How to Build Skills That Outlast Any Tool (From Data Analyst to AI Lead)

Let's be honest, 90% of all the AI in production is still just linear regression baby. The worth of knowing stuff in your head, memorizing it, that worth is only going down. Don't be a fool with a tool. That is one of the core pieces of advice I got started my career. If they understood the problem they wouldn't be hiring you, they'd have fixed it themselves. If I have skills and whatever to make a difference, but I choose not to, then what kind of man am

I? Today I'm joined by Marian Marcus, AI lead over at Cap Gemini, and he spends his time in tech improving people's lives. We discuss how he does that, how he got there, and what skills you should focus on to get there as well. It's a conversation that's raw, authentic, with many hot takes and a little bit of controversy. So enjoy. Can you share a little bit more about some of the projects that

you've been doing? Because I looked at your LinkedIn and one of your main passions is really leveraging data to better people's lives, and I'm curious what you've done. I started out in the scene as a

statistician, which is not sexy statistics and and and data. Who who does that? And my dad for decades was for a decade was asking, hey, my dad, what? What, what the heck are you going to do? How are they going to pay you? How are you going to make a living? Then I did an internship. Everybody please do an internship at Pyro 5 for five. And I was modelling the spread of Ebola back then pandemic. And we were using, I was making the visuals, the maps.

We were using that on the on the Dutch national news to raise funds. And we raised 10 dot 6 million euros to send emergency aid to West Africa back then. And I realized that the bullshit, pardon my French, but the the things I do with computers that was mocked at the time can actually help save people's lives. And that for me was the most empowering thing in my entire career, that hey, I can actually do something and I want to do

this more. And then it happened that that's the statistics and data became data science, and then machine learning, and then suddenly everything is AI. And now, now I'm sexy. Yeah, you were doing AI before AI. Hell yeah. Back when it was just statistics and saying, let's be honest, 90% of all the AI in production is still just linear regression, baby. So I lucked out in that regard, that I learned something a few years before it became popular. And then they said, is that data science?

And I said yes, 'cause I needed a damn job. Uh huh. So the trick is to know the trends coming up before the words for those trends even exist. Because by the time the word exists and it's all over over your social media feed, then you're already too late. So the trick is to convince people to invest in something before the buzzword arises. How consciously were you working on a skill that would later on

be kind of marketable? Because it feels like there was partly luck, but also you put in the effort to put yourself in a position to be lucky in the first place. So especially in modern careers, we have this overfit on doing what everybody else is doing. So, oh, everybody learned Python. Everybody learned Python. Back in my day, it was RI still miss R.

You need to know this package. You need to have that certification, but you will never out compete the the competition by doing the same thing as the competition. You will win by diversifying. I'm a social scientist, sociology, criminology, statistics. I will never be able to to out code a computer scientist. Heck no. But that's not what I focus on.

But when I have projects where we were modelling HR data stuff with some computer scientists and somebody comes in and ask, hey, Are you sure we're we're not discriminating. Our algorithm isn't discriminating people. The computer scientists panicked and I said hell yeah. I studied complaining about discrimination. So the point here is to have your niche and your unique combination of skills that make you valuable in the labour

market. And that in my case is a combination of, well, no, knowing a lot of knowing a lot of theory behind sociology, psychology, criminology, and applying that in a field where we're where we're modelling human behaviour at large, at large scale. I was doing stuff for the flow of refugees across borders years ago, and everybody was focusing on how can we get data on how many people cross. And I started talking about

hamburger prices. They're like hamburger prices. And I'm like, yeah, 'cause I read this paper, Google Scholar back then from Norway, showing that hamburger prices, the Big Mac index is the one of the best indicators of people moving across borders. Why? Because the price of a Big Mac is the best proxy you have for economic prosperity in a country.

Think about this. Most of the developing world, or at least parts, have governments that might not be fully objective in the numbers they publish. So you start using the price of the of the Big Mac instead 'cause that's the the closest you can get to an actual real food price. And you see the price of the Big Mac go up from 2016 seventeen. That means prosperity is going down because food prices go up. That's your basic benchmark.

Meaning the year after that, you will likely see more people from that country come to a western country because the economy there sucks. Outlier here is of course India, because they do not have a Big Mac. They have a big Maharaja with chicken. This, it almost sounds made-up, to be honest. It's incredible. Yeah, the Big Mac. Index is real. Yeah, I love that.

I like that a lot earlier you were speaking about people finding their niche, not just following what other people do, but actually figuring out what their unique selling points is or what a combination of skills are that makes them unique in they can actually leverage in their career. I feel like I don't have a traditional computer science background. I kind of started in operations.

I got rolled into software engineering, super excited about it, but I also had to look at my peers and be like, I don't have the same drive to go deep as they can. I would have to put in a lot more meters to get to that level and it it doesn't fulfill me to the same degree. I like communicating with people, like the people aspect a lot. I like certain outcomes. I'm very interested in the business side, in the product

side. I'm still trying to figure out what my niche is going to be and I'm on that path. But what would your advice be? Because I feel like you definitely fit in a lot of things together and what you're doing nowadays sounds super excited. What would your advice be for people to find their niche? So finding your niche is not linear. I love assumptions of linearity in my models, but they're often false. The only way you can figure this out is by trying lots of different things.

Imagine you're you just graduated. How are you going to figure out the one thing you want to do in life but by doing one thing for 2-3 years straight?

Or will you go like, Oh, well, this was nice, this role, now I want to try something else. This is why I like the consulting field that you and I both work in, because you will get to do many more different things in a shorter time frame. Different, different projects, different roles, technical business, large companies, small company, very governmenty, very

retail, very banking. And that's the only way you're going to figure out what you're good at, what you like to do, 2 very different things, and where the coffee doesn't suck. I spent my first I, I've spent most of my career in consulting and I think I developed way faster because of that steeper

learning curve, more hair loss. In my first year at Gap Gemini, for example, I, I was at 5 different clients, but because of that, I had much more of a learning curve was collecting data way faster than had I just worked for one of those clients directly for a year. And that way I could figure out what I'm actually good at and what I enjoy doing and where are the coffee? Oh man, that I'm public sector I love because I want to help people but the coffee is just

terrible. I'm just I'm just saying, just saying. But you will only collect this data to get a better verdict by trying different things. So anyone still studying out there, do a minors in something completely different, do a master's in something different, do internships at completely different places. Not because you will pursue a career in every one of those, but to figure out also what you do not like. Because when else are you going to figure that out?

When you're 4050, when you have a mortgage in kids, OK, most of you won't even get a mortgage at that age. But you, you get what you get. What I mean, you have to try different things and collect data. And the biggest problem I see both for individuals and for organizations today is that we're stuck in analysis paralysis, that we don't know what to do.

So we just do nothing while the rest of the world keeps advancing and we're like, oh, but we could do A or B. To quote Slavo Shisek, sometimes doing nothing is the most violent thing to do. And we we ponder and we worry about the price of action, but we forget about the price of our inaction, both at the individual and at the collective level. Can you share a little bit more about that?

When you see organizations or where you see teams or maybe even individuals that are stuck in analysis paralysis mode, too many options. I don't know what to do. I have trouble starting. How do you handle that or how do

you help them? I'm going to use an old example here, Thesis. The the recommendation I give to all my interns and when they do a thesis, like a master's thesis or a bachelor or whatever, you get to spend half a year to a year of your life on it. You make sure the that you enjoy the topic because you're going to spend half a year to a year of your life on it. And if you enjoy that topic.

I was doing analysis on crime back then for the Dutch police in my own hometown, Rotterdam, which was hella complicated. The data was horrifying, but I liked the topic. So I could keep pursuing that because I had that motivation. Doesn't mean you need to enjoy every aspect of it, of the methodology of the screaming at your computer, But at a basic level you need to have some interest in the topic, because that's the only way you can keep it up.

Yeah, I like that a lot. Previously, very early when I joined consultancy, it was a question of OK, what do you want to work at? What are the skills you want to develop? But also, do you have any industries that you want to work in or not want to work in? And back then, early in career, me was like industries, like I had never given that a thought even. So I said, no, I said industry doesn't matter. I want to walk with very smart people. I want to grow as fast as possible.

I want to have a lot of experiences and a lot of things so I can figure out what I like and what I don't like. And then I got into an industry and now it's on my resume. So you can probably figure out which one that is. And it's not something that I'm proud of. And I never even stood still at the time. And now I'm like, yeah, industry, it might matter. I'm now in healthcare and I see people come in, they say, well, I've taken a pay cut and things are definitely slower in this

industry. It's in healthcare. But they like the goal, they like the purpose, they like the fact that whatever they're building, that it might help society, it might help people, it might help in the end, the Netherlands as a whole, which is very motivating. And I love the current experience that I have because I get to see that behind the scenes, I had a lot of assumptions in working in the public sector or working in a lot of industries that are good for people, good for your

country or good for humanity. Might be very slow, might be very boring, might not have many opportunities for me to thrive in. And I don't know if that's true. I feel like it's still true, but it's definitely something that's been withholding me for from actually going there. I might go there maybe in a in a few more decades, But that's also a shame because I feel like that industry meets a lot of people and also people that are early in career, people of all

kinds. So I'm curious from your perspective, what makes it that's super exciting within those industries or what has been the case for you? So career choices are not black, white, XY01. There's this time factor that we often forget because in the short term, and I've worked for for banks, for example, in, in the past, in the short term, yeah, I was not doing much for for society or for the world, but the stuff I was building there and learning over there, because banks are hey, way

bigger budgets compared to some other sectors. The stuff I was learning there. Years later, I started applying in completely different fields like forecasting the yield for smallholder farmers in Kenya and India and and help it helping the worldwide organizations that help feed millions of people. And I would not be able to help them at that point in time, if not a few years before I was crunching similar numbers and models for for banking and for retail.

So here's the short versus long term, even if you're not not directly helping people in the short term. Heck, I could have joined a soup kitchen instead of instead of studying, but I think I can contribute more to the world with the skill set that I've developed since rather than just just doing soup all day back then. And yeah, that that's my answer to your question. Time. The time dimension is often

forgotten there. I can only do what I do now to help people because of the stuff I built in the past decade. Heck, remember, remember Andrew and G? We were talking about the before the 1st computer vision models. This is a dog, This is a cat. Those were developed in 2012, 2013, the Atlas NVIDIA GPU, back when GPUs were still affordable. Those were the first models that could say, hey, this picture, this bundle of pixels is a car. This is a whatever.

Nowadays, the same tech is in everybody's phone, in everybody's self driving car and in every autonomous killer AI drone that's out there out there flying to an alive people. Tech progresses so fast and we collectively as as a field can only help out with that because we did our homework and five to 10 years ago, we're fitting our own neural Nets on, I don't know, local GPUs with, with your laptop that you had to leave, keep on running overnight because tech progresses so fast.

And sometimes the best investment you can make is just to build something, home projects, hobby projects, just to keep up and have a little bit more hands on experience than the competitor who only read a paper about it or watched a YouTube video or asked Jack GPT about it about it. Because all diplomas and certifications, I'm sorry people, all diplomas and certifications are compensation for lack of experience. And this market mainly focuses

on experience and you lack that. You get something that a proxy and you go get a proxy for experience. And that is why we focus so much on internship stuff you built in your spare time, stuff you have on git, anything you can, you can point at. And some of my biggest achievements in my, my entire career are actually things that I can just point out that you can Google. And I'm like, Hey, that's my got my name on it on that.

And that's my next point of career advice for people. Focus on external stuff rather than internal stuff within your organization, because internal certifications or titles or blah blah of the of the quarter or God knows what you cannot take with you throughout your career. But if it's external, like standing on the stage, I'm a three time world world summer

day. I speaker for example, I really focused on that because that is external and I can I will keep that with with me wherever I go. The last few guests have all kind of mentioned the same thing. We're moving from an experience based economy to a skills based economy. So the fact that you have a paper might not distinguish you anymore from someone that can show and point to some of the skills that they have and that

they've built something with. It used to be more valuable, but right now we just have too many people with too many certification. So it evaluates. This is basic economics one O 1. Yeah, most of the people and most of the audience that's listening. I did a poll. What is your experience and how long have you been working in tech? And it actually varies, but the biggest slice of people have worked in tech for shorter than five years. I'm assuming mainly they are software engineers.

And if we are talking about the skills that are for the future, you're saying technology accelerates quite quickly. What are some of the skills that you think people should focus on specifically for their career but also for like peace of fulfillment and looking towards the future? The ability to learn first and foremost. None of the tools I work with I I learned. I learned SPSS people back in the day. Some some people in the audience will be cringing right now.

SPSS taught myself R to scrape Twitter back before it became shitter to to model the 2013 fourteen Syrian refugee crisis. I hated Putin before I knew where Ukraine was on the map. But from our I went into Python And now Python is the end all be all. But I'm from an era where people were still asking like, Are you sure? Should you be learning SAS? Because SAS is better in the

market right now. So God knows what we'll be using in 10 in 10 years, unless all the all the LLMS start overfitting on on just languages that are already in use. We might actually see a stagnation in the development in the development of coding languages now, since Claude and Gemini will not be able to adopt to new languages as much as produce more Java horrors. Meaning we will be stuck with Java until the death of the universe, I'm pretty sure.

But what I'm trying to show here is that those tools, those techniques, cloud platforms, they change so fast that you can't focus on learning a technique. You've got to learn a method to learn new stuff. That is the most single most important skill in the entire tech field to be able to learn not even master, but just work with new tech Anytime I have a new project, oh God, it's a new

cloud platform I haven't worked with. OK, well AWS, Google, Azure, I'm pretty sure it has most of the same functionalities. They they just call every damn button differently and that's how they vendor lock. So, so you can't go go to the other cloud platform because the names is different, which is less of a hurdle than you would think. And then there's of course nuance, like the billing models are different, the scaling is different. The, the, the type of servers

you can run it in is different. You cannot local host, I mean sovereign this this version. Remember that people sovereignty is the new local host. You're just running your own damn model on your own damn computer. But you don't call it local host you you call it sovereign. The client will love it, thank me later. So it's and that's the other thing. And I mentioned that before understanding the words because buzzwords will come, but they usually mean something that

wasn't new at all. Again, sovereignty is just local host but new. Everybody screams as as was screaming AI, but we mainly meant just deep learning on steroids with a lot a lot of GPU and compute. Big data was just data that you store on multiple different servers because you don't have a single server that can contain it all. But nowadays my laptop has more storage than a whole complex of servers a decade ago. Meaning. Big data is dead.

Long live Long live big data. The core problem here is the core problem of humanity, which is that sometimes we say the same words but we mean different things, and sometimes we say different words but we mean the same thing. And all of miscommunication stems from this.

And in our field, it is important to figure out not just what words people are using, which is what sales heavily focuses on, but what their actual problem is and what they actually mean, which can be, which can be completely different from the words they're actually using. Because I've had clients that that ask for AI and it can mean a random tree, a random forest, It can mean you have some kind of image recognition model. It can mean some type of speech

synthesis. It can mean producing synthetic data of bananas using 3D models. It can mean so many different things, but they all use the same word and it's our job to figure out what the heck they want and then to build that. Not just to receive orders and build something, because that job will be outsourced and automated to hell him back by whatever cloud copilot thing they they buy and or consume.

But the core skill to figure out what the fluff they actually want and need and what is the problem behind the problem. Because if they understood the problem, they wouldn't be hiring you, they'd have fixed it themselves. But they do not understand the problem, do not understand the solution. It's our job to figure out that solution, then do that. And to do that we need to be

able to learn new tech and learn new stuff. And that's why learning is key. I want to zoom in on that because I, I'm a big believer that compounding knowledge is one of the most valuable things you can have. And you can only compound knowledge if you bit by bit make ownership or take ownership of certain sources of information. Really familiarize yourself with it to a certain foundational level. And I'm assuming that a lot of listeners are going to hear you speak.

They're going to say he seems very well educated, communicated, all of that and much, much more. So they are seeing you from a level of where you are now, but they haven't seen this journey of how you got here. How do you actually get here, or how do you take ownership and get good at learning in the first place? How do you get good people? That's that's the question. Well, all the gamers out there, how do you get good?

You practice. Look, I'm not talking about video games right now because I get slapped and clapped by 13 year olds on online games nowadays because they got way better reaction speeds than me at the at this at this age. But again, practice and you shouldn't obsess over the short term and that you can't succeed all at once because learning all of this learning is not a Sprint.

It's a marathon. Unfortunately, we mainly teach people, kids to Sprint in education because it's to your next exam, to your next test and and then you go drink beer again. But it's about acquiring knowledge over time. I I always felt stupid back when I was a student because again, my teachers and my fellow students always knew more than me about this one topic.

And then in my in my actual job, I have to explain how burnouts work and what's, what's HR data forecasts that because there's a lot of stuff you can do to actually see that coming. Yeah, I read a bunch of papers about that. I, I wrote some, I built some models and I was just explaining that to an audience. And I only realized how much I

knew about this once. I had to explain it to an audience who did not know, which was very special to me because that was the point in time that I realized that, hey, I actually know some stuff. And I warmly wish for the for the audience and the crowd and all the listeners to experience that, that that feeling of what's the word?

Not justification, but just realizing your value, that you have value, that your skills and your knowledge have value, that you can be an expert on something beyond, beyond slapping people in Dota. And I love that. I don't want, I want more of that. Yeah. And that keeps me going to do that again over time, OK, then IoT becomes a thing. I'm going to get a Raspberry Pi. I'm going to get all the all the sensors. I'm going to stick that on everything in my house, including my cat.

And before I know it, I know something about it. I I can talk about it, OK. And we're going to, we're going to, we're doing, we're doing time series models on things for banks, on things for retail. And, and then we need to do that when lives are at stake. And I'm like, hey, I've done this before. I can do this and I can help people. Yeah. And that is just wild because that's what I want to do, do

data to help people. Because apparently doing data stuff and talking about it is what I'm good at. And I just want people to find the things they're good at and to then apply that to help people because we have these, we have the IT field here in the Netherlands and we talk about innovation. And usually that's counting the amount of AIPOCS you've done. We call that AI maturity. That was last year. This year we count the amount of Co piloted licenses you have in use and we call that AI

maturity. But most of the actual innovation does not come from banking or retail or or governments. Most of the actual innovation comes from the three fields we do not want to talk about, which is crime, warfare and the adult entertainment industry.

But like seriously, most of cybersecurity bit Bitcoin, streaming technology, 3D, HDVR and deepfakes all stem from California's most famous industry. And so if I want to keep up with new stuff, I'm more focusing on the fields where rules and laws matter less because that's where this stuff is invented and scaled.

And then that is transferred to the to the fields where we actually work in. And then lastly, there's the pro bono, there's the NGOs and there's the large governments that make the most of a difference to people in need, people who are hungry, people who are in depth, people who we want to help. But to help them with those skills, we first need to acquire those skills in other sectors. And that is usually, again, the banking, the retail, the

whatever. And we glean those, those skills and those techniques from the sectors that are most ahead. But unfortunately, then I'm going to talk about the Rotterdam drug traffic industry. Cause hey, we have the biggest port in Europe. We have thus the most cocaine traffic in Europe. Hey, represent Rotterdam and and or Modern Warfare because yeah, everything we see on drones nowadays, everything we thing we see on 3D printing and ARAI autonomous warfare, that's all happening in Ukraine.

That's not happening in the Netherlands. That's not happening in America as much as they they try to claim otherwise. Just this morning I saw the American military brag about their new drones they're acquiring for like 3330 KA piece even though Ukraine can build the same drones for less than 1000. But in warfare scale matters and down the line we will see pizza delivery drones or medevac drones. So ground based drones with wheels that can evacuate a person. That's healthcare too.

Those are all being developed and tested live at the front line to the extent that any any serious drone company that does not supply their stuff to Ukraine is not a serious drone company because they haven't tested and proven their stuff. To digress back to point to the point I was trying to make, there is fields where rules do not matter and that's where all the new stuff comes from. And This is why I professionally

watch Borne either. That's we why, why I we as professionals should at least look at these fields because that's where the new stuff is coming from. And that will trickle down into our banking, retail, whatever sectors. And down the line we use those skills that we acquire here to do good. And that is the eternal cycle. And we all have to find some kind of balance for that as as techies, as I tears as humans, so that we can learn and develop ourselves and also be able to

give back. Because it pains me to some extent that the newest generative AI stuff that we develop as humans is mainly used to generate porn and not to do good. Yeah, but there's a lot of that porn. There's more porn being generated nowadays than is actually being produced by humans. Think about that. And it's and it's really good. Oh, OK. Think about this. I, I've known that certain industries are way ahead in technology and I don't know how

I've known that. Maybe it's just anchored and I listen to a lot of podcasts, but it was always in there. And then you can kind of see what will trickle down into retail and banking and all that sort of stuff. But there was something that you mentioned where you are now equipped and also well equipped throughout history with regards to the skills that you've obtained to now help people's

lives. Doesn't it frighten you sometimes the position you are or what you're working on, that when you make a mistake or where there's a few mistakes that are compounding that, it can also negatively impact people's lives. Oh hell yeah. But that means you can make a difference. If you are afraid of responsibility or the consequences of responsibility, then you should go sit in the corner and do nothing. A year ago, well, well over a year ago, 'cause this is about taking heat.

A friend of mine on Discord tried to contact me saying, like, hey, Marine, your account's getting getting banned. Something happens, you need to report to the Discord help desk. And I'm like, I don't want to lose my memes. Yeah. So I contact Natalie Rosser to the Discord help desk. Please don't ban me. It's like, OK, can you identify yourself? I'm like, identify myself. Yeah, you place a birth, blah, blah, blah. And like, Discord should already know this stuff, right?

I just pull it up, right? I started to notice that Natalie Rosser is not actually Google, Google a bull. And that her answers were always after exactly 20 seconds, regardless of the answer being 2 words or 20. I saw a pattern. I was talking to a bot. Yeah, this was a reason. Sorry Sir, No no, this was almost a year ago before we started calling every goddamn

bot an agent. I was just talking to a bot impersonating a human but also impersonating my friend because my friend got hacked and it will and LLM was told to talk like him. Terrible spelling Unicorn smileys. No, no caps.

And had I identified myself to Natalie Rosser, they would have taken my account, talked to Discord saying like I am Mariah Marcus, this is my personally identifiable information. They would have tried taken my account and tried the same trick with everybody in my list. Now I have no clue who was trying to do this. Again, this was before we started calling everything an agent, but I was already talking

about agents. Basically because you do not need a Nigerian Prince on the other line or somebody pretending to be a Nigerian Prince, you can just use an LLM. Foreign agents of the future will be code and prompts and we are not even ready to start considering the implications of

this. Actually, we saw this last week with X Turn. Turns out that the biggest MAGA influencers in America, as well as some of the biggest nationalists in Poland and the Netherlands, were actually accounts based in Bangladesh and Nigeria and stuff. Again, this is basic data analytics, but it's either humans who are just profiting off of outrage or not even humans, just bots and agents and whatever.

And again, we, we pretend that agents are anything new, but they're all over our social media for years already because the criminal sector and the hybrid war sector have adopted these technologies long before our our banking and our retail and our shops will adapt to this. And This is why I obsess over disinformation about bots trying to hack me. Because this comes back to your question about heat. Yes, I should be scared about taking heat, but that is the price I pay for making a

difference. Then hell yeah, I had to calculate. I was involved in calculating the, well, how to feed people who suffer from malnutrition. That means you're calculating how many people you can save. It also means calculating how many you cannot. But that is where I can make the biggest difference with my skills in ways that I never could if I were applying that for just marketing purposes to sell candy.

And that's where I want to be. That's where I can make a difference, and if I have skills and whatever to make a difference, but I choose not to, then what kind of man am I? For people listening, let's say it's very inspirational what you're saying and I want to progress my career in a way where I can also do that. How do people get there? Are there any actionable steps? You already mentioned building up the skills first is actually your career is non linear.

So whether you do it now or whether you do it later, it can still come up on your path if that's really what you want. But how can people actively work towards getting themselves into a position to actually with their career and what they do on the day today, help whoever they want to. Careers are not linear. Yeah. They're also not even branching paths.

Careers are roguelikes. OK, like the video game where you can branching paths, but you go back to the start at some point because then suddenly data analytics is dead, but data science becomes a thing. Now everybody is an AI engineer. And I don't know what Pokémon names we'll be using next because the kids I educate these days never played Pokémon, so my

Pokémon jokes fall flat. But the important point here is that we keep reinventing the titles and the career paths faster than we can walk those paths. So it's more important to focus on on skills without expiration dates because you can master some type type of coding or some kind of language like English or French or Japanese.

But it's more important that you learn how to learn new languages because the more languages you speak, the the more easily you'll pick up the next. The same goes for coding. I've seen people go all in on on their learning COBOL way back in the day. But if that's the only thing they they know, then they're stuck. If you're go all in on learning one cloud platform, I know everything about Azure, then the company you works on my the company you work for migrates from Azure.

You're stuck going all in on SAP. Never go all in on one thing that has an expiration date. Focus on skills that do not have expiration. That we see this so much nowadays with the with the Gen. AI hype about learning this prompt or that even though those prompts, even though those prompt tips will be useless two months down the line when the model gets updated and it all falls flat and you have to and they no longer do the weird

dashes, you know? So there the skill is not to know on top of your head all these prompting skills, but to learn to be able to reverse engineer how the prompting works. That is a far more valuable skill. In the same time, in the same way that writing good speeches, anyone can generate a good speech, but how to deliver that, how to talk and how to connect with your audience and all that, that is still a far more

immaterial skill. And a lot of things we are automating right now, in the same way that steam, the steam engine and radio and electricity and the Internet helped us automate parts of tasks, but that only made the other parts of tasks more important. We have silly things like marketing nowadays that we never would have invented if not for for the past few industrial revolutions. Hell, we used to call it propaganda.

Now we only call it propaganda when we don't like it, even though both books were written by the same Frankfurt schuler back in the day. I also did a minor in propaganda studies, which is why I obsess over this information nowadays. And we see that these models are actually now starting to regurgitate disinformation and propaganda from totalitarian

states. Meaning it still becomes more important for us humans to have the skill to filter information and to give verdicts and to give judgements about pieces of of information rather than to just copy paste whatever the heck ChatGPT said. That goes both for your coding and for your business analysis skills. Drop Mike. I was on Twitter and I same as you. I'm so sorry for you.

Same as you, I got reached out to several companies actually, and this was in the span of a few weeks all with regards to we love what you're doing on the Internet, podcasting, social presence, anything like that. We want to sponsor you. I thought, well, I've made it very cool companies, companies that I look up to, I used to gain. Razor was one of them. GoPro was one of them, Udemy, which I thought great fit. My sweet summer. Child. All of them.

All of them scams. You thought you were talking to humans. Exactly. All of them scams. So that that was one. But this was also somewhere last year. And the obvious one was they sent me a signing link to one of their NDA's or a contract or whatever. And it was just a forefront, which is very well done to be honest compared to the actual the real thing. Now I made a post of that. I reported everyone, etcetera, etcetera. And now in the most recent one, it was a YouTube that reached that.

We're going to do this YouTube collab, We're going to do a podcast. It's going to be for a good cause. All money will be donated and we'll pay you X. And I'm like, the money will be donated. And then how do I get, how does this work? And then I'm in a group chat with everyone from the US, none of them in Europe, and they all say when they're going to be online, but everyone uses CET and I'm like, that doesn't make any sense.

So why would you translate that specifically to me, who I'm the only one there? And then the same thing signing link or and like I report everyone, these people have real Twitter, well, real Twitter accounts, but they also have links to their YouTube channel. And that same YouTube channel who has millions of subscribers also links back to the same Twitter account. So I haven't figured out exactly

what's at play. But in essence, this frightens me. Like, I'm excited for a lot of things in the future, but the fact that there is such manipulation of information and misinformation, that is the part that frightens me. This is the information age, not the knowledge age, and the skill to distinguish truth true from false will only become more important in the future, especially as no single point of information can be trusted

anymore. We can create fakes that look more real than real than real things by now, but our ability must be to triangulate between different points of data and to then go like. Yeah, well, actually this doesn't make any sense given from what I previously know, that will only become more important, even though back in the day it was viewed as not important because anybody can take your photo and make you make a video of you doing very,

very weird things. I read that last month over 15% of all American high schoolers have seen deepfakes of classmates doing very inappropriate things, and I was surprised because I thought that number would be higher. Really. Yeah, man.

See, that's the part where and mainly bring it back to anything more from a career perspective, people are saying very early on, topics are getting automated now by agents, which means that the people that are educating themselves and that usually that's a step for them to build up the skills to do very, very cool things that help society. That step is now changing and people are asking, well, what do I do then to make myself not

obsolete? And we're talking about anything with regards to communication and soft skills and learning. I agree with all of that. And then there's still a tooling aspect. Like I don't know what I should advise people with regards to, OK, how do you go from junior to actually in the end becoming senior? Because it's such great area that I don't know yet. I feel like we're really figuring things out. And the only advice that I have is be as open minded as you can.

Try and familiarize yourself with a lot of things. Try and build as much foundational knowledge as you can because tooling does change. I'm wondering what your perspective is on that. Don't be a fool with a tool.

That is one of the core pieces of advice I got. I started my career so over 90 years ago. God, don't be a fool with a tool. Back then we refer to only knowing our only knowing Python or only back then. Do you remember RPA people? Do you remember back when RPA was a was a thing? I was using a Python package back back in the day to to scrape Twitter. I forgot forgot the name Selenium. Yeah, yeah, I was learning Selenium because that was one of the first Python based browser.

This automate the browser and click down. Back then those were bots, but I knew people who doubled down on only learning Selenium and all the insurance and outs. But Selenium was open source and it was great. You could do everything with it. But then the blue prisms came in, which was basically the the company or the company organization equivalent of it. But it was reliable because you could sue somebody if it didn't work.

And suddenly the whole Selenium market disappeared because people went for for larger infrastructure tools instead. And the guy who knew everything about Selenium was stuck and the people who learned Blue Prism were laughing at him. Nowadays we laugh at the people who only know Blue Prism because the cycle continues. It's not about learning anyone tool, it's about being able to learn in general. And that involves learning the insurance and outs of tools.

I think it we are switching from an explicit knowledge economy to an implicit knowledge economy and our education systems haven't adjusted to that, that the worth of knowing stuff in your head, memorizing it, that worth is only going down. But the ability to look up stuff that was introduced like what, 25 years ago when Google hit the market, before we had that, we had start start that has been introduced during our lifetimes.

But the value of that, of finding stuff in large amounts of information, that is only going up, especially in the age of disinformation, because we are drowning in information. But truth and wisdom has only increased invaluable and has become relatively more scarce because now there's more bots and more fake stuff flooding the Internet than actual real stuff.

And the only way we can still distinguish truth from fake, because I see so many deep fakes now of Zelensky, of Putin, of F-30 fives that crashed in Iran. And we could only tell they were fake because there was still a a human in the cockpit, because they forgot to prompt it remove the human from the cockpit. We can only tell truth from fake because of human error. And that too will end. So what we need to learn, again, because learning is important, is to triangulate information to

figure out what's real. And This is why I I'm frustrated with modern media and journalism that thinks that just regurgitating and repeating what no liar say is somehow journalism. I forgot the quote, but somebody once wrote this. If one source tells you it's raining and the other says there's sunshine, your job as a journalist is not to report both, but to open a damn window. And that's what I'm missing. Yeah, I love that.

One of the final thoughts that I had was when you say don't be a fool with a tool, I really resonate with that. But then I look out in the market, I get bombarded, especially nowadays with tools, with so many tools, which means. Both human tools and software. Tools like like anything. And that means that there's definitely a market for tools. Are you saying don't use tools, don't master tools? Because I also love mastering my tools.

I take pride in being efficient with regards to whatever I do on the keyboard, but in the end it's still a tool.

Creating tools is cheaper than ever and let's be honest, 90% of all Gen. AI tools and and Gen. AI startups are just some front and API call to to ChatGPT, you know so tools became cheaper and easier to make. So as a consequence, we have more tools flooding the market than ever and 99 out of the out of 100, they're all the same or they have similar functionality mean it's a harder than ever to stand out because again, they're just a bunch of generated

things. And why the heck should I go for a generated for a generated third party tool when I can just vibe code my own tool and get to the 80% by myself where usually I would need months of developing time in an entire team? Sure, I will waste two or three times as much money on the last 20% to get it to get it home free and bug fix. And why can I upload 10 or 20

pictures but not 15? But overall I'm still accelerating, meaning the value of tools then decreases even further because I creating my own is technically now also way cheaper. It's just most organizations only have people in in their HR in their HR database that no specific tools stand out. Rise above the tool. The client doesn't care that I am the toilet duck experts.

They say ain't that I know everything about Azure, or that I know everything about Edo S or about Google or IBM, but that I can distinguish between them and tell them which which one sucks at what task and which one they should go for. And that's not some kind of Pokémon Dragon Ball Z, my dad can beat up your dad competition. But they all have their niches and they all have their own delicacies and this one is better than that.

That one has better image recognition service and that one you can saw is that one you can local host. I mean has sovereign options and AWS has not until they do of course, in two months time, but that's how we keep up. Nobody will appreciate you for just knowing the tool, but for your ability to distinguish between them, especially over time as tools and methods and techniques and insights change. And that's why you should listen to podcasts like these.

But I thank you so much for going on and sharing. This has been a real blast. Thank you. Awesome. We're going to round it off here. If you're still with us, let us know in the comments section what you thought of this episode and we'll see you in the next one.