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.