Ten years in marketing and data. Automating processes with AI.

Walking through the dead internet, I sometimes come across something alive. Most of what reaches us today was written, ranked or summarised by a machine. Maggie Appleton saw it coming years ago: an open web turning into a dark forest, so flooded with generated content that real people retreat into smaller, trusted spaces to find one another. This led me to create a new simple page on my site, where I share authors, blogs and articles that I have read and consider good.

A few weeks ago I installed a small local AI model on my laptop that watches a live camera feed. I turned the webcam on in the dark, and in near total darkness it recognised me and the objects in the room. That such things exist, I have known for a long time. What opened my eyes was the accessibility. I installed it in one prompt, free, and it runs entirely on my machine, sending data nowhere.

I once wrote about building my own privacy-friendly analytics tool. It had bot detection from the first version, yet it was not enough. Direct visits took a strangely high share of my traffic. When someone claims that 20% of their visits are bots and 80% are humans, I used to think the same. Today I would say the opposite ratio is closer to the truth. This is how I got there.

I will speak for myself, for what makes sense to me to read and to write. In the age of artificial intelligence it makes no sense to me to be a secondary source, to summarise or comment on what someone has already written. What interests me is being a primary source: to do something, to find something out, to have a conversation, and to write about it. Because no machine and no algorithm can replace a unique experience.

I have Heidegger and my notebook beside me. I am asking where all of this is heading, where artificial intelligence is taking us.

Sixteen of twenty-seven sources did not check out. They did not exist, led to dead links, or claimed something that was not in them. The report came from one of the largest consulting firms in the world. It was meant to be about cybersecurity. They pulled it.

Seventy per cent. That is where the first AI output begins, even when you give it the full company context and the best examples from the past. We are talking about the kind of output that cannot be defined programmatically. It is more complex. Often it is creative work. On one repeated type of output I reached eighty per cent within a week. Every further percentage point is harder than the one before.

For a long time we treated the internet as the main road. The place where work and relationships happen. Yet most of what we see on it today is, or soon will be, AI-generated: text, images, profiles and comments. The internet is turning into an online game full of bots, where you cannot be sure that a human is on the other side of anything. So I ask: was the online world the main road, or only a temporary detour that part of us will return from, back offline?

A few days ago I interviewed a senior marketer. An experienced man, years of practice. I asked him about AI. He said he barely uses it. He had one bad experience with the output and decided he was too senior for it to add value when it is not perfect. I know the other side too: professionals who automate everything that can be automated.

Europe does not have the capacity to face a full-scale, mass drone war of the kind we see in Ukraine. Three dependencies weaken it: China supplies the physical material for defence systems, the United States supplies capabilities Europe does not have, and twenty-seven states cannot agree how fast, or who pays. Rearmament plans exist, but they are being carried out slowly.

AI produces the graphic, the newsletter and the product page faster than a person. What is left for the one who used to do it is the judgement, knowing whether the output is good. But most people have worse judgement than AI. And whoever cannot judge quality cannot delegate either. How do you tell whether yours is the judgement a company relies on, or the kind it can replace?

In April, in the first part of this series, I wrote about an AI prediction system I had started building on my own machine. At the time the software was a few hours old and the prediction record was empty. The record since then has shown one thing: the system does not yet understand the market it is being asked to forecast. It can pull macro context, book value, earnings. But it cannot put those together into something that helps it understand the price.

Prague, 13 May 2026. On my way to work I started thinking about something that stayed with me for days. If most routine work on a computer disappears in the next ten years, and a large share of repetitive manual work disappears with it, what happens to the flow of money? Who pays whom for what? Which economic layers will exist, how large will they be, and what relationships will run between them? This is the six-layer map I sketched as an answer.

Four days in Catalonia. No computer, no AI, almost no social media. I bought this notebook so that I could write down what I would think about, and what I would come across and learn on the trip.

I am building an AI system to predict the S&P 500. It runs on my own machine, uses free public data (yfinance, FRED, the Shiller dataset), and grades every forecast against reality. This series documents the build itself: the decisions, the methodology, the mistakes. What I will eventually share from the running system is a separate question, and an honest one.

Yesterday I could not tear myself away from the computer. When I lifted my head, it was half past eight in the evening. I had been sitting alone upstairs for about three hours.

Will AI take my job? A certified Google trainer told me in June 2024 that my profession would cease to exist. Twenty-two months later, my job title has not changed, but ninety percent of what I do during the day is different. I have delegated more of my thinking to AI agents than I thought possible. I am not afraid. This is why, and what it means for anyone asking the same question.

One hour. Fifty-five minutes. That is how long it took to build what a Czech software firm had quoted at over €50,000. I built it with Claude Code. Not a prototype. Not a proof of concept. A working tool, the one the company actually needed. By the evening of the same day, it was running on staging. This is not about Claude Code. It is about what Claude Code exposes.

I have conducted roughly one hundred and fifty practical interviews over the past four years. Fifty for data specialist roles. A hundred for advertising and performance marketing specialists. Almost every one of them involved sitting down with a candidate over a practical task, something close to a real problem we actually need to solve at the company. Not theory. Not trivia. Applied problem-solving. Over time, I started noticing a pattern.

Before you can teach AI to understand anything, you need to see what it is hiding from you.

The moment other people needed access to it, the problem changed completely. It was no longer about whether the agent could learn. It was about who gets to teach it.

I wanted to build an agent that doesn't just assist. One that acts.

This is what I learned about local vs cloud AI, and why I switched to Claude Code.

What happened, and how can it be reversed?

It happens every day. It is happening right now.

It is home to all the large Carpathian predators.

The feeling I have not had since childhood.

If I take a certain risk, how much can I gain, and how much can I lose?

Manipulation without the feeling of being manipulated is the most effective kind.

Interesting opportunities often appear where nothing seems to be happening.

A few places close to my heart.

Big players like the US and China treat us as second-class partners. It is hard to watch.

These two steps are, right now, shaping my life and the direction I am heading in.

My body was not broken. Quite the opposite – it was smarter than me.

It is a strange feeling. I have not fully processed it yet.

We are heading toward a future where many things simply lose their value.

In every conflict, Slovaks are winners. Why? Because they are always on both sides.

Are the debates that today appear in political struggles and divide Europe more important than this?

How can we expect to come to terms with history or learn from it if we do that?

The more I talk with friends and acquaintances about AI, the more I notice something alarming.

When someone loses their job, their sense of security collapses, so they sell their stocks.

This exchange struck a chord with me, enough that I am writing this post.

I often get asked what I am doing with my finances this year.

This project changed the way I think about generative AI.

He used words like “certainty” as if statistics were part of Newtonian physics.

There was silence in the meeting room. We were discussing a mistake, but no one wanted to own it.

Preliminary signals already suggested the impact might not be just symbolic.

What is artificial intelligence? In plain terms, it is applied mathematics that predicts the most probable next word in a sequence. It does not think, and it does not understand. When we hear the phrase, many people imagine something mysterious, something that thinks, something that understands. It does not. I work with AI every day, and the more I use it, the clearer the truth becomes: it predicts what the next word should be. That is the entire mechanism.

This change has made a huge difference for me.

The more I think about it, the more I realize what a fundamental issue this is.

You might say I am being too pessimistic, that I am fearmongering. Fear is useful.

Many believe they have broad knowledge because they follow multiple sources.

Performance marketing isn’t just about ads, data, and analytics.

No matter how I look at the future, I see very few answers and far too many questions and problems.

If I have learned anything from this experience, it is that my life is not driven by something predefined.

When this sense of meaning disappears, it leaves behind an emptiness that most people find difficult to bear.

The future of work will not be determined solely by new technologies but primarily by our needs.

It is real, growing, and potentially devastating.

There is no need to attach anything with a negative connotation, ridicule, or the desire to change that person.

Let’s focus on reducing these risks by improving how we work with data.

The future can be European, but only if we give it a chance.

Right now, we are at levels reminiscent of the dot-com bubble at the turn of the millennium.

To everyone who has read, shared, and engaged with my blog last year. Thank you.

This is a serious issue, and it is high time we start acting responsibly.

The result is a fractured society where even family gatherings often become battlegrounds for ideological clashes.

For as long as I can remember, I have always thought in the long term.

Visiting my sister Kristína after some time, I was struck by how many more paintings she had than I remembered.

Why devote myself to a discipline even its practitioners can’t define?

Yesterday, I witnessed a glaring example of media misinformation while watching a Slovak TV channel.

The irresponsibility with which I’ve treated my own health is inexcusable.

Today, I see a level of hope in the market that puzzles me.

At the heart of my perseverance lies an unwavering pursuit of the best.

Looking at today's world, I see no rational argument against making Europe more united and self-confident.

From an early age, I recognised that I was part of a larger, interconnected world.

What do I look for in potential colleagues? Good chemistry, common sense, and internal motivation.

Embracing this perspective has made my investment journey a real intellectual adventure.

When it comes to mistakes, I see two types of people: those who hide them and those who harshly critique themselves.

Knowing that the entire stock market of the developed world grows at more than 10% per year, investing becomes an absolute no-brainer.

As an INTJ, I was the kid who loved reading and learning, always full of ideas to make things better.

If I could go back to 2016, I would tell my younger self one thing: start investing immediately.

I often wonder if sharing my financial journey and investment strategies publicly is worthwhile.

2016 was a landmark year for me as I began one of the most beautiful periods of my life.

Do I still need to improve my skills if AI could outperform me so dramatically?

Since my early childhood, I have been an avid reader.

Do I enjoy socializing? Yes. But staying in social mode for a long time? That is not exactly me.

Is it better to doubt or to act with determination?

To me, many commonly used signals and subtle indications feel like riddles.

The core of my productivity lies in embracing simplicity.

I strive to implement this mindset when making all managerial or investment decisions.

While it saved me a significant amount of time, it had an unintended consequence.

I lead performance marketing and business intelligence in e-commerce. I build teams, optimise ad spend, train AI agents, and ask questions that do not appear on any analytics dashboard.

Most people have never heard of phenomenology. Those who have often dismiss it as too complex to be useful. I studied it for three years at Charles University. I still apply it every day.

“Unforgivable, unjustified. It can never be forgotten.”

I ask: “Why?” Mom answers, and I ask again: “Why?” Mommy answers: “Because it is so.”

The protest at Letná is the biggest demonstration against the government since 1989's Velvet Revolution.

A real pan-European political party?

Thousands of people protest for decent Slovakia one year after the murder of journalist Ján Kuciak.

What are the main political forces in Slovakia today?

“I promise to properly exercise the rights and fulfil the duties of a member of the academic community of Charles University.