 and base camped it more so than they did. Because they've raised on the assumption there's an easy path to like hundreds of millions.

• 45:40Speaker 00

  There should be more small profitable $30 million revenue companies.

• 45:44Speaker 01

  Well, yeah, exactly. And I think a lot of these businesses would be great if only they didn't raise 20 and tell their investors that they're going to like easily be worth a billion or whatever. I think there's a genuine mismatch there where I think people have like overstated like how big this idea could get. You know, as in, hey, I know what we all 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 like and venture ambition. The other stuff I see is like, it is kind of like not focusing enough on the thing you're, the majority of your customers value. Like, it's easy to say, and 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.

• 46:27Speaker 01

  It's hard to do it in a differentiated way. So because, you know, obviously people learn that line of code. And that's where you're getting a lot of these like 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, like rather than like saying, hey, let's get really go to 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 it was 2012, I was in your office on, you know, in Friday, and I remember at the time, it wasn't,

• 47:13Speaker 01

  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 to be with PayPal. I remember like you guys had the discipline, we were 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 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, GIFs and screenshots. But actually, when you think about it, we're a global creativity platform and they have this premature view of themselves as being massive. And then they feel like, then they go and 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,

• 47:58Speaker 01

  is something that they're just truly world class. And it's like, it's not some sort of 80 20 trade off. They've just basically said, we'll be better than anyone at this, right? Like you say, like linear, it's basically like they have literally the most, world's most efficient UI for like for product management and they have all sorts of project management. And they've just gone really deep into like all of the surrounding adjacencies you would need to actually do that job. 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.

• 48:33Speaker 00

  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 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 cliche example if you're going to make that argument. And the flip side is, you know, you're mentioning Figma, which I think is 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.

• 49:17Speaker 00

  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, 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.

• 49:38Speaker 01

  Yeah.

• 49:38Speaker 00

  And you can't rush it, you know, it'll emerge and it's, but yeah.

• 49:42Speaker 01

  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. And Fing was a great example, if we have 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 slides and text to app builders and like every other dimension they want to go. And everyone's like, yep, that's, 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. It's probably has really nice APIs, probably works really well, worked it back. 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.

• 50:27Speaker 00

  Yeah.

• 50:27Speaker 01

  Like, obviously, it's a lot easier with some like stablecoin or whatever. But like, what kills me as well, when I'm like, you know, I don't even want to like name a weak SaaS company, but like, pick your favorite, like, you know, mediocre SaaS company and anything, like, is there any direction you would allow them expand in your head? No, like, it's the short answer, like.

• 50:43Speaker 00

  Yeah, that's interesting. Who are you really excited to adopt new products for versus who are you steering clear of the new products?

• 50:49Speaker 01

  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 Godden has this hilarious point where he talks about like the value of brand once it's, once it's like weaponized. He describes like Nike and Hyatt Hotels. And 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, like, because Hyatt has a logo and Nike has a brand. And that's the difference, you know?

• 51:21Speaker 00

  A version of this, actually, maybe quite literally is that I saw Equinox launched a hotel. It was a pretty good idea because the design center they had 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 pitch in the hotel space. Of like, don't give me any of that other shit. I just want to go to my room and not have like a super loud noise outside the window. Or like weird light coming into the room. You just want to be able to get some sleep.

• 51:48Speaker 01

  Precisely, yeah.

• 51:49Speaker 00

  Yeah, I thought that was funny. And you're mentioning kind of Stripe's expansions. And so this may be a good segue into your pricing model change. You guys are the 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.

• 52:12Speaker 01

  Yeah, sure. Our pricing journey is long and complex and a lot of your listeners or viewers will know.

• 52:19Speaker 00

  Intercom pricing is a charged topic.

• 52:21Speaker 01

  Yeah, not anymore. You know, we've turned a corner. Let me just back up a bit. So like when we had like too diverse a product strategy, we were trying to do sales software, marketing software, support software. And like sales software is typically sell based and leads created and marketing was charged by like how many contacted people you want to send and support were sold by seats. So we had this extremely, just to say detailed, but like unnecessarily complex like pricing setup. And we kind of, we lied to ourselves and said, don't worry because there's always going to be a human to help people navigate this because you're never going to have to self serve this. But like 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 Owen returned, one of the decisions he made was just like, hey, we need to like, you know, sort our pricing.

• 53:03Speaker 01

  And we handed back, like truly handed back, I think about 50 million of revenue.

• 53:08Speaker 00

  Was that controversial, like with the board, with investors?

• 53:12Speaker 01

  Like we had support for it. I think it was like, people don't really underestimate, people massively underestimate what it means to have a really happy customer base. It's because word of mouth doesn't have like an attribution or a UTM code, if you know what I mean. So like they don't understand how to think about like happy customers. So making the decision to basically like, you know, kind of standardize on an easy to understand pricing that's like fair, transparent, predictable, et cetera. That was the first decision that we made. This is 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 of years prior, I'd said to you or to Patrick, like, hey, you guys should actually build as part of your product offering a pricing page creator.

• 53:53Speaker 01

  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.

• 54:00Speaker 00

  It's on the list.

• 54:02Speaker 01

  I think you've done it since.

• 54:03Speaker 00

  We have.

• 54:03Speaker 01

  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 on to 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.

• 54:18Speaker 00

  Pricing is writing checks.

• 54:20Speaker 01

  Yes, yeah, exactly. And once, like, I remember like sitting at a Stripe mini all hands, whatever, explaining like that. Like, hey, now none of our business logic runs through Stripe. And I think either you or Patrick were saying like some version of like, that's not a good thing. I think, you know, generally speaking, my advice to 90s software companies 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.

• 54:43Speaker 00

  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 A, B, C, D, and E. And it's like, it is built in Microsoft Word, but it is actually, it's just not built practically in code because it just exists for this one customer. And it may not even be possible to build in code. Like sometimes, you know, 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.

• 55:12Speaker 01

  There's a guy called Ricky and he decides with the discount.

• 55:14Speaker 00

  Exactly. And there'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.

• 55:41Speaker 01

  Not having a large deal desk function and doing all the work behind the scenes. Yeah. So, sorry, 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 out just very fully, but like 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 twenty five percent less seats in the future. Or at the very least, what it would likely mean is the growth rate or the N R O of the seats model will be affected by the fact that it's in all the work. And now at sixty five percent, you'd expect it to be even further true. So it was like, hey, how do we charge in a way that makes sense? And we're and then also, like, how do we be aggressive? Like, as in, we want really wanted to like, like, put a mark on the market.

• 56:23Speaker 01

  Uh, that sort of says like, you know, we're like very A I forward. Yeah. I think what uh, what Owen and Endara came up with was just like, hey, like, let's just charge per literal resolution. Every time we do work, we charge. Every time we don't, we don't. Yeah. And this is at a time when like A I 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 in, you know, we're, we're, we're really happy with our margins, but at the time it was like, hey, this, this, this could. It was a bet. Yes, it was definitely a bet. We made the decision and uh, and I think the market responded really well because I think it was very clear that like the state, 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 in 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. Yeah.

• 57:06Speaker 01

  It's been copied a million times since, but I think like the actual decisions that we made in the run up there were really, really important from a point of view of backing up our, our claims. And then obviously for a lot of our competitors, they were like, oh, you know, 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 thrown cat amongst pigeons there, which has been like really well received by the market and our customers generally do love it. It is funny though, like you still get people being like, none of that sense ridiculously expensive. And then, 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. Have you, how much are the humans costing you? Yeah, exactly. And how much is your office costing you and all your stuff? Yeah, yeah, yeah. But people like certainty. How do you get them okay with the variable components?

• 57:49Speaker 01

  You know, you can obviously, you can contract out whatever you want, right? Um, 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 with customers who spike for taxis or customers who spike for Christmas or whatever. And we can basically say like, hey, let's like, let's contract your base rate and let's talk about overages for the months you needed. 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, they're not usually worried about this.

• 58:23Speaker 00

  Yeah. So you're using relatively new products type usage based billing for this. How is that you migrated from Zora for that? How has that process been?

• 58:31Speaker 01

  Yeah, I mean, I would say, just to go back to your 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, we ended up like, Kieran Lee, who's our CTO here. He ended up actually returning to the company with one mission, which was like, I am going to own.

• 58:54Speaker 00

  Fix billing.

• 58:55Speaker 01

  Yeah, exactly. To, to fix this, right? And like, it worked, right? But it was, it was like, it was a substantial amount of work to like unwind so much. And then like, they were like, to kind of like deconstruct so many of these like à la carte 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 a usage based on top was actually pretty simple in the greater scheme of things like. And like all the stuff that, you know, we needed, you guys were ahead of us on like, well, you know, discounts for volume, et cetera, all the sort of obvious stuff people would push for.

• 59:28Speaker 00

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

• 1:00:09Speaker 01

  I don't know if unlimited plans will ever, well, I don't know. Here's how I think about it. Like, I think ultimately all AI has like two vectors. There's like, how much work are you doing and how well are you doing it?

• 1:00:19Speaker 00

  Yes.

• 1:00:19Speaker 01

  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.

• 1:00:31Speaker 00

  Yes.

• 1:00:31Speaker 01

  We're just going to go nuts. So I think you have to have some, you know, I'm not a fan of like cost plus pricing, but it does place a kind of a lower bound on what you can do here, which is just like, you know, unlike SaaS, you are actually sending money out the back door as well. So I think you have to have something that's proportionate to how much work you're doing. And then I think aside from that, you have to charge consistently, 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, you know, fill in the 65% of that seat, we're still up because we're only charging like, whatever, $90 for the seat.

• 1:01:16Speaker 01

  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 that? You're like, cool, I don't know how much people will pay for that because they don't know, they don't know either. Or like, hey, you can now generate random graphics in your newsletter tool. You're like, okay.

• 1:01:37Speaker 00

  It's like vitamins versus painkillers, AI pricing.

• 1:01:40Speaker 01

  Yeah, and 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.

• 1:01:48Speaker 00

  Yes.

• 1:01:49Speaker 01

  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. Like, you know, I saw a while ago, like, someone said, like, you know, when Studio Ghibli came out and everyone was like using that, someone said, like, hey, the Fiverr.com equivalent of all these things would have been like trillions of dollars. And you're like, right, but like, 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 Huber 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.

• 1:02:20Speaker 00

  Yes.

• 1:02:21Speaker 01

  I think when your AI is not tied to business impact or is like debatable in quality or whatever. I think you end up with these people who are just like, oh, let's just stick a tenner on the seat and see what happens.

• 1:02:30Speaker 00

  Yeah.

• 1:02:31Speaker 01

  You know, so it's like, you know, a normal seat or an AI seat.

• 1:02:33Speaker 00

  Yeah, yeah.

• 1:02:33Speaker 01

  And you're kind of like, I hope no one uses the AI too much.

• 1:02:35Speaker 00

  Yeah, yeah.

• 1:02:36Speaker 01

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

• 1:02:45Speaker 00

  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 Matty from Eleven 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, or maybe three years after founding. But, you know, in my day, businesses didn't do that, and it's really striking for me how somehow they seem to climb the revenue ramps much quicker.

• 1:03:15Speaker 01

  I know.

• 1:03:16Speaker 00

  I mean, you guys at Finn is another example.

• 1:03:17Speaker 01

  Yeah, for sure. We forecast like Finn will be 100 million probably early next year, whatever, and like back in.

• 1:03:24Speaker 00

  Yeah, from when, like, starting from?

• 1:03:26Speaker 01

  I don't know, probably about two years from now.

• 1:03:28Speaker 00

  Yeah, yeah, so two years to 100 million ARR.

• 1:03:30Speaker 01

  Like, when we started, and probably when you guys started, like, it was like, that was the threshold to go public.

• 1:03:35Speaker 00

  Exactly, yeah, yeah. It used to take a long time to get to 100 million ARR.

• 1:03:38Speaker 01

  It was like seven years.

• 1:03:39Speaker 00

  There used to be a lot of money.

• 1:03:40Speaker 01

  Exactly, back in the day.

• 1:03:41Speaker 00

  Yeah.

• 1:03:42Speaker 01

  But yeah, it's the acceleration is more there. There's like, Matty's, you know, Eleven's a fantastic product, right? Like, 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 very C L four, but the things you want in an AI startup is kind of, one is like, is the revenue backed by usage?

• 1:04:02Speaker 00

  Mm hmm.

• 1:04:03Speaker 01

  And that's why I love usage based revenue, right? As opposed to like, you know, shelfware or pilotware.

• 1:04:07Speaker 00

  Yeah.

• 1:04:07Speaker 01

  You know, okay, we sold it to two guys in the corner and they're going to put it live 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 Eleven, like, if that doesn't work, that's really bad. 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 want positive unit margins and all this, or at least a clear path to positive 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 I've all for. It's such a rare sort of air to be in, to be like, actually, okay, 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.

• 1:04:51Speaker 01

  It's kind of like, you know, to generate JPEGs over Smurf or whatever. And you're like, all right, cool, I'm not sure that's going to renew, you know?

• 1:04:55Speaker 00

  Yeah, that's the simplest AI investing framework I've heard.

• 1:04:59Speaker 01

  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 my, most of the AI companies I've invested in are probably three or four, three or four, I'd say.

• 1:05:10Speaker 00

  The only one I might 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, a lot of tokens happening and just generally they seem to be delivering useful outcomes to customers because they're actually delivering value on the customer service side. Or people enjoy their mid-journey adventure, like people are getting value from the product.

• 1:05:34Speaker 01

  Are you saying, so it's a pushback that like doesn't?

• 1:05:36Speaker 00

  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 it right sizes as you optimize it. And so couldn't one be too focused on the current implementation?

• 1:05:54Speaker 01

  Yeah, I mean, this is a conversation we have internally with our CFO quite a bit, actually. Like, we're like, because we're good.

• 1:06:00Speaker 00

  You can imagine the kind of thing a CFO would want. Hey, Des, do you have five minutes?

• 1:06:04Speaker 01

  That's exactly.

• 1:06:06Speaker 01

  Quick chat, I can't help but notice the team have done this like preemptive like loading or whatever. It's costing a shitload of money. So like, what's my counter to that? I guess like, I prefer if the path towards profitability isn't just like.

• 1:06:21Speaker 01

  The, you know, OpenAI is going to figure this out for me, right? Like, an interesting way, I'd say, is 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. 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 autocomplete 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, right? Because your, basically, five sixths of your, of your costs is, is like, you know, it's not something you can resell.

• 1:06:49Speaker 00

  Yes.

• 1:06:49Speaker 01

  So, like, there is, there's a question there of, like, how much of your tokens are actually generating a thing that a user wants? Independent of what you charge for it. 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?

• 1:07:08Speaker 00

  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 tension-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 know, 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, it's useful to have someone to be able to, you go bad, mad by yourself, trying to solve all these fairly naughty problems.

• 1:07:53Speaker 00

  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?

• 1:08:05Speaker 01

  I mean, we're definitely all different. There's a lot of, like, key things we all agree on. Owen would be like a... Like first and foremost, I mean, he's like, he's a very strong CEO. He's very decisive and he's very brave is 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.

• 1:08:27Speaker 01

  You know, we didn't know AI was coming. He didn't know AI 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, I still would have like, and I can even, I even look back at my own performance in that period. I'm like, you know what? I wasn't brave enough. Like one of the things I unpushed for was the city of creating the team fin, which is like, hey, let's just build a new startup. Let's isolate them from everyone 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 had he not pushed for that, I don't know if we would have the clarity and the focus that we needed. People might be offended.

• 1:09:10Speaker 01

  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 that there's no path to like, there's no way, you know, the phrase I've settled on when I look back on 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 who are trying to adapt to AI, for example, I'll come back to the co-founder in a sec. Is like, they tell themselves that they've not, 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. Yeah, exactly. And we've updated our homepage to say we're at first. So like, we're good. Like, and I think you need to be willing, genuinely willing to like make brave, hard to undo bets.

• 1:09:51Speaker 01

  And I think you need like, sort of, obviously, you know, having this sort of moral authority of a founder and then 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, you know, 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.

• 1:10:24Speaker 00

  Yes.

• 1:10:24Speaker 01

  But I mean, it is a cocktail, like, as in, somebody needs to go and actually do the thing once we've decided what we're doing as well. The way it ended up, like, I was leading Team Finn after I own decided it, and like, that was ultimately what led to the creation of like, the whole Finn initiative, whatever.

• 1:10:37Speaker 00

  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?

• 1:10:46Speaker 01

  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 introduce 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, but you'd be shocked how many times you'll fail, or you'll get some sort of jazz hands type routine 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 in that is like, you know, the extremely market expandy type things, like, as in, if someone said to you, hey, like, all companies are gonna have a chatroom, and they're gonna all hang out in it all day and have unproductive conversations, it's gonna be big. I'd be like, oh, I don't see it, like, you know, whereas like, the so you would have missed out on Slack or whatever, right?

• 1:11:28Speaker 01

  But I think like, I can almost, you know, hear from the, like, what are you building and why and who's a 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 a lot, is like, it was a lot easier to invest when being a founder was uncool.

• 1:11:50Speaker 00

  Mm-hmm.

• 1:11:51Speaker 01

  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.

• 1:12:01Speaker 00

  Soho House.

• 1:12:02Speaker 01

  Yeah, yeah, exactly, yeah. All of that, right? To some degree, like, remote working, I'd really throw 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 is instead to be perceived like the whole kind of I could have been a contender rather than I could have contended.

• 1:12:27Speaker 00

  Yes.

• 1:12:27Speaker 01

  Like, if you don't really, really want to be, like, to actually play the game, instead 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, you're like, best case scenario, you'll sell a five million, but more likely, you'll still be alive in seven years, all your investors will wonder what you're doing.

• 1:12:43Speaker 00

  Yeah, yeah.

• 1:12:43Speaker 01

  And you'll be basically sending one investor update every now and then, you know.

• 1:12:46Speaker 00

  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.

• 1:13:02Speaker 01

  Yeah.

• 1:13:02Speaker 00

  Because companies always fail.

• 1:13:03Speaker 01

  I basically 100% agree. And honestly, you can even tell where the metrics are in the update.

• 1:13:08Speaker 00

  Yeah.

• 1:13:09Speaker 01

  Like, because often I like, my favorite updates, I mean, this company actually probably should.

• 1:13:12Speaker 00

  And no investor updates are fine. There's like a bunch of successful companies that just never buy. We never sent investor updates. Like, I'm sorry for all the investors, but we were bad communicators.

• 1:13:20Speaker 01

  I was curious, actually.

• 1:13:21Speaker 00

  Yeah, yeah. But if, exactly. But if you go, I owe you an email. 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 suggests some deep denial about what running a business means.

• 1:13:35Speaker 01

  So there's one company, I can't say, but we're both an investor in it, but like, their, their updates, just, one of the most recent ones was just like, here's performance, ARR 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 looks, see you next, see you next quarter this month. And I was like, yeah, brilliant. Archive, I'll mark it up, you know, like, yeah. There's something like, I, 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, like, which is like, if the numbers speak, then the words don't have to.

• 1:14:05Speaker 00

  Yes, yes. What else is predictive of success? Numbers is one.

• 1:14:10Speaker 01

  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 instead of their company brand. I hate seeing like people who are like obsessed about like if the first three or four plates I get are like 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. I like anything around like, you know, what are the customers saying like that's like, you know, whenever I reply and say like, what do customers think of this feature, they're like, oh, we're gonna ask them.

• 1:14:36Speaker 00

  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.

• 1:14:56Speaker 01

  Yeah, I would say that's definitely true. Like, so it's basically like if you've got like a decent, decent product, decent area, real solution, and you're just willing to like 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? Like, I think to some degree, even a successful founders can get distracted by glamorous opportunities where 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, 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.

• 1:15:36Speaker 00

  Yeah, totally. Last question, because I've had a loss. In what ways is Intercom itself AI native?

• 1:15:44Speaker 01

  The biggest initiatives we've driven recently has been like around how we actually do R and 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 and D before February 1st. That means the, and we measure this and like everyone's going to poke holes in this and that's grand, 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, cause like, so now, interestingly, everyone's just like, is that 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, Amit or Head of Design,

• 1:16:29Speaker 01

  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 ship code. Weirdly, the wind there is that like the amount of engineering distraction has just gone away. So every paper code in your UI used to result in a GitHub issue that 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 meatier stuff, like redesign this entire UI, redesign this flow, change this wizard. All of that's now being managed entirely by our design team. What that has resulted in is like engineers who are now doing far more like, who are staying in the zone far greater,

• 1:17:14Speaker 01

  using like whether it's Claude 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 Finnworks 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 WhatsApp, it's every other solution. So we went live to production with Slack, where I think we have like everything else now in like public beta, like 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 and then there's like a 50X productivity boost that we're finding. So I think that's probably the biggest way in which like the product has been built from an AI native way.

• 1:17:57Speaker 01

  On the go to market side of the house, we've been slower, but like, I think we're like, 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.

• 1:18:13Speaker 00

  Well, Des, thank you.

• 1:18:15Speaker 01

  Cheers. Thanks very much.

• 1:18:16Speaker 00

  Yeah.