← Cheeky Pint
Cheeky Pint
Des Traynor on reinventing Intercom twice and the “four horsemen” of good AI companies
01:18:20
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- [00:00]
A
Do you ever work in a bar?
- [00:01]
B
I've never worked in a bar. I have a Guinness keg in my house actually.
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A
Do you want another pint?
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B
Yeah, sure, sure. I was talking to a guy who runs procurement and 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.
- [00:14]
A
People do not have enough empathy for the procurement person who just has to endure non stop nonsense.
- [00:19]
B
Absolute garbage. ChatGPT launched, I think on a Thursday. I had a call with Fergal, our head of AI on Friday. I 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 blamed just kind of the entrepreneurial lifestyle. I blame my TikTok. I blame all these things.
- [00:42]
A
Soho House.
- [00:43]
B
Yeah, yeah, exactly.
- [00:46]
A
You just show me your technique and I will learn from you. Because I'm pretty sure I'm doing it wrong.
- [00:50]
B
Report appointing Guinness in America.
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A
My fellow Irishman, Des Traynor is the co founder of Intercom, the customer service giant turned AI company.
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B
He.
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A
He's also a prolific blogger and one of the most respected voices on product strategy.
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B
Cheers.
- [01:00]
A
Cheers. Okay. You are my first Irish guest and so I actually have a critically important question that has been burning this entire time whenever we release these episodes. All the YouTube commenters are obsessed with people splitting the G. This was never a thing for me growing up. A thing I never saw in Ireland. It's like an invasive species, maybe from TikTok. Is this a thing?
- [01:27]
B
No, it's not. Amongst anyone who you would respect. It's very much an actual TikTok thing. It's a slight bit of a tourist thing because of that.
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A
Yeah.
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B
But it basically means like you're drinking. I think it's a quarter to pint in your first mouthful and it's like, I don't know, I don't.
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A
Waste of good Guinness.
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B
Yes.
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A
Yeah. Okay. It's a little like when I first came to America, drinking games. It's like back home drinking is very serious activity.
- [01:46]
B
Exactly.
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A
Get a game out of it. Exactly.
- [01:49]
B
Yeah. Yeah.
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A
I was very confused by that in America. Okay. And then my other stout related question is I saw you opining on like Beamish Murphy's everything like this. I don't know what is your view on the stout landscape in particular?
- [02:02]
B
I probably default to Guinness. There's been like, there's been moments When I go Kilkenny, Beamish, Murphy, it's kind of. Usually it's like when you're. Every year in their respective hometowns. But for the most part I default to Guinness in for like one brief day. I tried Island's Edge. I don't know if you remember when Heineken. He was Heineken.
- [02:18]
A
Heineken launched the Guinness Killer.
- [02:20]
B
Like and it lasted all of like six months or something. Like I think literally they were giving it away at the end and still couldn't get rid of it.
- [02:26]
A
Have you heard all the Guinness stats about 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, they don't believe you. But the stats are really there.
- [02:41]
B
And it's weird, it trickles into modern day. Where I live by Castle Knock, chunks of the Phoenix park are owned still by the Guinness town. Exactly. Or the house but used to be there and they don't actually. And maybe they donated it to OPW or something like that. But yeah, it's very much still kind of carries forward.
- [02:58]
A
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 Qwikster 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 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 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?
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B
Yeah, that's true. There's a bit of extra context I'd give it. So when we started, it wasn't really. It was like about like this is like literally when we started. And our initial plan was like, hey, you remember the Internet? Because Stripe was in its early days back then as well. But there was no tooling to run a SaaS business. There was literally nothing. You were kind of abusing PayPal for payments and you were using Mailchimp for talking to your customers and stuff. We had this idea of talking to your customers is really important, so someone should work on that. And there was so much stuff in the early releases of Intercom. It was the first live cdp. Like you actually see who's live in your product right now and what they're doing and you could store data against them. You could say, show me all my premium customers. And weirdly like use cases like that still exist today. 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? So we started out like with a very, very general purpose idea which was like, let Internet businesses talk to their customers. And then we kind of fell in love with this jobs to be done methodology. And like one of the things you do in that is you look at how your product is actually used and then you iterate on it from that point of view. And that kind of led us down this path of sales, marketing and support. And then I guess to skip a load of years here, let's just say 2020 things were great, 2022 things weren't as great. And then it was like, we need.
- [05:34]
A
To concise precede of the period. Exactly.
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B
Let's just cut a lot of the reasons why or whatever, some sort of disease as well along the way. But yeah, so 2022, it was like, hey, own returned owner left in 2020. I think owned return business had been in declining net new revenue. He said we need to focus, we're going to 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 I had a call with Fergal, our head of AI on Friday. I spoke with Owen all through the weekend and we made the decision. Owen made the decision on the Sunday, I think it was. And we started working on the AI version of Intercom on the Monday. And that was 2022. And I think were it not for that, it's hard to say exactly where things would have gone. But certainly that's the reason I'm sitting here.
- [06:19]
A
And obviously people are naturally wired to be skeptical when they hear the AI version of Intercom. You have 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.
- [06:32]
B
The biggest thing it means for us is our product Fin. So we launched Fin in March, I think 2023. We launched a few little AI features. We were the first people to actually build anything on the GPT 3.5. And then we launched Fin in March, GPT 4 launch date. And Fin was like basically the first chatbot that worked. It's the best way you can think about it. What that really meant was we could actually have conversations and answer questions. And when we launched it, it was doing I think 25% resolution rate. And that was like crazy numbers. Today it's like 65%. And today fin is resolving about it. I think it's over a million conversations a week. It's handled about 40 million actual end to end customer service scenarios to date. It's growing over 300% year over year. It's like we charge a dollar per ounce so you can work the revenue out or 99 cents even. It's becoming just this AI sort of growth story inside Intercom, which is already like a sort of 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 fam, we're using custom rerank or custom retrieval, summarization, et cetera. And we're doing a lot of this work. We have like an AI lab of 50 people and we really just kind of have gone all in on the idea of like, you know, you know, like obviously Intercom still has a help desk product, but like the entire future of CS is clearly going to be AI and that's what we're all in on.
- [07:55]
A
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 mobile Internet and, you know, you'll buy Cinema tickets via WAP.
- [08:10]
B
It's like and J2ME and all that.
- [08:11]
A
Exactly, yeah. Yeah.
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B
We actually had our version of that. Like, we had a product called Resolution Bot. It was originally called answerbot, but I think Zendesk trying to sue us because they had a competitive product. But like, resolutionbot was actually a good, good AI product at the time, but it's just AI wasn't there. 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. So we were able to jump a lot quicker than a lot of folks. But yeah, I think a lot of these products, you're right, have two or three stabs before they go mainstreaming.
- [08:37]
A
Yeah. And there was this whole enthusiasm cycle for bots in 2017, I want to say, and the tech just wasn't there at all.
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B
It was a horrible experience for customers. It was also quite clunky to set up for businesses. And at some point, I think everyone looked, there was a genuine question at times where it was just like, is a web form not just better? Yeah, like, I think in a lot of cases it was.
- [08:54]
A
Yeah, yeah, yeah. Whereas I think now people are starting to have the experience of, you know, the classic thing is, you know, you're talking to a boss. It's like, please, will you please just connect me to a human? Whereas now it's like, can you just connect me to a bot? And we see that a lot.
- [09:06]
B
We see like, oh, hey, Jenny, sorry to bother you, can you put back onto fin? It was actually doing a great job. 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 because partially cause, like, human considerations, like, one of the reasons people go to like the kiosk in McDonald's, I suppose because as opposed to their actual counter, is because they don't have to think out loud in front of a human. They're like, oh, give me a second, do I want fries? A lot of the reason why people prefer Waymo for some people, it's like, I just don't want to have the conversation. I don't want the awkwardness around tipping or whatever it might be. And I just think what we see a lot is like, once Fin answers one question, well, people are like, oh, this thing's paying out. Let me. Now that you're doing that, I'm going to ask you all of the things I was wondering about. Whereas I think they'd feel probably nearly weird when loading all that on one per CS rep, you know.
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A
Okay, so you're seeing a lot of induced demand where people use interactive customer.
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B
Service, which is interesting because it turns Fin into not just being a kind of a cost takeout, but also it's like, how much better would your business be if everyone knew how to do everything they wanted to do? And like, the answer is a lot of times 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 this perfect human that does not exist. Like the driver that never crashes. Or like in our case, it's like, well, a human are 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.
- [10:29]
A
It might not presume you're doing those handcrafted answers, which you're not someone who's like busily trying to close the case before they move on to the next one.
- [10:35]
B
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 showing up hung over, only speaking one language and only working six hours or whatever. You know, it's just, it's a funny contrast.
- [10:46]
A
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, but 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.
- [11:23]
B
Yeah. I mean we talk a bit about like this idea of like what is ultimately a customer agent going to be like? That's what fin will be. As it grows up, it'll just become like this way in which customer conversations are handled. And obviously the most direct attack here is like customer service. But you know, I think every single customer touchpoint can be improved by like by basically immediate, accurate answers available all.
- [11:45]
A
The time 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 you want to see. Exactly. 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.
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B
Like it's reacting to what customers say.
- [12:12]
A
Exactly.
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B
A customer has to come along and like type things into the box today. That's what customer service is. It's still kind of like, here's my problem and it will solve it. I think for sure. There's obvious directions this will go as, hey, what does a good customer look like? And maybe we can honestly infer that as well. But certainly people like you should do things like this is definitely an understandable domain. And then I just think working at the right level of interruptive help, you don't want to be too naggy or too pop up y 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 that looks like you're stuck on. Like if someone's on on the renewal page and they have an error message, we know they're probably going to open the thing and we know they're probably going to say something that's got a lot of the context already there so we can work out the right things to say and do. I think that's pretty doable.
- [12:57]
A
It feels like you could do a lot around. Yeah, you train a model on what the customer is seeing on that web page at that moment in time and use it to feed the answer and things like that.
- [13:07]
B
We already do a lot of that already in customer context. So knowing that it's John and he's on the 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. Because I think people, a lot of the yc, I could build that in a weekend type hacker news crowd. I think one of the things they often they're thinking every customer support query begins with like, hi there, my name is Vlad, my username is Blah. But actually most support conversations begin with like this is broken. And you're like what's broken? And so to solve that you need like a FATIC reply engine that's just like hey, let's chat about what's going on here. But we realized quickly 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. A lot of people just don't realize how deep you have to go to actually do a great job. Say if you install FIN Today you get 65% resolution rate after 30 days. That's shocking. But we have had to go really deep to actually get to those numbers. And it involves 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.
- [14:13]
A
What are the other smart things?
- [14:15]
B
Abstraction. So I guarantee you you've got no pages on your website that say stripes works really well for a dentistry. Right? You probably don't have that in your docs. A very naive rag bot will be basically like, well, 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 is, well, what is a dentist? It's a type of business. Does stripe work for businesses? 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. That's one of like 27 different sort of components of fin. Then you've got obviously your rag and then you've got like, you're like, hey, is an escalation appropriate at this time? Like hey, have they threatened something? Or if 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 when you're in customer service. Yeah, 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 going to happen sooner. Will AI people learn how to do CS or will CS people learn how to do AI? Thankfully, as I said, we kind of started off with CS and AI in our DNA.
- [15:45]
A
I would say people. You mean companies in this case, like OpenAI get better as customer service faster than Zendesk gets better at AI?
- [15:50]
B
Exactly, exactly that. And I think we just. We were lucky in that we kind of had already backed both horses somewhere along the way. So, yeah.
- [15:56]
A
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? Because it just feels like it's a lot happening and we need to be making sure we're on the leading edge of AI. And then every company was like, oh, we're actually doing a lot in AI. For example, we've seen great automation wins in customer service. And so it's kind of like, you know, the joke about the bike shed, you know, versus the nuclear power plant, where everyone has opinions on how to build a bike shed. Similarly, kind of everyone has opinions on how to do AI customer service. And so I'm curious how you sell, given this. I'm guessing a lot of your customers think, oh, we know how to do that. It's not that hard. We hooked it up to a model and, you know, we're actually very smart on this topic already. How you sell in that environment where everyone has been.
- [16:41]
B
Yeah. Is like, I've Never seen the like, build versus buy thing play out more often than we do today. Especially with like, certain, Like a lot of customers are like, you know, that meme on Reddit, but I'm not like other 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 100 questions to us, Let us know. Oftentimes that's where they're like, yeah, okay, we think we need to buy your product. But I think there is a. Everyone has this idea of like, in a move to AI, what can we definitely do? And we can definitely answer questions like, how do I reset my password? And again, this is back to the whole, that's such a small amount. What they can't do is actually have conversations and all that sort of stuff. We're like, 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, 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 then like, you know, two years later you're telling people, oh, Apple intelligence is coming in 26 or whatever, right? So like in this case, a lot of people start the project, feel like they definitely don't need to buy Fin. We just help them understand the difference between a good bot and a bad bottom. And then they come back and they buy fin.
- [18:08]
A
So where is the fin 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?
- [18:19]
B
We're about 6,000 customers and growing quickly. Fin does about a million resolutions a week. We're charging a dollar per resolution, so you can do that.
- [18:27]
A
So 50 million revenue run rate, give or take.
- [18:29]
B
When we launched initially, we sold just to our own customer base. And then as we kind of progressed, we realized, hang on, moving help desk is a Nightmare. Like you've probably done it once or twice, right? You've probably done.
- [18:42]
A
It's a big jump.
- [18:42]
B
One twin. It's a whole ordeal. And Fin is brilliant. So we're like, loads of people want this product but can't buy it. So we made the decision to launch what we internally call Fin standalone or Fin for platforms. So now you can use FIN on top of Zendesk or HubSpot or Salesforce or any of those as well. So basically Fin is available to everyone and that's a relatively new muscle that we've been growing. But it's actually that's kind of where we see a lot of the future.
- [19:05]
A
Growth and so do you. Is Fin like you can connect your ipod to Windows for itunes for Windows, but we hope that one day you buy a Mac and it's part of the whole Digital Hub strategy or we're actually now all in on Fin. The engine and whatever customer service platform you use is actually not a topic of huge interest to us.
- [19:27]
B
This is such a core question that we kick back and forth quite a lot.
- [19:30]
A
This is the off site debate that.
- [19:31]
B
Is currently being genuinely at least it's certainly one of them. The way we think about it first and foremost is the future is AI. So FIN just has to win kind of 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 they're 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. I think the actual battleground we care most about genuinely has to be the AI agent. That's the one we care about most. But it does produce a lot of demand for the actual help desk product too.
- [20:11]
A
I'm curious what your AI stack looks like. Where concretely, 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 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.
- [20:30]
B
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 re ranker, 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 that means there's no one particular model. So our primary partner will be anthropic. For Claude Sonnet, we've architected it such that we plug and play various different pieces whenever a new model comes out, or honestly, a new idea for a new architecture is in. Hey. 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. Whenever we have to change the architecture, we have this kind of arduous torture test of thousands or at least a thousand CS scenarios where we have, here's the question, here's the context we're provided, here's what the current FIN answer to this question is. Here's the best available human answer that we know of. And then basically with this new version would offer us. And then so like, whenever we say, like, oh, GPT5 comes out or something like that, we're like, you know, the reason we're not just a lot of our competitors are kind of quickly, oh, we never run a GPT5. And I'm like, oof, I take a beat on that one. You know, like, you shouldn't assume everything's going to be great for your use case always. Right. And so we ultimately we have to run it through this pretty, like, expensive test to work out where the edges are if it's scoring higher resolution. Right. We need to understand why, because it could be just that, it's like trying more stuff. Yes, yes. But that could also, the shadow side of that could be like excess hallucinations or whatever. So whenever a model upgrade comes, we have to trigger this whole thing. But when we launched, fin was like 25% resolution. Today it's like 65. We've been increasing at roughly a percentage point a month, give or take, but very little of that is actually because of the upgrades or the bumps from the models. Genuinely, I actually think, and I say this with a lot of respect and love for the CS craft. I actually think we've had enough intelligence for CS for quite a while. In fact, we published some material on this on our research blog post recently. Like, when you look at like, you know, people are saying things like, oh, like the latest whenever, you know, Grok can compete at mathematical Olympiad like level seven or whatever. We're like, right. I think you can probably do most cs, you know, like, so it's often not a lack of intelligence is the reason why we're not 100%.
- [22:49]
A
It's because they're too distracted by any.
- [22:51]
B
Exactly. A lot of the wins come from like, honestly, better architecture, better like tailored models or like changing into UI can change exactly how things work. And then sometimes you will get an occasional bump here and there from model swap.
- [23:04]
A
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.
- [23:14]
B
Of the secret sauce, perhaps, but it kind of varies 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 a resolutionary graph, there's no pop, give or take one or two little tweaks. Like, it's mostly just, hey, we ground out through like, like optimizing this prompt and changing this handover. We ground out another 0.7%. And you see the AI team celebrate that on the balcony on the Friday being like, 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.
- [23:48]
A
How deep down the stack will you go? Like, what's Intercom's version of Apple Silicon?
- [23:52]
B
That I don't know for sure. I mean, we're going to chase any edge we can get right now. I think custom models is definitely where we're going. And that's like a large investment from the AI group, which is like the most contested resource that we have. Every bit of work they're doing is finding a new edge in resolution rate or resolution quality. So right now it's paying out pretty well. So I think we're going to kind of place all our chips there until something changes.
- [24:14]
A
What does selling AI look like?
- [24:16]
B
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 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. Like linear can get away with that, because their product is the sexiest. I think with AI, everyone's chatbots look the same. Everyone's kind of copied our messenger. Everyone's kind of like roughly converging on a certain UI paradigm. And so you have to ask, then when we say we are the best AI agent, what do you think all the rest of them are saying? We're the worst. No, of course. So they're all saying this and then everyone has the same screenshots because it's like, look what we do inside a chat window. So you're like, all right, how do you actually out market? And then how do you outsell? And one of the reasons we launched the Fin guarantee, this idea that we'll pay you a million dollars if you find somebody who outperforms this, is because we're trying to stress to the market this idea that we actually believe in our product to a ludicrous degree, such that you should engage with us on any sort of bake off you're doing. But I think from a marketing perspective, it's really hard to stand out. So all you can really do is rely on backing up your claims as hard as you can. And obviously customer testimonials selling is harder because I think again, in the olden days, like selling SaaS in the olden days being like pre2022, it was kind of like, our UI is nice, theirs is ugly. Here's a feature grade checkbox. We've got 24 checks, they've got 17D7 matter. We're in. And that was obviously I'm skipping over several steps. Of course, sales enablement would kill me, but you get the basic idea right and I think now selling AI is closer to selling infrastructure in a sense. It's more like, like our cloud is better than their cloud and our performance criteria are better. It's like at times it might feel like intel amd, or at times it's like it's our response times versus dares or whatever. But you're ultimately coming into it with a battle of metrics and stuff, like our resolution rate and our CSAT versus theirs. But then people say, well, why? And then you have to then explain what's actually happening beneath the surface a little bit so that people can actually get a bit of conviction other than just trust us or please just go and try our product. Because it's not that easy to try Fin. You have to still have to turn a lot of keys and open a lot of APIs and stuff. So the challenge genuinely becomes, how do you have a sales team that's actually able to speak with a good degree of familiarity about AI.
- [26:35]
A
It's funny you mentioned 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 businesses are in the business of 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 webflow 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, if you're seeing a kind of only 85% conversion rate on that form, then obviously getting it up to 90%, that's a huge deal. And those would 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 Lync then, where you're not asking people to re enter the payment details, that delivers a big offlift. The second one, which is even crazier, is after people enter their credit card details, frequently charges are denied kind of spuriously. And so your bank thinks that it's fraudulent because 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 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 had 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 because everyone is out there saying we are the thing that gives you more revenue. And we've had the exact same thing where, where despite you can have all the numbers and all the case studies in the world, it's just. It's hard to sell because it's undifferentiated as a message.
- [28:29]
B
I remember even when we switched back to Stripe, either you or Pastor, you 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, right?
- [28:42]
A
It feels unlikely.
- [28:42]
B
Yeah, it just feels implausible. But like at the same time the data is not like, not really debatable. Yeah, I think people, people like to be able to explain it to themselves and like not like, you know, I think Yava wouldn't. 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, 65% thing is gonna stick, it's not. It's just, I take it, I divide it by 10 at this stage, you know, and you tell me, oh, you're gonna save me 2 million in CS salaries or whatever. I'm like, yep, maybe in three years time we'll see 200 grand. You know, that's the kind of the default posture for a lot of these people. I think it is just, just, it's like they've developed quite an adverse reaction to like marketing.
- [29:23]
A
People do not have enough empathy for the procurement person who just has to endure non stop nonsense, absolute garbage. 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 your guys million dollar guarantee. Has that worked?
- [29:45]
B
It's 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 like what has worked is like it's.
- [29:51]
A
Landed the mess of we stand behind the problem.
- [29:53]
B
Being able to say like here is the reason why you can buy condos. I think that's a strong message. I mean obviously like being able to point to real customers with real results, sort of like and you can say, hey, go talk to Natalie at Nuuly or whatever company you want, go talk to that person and ask them. Cause like that's their name, that's their job title, they work there, they're saying this. You know, with 6,000 customers, it's kind of, it gets more believable as the numbers kind of tick up. But so like I guess either, you know, you can make crazy guarantee claims, you can just point to a lot of successful customers. For us it might be different depending on Your domain. But for us, it's not like we can show you, we can show you, hey, here's a beautiful back end product, here's fancy reporting and all that. But that doesn't speak to the courting someone's buying when they're buying AI off you is to some degree a replacement of work that they have 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.
- [30:48]
A
We'Re doing really well.
- [30:50]
B
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 we'll say like, hey, try this type of question or ask them about this help. You're almost trying to teach them to be much more conscientious buyers because we know the more informed buyer that suits us. It doesn't suit people who are just kind of like jazz hands ing their way to an AI product. But like, yeah, it's a difficult 1 Ultimately, like five years ago it would have been like, well, the trick, John, it's is GIFs. Have you ever considered using movies on your homepage? That's really engaging. None of that works anymore because I just think what you're selling is basically, it's like an iceberg. Like you're saying this little bit of upfront UI of here's what actually happens for your customers. Doesn't that look nice? And you're selling this gargantuan pile of work beneath the surface that is like, hey, all of the human toil goes away if you make the switch.
- [31:39]
A
Yeah, I can see that. What are your other pet peeves when it comes to product marketing? Actually, do you want another pint?
- [31:44]
B
Yeah, sure, sure, sure.
- [31:45]
A
See again, this one. Did I not let it settle for long enough? And then you have the small head. Like, is the settling.
- [31:50]
B
I actually think your one's gonna work out perfectly.
- [31:51]
A
Is the settling time load bearing. Okay, so what are your pet peeves when it comes to product marketing?
- [31:56]
B
I think the thing that still kills me and it's still very common is marketers that love marketing. So like you'll, rather than actually saying anything useful or specific, you'll get like, you know, forget everything you know about email. You're like, okay, what am I buying? Or like, you know, transformation Reinvented. And you're like, cool, cool. Sounds like I'm gonna reinvent some Transformers. Like, but like what's actually happening here? Yes, I think there is a general still type a type of thing where my screensaver on my my laptop is like literally a typewriter where someone said, what are you actually trying to say? And I keep that there as a reminder of like just nine times out of ten, the best marketing comes from just writing the thing you want to say. Because I do know how to 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 instead of this? Why is there 2000 more words? 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 market, 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 Ogilvie used to quote which would say something like, of all the winners of the can awards every year, something like 2/3 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 where a lot of people, 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 think that people don't get is like, everything means something. And this is like where own our CEO is so differentiated. It'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 copy paste somebody else's branding, even in a sort of like, oh, we'll change your homework along the way. I think what they're really doing is saying, we don't really understand what we're doing here. And that's why a classic of this is whenever an incubator spits out a new batch of startups and they all basically have right hand side screenshot, left hand side, three bullets, sign up button, whatever. You're kind of like, okay, cool, but have you actually thought about what you're trying to say to the world?
- [33:55]
A
There's also a thing for startups where they probably shouldn't look at what established companies are doing because stripe for so long we clung to making sure that we had code on the homepage, and people were like, if you want to accept credit card payments for your website, we're the place to come. And at a certain point, most of the relevant people coming to your page actually know that you could do that.
- [34:14]
B
And you can experiment a little bit more.
- [34:15]
A
And, you know, Salesforce doesn't have to hit CRM so hard on the homepage because after 20 years, they've earned the right to talk about Einstein a bit.
- [34:22]
B
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.
- [34:31]
A
Yes.
- [34:31]
B
Not realizing that 99.49s of the world have not even heard about the original thing yet. But there they go, destroying their original pitch by being like, and now we've got blah, blah. And I'm like, dude, no one's even heard of the original thing yet. And here you're pitching some nuanced take on the Maxtra feature. Yeah.
- [34:44]
A
Yeah. Speaking of, David Ogilvy, you've read on advertising, it was just like, that's such a beautiful book where all the marketing copy in it 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. But somehow that, yeah, it should be mandatory reading for all product marketers.
- [35:02]
B
Absolutely.
- [35:03]
A
What kind of person succeeds in product at Intercom?
- [35:06]
B
When we set up Intercom originally, like, we were kind of like, building one thing once we forked it 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 favorite app? And the amount of time someone's like, oh, you know, I never really thought about that. And I'm like, oh, so, like, what's your favorite song? Like, you know, like, I'm sure you care about some things.
- [35:44]
A
Yeah, yeah. Certainly if you're interviewing musicians, they should.
- [35:47]
B
Have a favorite song. Yeah, yeah. You'd like to think that. But they also probably have a favorite app too. So I think, like, taste is a kind of prerequisite. And then I just think, like the conference to pick a direction and a. Then we say at Intercom, we often say shipping is an act of confidence and humility. What that means is you have to be confident enough to put alive and then humble enough to take the slap in the face when you got it wrong totally and react to that slap. Don't be like, no, it's not me, it's the customers don't get it right. So I think we need high taste and then confidence and then ultimately understanding that in the Mark Andreessen sense, a product is a conversation with the market. Your launch is like your opening. 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 again, the confidence to prune certain things. And like, no, we're not building an attribution engine. Yes, we'll take on some feedback on the CRM side, but I think, like, a lot of product managers who don't work out for us are like, a lot more spreadsheet y and like, you know, they won't take a bet, they won't take a gamble, they won't take a stance. They'll just be like, forever mired and like, well, the data suggests they're just trying to hedge their bets. For us, it's just not the sort of company we are. I think we kind of believe in having an opinion about a space.
- [36:55]
A
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.
- [37:04]
B
They have to be able to. Yeah.
- [37:05]
A
And hear what I think about this a lot in the context of tech companies where Stripe's first operating principle is users first, we think that actually paying attention to what users tell us, tell us in every sense, you know, via revealed preferences in the data via. Just like when we actually have conversations with them, we start every week with Monday morning meeting. The first thing we do is we actually host, you know, with the 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. It's seldom an A. They always have things they want to fix and they're very pragmatic things that they want us to improve. There's no overcomplicating. And then when we do our weekly all hands fireside, we also bring customers to that, but I feel like there's a problem of over complexifying things and under talking to users in Silicon Valley where yeah, it's a bit too much celebration of the individual kind of product vision or a bit too much, as you say, trying to data your way out of it. And, and if you're a product manager and you're not talking to many customers each week, something's probably wrong. I bring that up because like the whole original Intercom product was a way to talk to customers. Like, this is kind of your guys. But would you agree that diagnosis that a lot of tech products would be better if people simply talk to customers more?
- [38:28]
B
Yeah, I mean like one of the ideas that still can be very erdoganic was like 2009, 2010 and 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 and I can't work this out. Does 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 all and 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. So you can kind of either get ready to meet me or just ideally other people can replicate. But question one is basically what did our user say about this when you showed it to them? And everyone has to have an answer to that question when we go in, I'm like, hey, well what did the user say? And I need to understand that because if you're not actually asking your users, what are you doing? The only validation we have is the market. I do think in the Valley. Well, I'd say the Valley, but that just basically means in the tech industry there is this epidemic of hiding behind your data and what can we instrument and how many different mix pan dashboards can prove to me that this product should be working. Just ignore the fact that it isn't or whatever. I think there's something kind of just fundamentally broken there and interesting. You say stripes. Value is like users first. I'm just curious, 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.
- [39:59]
A
Yeah, we deliberately chose users because we just meant the people using the product as opposed to customers. If there's a buyer versus user, yeah.
- [40:09]
B
You want to focus on the people.
- [40:10]
A
Who are actually using the product, the people who are managing fraud within the business or actually responsible for increasing conversion.
- [40:17]
B
Or something like that.
- [40:18]
A
So that was why we chose that one.
- [40:19]
B
Yeah. No, it's not perfect. It makes sense because I find oftentimes if you want to perfect the product, you talk to the users. If you want to expand your market, you talk to prospective buyers. But whenever I like, even in my own portfolio, when I talk like, what are you actually doing? Like, the businesses that like are, how would you say, prematurely talking to more prospects when they have a load of unhappy users are guaranteed this kind of miles wide, inches deep, messy product that doesn't actually satisfy anyone, but they'll get there. Kind of like one promise at a time. Oh, we'll build that for Johnny and Johnny will sign and we build this for Jenny, and Jenny will sign and at no point do they have one happy customer. What they have is like a marauding churn bomb of a user base.
- [40:58]
A
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're dancing with the girl that brung you over here and then you have this future potential user who firstly by virtue of the fact they're not already using you, maybe they're slightly outside your wheelhouse or the use case isn't perfect or something like that. So maybe they're not quite as good a fit as your existing customer. 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 not everyone in the org will be bought in versus the people who grew up on your product. And so maybe just restating what you're saying, I'm always struck by people are way too focused on we tried to win this big new shiny enterprise account and 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 products and really like it. But they wish you had fixed A, B and C. And just the nature of the fact that sales gets more airtime than account management essentially means people really misprioritize where they spend time.
- [42:15]
B
Yeah. And people take NRO for granted and think that like the net new revenue is hard. Right. And I think one of the things that we see a lot of is like, in terms of like working out for your current customer. 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 the AI. Okay, let's work on VTree. But like is V2 in good condition? And then permission to expand is like VTree isn't actually that exciting. Everyone's happy with V2. Now I think we can try to do something new for customers like expand our share of wallet or whatever. But I think a lot of people try to solve revenue growth with like aimless product expansion. To just try and increase the share of wallet for the people who are stuck with you.
- [42:58]
A
Yes.
- [42:59]
B
And then they convince them themselves they got PMF or like, you know, that they have like some sort of a good product because they're kind of like F. GR 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 annual like, yeah, you can force your current customers into whatever upsells you have or whatever, but your product marketing along the way is getting really difficult because all these features don't make sense and are just kind of, 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 then you end up kind of twisting yourselves in knots. And a lot of startups like Jason them can you have this thing of like from 0 to 1's impossible, from 1 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 you 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. Customers. True. Like just forced product adoption of new stuff. Like, you know, you see like here's your copilot. I know you didn't want it, you know, but here you go, like that type of thing.
- [44:05]
A
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 multidimensional very quickly now. Fortunately, complicated and multidimensional is what Stripe Billing specializes in. Our usage based billing engine can ingest up to 100,000 events a second. 100,000 events a second. So AI companies can monetize products based on real time customer usage. We're powering consumption billing for companies like Figma, Cognition and tons of other leading AI applications. Our usage based billing platform has grown 145% so far this year. So whether you're changing your business model like Intercom or starting a new product from scratch, your business strategy should dictate the billing system and not the other way around. For usage based billing, check out Stripe Billing. As you think about the prototypical $10 million 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?
- [45:15]
B
I mean the biggest problem mistake is, is like not aligning your fundraising with your tam. I think a lot of folks, 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 basecamped it more so than they did because they've raised on the assumption there's an easy path to like hundreds of millions of revenues.
- [45:41]
A
There should be more small, profitable $30 million revenue companies.
- [45:44]
B
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 you're going to easily be worth a billion or whatever. There's a genuine mismatch there where I think people have overstated how big this idea could get. As in, hey, I know all we do is time tracking for dentists in Delaware, but 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. That's one problem. Which is more like kind of business model and venture. And the other stuff I see is it is kind of like not focusing enough on the thing the majority of your customers value. It's easy to say the best business in the world is one line of code that all users execute and you sell it to all users. They're like the sweet spot. It's hard to do it in a differentiated way because obviously people learn that line of code. And that's where I think a lot of these horizontal products, they say something like a loom or whatever, they're brilliant, they're a piece in everyone's work, but they're no one's end to end workflow. I think they can do well too. But I think the challenge is when people, rather than nailing a specific small thing, going back to the earlier point, rather than saying, hey, let's get really good at X before we go beyond, when they kind of prematurely expand, I think they forego all opportunity of 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 Fidi. And I remember at the time it wasn't, it wasn't obvious to me that you weren't going to expand and do some sort of like, you know, peer to peer transfers and compete with PayPal. And I remember like you guys had the discipline, 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 we're a global creativity platform and they have this premature view of themselves as being massive and then they feel, then they go and raise off that and they need to expand into that. But I think at the core of every great business, every great SaaS business in the future, AI business is something that they're just truly world class and, 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 if you take like linear, it's basically like they have literally the 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 really well. 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.
- [48:33]
A
And I also think there's a weird celebration in the valley of Act 2. Like the Valley is obsessed with finding second acts that are totally unrelated to the first business. Like the number of people who bring up like, you know, oh, and we like invent 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 make a case for how Nvidia can be a really big company, maybe you'd say, oh well, we can expand into. Maybe we'll actually make our own gaming rigs or. Cause it was all gaming gaming at the time originally. Maybe we'll make gaming consoles or we'll expand to some larger markets. Whereas actually what transpired is it turns out the GPU market is quite a lot bigger than people thought. And being the best at GPUs is a really valuable prize and you can't rush it. It'll emerge and they could have killed.
- [49:43]
B
Themselves if they had gone in every other direction and they would have lost their edge in some sense. Figma's a great example if we have permission to expand. And 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 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 probably has really nice APIs, probably works really well, workday, blah. 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 bet. Like, obviously it's a lot easier with something like Stablecoin or whatever. But what kills me is when I'm like, I don't even want to name a weak SaaS company, but pick your favorite mediocre SaaS company and anything. Is there any direction you would allow them expand in your head? No. It's the short answer.
- [50:44]
A
Yeah. Yeah, that's interesting. Who are you really excited to adopt new products for versus who are you steering clear of the new products?
- [50:49]
B
Like if linear, I don't know, let's just say a source control tool. Like, yeah, it's probably gonna be really, really good. Seth Godin has this hilarious point where he talks about the value of brand once it's weaponized. He describes 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 gonna look like, you know the vibe of the whole place. You know everything it's gonna be, if Hyatt launched a sneaker, you're like, what? And it's just, that's the difference. Cause Hyatt has a logo and Nike has a new brand. And that's the difference here.
- [51:22]
A
A version of this actually maybe quite literally is, I don't know if Equinox launch the hotel, it's 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 shout. I just want to be able to go to my room and not have like super loud noise outside the window or like weird light coming into the room. You just want to be able to get some sleep.
- [51:49]
B
Precisely. Yeah.
- [51:50]
A
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.
- [52:13]
B
Yeah, sure. Our pricing journey is long and complex and a lot of your listeners or.
- [52:19]
A
Viewers will know Intercom pricing is a charged topic.
- [52:22]
B
Not anymore. You know, we've turned a corner. Let me just back up a bit. So like when, when we had like too diverse a product strategy, we were trying to do sales software, marketing software, support software, like sales software is typically sold based on 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, let's just 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 service this. But ultimately people are just like, I have been refreshing this for 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 first move up market. When Owen returned, one of the decisions he made was just like, hey, we need to sort out pricing. And we handed it back, truly handed back, I think about 50 million of revenue, I think was that controversial with.
- [53:11]
A
The board, with investors?
- [53:13]
B
We had support for it. I think it was. People don't really underestimate. People massively underestimate what it means to have a really happy customer base. It's cause word of mouth doesn't have like an attribution or a UTM code, if you know what I mean. So they don't understand how to think about happy customers. So making the decision to basically 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 was before AI, right? And that was like us returning to stripe was a large part of that. In fact, as a small segue, like I think like a couple years prior I had said to you or to Patrick like hey, you guys should actually build as part of your product offering a pricing page creator. And I think at the time I probably got one of those like thumbs.
- [53:57]
A
Up replies or something like that.
- [53:58]
B
I was like, yeah, whatever it is.
- [54:01]
A
It'S on the list. I think you've done it since we have.
- [54:03]
B
Yeah, yeah, yeah. But like my thinking at the time was basically some version of this, right? You need to not let your customers go wild with pricing, right? You need to like actually put some sort of guardrails onto how they think about pricing. Otherwise they're going to go and invent stuff that you guys don't support and then you're going to move all your business logic pricing is writing checks. Yes, yeah, exactly. And once, like I remember like sitting at a Stripe mini, all hands, whatever, explaining like that. Okay, now none of our business logic runs through Stripe. And either you or Patrick was saying like some personal, like that's not a good thing. I think, you know, generally speaking, my advice to any software company is like, don't afford yourself too many degrees of freedom here because you'll actually cripple yourselves in a quagmire of complexity that you'll take you many years and ultimately many tens of millions of dollars to get out of.
- [54:44]
A
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 it's kind of ambiguous or it's like, and if in the subsequent year this happens, then we go back to prior year and we do an adjustment. Exactly. 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 contracts that were agreed during the sales process. And so as you were 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 Go customer month, then that's fine.
- [55:42]
B
And having a large deal desk function and doing all the work behind the scenes. Yeah. So that was the first piece of our pricing. And then the second piece was obviously when we launched Fin, then it was like, hey, how do we charge for this? Because we're replacing seats. And at the time it hasn't proved out this way fully. But at the time FIN 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 assumed that means like 25% less seats in the future. Or at the very least, what it would likely mean is the growth rate or the NRO of the seats model will be affected by the fact that Fin's doing all the work. And now at 65%, 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 then also how do we be aggressive? As in, we really wanted to put a mark on the market that sort of says we're very AI forward. I think what Owen and Dara came up with was just like, hey, let's just charge per literal resolution every time we do work. We charge every time we don't. We don't. And this is at a time when AI was like, you know, margin negative and all that sort of stuff. We were still working out how the whole world plays out today. We're, you know, we're. We're really happy with our margins. But at the time it was like, hey, this could.
- [56:46]
A
It was a bet.
- [56:47]
B
Yes, it was definitely a bet. We made the decision and I think the market responded really well because I think it was very clear that, like, the 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 from the same vein as the guarantee, which is just. Just like, that's how, you know, that we believe in our product and that's how our product works. It's been copied a million times since. But I think the actual decisions that we made in the run up there were really, really important from a point of view of backing up our claims. And then obviously for a lot of our competitors, they were like, we don't really have a great way to respond to that because either our product doesn't work or we're kind of hooked on these really expensive resolutions. And we were totally throwing a cat amongst the pigeons there, which has been, like, really well received by the market. And our customers generally do love it. It is funny, though, like, you still get people being like 99 cents 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.
- [57:40]
A
Yeah, yeah. Have you. How much are the humans costing you?
- [57:42]
B
Yeah, exactly. And how much is your office costing you and all the other stuff you own?
- [57:45]
A
Yeah, yeah. But people like certainty. How do you get them? Okay. With the variable components, you know, you.
- [57:50]
B
Can, obviously, you can contract out whatever you want. Right? Like, but what we offered people is like, hey, like, you know, most of the time people have like, at least one or two years look back on, like, what? You know, like, we've customers who spike for tax season 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 need it. And that's like, that totally works. What we're basically saying is like yes, you don't have predictability in the sense of it not being fixed, but you have like, you can model it based on what's happened in your history and it's only really like brand new startups that don't have a clue what's going to happen but like they're not usually worried about. About this. Yeah, yeah.
- [58:24]
A
So you're using a relatively new product stripe usage based billing for this. How is that? You migrated from ZORA for that. How has that process been?
- [58:31]
B
Yeah, I mean I would say just to go back to 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 is our CTO here. He ended up actually returning to the company with one mission which was like I am going to unless fix billing.
- [58:55]
A
Yeah, exactly.
- [58:56]
B
To fix this. Right. And it worked. Right. But it was a substantial amount of work to unwind so much and then to kind of deconstruct so many of these a la carte Microsoft Word style deals into something that was a go forward acceptable or whatever. And then obviously moving towards 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 all the stuff that we needed, you guys were ahead of us on like discounts for volume, et cetera, all the sort of obvious stuff people would push for.
- [59:29]
A
Is this just where pricing in this new world goes? Because obviously no one buys labor on an unlimited basis. And at least for the moment the inputs of AI do actually scale with usage for a significant basis. And so it feels like you have to have some usage based pricing. This is certainly the batch we are making where again the reason that that billing kind of the top thing they're thinking about is kind of making billing work well in the 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, I don't.
- [60:10]
B
Know if unlimited plans will ever Well, I don't know. Here's how I think about it. I think ultimately all AI has two vectors. Just like, how much work are you doing and how well are you doing it?
- [60:19]
A
Yes.
- [60:20]
B
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 or whatever. So you're going to want to factor that in, especially if you're a consumer app as well, where people are just going to go nuts. So I think you have to have some. I'm not a fan of cost plus pricing, but it does place a kind of a lower bound on what you can do here, which is just like, hey, unlike SaaS, you are actually sending money out the back door. 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 consistent with like how much work are you displacing? I think that's where you can sort of say, hey, like, you know, for us anyway, like if you take an average person who sits in a seat to do customer service, if they do, like, let's just say they do 20 conversations a day, that's what, 400 conversations a month. When we were thinking about how we charge, we're like, hey, well, if that person does 400amonth and Fin does 65% of that seat, we're still up. Cause we're only charging, whatever, $90 for the seat. So from our point of view, it was like an obvious and easy swap. I think for a lot of businesses it might not be if your AI doesn't work or it's spurious or its value can't be articulated. 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 either. Or like, hey, you can now generate random graphics in your newsletter tool like.
- [61:38]
A
Vitamins versus Painkillers AI pricing.
- [61:41]
B
Yeah. And, and it's specifically in this case, the painkillers have a very strict if we don't do it, a human's going to do it and we know exactly what they cost and the vitamins doesn't have anything approximating that. So not only is it nice to have, it's like, I don't even know what it's worth. I saw a while ago someone said when Studio Ghibli came out and everyone's using that, someone said, hey, the fiverr.com equivalent of all these things would have been like trillions of dollars. And you're like, right. But no one was ever going to spend that. So there's no sane way to actually talk about what actually happened happens here. I think it was Bern Hobart who said that 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 make a business case for saying, swap this over to AI. It's better, faster, cheaper. I think when your AI is not tied to business impact or is debatable in quality or whatever, I think you end up with these people who are just like, oh, let's just stick a tenor on the seat and see what happens. So it's like, you know, a normal seat or an AI seat, and you're kind of like, I hope no one uses DAI too much. You're. 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.
- [62:45]
A
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 ElevenLabs. We actually had a great session at our customer event in London, but he tweeted that they've just passed 200 million in arrangement and that's two years after founding on it. Maybe three years after founding, but in my day, businesses didn't do that. And it's really striking for me how somehow they seem to climb the revenue ramps much quicker.
- [63:15]
B
I know.
- [63:16]
A
I mean, you guys with FIN is another example.
- [63:17]
B
Yeah, for sure. We forecast, like, fin will be 100 million probably early next year or whatever. And, like, back at home.
- [63:24]
A
Yeah. From when? Like, starting from, I don't know, probably.
- [63:28]
B
About two years, something like that.
- [63:29]
A
Yeah. So two years to 100 million, like.
- [63:31]
B
When we started and probably when you guys started, like, it was like, that was the threshold to go public.
- [63:35]
A
Exactly. Yeah. It used to take a long time to get to 100 million naira.
- [63:38]
B
It was like seven years.
- [63:39]
A
It used to be a lot of money.
- [63:40]
B
Exactly. Back in the day. But, yeah, it's. The acceleration is more. There is, you know, 11 is a fantastic product. Right. Like, and 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 CL4. But the things you want in an AI startup is kind of one is like, is the revenue backed by usage? And that's why I love usage based revenue as opposed to like shelfware or pilotware. Okay, we sold it to two guys in the corner and they're going to put it live someday. So you want revenue backed by usage. You want the usage tied to a real business impact. So that's the mission critical. As in like if you're building a phone product on top of 11, like if that doesn't work, that's really bad. So it's. The third one is obviously you want deep AI. Deep differentiated AI can't be a thin wrapper. And then the fourth one is like you actually want positive unit margins on 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 evolve for. It's such a rare sort of error 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 0 to 6 million overnight. It's kind of like to generate JPEGs of a Smurf or whatever and you're like, all right, cool, I'm not sure that's going to renew.
- [64:57]
A
That's the simplest AI investing framework I've heard.
- [65:00]
B
I'll tell you why it's simple because you're going to basically write no checks. So I guess I'd say most of the AI companies have invested in probably three or four. Three or four.
- [65:10]
A
I'd say the only one I might equivalent there. I think that's very good for staying out of trouble. And this is where I tend to 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. I think there's a lot of tokens happening and just generally they seem to be delivering useful outcomes at customers because they're actually delivering value on the customer service side or people enjoy their midjourney adventure. Like people are getting value from the products.
- [65:34]
B
So it's a pushback that doesn't get.
- [65:36]
A
I was going to push back on number four, which is positive unit margins. Positive unit margins because just aren't the underlying costs. Like again, when you guys started fin, 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?
- [65:54]
B
I mean this is a conversation we have internally with our cfo quite a bit actually. We're like. Because we're good.
- [66:00]
A
You can imagine the kind of thing a CFO would love.
- [66:02]
B
Yeah.
- [66:02]
A
Hey Des, you have five minutes. That's exactly AI products.
- [66:06]
B
Yeah. Hey, quick chat. I can't help but notice the team have done this like preemptive like loading or whatever. It's costing this load of money. So what's my counter to that? I guess I prefer it if the path towards profitability isn't just like the, you know, OpenAI is going to figure this out for me. Right. Like an interesting way I'd say this like with fin for example, obviously our profit goes up when we are firing less dead tokens. A dead token being we've generated an answer and it wasn't right. So we can't charge money for it. Like if you're like say like guessing the next line of code right or like tab to auto complete the next line of code if like 5 of 6 of those is wrong. I don't know if you're ever going to get bailed out because you're basically 5/6 of your of your costs is is like it's not something you can resell. So there's a question there of how much of your tokens are actually generating a thing that a user wants independent of what you charge for as long as the user wants it. I think you're always in good condition. Whereas if you're burning a million tokens to find one and that one you're never going to be able to recoup your cost. Or at least I'd love to see your telemetry to make sure that you actually have thought this through. I suspect you haven't.
- [67:09]
A
I'm curious about the co founder dynamic you guys have across all the co founders.
- [67:13]
B
Where.
- [67:13]
A
Let me try the sun. My sense is that people want to have a subject matter area based explanation for co founder collaboration where 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 we have food at home already. You got to finish the products that you're already doing or I'm more frugal and he always wants to spend all our money or whatever. The tension you're describing. And then there's a useful, well, one. It's useful to have someone to be able to. You go mad by yourself trying to solve all these fairly naughty problems. But also a good company strategy probably exists at the intersection of those tensions. Does that describe your relationship with your co founders and what would you describe as the personality tensions?
- [68:05]
B
I mean we're definitely all different. A lot of key things we all agree on own would be like a, like first and foremost, I mean 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 mindedness. 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 search, 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, even being as AI pilled as I am, I still would have like. And I even look back at my own performance in that period and I'm like, you know what? I wasn't brave enough. Like, one of the things Alan pushed for was this idea of creating the team fin which is like, hey, let's just build a new startup. Let's isolate them from everything else. Different floor, different section of the office. No one else is in there, 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 focus that we needed.
- [69:10]
A
People might be offended.
- [69:11]
B
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 an example, and I'll come back to the company, anything in a sec is like, they tell themselves that they've done enough because they, oh, a few sparkly buttons. The merge features AI and we're happy.
- [69:40]
A
We have an AI assistant.
- [69:41]
B
Yeah, exactly. And we've updated our homepage to say we're AI first, so we're good. And I think you need to be willing, genuinely willing to make brave, hard to undo bets. And I think you need obviously having this sort of moral authority of a founder and then being CEO kind of gives you some of that. But the, 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 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. But I mean it is a cocktail. Like it's in. Somebody needs to go and actually do the thing once we've decided what we're doing as well. Because the way it ended up, I was leading Team Fin after Owen decided it and that was ultimately what led to the creation of the whole Fin Initiative or whatever.
- [70:38]
A
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.
- [70:46]
B
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, 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 going to have a chance chat room and they're gonna all hang out in an 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 so you would have missed out on Slack or whatever. Right? But I think like I can almost you know, hear from the like, you know, what are you building and why and who's it for and show me what the product does. If it's not a real solution to a real problem, I'm kind of already out. And then the other big, I'd say prediction is just like there's one of the things that's happened in the last 10 years. I'm sure you've seen this a lot is like it was a lot easier to invest when being a founder was uncool. And I think like combination of like I blame genuinely the social network. I blame just kind of the entrepreneurial lifestyle. I blame my TikTok. I blame all these things.
- [72:02]
A
Soho House.
- [72:02]
B
Yeah, yeah, yeah, exactly. Yeah. All of that. Right. To some degree, like remote working, I nearly 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 kind of go and build something if their actual motivation isn't the problem or isn't just some deep like desire to be quite successful, but it is instead to be perceived like the whole kind of I could have been a contender rather than I could have contended 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 best case scenario you'll sell at 5 million but more likely you'll still be alive in seven years. All your investors will wonder why you're doing and you'll be basically sending one investor update every now and then.
- [72:46]
A
Yes, I have noticed investor updates with metrics don't predict success. But investor updates without metrics that tell a really fancy story but don't have metrics are actually quite predictive of failure. Those companies always fail.
- [73:04]
B
I basically 100% agree. And honestly, you can even tell where the metrics are in the update because often my favorite update, I mean this.
- [73:12]
A
Company actually probably should and no, investor updates are fine. There's like a bunch of successful companies. We never sent investor updates. Like, I'm sorry for investors, but we were bad communicators.
- [73:20]
B
I was curious.
- [73:21]
A
Yeah, yeah. But if. Exactly. But if you go. 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 means.
- [73:36]
B
So there's one company I can't say, but like we're both an investor in it, but like they're up 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, I hope you can see from the numbers. We're doing great. Best of luck. See you next quarter this month. And I was like, yeah, brilliant archive. I'll mark it up. There's something like. I think in general, the degree to. I think it was Paul Graham said the ratio of numbers to words is usually the actual thing you're looking for, which is if the number is speak, the words don't have to.
- [74:06]
A
Yes, yes. What else is predictive of success? Numbers is one.
- [74:10]
B
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 updates 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, 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?
- [74:36]
A
They're like, oh, we're going to ask them. Maybe what you're describing is there's a very boring playbook, boring and glamorous playbook for making products work about writing code, talking to customers, running that iterative loop and avoiding distractions. And people who seem incurious about that playbook or just are failing to execute on this is kind of a warning.
- [74:57]
B
Yeah, I would say that's definitely true. So it's basically like, if you've got a decent product, decent area, real solution, and are you just willing to work on the boring stuff that needs doing to actually make that whole thing? And then will you get bored in a year or are you still excited by it? I think to some degree, even a successful founders can get distracted by glamorous opportunities. Whether it's like, oh, there's a new wave of whatever, like crypto or NFTs or whatever, you'll see people get their head turned or quite a bit. And I think that if you're genuinely married to the problem and married to the solution, you'll tend to sort of not be as distractible. And then like, so many of these businesses just need time. They just need time and execution.
- [75:37]
A
Yeah, totally. Last question, because I've had a lot. In what ways is Intercom itself AI native.
- [75:45]
B
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, 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 ground, but it doesn't really matter. The measurement is. I think it's deployments to production involving code that has to execute regularly, right? So it's a hard thing to fake, which is if you fake it, it's like, we should probably fire you now. Interestingly, everyone's just like, is that just the engineers going really hard? No, there's so many different elements to. But one of the biggest ones that we saw recently, which really has been awesome. As Emmett, our head of design, he basically said, every designer by August 1st needs to be shipping code. This is like the end to the discussion of should designers code? Right, Designers should code. So we basically said, hey, all designers can now ship code. Weirdly, the win there is that the amount of engineering distraction has just gone away. So every paper code in your UI used to result in a GitHub issue that would get filed and triaged and get picked up on a Friday, right in between breaks or whatever. And now all that just goes. So 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 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 engineers who are now doing far more, staying in the zone for far greater using, whether it's called code or codecs or any of those, or augment or any of those tools to actually just be far more productive. And there's some real wins here. One recent one we had was Fin Works in Slack, but when we were building that, it was built very firmly from 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 cloud code, right? The Microsoft Teams, the discord, the WhatsApp, it's every other solution. So we went live to production with Slack, but I think we have everything else now in public beta and it'll all go live. So we're finding all these things is 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. On the go to market side of the house, we've been slower, but like, I think we're looking at like, we've trained a GPT, if you like, on like all of our marketing copy, our principles, our content, our visuals, et cetera. And we've been using that to produce a lot of like, you know, stuff like event invites and things like that.
- [78:14]
A
Well, Des, thank you.
- [78:15]
B
Cheers. Thanks very much.
- [78:16]
A
Yeah.