SaaS Stories
SaaS Stories is my not-so-secret quest to learn what it truly takes to succeed in the world of SaaS—and I’m inviting you along for the ride! I have the pleasure of sitting down with brilliant minds and industry trailblazers to explore their journeys, uncovering the secrets behind their growth, the gaps they spotted in the market, and what really drives them.
It’s not all smooth sailing—there are challenges, unexpected turns, and moments of reflection where they share what they’d love to change about their journey. Think of it as a candid, insider’s look into the world of SaaS, with just the right amount of curiosity, empathy, and wit.
Join me as I dive deep, selfishly soak up all the insights, and hopefully share a little inspiration with you along the way—one SaaS story at a time.
SaaS Stories
Speed matters, but passion matters more. Building tech teams with passion.
Daniel founded TLV Tech in 2018 to address the fundamental conflict in vendor-client relationships where vendors prioritize selling hours while clients aim to minimize costs.
• Grew from garage startup to a 50-person global team serving clients from pre-seed ventures to Fortune 50 companies
• Uses a "gear system" to adapt working styles between startups (speed-focused) and enterprises (process-oriented)
• Prioritizes hiring engineers passionate about technology over specific experience or tech stack familiarity
• Recommends non-technical founders stay involved in product development rather than completely outsourcing
• Suggests future-proofing tech stacks through language consolidation, thoughtful tech selection, and community support
• Embraced AI early across all business functions, making them more efficient and cost-effective
• Compares startups to speedboats and enterprises to yachts - with AI giving speedboats unprecedented opportunity
• Believes software engineering jobs aren't threatened by AI but will require different skills
• Advises founders to ask themselves: "If you couldn't fail, what would you do?"
What inspired you to launch TLB Tech. I want to see how it looks like when I become the vendor.
Speaker 2:Tell us a little bit about your hiring mistakes. If you could go back in time, what would you do differently with the hiring process?
Speaker 1:Don't just outsource the whole product right. Understand the choices they make, understand the trade-offs they have.
Speaker 2:Let's tackle AI now. How do you use it and do you think software development jobs are at risk?
Speaker 1:Let's just put it inside our processes right now. So it's putting a credit card number away from introducing that to the company. So we've done that and we have, you know, plenty of AI in the company.
Speaker 2:So do you find a difference between the two? Is there a different model of working between those two types of companies?
Speaker 1:That'll probably change my entire journey between those two types of companies.
Speaker 2:That'll probably change my entire journey. Welcome everybody to another episode of SaaS Stories. Today I'm joined by Daniel, ceo and founder of TLV Tech. Welcome, daniel. Thank you so much for having me, joanna no-transcript.
Speaker 1:R d. You know center group department what led me to it. We started in 2018, um, before that, I was in the tech space, so anything from an ic level to a-level executive, anything from a few folks in the garage all the way up to IPOs and that's a pretty kind of a wide you know wide range and I got to work with so many different you know very successful, very talented engineers and engineering managers, and I also got to work with a lot of different you know tech services companies, right, and I don't know I a lot of different tech services companies and I spent like a decade doing that and I worked with a pretty substantial amount of vendors Anywhere in the world, any seniority level, any company sizes. I worked with small boutique shops and then with larger multinational organizations and I was never too happy about that relationship in general not the companies themselves, but the relationship, because the engagement there is in our space is that, well, we get compensated like our kinds of companies get compensated by the hour, right, and the client is also paying by the hour, but the interests are different. You know, by definition, right, if you look at it from like, if you take emotion aside, if you take. You know, ethics aside, the vendor's first priority is to sell as many hours, right, but the founders or the engineering managers' priorities are going to be to purchase many hours, right, but the founders or the engineering managers priorities are going to be to purchase as little, right? So there's a conflict in there.
Speaker 1:In the first place and I've seen it happen again with all the different vendors I've worked with there is a conflict by design. There is an issue there, a challenge. So I said you know what? I want to explore that space, I want to see how it looks like when I become the vendor. And I swear to myself I would never bill on an hourly basis, I would only look at what's going to be the client expectations. And then I'm going to translate that with my technological background to then explain why it is that difficult or that easy, or how long should it take, et cetera, et cetera.
Speaker 1:Right, and if there's any blind spots, and yeah, and that's what kind of led me to start TLV Tech, trying to bridge that gap between the client expectations and the vendor expectations, so to speak, yeah, and we've been running for the past seven years. We're now a team of about 50 folks, almost all engineers based out of Israel working with clients pretty globally. So Australia kind of a right-hand side, europe, israel and then US and Canada on the left side of the map, anything from like pre-seed ventures all the way up to Fortune 50s.
Speaker 2:Amazing. Well, I could think of a few companies that started out in a garage. So glad your story started there too. I think that's where all the best stories start. Yeah, I think that's so challenging, isn't it Kind of charging clients by the hour, because they always feel like billable hours is probably the most valuable thing to the agency, whereas you're just trying to service them as best as you can? And I think CLV Tech, you work with both startups and large enterprises, so do you find a difference between the two? Is there a different model of working between those two types of companies?
Speaker 1:So commercially not really, but in the day-to-day, in the expectations, there's a very big difference. Right, we internally call it gears. We have the system where we call it gears like car gears and we said you know what a startup needs to, okay, so every client needs to identify the right gear for them, right? So a startup might want to go in the first gear. They want to go as fast as possible, not being too let's call it responsible, right? Not thinking about the more kind of complex challenges that come with larger companies, like scale and like extreme cybersecurity and extreme privacy and compliance and all that. Right, we never do like irresponsible work, right, but we don't necessarily want to invest too much in cybersecurity or privacy or compliance in day one of a company, right? So that's a good example of the first gear. And then with larger companies, it's the complete opposite. You work in your fifth gear, right? So everything is very slow, right? You don't want to launch yesterday. Like all of our startup clients. You have a plan, you have a release cycle. You understand when it's going to be live. What's the process of getting there? Going live is not clicking a button. It's going through legal and compliance and marketing and communications and a lot of different departments in organization. So there the process is slightly different. And also, usually the engineers who enjoy this process are very much a different nature than the ones who like going fast to market.
Speaker 1:So, yeah, so a very wide range of differences between them, right, and there's obviously a lot of in-between, right. So in startups you also have, you know, early stage, that's pre-CEC, and then you have round A, b, which looks slightly different, and then CD, when you have your product in place and you just wanna, you know, expand that. So, and almost ironically, right, the gears shift with those stages of companies. And that's before speaking about you know, the complexities of, like taking it simple, right, even to log into the computer right Of an enterprise system. It's a much more complex, you know, event right Than just starting up the laptop and start coding. So there's many differences. We had to learn them as a company throughout the years and I think we now understand the differences.
Speaker 2:We understand, uh, the expectations of those clients and understand how to properly serve them yeah, yeah, the reason I ask is because I think I have the same challenge as well. So we, you know, as a SaaS marketing agency, work with both startups and, uh, enterprise level, and so you're right, it's it's the speed at which they want to travel, um is so varied and it's really it just takes a moment to realize you know what is their speed, what are their priorities. So, again, like for anyone listening and you needing to service different types of clients, this is a good learning experience, just to kind of identify how do we create different customer journeys and how do we service each one.
Speaker 1:I always look at it like a C right, you have the large enterprises who are basically a yacht right, super stable, you know no chances of being flipped um, you know very slow and steady. And then there's startups who are like speedboats, right, uh, there's plenty of them. They're very fast, they can turn pretty quickly, uh, but there's always the risk right of flipping over um. So I think, uh, actually, I think the the most interesting scenario is something of an in-between. Maybe we'll touch that a bit later when we talk about AI and the world and how it's changing, so I'll just leave it for later.
Speaker 2:Yes, oh, ai is definitely coming up. I think that topic always makes its way into every and each and every podcast, but I'll let's, um, let's talk about your journey as a ceo, because you've gone from a founder in a garage, like all the greatest brands, to now being a ceo of a plus 50 people company. What has been your biggest learning, and how do you manage an entire and lead an entire organization?
Speaker 1:uh, well, it's a very complex question. I think the first thing that everybody needs to know is that nobody is born a CEO, right? Anyone who wants to step into that position have so much stuff to learn, right, starting with basics. I think the thing that terrified me the most when I started the company is how am I going to pay taxes? What's the process of paying taxes? I have no idea. I used to get a salary paycheck, right, you know. Things are getting automagically paid for me by my employer. What's the process of speaking to the authorities, to the IRS, whatever it is, and that terrified me IRS, whatever it is, and that terrified me. And yeah, I think, if you look at it from like a very naive perspective, that was the biggest learning curve. It didn't come from finances, I didn't come from the business space, and having to learn on how to do the regular stuff that every business owner does, that was biggest um learning curve, uh.
Speaker 1:But then obviously you have you know how do you hire, how do you uh keep people engaged, how do you um create good company culture? Um, in our field of profession, the challenge is when you grow right. So being a good technical person means that you can control a small team, right, and have everything in place and manage the whole thing almost like a team lead in a standard company. But then as you grow, you have to make sure that the quality doesn't get hurt, right? And then it's not.
Speaker 1:And I obviously don't speak to 50 people every day, right, I think I speak to maximum of like five to 10 people. And then how do you take? How do you first of all, pick those five to 10 people who you want to communicate with on a daily basis and make sure that you're aligned? And once you pick them, how do you get your values to them? But not only in the way that you know they behave like you, because, I don't know, because they're close to you or want to satisfy you quote, unquote but how do they also take the values, understand what's behind them, right, see different examples in real life, and then pass them on to their five to 10 people that they speak to on a daily basis, right? So I think that's a big challenge that we faced and I think, in some ways, that are still facing right now, and I think this is something that will probably lead me, like whatever we grow, to I think hiring is a big problem for every organization.
Speaker 2:I don't think anyone has it right. There's so many mistakes being made. Maybe tell us a little bit about your hiring mistakes. If you could go back in time, what would you do differently with the hiring process?
Speaker 1:So I think maybe let's talk about what's important in the people we hire before that, because mistakes only happen when you have misalignment. It's not like hiring. I don't believe in hiring a bad person. I believe that there's just a misfit between your expectations and values and that person's expectations and values and wants right. So there's no bad employees, just a misfit. So what's really important for me, and was important since day one, was to hire people who are passionate about technology. Right, I didn't care about their background, about their seniority level, about how many years in the industry they have or if they wrote in this on that tech stack. I really don't care about that, still don't. What I care about is being passionate around the job, right, and you find it not when asking people are you passionate around your job, right? You find it when you-.
Speaker 2:I still say yes.
Speaker 1:Yeah, exactly, exactly. You find it by asking like things around it, right, so like in that AI space, what did you learn? You know deeper in AI, besides using ChatGPT and Cloud and Gemini and whatever right, and how do you integrate that in your day to day? How does it help you as an engineer? Did you ever, like I don't know, use Venmo and ask yourself how would you implement Venmo? And ask yourself how would you implement Venmo as an engineer? Not because you wanted to create a Venmo, but just because that engineering curiosity is there all the time.
Speaker 1:Right, you see your everyday products and you think, like, how would I build that? What are their challenges? And a person who's passionate around technology thinks about it, whether they want it or not. So these are the kinds of questions that I ask now that really show me the passion of those engineers and make me believe that these are going to be, you know, very, very strong engineers and they have a very good cultural fit to our existing team. And I see it during lunchtime, right, I see that around us there's plenty of tech companies and they speak about you know, last night's Eurovision contest or the soccer game we had and then our team consistently talks about technology, about Google's last announcements, about the version update of Cursor AI or something else, and I see that it becomes like I'm really proud of that right, because I see that my passion around technology is now not only my thing and not only thing that surrounds me with those five to 10 people, but it's actually company spread right, so everybody are passionate around that and that brings them together.
Speaker 2:It makes a lot of sense, doesn't it? Because, I mean, with AI changing rapidly the world that we live in, I think the best kind of skills you want is someone that can learn really quickly and adapt really quickly, and the only way to do that is if they have a passion for that specific skill set. So, yeah, you're right, if they're kind of passionate about that, then they're more willing to learn things that they need to learn. Coming back to the customer, so let's say early stage startup founders as an example what are some technical mistakes and oversights you see them making when they go about building their products?
Speaker 1:So there's basically, I would say there's a few choices that you make as a founder that are going to determine the rest of your journey, right, like a startup.
Speaker 1:And there's just a few, maybe a handful. It's going to be the tech stack, the architecture and maybe like your standard processes of how do you release a feature product, whatever, and a lot of early stage founders. And that's again that's a question of is it the first time or a second time, or a tech founder, not a tech founder? But I would just generalize the question. Usually what happens is that early stage startups consist of classically, right, a tech founder and a non-tech founder. Right, the non-tech founder takes the commercial position, right, of raising capital, of raising clients, on building, you know, marketing plans, go to market, etc. Right, I'm taking this, this part aside. They don't usually handle tech at all, which is fine. And then the tech founder is it can be a very wide range of tech folks. Right, it can be people who used to be IC level engineers and they used to think in that mindset of an IC, right.
Speaker 1:And then there's tons of mistakes. Right, they don't think strategically, they pick bad tech stacks, they don't know how to think about hiring, about growing a team, about bottlenecks, et cetera. And then there's very experienced engineers and managers who are usually are very far from the keyboard the way we call it Right. So these are people who used to write code. You know five, 10, sometimes 20 years ago, and they know what they know right, which was relevant 20 years ago, but the world has changed so much since that, and speed matters. In a startup, speed is the probably number one thing that matters, and picking a tech stack that was relevant 20 years ago, when things changed so much, is not going to contribute to speed right. So that's and that's going to be strategic, because when you pick a tech stack and an architecture, as I said, it leads you throughout the next five to 10 years.
Speaker 1:So plenty of mistakes. And that's like I'm speaking about the classic journey of a tech founder and not tech founder. There is sometimes non-tech founders who just rely on a vendor or a freelancer or the first employee to build something good and then, five years later, they identify the issue and you know it's painful. So there's plenty of mistakes. I think the kind of my number one tip is going to be just like you validate your products in the commercial space and you're talking to customers and you're talking to partners and competitors and mentors. Do the same thing with your tech side, right? Don't? Don't centralize the decision-making in just one person. Consult from a respectful way, right, because sometimes you have the best tech co-founder who knows exactly what to do as an entire playbook A to Z. But it wouldn't hurt to speak to another five technical founders or technical executives just to validate that, to make sure that the decisions you make are the right ones, not just today, but also in two years.
Speaker 2:Yeah, yeah, I think that is the classic journey though non-tech founder and tech founder and that's probably the most successful companies in the end, because you have these two different skill sets. It's also the types of companies vcs are more likely to fund as well, because you know you've got two founders working there. But the non-technical founders I've actually had a few on, you know, on this podcast as guests and you're right, their journey has definitely been more long, more painful, harder, because they don't have that coding skills or knowledge. What's one piece of advice you would give to those guys, the non-technical founders, who are trying to build the product for the first time? So validation is one of them. What's another one?
Speaker 1:I think don't just like from a mindset standpoint, don't just outsource the whole product. Right, be involved. Right, understand the choices they make, understand the trade-offs they have. We, I guess, as engineers, we have so many micro decisions we're taking every day. Right, and obviously as a non-tech founder, you can't be in any decision, in every micro decision, but at least the biggest junctions that you have ask to be asked.
Speaker 1:When an engineering team has multiple ways of going when implementing something usually it's like the quick fix versus the enterprise uh solution then you know, stop there and tell them. You know, just ask me, ask me, what do I prefer? I prefer to do it in a quick and dirty way, because sometimes we have to, because the client waits for something or the investor needs to see that, or just because it makes sense at the time, versus some things you would want to uh, invest more time and capital on to solve it properly, and that's probably going to be the core of your product. I see too many non-technical founders just give their wireframes or mockups or Figma screens and say, you know, just do with that. Don't do that. Be involved, at least in a weekly basis with the engineering teams that are working with you to make sure that those biggest junctions, you catch them on time.
Speaker 2:Yeah, that makes sense for sure. You mentioned the word tech stacks quite a few times in our conversations. I'm just wondering, you know, with so much coming out, so much new technology you know, ai, new code, so much new technology, ai, new code what's one way that clients can future-proof their tech stack and make it scalable from day one?
Speaker 1:Scalable is also a difficult question. I'm trying to kind of scratch 20 years of experience into a single question. I think, even though we have AI and everything, the fundamentals haven't really changed too much, right? Ai helps write code in the same languages, more or less, that we wrote in five years ago.
Speaker 1:I think what's important when picking a tech stack is, first of all, consolidating, right.
Speaker 1:Today is very popular to have full stack engineers, right, and the advantage of having a full stack mindset is, first of all, there's plenty of software ones, right.
Speaker 1:But the main hard advantage is that you have the same language, usually right, across your front end, back end and usually mobile tech stack. So consolidation is important because some people they want to work with full-stack engineers but then they choose on different languages in the front-end and back-end. So it's not like there are not engineers that can write in language A and B, like Flutter, for example, and JavaScript in the back-end, but statistically it's going to be more difficult to hire those people down the line versus having somebody who writes JavaScript on the front end and JavaScript on the backend, right. So it's all about statistics and when you pick a tech stack, you also have to think about how easy, statistically, it's going to be to hire a team of 10 engineers in five years. Okay, so not picking a very modern tech stack Modern is not the word, but not picking cutting edge tech, because it might not be around in five years. It doesn't have a proven record. But then not picking a too old tech stack that is going to become like a dinosaur language in five years.
Speaker 1:Yeah, so I think consolidation is one thing, thinking about how to hire a larger team down the line is another one. And then community is very important as well, because the R&D profession has a very wide and very supportive community. Right, a lot of the stuff that we build are based on open sources, which are, by definition, community built products. And then you have organizations on top of that, like Apache, who are like global organizations that ship A to Z products in an open source manner. Right, the community is so supportive that not taking advantage of it is a mistake by definition, right. So when you pick a stack, you also want to see the popularity of it, the trendiness, the amount of people contributing to that stack and building supportive tools and supporting frameworks to that. I think that's a key differentiator.
Speaker 2:That makes sense. All right, let's tackle AI now. I think we've alluded to it a few times. How do you use it and do you think software development jobs are at risk with what AI can do right now?
Speaker 1:Yeah, so as a company, we have a lot of AI-infused processes, right, and it goes across everything in a company finance, operations, project management, marketing, sales and, of course, of course, of course, engineering. Right, I think we are probably one of the first thousand organizations that implemented like AI native processes in the company Because, again, we're a small company. Going back to that, you know speedboat mentality we don't have a legal compliance department that stopped us from sharing our code to open AI, entropic or anything else. It basically was a decision, right. Ai is going to be huge, saves us a lot of time and effort and errors. Let's just put it inside our processes right now. So it's putting a credit card number away from introducing that to the company. So we've done that and we have plenty of AI in the company. It helps us being more efficient, it helps us being, you know, faster and eventually it makes us build and ship more solid products faster and cheaper for our clients, right? So this really gives us an edge in the competitive space. And to your question, is it going to eliminate software engineering jobs? I don't think so.
Speaker 1:I think that right now maybe I'll take it in a larger scope here the question I think we're all in the middle of a revolution. I assume that everybody understands that. It's like the internet, it's like mobile phones. This is the magnitude of the revolution we're going through. What happens in those revolutions, historically, but also right now we see that small companies who catch the revolution on time, those speedboats that grab the treasure chest fastest they can grow into a yacht much quicker than the yacht that ships next to them.
Speaker 1:Okay, and we've seen that historically, with small companies becoming, you know, huge companies in the matter of a few years, and we're actually seeing it right now. We're seeing anonymous companies like OpenAI, right, becoming is, you know, giants. Giants value that, you know, three digits, billions of dollars in a matter of a few years, in a matter of a few years, right, and that's the extreme situation. But there's also plenty of smaller companies. In every vehicle you pick, right, take, I don't know, cybersecurity, health tech, education, et cetera, you see a lot of smaller organizations who have the mindset and the ability to infuse AI into them, becoming like a serious competitor to multi-year giants, right.
Speaker 1:So I think right now we're at this phase of there's plenty of speedboats around and the first one who will catch the treasure chest is the one that is more likely to grow bigger, and the yachts they have. You know, sometimes they catch treasure chests, treasure chests, sorry, but it's much more difficult for them, right? They would probably rather to buy a few speedboats, right, and to send them on those missions to identify those treasure chests and bring them back the yacht, yeah, so. So AI is not taking away the engineering, the software engineers' jobs. It makes them slightly different, right? Their, like, syntax is not as important as it used to be, speed is not, arguably, as important as it used to be, but I think just thinking deeper and leveraging those AI tools becomes like almost like a prerequisite of being a software engineer yeah.
Speaker 2:So for all the sas founders maybe of startups or scale-ups listening right now, thinking I want to catch those treasure chests what are some recommendations in using ai? I mean, I'm sure everyone's already using ChatGPT, but what are some ways and creative ways and maybe some other tools in AI that not a lot of people have heard about that you can share with us?
Speaker 1:There's plenty.
Speaker 1:I think that the biggest change that I see is being able to infuse AI into your marketing funnels, because everybody are used to seeing billboards or TV commercials or banners and it catches them everywhere.
Speaker 1:But I think that now things are changing because we're able to leverage AI and almost authentically market your service or product right Without having to go through the traditional marketing strategies of spending money on PPC and SEO and all that, and I think that authenticity almost becomes like a marketing channel on its own right. I see a lot of companies where the founders share their stories A to Z and they do it on a weekly, bi-weekly basis and they get tons of traction just by sharing it authentically. But then you would not be able to uh, maybe you would right, but I think that leveraging AI and even playing with it just to identify how to structure a personal, authentic uh post what are typical hooks that I can share? Um. As a non-marketing founder, that would make my post be more marketing oriented, um, and a bunch of other things. So I think that in everything you do before you hire somebody, ask yourself can I do it using AI? Can I make it faster, easier with AI, without having the burden of an additional paycheck to pay.
Speaker 2:I think it's important to recognize the human element as well. Just from my personal point of view, I know everyone's now using AI to create content. So, like a lot of the blogs, articles, ebooks, they're all written by AI Maybe not all, but a lot, I think and it just makes me not really want to read them anymore. Like if I was to watch a video of a founder telling their story, that is something I do want to watch, that is something I can connect with, because it's like, with all this AI happening, you know, I can kind of see the human connection with that bit of marketing content. So there's definitely, I think, or there will be, a trend towards us craving more of a human touch.
Speaker 1:Yeah, yeah, I wonder how that would feel like now that Google announced the vo3, which creates videos that you can't really uh understand if, uh, if they're ai generated or not.
Speaker 2:I wonder if that is going to change as well yeah, well, just you know, I was experimenting with one particular ai to see if it would um create a podcast for me out of an ebook that I wrote, and unfortunately they couldn't get my voice right, so we're not quite there yet. I gave me an American accent, which I thought, well, it sounds like me, but it's not quite me. I think we're yet to get there and I mean again, I don't think I'd want to watch something that was ai generated, even if it was taking the person's you know, visuals, their voice and creating content. I think I think we're going to be craving that human element yeah, question is would you be able to identify?
Speaker 1:it's not a human I don't know.
Speaker 2:We'll wait and see. Um so much to look forward to I. I think with ai no one really has all the answers and you know, I guess we'll soon find out. My last question to you, a question I ask all my guests, is if you could go back in time and give yourself one piece of advice. Whether it was when you were first starting tlb tech or, you know, maybe it it was when you were scaling it for the first time, you can pick whatever moment in time you like. What would that moment be and what bit of advice would you give yourself?
Speaker 1:I think actually Jimmy Carr said it once. He said if you couldn't fail, what would you do? And this is something I didn't ask myself when I was a teenager or even in my early 20s. I was very like, not confident, and I always went for the kind of a safe place right, I'm going to get a good job, I'm going to get a career security and I'm going to build, you know, a good career as an engineering manager or as an engineer or or something like that. But I never thought big. I never said you know what, I'm not going to fail, what would I want to do? Um, and if I could take myself to as young as possible and give that sentence to myself, uh, that would probably change my entire uh journey do you think you would have started TLB tech earlier rather than later?
Speaker 1:sure, for sure. I would have started in high school yeah, yeah, it's so fascinating.
Speaker 2:But then you think, what if I listened to myself at that age as well?
Speaker 1:uh, there's some it creates, like a unique color. You know, um, even if, like, obviously I would not be as confident as, not as reliable maybe, uh, as I am right now with my years of experience and, you know, supporting founders and executives, right, so I don't see an executive listening to a 15 year old on what to do with technology. But that that's not the thing, right, because it's all about the passion to it, right, and the passion was there for technology all along. So maybe I couldn't give an advice, but I could definitely do other things. I had more time, I could, you know, learn new stuff more easily. There's plenty of color that I could bring to the table that is different from the color I have right now, and that color on its own would probably make me stand out when I was 15 and I couldn't give it an advice on a tech strategy.
Speaker 2:Let's say Love that. Daniel, thank you so much for being on the show. I think we've got some really good advice in terms of hiring, in terms of how we can creatively use AI and just yeah, I think, from a tech stack point of view, some really good future-proofing and scalable way. So thank you so much for your insights.
Speaker 1:Thank you, John. I thank you for having me.
