Article
All in on AI agents, or an analogue life.
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.
The notebook also records the driver who took us to where we were staying, a man who has lived in Barcelona for decades, although he was born on the opposite side of the Iberian peninsula, close to the Portuguese border. During the ride he spoke, among other things, about the tension between the Catalan question and Spanish centralism. He was clearly on the Spanish side.
We spoke about other topics as well, and he recommended places to visit.
The next day we went into the city. And alongside the pleasant views, we came away with some very unpleasant experiences.
The notebook records, for instance:
“7 May, in the afternoon. A side street running directly off Barceloneta, ten metres from us, in broad daylight: someone violently snatched a valuable straight out of another person’s hands and ran.”
Or:
“9 May. For the second time in three days, again about ten metres from us, in broad daylight, a valuable snatched by force out of another person’s hands, followed by a run. We saw it from the taxi.”
I had never seen a theft like this in my life, and now twice in three days. It would deserve its own article. So would other notes that I am not writing about here.
I have plenty of material. On everything I lived through, I formed my own view, and I wrote it all down. Only now, after returning, am I moving it into digital form. This process makes a great deal of sense to me.
FRAGMENTED ATTENTION, TWO EXTREMES, NO MIDDLE GROUND
For as long as I can remember, I have been surrounded by digital technology. Email, chat applications, project tools: all open, all the time, whether I was working, resting or travelling, the phone usually in my hand. The only stretch of my adult life when that was not true was during my master’s degree, when I read philosophy books in the library, and when something existed only in digital form, I printed it and went to the park to read it there.
Outside that period, the digital world has been everywhere around me. Over time my sense of being overwhelmed by it grew, and my attention became persistently fragmented. The information smog in my inbox and in the other tools I use to run projects reached the point where I could no longer find my own priorities through it.
That is how I arrived at the way I now work: I move in two extremes. Either I solve everything digitally, mostly through AI agents, or I work entirely without a computer. When I pushed the digital side as far as it would go, I even tried running local AI on my own hardware before settling on cloud agents. The things that are genuinely important to me, I write down on paper. On my desk there are about twenty sticky notes with the tasks and projects waiting for me, and I record my thoughts and findings in a paper notebook.
Join the Library
Full access to my thoughts, personal stories, findings, and what I learn from the people I meet.
Join the Library · €29.99 per yearGet the full article by email and feel free to reply if you want to discuss it further.
Summary
Common questions on this article's topic
Should you use AI agents or work offline?
What is attention fragmentation?
Why is writing by hand better for thinking?
Can you live an analogue life and still work online?
What does working with AI agents look like in daily work?
Is a hybrid AI workflow worth it?
If you have any thoughts, questions, or feedback, feel free to drop me a message at mail@richardgolian.com.
LinkedIn
Related articles
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.
More articles
The same task, two models. Fable 5 against Opus 4.8. On paper Fable is the better model, with a larger context and stronger specs. And still it lost. Opus handled the task with a single round of checking for 721,000 tokens, while Fable needed nine rounds and burnt through 2.78 million tokens. The difference was not in the model, but in how I set the task. And I know it, because I measured it.
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.
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.