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AI Native Transformation: Mono AI.

March 31, 2026 · Hosted by Dexter Cousins

David Hyman’s Next Chapter After Building a $107B Platform

David Hyman spent 13 years building Lendi Group into Australia’s largest non-bank mortgage platform. $107 billion loan book. Five million customers. 220 retail stores. $350 million in annual revenue. He stepped down as CEO in January 2026. Instead of relaxing on a beach he was building again within days.

His new venture is Mono AI, a platform business that exists to help mid-market enterprise go through AI native transformation – before an AI native competitor makes them irrelevant. In his fourth appearance on Fintech Chatter, David sat down with Dexter Cousins to explain what he learned leading Lendi Group’s AI transformation why he started Mono AI, and what business leaders are getting wrong about AI right now.

From Mortgage Platform to AI Platform: Building AI Native.

The Lendi story has three distinct chapters. The first was building the original digital mortgage platform from scratch, competing against banks and brokers at a time when you simply could not get a home loan online. The second was the acquisition of Aussie Home Loans from CBA and migrating everything onto a single technology stack. The third, and most recent, was what David calls the find, buy and own era: 140,000 property listings, 11 million property records, and a full end-to-end experience layered across the broker and retail network.

The moment David points to as the culmination of his time at Lendi was the company-wide conference in March 2025, where the Lendi team brought the AI native future to life for brokers, partners, and the wider real estate industry at a time when most businesses were still asking whether AI was relevant to them.

“We were early,” he says. “We had a healthy level of resting anxiety every day because we were watching the AI models race ahead and challenging ourselves to keep going and keep going faster.”

That experience, combined with time spent visiting businesses in the US, Europe, and Asia, gave David a clear view of the gap between businesses starting from a blank sheet and those trying to transform legacy operations. “The vast majority of businesses don’t have the luxury of starting fresh,” he says. “And in 12, 24, and 36 months’ time, they’re going to be competing with AI native businesses that are growing very, very quickly.”

What AI Native Transformation Actually Means

The term gets used loosely. David is specific about what it means in practice.

He draws a distinction between two modes of operation. Human motion is how most organisations work today: everything moves forward because a person takes action or asserts judgment. Agentic motion is where AI agents run in loops, 24 hours a day, handling what he calls the busy work, while humans remain on the loop for certain checkpoints and in the loop for specific high-judgment decisions.

At Lendi, this took shape in a product called Guardian, which David describes as a combination of humans on the loop and humans in the loop. The AI and the customer move through a process without interruption until guardrails are hit, at which point a human gets involved. Certain moments like product recommendations or identity verification are always human-in-the-loop by design.

What this is not, David is clear, is a technology problem. “AI has moved from being a technology problem to being a human change and business model problem,” he says. The execution gap is not about tools. It is about whether leaders can help their teams lift their gaze, understand where the business is going, and move through the change without requiring certainty about every step.

The Revenue Per Employee Benchmark Every Leader Should Know

David uses a single metric to frame the scale of what is coming: revenue per employee.

Traditional businesses run at $200,000 to $300,000 revenue per employee. The best enterprise SaaS businesses reach $500,000 to $700,000. Then there is the new cohort of AI native companies. ElevenLabs generates approximately $400 million in revenue with roughly 200 employees, including only 18 people in its go-to-market function. That is $2 million revenue per employee.

“That revenue is not from their revenue-producing employees,” David says. “That is across everyone.” And that is the operating leverage your business will be competing against within the next two to three years.

David is direct about what this means: businesses that do not go through AI native transformation will face a structurally lower-cost, faster-moving competitor that almost certainly has a better product. “What really gets me out of bed every day is helping businesses compete head on with those AI native businesses.”

The Mono AI Platform: Three Components, One Goal

Mono AI is not a consultancy. David is emphatic about this. The business has three components.

The platform is a multi-agent orchestration system that is cloud agnostic and model agnostic. It connects to all major AI models either directly or via inference platforms like AWS Bedrock, Google Vertex, or Azure. It includes a memory system that compounds knowledge over time, fine-grained access controls at user, team, and organisation level, and out-of-the-box connectors to internal systems. The goal is to avoid relying on large data migration projects and instead reason directly over source data.

The wedge system is a library of playbooks for specific business domains, verticals, and industries. These playbooks map out the pathway to AI native and define where to start based on the business’s actual objectives.

The forward deployed pods are senior Mono AI employees who co-build with the client and embed inside the organisation for the duration of the engagement.

The target market is mid-market companies with revenue between $200 million and $2 billion. David’s reference point is Palantir, which serves the top end of government and enterprise. Mono AI is targeting the mass mid-market where the P&L pressure to act on AI is real but the resources and methodology to do so are not.

The Wedge Model: Six Weeks to Proof of Value

The enterprise sales cycle is one of the most well-documented traps in B2B technology: twelve months of stakeholder alignment, a key sponsor who leaves, and you start again.

Mono AI has structured its go-to-market specifically to avoid this. The wedge is a high impact, low risk use case that can be co-built with the client in two to six weeks on a fixed fee. Before the wedge, Mono AI helps the business map its current technology stack, define what an AI native version of its business could look like, and identify the best starting point, either a vertical (a division, region, or department) or a horizontal (executive intelligence, sales funnel acceleration, meeting intelligence).

“Let’s not spend six months deciding what we’re going to do,” David says. “Let’s get started in six weeks, have something we can all look at and say: these things worked, these things didn’t, this was our view on AI native. These things still hold. Some things have shifted.”

Because Mono AI is positioning at the CEO and board level rather than at the technology buyer level, the sales motion is fundamentally different from standard enterprise SaaS. “We’re not trying to displace an existing spend. We’re trying to work with businesses on their broader business model. The whole P&L is in question.”

The CTO Problem Nobody Talks About

One of the more striking observations David shares is that the biggest blocker to AI strategy in most organisations is not the CEO. It is the CTO.

“When I speak to CEOs, the biggest blocker in most organisations to executing on their AI strategy is the CTO,” he says. “They’re great. I’ve worked with amazing technologists. But those closest to the technology are not necessarily lifting their gaze and thinking about how this plays outside of just providing services within a particular part of the business.”

This is not a criticism of individuals. It reflects a structural misalignment: AI native transformation is a business model problem, and most technology leaders are still framing it as a technology delivery problem.

Two Traits That Define Who Thrives in the AI Era

David is consistent on this point across the conversation. Two characteristics determine whether a person moves through the AI transition successfully.

The first is curiosity. Not a growth mindset as an abstract concept, but active willingness to break apart existing processes from first principles and ask whether they still make sense. The second is high agency. Not coming to the table with reasons why something cannot be done. Identifying what needs to be solved and moving toward it.

“We’re seeing some people have the absolute time of their career in this change,” David says. Those are the people who combine both traits.

Why Mono AI Is Building From Sydney

David has spent significant time in the US, Europe, and Asia over the past two years. His conclusion about Australian talent runs counter to the conventional narrative that you need to be in Silicon Valley to build a global technology company.

“Australia really punches above its weight in terms of the quality of entrepreneurs, technologists, and product people compared to any other market around the world,” he says. “The more you spend time in Europe or the US, you realise that the calibre of people here is just top world class.”

Mono AI’s plan is to launch additional markets over the next few quarters, establishing hubs in West Coast US, East Coast US, and EMEA, all supported by a Sydney base.

What Roles Mono AI Is Hiring For

Mono AI is hiring. Not at scale, and not across every function.

The company is looking for people on the product and platform side as it continues to build out the core offering. On the go-to-market and delivery side, it is specifically interested in people from enterprise SaaS backgrounds and Big Four consulting who identify as being on the entrepreneurial end of those environments.

“If you’re in Big Four consulting and you feel like you’re more on the entrepreneurial side, whether it’s on the go-to-market or delivery side, we’d love to chat,” David says. Connect with him directly on LinkedIn. DMs are open.

Frequently Asked Questions

What is Mono AI?

Mono AI is a platform business founded by David Hyman that helps established companies go through AI native transformation. It combines a multi-agent orchestration platform, a library of business-domain playbooks (the wedge system), and forward deployed teams who co-build with clients. The company targets mid-market businesses with revenue between $200 million and $2 billion.

What is the wedge model?

The wedge model is Mono AI’s approach to getting enterprises started quickly rather than spending months on planning. A wedge is a high impact, low risk use case that Mono AI co-builds with a client in two to six weeks on a fixed fee. It is designed to generate tangible proof of value fast, after which the broader AI native plan is refined.

What is AI native transformation?

AI native transformation is the process of reimagining how a business operates in an era where AI agents can handle the majority of process-driven work. It moves businesses from human motion (everything requires a person to take action) to agentic motion (AI agents run continuously on routine tasks while humans focus on judgment-intensive work).

What was Guardian at Lendi Group?

Guardian was Lendi’s AI product, developed as part of Project Aurora. It combined humans on the loop (AI and customers move through workflows autonomously unless guardrails are triggered) with humans in the loop (specific high-trust moments like product recommendations or identity verification that always involve a human). It was a practical demonstration of AI native transformation in a regulated financial services environment.

Why is the revenue per employee metric important for AI strategy?

Revenue per employee is the metric that shows the structural operating leverage AI native businesses are building. Traditional businesses run at $200,000 to $300,000 per employee. AI native businesses like ElevenLabs are running at approximately $2 million per employee. Within 12 to 36 months, most established businesses will be competing against companies operating at that level of leverage.

What roles is Mono AI hiring for?

Mono AI is actively hiring on the product and platform side, and on the go-to-market and delivery side. The company is specifically interested in people from enterprise SaaS and Big Four consulting backgrounds who sit at the entrepreneurial end of those environments. Connect with David Hyman on LinkedIn to start a conversation.

Links from this episode.

David Hyman on Fintech Chatter.

More on AI native businesses.

Full transcript.

Lightly edited for readability — filler words removed, wording otherwise unchanged.

Dexter Cousins
Hello and welcome to Fintech Chatter, the podcast where I chat with fintech leaders about their secrets to success. I’m Dexter Cousins, your host and the founder of Tier One People, an executive search firm that for the past decade has been helping founders like today’s guest hire that 1% of exceptional talent who help you redefine what’s possible.

In today’s show, I’m joined by David Hyman. It’s his fourth time back on the show, and many regular listeners will know him as the CEO of Lendi Group. David co-founded Lendi in 2013 with Sebastian Watkins. Together they built it into Australia’s largest non-bank mortgage platform with $107 billion loan book, 1,350 brokers, 220 retail stores, and over $350 million annual revenue. David led the acquisition of Aussie Home Loans from CBA and was winner of the EY Entrepreneur of the Year award. He also drove Australia’s most ambitious AI transformation in financial services.

In January of this year, David stepped down from the CEO role and he joined me recently to talk about his latest venture, building a global AI business from here in Sydney. We recorded this show just before the major job losses at Block and Atlassian, and it’s possibly one of the most important shows that we’ve ever released. But before we get into it, if you are new to the show, make sure you follow us if you’re listening on podcast. And if you’re watching us on YouTube, please give us a like and subscribe. It really helps us get the message out there. David, welcome back to Fintech Chatter.

David Hyman
Thanks for having me, Dex. I kind of forgot that it been four times, but we must like each other.

Dexter Cousins
Yeah, what can I say? You must be my favourite guest. Well, I guess we’re here to talk about your new venture, but it would be remiss of me not to at least touch on the legacy that you’re leaving behind with Lendi. As you look back, what’s the kind of moment that you’re most proud of?

David Hyman
That’s a really big question. Look, there’s been so many moments over those 13 years that have been super, super memorable. Maybe just to lay out some of the chapters in that story, we had the first chapter was the Lendi chapter. So, couldn’t get a home loan online. You had to meet with a bank or a broker. So, we built out the first digital home loan platform. And that was, I’m going to say that was like scrappy startup, like high growth. We were hiring very quickly, scaling our brand, scaling marketing, sponsoring sports teams, doing all the things that you need to do as building.

Dexter Cousins
I remember the bus ads.

David Hyman
Lots of ads, testing lots and lots of different creative formats. Trying to find a way to beat Google and, over time, Meta. Anyway, that was the first chapter.

Second chapter was, as you just outlined, we were fortunate enough to be in a position to acquire the Aussie Home Loans business from CBA and we merged Aussie and Lendi together. That was a very different chapter, incredibly rewarding, but for different reasons. We’re able to kind of migrate all the customers and the brokers to one technology stack. And as you outlined, we’ve now got over 200 stores, over 5 million customers. We’ll do close to $40 billion worth of home loans this year, which is a really, really exciting milestone for the business. And there was lots and lots of milestones in that journey.

And then the final chapter was find, buy, own, or the most recent chapter is find, buy, own, where we’ve taken this group that has such big coverage in the market, presence in the market, both from a brand perspective, a tech perspective, brokers and stores. And we’ve been able to shift left and right of the mortgage and really give customers a full end-to-end find, buy and own experience. So there’s now buyers agents, there’s 140,000 listings on the platform. There’s 11 million properties.

But along that journey, probably the moment that stands out to me the most, because it kind of brings a lot of these things together, would have been the conference we had in March of last year. So just almost a year ago now. And this was really the culmination. We do a big company-wide conference every couple of years. And this was really the culmination of a whole bunch of things, but we really brought find, buy, own to life in the context of the AI era.

So if you sort of take yourself back to the start of 2025 and people had shifted from is AI just a fad to there’s this AI thing and I’ve got to kind of work out how to use it and how it’s going to impact what I do and how I serve my customers. And we were able to kind of bring together all of those different elements into a really sort of high quality production where we sort of brought that future experience to life, not just for our brokers but for our team members, for our partners, and was just, our property platform was just about to go live. So we had a large amount of the real estate industry there and it was really the, almost the pinnacle of telling that story. The business has now been executing on that off the back of that. But yeah, that really stands out as one of those moments to remember.

Dexter Cousins
Awesome. Now, you’ve passed the baton on to Sebastian Watkins. So, I think last time you’re on the show, we did a whole origin story of Lendi in there. So, anybody, you can check a link in the show notes. I’ll put a link to that podcast because it’s a fantastic episode. But I guess you’ve now passed that mantle on to Bass. So, what’s next for you? Most founders would be chilling in the Caribbean right now or something, but not you, which is probably the reason why this is your fourth time on the show, right?

David Hyman
Yeah. Well, look, it’s funny because we announced the handing of the baton to Sebastian just before Christmas last year. Internally it happened a lot earlier. I was very, very deep internally around building out our AI product. So early last year me and my chief product officer Trav delegated most of our role and we went deep with the team building out our AI native platform and Bass took over operational CEO at that point.

But it’s kind of funny getting to Christmas when we made the announcement. I had lots of people reaching out and saying what beach can I find you on? And there was definitely a beach they could find me on for about two weeks over the Christmas period, but from the 12th of January, we’ve been busy building. And we’re building and actually second day I’ve actually worn this t-shirt. So, reasonably fresh, but we’re building a business called Mono AI and Mono AI exists to help companies transform and become AI native. We’re a platform business and really inspired by what we saw at Lendi, not just in our business, but in the broader market.

So, we went on this AI native transformation journey that had many different aspects to it. We built different products for our customers, for our brokers, for our team members. And in hindsight, I think we were early. We probably had this, and I describe it as a healthy level of resting anxiety every day because we’re watching the AI models race ahead. And we’re challenging ourselves to kind of keep going and keep going faster.

But sort of zooming out from that, I was fortunate enough to spend time in a number of different other markets. So we spent time in the US, spent time in Europe, spent time in Asia and speaking to other businesses there. Both businesses trying to work out how do they embed AI in their business, as well as some businesses at the forefront of AI, to some of the leading product businesses in the AI space, many names that you’d know, and realise that there’s a lot of new businesses building on top of AI as AI native businesses. And those are the businesses you’re seeing in the headlines, and they’re flying. They’re doing many millions of dollars revenue per employee. They’re some of the fastest growing companies ever in history of company building.

But they started with no legacy. They started with a blank sheet of paper in this new technology, yet the vast majority of businesses don’t have that luxury, and in 12 and 24 and 36 months’ time they’re going to be competing with these new AI native businesses that are growing very, very quickly. And became really obvious to me that there was an opportunity to help existing businesses go on this transition, not as a consultant but really from a platform perspective. And so that’s what we’re doing. We’re getting very, very close to public launch and really, really excited to be working with thousands of businesses as they go on this transition.

Dexter Cousins
If I look at the challenges that I’ve seen many other fintech and tech businesses, particularly when it comes to legacy, is the ideas are great, but the execution of it, it kind of falls into lots of problems. How have you kind of identified how to overcome that problem of the execution piece?

David Hyman
What’s been really interesting in the Lendi journey is we’ve been able to do it in a somewhat organic fashion, where we started originally top down. We then moved to bottom up and we were sort of executing both of those strategies in parallel. And what that’s allowed us to do over sort of a three-year window is really start to get a feeling for a few things. One is the types of opportunities that are worth going after. Number one. The second is, and this is probably the most important part, what is the human change aspect that needs to happen to bring some of this stuff to life. And what I mean by that is not just how do you get people to use AI tools every day, but how do you get people to lift their gaze and think about the art of the possible.

So there’s a lot of media attention probably 12 or 18 months ago around AI equals job losses. Yes, in its most simplistic form, you could look at a job that is done today with a person and a job that is done with AI and therefore that job doesn’t exist. But actually the exciting bit is we’ve got this amazing technology which is literally by definition intelligence on tap, and how do we point that at things that we couldn’t do before? How do we point that at things that maybe were uneconomical or not even possible technically and create new possibilities? And whether that’s new ways to go to market, new products, new experiences, new ways to delight customers. And where I’m a self-described AI maximalist. I think that humans have a great knack of filling the space, kind of gas expanding to fill the void. And I think that the opportunity for us as business leaders and as a society is to think about AI in that context.

Now to go back to your question, AI’s moved from being a technology problem to being a human change and business model problem. And that, therein lies the answer to your question, which is if you lift your gaze and think about how can I apply AI to my business and what does an AI native version of my business look like, and then how do I take my people on the journey to know that yes, look, we don’t have all the answers. Yes, there’s going to be a lot of volatility. There’s going to be a lot of change, but we don’t have all the answers and we’re going to help you on the way and here are the principles around how we’re going to do that. That’s the model that we’re seeing and we certainly saw at Lendi help with that execution between the idea and actually getting something that works.

Dexter Cousins
So, interesting you mention that because I think back to my very first year in recruitment, which was actually in the last century, showing how old I am.

David Hyman
It’s not that long ago.

Dexter Cousins
Yeah. But very similar problem was the introduction of computers into the workplace, where all of a sudden everybody had a computer on their desk and the way in which they worked had to change. And you witnessed a lot of people who kind of felt displaced because they didn’t have know-how to use Microsoft Word or Excel or how to use the internet and they were then missing out on roles and opportunities. The big difference back then was this was like a five-year roll out.

The changes in just what I’ve seen personally in the last 12 months and the changes in just a one-person business of what this technology can do, it’s frightening, right? The pace at which it’s going. How do we kind of help humans keep up pace with this and also, think more importantly, lead us?

David Hyman
Yeah, I think there’s a how fast is this happening, but beyond that also, what is it doing to the way we work and organise ourselves? So I think as you articulated, when computers came into the workplace it happened over a longer period of time. But it was also a new tool to use. Work didn’t fundamentally change. Instead of picking up the phone or sending a fax you sent an email. Instead of writing a document you typed a document.

What we’re seeing now is instead of five years it happened in one or two and it happened a lot quicker. But fundamentally the mode of work is changing. And so yes, there are still the vast majority of people using ChatGPT to write better emails or help them with their board papers or whatever that is. But actually the real game is not that. It’s changing and shifting from what we call human motion, where everything moves forward based on a person taking action or asserting judgment, into what we call agentic motion.

And so agentic motion is where you’ve got agentic loops where AI agents are working 24/7 and they’re typically working on the busy work. There’s a level of judgment in there now because we have the reasoning models, and those reasoning models, in particular the current generation, are amazing. They continue to blow my mind every day. But they’re not there for everything. They’re there for certain components.

And so how we use that at Lendi we have, and if I just even refer back to Guardian, which is the AI product we brought out last year that Project Aurora built, it’s a combination of humans on the loop, like an agentic loop, and humans in the loop. And so we have humans on the loop at certain points. So the AI and the customer is working through things from point A to point B without any interruption. And humans only get involved if the guardrails are hit or if the AI, customers get stuck or whatever that is. And then there’s very, very intentional points where humans are in the loop. So this is where we’re building trust, we’re building rapport, we’re exercising judgment that might be around a product recommendation or VOI or whatever that might be.

And the reason why I sort of got into those details is because it’s both happening a lot faster, but also the way we work is fundamentally changing. And so to answer your question, it really requires leaders to take, and it’s funny to say it like this, but to take a leadership position. Lots of leaders are leaders by title, not by action. And it really requires people to think about what is my role as a leader. How can I help? I don’t need to have all the answers, but how can I help my people understand where we’re going, what we are doing as a organisation or as a team or whatever the context is to get there, and how we’re going to support along the way.

And how it’s required a lot of leaders to get back in the trenches, I’m hearing, so some of the best leaders. I was actually just with the CEO of a very, very large business, hundreds of millions of dollars of revenue, and he’s sitting there with his head of IT on his laptop on the tools, sitting there working through exactly how a particular workflow works for one of their team members. And what I’m seeing in that context is leadership, because he’s working through exactly trying to understand the exact problem and work it through. When big change like this happen it requires leaders to think like that.

On the flip side, for team members or if you’re in a business where you’re being led by someone, my number one, you don’t need to have all the answers either. It’s moving very, very quickly, but there’s really two key characteristics I’m seeing that are helping people kind of go from A to B or move past this and move through this change. And it’s number one, curiosity. So don’t be close-minded, have a growth mindset. Think about how you might be able to do something you’re doing today differently and break that apart into, maybe there was a process that was built 10 years ago around people and spreadsheets and all that sort of stuff. And starting from why does it exist in the first place and first principles is often a great place to start.

And then there’s high agency. So don’t come up with problems or why this won’t work or why we’re in a regulated industry, so we can’t handle hallucinations. These are all things that need to be solved, but they’re not reasons to not move forward. And so if you have that high curiosity and high agency, try and work through problems and think about things with first principles, we’re seeing some people have the absolute time of their career in this change.

Dexter Cousins
So we’ve seen a, I guess, not dissimilar kind of movement in the last 10 years, particular if you look at the big four banks, where famously they were doing agile rather than being agile. And I kind of make that distinction of, it’s only two letters, but it makes a massive difference between trying to do something and actually being that thing, which I think it’s kind of the essence of what you’re saying your Mono is really there to do, is to help businesses on this transition from we’re not going to do AI, or do AI native, we’re going to be AI native.

David Hyman
Correct.

Dexter Cousins
And what does that mean? How have you then seen, you’ve kind of touched on this a little bit, but the actual kind of embracement of the, I guess, philosophy and methodology that you’re bringing to enterprises where, as you mentioned, you’ve got all this stuff about hey, well we’re regulated, we’ve got legacy debt technology, all of these things? Is there a real appetite there or is it still very much hey, this AI thing, let’s wait until the 10th client’s on board and then we’ll do it?

David Hyman
Look, maybe there’s a bit of a selection bias in this a little bit, given where we’re kicking off and we’re dealing with the first few cohorts of customers. But I’d say I’ve seen a real shift in people’s perspectives in terms of A, where are we on the AI curve, and B, what do businesses need to be doing around it? So seeing a lot of demand and seeing a lot of appetite for businesses to completely reimagine how they’re operating. Because I think the shift from the technology to the business model framing has started to permeate through business leaders, and business leaders are understanding that if you’re in knowledge work and you charge by the hour, you’ve actually got to get ahead of that curve because the business model is likely to change in some way, shape or form. And if you’re embracing the technology, you’re more likely to be the one writing what that new model looks like as opposed to having it happen to you.

And in other industries, I think we’re now at a point where the technology has moved past the point where there’s question over the quality, capacity, speed, cost, etc. Such that getting operational efficiencies in, say, a logistics business are really interesting. And you talked before about some of the concerns people might raise, like in a regulated industry or otherwise. Again, what’s really interesting with AI in particular, AI applied really well, is things that were actually hard to create controls and governance around before are now easier to create controls and governance around, because you don’t need to be so deterministic.

I mean, the amount of, and I won’t name names, but the amount of banks that I’ve seen run their controls systems on spreadsheets that require spot checks on a sample, etc., etc., etc. Well, now you can have a system that is observing the system and flagging issues or taking action on those issues and getting 100% coverage. So, I would argue and posit that a well-designed and thought through AI system actually is a much higher bar than the old way. It just requires slightly different type of thinking.

Dexter Cousins
Yeah. I’m really interested as well to understand what the business model is that you’re building, because we’ve talked a bit and it sounds more like it’s a management consultancy, but it’s not. Do you want to talk about the solution that you’re building and the platform that you’re building as well?

David Hyman
Yeah, of course. So our proposition is really simple. So firstly, our mission is to help businesses become AI native and really do things for businesses and people to do things that weren’t possible before. And the way we do that is through a three-pronged approach. So we have a platform, genuinely best in breed multi-agent orchestration platform, which I’ll come back to in a second. We have what we call our wedge system, which is a series of playbooks that are business domain or business vertical or industry vertical specific, which again I’ll come back to in a second, which help lay out the pathway for businesses to become AI native, so to speak.

And then the final aspect is our forward deployed pods. So our forward deployed pods go and work with the businesses we’re working with. They co-build. They’re embedded in those businesses. They’re high level employees, as in they’re senior employees. They’re very well versed in not just the platform but how AI native is applied within an organisation.

So coming back to the platform, we’ve taken a view that we don’t want to be trying to disrupt major parts of people’s technology stack. So we’re cloud agnostic, we’re model agnostic. So we can go and we can get deployed into any of the major clouds or data centres. We connect to all the major models either directly or via inference platforms like Bedrock or Vertex or Azure as well. We have multi-agent framework. We have really good memory system, which means that as the platform gets used more and more the knowledge compounds, and so intelligence rises to the top that can be dealt with at a user level, a team level or an organisation level.

So there’s really good fine access controls around everything that really means that as businesses use more and more of the platform they start to unlock some of that intelligence benefit that you get from when you’ve got, not losing all that information or relying on people having relationships to share things. We’ve got a whole bunch of connectors out of the box which allow us to drive connection within internal systems. And that’s really important because what it means is we’re not having to rely on these big data migrations or data lakehouse projects that might be quarters or years away. We can pull data directly from source systems and reason over that data and create great agentic experiences for our customers.

And really, again, I hate describing it like this, but businesses like Palantir have done a great job at dealing with the big end of town from a top thousand companies around the world perspective and enterprise, and sorry, in government. We’re really targeting that mass mid-market, from sort of 200 million revenue up to 2 billion revenue, where from a P&L perspective there is a very strong impetus to do something from an AI perspective. And I don’t mean the cost side, I mean the revenue side and leverage.

We’re really thinking about things in the context of how do we, in the context of lending, how do we write 80 billion worth of loans, not 40 billion worth of loans, from a growth perspective. How do we bring new products to market that we couldn’t bring before, like Guardian for example. So taking that sort of approach. And really there’s a really big cohort there of customers or companies who they have great businesses today. They have great customer bases today. They have great and loyal employee bases. But a large number of them are going to be challenged in the next 12 and 24 months by an AI native version of themselves.

And that AI native version of themselves is going to have a structurally lower cost base, probably a better product, and they’re going to be able to move faster. And what really gets me out of bed every day is the ability to kind of help businesses kind of go through this journey and compete head-on with those AI native businesses and reimagine themselves as to what this looks like in an AI native future.

Dexter Cousins
Yeah. So I guess the biggest challenge that anybody has when they’re selling a technology solution or consulting solution or whatever it is, is you get on this enterprise path where you’re leading a dance for 12 months and decisions take forever and there’s 20 different stakeholders and the key sponsor all of a sudden quits and you’re back to the beginning. You’re in that kind of horrible part of that adoption curve where people know that they’ve got to do something, but there’s still that level of scepticism. Approach that you’ve got of how to quickly get in and kind of start to earn trust with customers and prove out the model, because I guess the concept to them is pretty new as well.

David Hyman
Yeah, it’s a really good point, and I think I see this all the time with other enterprise SaaS businesses. And maybe just as pulling on that thread a little bit, one of the things that when you look at enterprise SaaS, whether it’s enterprise SaaS AI or otherwise, you typically have a product that you’re selling to a particular stakeholder in a business. And let me just, I won’t choose a particular company name, but I’ll just call out like a cloud security company, right? They’re selling to CISOs typically. The CISO is typically not in the exec team, but they’re a senior influencer. You’re typically selling on a two, three, four year cycle based on the incumbent, and you’re effectively competing against a line in someone’s opex budget.

And you’re either trying to get them to spend more to get more value or you’re trying to get them to save money on your product and spend less. That’s typically the way that cycle goes. And anyone who’s been in that world would know that it is fun, but it’s a bit of a grind.

With our platform, and I’ll come back to the point before about how do we get in there and prove value quickly. AI is so interesting and AI native transformation is so interesting in a sense that we’re genuinely having conversations with, if it’s not the CEO, it’s the chairman or chairperson.

Dexter Cousins
How have you done that then?

David Hyman
Well, as I said before, we’ve moved into this world where it’s a…

Dexter Cousins
That’s mind-boggling, right? Because if you think of a startup, right? Usually you’re starting the ground up and trying to kind of build up to get credibility and get an internal sponsor who’s going to fight your corner and gradually you work your way up to the, you never get into the chair. Usually you might at some point get to the CEO, but you’re not starting from top down chair.

David Hyman
I think the difference we have is we’re operating from a world where Lendi has done such a great job from an AI native transformation perspective and genuinely been market leading that that’s opened a lot of doors.

Dexter Cousins
Right.

David Hyman
Both over the last 12 months we intentionally built in public, and as part of that process there was actually a point in September where I had a 5-day week where I did something like three keynotes, four boardroom lunches. And this is not things that we were getting paid to do. This was just doing favours for the hyperscalers or companies that we had good relationships with. And we’re talking about our AI native journey. And through that process, we’ve met a lot of people. We’re now starting to get inbound interest from companies as we’re, we haven’t, as I sit here recording this today, we haven’t officially launched, but people are talking about it. So, that’s probably answer to your question.

I suspect as we grow and scale those conversations will shift. But the point I was making there was the conversation is a lot more senior and we’re not trying to displace an existing spend. We’re trying to work with businesses on their broader business model and therefore the whole P&L is in question. And we’re not trying to fit ourselves into a two or three or five year cycle. We’re genuinely creating a category, and so while in a lot of senses that is difficult and in the opposite sense, if you have a strong proposition and strong appetite on the other side, it means that motion happens faster.

So the way we are building trust, outside of credibility of the story historically etc., the way we’re building trust is through that wedge model that I described. So we work with businesses to first understand their technology stack and where they’re sitting across stuff they’re working with at the moment. Are they using different tools? Which cloud are they in, etc. And as part of that we help them define their AI native vision. So what could their business look like in an AI native world? Now it doesn’t have to be written in stone. It’s intentionally high level, low fidelity.

We then use that to then work backwards and identify, based on their objectives, so their business objectives, where do we start? And that’s either a vertical or it’s a horizontal. So the vertical could be a particular division or a state or a department in the business, or the horizontal could be something like executive intelligence or sales funnel acceleration or meeting intelligence are some areas that we’re seeing a lot of demand in.

We then, through those horizontals and verticals, we identify a starting point which we call a wedge, which is part of that wedge system, which is a high impact, low risk use case that we can deliver in two to six weeks. We co-build that with the business. It’s priced on a fixed fee, which is a very palatable price, to really get started so we can show value very, very quickly. And we’re finding that that motion is really resonating with the customers we’re working with, because it allows us to say, let’s not spend six months deciding what we’re going to do. Let’s actually get started in six weeks’ time. Have something that we can all stare at and say, these things worked, these things didn’t. This was our view on AI native. These things still hold true and these things have maybe shifted a little bit to the side and we can then adjust the plan accordingly.

Dexter Cousins
I want to talk about the name. One of the privileges that I get of working with founders like yourself is I get to see the multiple iterations of the name of the business. How did you land on Mono?

David Hyman
You are referring to the project name.

Dexter Cousins
Yeah.

David Hyman
That we had beforehand. We may have run into some IP challenges there, but that’s easier to solve those before you go to market later.

Dexter Cousins
It’s why there’s so many fintech names where they’ve got no vowels and it’s the…

David Hyman
Exactly.

Dexter Cousins
So you cut the vowels.

David Hyman
Yeah. So I’ll tell you exactly how we came up with the name. So there’s a guy that works with us in the Lendi business and he’s talked pretty affectionately about Japanese business culture. He spent a number of years over there. And a number of the Japanese business principles really held true for a number of years and read things like The Toyota Way and that sort of stuff. And Japan’s also home to one of the oldest businesses in the world, is I think it’s like a six or 700 year old construction company.

So when we were building out the plan for the business, we had a whole bunch of principles that underpinned the way we wanted to build out the culture in the organisation. And I won’t go through all of them, but I’ll maybe touch on a couple. So in building a business like this, AI is very almost very, very tech by definition, very, very technology-driven, but we wanted to keep the human element in there. And one of those principles is genchi genbutsu, and it literally translates to go to the source. And Japanese business principles, it’s all about walking the shop floor and understanding exactly what customers are saying, sitting with the person using the system to understand exactly how they’re using it. Clearly in our context, it’s incredibly important.

So, got principles like that. We have principles like kaizen, which is always improving. You don’t have to be perfect on day one, but compound 1% every day, and you end up with great compound growth over time, etc., etc. So, they’re the principles, and they’re all based on or grounded. There’s four or five of them, or five of them, and they’re all grounded in Japanese business principles. Mono is short for monozukuri, and monozukuri translates directly to the Japanese art of craftsmanship. And so we’ve shortened it to Mono. And yeah, obviously you can see the brand here.

Dexter Cousins
That’s pretty cool actually, because there’s been a narrative that’s been thrown out there that AI will allow people to be more creative, which I’ve kind of, I think it will, but whether people actually are creative or want to be creative is perhaps another question. But I think what it’s certainly what I found in my use of AI in this last 12, 18 months going deep into it is what it’s actually allowed me to do is go all the way back full circle to really focus on my craft. My craft is meeting people, right? It’s like spend more time face to face and less time doing the stuff that was take me out of that. So I really like the thinking of the name there.

David Hyman
Yeah, and you’ve just hit the nail on the head in terms of some of the double meaning behind the name. And that’s exactly right. I think when you break it all down, AI is not about job losses. AI is about new possibilities and getting back to your craft and putting the busy work, the stuff that we all didn’t really like to do, pushing that down the stack so we can spend more time on the things we love.

Dexter Cousins
One thing I have noticed being back in the city, two days a week this year, and I don’t think I’ve seen Sydney this busy since pre-COVID. And that pretty much everybody that I’m speaking to back in the office four days a week now, some five, a few three, but mainly it’s four with one day working from home. Can’t help but think that AI has kind of risen the game and provided a level of competition that perhaps hasn’t been there since COVID times and maybe we all got a little bit too comfortable and we had government paying for us to stay at home and work from our bedrooms. What’s your sense as to what you’re kind of hearing from your clients and the people that you’re talking to around what they’re seeing within the workforce and whether they are seeing an uplift in performance?

David Hyman
It’s a really good insight. I’m going to come at that from a few different perspectives. I might start with agreeing with what you’re saying around performance. I think we had record low unemployment rates for a number of years. If you exclude COVID and the protectionism that happened there, you could basically walk out of a job and into another one, probably get a pay rise, for most of the last 5 to 10 years. And that drives a certain type of behaviour.

The second theme that’s playing in is the sync versus async. So good businesses pre-AI era were very deliberate about which tasks needed to happen sync, and that happens in the office, and which tasks could be async, and they were longer running and maybe turning around a design or a document or whatever that is. And so that lent itself to hybrid working in a whole bunch of different ways. With AI, the cycle times are now minutes. Maybe, I don’t know, half an hour, depending on what you’re doing, and therefore being in the same room and next to each other and actually getting that real-time feedback, either what you’re doing or what you’ve got AI agents doing on your behalf, is so much more important. So those are definitely underlying drivers.

But what you’re saying here is interesting in a sense that what I am seeing from, and there’s definitely a spectrum here, but from the forward looking businesses, the ones that are to my mind using AI in an expansive way, they are definitely holding a much higher bar internally because of two reasons. One, there are things that they used to get people to do in their business before that AI can probably do as well or better. And so therefore the bar around delivery is higher. The second thing is there are some businesses deliberately reshaping their workforce. They might have had four people in a function before and as natural attrition happens they might keep the same spend level, but now they’ve got two people in that function on a higher wage with higher capabilities, and that just lifts the bar with everyone. So I do think we are going to see a quality bar increase from a whole bunch of these things kind of all compounding together.

Dexter Cousins
Yeah. I’ve been speaking to a lot of people that David and help new with hiring, the 1% who can redefine what’s possible. And I’ve got to be honest, I’m a bit shocked by the number of people who haven’t kind of grasped what it is that you guys are doing and this change that we’re right in the midst of. Now, a lot of these people that I’ve been reaching out to, either solutions architects, engineers. You’re not an engineer. What kind of impact has that had on you running an AI business?

David Hyman
Well, I think it’s really interesting because I’ve been running product and technology businesses for, well Lendi for example, product and technology business from day one for 13 years, and before that was always in product and tech businesses. If I go all the way back, take myself back, and I think we might have covered this in one of your previous podcasts, when I was 8 years old I was building computers and selling computer parts, and handwriting lines of code as a 10 or 11 year old in PHP and on a MySQL database and all that sort of stuff.

So kind of going way back I was, but actually the pathway I’ve taken mostly through my entrepreneurial career has been on the commercial side. And as I said before, this has moved from being a technology problem and becoming a business model opportunity. And I think what is really interesting, you asked before which stakeholders we’re dealing with. When I speak to CEOs, believe it or not, the biggest blocker in most organisations to them executing on their AI strategy is the CTO. And I love CTOs. I’ve worked with amazing technologists. They are great. But I’m seeing that happen in the market. And so it’s really interesting, those that are closest to the technology not necessarily lifting their gaze and thinking about how this plays outside of just providing services within a particular part of the business.

Dexter Cousins
Talking about, I guess, people and headcount. If I look at the conversations I’ve had with founders over this last 12 months and those that started businesses at around about the same time as you would have done with Lendi, if they could do their time again, they’d build a very, very different business. And I’ve had a number of people in my network and founders say, “Hey, I actually think I could build a billion dollar business with 30 to 50 people.” And I absolutely believe them. I got no doubt they could. What’s your view on the business that you’re building, and kind of are you, with Lendi, you what, nearly 2,000 people, 1,500 people, do you ever see Mono getting to that size or have you got a very different idea in mind?

David Hyman
Yeah. So, I think what AI does is it gives you leverage. And when you’ve got a highly aligned team of high curiosity and high agency people, going back to that example I was giving you before, and then you give them the superpowers of AI, you get a lot of leverage. And so the way we’re thinking about this internally is how do we, for every single person we have in the business, how do we give them that superhuman leverage through a team of AI agents or a workbench of AI agents that allow them to operate at a different plane to others. And so yeah, we’re very much in the camp that we can continue to grow and build and scale our business at a different level of leverage to others.

The way we think about that is, and we’re seeing this both in our own business, but also how we’re thinking about the businesses we’re helping, is in the context of revenue per employee. And so, if you think about that, just to set a couple of mile markers, traditional businesses were more like two, $300,000 revenue per employee. Maybe some of the best enterprise SaaS businesses were five, six, $700,000 revenue per employee. And then you sort of fast forward to some of the new AI native businesses. ElevenLabs is a great example. $400 odd million dollars worth of revenue, couple hundred employees. It’s like $2 million revenue per employee. That revenue is not from their revenue producing employees. That’s across everyone.

I think they’ve got something like 18 people in their go-to-market team. That is leverage. But going back to my earlier point, it’s businesses like that that the incumbent business is going to be competing against in 12 and 24 and 36 months’ time. And that’s the structurally differentiated operating leverage that I was talking about before. And I think it would be completely hypocritical for us to build a business on our side that didn’t operate at those levels of leverage ourselves.

Dexter Cousins
There’s quite a few of them out there.

David Hyman
Oh, there is.

Dexter Cousins
The hamster wheel is going in the background.

David Hyman
There is. But I think it’s a really good constraint for us to build around when we’re thinking about how do we go from A to B. We’re really thinking about that in the context of capabilities as opposed to capacity, because the capacity can start to become elastic as we’re thinking about using AI in the centre of everything that we do.

Dexter Cousins
Yeah. You would have kind of seen similar with fintech, and I think one of the things that always distinguished you from, certainly the early days, was you never went chasing the noise. It was very much about substance, and those who did chase the noise and the sizzle, kind of no longer with us. And in terms of the businesses, do you see there’s a similar kind of narrative and danger happening around AI, where people are chasing the sizzle and making all of these promises, but the technology’s not there yet? Or is it different this time?

David Hyman
So, in any hype cycle, there is always going to be smoke and mirrors somewhere, because human nature, there are certain cohorts of our great species that go and chase the noise and chase the shiny thing. With all of that being said, the technology is 100% there. And anyone who’s used the latest models, whether that’s Gemini Pro 3.1, GPT 5.2, Opus 4.6, Grok 4.2, whichever one it is, it actually doesn’t matter. They are all strong enough, powerful enough, fast enough to fundamentally change everything that we do.

I’ve said this a couple of times and I’ll keep saying it. All the R&D could stop and as long as we can solve the capacity issue, which is mostly power and water, the world has fundamentally changed. But the R&D is not stopping and we’re seeing the acceleration curve of, whether it’s the time that these models can operate autonomously through to where they fit on the benchmarks, all the way through to real world applications and what they can solve, that’s only accelerating even faster than it was in the previous period. So, super exciting time to keep building.

Dexter Cousins
We’re recording this in the week that Eucalyptus has just been sold. Everybody’s super excited. Fantastic news. Great outcome. Congrats to everybody. I genuinely think this is a bigger opportunity than what we’ve seen with Eucalyptus, that you’re working on. And you’re building here from Sydney, not Silicon Valley. First of all, why you building here in Sydney? Second of all, if anybody’s listening, how do they get involved?

David Hyman
Yeah. So, firstly, congrats to the you guys. What a great outcome. I saw a couple of the team yesterday and gave them my congratulations. It’s just amazing for the Australian ecosystem for all the reasons that are obvious to everyone listening.

Why build from Sydney? So, I mean, outside of it is one of the best cities in the world. Great safety, great lifestyle, great weather, all that sort of stuff. Australia really punches above its weight in terms of the quality of entrepreneurs, technologists, product people compared to any other market around the world. I spent a lot of time in other places around the world. And what’s really fascinating about that is the more you spend time in Europe or US, you actually realise that the calibre of people here is just top world class.

And so we’re building our base here. But we are going to be launching other markets over the next few quarters, and as we turn those markets on we will build hubs in West Coast US, East Coast US, EMEA, etc., etc. But those hubs will be supported by a great base here in Sydney. We’ve seen some great technology companies do that historically and I just think there’s a really big opportunity for Australian entrepreneurs, and even if they’re not entrepreneurs, people working in product, technology, go-to-market, support, whatever that role is, to continue to put Australia on the world stage, and that’s what we’re passionate about doing here.

How can they get involved? Probably best way, if you don’t know me directly, is hit me up on LinkedIn. We’re pretty active there. DMs are open for those that want to get connected and we can have a chat. We’re hiring pretty quickly, but we’re not hiring thousands of people. But we are looking for people on the product and platform side as we continue to build out the platform, and we’re looking for people on the delivery and go-to-market side. So if you’re in enterprise SaaS, if you’re in big four consulting and you feel like you’re more on the entrepreneurial side of both of those businesses, whether it’s on the go-to-market or delivery side, would love to chat.

Dexter Cousins
Awesome. Well, David, it’s been fantastic to catch up. First of all, congrats with everything that you’ve achieved with Lendi. And I’m so excited about what you’re building. It’s, for somebody who, all the things that you’ve talked about, the reasons why I started Tier One People, and to hear you not only talk about this change in the nature of work, but also your endorsement of the talent here, which is exactly what I’ve been trying to bang the drum for the last 10 years. It’s a really gratifying thing to hear.

David Hyman
Yeah. Awesome. Thanks for having me again. Let’s tee up number five some.

Dexter Cousins
Absolutely. Absolutely. As always, folks, you can catch up with me on LinkedIn and X. If you’re new to the show, make sure you follow us wherever you listen to podcasts. And if you’re watching on YouTube, give us a like and subscribe. And if you are looking to hire exceptional people and you’re a founder like Dave and bought you on that journey, reach out to me. There’s a link in the show notes. Until the next episode, be good.

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