He built for 2 years before raising a dollar—then hit $13M ARR and a $40M Series B. | Alex Halliday, Co-Founder & CEO of AirOps

Alex Halliday (00:00:00) :
So I was talking to Sam Altman before ChatGPT was a thing and I said, "Hey, what's got you excited at the moment?" Or some vague question like that and he's like, "the AI stuff's getting really good." And I had no frame of reference for LLMs. We got to a million in Q1 of 2024, and then we hit thirteen in Q4 of 2025. It was the machine starting to work, the positioning getting better, as I mentioned, and just it really clicking with the market.

Pablo Srugo (00:00:27) :
When was the moment when you felt you'd found true product market fit?

Alex Halliday (00:00:30) :
I think when I stepped away from the business for a week and we closed $300k or $400K in new ARR. And I came back, and I had nothing to do with any of those processes.

Previous Guests (00:00:43) :
That's product market fit. Product market fit. Product market fit. I called it the product market fit question. Product market fit. Product market fit. Product market fit. Product market fit. I mean, the name of the show is Product Market Fit.

Pablo Srugo (00:00:55) :
Do you think the product market fit show, has product market fit? Cause if you do, then there's something you just have to do. You have to take out your phone. You have to leave the show five stars. It lets us reach more founders, and it lets us get better guests, thank you. Cool, man. Well, Alex, welcome to the show, dude.

Alex Halliday (00:01:12) :
It's great to be here.

Pablo Srugo (00:01:13) :
So you just raised a $40 million Series B from Greylock not too long ago, and you're in this world of which there's a few players. So we're actually going to talk about what you do differently and even just maybe broadly about competition. Because it's a huge topic these days but what you do is you help, kind of like there's SEO to rank up on Google, and now everybody's trying to rank on all of the different chat apps. Whether it's ChatGPT or Claude or Gemini, and you help companies do that. So, we'll get into how that all started. Maybe that's a good place to start, tell me a little bit about what you were doing before you started AirOps. Just give me that context.

Alex Halliday (00:01:47) :
Yeah, for sure. I mean I've been in early stage companies for now about eighteen years. I got started pretty young. First half of my career was spent as a founder in the UK. I ran a social networking platform for five years. We had about fifty employees. We were battling Marc Andreessen's startup at the time. Can you believe it? And then I went to San Francisco. Originally for six months, ended up staying for ten years and during that time, I was the first product hire through to an established product design engineering org for three Series A companies. And I took them all through Series CD, including MasterClass. Which is the one most people have heard of. So I've always lived at the kind of intersection of product growth and engineering. That's where I'm meant to be in the world.

Pablo Srugo (00:02:33) :
And when did you start AirOps?

Alex Halliday (00:02:35) :
We actually incorporated the company during the pandemic, and I was building with my co-founder for a full almost two years before we raised any money. And this was nights and weekends, tugging ideas, playing with things, and also forming the relationship. Because, you know, I've had many co-founder relationships in my life, and that is the bedrock of the whole thing. So we founded in 2020, but we ended up raising money and really finding our initial team at the end of 2022.

Pablo Srugo (00:03:01) :
Just tell me a little bit more about maybe the origin story for AirOps specifically. How did you decide to get into the space?

Alex Halliday (00:03:06) :
Yeah, so we actually spent a couple of years in the idea maze. So the initial area we were exploring was really building for ourselves. Having run incredibly complicated teams in marketplace businesses and the fact that our teams never had the right data at their fingertips to run their roles. So we were dealing with product teams and frontline teams. It was just this mess of spreadsheets and CSVs. So we actually initially built a workflow tool to help those users and basically help us in a form of life. And that was a good six to nine months of building in that space. We launched a couple of products with different takes on the problem. We got our first ARR from our first few customers and then right in the middle of 2022, we actually started, I actually started playing with the early OpenAI models. So I was talking to Sam Altman before ChatGPT was a thing and I said, "Hey, what's got you excited at the moment or some vague question like that." And he's like, the AI stuff's getting really good. And I had no frame of reference for LLMs.

Pablo Srugo (00:04:09) :
Did you know Sam or is that an event or what?

Alex Halliday (00:04:11) :
I knew Sam, yeah. So we met when I first moved to San Francisco, walking down the street. Actually, during San Francisco Pride. We were just wandering down the street with ten thousand other people and he was walking next to me. We got chatting. We've been friends ever since.

Pablo Srugo (00:04:25) :
No way! That's just crazy coincidence.

Alex Halliday (00:04:28) :
Yeah, it's crazy. Well, that time in SF as well, you just would walk into a coffee shop and Jack Dorsey would be there or Kiefer Boyce or Peter Thiel. I look back now and I realize how insane it was. But yeah, that was the origin story there. So he got me onto LLMs, and I just totally fell down the rabbit hole, and the business started moving in that direction. And that was kind of one of the big inflections in the business that changed its direction.

Pablo Srugo (00:04:53) :
Yeah, tell me more about that time because I can imagine as you're playing around with these tools is right before ChatGPT. On the one hand, I'm like, yeah, I could see how you play around. You're like, wow, this is so impressive. It's not that easy to connect that to a business opportunity, like you figure out, OK, here's how I'm going to use this. What were some of your initial guesses?

Alex Halliday (00:05:12) :
Yeah, it's such a good point. I remember I was on a plane flying to Atlanta and I was like, OK, I'm going to go do this. I'm going to try this OpenAI thing and sign up for an account. So I remember my first few prompts I put in were actually around SQL generation. It was like, can it create credible SQL for actually working with Shopify stores randomly? That was my initial throw at it and when it started coming back with kind of joins and, let's say, plausible SQL in those days. I just felt like the laws of physics that govern software were changing. It was just one of those moments where you're like, wow, there's this general purpose intelligence, and I didn't really have. Honestly, a fantastic business case for it back then. We started applying it initially to generating SQL and explaining data tables for customers. We released a little Chrome extension on Product Hunt. We started, you know, just kind of creating little experiences for existing customers. But there was this pulling of a thread that took us about six months that led us to our eventual customer, which were marketing teams. But what I realized was that there was going to be this explosion of use cases and businesses that would use this technology. And for me as a founder, the idea of being truly horizontal and trying to do everything for everyone just kind of lowkey terrified me. I remember feeling very strongly that we needed to pick a customer that we wanted to build for a decade and we had people using our tool in all these different ways. And I just looked at this map, and I felt if we try and serve all these people, no one is going to be happy. So we ended up picking marketers. It was a great choice. They found us, and then we doubled down on them.

Pablo Srugo (00:06:51) :
Just to be clear, what were marketers doing with the product initially?

Alex Halliday (00:06:55) :
Yeah, it's a great point. So we had a four-step workflow template for writing an article like a blog post template. It was very throwaway. We put it on the platform and I remember thinking, no one's going to need something that's four whole steps. That seems like a lot and then we would log into the platform on a Sunday evening. And we would just see all this activity, and we would click into it. And it was marketers building like fifty to eighty step workflows, to try and do really precise content work with LLMs, breaking down the problem into little steps.

Pablo Srugo (00:07:23) :
And this was, by the way, timeline? Was this before or after ChatGPT? What are we talking about?

Alex Halliday (00:07:27) :
But at this point, this was very early in 2023. So this was just after ChatGPT.

Pablo Srugo (00:07:32) :
Just after. OK.

Alex Halliday (00:07:33) :
Yeah, yeah, so it was people who played with ChatGPT, and they wanted to do more with it. So they were like, OK, like this, I want to orchestrate it, I want to do that extra mile and so they were coming to our platform. And I remember just thinking, is this the customer that we want to build the business against? And what I loved about marketers is they are so creative with the technology, and they have really high taste. One piece of advice is build against the high-taste user, and they will keep rejecting you till you pass their very, very established exit criteria for a problem. And it's the best way in the early days to get really good at something, in my view. It's very hard for a team in the abstract, unless they have recently practiced that role, to know what very, very good looks like. So that was kind of how we found our true customer that we ended up building a whole business against.

Pablo Srugo (00:08:20) :
And what exactly were they doing eighty steps for? What was the end product of that?

Alex Halliday (00:08:25) :
Yeah, so in those days, it was a lot of content creation for pretty basic stuff, right? But it would be like creating local pages for a national franchise or things that we typically call like programmatic SEO. So that was our first real cluster of interest. So I remember the CMO over at Deepgram created a workflow where he would look at Product Hunt every day for new products. He would then research those companies and create pages for each startup that launched on Product Hunt that met his criteria. And because those companies had nothing written about them, he would rank number one for all of them. And because Deepgram had domain authority. And so he'd figured out this sort of early use case for LLMs to create interesting, novel content in a semi-automated way. And I think it's 35x Deepgram's traffic to their website. So that was an early opportunity. Now, the space has moved on a lot from that, but it was incredible to see both the energy they were putting in and the wins that they were getting.

Pablo Srugo (00:09:24) :
So this is interesting because it's this mix of you've got a product, you've got some data, you've got people using your product in a certain way, and you're actually able to leverage that to double down. Let's go deeper on that because I think this is not an easy thing to do and a very important one. How do you take that next step? Do you go to everybody that's using it on the marketing side and have fifty conversations? Do you start maybe more from like first principles, you know, strategy? What is kind of that next move to say, OK, if we're going to go all in on marketing. What does that really look like?

Alex Halliday (00:09:55) :
Yeah, I mean, I think it's a good question. The first piece of it for us is, can we solve the problem for one customer really, really well? So it's that true solution acceptance by a high-taste user. Where they go, this is it, this is great. I will be a referenceable customer. I really, really like this, and then you have to figure out whether or not the pain that this problem that you're solving is widespread enough as you need it to be, and also acute enough. You don't want to be people's number three or four problem. You want to hopefully attack their number one problem. So whilst you're figuring out if you can actually solve the problem, what the solution looks like, starting to learn about the shape of the sales motion. How you would end up selling this to more people. How broad-based this problem is in the market is incredibly important as well.

Pablo Srugo (00:10:41) :
But how did you do that? How do you figure out that you're actually not? Because I agree, you've got to be a number one pain. So how did you figure out that you were solving a top pain for these customers?

Alex Halliday (00:10:49) :
I mean, for us in those days, there was an initial concentric circle of investor intros and network intros. And so, we would try and book our calendars as full as possible, just talking to people about this again and again. And then the outer concentric circle, which is almost more important to me, was starting to just do the basic growth tactics at a low level of scale. Meaning like just having some LinkedIn outbound going from a founder to your ICP. Start sending cold emails, start asking for intros and the goal here is to really look at things like the response rate and the appetite. And how quickly people get back to you when they don't have a natural incentive to. And I think the other thing I did not appreciate as someone who spent most of their career in consumer was just how important positioning is. And I cannot state this enough. Everybody, I mean I'm a product person, I really believe in the great product wins in the market, but I have been humbled so many times over when we have not clearly articulated what we do in a way that resonates with the buyer and it's like that is a continuous game of iteration. And to your question, at no time is it more important than when you are initially testing the waters in those early motions and you're listening for signal.

Pablo Srugo (00:12:05) :
Do you remember the messaging that didn't work and the messaging that ultimately worked?

Alex Halliday (00:12:10) :
So what worked for us at the very, very beginning was, this is a bit of a cheat code for us. Was we mentioned our investors in the outbound to get people on the phone. That doesn't pass the sniff test of saying with the second concentric circle. I think what we realized, and another reason to get very, very focused, was that proof point driven outbound is just so important when nobody's heard of you. So you have to leverage other people's brand equity. So really being thoughtful about who you know that you can turn into a referenceable proof point really early, and then using that to at least get people to open the email. So when we had this Deepgram case study, when we had those early proof points, those early wins. That was the thing that stood out far above our name or any other detail about us and then, can you get them past the second or the third message with the problem statement? And for us, it was very much about this notion of organic growth being very challenging for the people we trying to reach out to, and they were a higher sales process. You have to arm the seller with the right talk track. You have to make them feel like they'll get promoted. You have to continuously kind of nail that as you get introduced to other actors in the buying process, especially as you start to ask for bigger and bigger contract sizes.

Pablo Srugo (00:13:39) :
And then like what you're doing today is pretty different than what you were doing then, right?

Alex Halliday (00:13:43) :
So about seventy percent of what people use our apps for is a combination of content creation and refresh sort of operations. So that's a huge part of what we do. That's where we're like light years ahead in the market and where we really take a lot of time and care to make people successful. We have a team of about forty people who just work with brands all day long to sort of do those use cases, albeit generation eight of those. Given how much the market has changed and now we have a new consumer, a new audience in town. Which is agents, who are a big, big focus of the kind of content work we do now and then the other thirty percent would be all of the analytics we do around how agents are reading content. Which content they prefer and why? Which content is influencing the sentiment of agents. So it really is the combination of the production of content, the mainstays of content, and the analytic story that drives that.

Pablo Srugo (00:14:36) :
So maybe let's go deep on content marketing. Clearly you're an expert on it, and the product you've built is around this, and, frankly, everybody's interested in getting more traffic, getting more views. That world is completely changing. I mean, the old world of SEO, at some point the playbook is pretty figured out, write content, write blogs, high quality, fresh, keyword density, etcetera, etcetera, and rank over time. That's very, very high level, but that's more or less a playbook. What does best in class look like? We get to start high level, or if you have any examples that come to mind of something that somebody's done recently, or something that you're doing for someone that is really working and really driving traffic, that would also be interesting to hear.

Alex Halliday (00:15:12) :
Yeah, I mean, I think it's interesting that we created this separate category of AEO for a long time and now I think there is this conflation again into one system. Which I think is actually a better model. You know, Google is going AI first with AI Overviews and AI Mode, ChatGPT, and now Claude. Very important for businesses to understand. I think much of the practices that worked very well in SEO continue to work, but the contrast is turned up on some of the sub-bullets. In particular, the importance of information gain, so adding materially like net new information to the market through the content that you write. So Zola is a customer of ours. They have all this pricing data on how much things cost in weddings. So they create these pages which talk about how much wedding florists cost and wedding buffets and all the different variants of weddings. Because they have all this really interesting data inside the business and so their play is really providing, the models and human users with just this amazing set of content. That talks about all of those interesting pricing and vendor questions that come up. Maybe Klaviyo is another example of ours where they have all this data on email open rates and the behavior of email for marketers, and they can use that to combine with their internal experts, and internal expert interviews to create rich content about all the practices that email marketers do. Because that's the audience they're really trying to talk to. So I think information gain is one big theme of how can you take unique information from inside the business and put it outside the business.

Pablo Srugo (00:16:43) :
Let me ask you this, maybe because I'm selfish and maybe we can make it tangible. We go through some of the ideas through this. Let's say I was actually a customer, for the Product Market Fit show and I'm like, I want to get more views. I want to get more traffic. I want to rank on all the chat apps and on Google and all this stuff. And money is no object. I'm not going to, I don't want to do paid stuff, fully organic, but money is not the issue, right? What would be some of the things that would make the most sense to do?

Alex Halliday (00:17:05) :
Yeah, so one thing we would do is we would figure out the intents that people are expressing that the Product Market Fit show probably isn't a good place to answer. So we would have a couple of agents that would spend their time looking at startup conversations, Hacker News, Reddit. Really understanding what the evergreen questions are that people are asking and the discussions people are having. And then what new questions are emerging, because Claude Code is on the rise or the QBs might be removed from New York State, right? So you really want to think about evergreen questions and then frontier questions. So that's the intent cloud that you have a right to speak to, and then it's the content creation to speak to that. And so, you would put all of the transcripts that you've ever had on the show with a definite bias to the most recent ones into Aerox or into a system like Google Drive or wherever they live and you connect them to us. And then, we would have a process which would on a regular cadence, identify the highest priority questions to answer. Would ping you to then go and approve those along with a ton of research from your shows. Probably some questions for you to answer as well to really make sure that that article had your perspective, your overarching narrative and then we would publish that content rich with references to your shows. Like links to where people could go get them on Apple Podcasts or YouTube, and treat that as an ongoing content production drumbeat. So that you can start to get all of the great value out into the world in an organized way, and then on the pages of content themselves. We don't have to go into all, but there's best practices around structuring that content to make sure you're basically spoon feeding those answers to the models and preparing them for citation. Because ultimately you want to be quoted a nice big paragraph in a ChatGPT response saying on the Product Market Fit show, Alex Halliday said, XYZ, and that's a really useful chunk that matches the user intent that you've identified as one. So that would be one loop that would be really valuable to you. You'd be totally within your rights to create that and it's a durable strategy for you. It's not something like gaming the system and consumers would love it. You're adding to the conversation.

Pablo Srugo (00:19:14) :
That's the classic blogging approach, just using AI to make sure that you're always touching the latest frontier questions and leveraging as much of the work you've already done in the past.

Alex Halliday (00:19:25) :
Yeah, and I think if you were a brand in that same situation. You would really think about what are the offsite, like not on your own domain. What are all the pages that influence the ChatGPT for those priority questions as well. So we do a full audit of that. You've got, a heat map of influence. So maybe Reddit or a Substack, or a YouTube channel driving most of the sentiment and opinion for the things you care about. And so, the play for those would be different. Obviously, it wouldn't look like publishing. It would look more like outreach or conversation participation.

Pablo Srugo (00:19:56) :
Let me ask a little bit about competition. Competition has really risen to the top, at least for me as a VC. It used to be a bit more of a secondary thing. I think any investment, obviously, you ask about competition but it was not the most important thing. Lately, it just tends to be number one. Because there's so many ways to deliver insane value. Really, the big question is, why isn't everybody else going to do it? With the example you gave, my question would be something like, why couldn't I, or what's the difference between what you're offering and let's say putting all my transcripts into Claude Code. And then, having a scheduled task that runs every week and checks the latest questions, and writes a block for me.

Alex Halliday (00:20:31) :
Yeah, it's a great question. I mean, you certainly could do that. It actually might work quite well, to be honest, given that use case. But if you think about content in the current market, competition exists on the startup side but it also really exists on the content side as well. So each piece of content is in composition with a sea of other pieces of content and so to get the most from an AI model. It's much less so the capability of the model, it's much more so the context that you can have available for the model, right? When doing any sort of content task inside of AirOps, we have a huge data engineering team whose sole job is to make sure that we can give that model an unfair advantage when it's tackling your problem. So if it's, for example, a page you want to have ranking in Google search or it's a particular question for ChatGPT. Before you even start writing we understand every single page that is in competition with it, we understand all of your pages that could be in competition with that, you don't want to cannibalize your own content. We understand which questions you should even be going after in the first place. We collect almost one point two billion answers every sixty days from these answer engines and we analyze them. And then once you create your content, we also have a full picture of your tone and voice, your do's and don'ts in your language, your sitemap for internal linking. So you can think of this as like if Claude is the model at the beginning in the center of the picture, can you give it these concentric circles of knowledge that are actually quite hard to compile, but give it that unfair advantage so the content you create is more likely to win, and then the nice thing also about doing things through us is we also track the impact. So you know, hey, in January we published twenty eight pieces of content. We know that ten of them are absolutely crushing it and we should go do more of those. And that knowledge feeds back in to our agent on a go forward basis. So I think in the case of like working with your transcripts, you would have a really good result just doing that with Claude Code and that works well. I think when you're dealing with tens of hundreds of thousands of pages or millions of pages. Prioritization is the most important thing, followed by the context you can provide on competition and those are two things we nail for our customers to make sure they continue winning.

Pablo Srugo (00:22:44) :
I'm really worried because listen, you've been listening for what? Ten, twenty, thirty minutes now? Clearly you like it and the thing is, the next episode is way better and you're going to miss it. You're going to miss it, because you're not following the show. So take your phone out and hit that follow button. And do you see any reasons for what works broadly? Because again, we think about this strategy, it's the same strategy just done with AI. But is there any reason that this changes? This is something you hear a lot. It's like, well, there's going to be so much AI written stuff, slop. Whatever you want to call it, whether it's good or not. It almost, when you just think about that at a high level, you're like, there's no way this is still the future. There's no way five years from now, it's still all about blogging. There's going to be so many blogs, but is that real? Or is this just going to be, this is still the strategy and there's a reason for it?

Alex Halliday (00:23:27) :
I think the human web will continue to exist. I think AI content gets conflated into one blob. I think some of the best content created uses AI and much of the worst content uses AI. That's not the right distinction. So I think understanding that there's really great applications of AI to improve content quality and also improve content health in the long term, is something that I think folks need to understand on that front. But the human web is designed for humans to click around and right now, we're duct taping agents over the top of that. So ChatGPT is going to a search index and is retrieving pages, and including them in its response. And there's a lot of protocols out there that look to try and unseat that, including one called NLWeb and, obviously, traditional MCP as ways in which ChatGPT can ask us questions about the Product Market Fit show and get back the perfect snippets without ever having to visit your website. Irrespective of what the protocol is, whether it's going through a search index and going to the web or going directly to an endpoint for the Product Market Fit show in this example. The underlying content needs to be really, really good. So I actually look forward to us moving on from creating yet more pages of content to something smarter and we actually interviewed Glenn Coates from OpenAI at our last conference. Who is running the OpenAI apps program and he said they're really actively exploring this for later this year. And the way he positioned it to me was you want to be the sharpest tool for the job. Meaning if ChatGPT wants to know about congestion in Barcelona or the best restaurant to go to in Copenhagen. They are going to start to form an opinion of which tool is the best for the job to answer that. Which can give the model the best quality response and allow the model to do even more for that user's journey. Yeah, it's going to change. I think as we've seen with many of these things, the behavior of going to websites and reading content is such a muscle memory for billions of people. The web isn't going away in its current form, but it will have a sibling of kind of agent first web, and I'm excited to see that develop.

Pablo Srugo (00:25:33) :
When in the story did you land on the current idea and maybe share the story of how you went from what you were doing originally for marketers to what you're doing today?

Alex Halliday (00:25:42) :
Yeah, so I think my co-founder and I got us to about $1.3 million in ARR selling ourselves.

Pablo Srugo (00:25:50) :
Just the two of you?

Alex Halliday (00:25:51) :
Just the two of us. Yeah, and it was a slog. You're on the road, you're trying to persuade people that you can meet their problems. You don't understand the problem well enough to be honest at that stage. It was very hectic and you're also doing all the deal paperwork. It is full on product roadmap, design, everything.

Pablo Srugo (00:26:08) :
So before you move on, why did you keep it to just the two of you? I've heard a few people do that, and I actually think it's a good idea. But for you specifically, why did you keep it to just the two of you to get to a million ARR? Why not hire at least, I don't know, four or five more people?

Alex Halliday (00:26:19) :
Sorry, I meant two of us actively selling and dealing with customers. Yeah, so we were doing the full deal lifecycle, prospecting, we were doing everything. I think the team was probably about eight or nine at that point, yeah.

Pablo Srugo (00:26:32) :
That makes more sense, gotcha.

Alex Halliday (00:26:34) :
Yeah, yeah, yeah. It was still a knife fight and I remember right around the time we raised our Series A, we had about sixty percent of our revenue came from these core use cases. It was larger B2B SaaS businesses, their content was stale. It was really bad, they had these blogs they've invested years of work in and all the product positioning was out of date, all the links were broken. They were like, oh, this is horrible. Let's contact AirOps and we'll help you with that. The real inflection point for us was actually hiring our first sellers and actually having them, have to learn and then practice and then perform the whole sales process without us. And that handoff was so nerve wracking. But what it forced us to do is really kind of focus our solution and what we were talking about. I think that transition, you shouldn't do it too early. You definitely shouldn't do it too late. But you also need to make quite a lot of decisions and stop doing a lot of things in order to make a fresh sellout coming into that environment successful. So it's a forcing function for focus.

Pablo Srugo (00:27:37) :
Give me a sense of just that growth curve. How fast did you get to a million? How fast did you get to, five or ten or whatever?

Alex Halliday (00:27:42) :
We got to 1 million in Q1 of 2024, and then we hit ten in 2025. That was kind of a big ramp for us. We actually hit thirteen in Q4 of 2025. So that just was like an insane year for us. It was the machine starting to work, right? It was the positioning getting better, as I mentioned, and just it really clicking with the market with the tailwind of AI and people being concerned about ChatGPT, and shifts there. But then also internally, really learning how to have a repeatable motion. Which something that my co-founder actually has really been leading, but it has been a masterclass to me in iterating on process and just continuously practicing, and tweaking as we learn more and more. And the sort of sophistication of that just building over time.

Pablo Srugo (00:28:29) :
Yeah, let’s go deep on that. I’m thinking in my head, I’ve got this portfolio company I work with closely. We’re at $2 million ARR, things are clicking, product market fit is there. We’re trying to get to that 10 number, and things are just working but it’s a little bit still happenstance. Still a little too messy, not predictable. What did you do that really worked? What is that setup that you ultimately ended up with that helped you grow from one to thirteen and whatever that is, eighteen months or so?

Alex Halliday (00:28:55) :
Yeah, we had two sellers in initially, right? So we had two AEs that really taught us a lot as founders about communicating the process and really iterating that kind of default playbook. Because you can do jazz as a founder in a way that you can't do when you have real sellers in. So first two in, there's some competition between them, right? So that's good. You don't want just one because you have no point of reference and what we quickly learned through those two is that people really liked how we were showing up, like the personality of our sellers and how it was a consultative sale, right? Because AI is scary, people are anxious, people don't know what to tell their board, the boss. It's a time of a lot of emotion, actually and so we learned very early, that showing up and being disarming, helpful, knowledgeable, and prepared really worked. So the first thing was like, can we make these two sellers successful? Turned out they absolutely crushed it. But interestingly, in very different ways, they had very different styles initially and then the next thing was finding our sales leader. And that's a hard one, right? Because as with any exec right now, you don't want people to over rotate on a playbook that's like kind of out of date because things have just shifted. But you also don't want people to have no frame of reference or sense of what good looks like. So you're actually trying to thread the needle where they know a lot and they're also prepared to throw it away should they need to. And we found this sales leader called Nick Casale who just felt it was a little bit more of a step up higher than some of the other people we talked to who are seasoned SaaS veterans. They've fucking seen it and done it. Sorry, sorry and my co-founder and I met with Nick and he was just, first of all, incredibly charming and had done his homework and prepared. And I think following the line of people, buying from people, they really, at this moment, want to feel a sense of security and safety. I think, particularly from their vendors, weirdly. We felt like he was the right fit and he was able to then bring in a lot of, people from his network and start layering on. But the amount of iteration you have to do on this process is wild, like across every dimension from first call deck to how you do discovery to the AI processes you have in the background for processing sales calls.

Pablo Srugo (00:31:07) : 
What were some of the biggest findings? I don't know if most of your leads are outbound or inbound. I don't know what your process is, if you have a demo or if there's PLG. What were some of the biggest things that you're like, holy shit, that really worked? 

Alex Halliday (00:31:19) :
Two things, deep discovery at the beginning and I'm a founder who wants to talk about product but I've really learned to shut up and ask questions. Then showing up really prepared. There's a specific channel we focus on. It's organic growth. There is publicly available data on that. We understand how they're doing. We understand how their competitors are doing. We can talk to that confidently.

Pablo Srugo (00:31:37) :
And this is enterprise sales, by the way? What's the ACVs just for context?

Alex Halliday (00:31:41) :
Enterprise sales. The ACVs are sixty to two hundred and fifty, right? It's a big range.

Pablo Srugo (00:31:46) :
OK, so meaningful. Not massive, massive, but meaningful enough it's worth spending the time.

Alex Halliday (00:31:49) :
Right, and so we really got very good at all of the automations of background processes and things to make our team fully prepared, right? To step into that call and not to firehose them with information. First to listen, really good discovery and then to start to talk to them about their priorities, but in the context of their priorities, have the data to have a meaningful conversation. And for some sales reps, that's quite different, right? Because they're used to saying, we sell email marketing software and it works like this. But actually, we need to earn the right to be part of their stack at this moment. Because competition is so high and we earn that right through the software. But also through the feeling that they have when they leave a call with us, and really giving them the feeling that they want to bet on us for a three to five year period as things change just immeasurably. So I really just have a lot of respect for how my co-founders run this and worked with the team to just create a culture of, experimentation and just making sure we learn with every call.

Pablo Srugo (00:32:48) :
For the higher end of that, the ones that are let's say $100k plus, right? Are you doing pilots? Are you doing some sort of trial period? Are you just signing them up annually? What works? 

Alex Halliday (00:32:57) :
You have to do pilots at the beginning. You have to be prepared to prove your value. We actually, last year, I think we had all but two pilots convert to annual. Which in the world of AI is actually insane and it's because it takes us four to five weeks to onboard a customer. Because we take them through a really rigorous process that we've actually built out of necessity. I'll give you one tiny sliver of that, is getting a customer to agree on their brand voice. So that they can actually use our systems and people think they know, but they don't know until you start showing them things. So calibrating with customers, that onboarding process, us holding their hand through that flow and making sure that they get to great as part of that POC is how we build a lot of trust in us. So we do POCs sometimes, less and less honestly, because there's a lot of proof points in the market. We typically start with two really strong focus areas that we want to work with them on. Because there's a million things we could do and then we have a roadmap of things we want to get to. And then one thing we've invested in from the beginning is education. So we offer to put all our customers through a training cohort where it's super fun. They become a content engineer at the end. A lot of people update their LinkedIn job titles. We throw conferences around that. So education-led sales and a consultative-led sales has been a big part of how we have gone and done this.

Pablo Srugo (00:34:17) :
Here's a pointed question about the sales leader you mentioned. Out of these four things, what do you think is the most important for a sales leader. The ability to manage people, the ability to hire and recruit, the ability to implement a process, or the ability to sell themselves?

Alex Halliday (00:34:30) :
I think it's hire and recruit followed by manage. It's an energy-led sport. The team has to want to win with you at the helm as a sales leader and I think Nick does that exceptionally. He's just the best in the world I've ever seen and it's incredible to watch.

Pablo Srugo (00:34:45) :
That's been, for what it's worth, my number one kind of observation for any leader across the organization is, are they able to hire and recruit? More than anything else, do the people that are going to be in that department want to work for that person? In some cases, it means maybe they also need to know how to build, or they also need to know how to sell, or they also need to know how to market, because that builds credibility. But that's a means to an end, where the end is, are you able to attract and retain the absolute best people? And if so, you're a leader. And if not, at best you're an IC. You know, everything else is secondary to that. Just because once you're scaling, I know there's all this AI stuff and for sure that's changing things, but you still need great people. You continue to need great people and great people want to work for great people. So if you've got that flywheel going across every department, everything just gets so much easier.

Alex Halliday (00:35:30) :
I will say that selling to your audience is not like a static challenge. Your buyers are getting more sophisticated all the time. Especially if your category is just evolving and so there is a need to identify the gaps in the sales team, both from a training and skill set standpoint, and just evolve that as you grow. So I think the hiring point, being really good at hiring, but also identifying the problems you're trying to solve with each new tranche of talent. In our space, for example, a year ago, people had no idea how to evaluate a tool like ours, to be honest. And now, we get people showing up with really sophisticated RFPs and different evaluation questions. And they want to try the product, they want to do bake-offs. It is just the nature of the sale if you're successful, it will shift pretty dramatically as the market evolves.

Pablo Srugo (00:36:15) :
Here’s another question on competition because like I compared to Claude Code, but that's kind of the beginner premium kind of thing. There's also a lot of players that do something very similar to what you do like, you know, GEO and whatever. How much does that matter? It's kind of a broad question, but it's the concern of every VC right now that these areas get competitive and the fallout of that is that. Therefore, you know, no one's going to win or the market is going to be split like fifteen ways and it's just going to be small. You're actually living that competition. You're in a place that you're certainly not the only one and yet obviously you're getting a lot of traction. How does that really play out in the day to day? How much does that really matter? Or is it just one of these worries that it's just not that important.

Alex Halliday (00:36:51) :
It matters a lot and I think, to be honest, we are in more competitive processes than we were a year ago and that was part of my comment about kind of maturing our sales muscle to still thrive in that environment. I think VCs grew up in a world where there were like nice, neat Gartner squares for categories, and those squares would be relatively durable. I think AI is like a bowling ball going down the middle of all of that. Not because there aren't going to be categories. Categories are very real. I just think that most categories that are emerging now are like Pokémon that haven't found their final form yet. Because the way we work is shifting, and agents are kind of a thing, but not quite yet and the data story, and what really matters, and how ChatGPT is reading content. It's all just kind of evolving. I think what's really important as a founder is, use that competitive energy for excellence. It's like we've got to go, this is ours to win. But having a clear line of sight to what you think the category and more importantly, the buyer's life, a week in the life of the buyer is going to look like eighteen months, two years from now, and shoot for that. Otherwise you over rotate to this present day kind of feature fight. I think it's really unproductive. But to the extent that buyers of our customers have budget line items that say something on the left and a dollar figure on the right, and they allocate that. You know, you do have to fight it out. You do have to kind of be successful in the world of today in competitive processes while keeping a firm eye on what you want to bring into the world two years from now. Given how fast everything's changing and honestly, it's like the challenge of a lifetime. Building right now and being a founder as your listeners are probably experiencing too right now is unlike anything I've seen in twenty years and, you know, we will look back and think these are the good old days in many ways. Because it is the best time ever to be building a company. But it's also the most challenging as well. Because things like that that were set in stone, worked a specific way, just don't play out that way anymore, in my view.


Pablo Srugo (00:38:45) :
Perfect, so let’s stop it there. Let me ask the last few questions we always end on. When was the moment when you felt you’d found true product-market fit?

Alex Halliday (00:38:51) :
I think when I stepped away from the business for a week and we closed like $300k or $400k in ARR. And I came back, and I had nothing to do with any of those processes. I think we went from $1.1 to $2 million in ARR in a quarter. So it was really, really, really crazy.

Pablo Srugo (00:39:12) :
Incredible, what would be your top piece of advice for an early stage founder that's looking for product market fit today?

Alex Halliday (00:39:18) :
I think find the highest taste representative buyer you can and become their best friend. Live in their office if you can and just really attach yourself to their mental model of work, what they value, what good looks like to them, and observe all the non-consensus, non-obvious points of friction that you can solve. Consensus software is everywhere. Everyone can build a CRM, a task tracker, but what are the non-consensus things that you can observe that exist in the real world for your buyer that you can go solve that they will really appreciate?

Pablo Srugo (00:39:50) :
And high taste is what? Is that an early adopter or is that just someone very opinionated about the product? How do you think about defining that?

Alex Halliday (00:39:57) :
You don't want to build off a cliff by following someone that's just not very good at what they do, in my view. Again, you don't want to also build for the world's most sophisticated practitioner, but it's finding someone that has good instincts and reactions to the products you put in front of them. And is representative of the kind of customer you think you want to have a thousand, ten thousand, a hundred thousand of.

Pablo Srugo (00:40:17) :
Perfect. Well, Alex, thanks so much for jumping on the show, man. It's been great.

Alex Halliday (00:40:21) :
So great to see you, Pablo. This was a ton of fun.

Pablo Srugo (00:40:23) :
Wow, what an episode. You're probably in awe. You're in absolute shock. You're like, that helped me so much. So guess what? Now it's your turn to help someone else. Share the episode in the WhatsApp group you have with founders. Share it on that Slack channel. Send it to your founder friends and help them out. Trust me, they will love you for it.