454: Fyxer: From Executive Assistant Agency to $18M ARR AI SaaS - with Richard Hollingsworth

Summary

The SaaS Podcast: Episode 454 Summary

Title: Fyxer: From Executive Assistant Agency to $18M ARR AI SaaS - with Richard Hollingsworth
Host: Omer Khan
Guest: Richard Hollingsworth, Co-founder & CEO of Fyxer
Date: September 25, 2025

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Overview

This episode tells the remarkable story of how Richard Hollingsworth and his brother Archie transformed their executive assistant (EA) agency into Fyxer, an AI-powered email assistant that has grown to $18M ARR in just over a year. The episode provides actionable insights on leveraging customer data, achieving product-market fit, balancing growth between product and sales, and navigating the intense challenges of hypergrowth in the SaaS world.

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Key Discussion Points & Insights

1. From Rural Roots to SaaS Stardom

• Background: Richard and Archie grew up on a farm—an environment defined by slow feedback loops and factors out of their control.
  • “It was very obvious to us that farming life wasn’t right... we plotted a way of what was like the opposite environment to that and we saw tech as that opportunity.” (07:24)
• Early Business: Before Fyxer, they built and bootstrapped the UK’s largest EA agency, learning cost control and collecting deep industry insights.
  • “We bootstrapped it... [by] insisting as our terms... you had to pay us three months in advance... that was how we funded the whole business.” (09:27)

2. The Genesis and Iterations of Fyxer

• Fyxer was always intended as an AI business, but initially relied on humans due to tech limitations.
• The agency required assistants to log every task, building a unique, extensive dataset on real EA workflows.
• Multiple failed tech attempts taught them what didn’t work.
  • “We spent four years building attempts at a tech enabled service... in one invention [GPT3]... suddenly the price would fall 99%.” (11:32; 13:04)

3. The GPT-3 Breakthrough (14:43)

• GPT-3 was the turning point — suddenly, software could outperform humans on certain tasks.
• Fyxer’s first AI-driven workflow mimicked the best EAs at organizing inboxes; only launched when AI was verifiably more accurate than humans.

Quote:
“This was a workflow that people were paying our agency business $60 an hour for. And so if we're charging 30 bucks a month, we knew that this was something that people really wanted...” (13:16)

4. Building, Selling, and Finding Early Growth

• Brought in a technical cofounder, Matt, via a compelling pitch emphasizing data, workflows, and proven demand.
• The founding team of four focused solely on building product and talking to customers.
  • “Our rule as a team was to spend time doing one of two things. You were either building product or you were speaking to customers. That's all we did.” (18:17)
• Early users were recruited from their agency client base and encouraged to share their experience on LinkedIn, harnessing social proof to drive trust and virality.
  • “We would cross reference new customers with their LinkedIn following... and then if they became happy customers, ask them to post about us online.” (18:17)

5. Escaping the UK "What if Google Does This?" Mindset (23:11)

• Initial growth in the UK was hampered by skepticism and fear of big tech competition.
• Relocated to San Francisco and joined a unique accelerator (HF0), living and working intensely in a founder-focused environment.
• The US startup ethos and local ambition dramatically accelerated progress, 8x'ing revenue in four months.
  • “The narrative shift from ‘what if Google do this?’... became ‘this might not work, but if it does, it’s going to be huge.’” (23:11)

6. Product-Led Growth Crosses with Sales Expansion

Land & Expand Playbook:

• Individuals at customer organizations would self-serve and adopt Fyxer using their work emails.
• Strong internal word-of-mouth led to organic expansion inside client businesses.
  • “Usually an individual signs up... puts their work email address in... and then others at the organization also have a meeting and email problem.” (27:27)
• Archie’s sales background meant they layered in a proactive sales motion to amplify expansion. For every one marketing-acquired user, sales could often add one or two more seats.

PLG + Sales = Turbocharged Expansion:

• “We managed to take customers from one seat to five seats, to 10 seats, to 20 seats within one company... Because we had Archie... we decided to do that as early as possible.” (27:01)

7. Nailing the Ideal Customer Profile & Scalable Onboarding

• Focus moved away from tech to professional services (real estate, recruiters, consultancy)—where email pain is greatest.
• Cold email and paid ads (especially Meta and Google) brought in new leads.
• A growth engineering hire radically improved onboarding, making self-serve at volume feasible.
  • “We hired a fantastic growth engineer who completely transformed the onboarding experience for people so that we were able to do it at 10x the volume...” (29:00)

8. Facilitating Enterprise Deals – From User to 5,000 Seat Account (31:14)

• CEO of eXp Realty (US’s largest brokerage) self-served through Meta ad, loved the product, and escalated from 1 to 5,000 seats within a week.
  Memorable anecdote: Archie flew unannounced to the CEO’s hometown, securing a deal after an afternoon of in-person rapport.

  • “I think he was just so bowled over by the drive of Archie that he invited him up to his lake house and... by the end of it, they said, we can get this done in the next week.” (31:14)

• For other organizations, sales identified high-usage customers, cross-referenced with company size, picked up the phone and asked how to help. Intensity and high touch paid off.

Quote:
“You do that for long enough and you get some really fantastic opportunities. But you’ve got to put in the hard yards. Was our takeaway.” (35:11)

9. Hypergrowth Pain: Customer Success and Scaling Issues

• 5x'ing users in 3 months led to a deluge of support tickets; response time ballooned from minutes to hours.
• Solved by pulling the whole company into support, aggressive hiring, and rapid process documentation.
  • “As we 5x’ed the number of people that were using the product, we 5x’ed the number of support tickets... Our response time... went from five minutes to five hours... had to get everybody in the company to start jumping on responding to customer support tickets.” (37:35)
• Lesson: Plan for success as seriously as for failure.

10. Cultural Reinforcement Amid Rapid Hiring

• Team grew from 4 to 40 in less than a year.
• Deep focus and “unreasonable effort” are enforced: every team member answers, “What is the one thing that you will put unreasonable effort to this week to contribute towards our most important goal?” (04:13)
• Addressed worry that as the team scaled, intensity and ambition might get diluted:
  • “It’s absolutely essential... every person... experiences a kind of re-education... about what is possible to do in a week.” (39:42)

11. Impact & Human Side

• Customers shared stories of Fyxer changing their work-life balance, including saving marriages.
  • “This is a story we hear quite often... that hours changed their marriage as a result of it. It was a really sort of really reminded me of why we do this.” (41:07)

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Notable Quotes & Memorable Moments

• “You were either building product or you were speaking to customers. That's all we did.”
  — Richard Hollingsworth (18:17)

• “The mantra... we repeat... every week is: what is the one thing that you will put unreasonable effort to this week to contribute towards our most important goal?”
  — Richard (04:13)

• “The narrative shift from 'what if Google do this?'... became 'this might not work, but if it does, it’s going to be huge.' We totally fell in love with that...”
  — Richard (23:11)

• "We managed to take customers from one seat to five seats, to 10 seats, to 20 seats within one company. And learning how to do that."
  — Richard (27:01)

• “We built the AI to mimic their [human assistants’] exact workflow. Then we used the assistants to train the AI to be more accurate than them... only launch the product when we could see it was beating the assistants in terms of accuracy.”
  — Richard (13:16)

• “Support queues exploded and response times went from minutes to hours... had to scramble to keep customers’ trust, which was critical for a product built around access to their email.”
  — Omer, intro (00:00)

• On high-intensity execution:
  “We like to approach things with really intense time frames but try to do it in a kind of calm and like always with a smile on our face.”
  — Richard (44:15)

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Timestamps for Important Segments

• Richard’s background & EA agency origins: 07:24 – 10:18
• Transition to SaaS, early failed tech attempts: 10:24 – 13:04
• GPT-3 breakthrough and model training: 13:16 – 15:05
• Initial go-to-market: customer calls, leveraging LinkedIn: 18:17 – 20:32
• US move, accelerator, and mindset shift: 23:11 – 25:16
• Hypergrowth, PLG + Sales strategy: 27:01 – 29:00
• Enterprise deal story (eXp Realty): 31:14 – 34:27
• Scaling pains: customer support breakdown: 37:35 – 39:36
• Maintaining culture during scaling: 39:36 – 40:53
• Customer impact stories (saving marriages): 41:07
• Lightning Round (favorite quote, book, habits): 42:18 – 46:57

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Lessons & Takeaways

• Years of industry experience and data collection can give an enormous edge when tech finally catches up and the market is primed.
• Early SaaS growth doesn’t depend on hacks—it’s relentless customer conversation, rapid cycle learning, and laser focus on the right problem.
• Product-led growth can scale through internal championing, but “land and expand” sales is crucial for enterprise traction.
• Planning for success is just as critical as planning for failure, especially at scale.
• Company culture—intensity and focus—must be intentionally reinforced as the team grows.

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For more on Fyxer: https://fyxer.ai (with a Y)

Contact Richard: DM on LinkedIn (link in show notes)

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This episode is a playbook for founders aiming to turn deep service experience into scalable SaaS success, blending AI, operational hustle, and a relentless customer obsession.

Transcript

[A]

Foreign welcome to another episode of the SaaS podcast. I'm your host Omar Khan and this is a show where I interview proven founders and industry experts who share their stories, strategies and insights to help you build, launch and grow your SaaS business. In this episode I talked to Richard Hollingsworth, the co founder and CEO of Fixer, an email assistant that organizes the inbox and drafts replies for busy professionals. In 2016, Richard and his brother Archie started an executive assistant agency to keep the lights on. They asked customers to pay three months upfront, which helped them bootstrap. Over the years they collected a ton of data on what assistants actually did, but every time they tried to turn that into software, those attempts failed. Then GPT3 came along and suddenly the tech was good enough to outperform humans on certain tasks. They brought in a technical co founder and built their first feature which was organizing inboxes. In early 2022, they released the product to paying users and hit 200k in ARR by September. But beyond that, growth in the UK was slow. Everyone kept asking what if Google does this? To break out of that mindset, they moved to San Francisco, joined an accelerator program and after months of intense focus on building product and talking to customers for hours every day, they hit the first million in ARR. From there, growth accelerated, but it wasn't easy. The team focused on two things, building product and talking to customers. They got users to share their experiences on LinkedIn to their audiences and leaned into a land and expand sales motion that turned single users into company accounts. But hyper growth came with its own problems. In less than a year, they grew from four to 40 employees and had to figure out how to keep the fast pace and focus that had helped them grow. At the same time, support queues exploded and response times went from minutes to hours. They had to scramble to keep customers trust, which was critical for a product built around access to their email. Today Fixer is doing over 18 million in ARR with around 40 employees across London and New York serving thousands of professionals and they've raised over $40 million to date. In this episode you'll learn what specific strategies help Richard and Archie turn an EA agency into an AI SaaS company with early traction. Why? Focusing on professional services instead of tech companies gave Fixer its biggest growth opportunities. How a mix of PLG and sales led expansion helped them turn one user into a 5,000 seat enterprise deal. We talk about what mistakes nearly broke their customer success team during Hypergrowth and how they recovered and how Richard reinforces culture and intensity while hiring 40 people in less than a year. So I hope you enjoy it. I talk to a lot of founders stuck in the same spot. They've got a clear vision. They just need the right team to build or scale it. That's where Gearhart comes in. They combine AI, real engineering and product thinking to help B2B SaaS founders move fast from early idea validation to scaling real products. For over 13 years, they've helped launch more than 70 platforms, including SmartSuite, which raised $38 million and is used by companies like Capital One Bank. Through the end of September, you can book a free strategy session and get 20% off validation, discovery, prototyping or embedded engineers. For your existing team, visit Gearheart IO. That's Gearheart IO. Richard, welcome to the show.

[B]

Hey, thank you so much for having me. I'm so looking forward to this. We have had a crazy last six months and so excited to talk it through with you today.

[A]

You have a great story and I'm going to do my best to pick your brain as much as possible so people can learn from your experiences and hopefully be able to apply some lessons to their own businesses. So before we get into that, do you have a favorite quote, something that inspires or motivates you?

[B]

Yeah, that's a good question. I think the thing that stuck with me most this year has been we've experienced this hell of a ride in terms of growth this year, and it's because of how intensely we focused on being the best we can in terms of execution. And the mantra that my team live by and that we repeat to each other every week is what is the one thing that you will put unreasonable effort to this week to contribute towards our most important goal? And every single person in the company should be able to answer that question at any point during the week.

[A]

That's nice. Nice. That's a great way of getting focus. And we're going to talk about the importance of focus shortly. So tell us about Fixer. What does the product do, who's it for, and what's the main problem you're helping to solve?

[B]

Yeah, sure. So for those that don't know, Fixer is the world's largest AI email assistant. And our job is the way we look at it is saving people from their emails is the biggest productivity opportunity in AI. If you ask anyone on the street what's the thing they hate most about their work, they'll tell you it's either their manager or it's their inbox. So, like, a $10 billion company is going to be built in this space and we are currently with the market leaders. So our goal is to predict the next email that you're going to write. You can think about it a little bit like cursor, whose job it is to predict the next line of code that you're going to write. And if we can do this, if we do this, then it's just going to change the way that people work. Email is the first thing that I look at in the morning and it's the last thing I look at before I go to bed. I'd love to change that.

[A]

Cool. And give us a sense of the size of the business. Where are you in terms of revenue, customers?

[B]

Yeah, we've had a hell of a journey this year. We started the year on January 1st with a team of four people and doing about a million dollars in ARR. Today we're a team of 40 people split across New York and London, and we're doing 18 million in ARR and we're growing at about three quarters of a million a week. So the speed and rapid growth of the company has just been absolutely crazy. The thing that we're most proud of, though, actually isn't reven. It's about retention for us. In order for the business to grow at the clip that we want, it's so essential that we build a kind of lasting product. And the thing that we pride ourselves on is that 90% of our customers who pay for Fixer are still with us after three months.

[A]

Now, when I was researching for this interview and I looked at Fixer and, and this hypergrowth period you've had where you've gone from like 1 to 18 million ARR in what, eight, nine months? It's like ridiculous, Ridiculously fast. But then I looked at your background and I was like, this doesn't look like a typical founder, startup founder background. I mean, is it true that you and your brother Archie, who's one of the co founders, did you guys grow up on a farm?

[B]

Yeah, we absolutely did. I think I'm the only tech CEO I know who, who started life on a farm. And actually the life on a farm is so Archie and I used to work on the farm together in the summer holidays. And it was very obvious to us that farming life wasn't right. It's a really slow pace of life where you have to plant something at the beginning of the year and you have to wait 12 months to work out whether that was the right decision or not. And a lot of the results of farming are totally out of Your control as well. So the price, the weather are the things that determine the result, the sort of most for you and those totally out of your control. So we plotted a way of what was like the opposite environment to that and we saw tech as that opportunity. But it sounds a bit like, you know, we have had this overnight success in terms of we only launched our product 15 months ago and to be sitting here with 18 million ARR sounds like we've had an overnight success. But actually we've been working in this space now for eight years. So prior to Fixer AI, Archie and I started what became the UK's largest executive assistant agency. So I've hired hundreds of executive assistants in that business. Archie, who was our head of sales, sold millions of dollars of contracts to companies from small startups all the way up to PwC. And I think the takeaway we have from that business is we learned so much by doing it. It was a remote company, so learning all of the basics of how to run and lead a team, all of those things were huge lessons for us. But the real thing that we took away and have taken into Fixer AI is that we know more about what customers want from this product than anybody else in the world and that gives us a huge advantage.

[A]

Yeah, so you built that business too. I think you grew to around 5 million.

[B]

That's right, yeah, we bootstrapped it as well. So it's just such a different world. And as you just remember how difficult that is for anyone that's bootstrapped a company, you kind of know cash is king and just quite how difficult it is to scale the business. Our early customers were venture backed startups and Archie and I worked out that all of them had the money in the bank. So what we did is we asked or we insisted as our terms of working with us was that you had to pay us three months in advance for the service and that was how we funded the whole business. You had to be really creative and it taught me a lot about cost control and all of these sorts of things that have been really helpful in Fixer AI.

[A]

So what was the point where you guys decided that this was going to become a software business?

[B]

So on day one of the company, we saw this as an AI business. The challenge was there was a whole bunch of other people in the market at the time. There was a company called X AI who were building in the space and a Sequoia back company called Clara Labs as well. But none of them really seemed good enough in our view. And the popular opinion at the time was that you would use humans to close the gap to where AI wasn't able to answer the question. So we knew that the first step to building the AI company was going to be top tier human assistants that would be able to close those gaps for us. And on day one of the company, what we did is we asked all of the assistants to time to log and to describe all of the tasks that they did for the client so that we would have the map of what it is that people actually use assistance for and then could verifiably say these are the key workflows to work on.

[A]

So you started the executive assistant business with the software business in mind. How long did it take before you wrote that first line of code?

[B]

We had many failed attempts at leveraging technology to make the essentially the executive assistant service cheaper. So we saw this is going to be a service business and then a tech enabled service business and then a tech product. And we spent four years building attempts at a tech enabled service. And the premise was that we were working mostly with kind of executive level customers, folks that were on like 200 grand a year plus. And what we needed to do was work out how we could pull the price down so that we could service like this massive, much larger group of people that sat beneath them but, and had all of the same dynamics in terms of volume of emails and meetings and all of this thing, but none of the support. And that was our goal was, was to try to service those people. And when GPT3 came out, they, I can't even remember where we were like sitting in our office in our co working space in Shoreditch in East London and just being like, oh my God, this is the solution to our problem. We've been working and grinding on this for six years, four of which spent probably working on three serious failed attempts at trying to kind of leverage technology to pull the price down. And in one invention it felt like suddenly the price would fall 99%.

[A]

And so the, the version of fixer that we see today, you really started working that after GPT3 was available.

[B]

Exactly, yeah. So what became clear once that technology came out was that if you were very, very focused on what you asked GPT to do and you spent a lot of time training it to do that specific thing, then you could get results that across the right workflows would exceed the quality of what a human can do. So the best example of that is our first workflow that we built which is organizing your inbox into folders. So this is a very logic based workflow. And what we did is we asked the assistants in the agency business, how do you do this for your clients? And so we built the AI to mimic their exact workflow. And then what we did is we used the assistants to train the AI to to be more accurate than them. So we would pit 10 assistants against our AI and only launch the product when we could see that it was beating the assistants in terms of accuracy. That was really, really key because it meant that when we launched the product, we had total confidence in it just flying off the shelves because this was a workflow that people were paying our agency business $60 an hour for. And so if we're charging 30 bucks a month, we knew that this was something that people really wanted and we were able to do it more accurately than a human can do it. This is sort of dead set to, to to be a solid product market fit.

[A]

How did you figure out where to focus the product? I mean, you've got GPT3 and then suddenly, you know, there's so many things you could do, so many things that you could build and an EA is probably juggling multiple things for, for this executive. So how did you decide what features to focus on?

[B]

Yeah, the first problem that we had was it was just Archie and I and neither of us are technical. So our first challenge was we had been wooing, if you like, for a while, Matt, our now CTO and co founder, who was an oka partner of Archie's. And we knew he was the guy that we wanted to build this, but he was very much in demand from other people pitching to him. So our pitch to him was we have six years of this time tracking data that tells you exactly what people use assistants for. And then we have the assistant agency itself to A show you exactly how the workflow should be built and B to use the human assistants to be able to train the AI itself. Plus, we have already been selling this product for $60 an hour to people. So we are a really solid go to market bet. And that pitch really, really resonated with him. And what it reminded me is that actually for the go to market folks out there, there is such a strength in that in terms of your pitch to technical founders as well as I think people think the power dynamic often is how do we get the techn rather than they are also looking for folks to jump on those sales calls.

[A]

Yeah, so you alluded to this earlier that if we just look at what fixer AI has done over the last year or so, it doesn't give us the full picture of all the pre work that you guys did to get to that point. And now what I'm hearing is it wasn't just the experience of building that EA business, it was also the data that you had collected over that time that gave you a whole bunch of valuable insights about what the software product should do as well as all the failures that you had trying to build a software business. And sort of like the Edison thing about, I'm not quite sure about the right software, but here's all the things we've tried and failed at. We know that don't work.

[B]

Yeah, I think that's exactly it is. It gave us the ability to say no to things and it gave us the confidence that when we released things that we knew that what we were releasing would work, which saved us a huge amount of time, gave us this instant product market fit. So that, yeah, that was just incredibly valuable because it's so tempting, as we all know when we're building a product to go off and listen to a customer say they want something and go off immediately and start building it without really being that confident that it was the right thing to spend time on.

[A]

So there was four of you, the three co founders. So Matt came on and then you hired one other person and that was the team of four that got you to the first million in ARR. How long did that take to go from like zero shipping the product to getting to the first million?

[B]

Yeah, I think we launched the product in January last year for beta users and then to paid users in something like May last year. And we approached it slightly differently to how most people would. I think we were fortunate to have a kind of initial group of customers that we were able to share it with from our agency business. And then what we did is when we would, at this point we maybe would have three or four signups a day, something like that. We would spend. Our rule as a team was to spend time doing one of two things. You were either building product or you were speaking to customers. That's all we did. And every single person that signed up to the product we would speak to. And eventually we started speaking to people who initially you would just be solving kind of customer support issues like oh, I wasn't able to connect my email or I don't understand how this works. And we would then feed all of that, that back to the product team. And we created this really high velocity cycle where we would solve problems within an hour of finding them out, which was really really Valuable and just helped speed things up as much as possible. And then we would cross reference new customers with their LinkedIn following and spend lots of time with customers, and then if they became happy customers, ask them to post about us online. We knew that we were just four British guys in, you know, in London. Nobody had heard of us. And so. And people's emails are incredibly, you know, incredibly close to their hearts. You know, people do not want to give access to their emails and all these things up very easily. So trust is really, really important. So we knew that for these folks that had 20, 30,000 followers on LinkedIn, their credibility and trustworthiness would be the thing that would get new customers over the hurdle and start using the product. And so it created this great cycle where we were simultaneously learning how to improve the product by spending more time with customers and growing the customer base as a result of it.

[A]

So it sounds like the first 10 customers at least came from your existing client base, from the EA business. And then with, with LinkedIn, I think it's really smart. Rather than you posting on LinkedIn about how great Fixer is getting your customers to post about their experiences and telling their followers about that. Did you ask every single customer to do that? Or if, if you sort of picked people, how did you decide who to pick, who to ask? And then was the request simple as, can you go post something on LinkedIn or did you, did you write something for them? Or like, what, what, what was the logistics of making that work? Because it's kind of, it's a very simple thing, but it's not always that easy to pull off.

[B]

Yeah, absolutely. It's great question. So we, the way that we would approach it is we just spent loads of time with these people and we would look at what their following was and you'd need their following to be more than 10,000 people. And I suppose there was a correlation between if you've got a high number, if you've got an email problem, you're probably more likely to have a high number of LinkedIn followers. There's probably a higher density of people with lots of LinkedIn followers in that group of people than maybe for another product. So we were sort of fortunate from that perspective. And just by virtue of spending time with them and proving to them that we were able to solve the issues that they saw in the product extremely quickly, People believed in us and got confidence in us as a team and as a product, and believed that the product would get to the place that it needed to be. So when we would Ask them, is there anybody that you know that could use the product and would you be happy to share about it on LinkedIn? We would sometimes write it for them if that was a hurdle, but we always try to steer them towards authenticity as much as possible because it's always quite obvious, I think, when people kind of, you know, somebody's written it for them, particularly if ChatGPTs written it for them.

[A]

So I think that got you to about 10, 15, 15 k. Mrr. Maybe you were doing about 200. 200 k?

[B]

Yeah. By about September, I think we were at about 200k, something like that in ARR.

[A]

And then you decided to abandon the UK for a while. And I know you joined an accelerator, but it wasn't just the attraction of going to the US and working with an accelerator. It was also to maybe just step away from some of the challenges that you were experiencing in the uk.

[B]

Yeah, yeah. It's fair to say we think Europe and the UK is the right place to scale our company. But starting up, we found it quite difficult. The thing that, this is probably the thing that we got most wrong in those first few months was we just weren't thinking big enough. And everyone in the uk, it wasn't helped by the fact that everyone in the UK just kept saying to us, oh, but what if Google do this? And we found that really demotivating and kind of frustrating that people couldn't get over that hurdle. So we decided to come to San Francisco for a week to meet some of our, some of our customers and to get inspired, really. And we ended up staying for four months. We, in that four months also eight times our revenue as well. And that's what broke a million dollars. So what happened was, is we, we came out and one of our customers said, you should join this program called HF0, which is, it's an AI residency, which is not something I had heard of before, but the premise is that you live in a huge mansion in the middle of San Francisco with 10 other startups and they remove everything from your day so that you can spend all of your time working. And so food is cooked for you, cleaning is done for you, even your washing is done for you. There's a gym in the basement with a personal trainer and you can just spend your entire time either eating, sleeping, exercising or working. That's it. And that was incredibly motivating for us. And the thing that the narrative shift from what if Google do this? To became what they would say to us, this might not work, but if it Does. It's going to be huge. We totally fell in love with that because it was belief in ambition unlike anything we had seen in the uk.

[A]

Let's talk about that growth, the hypergrowth period. Right, because that's super interesting. So as we said earlier, you went from million ARR to about 17, 18 million in about eight months. Just walk me through how that happened and what you feel put you in a position to be able to have that kind of growth. Because this is not just about, oh, we found a new growth hack or something. Right. There was a bunch of things that needed to come together to make this happen. So just walk us through that.

[B]

Yeah, absolutely. So during the course of that program at HF0, as I say, we kind of grew revenue from zero to a million. And I think most people when they launch their product, think, great, now I need to start marketing it. And we took the entirely opposite approach. Just continued doing what we had been doing before by just selling the product. So getting on the phone with any customer that instead of getting on the phone with all customers, we started getting on the phone with customers who had five or more employees, 10 or more employees, 20 or more employees, and started just growing that number. And again, we were just still a team of four people. So we had the two engineers just building product and then myself and Archie just speaking to customers and we didn't do anything else. And that was the motion that got us all the way to a million. And at the end of the year, we raised a series A and came back, decided to come back to the UK and build the company from London and we started marketing the product, which is something we just hadn't done before.

[A]

So up until that point, everything had just been inbound through LinkedIn, word of mouth, that was it.

[B]

And then sales. Yeah, exactly, yeah. And what we had done is we've managed to take customers from one seat to five seats, to 10 seats, to 20 seats within one company. And learning how to do that.

[A]

Just explain that a little bit, what you mean by that. So typically what happens is like one random person in an organization comes and discovers fixer starts using it and then that is your sort of entry point into the organization.

[B]

Yeah, exactly. So usually an individual signs up and probably pays for this themselves, but they put their work email address in because that's the one that gets all the traffic. Right. So probably 95% of our revenue comes from people's work email addresses. And then usually there is other people at their organization that also have a meeting and email problem. And so what we do with the product is by virtue of them using it, they start to tell the people in their organization or people see that they're using it and start trying it themselves. And so you start to get this kind of spread through a company. And this is really important for the long term thinking. We knew that in order for us to ever, you know, for us to hit a billion dollars in revenue, you need to have a really strong sales motion. And because we had Archie in the business whose background was sales, we decided to do that as early as possible. And what that does is it meant that the marketing dollars that we eventually started spending at the beginning of this year were so much more efficient than they would otherwise have been. Because for every one person that you acquire through marketing, you might acquire one or two people through sales.

[A]

Okay, so talk me through. You said you started marketing specifically, what did you start doing to generate more leads and how were you finding those people? Because it kind of sounds like fixer could be for anybody. And that's good, but that's also bad because that makes marketing incredibly difficult. Like who you're targeting.

[B]

Yeah, it was super interesting and quite confusing question that we had to answer to. We are building the product for customer facing people at professional service companies, so not the tech industry. And so actually being in San Francisco was a bit confusing from that perspective because everyone there works in tech. Right. So it was really important for us to we in order for this company to be multibillion dollars of revenue, it needs to be targeted at the non tech industry because that is the industry for whom email is like the biggest problem. So people like real estate brokers, people like recruiters, people who work in consultancy, they suffer much more heavily from the pain of email than developers do, obviously. So that was, that was the hour goal. And so we started targeting people through cold email, through and through kind of paid advertising, through Matter and Google search and that sort of thing. The other thing that we really had to overcome was how to acquire people at scale because we just hadn't done kind of low touch or no touch self serve motion as well. And we hired a fantastic growth engineer who completely transformed the kind of onboarding experience for people so that we were able to do it at 10x the volume of what we've been used to.

[A]

Okay, great. So you're using cold email, you're running some ads and you did have an idea of who you were targeting. So you talked about the professional services and the types of people that make the most sense. And then the playbook really is like Product led growth. Right. So they get to fixer, they can sign up themselves, they can connect it to their email and hopefully they start to see the benefits of using the product. Walk me through how you then turn that into one person at some real estate company to selling 50 seats at the company.

[B]

Yeah. So I can tell you how we closed. The largest deal that we closed this year is a 5,000 seat, $1.2 million deal. And we closed it in seven days. Wow. The way that that happened was the CEO of the largest real estate brokerage in the U.S. a company called Exp Realty, where they got 80,000 staff. He signed up via a meta advert. It's one of our first adverts. It's very good. It was a very good stroke of luck, this. So the first he signed up and he called us at the end of his two week trial. Seven days, the trial now, but back then it was two weeks. And he called us at the end and said, I have 40 of my team using this because we have such a bad email problem in this industry. And I have shared this with so many of my team members. We have 40 people using it. I want to roll this out to 5,000 of my staff. And what he was explaining to us, which is so really told us we were onto something here, was that for him, more meetings equals more money. So the more viewings that his team do, it's their best lead indicator for revenue. And currently all his team do is either do house viewings or prepare for or debrief from or schedule those meetings can take the second thing away. They can do more meetings. And he currently works on 1 1/2% margins. So if they can make 20% gain, that might have 50% impact on net margin and could triple his stock price. So this is a really transformational opportunity for him in AI. And we had this fantastic call with him and at the end of it we said, so how quickly can we get this done? And he said, oh, it'll take three to six months. We're a public company. That's just how it works. And Archie and I got off the call and he lived in actually not far from where he used to live. He lived in Bellingham, Washington, on the border with Canada. And Archie was like, he's the majority shareholder of the company. I believe that he really wants to do this. What if I just fly there? And so he got the first flight out in the morning, got to Seattle, drove two and a half hours, having rented a car to Bellingham, and then text Glenn the CEO, when he arrived and said, look, I'm in town and I want to do a deal this afternoon. And I think he was just so bowled over by the kind of the drive of Archie that he invited him up to his lake house and the two of them spent the whole afternoon together. And by the end of it, they said, we can get this done in the next week.

[A]

That's a great story. Obviously, most CEOs weren't reaching out to you and saying, I want to have 5,000 people using this at my company. So in other cases where you have somebody join from a company, you know who that organization is, you know they're a good fit. How did you then start that sales conversation? Or how did Archie start that conversation? Who did you know who to reach out to? Would you go to the CEO? Was there another ICP you had in mind? But, like, how did you convert that one sign up to another sales conversation when they weren't reaching out to you?

[B]

Yeah, so what we would do is we would just pull the users and rank them by the number of draft emails. So the value of the product is in our ability to predict the next email that you're going to write. So what we would do is we would rank our users by the volume of emails they send and the percentage of our drafts that are in that group, and then cross reference that with the amount of employees they would have at the company, and then just pick up the phone or send them an email and ask, is there anything more we can do to help improve the experience of the product for you? And our calendars, I'd love to show you. We just looked just insane in these days because when there were four people and we were living in this. In this crazy environment in San Francisco, we did slightly lose, like, perspective on a normal working day. We were probably working 16 hours a day, seven days a week. And the reality was that for me, most of my day was just sitting in front talking to customers. And you do that for long enough and you get some really fantastic opportunities. But it's, you know, you've got to put in the hard yards. Was our takeaway.

[A]

Yeah. So the scaling, I mean, that playbook. Brilliant, right? So you, you've, you've done, you put in all the hours or the years into getting to this point. You have really focused on two things. Building the product, talking to customers, and just feeding that, those conversations into continuing to build a better product. And then now you're at a point where one person can sign up. It's basically a plg type model, getting them to be successful, and then you switch to sales, and then it's from that one person to maybe five, ten hundred thousand, whatever. And then it just sounds like it was just sort of rinse and repeat and keep doing that and doing that as well as you can. But scaling that quickly, I'm sure, also comes with a bunch of challenges, whether it's hiring or. I think even with support. Support very quickly became a struggle for you. Right. For something that you'd been very proud of, very quick to address, suddenly became an issue because you hadn't expected this type of success to happen so quickly.

[B]

Yeah. So this was at the beginning of this year, and we grew from 1 to 5 million within three months. And I absolutely kicked my. We found ourselves again not thinking big enough. And what we hadn't done is we had spent a lot of time thinking about, well, what if this marketing and growth engineering strategy doesn't pay off? And what we hadn't thought of is what happens if this works? And so as we kind of 5x the number of people that were using the product, we 5x the number of support tickets that we got. And our CS team was just two people at this point. And basically our response time on support tickets went from five minutes to five hours. And customers became very unhappy very, very quickly, as you can imagine. You know, the expectation is an immediate response not five hours later. And we had to get everybody in the company to start jumping on responding to customer support tickets, had to aggressively hire support people to help solve the gaps, get them onboarded and trained, and write documentation for the first time. And all of this work that really should have been done in January was being crammed into about 10 days in March. That was such a massive pain point. And it reminded me, like, you have to plan for what happens if this works as well as what happens if it doesn't.

[A]

Yeah. Yeah. I think in many ways we're so stuck into that mindset of things not working and what you're going to do next that. I mean, it's a quite nice problem to have to think about what if this succeeds? Right.

[B]

It's a nice problem to have, for sure, but it doesn't feel like it at the time. You're absolutely kicking yourself because you think it's the only chance and you worry that you've missed it. So it was. You're right, it now looks like a nice problem to have, but it didn't feel like it at the time.

[A]

And tell me about hiring as well. You've gone from four to 40 people now in a very short space of time.

[B]

Yeah, that's the thing that we sort of worry about, think about the most we see it as our biggest challenge is when you're four people living in this sort of perfect work environment, really in San Francisco, you're able to the. The sort of potency of our focus and of our work ethic and of our intensity was just absolutely crazy. And as soon as you start hiring people, you worry about that being diluted, particularly with folks having a kind of UK mindset when it comes to work ethic and when it comes to belief that it's possible to build these companies. And so it's absolutely essential to us that every person that joins Fixer experiences a kind of re education, if you like, about what is possible to do in a week. And that's why we asked them that question of what are you going to put unreasonable effort to this week to.

[A]

Move our most important goal and are you hiring? Are you building most of the team in the uk?

[B]

So our engineering team is here, our go to market team is in New York. We're probably 75% London today. By the end of next year we'll probably be 50. 50.

[A]

Awesome. Okay, we're gonna have to wrap up before we get into the lightning round. One other question for you. I came across something when I was researching. Is it true somebody said fixer saved their marriage?

[B]

Yeah, yeah, that was a customer call I had maybe six weeks ago now where it was with a real estate broker. And he said that we had saved him from getting divorced. He said, and this is a story we hear quite often, that folks will go home from a long day's work, maybe out on the road all day, come home, put their kids to bed. And then the hour that they spend with their partner before they go to bed is spent writing follow up emails and Fixer drafts all of them for them now so they can spend 10 minutes doing that rather than an hour. And that hours changed their marriage as a result of it. It was a really sort of really reminded me of why we do this. I've been doing this job for my whole career now. I've been supporting people in this way and it's a like really firm reminder about why this is so important for people.

[A]

Yeah, let's love it. All right, let's get into the lightning round. So I've got seven quick fire questions for you. What's one of the best pieces of business advice you've received?

[B]

Our first investor, who when we were deciding to Do Fixer AI supported our decision to and said the key thing is to always invest where you have an unfair advantage. And we were trying to work out oh well, what if Google do this? We were being very British about it. He said you have an unfair advantage here. You should invest your time.

[A]

What book would you recommend to our audience and why?

[B]

The CEO of Snowflake or the ex CEO of Snowflake, a guy called Frank Slootman wrote a book called Amp it up and it's all about how intensity at work is a about the number of hours you work, but B it's all about what you get out of every single hour and how always you would need to shorten the time period. So if someone tells you they can do it in a week, ask them how many days they can do it in. Somebody tells you you can do it in a day, how many hours can you do it in?

[A]

What's one attribute or characteristic in your mind of a successful founder?

[B]

The thing that people tell me about myself is that I'm very calm in a storm. When there's an emergency I just know what to do. And this really highlighted me when we raised our series B this so far this year we've added $2 million in valuation every day. So us stepping out of the business is very expensive. We decided to run the process for raising the B in nine days and I was running probably 10 meetings every sing day and you'll see we actually released a vlog on LinkedIn today of our experience doing that and you might think that'd be really stressful. We always had a smile on our.

[A]

Face that doesn't jive with the like I see you and you seem just so chilled and laid back and then you sort of describe this sort of daze and I sort of imagine a sort of a type a go go go type guy. But you seem to deal with that well.

[B]

Yeah, I think that's like the juxtaposition I really like. We like to approach things with really intense time frames but try to do it in a kind of calm and like always with a smile on our face.

[A]

What's your favorite personal productivity tool or habit?

[B]

So I'm super protective of my mornings. There are three things I like to have done before midday. One is I need this. But I have an 18 month old son and I like to spend at least 15 minutes with him every morning, usually at some horrible hour early in the morning. The next thing is I like to have three hours of focus time usually between six and nine where I can just Work totally undisturbed. And lastly, I like to go to the gym.

[A]

Cool. What's a new or crazy business idea you'd love to pursue if you had the time?

[B]

People often say you should build kind of businesses out of like the things that you build in house for your own needs, as it were. A bit like Amazon did with Amazon Web Services. We have built in house a like incredibly sophisticated human training sort of data annotation unit. In our business. We have over 100 data annotators that build custom models for our product, which is what makes it so accurate. This is something that lots of companies are starting to do as a kind of service for AI products, like people like scale AI. And I think I'd just be fantastic at building that company. So in another life, like I would do that. And I just really enjoy the kind of paradox of it being a human orientated business, but it being on the front lines of AI, that's a cool one.

[A]

What's an interesting or fun fact about you that most people don't know?

[B]

Well, as I said earlier, I'm definitely the only tech founder I know that grew up on a farm. For any Star wars fans, I'm also related to the original Obi Wan Kenobi. How are you related? He is my great uncle.

[A]

And finally, what's one of your most important passions outside of your work?

[B]

Sadly, the combination of running a startup and having a young baby means that like hobbies and things outside of work really, really just revolve only around him. Hobbies and friends and stuff have sadly fallen away somewhat. But pre Fixer AI and Pre Baby, I used to spend a lot of time traveling the world driving motorbikes. So I've been to Europe, been to India, been to Nepal. I've driven on the highest road in the world. That's where like I used to sort of spend my holidays, my trips.

[A]

Nice. Love it. Well, Richard, thank you so much for joining me. It's been a pleasure. Just sort of trying to sort of unpack the last couple of years. Congratulations on everything that you and the team have accomplished so far. If people want to check out Fixer, they can go to Fixer AI. That's Fixer with a Y, F, Y, X, E, R, A, I. And if folks want to get in touch with you, what's the best way for them to do that?

[B]

Just reach me out on LinkedIn and be the best. Hit me up with a DM on LinkedIn.

[A]

All right, we'll put a link to your LinkedIn profile in the show. Notes great. Well, thank you so much for joining me. It's been a pleasure and I wish you and the team the best of success.

[B]

Thank you so much.

[A]

My pleasure. Cheers. If you're building an AI agent, a SaaS product, or trying to scale, check out Gearhart. They're a product development studio building scalable SaaS platforms, AI tools and custom software for startups and growth stage companies. As founders themselves, with real exits behind them, they know exactly what you need at every stage of the founder's journey. With tailored services, enterprise grade engineers, and an AI partner with 15 years of experience on projects for Meta and Google, this is nothing like a classic dev shop. Through the end of September, you can book a free strategy session and get 20% off validation, discovery, prototyping or embedded engineers for your existing team, visit Gearheart IO. That's Gearheart IO.