S1. Ep21 - How Make.com Helps Startups Automate Their Business

Katie: Welcome to the AI Automations for Business Podcasts. We're your hosts, Katie and Noel, and we'll be discussing how you can use AI for your business along with the latest news, updates and automations to help you stay ahead of the curve, allowing you to grow and scale your business more efficiently. Please be sure to subscribe and I hope you enjoy this episode. Hello, welcome back to another episode. Hi, I'm Katie and I've got Noor here with me. Hey, Noel.

Noel: Hello.

Katie: How are you doing today?

Noel: Yeah, as good as always, excited for this one, though.

Katie: Well, do you know what, I was expecting a bit more of a bit more excitement from you today, seeing as who our guest is.

Noel: I'm trying to keep my call.

Katie: Oh, yeah, is that what I'm doing? I'm trying not to like fanboy.

Noel: Yes.

Katie: Well, regular listeners will know that Noel mentions make.com pretty much every episode. and I usually follow it by saying we are not sponsored by make.com but today we are joined by martin from make hello martin

Martin Hýravý: hello katee it's an immense pleasure to be here and i can confirm this podcast is not sponsored by make however i'm still super happy to be here and to provide my insights on what's going on inside of Make and also what's going on in the industry itself. So yeah, once again, super happy to be here. Thank you so much.

Katie: Thank you. Thank you, Martin. So Martin, Ian make you help startups, don't you, with AI automations? Absolutely.

Martin Hýravý: That's definitely one way of putting it. And one of the best ways to put it as well. So on paper, I manage our startup program. And I also am part of the AI team as well, but mostly still working with startups and making sure that they can make the most out of the platform and that they can start automating whatever is necessary and whatever is possible for them. So I would say, yes, my core job is helping startups to use Make in the first place.

Katie: Amazing. Okay. Well, we've got a lot of juicy questions for you today, Martin. So I'm just going to jump straight in, if that's okay. Let's do it. Okay, let's do it. I like it. Okay, so why should businesses implement AI automations? And also, the other way around, why shouldn't they implement AI automation?

Martin Hýravý: That's an amazing question. And you can imagine that I get this on almost daily basis, not only from the people that are within business, but also from my family members as well, which is quite interesting. whenever I try to explain what I'm actually doing within Make and what Make actually can do. But to grapple this question from the complete beginning, so in terms of AI automation, I would always encourage people to start with just automations themselves, because one thing that I try to constantly mention is that even without AI, automation and platforms like Make, you can still gain immense value. you can save a ton of time, a ton of resources just by doing very simple automations on repetitive things that you might already be doing. And when you sprinkle the magic word of AI into it, that's when we enter a bit of a different realm where you can gain even more benefit by this. So to come back to the ground question of why should startups and maybe solo founders use AI and automation, I would say it's slowly, or maybe not even slowly, it's surely becoming a sort of a standard in competing in almost any market, I feel like. So what I keep seeing by talking not only to startups and founders, but also to people from larger corporations or larger companies, is that the competitive advantage that startups and small teams can have over maybe larger teams that have more human resources, more capacity, is this sort of flexibility that they can use AI and automation almost, I don't want to say unlimitedly, but to an extent where they can save on so much resources to be so much more agile and fast. So I would dare to say that if it's not already a standard to have AI automation within your business, then it definitely should be as soon as possible, I would say.

Katie: Yeah, that's a great answer.

Noel: Yeah, we, especially with the agile part, because obviously we're only a very small team so we can implement an automation with an afternoon. So we have an idea and say, oh, this would be good if we could do this. Absolutely. Get it in there straight away, get it working, testing, done. You know, yeah. So you've definitely got the advantage as a small business.

Martin Hýravý: Absolutely. Yeah. And one thing that I would, I guess, encourage people and also try to recommend is to get into the automation mindset as soon as possible as well. So one thing I would say is learning the skill of automating things, then building automations, building flexible systems. But what comes with it that I feel like might even be more valuable is the mindset about and around automation. So for myself, now that I see myself, spending time on things that are taking up a lot of my hours, I immediately start thinking like, okay, so what can I start automating in this moment? And it becomes my priority, because I know the sooner I do this, the sooner I build the scenario in Make or even some native automations, then it's that much time I can save. And I can give an exact example. So I mentioned that I manage the startup program at Make, And currently we have over 3,500 startups. And we're a team of three, rather two and a half, two and a half, I would say. So, and the customer care is handled by almost exclusively me and my colleague.

Katie: So you can

Martin Hýravý: imagine it's a lot of emails.

Katie: And the

Martin Hýravý: thing that I started thinking immediately when I started spending three plus hours every day, just responding to emails was like, I need to build a scenario and automation that's going to help me with this ASAP. Because I feel like with the older mindset, I would start thinking and proposing, hey, we need to hire somebody to handle these emails.

Katie: Yeah.

Martin Hýravý: Like this would be the first thing five to 10 years ago, definitely I would say, we need somebody for this customer care because this is just consuming so much of our time and it would bring us a lot of value. But now, instead of this I think in terms of how I can automate these things so we don't need to hire anybody else and I can actually spend time on things that are going to bring some money to the table if I can say this.

Katie: Yeah that makes sense. Yeah I love that change of perspective because you're you're so right even just a couple of years ago we would have like been going to our boss like you know I've I've got too much work you know I can't answer answer all these emails, or I'm spending all my time just answering emails. We need to hire someone else. And now it's just like, actually, I can handle the workload, but actually I need to put in automations. And I love that. Precisely.

Martin Hýravý: I feel like this is going to be the mindset from nowadays onwards. And the faster we can start implementing this for every single individual, the better and faster and more flexible the teams are going to become.

Katie: Yeah, because you haven't got that delay either of, you know, advertising the job, then interviews, then actually hiring someone waiting for them to start and then training them up on, you know, everything that they need to know, the knowledge base, it's literally straight away, it can be solved. Absolutely.

Noel: Yeah. And they don't leave either. that's the worst but you train someone up and then they go

Martin Hýravý: yeah absolutely you you can then improve them and give them more capabilities so they only grow as you gain more skill so not that i would not want to work with people of course but you know we know

Katie: what you say

Martin Hýravý: absolutely i love working with people i love working in our office that make it's the best thing about this but like sometimes you need to think a bit more in terms of how i can actually grow this in the more effective way. So yeah.

Katie: Okay. I love that. And then so the flip side to that question, Martin, was like, why shouldn't you be using AI automations? And I think you kind of cover it by you were saying like start with automations first and then sprinkle in the AI magic later on once you've, you know, got the hang of building out those, you know, know, automations first.

Martin Hýravý: Yes, I would say I completely agree, because the automations themselves, when you learn how to build them as a groundwork without AI, you will, I believe, inevitably gain the skill and the perspective of where I can actually implement AI in the first place. So I feel like you need to have this initial skill of trying to build something that is rather simple to build, but it's going to have a really, really good impact. One thing that I always try to tell people whenever, for example, they ask me about AI agents. I get startups all the time into our startup program that their vision of make is like, I'm going to get in and I immediately want to start building AI agents. I'm like, amazing. Wow, AI agents, great thing. But hold your horses. Try to build simple automations, maybe with, without AI in the first place. And then later on, you can make, use them as tools to then build AI agents that might have more capabilities or just more functionality. But still, I really wouldn't skip that first step of building just normal workflows that are automated through make or even natively through the platforms.

Katie: No is literally nodding along as you would say in that about AI agents.

Noel: Yeah, everyone calls everything an agent, but there's the learning part as well, because I started off building AI automations with AI there already. And then it wasn't until we had one of our first customers, and they were like, I want this doing, all this information scraping, was like, wow, okay, am I actually going to have to go cold turkey and no AI? Wow, okay, you know, I have to figure this out manually. And even going through, like, the academy training would make, you know, I'm still learning stuff that's in there that I just haven't got around to using it because I'm kind of cheating the system by using AI. No, yeah. When really I should really be using the tools that are already there, I could already do that job for me.

Martin Hýravý: But regardless, this is a great mindset to have, like, where can I actually use AI to then maybe fast forward, not necessarily skip, maybe on paper? So, I mean, I feel like this is a great mindset to have when it comes to learning pretty much anything. So it, for me, for example, hasn't been that long ago when I was writing my bachelor's thesis. And I remember I was doing everything very manually. I was reading through every single research paper. And now I don't think that there is a single student that is reading the papers through and through. if you have notebook lm you have any any other lm there is no reason for you not to be using it i mean if it's super interesting absolutely read it out but as many of people before i had to read everything just to gain some insight whether it makes sense for me to read it so

Katie: yeah martin i'm i'm of the generation where i had to go to the physical university library and take a chunk of the journals that were like on my subject and sift through page by page to see if there was any articles relevant to like the essay that I wanted to write because it wasn't catalogued anywhere. It wasn't online. The university hadn't put that online. So I would sit there for hours going through all these journals. Oh, so like to for, for university, students now to just be able to like have that shortcut oh my god like I want to know what they're doing with all their time like I'm so jealous

Martin Hýravý: I mean I know exactly what they're doing but I mean the outcome is pretty much very similar but yeah yeah this is I would I would actually take a moment just to appreciate like how much progress we've made just in this area because it's it's immense how much time we're saving on this but also So on the flip side, I would maybe like to ask you, do you think that there is a negative side to this? That maybe people, when they're studying, they're sort of losing this, maybe determination to just sit down, do the research, have the ability to, like, get those books and dig through them and just have the determination to actually read through these things? Yeah,

Katie: I've actually noticed it when I've been with people who are younger than me, even like 10 years younger than me, their research skills are not the same as my research skills. So I didn't do anything to do with research at university. I did geography with landscape management. You know, so a lot of maps, you know, a lot of colouring in, you know, a lot of trips. But it was the fact that I had to go and look through books, look through journals, and find the information. Because, yes, we had Google, but it was nothing like Google is today. There was obviously absolutely no AI. And I feel like those skills have been like really great for me. throughout my life, you know, through, you know, different aspects to even like having my own business. And I have noticed, like, when I've been working with people younger than me, like, they don't quite have the same research. And it's almost like it's the patience to be able to kind of like, okay, let's look into this. Let's see what we can find out. And they kind of want an answer like within 30 seconds. Yes.

Martin Hýravý: Yes. I feel completely the same with this. And that really makes me wonder whether we're going to get to a point very soon where these skills and abilities are actually going to be the ones that are going to separate the ones that are going to be actually efficient and actually successful, even though we're all going to be using the same tools. because I feel like we might be like we're moving so fast that I feel like even for me as someone from a generation that is sort of growing up with these tools I feel like we might come to a point where we're just going to turn back and be like wow like these skills were essential and we really need to start re-implementing them because we've been moving so fast that we completely lost track of the fact that we're not you like sort of gardening these abilities I feel like.

Katie: They're kind of like skills that just aren't used anymore and kind of will be like phased out or they'll become like a like, you know, a special skill set that only a few people will hold. Right.

Martin Hýravý: I remember it wasn't really that long ago and I feel like this is still applicable. And one of the most sought after skills with professionals and doesn't matter if they're young professionals or mature professionals is critical thinking. And as far as I know, AI cannot really help you as much with critical thinking. It can to a certain point, I feel like, but in those critical moments, I feel like you cannot really turn into AI as much. So I still believe that the skills that AI cannot really assist you that much on are going to be the ones that are going to be separating the people that are going to be just the most successful and the most efficient.

Katie: Yeah. I love that. So many valid points and such an interesting conversation for sure. Yeah, I love that. So, Martin, going back to the startups that you help. So some businesses find it hard to even get started with automations because they don't know what's possible. So what would you say to those? business owners that just don't even know where to start with an automation, be it AI automation or just like starting off with, you know, an automation with no AI.

Noel: Yeah,

Martin Hýravý: so this is a very common area that a lot of startups come to our startup program. They might hear that automation is something that they should be implementing and they might not have the best perspective and best idea on what they can be actually automated. in the first place. So first, there are a few points that I always try to recommend on a very general point of view. And these are the ones where you should be looking into your current tech stack and the current tools that you are using. Then, based on these, try to think, where am I spending the most time per each day? What sort of tools, what sort of software am I spending most of my hours on? Is it email? Is it Excel? Is it something that has to do with coding? It always depends. It's very individual every single time. And that's why within the startup program and make, we really try to share and build this framework that is applicable to most or majority of the founders. Because inherently it's going to be different for everyone. That is going to start with. with make or with any automation platform. But a rule of thumb with this one would be always looking for repetition. If there is something that you do on a weekly basis that is recurring twice, three times or more, there is already a potential for automation. If there is a task or an action that has anything to do with transferring data, generating text, these are the hotspots for automation. So as much as we would love to help everyone individually, because I feel like this sort of consulting of giving them the idea of what they can be automating, we cannot feasibly do that for everyone. So trying to give them this sort of framework where they can think for themselves and gain this mindset that I've already touched upon earlier, it's something that we're really, really focus on as much as we can. Because, as I mentioned, I believe majority of the startups that join startup program that join make, they're not fully aware of what they can be doing in the first place. So we really try our best to help them gain this perspective and gain this mindset as fast as possible.

Katie: Yeah. Yeah, that totally makes sense. Yeah.

Noel: Yeah, you always kind of need to get the first one in as well before you then, you know, then they might click in their brain. and they think, hold on a minute, if I can do that with this bit, maybe then I can extend that and do something else. Absolutely. Just getting that one simple, easy winning first is quite key. I usually find.

Martin Hýravý: Yes, I totally agree on this. And there has been this one topic that we've recently discussed at No Code Week in Milan, which is sort of a meetup slash event for no-code enthusiasts in primarily central. Europe, it was something with the fact that a lot of these people are extreme experts with with no-code tools. And I feel like there is this notion between a lot of people that they feel like when somebody says no code, it also means no effort, which is not particularly the case, right? I mean, I guess it's easier for, or it is easier for most people, but it doesn't mean that it's going to come towards you automatically,

Noel: right?

Martin Hýravý: So there is still a bit of a learning curve and getting through those initial barriers and exploring and discovering what's possible with the platform itself. It's absolutely essential, I feel like.

Noel: Awesome. Awesome.

Katie: What do you wish AI or AI automations could do that it can't or edit? This is a great question.

Martin Hýravý: I feel like a lot of people start conversations based on this question and it's this is super interesting for me because realizing what sort of thing it's it's not already capable of doing is always super difficult because I feel like the discovery stage of where you are personally finding out what it can do is one of the best things I feel like of the journey of implementing AI but who I feel like I feel like this is something that we might not be fully realizing it but uh one thing that in my eyes separates any sort of artificial intelligence to actual humans is the emotional intelligence and in some sort of way trying to filter through the bias that a lot of people have because I was just listening to a podcast which was a diary of a CEO very popular podcast you probably know And there's been essentially this point where the prompts and the conversations that you have with AI are going to be very often based on confirmation bias. Because the fact that you have a conversation with AI doesn't necessarily mean that it's going to tell you the truth. I'm having a feeling that in a lot of conversations, it's sort of trying to. to predict or trying to put out what you want to hear in that particular conversation or in that particular topic. Yeah.

Katie: Like everything is great. Everything's, oh my gosh, that's, you know, fantastic. That's what it usually says back to you, isn't it?

Martin Hýravý: Absolutely. I feel like every single conversation, no matter the input that you give to the LLM, it always starts with an encouraging first sentence. And then it tries to give you things that might mostly appeal to you. Because, I mean, not sure if I can blame them in the first place because they want to make people feel good about using AI. If it was just brutally honest every single time, it would probably discourage a lot of people. And they were like, they would be like, oh my God, I'm never using this chaty pt again. It insulted me. It makes me feel stupid. But, I mean, that's true. If it's true, then you probably shouldn't be blaming it. But I don't think this is the case. So this is where I would probably try to not give as much props to AI when it comes to emotional intelligence. Because I don't think it can yet fully realize how to communicate with people when it comes to facts and stuff. truth, when in specific conversations.

Katie: Yeah, I often actually say to my marketing clients that if you use your, your emotions and your stories, AI can't do that. So that's why I encourage everyone to use their emotions or their storytelling within their content, within their marketing, because it's, you know, a step ahead of what AI can do at the moment.

Martin Hýravý: Absolutely. Yeah. Yeah. I'm also always trying to realize whenever I'm having a conversation with an LLM or whenever I'm maybe even trying to prompt AI agents to somehow input the fact that, okay, I might be biased. And if there is anything that I should be rethinking, if there's anything where I could have gaps, please point it out. If you're explicit with the prompt like this,

Katie: then I believe

Martin Hýravý: that there is a much higher chance that it's going to give you. something that's at least closer to the truth that will be beneficial for you in the first place. Yeah.

Katie: That's such a great idea today. Yeah.

Noel: It really sticks out, though, when AI actually tells you off, because I've only had it once. And straight away, I was like, wow, okay, it got sassy with me. It was chat GPT and I gave it an error code. Also, it was like some sort of error report. And I said, look, I'm having this problem. Can you help me fix it? Here's the output from the console, whatever. And it came straight back. It was like, it literally tells you the answer within the first two lines. I was like, yeah, all right. Can't dare. It's like, wow, okay. I haven't got time to read all of it. Yeah.

Katie: Yeah.

Noel: I really stuck out as soon as that happened. I was like, oh, yeah. Less of that, though.

Katie: Brilliant. I love that. Rotten, we would love to ask you some questions on Make, if that's okay.

Martin Hýravý: Absolutely. I mean, this is why I'm here.

Katie: Okay, let's do it.

Martin Hýravý: Let's jump in.

Noel: Should I jump on on these ones?

Martin Hýravý: No, please help me out. If I'm not going to be able to answer anything, please jump in and save me from the embarrassment. I hope my colleagues are not going to abandon me for this.

Noel: I'll leave you I'll end the call in a minute as soon as I'll ask the question.

Katie: Leave you to it.

Noel: So there's obviously like a real big push within the Make platform within, I'd say like the last six to eight months, especially since I said MakeWaves 24. Last, was that last November? I think it was. It was November,

Martin Hýravý: yeah.

Noel: Yeah. So there's been like a real big push towards AI like you guys have kind of noticed what people are used the platform for and you've provided some tools to help with the usage of AI I was just wondering is there going to be an even bigger push now like the text like going so fast is there going to be more things that makes going to bring in from the AI side of life?

Martin Hýravý: Yes so I believe it's been quite obvious that there's been a huge push towards AI ever since we had waves in November member. And to be completely transparent, this year we had a kickoff where we disclosed that the main topic of this year is going to be AI. So on one hand, there is the external push from the market and from the industry to focus on AI as much as we can. But also, on the other hand, something that people might not see in the first place is that even looking at our internal data and the platform usage, we can clearly see that I believe currently it's our second most used module is chat GPT. It's literally almost in every single scenario and people actually want to use it regardless of the fact whether we encourage them to use it or not. So the topic of and our focus on AI comes, I would say, both from our internal data and internal push and also the external push from the industry itself. So I would say it's been quite clear for us where the focus should be. And I feel like it's been pretty obvious for everyone that's looking at what we're currently working on, what sort of products we're launching. and essentially the experience that we want to give to the customers when it comes to using AI within any automations.

Noel: Yeah, sounds good. I think with the chat GPT is quite interesting one where everyone seems to be using that, but I always find in automations it's kind of not the best. So although everyone seems to use it, I always seem to use Claude because it always gives me the best output. So it gives me the best. So if it's like content creation, it gives me the best. best output. If it's for controlling an agent, it does the best job. So it's really interesting how most people use that. Whereas, yeah, for me, I forget that one. I move.

Martin Hýravý: I'll go to Claude. Absolutely understandable. Noel, I'm going to be fully transparent whenever I'm using LLMs for texting, not within my scenarios. And I'm not even taking my chances anymore. I'm literally taking the same message and I'm putting it into three different LLMs. And I'm I'm literally seeing which one gives me the best answer and then I'm continuing the conversation. I'm sorry. I mean,

Katie: it's available.

Martin Hýravý: You know, I mean, I just write the message. I copy paste it into Claude. I copy paste into Gemini and then I'm, you know, whichever one I like the most that I'm carrying on.

Noel: That's great.

Martin Hýravý: It's what works,

Noel: isn't it?

Katie: Yeah.

Martin Hýravý: I need to be very careful, though, because internally we use Gemini. So whenever there is something confidential, I of course only use Gemini.

Katie: Yeah.

Martin Hýravý: Yes. colleagues. I use Gemini. Internal data.

Katie: Martin is careful. Yes.

Martin Hýravý: Gemini only. Any data,

Katie: only Gemini.

Noel: Important disclaimer. We'll put that in description. Yes. But I guess also when it comes to using AI in your automations as well, like there's, I think that the biggest limiting factor with some people is their ability to do prompt engineering. So within an AI automation, say you want a specific output, you know, you've got to be really on your prompt engineering, you've got to give it examples and, you know, tell it what not to do as well as what to do. And I did notice on your AI agents, there's a little improved button within the system prompt. So I was just mucking about doing a bit of testing. I hit this improved button, and the prompt it gave was brilliant. So I was just wondering if there's anything coming up maybe, you know, or if there's got any sort of plans to help those people with prompt engineering. So they get the most out of their automation.

Martin Hýravý: No, well, that's been an amazing notice from your side. And I feel like when it comes to this topic in particular, there are a few areas that we need to disclose and that we need to look into because, for example, with AI agents, there could be a few, points of failure for you. So one point of failure could be the fact that you use wrong tools, you build the underlying scenarios wrongly, and then it just doesn't give you the output that you desire. But then there also might be the fact that you don't prompt it will. And based on the prompt that you give it, it just doesn't give you the thing that you would like to. And you can imagine that we really want to avoid this to the largest extent. So one thing that I've noticed generally with using make and platforms that have to do with AI is the fact that you want to help the users to use the platform in the best way possible and to assist them with almost every single step to help them to get the best outcome. Because we truly want to avoid having somebody banish our platform or stop using make for the fact that they cannot prompt properly, right? It can completely happen. And I can imagine that in a lot of cases, this could have happened with chat GPT. And if you don't prompt it well, if you don't give it the best instructions, it's just not going to give you the outcomes that you want. And we truly, truly want to avoid this to the largest extent. And this is the reason why this prompt assistance or even the AI chatbot that we have for errors, is there and it has a very good reason. So as I mentioned, it's really essential for us to be focusing on the assistance, ideally with AI. Yeah,

Noel: because it was kind of a sneaky feature that you added in. Because there's a couple of things. You guys are really sneaky when you add things in. So it was like, I want to try out a different agent for something we're building together. And I opened it up and then there was like a chat screen, we could talk to it before you even have to build an automation. I mean, that blew my mind straight away. I was like, where did that come from? And then I saw the improved button. I was like, really? I've really not looked at this for a week. It's going crazy.

Martin Hýravý: These sneaky features, they come every single week, and they even surprise me.

Noel: And I always need

Martin Hýravý: to dig in our product launch channel to try to find out, when did we actually launch it? Like, has it been, like, last week or, yeah? yesterday. So this, this happened to me literally over this weekend. And I was building an automation just on Saturday. And it was in the evening. And I noticed that we've added a new module. I'm not going to disclose yet, but we've added a new module. And I was like,

Noel: what is this? Like, when did we launch it?

Martin Hýravý: And then I realized we launched it on Thursday. It was just a few days before. And there's a, we also have a separate channel for just feedback on new modules. So I immediately went there, I was like, guys, like, I didn't even notice that this is happening. So I always want to get some feedback to the team. So, yeah, this is happening every time even for us internally.

Noel: So, yeah. Because you even snuck out one today, which is adding API keys to web hooks.

Martin Hýravý: Yes.

Noel: Yeah, yeah. So this is one of

Martin Hýravý: those.

Noel: I've spoken to some other guys there, and they were like, whoa, where's this come from? I was like, I don't know. But it's a great feature. Yeah. Awesome. With the speed of AI technology, how do you make plan to keep up with it? Because obviously, this year's been relentless. You know, the first six, seven months, you know, it's just been carnage. You know, like Open AI seem to be releasing new features every week at one point. It's going to be great content for a podcast. Yes. But for people like yourselves, you know, that's really hard to keep up with and keep providing things that users are going to find that, really helpful and useful and use those tools.

Martin Hýravý: Yeah, it's extremely challenging to keep up with such an immensely growing market all the time. And I mean, it's quite clear that there are tools coming out also literally every single week when it comes to AI automation. It's incredibly trendy. And we always need to firstly keep our eyes out for where the industry is going. But then also, we always need to stay focused on our customers. and listen to their feedback and not necessarily try to appeal to someone who our product might not be for in the first place. This is something that I keep seeing quite often and I'm having conversations with people who are fully non-technical to people that might have even 30 years of software engineering. I literally had a call with a person like this last week and it's always extremely interesting for me. to see how we are still able to build a product that is usable for both of these categories of users. On one side, we have these people that are just not technical at all, and they are happy that they can build very simple automation, and then we have people who need a lot of flexibility and that have the capabilities to build incredible, incredible systems and incredible workflows, and always trying to listen to what our main, base, of customers is looking for is absolutely critical. So on one hand, keeping our eyes out on where the industry is going, for example, like with AI, it's quite obvious, AI agents, massive trend. I feel like before we launched AI agents, everybody knew that we're going to go this way.

Noel: I think it's been clear to everyone.

Martin Hýravý: So it was just a matter of time. And now it's just up to us to build on top of it and to stay full. focused as well. This is actually from the words of Fabian, our CEO, that what we currently need is focused. And I can completely agree because with such an immensely growing industry, there are so many different areas where you can get distracted and try to build something that might not even have as much value for the majority of the users that we're trying to build our product for. So these are the points that I would always try to keep in mind. And I feel like so far we've been doing a great job and I also have a very strong trust within the team that we have at make. I see what people are in our leadership team. I see what people we're hiring for the key roles. I have the privilege to sit in next to the CEO office and so I know them personally really well and I see what they're working on and I'm very confident in the path that we're going, so.

Noel: Sounds good, yeah. We just hand you a microphone so you can put it under his door for us so we can get the insert.

Martin Hýravý: All right.

Noel: That's a deal.

Katie: I think that goes against Fabian's trust. Oh, previously.

Noel: Oh, yeah.

Katie: Maybe not there. Right. Yeah, he's all about trust. And I don't think that is really in that remit. No.

Noel: We'll have to wait until the next Make Waves event.

Katie: Do what's going

Noel: on. Yeah.

Katie: We'll just follow him about.

Noel: Yeah, absolutely, yeah. It's really interesting where you say about the feedback because with all platforms I've used so far, Make is probably the only one that actually responds to feedback. And it's not just like an automation. I submitted some feedback about the grid just before it got released to the general user. And I had two guys straight away, straight in my inbox. Oh, my God, thank you so much for this feedback. how what can we do how can it be better what should it look like and i was like wow okay you know that was within like a as soon as they got in that morning nine o'clock bang email straight out so yeah it's it's incredible knowing that there's a team like that we didn't make and that sort of um i don't know that sort of type of people in there that just want to do the best that's yeah

Katie: like they really care

Noel: they do yeah yeah

Martin Hýravý: i'm super happy to hear that and especially with Newly launched products like Grid, I feel like it's been super important for us to listen to what the people have to say about it. Because in my eyes, actually, Grid is currently going to be one of our key products. For me, Grid has been incredible since the day we had it available internally. So in one of the videos that I shared on my LinkedIn, I mentioned that for me, I've been using Grid for over six months right now because it's been available internally for quite a long time. and managing our startup program with, I believe we have over 40 different scenarios that are running the program from a central database. It's been so, so helpful for me when I have to troubleshoot to see where the data is flowing. I feel like this is something that might be slightly overshadowed by our AI agents, but I don't think it should be. And I'm very happy to hear that your experience with the feedback to this particular product has been great. Oh, it's excellent. Amazing.

Noel: They must have me on a watch list.

Katie: They probably do know for all the wrong reasons.

Noel: We need to make

Martin Hýravý: sure that you're on the watch list all the time.

Katie: Watch out mentioned. Is that all your questions, Tom?

Noel: Yeah, I mean, we could go on for so much longer. I got so many more questions, but, you know, yeah, we'll have to, you know, see if you ever wanted to come back on again, in the future with new features and things come out. That'd be awesome to have another chat. But, yeah, I've loved it. I've loved hearing everything you've had to say. I think so, yeah, thoroughly enjoyed it. I don't think one else has as well.

Martin Hýravý: Noel, with our current pace, I feel like we could do this podcast in the next two weeks and we're going to have much more topics to talk about. So I can do a list. I can look into the product alphas that we have ongoing and then we can discuss it. And, yeah, there would be a lot of topics to talk about, of course. With such a comprehensive platform, it's always, always something to talk about.

Noel: Awesome.

Katie: Well, thank you so much, Martin, for joining us on this week's podcast. It's been an absolute pleasure to talk with you. And I think I can say that for, you know, myself and Noel.

Noel: Oh, yeah.

Katie: we will put your details below Martin so like people can go and check you out on LinkedIn and don't forget if people want to join our free LinkedIn group then you are more than welcome to we will put all the details for that below as well as our website and we will catch you on another episode very soon