Manuel Kanah on From Developer to CTO: Scaling Systems and Navigating the AI Revolution | Ep.282

Manuel Kanah's Journey: From High School Coder to CTO & Company Exit Welcome to Secret Experts, where hidden knowledge, insider insights, and the truth that shape real power. Speaker 2 Hey everyone, welcome to the Secret Expert podcast where we showcase it in terms of experts so you and I can learn from them guys, definitely, I'm happy to be here with you. And today we are with Manuel Kanem. Manuel, how's your day going? Speaker 3 Very good indeed. Speaker 4 So thank you for asking. Speaker 2 And thank you for being here again with us. And of course, without you, I think this podcast wouldn't happen. But of course, once for our opening or opening remarks for those who do not know you, Manuel, who is Manuel Connor and maybe you can share us a little bit more about yourself. Speaker 5 Absolutely so. Speaker 4 I've been passionate about. Speaker 3 Technology for a very long. Speaker 4 Time. Speaker 5 Since I was 12. Speaker 4 So I don't know 3345 ages ago and. Speaker 5 Basically I started to call. Speaker 3 Professionally for. Speaker 4 Web-based application or website in 1999, the last century and I've been and since then. Basically I've been developing for a web. In 2007 I started. Speaker 5 To work for SAS. Speaker 4 Company and more. Speaker 5 Specifically with startups. Speaker 4 And that was kind of revealing because I said, Oh my God, I literally found myself in the job and I started to really love my job even even further. And basically since then I was basically kind of leading the technologies and I've been CTO in a few different companies. At some point I moved to the UK and starting to. Speaker 3 Work more. Speaker 4 Internationally and basically last. Speaker 3 Year as a CTOI have. Speaker 4 Been doing an exit for from UK selling the company. Speaker 5 To AUS based. Speaker 4 Company that was. Speaker 3 Very, very interesting. Speaker 4 In so many ways. Speaker 2 Wow, you actually have a great background. Sorry, I think a lot of our audience would be motivated with your story. Then again, I I want to ask and well what I know that you started young, what originally pulled you into the software engineering and technology in your overall idea how you came up or maybe land up to this kind of industry? Speaker 4 That was kind of a I I I landed into coding in a in a very. Speaker 5 Strange way. Speaker 4 So when I was into in my secondary school, 1. Speaker 3 Professor actually asked us or. Speaker 5 Actually. Speaker 4 Shows how to to code and basically I end up for coding the solutions of my mathematical problem or my geometrical problem instead of doing the homework I was actually coding or solving those issues. Speaker 3 That created this mindset where? Speaker 5 You always have to. Speaker 4 Generalize and make the codes. Speaker 5 As as. Speaker 3 Intelligent as possible for for. Speaker 5 You to solve your problems. Speaker 4 At some point and then during my high school actually attended an artist school. So even if I was holding and doing things in background, my my main focus was drawing and sculpturing and doing this kind of stuff. And later on when I was attended attending architecture university then I just found myself working in. Speaker 5 IT so while I was. Speaker 4 Studying I was working in the IT and I was one of the few people in Milan, Italy that was able to create internal. Speaker 3 Networks. Speaker 4 And was able to create Internet connections and work on Internet and creating websites and so on and so forth. And at some point working with a few companies here in Milan, one one of the biggest actually, they told me. Speaker 5 Would you like to? Speaker 4 Join us in our journey to create a web company and I said. Speaker 5 Absolutely. So I joined. Speaker 3 There. Speaker 4 And I started to code. Speaker 5 Like basically 24/7. Speaker 3 And I did that for probably 3-4 years where I was basically. Speaker 4 Coding all the time, like evening, morning, early morning, over the weekend and so on. And I've learned so much. And I've been. Speaker 5 Actually glad I took this. That was so, let's say, so braved. Speaker 3 To leave everything behind and. Speaker 4 Say no, this is my career. This is. Speaker 5 What I love this is. Speaker 4 What I'm going to? Speaker 3 Do even if my university. Speaker 4 And my high school was not really related to what I was doing. Speaker 5 But I was very good at it, so I just. Speaker 4 Took the chance and at some point nothing would like, just my expertise and my knowledge. Speaker 5 Stood up. Speaker 3 Above other people. Speaker 4 And I been hiring like people been hiring myself. Speaker 3 For CTL position. Speaker 4 And so on and so forth. Like leading teams. Mastering the Shift: Developing Leadership Skills Beyond Technical Expertise And then at some point, if I need to be honest, I found myself being a. Speaker 3 Leader where my. Speaker 4 Expertise was not matching the leadership because being a technologist is not the same of being a leader, so I needed to. Speaker 5 Literally study and looking into new ways to to. Speaker 4 Bring. Speaker 5 Value as a as a. Speaker 3 Leader as an engineer. Speaker 4 Into a deaf team and that. Speaker 5 Was a a a big? Speaker 4 Challenge of mine. Speaker 5 Because I was always. Speaker 3 Being a very. Speaker 4 Technical guy, but when I I needed to become. Speaker 3 More like a leader, more like a person. Speaker 5 That is actually able to. Speaker 3 To interact personally and. Speaker 4 Being able to mentor people and physically. Speaker 3 Make other people thrive in their career. Speaker 4 That was a different challenge. Speaker 2 And I think many long term term technology leaders begin with curiosity and about solving problems and building the systems itself. So you mentioned that leadership. I know that it's unexpected. In any case, it did it come to your mind that you always know you'd move into leadership. Speaker 4 Yeah, absolutely. Like moving into leadership is mine might be. Speaker 3 A very different skill set. Speaker 5 Because. Speaker 4 As you are a technologist. Speaker 3 Or you are a developer, you are a software engineer, you are a software architect or whatever. That right? Or a tech. Speaker 4 Lead Most of the time we have this relationship. Speaker 3 Where you really need to. Speaker 4 Know you need to know. Speaker 3 Your. Speaker 4 Domain you need to know. Speaker 5 What to do with? Speaker 4 Technology you need to know what. Speaker 5 To do if you. Speaker 4 Want to deploy something if you want to create values in the company from a technical perspective, but then at some point someone I don't know. Speaker 3 Push you forward and you. Speaker 4 Become a leader and then suddenly you find. Speaker 3 Yourself. Speaker 5 Leading. Speaker 3 People, but the skill sets. Speaker 5 As a? As a. Speaker 4 Solution Architect as a software. Speaker 3 Engineer as a. Speaker 5 As a tech lead. Speaker 4 Is totally different from being a leader. Speaker 3 Because when you are a leader. Speaker 5 Focus is. Speaker 4 I mean. Speaker 3 If you are a software. Speaker 4 Leader like a team leader. Speaker 3 For. Speaker 4 A team of software engineers. Then obviously you need to know. I mean, technology should. Speaker 5 Supposed to be your bread as well as. Speaker 4 You need to understand how to deal with. Speaker 5 People how to deal with. Speaker 4 I don't know, difficult situation how to deal with people not performing well. Speaker 3 Or even I don't know. Speaker 4 Trying to make digestible the fact that they need to train they. Speaker 3 Need to learn more or they need? Speaker 4 To change what I've been doing and. Speaker 3 So far because your. Speaker 4 Vision is different from what they have and even having nice fights where and with nice fights I mean smiling and keep smiling even if someone is going against you and. Speaker 5 This is a skip sets. Speaker 4 Totally different from from and. Speaker 2 It actually makes sense. So over the 25 years in time, in your experience and of course in your perspective, what what changes turn out the most like what shifts change the industry the most? The Three Revolutions: How Internet, Cloud, and AI Reshaped the Tech Industry I guess the ability to create value, I mean, we've been through at least two revolutions, OK, in the last. Speaker 3 25 years we're. Speaker 5 Actually, probably. Let's say. Speaker 4 2 1/2 because the Internet came out a little. Speaker 3 Bit earlier, but let's say. Speaker 4 In in the last. Speaker 3 3030 years we've seen. Speaker 4 Internet coming and then that changes everything and created a humongous amount of opportunities, not just. Speaker 3 For. Speaker 4 Developers themselves, but for everyone and being able to be, to be present everywhere in the world, just being, I don't know, creating your own content. Speaker 3 At the very. Speaker 4 Beginning it was maybe a blog and then became, I don't know, the blog and then became something else, right? And then obviously Instagram and TikTok and all the. Speaker 3 Other in stuff, but let's say the first. Speaker 4 Revolution was Internet by itself. The second one was the cloud because I see myself like back in time when I was working basically next to my to my. Speaker 5 Server far I was. Speaker 4 Actually literally working and in background I had this sound of all the fun like running all day long. Speaker 3 But with the server just. Speaker 4 Next to me. So if something was happening, that was. Speaker 3 Actually go there. Speaker 4 Connect a monitor, connect a keyboard and then look into. Speaker 3 To the server myself. Speaker 4 And then going into, I don't know. Speaker 3 Server farms where there was real data. Speaker 4 Centers where you could go. Speaker 3 And print your your rock and. Speaker 4 Put your blades into it. And then the cloud arrived and suddenly everything became like I don't know I need. Speaker 3 100 servers. Speaker 4 Today and tomorrow I'm going to shut down my company and that's it. You just you don't. Speaker 5 Need to provide to basically. Speaker 4 Buy any blaze and you need to to renew any blaze and you need to update any. Speaker 3 Server and you. Speaker 4 Don't need to do anything. Speaker 5 You just do that. Speaker 4 And at some point also became. I don't know. Speaker 3 Infrastructure service. Speaker 4 But that's not very revolutionary. Speaker 5 At all but. Speaker 4 That became even easier, like all the the provisioning. Speaker 3 Of all your hardware or virtual. Speaker 4 Hardware became so simple that right now, I mean it's a no brainer. Speaker 5 To to go. Speaker 4 Through that and the third one is. Speaker 5 AI. So AI probably is. Speaker 4 I don't think he's the. Speaker 5 Biggest but is is. Speaker 4 Probably at the same level of the Internet revolution. Cloud is just in the middle. Make everything simpler but. Speaker 5 Has been a revolution itself. Speaker 3 Where? Speaker 5 AI probably is at the. Speaker 4 Same level of the Internet because AI is somehow creating new jobs and removing it. Speaker 5 A few others jobs. Speaker 4 In the end it was probably the same, creating new jobs and removing few other. Speaker 5 Jobs because. Speaker 3 Before you were. Speaker 4 Creating, I don't know, say. Speaker 3 PDFs or Flyers or stuff like. Speaker 4 That and suddenly everyone that was printing Flyers and so on became like, yeah, you just need to have a a. Speaker 5 Website. Speaker 4 And that's it. Like no Flyers at all, No people printing, printing and tearing down. Speaker 3 Trees for for Flyers. Speaker 2 Yeah, you can definitely see that. I think technology evolves rapidly and also first engineers so many years to continuously adapt. As you've mentioned earlier, back then you actually need to like create a fires and right now you just need to create a website for them to know who you are and of course your service. But then again, since it has evolved, in your perspective, how has engineering culture like culture evolved and what skills matter most today than before? Speaker 3 The culture of. Speaker 4 Software engineer and now is probably the most valuable thing you can you can have. Speaker 5 That's why I see. Speaker 3 Junior people actually struggling to. Speaker 4 Not maybe to find a job. Speaker 3 But struggling overall because. Speaker 4 As a navigated. Speaker 3 Software engineer and CTO and. Speaker 4 Tech lead and. Speaker 5 XAW. Speaker 4 F solution architect and so on. I mean. Speaker 3 I understand how everything should be created right? Even if. Speaker 4 I'm not creating myself. I totally understand what kind of constraints you should have. What kind of? Speaker 3 Architecture you. Speaker 4 Should have in place. Speaker 5 For you to be able. Speaker 3 To create. Speaker 4 Something that is going to be maintainable and it's going to be scalable and it's going to be, I don't know, resilient and reliable and available and so on and so forth. And this expertise comes with I don't know you're. Speaker 5 On the field expertise AI. Speaker 4 Can expedite and can can. Speaker 3 Give you access. Speaker 5 To a. Speaker 4 Lot of information, but if you. Speaker 3 Don't have the expertise? Speaker 4 To understand that, then it's pretty much useless. Speaker 2 It's like a thing, just just a quick side note or just a quick comment. It's like reading the Asian text. Speaker 4 Exactly, exactly, exactly. It's like reading the ancient test, like it's nice. I can barely get that. I mean to study that it's a completely different. Speaker 5 Story as well as. Speaker 4 You know, sometimes you can. Speaker 3 Hear about developers going. Speaker 4 Annex because they're using AI. I'm probably going 15X right now. Speaker 3 I can work on. Speaker 4 Different projects at the same time I can do. Speaker 3 Many things here and there I can even refactor big. Speaker 5 Data sets or this for? Speaker 4 Big. Speaker 5 Based based just by. Speaker 4 Going there, run analysis, moving this analysis back and forth between a new project and a new and another one. And basically I can even start to avoid prompting because I can ask the AI to prompt based on previous previous. Speaker 3 Architecture or previous projects. Speaker 4 And then create new 1 based on the old one. That's an interesting, that's an interesting era to live into. Unfortunately, I mean, I have a son and it took a a Python course last year and it was like, oh, that's, that's incredible what you can do. Speaker 5 With with. Speaker 4 Python And it's it's amazing and blah blah blah and basically and it. Speaker 5 Was about to tell. Speaker 4 Me like I'm going to do the. Speaker 3 Developer like you in the. Speaker 4 Future not like. Speaker 3 As a as a career. Speaker 4 And I was like. Speaker 5 Yeah, if you if you. Speaker 4 Want to why not but now if my son will tell me that so I will say no, you should not just spend any time on that because at some point the. Speaker 5 Code. Literally the code. Speaker 4 Is not going to have any value. Speaker 5 Because AI will be able to produce codes as. Speaker 4 There's not two more and and as everyone can produce. Speaker 5 Code the code. Speaker 4 Is not going to have value. What is going to have value is going to be. The idea behind it is going to be the how you implement, how you deploy, how do you make this code maintainable and reliable and resilient and scalable and so on and so. Speaker 3 Forth and the overall architecture. Speaker 5 So I guess the AI. Speaker 4 Can substitute the software engineer. Can substitute the software developer. Cannot substitute a solution. Architect the solution. Speaker 3 Architect is a, is a. Speaker 4 Let's say it's a professional that will be. Speaker 3 There for I can see. Speaker 4 For let's say a long time still. Why Raw Code Loses Value: Data Structures and Architecture as AI Differentiators And it actually makes because language and AI right now is definitely booming changing the, if you're considered it the playground of most software engineering team. And as you mentioned, it's about like maintaining instead of like doing the code and making the code more valuable. But then again, maybe you're gonna say something. Very sorry. Speaker 5 Probably just. Speaker 3 Out of your last words. Speaker 4 But right now I'm focusing. Speaker 3 More on the data. Speaker 5 Structure. Speaker 4 So most of the time most of the functionalizers you can provide to clients or you can provide. Speaker 5 To services. Speaker 4 Are based on your data. Speaker 5 Structure if your data structure. Speaker 3 Allows. Speaker 4 Certain functionalities then you are going to be able to provide this functionality. So your focus is not about creating an. Speaker 5 API that will will least. Speaker 3 I don't know. Speaker 5 Your to do. Speaker 4 'S or will least something. Speaker 5 Or will create the legal. Speaker 4 Algorithm that will intersect. Speaker 5 To arrays of whatever, probably the value right now. Speaker 3 Is in the data structure. Speaker 4 And so you can create code based on. Speaker 3 The structure. Speaker 4 Is mainly my focus. In fact, I was having a conversation. Speaker 3 The other day where I was suggesting that. Speaker 4 The value of the company is actually the. Speaker 5 Value of the data that you. Speaker 4 That you own and you. Speaker 3 Produce because the data are. Speaker 4 Mainly information and you know the. Speaker 3 Power is in the information. Speaker 5 So if you if you. Speaker 4 Want information? You own the power. So basically again, the code is not going to have value, the implementation will. Speaker 5 Have value. The data will have value. Speaker 4 And so the idea behind the data there, you're going to. Speaker 5 Collect the focus supposed to be. Speaker 4 On the data structure and software architectural. Speaker 5 Let's say as a solution. Speaker 3 Architect all the rest. Speaker 5 Will lose completely the value. Speaker 4 In a couple of years, there's not going to be value in there, yeah. Cutting AWS Costs by $55K: Performance Optimization at Scale Totally makes sense. So again, Manuel from we're going to transition to our next section of podcast I think from engineering foundation into scaling technology and I know that you've architected systems handling millions of requests per minute. What changes when when systems reach that kind of scale? Speaker 4 And that's interesting, I. Speaker 3 Gave a speech for the. Speaker 4 Nod JDS make up in London. Speaker 3 When I was working for the company where we were delivering 4 million requests per. Speaker 4 Minute, which is a humongous amount of requests and. Speaker 5 And basically I would say. Speaker 4 Performance is probably the biggest concern and it's not like. Speaker 5 Because you. Speaker 4 Want to perform very. Speaker 5 Well, as you have a. Speaker 3 4 million requests per minute. Speaker 4 Because you can might have 4 million requests per minute. Every request can take, I don't know, half a second and then you can say yes, but I don't. Speaker 3 Care, and I will. Speaker 4 Scaling definitely on AWS using thousands and thousands of instances and that's I mean. Speaker 5 That could be an approach. Speaker 3 However. Speaker 5 When you get to that. Speaker 4 Point the cost became insane OK so when I. Speaker 5 Started to to add this. Speaker 4 Kind of volume. The problem was AWS was costing me probably $136,000 a month. OK and that was insane. Was like more than my salary per month in AWS. Speaker 5 So I said OK. Speaker 4 That's fine how we can? Speaker 3 Improve or how we can. Speaker 4 How we can cut some costs and the idea? Speaker 5 Was if the code. Speaker 4 Is more performant then you're going to save CPU, and if you just say CPU you will save money. Speaker 5 Because obviously you pay. Speaker 3 For your CPUs. Speaker 4 And so on and so forth. And if you have to compute less. Speaker 3 And even if your if your response. Speaker 4 Will come back in 2. Speaker 3 Milliseconds rather. Speaker 4 Than 200 milliseconds then. Speaker 3 It means. Speaker 4 That you can with the same instance you can provide 100 times the requests. So my focus became became on optimization and I started to optimize everything that was. Speaker 5 Probably 1. Speaker 4 One of the most interesting things I've ever done. Speaker 5 But as a as I. Speaker 4 Started to code in node JS at that point like that was. Speaker 3 Literally a period where I. Speaker 4 I moved from PHP to node JS and I said OK node JS is. Speaker 3 Performing very well. However, the. Speaker 4 Same codes can be implemented in 200 different ways in node JS where? Speaker 5 PHP is like basically very straightforward. Speaker 4 There's a single. Speaker 5 Way you do that, that's it. Speaker 4 You can be object oriented or I don't know, procedural. Speaker 3 Or. Speaker 4 I mean or it's not functional programming right now you can even use for functional programming in node JS. You can literally implement the same the same coding 25 different time in different ways. Speaker 5 So I started to read the code of. Speaker 4 The V8 engine of node JS to understand how to write the code to make the code more performant and basically reduce. Speaker 5 The cost because I was. Speaker 4 Using less CPU. Speaker 5 By the way. Speaker 3 After around of. Speaker 4 A month and a half working basically day in and day out on optimization, cost optimization and so on and so. Speaker 5 Forth, I cut the costs by 60. Speaker 4 5000 No. Speaker 5 A little bit less 50. Speaker 4 5000. Speaker 5 Dollars a month, which was basically 6. Speaker 4 Hundred 600,000. Speaker 3 Dollars a year, I mean. Speaker 4 More than half a median. I didn't get any of them in my salary. Speaker 3 By the way. Speaker 5 I didn't get the bonus for that. Speaker 4 I still, I still regret that. Yeah, I know. I could be like, yeah, just give me. Speaker 3 I don't know 50. Speaker 4 Percent of this, or even 30 percent, 20% doesn't matter. That was. Speaker 5 A big. Speaker 4 That would be a big bonus anyway. Speaker 3 Just working with the. Speaker 4 With the data and then working with how to optimize the data? How to? Speaker 5 Use data lights. How to cut the costs of. Speaker 3 Infrastructure by. Speaker 4 Using the spot distances that could die and. Speaker 3 And to be restored. Speaker 4 And it's any point in time. Speaker 5 Anyway, because of the cost. Speaker 4 Of the spot distances. Speaker 5 I was able to reduce the cost by just because of that. Speaker 4 By 20% and that was an hybrid situation. Speaker 3 Where I had reserve distances. Speaker 4 On demand distances and spot distances all working at the same time and I need. Speaker 5 To call it that because the fleet. Speaker 4 Of the outer scaling groups were not able to provide an hybrid situation between spot distances and on demand and reserve distances. Right now, probably the that. Speaker 5 Will be a little bit different because you would work. Speaker 3 On your. Speaker 5 How does it call? Speaker 4 Based on the provisioning of the compute. Speaker 3 Power. Speaker 4 Which has a name but it doesn't come to my mind then and then optimizing by milliseconds of fuel micro services that I'll save thousands. Speaker 5 Of dollars. Literally I. Speaker 4 Was able to improve. Speaker 3 The performance of the service by 4-5 milliseconds per request and overall I could. Speaker 4 Cut up $3000 of costs in terms of instances over a month because reducing the CPU utilization and so on and so. Speaker 5 Forth actually let ours reduce a lot of a lot of computation. Speaker 4 That being said, at some point. Speaker 3 The code was performing. Speaker 4 So well. Speaker 5 That I actually separated the. Speaker 4 Bandwidth of my in AI. Speaker 3 So my network card. Speaker 4 And and that was very funny. Speaker 5 Because I was like, yeah. Speaker 4 Everything is working so nicely and the CPU is fine. Why I cannot get the data? Speaker 5 Because basically I was, everything was. Speaker 4 Performing so well that the problem became the network and not. Speaker 5 The CPU. Speaker 4 Or there are many more and then I need to? Speaker 5 Scale. Speaker 2 It's like a problem they you definitely dream of if you think about, Yeah. Speaker 4 Absolutely no. Yeah, nothing. And then I needed. Speaker 5 To to scale a little bit the. Speaker 4 That infrastructure just to. Speaker 5 Avoid to have this. Speaker 4 Bottleneck later on, but that that was an interesting problem to have. Manuel's Growth Plan: Mentoring Tech Professionals for Long-Term Career Success But then again, Emmanuel, right now let's talk about what you're doing. What are you aiming right now in this current age or in, in this, in, in this industry? What's your service right now that you are you are trying to offer help to other? Speaker 5 People, basically. Speaker 4 Right now and that. Speaker 5 Could like to help other. Speaker 4 People, that's an interesting question. Speaker 3 As to help other people. Speaker 4 I am right now. Speaker 3 Delivering this mentoring service for the people I'm. Speaker 4 Working with which I call. Speaker 5 The growth. Speaker 4 Plan. The growth plan is basically based on the idea that even if. Speaker 3 You work with me. Speaker 4 We are not going to. Speaker 3 Work together forever and your career. Speaker 5 Probably will last 40 years. Speaker 3 So I mean. Speaker 4 I'm not going to work. Speaker 3 For for another 40 years. Speaker 4 Exactly for that long, so at the end I could. Speaker 5 Say that. Speaker 4 We need to work together. Speaker 3 For. Speaker 5 Yourself to be able to. Speaker 4 Improve while we are working together so you can have a. Speaker 3 Better career later on. Speaker 5 We start. Speaker 4 On having conversation about. Speaker 5 What you like What? Speaker 4 Would you like to do? And so on and so forth. And at some point we end up creating a job spec for. I mean, you are going to write. Speaker 5 The job spec. Speaker 4 For yourself in a near time and then basically by writing your own jobs back, you can see that I don't know you like. Speaker 5 To do. Speaker 4 Something right now, and you'll probably want to concentrate your focus on learning more about I don't know. Speaker 5 Cloud or AI or or architecture or or whatever. Speaker 4 Else and then basically we start working every week on on what could make. Speaker 3 You a better developer what can? Speaker 4 Make you a, let's say, a better yourself. Speaker 3 In the future in your. Speaker 4 Career, and this doesn't have to be. Speaker 5 Necessarily related to the job. Speaker 4 You're doing right now. Speaker 5 But it has to be. Speaker 4 Something that can help can propel. Speaker 3 Your career looking forward. Speaker 4 That being said right now. Speaker 5 As a? As a. Speaker 4 CTOA obviously helping the business. Speaker 3 Striving. Speaker 4 Because at the end of the. Speaker 5 Day Let's say tech is just a facilitator of the. Speaker 4 Business and the day you understand that. Speaker 3 Is going to be. Speaker 4 Very revealing because I mean, you can do do amazing technologies, but at the end of the day, if you don't produce value for the business, there's no. Speaker 5 Way for you to produce. Speaker 4 Value. I mean, there's no way for. Speaker 5 You to do technology at all. Speaker 2 And you've also, you've mentioned you have a program. What does it look like? Let's say for example, I am, I'm a new person, maybe I want to be your client. What should I expect? Like in in 30 days to 90 days, what result should I get? Or maybe what should I expect in this program? Speaker 4 You mean the mentoring 1? Speaker 3 Or as a. Speaker 2 The mentoring 1 And of course maybe if you can share your other services as well, that would be great. Speaker 4 OK. But the mentoring 1 is kind of interesting because you might in 90 days. Speaker 5 You will have a better. Speaker 4 Vision on what you. Speaker 5 Supposed to study what could be your goals? Speaker 4 How you can achieve your goals and what kind of technologies are needed Most of the time, the growth plan can go I had. Speaker 3 For. Speaker 4 I don't know, even like many more months, I mean. Speaker 3 Up to 20 years, a couple of years. Speaker 4 And at some point I also found people, maybe in the second. Speaker 3 Year. Speaker 4 Just coming for for random topics so I could see people jumping in the cold. Speaker 3 Where they say yeah I. Speaker 4 Don't want to have a plan anymore, I just want. Speaker 5 To like troll topics. Speaker 4 To yourself and we can. Speaker 5 Just discuss topic or. Speaker 4 Something I'm facing in my day-to-day job, and I would like to have a second pair of eyes on that, or a second ideas or another point of view on on that. And we start discussing how you can approach problems, how you can approach different solutions, or why a solution is better than another one. Speaker 3 Or we try to. Speaker 4 Validate your ideas by finding different solution and comparing with. Speaker 5 What you. Speaker 4 Actually end up with and that's an interesting. Speaker 5 Approach is basically open. Speaker 4 Someone mind on on the opportunities you have because sometimes you don't know technologies. Speaker 5 By themselves or you? Speaker 4 Think I don't know, I don't know. Speaker 5 How to scale? Speaker 4 This specific technology or I don't know how to. Speaker 5 Scale. Speaker 3 My service or I have a. Speaker 4 Client that has to collect petabyte of data and I don't know how to. Speaker 3 Query this data right? Speaker 4 And then there are all different practices and different. Speaker 5 Approaches to the data to. Speaker 3 Software scalability. Speaker 4 Asynchronous computation or synchronous computation or even distributed system? Speaker 3 Where I don't know, I could say messages are not. Speaker 5 Used a lot people. Speaker 4 Now tend to go more in event driven architecture more than distributed system they still find fascinating. Speaker 5 How they could be? Speaker 4 Different in so many ways. And then we go through different type of architecture or different type of paradigms in programming and so on and so forth. So it can be. Speaker 3 Literally very vast. Speaker 4 I've been having people that needed to create. Speaker 3 Leadership to ship skills. Speaker 4 And then? Speaker 5 I started to suggest. Speaker 4 Readings and we went through some of the. Speaker 3 Books they read because I. Speaker 4 Read myself before and we started to look into I don't know big leaders and how. Speaker 5 You treat people. Speaker 3 And how the people, people's brain works. Speaker 4 Differently because you can be. Speaker 5 More like a solo. Speaker 3 Player or. Speaker 4 You can be a team player. Speaker 3 Or you are more creative than. Speaker 5 Logic. Speaker 4 Or you are more logic than creative and so you need to. Speaker 5 Basically, squeeze the best out of the people. Speaker 4 Next to you. Speaker 3 If you are a leader. Speaker 4 And you need to understand, is this guy more? Speaker 3 Creative or or a solo? Speaker 5 Player if it's creative. Speaker 4 And a solo player, then probably you want to go to this guy. Speaker 3 And I don't know. Speaker 4 Ask questions and ask different approaches to issues. Speaker 3 Or. Speaker 4 Something else? Speaker 3 Where if you are. Speaker 4 A team player, probably. I don't know. You're going to end up being a team leader at some point probably, so you need to understand and leverage everyone's power when you. Speaker 3 Are a leader. Speaker 4 And probably be surrounded by the people more interesting than you. Speaker 5 Because. Speaker 3 If you are the. Speaker 4 Smartest people in the room. You are in the wrong. Speaker 2 Room definitely. I have heard it from a lot of people from this podcast. If you're surrounded by people or you're the one that's smartest in the room, because in any case, the the people that you're in or the environment, it actually helps you moving forward. If you want to maybe progress everyday learning is a big thing and giving like feedbacks from one another. I'm having like that kind of people surrounding you. It definitely helps you. But then again, let me just ask you what what is mindset should what? What idea mindset should your client have when they work with you, may it be into mentoring or your other services? The Essential Mindset: Why Continuous Learning Fuels a Lasting Tech Career I've been mentoring myself. Speaker 5 OK, it's like when you go to. Speaker 4 A therapist, actually. Speaker 5 You. Speaker 3 Actually. Speaker 4 Realize you need help. Speaker 5 And it's not. Speaker 4 Because you need help. Because I don't know, you struggle at something. It's because you need help. Speaker 5 Because you want to be. Speaker 4 I don't know healthier than before or you want to be smarter than. Speaker 3 Before or you are just. Speaker 4 Curious and you want to satisfy. Speaker 5 Your curiosity, right? Speaker 4 Or you want to understand? Speaker 3 What there is? Speaker 4 I don't know, behind the wall. Speaker 3 Or. Speaker 4 Behind the window. Speaker 5 Because basically by. Speaker 3 Learning you understand. Speaker 5 What you have to learn? Speaker 3 Right. Speaker 4 Every time I'm. Speaker 3 Learning. It's not. I'm learning because. Speaker 4 I want to be the best. Speaker 3 One but I'm learning because. Speaker 4 I understand what I have to learn next when you. Speaker 5 Like today. Literally today this. Speaker 4 Morning I was looking into how to analyze big massive piece of text. Speaker 5 With the AI. Speaker 4 And then I started to look into, I don't know approaches and semantic approaches and talking approaches and how you can chunk text and how you can indexes all of them and now you can refer to text. Speaker 3 Here and there. Speaker 4 And at the end of the day, how you can? Speaker 3 Create the vector data lake. Speaker 4 And just so you can. Speaker 5 Query across terabytes of text. Speaker 4 Like in a semantic way. And that then became interesting, and now I know. Speaker 5 There is still. Speaker 3 A lot of blur. Speaker 4 I can. Speaker 5 Give you a speech about. Speaker 4 I don't know how to now index. Speaker 5 The the text but. Speaker 4 It's because I have the knowledge understand that, and I have the knowledge to understand what is coming next, and now I have the knowledge actually to understand what is coming next. But the point is. Speaker 3 Sometimes learning. Speaker 4 Is just a way to understand what is coming. Speaker 3 Next or what to? Speaker 4 Learn next and that's very important because in our career and I was actually I was having I was giving a speech last Wednesday in in a school where I was presenting how to tackle the how. Speaker 3 To career. Speaker 4 And I said the. Speaker 5 Day you decide to stop. Speaker 4 Learning to stop studying. I mean, your career is done. Literally your career is done. So your mindset? Speaker 5 Supposed to be. Speaker 4 Ask for help. Speaker 3 Learning study, be couriers, but never stop learning otherwise like your careers. Speaker 5 Is basically started doing and then. Speaker 2 In any in any case, right now, what excites you most more about your future? Maybe they're in the scene. Of course, your career right now. Anything you want to share with us? Beyond Buzzwords: How SaaS Companies Can Strategically Leverage AI for Real Value Sorry. Speaker 3 As a suggestion for a career. Speaker 4 As I would say on, don't fall in love with the solution, fall in love with the. Speaker 5 Problem. Speaker 2 That. Speaker 4 And that's the, that's the point when you, when you are dealing with the AI, you. Speaker 5 It's not about the. Speaker 4 Solution is actually about the problem you're. Speaker 5 Trying to solve so fall in love with the. Speaker 4 Problem. Don't fall in love. Speaker 5 With the solution. Speaker 3 Which is a very. Speaker 4 Interesting approach, which means you need to understand the problem you need to explain. Speaker 3 Very. Speaker 4 Well, and you need to have a solution for that problem, but then implementation it's a something you should not. Speaker 3 Care of. Speaker 2 And of course, Manuel, I know that you're an expert in SAS and you you're using or implementing AI driven solutions in business and environments. How do you see AI changing SAS companies and how do you think or what do you think SAS companies need to survive over the next decade as we definitely it's a different game. AI is changing every day. Speaker 4 I guess a company right now is not thinking to board AI somewhere and or another it's going to be cut off from the list of. Speaker 5 Feasible. Let's say solution. Speaker 3 For other company the problem. Speaker 4 Is right now. Speaker 5 AI is also by a buzzword. Speaker 3 So. Speaker 4 If you are not talking about AI in some way or another. Speaker 3 You are not doing your job or you're. You're just. Speaker 4 Behind. You're already behind by by many distances by many miles. Speaker 3 So I guess at the very. Speaker 4 Begin it was about having a chat. Speaker 3 Bot right, we're running analysis. Speaker 5 Through a chat bot. Speaker 3 Or I don't know, getting the service. Speaker 5 To a chat bot. Speaker 4 That was an interesting approach. Right now I guess working with the AI is. Speaker 5 To. Speaker 3 Create real values to create. Speaker 5 Real data or to. Speaker 4 Manipulate real data to understand what you could not. Speaker 5 See before, let's say. Speaker 4 AI is able to analyze a humongous amount of data in a new creative way, which was not the way has been processed before. Speaker 3 I mean AEI is around. Speaker 4 Since for that it is not since forever, but even machine learning is AEI in some way or another. Speaker 3 Right. And when you create. Speaker 4 A machine learning model. Speaker 5 Is basically is. Speaker 4 Understanding the logic behind the data and creating a model. Speaker 5 That will actually being able. Speaker 4 To predict to something that is going to happen next or is able to understand. Speaker 3 If a picture has a. Speaker 5 Has a Kitty cat. Speaker 3 Or a dog. Speaker 4 Right, that's machine learn I. Speaker 3 Is more creative. Speaker 5 Because basically is able. Speaker 4 To understand more complex topics. Speaker 5 Is able to literally. Speaker 4 Understand the semantic and the value in the data which which is opening as a. Speaker 3 Lot of floors or new. Speaker 4 Analysis for new understanding of. Speaker 3 Behaviors and human behaviors and. Speaker 5 AI. Speaker 4 Is new year? I don't think we are using AI. Speaker 5 The way that it like. Speaker 3 In a proper way. Speaker 4 I've been seeing people doing incredible things right, but. Speaker 3 There are very few. Very few. Speaker 4 Companies using AI the actual. Speaker 5 Way the AI will create a value. Speaker 4 You cannot create another way or another. Speaker 5 I would. Speaker 4 Say AI is the next. Let's say is the next. Speaker 5 BBB. Speaker 4 Game you need to play, but to be smart in in the way you played. Speaker 5 Because. Speaker 4 Creating the chatbot is not going to be is not going to create any value. Speaker 3 Or explaining some data verbally instead. Speaker 4 Of do you using the? Speaker 3 Chart. Speaker 4 I mean, can create some value, but it's not going to be. Speaker 3 Repeating while probably. Speaker 4 Understanding creating new content or creating new data or. Speaker 3 Creating or another. Speaker 4 Analyzing data in a broader way with some multiple input, it's going to be, it's going to be very interesting, I mean. Speaker 5 We will see. Speaker 4 Probably in the next starting from a year from now, we will. Speaker 5 See. Speaker 3 A lot. Speaker 4 Of new ideas coming with and using the AI the way. Speaker 5 The the way the AI is supposed to be. Speaker 4 The real game changer in the in the game. Manuel's Advice: Find Your Passion, Stay Curious, and Connect for More Insights But in any case, panel, before we end this podcast, if there's one message you want listeners to take away from this conversation, what would it be? Speaker 4 Conversation we've been talking about many, many things we've been coming out with a very nice quotes and sentences, but. Speaker 3 I would say I. Speaker 4 Don't know? Have fun. Find something you have fun with and make. Speaker 5 That your job. Speaker 4 And and and. Speaker 3 Keep keep being couriers forever because otherwise your your career is already. Speaker 4 It's already done. It's gone. Yes, except. Speaker 2 But then again, and if a person wants to work with you, maybe collaborate or maybe ask for your help me it be a mentoring or course technology, SAS, where can they contact you or where can they find you? Speaker 4 Absolutely on LinkedIn like. Speaker 3 There are a few articles. Speaker 4 I wrote for LinkedIn a month or month and 1/2. Speaker 5 Ago about all these topics. Speaker 4 And how teams should work and how you should work with teams and so on. But I'm I'm. Speaker 5 Really. Speaker 4 Reachable and please text me or bribe me and I'll. Speaker 5 Be I'll be happy to to. Speaker 4 Talk to everyone of you. Speaker 2 And of course, anything you want to promote, of course, we would love to share it to our audience as well. Speaker 4 I'm trying to. Speaker 3 Work on my personal project. Speaker 4 Of mine. Speaker 5 Which is, which is. Speaker 4 Actually, the Victor Intelligence, Victor Intelligence is a is an. Speaker 3 Intelligence platform for big. Speaker 4 Companies and big energy companies to to basically monitor the economical and political. Speaker 5 Issues across the globe. Speaker 4 So you can react ahead of time to potential issues or potential market issues and so on. It's it's an interesting. Speaker 3 Topic and I'm trying. Speaker 4 To work this out, so I hope this is going to go well. Speaker 2 I think it's going to go well, but then again, this was a fascinating conversation with Emmanuel about engineering leadership, SAS growth scale and technology to force the AI and building organizations that create like lasting value. So your your perspective. I think it's much of A highlight that great technology leadership is not just about writing code. It's about aligning people, of course, following what you love, following what you love and finding the the right passion in the job so that in any case you're you're learning everyday and you're happy with or content with what you're doing. But then again, thank you so much. I hope you had a wonderful time with us. Speaker 3 And thank you for having me and thank you pleasure. Speaker 2 And guys, if you're new to the channel, please set the like share and subscribe. I know that my energy went down, but again, thank you so much and have a great day. Bye, bye for now. Speaker 3 But cheers. Speaker 2 Thank you SO. Speaker 1 Thanks for tuning in to Secret Experts where hidden knowledge, elite insights, and untold truths rise to the surface. Speaker 3 You're ready to go deeper. Speaker 1 Subscribe, follow and join us on the next episode.