What nobody told me back then was that this whole equation assumes that the job you're preparing for will still look roughly the same five years later.

So what's the point of figuring out your career early if you don't even know what that career will look like by the time you get there?

I don't think that assumption really works anymore.

5 years is a long time

It's 2026 and someone is graduating from school and starting university at 18. They'll probably have their bachelor's degree around 2029 and their master's around 2031.

Now think about the technological jump we've seen over the last five years.

ChatGPT wasn't even publicly released until the end of 2022. In less than four years, generative systems went from relatively simple chatbots to tools that can write large amounts of code, do research, generate images and videos, and do a lot of other things.

Someone graduating from school today has to make decisions for a job market that won't exist until 2030 or 2031.

And that job market could look very different from the one they're looking at right now.

Some examples

Let's just take a few professions.

Software development

This is obviously the easiest one for me.

Imagine starting a computer science degree today because you want to become a software developer. You start learning programming fundamentals, algorithms, databases, software engineering, web development and so on.

And of course those things still mater. But think about what someone imagined a software developer doing five years ago.

You get a ticket. You open your editor. You write the implementation. You spend an hour trying to figure out why something doesn't work. You search Stack Overflow. You write some tests (maybe). Eventually you find the stupid mistake you made three hours ago.

That's how I learned a lot of what I know.

Today I can give an AI a description of a problem and get a surprisingly decent implementation back. I can give it an error message and ask what's wrong. I can give it existing code and ask it to write tests for it.

That doesn't mean software developers are disappearing. Someone still has to understand what should be built, how it fits into everything else, whether the generated code actually makes sense and what happens when it doesn't.

But that's kind of my point. If you start studying computer science today because you want to become a software developer, the job you'll get in five years might still be called "Software Developer". I'm just not sure you'll spend your day doing the things you currently associate with that title.

Writing, translation and marketing

Writing is probably the most obvious example because we're already surrounded by it.

I have no idea how much of what I read online today was written by a person, written by AI, or written by a person and then rewritten by AI. And honestly, most of the time I can't tell anymore.

Take translation. A translator could spend hours translating a document. Today you can paste the same document into a model and get a translation back in seconds. Is it always correct? No idea. And depending on what you're translating, "probably correct" is obviously not good enough.

And the same thing happens with marketing copy, product descriptions, emails and all the other little pieces of writing companies produce every day.

Maybe one marketer can produce the amount of material that used to require three. I don't know. But if you're starting a degree today because you want to do one of these jobs, that's a pretty important "I don't know".

AI probably won't simply take the jobs

I think this is an important distinction because the data doesn't really support the simple "AI replaces everyone" argument.

The ILO says that about one in four workers worldwide has a job that involves using generative AI to some extent. But it's probably not a complete replacement. It's transformation (source).

To be fair, that's based on their 2025 report. And with how quickly things are moving, even data from last year is already old.

Most jobs probably won't disappear overnight. The actual work just starts to look different.

I can already see that with programming. I give Claude something to implement, do something else for a while and come back to mostly finished code. Then I spend my time figuring out what it got wrong instead.

The junior problem

If we extend the equation from earlier, a traditional career looks something like this:

Beginner, simple tasks, mistakes, experience, harder tasks, expert.

Simplified obviously. But that's how we learn. The problem is that AI is particularly good at many of the tasks we've traditionally given to beginners. Take software development as example.

A junior developer might work on simple implementations, boilerplate, tests, documentation or smaller tickets. Those tasks aren't just cheap work that someone has to do. They're also how you get into the workflow, make mistakes, understand systems and slowly learn how everything fits together.

A senior developer deals more with architecture, ambiguous problems, legacy systems, stakeholder communication, trade-offs, and responsibility.

But you don't just wake up one morning and become senior. You get there by doing the simpler work first. So what happens when we automate the work that people used to learn on? Or maybe the better question is: How do you become senior if nobody needs you to be junior?

A Stanford analysis updated in August 2026 looked at millions of US payroll records and found no broad AI-driven collapse in employment. But employment among 22-to 25-year-olds in jobs with a lot of AI was about 19 percent below what it would have been if it had grown like employment among their peers in less AI-exposed jobs.

It seems like the difference mostly comes from companies hiring fewer young people. That doesn't prove AI caused it though.

But developers don't have to lose their jobs for this to become a problem. If companies need fewer juniors, fewer people get those first few years of experience they need to become seniors.

Maybe university was never about learning a job

A computer science degree shouldn't just teach you a specific technology like React. Just like a law degree isn't only about writing contracts and a design degree isn't only about learning Photoshop.

University teaches fundamentals, mental models, critical thinking, domain knowledge and hopefully the ability to learn.

I mean, of course we're not going to university just to learn how to do one specific task at one specific company.

If React disappears tomorrow, my computer science degree doesn't become useless. I still learned a lot of things that have nothing to do with React.

But… at some point, education has to turn into skills that someone is willing to pay for. And it's getting harder to know what those skills will be five years from now.

AI will create jobs too

The World Economic Forum expects major changes in the job market by 2030, but not a collapse. Its 2025 report estimates that 170 million jobs could be created while 92 million could be displaced. That's a net increase of 78 million jobs.

At the same time employers surveyed for the report expect almost 40 percent of the skills required at work to change by 2030.

170 million new jobs sounds pretty good. The problem is that an 18-year-old can't study for a job that doesn't exist yet.

So even if AI creates more jobs than it destroys, you still have the same problem when you're trying to decide what to do with your life now.

Maybe we're optimizing for the wrong thing

The classic question is usually: "What do you want to be when you grow up?"

I think that question is outdated. It assumes that you choose something, become good at it, and then more or less keep doing it. Maybe at different companies, maybe with more responsibility, but the basic idea stays the same.

Maybe putting so much weight on the job title is the problem.

Saying "I'm a programmer" and saying "I know how to understand problems and build software to solve them" are two very different things. The first describes a job. The second is something I can still use if the job changes.

I don't know if I'll spend most of my day writing code five or ten years from now. Maybe I'll spend more time describing what I want software to do (which is very boring in my opinion). Maybe programming becomes much more about reviewing and architecture. Maybe something completely different happens.

I have no idea. And that's kind of the problem with planning it.

The strange thing about being in your twenties

The twenties are already a weird time.

You're supposed to figure out where you want to live, what kind of people you want around you, how to deal with money, what you actually care about, and somehow also what you want to spend the next forty years doing for work.

And you're supposed to make a lot of those decisions with very little experience. Career always seemed like one of the things you could at least somewhat plan. Study this. Become that. Get better at it. Move up. Well, that seems a bit less likely now.

I'm studying computer science while the way we build software is changing in front of me. Some of the things that seemed difficult when I started programming can now be done by an AI in a few seconds.

And I don't think that's necessarily a bad thing. I use these tools myself. They can make me faster and they can take away work I never enjoyed doing in the first place. But it does make me wonder what exactly I'm preparing for. I'm pretty sure people will still build software when I'm 30. My role in building it? I don't know.

So what are you supposed to do?

The obvious answer would probably be something like: learn AI.

And sure, that's probably useful right now. But five years ago the advice would have been different and five years from now it'll probably be different again. So replacing one thing you have to keep up with with another one doesn't really solve the problem.

I don't think anything is really future-proof then. You learn something, it becomes useful, things change and you learn something else. Knowing the fundamentals probably makes that easier. So does actually building things and figuring out why they work instead of just learning whatever tool happens to be popular right now.

And you'll probably have to do that more than once.

The World Economic Forum report I mentioned earlier doesn't only predict increasing demand for AI and technology skills. Employers also expect things like creative thinking, resilience, flexibility and collaboration to become more important.

Which makes sense. Being really good at one tool only gets you so far when everything keeps changing. At some point you just have to get used to learning new ones.

A bad time to plan your life

Back in school, the question was always what I wanted to become. Chef. Developer. Engineer. Whatever. It seemed like there was a right answer somewhere and I just had to figure it out.

I don't really believe that anymore. I can decide what I want to do next. I'm much less convinced that I can decide what I'll still be doing ten or twenty years from now. I might make the right decision at 18 and still end up doing something completely different at 25.

That doesn't make the decision pointless. You still have to start somewhere. It just means you're probably going to make that decision more than once. The further ahead you try to plan, the more assumptions you have to make about a world that's changing while you're making them.

You probably won't guess where you'll be in ten years anyway. Things will turn out differently than you expected, and you'll have to figure it out as you go.

After graduating at 17, I wasn't really sure what I wanted to do next. I remember going to a career fair where I ended up talking to representatives from a hotel. They told me I could spend three days with them, working my way through different parts of the kitchen to see if becoming a chef was actually something for me.

It wasn't just any kitchen either. It was a gourmet kitchen inside a luxury hotel.

So I went.

Living where you work

I didn't have to find a hotel room or somewhere else to stay for those three days. I was allowed to stay in the staff accommodation, which was also where I would have lived if I had started an apprenticeship there.

Wake up, grab some breakfast, and head into the kitchen. All within about 15 minutes. The entire day revolved around the different services. I woke up, ate, worked, took a break, worked again, and went to sleep.

Everything happened in the same place and for the same purpose.

What a day looked like

9:00 in the morning. That was roughly when my day started, although I later realized that I might have been allowed to start a little later because I wasn't actually part of the regular brigade.

The morning started with relatively simple tasks. Preparing fruit. Cutting up a pineapple. Making crêpes. Chopping and preparing whatever was needed.

This was already where I started noticing the difference between cooking at home and working a professional kitchen. At home, I would cook a dish. Here, I could spend the first two hours preparing ten different things without actually finishing a single dish. Everything was about the mise en place: getting every ingredient and component ready so that once service started, everything was exactly where it needed to be.

After breakfast service, we had a short break of maybe 10-15 minutes before heading back into the kitchen for lunch prep. 

This was where a lot of the actual craft came in. Knife skills, preparing ingredients, organization, speed, and all the little fundamentals that you don't really think about when cooking at home. I remember learning things that sounded almost ridiculously simple afterwards. For example, not dragging the sharp edge of my knife across the cutting board when moving ingredients.

Then came lunch service and all the mise en place had a purpose. What fascinated me most was how quickly the atmosphere could change. Before service, people could talk to each other, joke around and laugh. Once orders started coming in and the pressure increased, the kitchen changed. 

After lunch came the afternoon break. We had around three hours off. That sounds like quite a lot of free time, but in reality it mostly split the day into two shifts. Sure, I could go back to my room, lie down, and relax for a bit. But those three hours went by incredibly quickly.

And then it was time to head back into the kitchen. Dinner followed the same basic pattern: mise en place first, then service.

This was also where I got to learn more about actually cooking. How to properly sear something, how much timing and temperature matter, and how quickly you can burn your hands when working around hot pans all evening.

And then there was plating. That's one of the things I still remember well. Everything had its place. The presentation had to be precise and consistent. It wasn't enough for the food to taste right. It also had to look right when it left the pass.

At one point, I was plating caviar using a piping bag. That was a pretty surreal moment for me because, until then, I had never eaten caviar. I hadn't even seen it in real life. This was one of those small moments that made me realize just how far away this kitchen was from what I was used to cooking at home.

Which, considering my obsession with plating food at home, was probably exactly where my younger self would have wanted to be.

The cost of perfection

But that level of precision also left an impression on me for a different reason. The kitchen worked to a standard that, as a guest, you probably take for granted. If something on the plate wasn't right, it didn't go out. And sometimes that meant it went straight into the trash.

I was surprised by how much food I saw being thrown away during those three days. I understood the reason behind it. In a kitchen operating at that level, you can't just send something out and hope the guests won't notice. 

But understanding it didn't make the waste bother me any less. There was a strange contrast to it. So much care went into every ingredient, every technique and every plate. But if the final result didn't meet the standard, none of that mattered anymore.

When service started

The change in atmosphere during service deserves its own section because it's one of the things I remember most clearly. 

The work itself never really scared me away. Most of the time I actually enjoyed it.

During prep, the mood could be genuinely good. People talked. People laughed. Then service got closer, tickets started coming in and suddenly everything had to work at the same time.

Timing mattered. One station being late could affect another. A mistake didn't just stay a mistake. It could slow down the entire service. And the atmosphere changed with it.

I remember one of the cooks getting something wrong while working at the stove. I don't remember exactly what happened anymore, but it delayed things. 

I do remember the chef shouting. A lot.

That's when you realize how different cooking professionally is from cooking at home. If I mess something up in my own kitchen, dinner is ten minutes late. During service, other people are waiting for you.

But I enjoyed it

At this point, this probably sounds like I'm building up to saying that I hated those three days.

I didn't. I really enjoyed working there. I learned an incredible amount in a very short time. I worked with food all day, learned techniques I had never even heard of before, and got to see how professional kitchen actually operates.

And I got to do the things I had always enjoyed doing at home: cooking, searing, experimenting with techniques, and plating.

The job itself wasn't the problem. It was everything around it.

The problem wasn't cooking

I still remember lying in bed around 10pm after one of those days. I was completely exhausted. During the shift, I hadn't really noticed it. There was always something happening, so I never thought much about being tired.

It hit me afterwards. And lying there completely exhausted at 17 made me realize that I didn't want this rhythm every day.

I mean, I still loved cooking. But I started to understand that a job isn't just its core activity. Being a chef isn't only about cooking. It's also about when you cook.

Restaurants are busiest at exactly the times when most other people are free: evenings, weekends and holidays. The three-hour break in the afternoon looked different when I realized why it existed. My free time would be structured around service just as much as my working time.

Maybe I saw it too strictly at 17. Maybe I would have had more free time than I imagined. But I knew I didn't want to build my future around work always coming first. Until then, I had mostly been asking myself what I wanted to do for work.

Those three days made me realize that I should also ask myself what I wanted my life outside of work to look like.

Cooking stayed. The career didn't.

We're often told to think about what we enjoy doing and then ask ourselves whether we can turn it into a career.

I hope everyone who genuinely enjoys something gets the change to make a living from it. But maybe there's another question we should ask first: Do I actually want the life that comes with this job?

Those three days for sure didn't make me lose my love for cooking. I still love cooking today (assuming I have the ingredients and the time). At least for now.

Maybe I'll come back to it in some distant future when AI has taken over my programming work and needs someone to cook dinner.

You owned your movies

Think about it: A DVD is a one-time transaction. You give someone €10. They give you the movie. Transaction over. You don't need an account, recurring payments, or licensing agreements that change depending on your region. No internet connection and no company deciding whether the movie will still be available next year. Put The Lord of the Rings on your shelf in 2005 and, if the disc still works, you still have it today.

Streaming changed this process. Actual ownership became access. And subscriptions changed it from ownership to temporary access to a changing catalog. Take Amazon's licensing documentation as an example. Access is explicitly tied to the period in which someone qualifies as a subscriber. A "Digital Purchase", on the other hand, allows you to stream something repeatedly.

Since I personally think winter is the best season, let's use that for our example. I watch the same movie every Christmas. With a DVD, I ask myself: Where did I put it last year? If I want to stream the movie, I ask myself: Which service has it? Is it included? Is it somewhere else? Do I have to rent it? Is it even available in Germany?

Physically owning the DVD solved the problem of finding the movie.

A movie collection is an identity

I think this is one of the biggest things we lost. Imagine you're visiting a friend. You walk into their room and see this on their shelf: Star Wars, Fight Club, Harry Potter, some Japanese movie, every season of The Simpsons, and a questionable comedy that probably wouldn't even be made today. That collection is autobiographical. It tells you something about that person.

Our collections were part of our physical identity. Books mostly still are, vinyl records are, games sometimes are too, but with movies it mostly stops there. I wouldn't really describe my Netflix homepage as my collection. Maybe it's Netflix's collection, rearranged for me every once in a while.

"Come and look at my collection" just sounds better to me than "Come and look at my Netflix watch history." I mean, they probably contain the same information, but one is a collection and the other is telemetry.

I know that today we share Letterboxd profiles, Spotify Wrapped, playlists, and all of that. I do it myself. Digital identity is replacing physical identity. And maybe a Letterboxd profile tells you much more about someone than a shelf full of DVDs ever could.

And I understand that point, but I still think there's a difference between curation and ownership. A Letterboxd profile says: "These are movies I like." A shelf says: "These movies mattered enough to me that I decided to keep them."

The consequences of choosing a movie

When you rented or bought a movie, you already made your first decision before pressing "Play."

If you walk around a store for 20 minutes and then pay €3 for The Matrix, you're probably going to watch The Matrix afterwards.

Streaming is pretty much the opposite and you can just constantly switch back and forth. Don't like the movie after ten minutes? Back. Scroll. Trailer. Back. Open another app and so on. And suddenly you're back to spending another 35 minutes trying to find a movie.

Now imagine going back to a time when you only had 20 DVDs. You probably watched some of them more than five times. Not because they were the 20 greatest movies ever made, but because they were simply there. Unlimited choice on the other hand means you don't really have to watch them again.

Maybe that's just bias though. Maybe I simply remember the good DVDs. Maybe I just forgot about the bad ones. I still had to watch those because I had already paid for them. That's where streaming has the advantage that we can simply avoid bad entertainment.

But did removing the cost of switching help us find things we enjoy more, or did it just make us better at giving up on things before we start enjoying them?

We gained infinite choice and created a new problem

I think the problem here is that during the DVD era, we only had the problem that we couldn't watch a movie because we didn't have it. In the streaming era, we can watch thousands of movies, but we don't know which one.

Streaming didn't really solve scarcity. Scarcity just moved from content to attention. There aren't too few movies anymore. There are too many movies competing for two free hours.

Ok, recommendation algorithms are supposed to solve that. Netflix doesn't show you its entire catalog. It predicts which movies you might actually like. And yes, without streaming, it would be much harder to discover international niche movies, documentaries, or old TV shows. That's a huge improvement.

While recommendation systems reduce the amount of searching we have to do, they come with the trade-off that platforms increasingly decide which movies are shown to us. With DVDs, discovery happened through friends, stores, magazines, television, and so on.

The extras of DVDs

I almost forgot this was even a thing, but DVDs used to include deleted scenes, bloopers, director commentary, behind-the-scenes footage, interviews, and concept art. You didn't just get the movie. You got a small archive of what made the movie.

For example, if you're interested in filmmaking, you can watch a DVD with director commentary and learn things that could theoretically come close to a two-hour lecture. And all of that in one movie.

Some streaming services offer extras as well but it's not a fundamental part of streaming (and it probably never will be).

But couldn't you just watch all of this stuff on YouTube? Yes, and maybe YouTube actually improved this. Today you can find almost anything there, whether it's cast interviews or something else, and most of it is free. The difference is the context. The DVD gives you the movie and then shows you how the movie was made. The modern internet gives you the movie and says: Go search another platform if you're interested. So the information didn't really disappear, but the package it originally came in did.

Better quality

A normal DVD is obviously worse than 4K streaming. Physical 4K Blu-rays, however, can offer much higher bitrates and lossless or uncompressed audio formats compared to heavily compressed streaming. That's one of the reasons current 4K Blu-ray hardware is still attractive to enthusiasts.

Streaming has bandwidth limitations. Physical media doesn't have to optimize transmission across millions of internet connections at the same time. So somehow, the supposedly "outdated" way of watching a movie can still technically be the better one.

Of course, a lot of people probably don't care. Streaming quality is good enough for most people. Many probably wouldn't even notice the difference. A 4K disc, a player, a good TV, and then a sound system on top of that takes effort and costs a lot of money. Simply opening Netflix on a €500 TV is probably much more attractive to most people than thinking about bitrates. In the end, convenience wins again.

Streaming libraries aren't archives

Streaming makes it feel like every movie ever made is online. But it isn't. Netflix's DVD catalog apparently had around 100,000 titles at its peak. And one reason people kept using it until the end was that it gave them access to obscure, classic, and foreign movies that weren't available through mainstream streaming.

Streaming platforms optimize their catalogs for economic reasons. I mean, that's understandable. They're companies after all. But commercial availability and cultural preservation are two different goals. A movie that only a few people watch might not justify licensing costs, digitization, operations, or whatever else is required. A physical copy doesn't care whether anyone else wants it.

Imagine only 2,000 people in the entire world still care about some mediocre movie from 1987. Commercially? Almost irrelevant. Culturally? Those 2,000 people might still want it to be preserved.

A DVD sitting around in someone's home doesn't have to justify its monthly existence to an algorithm or a licensing department.

Maybe some of you are thinking now: Didn't physical media have exactly the same problem? Yes, that's true. Studios stopped producing obscure DVDs. Discs degrade. Players disappear. Rare releases become expensive. And streaming can actually save some of this content because distributing one additional digital copy costs very little.

Neither commercial streaming nor physical media alone is an acceptable system for preservation. So the real question isn't: DVD vs. Netflix. It's: Who preserves culture when preserving it isn't profitable?

Streaming won for very good reasons

Streaming gives us immediate access. You think of a movie and could theoretically be watching it ten seconds later. Hundreds of movies on streaming platforms don't take up an entire wall. Then there's the portability you get. You can watch on your TV, your laptop, your phone on the train, or pretty much anywhere else. Streaming also gives us accessibility: You can watch shows in their original language and you have audio descriptions. And you don't have to spend €10–30 every single time you want to try something new.

Netflix's history makes this even more obvious. The DVD business kept shrinking until maintaining it no longer made economic sense, while streaming became the core product. That's simply a fact. DVDs lost the fight because streaming solved real problems.

But convenience isn't free

So yes, streaming won. And for good reasons.

But I think we often look at technological progress like this: There is an old solution, then someone invents a new solution, and suddenly we basically have the same thing, just better.

DVDs became streaming. Streaming is more convenient. Therefore, streaming is better. But it wasn't that simple. We didn't replace DVDs with a better version of DVDs. We exchanged one set of advantages and disadvantages for another one.

We gained instant access. We don't have to fill an entire wall with plastic boxes anymore. We can watch movies on our TVs, laptops, or phones. Within seconds, we have access to huge catalogs and algorithms trying to find something we might actually like. That's a pretty good deal.

But in return, we also gave some things up. We traded actual ownership for access. We lost some permanence. Our movie collections disappeared from our shelves and moved into accounts that don't really belong to us. Bonus material became less important. We gained almost unlimited choice, but that also made choosing something more difficult. And even though physical media is considered outdated, a 4K Blu-ray can still offer better quality than streaming.

So was the trade bad? No. If I had to choose between using only DVDs or only streaming for the rest of my life, I'd probably choose streaming. But that's exactly why I find this change interesting. Convenience is incredibly easy to measure: How long does it take until I can watch the movie? How many movies can I access? How much space do they take up? The things we lose are much harder to measure. How much is it worth that a movie actually belongs to you? How much is it worth that nobody can simply remove it? How much is a collection worth when it maybe even becomes part of your identity? I don't know. And maybe that's the problem. We measured pretty much everything streaming added but we barely measured what disappeared with DVDs.

Maybe I'm just nostalgic

There's also a much simpler explanation for everything I've written so far: Maybe I'm just nostalgic. We romanticize old technology because we connect it to a certain time in our lives. Vinyl sounds better. Old video games were better. The early internet was better. Phones were better before smartphones. And now I'm sitting here telling you that DVDs were somehow special.

Maybe in 20 years someone will write an article about how much they miss opening Netflix in 2026.

But yes, I don't need 500 DVDs sitting around in my room. I also don't need to buy every movie I watch. Maybe I stream 95 percent of the movies I watch and physically own the other five percent. The movies I watch every year. The movies that actually mean something to me. The movies I know I'll still want to watch again in ten years. Streaming doesn't have to completely replace owning movies. It can replace owning the movies I never wanted to own anyway.

Maybe we should just treat movies like books. I can have hundreds of books on one small device. I can take them anywhere. But I can still have a bookshelf. Nobody has to choose one or the other. And maybe movies should work the same way.

Streaming is easier. Streaming is faster. And most of the time, streaming is simply the better way to watch something.

I just miss the idea that when a movie mattered enough to me, I could make it mine. And maybe, sometime in the distant future, we'll find a better solution for that.

The original promise of streaming was simple. Everything would be available whenever you wanted it. You could sit down in the evening and binge an entire season without waiting a week for the next episode.

Well... weekly releases seem to be making a comeback. I've forgotten more than one show simply because I had to wait a week for the next episode. But overall, streaming still changed the way we watch movies and TV. 

I still remember recording TV shows because otherwise you'd miss them, or waiting until 8:15 p.m. (the prime time) because that's when the big movie of the week started. Today you just lie down in bed, open an app, and watch whatever you're in the mood for. Broadcast schedules don't matter anymore. 

Another huge improvement was the lack of ads. One of the most annoying things about television was the ad breaks every fifteen minutes. Early streaming didn't have that. You paid for a Netflix subscription and that was it. 

It was also usually cheaper than cable or pay TV, although I'm honestly not sure that's still true today. And maybe the biggest advantage of all was that one streaming service was enough. Most of the movies and shows people wanted to watch were in the same place, so you never had to think about who owned the rights.

Then everything started to fragment. Over time, it felt like every major studio launched its own service. Then Netflix proved just how profitable streaming subscriptions could be. Instead of licensing their movies to Netflix, studios realized they could keep the content, launch their own platform, and collect the subscription fees themselves. From a business perspective, it made perfect sense. From a viewer's perspective, it was the beginning of the mess. Disney made Disney+, Warner launched (HBO) Max, Paramount created Paramount+, and so on. Each company wants to keep its own movies and shows exclusive to its own platform. It's what convinces people to subscribe. The downside is that movies disappear from other services once the licensing rights move back to their original owners. And it's not just movies and TV. Sports have become just as fragmented. The Champions League is on one platform, Formula 1 on another, the NBA somewhere else. And even if you're lucky enough to subscribe to the right service, the movie you want might be on Hulu in the US, Disney+ in Germany or simply unavailable where you live.

As a student I don't have unlimited money. Three streaming subscriptions at around €8 or €10 each might not sound like much, but they add up quickly. If you want 4k or need more than one device, that's another extra charge. 

Subscription growth eventually slowed down, so streaming companies started looking for new ways to increase revenue. That's when ad-supported plans became the norm. The cheaper tiers include ads, while the ad-free versions keep getting more expensive. So you start with the ad-supported plan, eventually get tired of the worse experience, and the premium plan is the only option left.

And sports subscriptions are even worse. If you want to follow everything related to your favorite sport, spending €50 a month isn't unusual. Add regular price increases on top of that, and suddenly streaming isn't the affordable alternative it used to be.

Let's say you've accepted that this is just how streaming works now. Now you have to figure out where your movie actually is. Every app has its own interface, its own search function, and its own way of organizing content. Personally, I've never liked how clunky TV apps often feel. I'm looking at you, Prime (mostly the old Prime).

Eventually you find your movie. After it's over, another interesting recommendation pops up, so you save it to your watchlist. Except every platform has its own watchlist. Sure, every company wants you to stay in its own ecosystem. I get it. But before you know it, you've got movies saved across six different apps. Video quality isn't consistent either. One service includes 4K, while another only offers HDR or Full HD unless you pay more. And sometimes it's almost ridiculous: you watch the first movie on Disney+, then have to switch to another service just to watch the sequel.

There are more movies available than ever before, yet it's somehow harder to find one to watch. At least for me, it's not unusual to spend twenty minutes scrolling through different apps just to watch a ninety-minute movie. Sometimes, after all that searching, I don't even feel like watching anything anymore. And the recommendation algorithms. I mean, they've suggested some genuinely great movies to me so I don't want to pretend that they're completely useless. But a lot of the time they keep pushing the same popular titles.

Ironically, streaming is starting to look a lot like TV again. Ads are back unless you pay for the expensive tier. FAST channels with fixed schedules are becoming more common, because they're cheap to operate and generate advertising revenue 24/7. Bundles like Disney+, Hulu and ESPN+ feel a lot like cable TV all over again. Exclusive licensing means certain shows only exist on one platform. And live events, like boxing on Netflix or exclusive sports broadcasts elsewhere, are bringing appointment viewing back.

But it has consequences. Some people end up turning back to piracy. It's not just because they don't want to pay. A lot of them are already paying for several streaming services. The bigger issue is the convenience. Spotify showed that if legal streaming is more convenient than piracy, most people are happy to pay. Illegal platforms usually put everything into one interface. There's no jumping between apps, no wondering who owns the rights this month and regional restrictions often disappear. Of course there's a reason it's called piracy, but you get me. For every piracy site that is taken down, two more will pop up.

There are probably a few ways to improve things. Cross-platform search should be standard by now. A shared watchlist across services would help. You can track movies with Letterboxd or one of the other apps, but then you're relying on yet another app to organize your entertainment. Bundled subscriptions where you choose three services for a discounted price could also make things simpler. Those are just a few ideas, but they're probably easier said than done.

Streaming is still great, don't get me wrong. The flexibility is unmatched, and the picture quality has never been better. The problem isn't with streaming itself. It's just that the ecosystem became too fragmented. Streaming solved TV's biggest problems. But over time, it slowly recreated most of them. And that's why I'll probably keep asking myself the same question for a while longer: Wait… which streaming service was that on again?

You might also want to check out my macOS app. It solves that problem for me, at least: Wianu

When you hear a new song, your brain immediately starts trying to predict what comes next. Since it doesn't know the structure yet, almost every part of the song is a small surprise. Those surprises activate your brain's reward system, which leads to the release of dopamine. The result is that feeling of excitement that makes you want to hit replay the moment the song ends.

Another reason is something called the mere-exposure effect. People tend to like things more simply because they become familiar with them. The first listen might even feel confusing. By the fifth listen, though, your brain has started recognizing the patterns, making the song much easier to follow. Of course this differs from song to song, but it's also why (at least for me) my favorite songs are almost never my favorites after the very first listen.

With every replay, your brain notices new details. At first you might only focus on the lead vocal. Then you suddenly hear the bass line. Then the background vocals. Then some tiny production detail you've somehow missed ten times already. Every listen adds another layer to your mental model of the song. You're not just hearing the same song over and over again. You're hearing more and more of it.

Another point on my list is the situation you're in when you hear a song. For me, it could be a song I heard at a festival while my friends and I were having the time of our lives. For someone else, it could be a song they listened to during a breakup or while studying for exams. The song becomes linked to those emotions. Later, hearing it again can bring back parts of that emotional state almost instantly.

But if that's true, why can't I listen to the same song every day forever?

One of the brain's most basic learning processes is habituation. Repeated exposure to the same stimulus reduces the brain's response over time. Your brain simply gets used to the song. It already knows what's coming. As a result the emotional reaction gradually becomes weaker.

There are also other factors. Dopamine isn't released simply because something is enjoyable. It's closely tied to anticipation, learning, prediction errors, and uncertainty. Once you know every note, every lyric, and every transition by heart, there aren't many surprises left. The brain has very little left to learn, so the reward signal becomes smaller.

The same thing happens with positive experiences in general. Think about buying a new phone or going on vacation. Eventually those things stop feeling extraordinary because we adapt to them. Our baseline shifts. What once felt exciting eventually feels normal. This phenomenon is called hedonic adaptation.

So if you want your brain to experience that reward again, the best thing you can do is take a break. Try not to listen to the song for a while, maybe a few weeks or even months. During that time, you'll forget some of the small details as well, your predictions won't be on the spot, and those emotional connections might feel new and fresh again. The song feels a little uncertain again. It probably won't sound like the very first listen but it'll sound better than it did after the twentieth replay in a row, trust me. At least for me, when I go back and listen to my most listened to songs from past years, I always find one that I forgot and start loving again.

But why do some songs lose their "magic" after twenty listens while others stay exciting after a hundred?

As I mentioned earlier, not every song works the same way. Research suggests that the more musical layers, harmonic complexity, emotional depth, evolving dynamics, and subtle details a song contains, the longer it tends to stay rewarding. Simpler songs can deliver a huge initial dopamine hit, but they often run out of surprises much faster. So keep this in mind before clicking the "Skip back" key.

A monitor is storage.

A keyboard is storage.

A BIOS splash screen is (maybe) storage.

A favicon is storage.

And yes, here we are.

Every website has a favicon. It's that little icon in your browser tab. Usually you upload it once and then never think about it again. But. A favicon is just an image. An image is just pixels. And pixels are just bytes.

So of course I wondered if I could store something inside one.

The idea

My first thought was steganography. 

Steganography is basically about hiding data in an image without making it obvious. You take a perfect normal photograph and modify a few bits so it secretly contains a message.

The favicon itself (at least in my demo) doesn't need to look like an icon. It could become pure storage.

Every pixel has red, green and blue values. That's three bytes. If I wanted to store text, I could just take the UTF-8 bytes of the text and write them directly into the RGB channels.

The browser doesn't care what those bytes represent. To the browser they're colors. To me in this case they're HTML.

Building a favicon website

I started with a tiny HTML payload:

<h1>Website in a Favicon</h1> 
<p>
	Everything you're reading right now was decoded from favicon pixels.
</p>

The process is pretty straightforward.

First I convert the HTML into bytes using TextEncoder.

Then I prepend four bytes containing the payload length.

The length header is important because the image itself may contain unused pixels at the end. If there's no length value, there's no way to know where the real payload stops.

Then I just start filling pixels: the first byte becomes the red channel of the first pixel, the second becomes the green, the third becomes blue, and then the next pixel, and the next, and the next, until the whole HTML document exists as colored pixels. The result looks like visual noise.

Very small

What surprised me most wasn't that it worked, to be honest. It was how small the resulting image was.

The payload ended up being 208 bytes.

Adding the 4-byte header brings the total to 212 bytes.

Since every pixel stores three bytes, I needed:

• 212 bytes total
• 71 pixels
• A square image large enough to contain them

The smallest square that works is 9x9 pixels.

That's only 81 pixels.

The final stats looked like this:

• Payload: 208 bytes
• Image size: 9x9 pixels
• Capacity: 239 bytes
• Used: 87%

Somehow a whole little website (okayy, html with some styling) fits inside an image that's smaller than the usual favicon.

Reading the website back out

Storing data is only half the problem. The other half is getting it back.

Browsers already have everything needed for this.

1. The favicon gets loaded as image.
2. The image gets drawn onto a canvas.
3. The canvas API lets JavaScript read every pixel.

Once I have the pixel data, I simply reverse the process.

1. Read the RGB values.
2. Reconstruct the byte array.
3. Read the first four bytes to determine the payload length.
4. Extract the payload.
5. Decode the UTF-8 text.

At that point I have the original HTML again.

The browser read a website out of its own favicon.

The important catch

The favicon doesn't actually contain the whole website itself.

It contains the content of a website.

You still need a tiny bootstrap loader to decode the image.

Without the JavaScript the favicon is just a PNG (which contains your website content).

For showing this scenario the site includes a "Render Website" button. It reads the favicon, decodes the HTML, and replaces the page with the reconstructed content.

Is this useful?

No, of course not.

The amount of data you can store is tiny. The page needs JavaScript to bootstrap itself. There are dozens of better ways to distribute a small HTML document.

But at the end its about testing the boundaries, right?

A favicon feels like a very specific thing. It's supposed to be an icon.

But at the end it can just be a PNG.

And a PNG file is basically just bytes.

And this is probably the smallest website I've built…

Alternative approaches

• Store markup directly in SVG favicon and read it on page load.
• Use PNG comment chunks like tEXt, zTXt and iTXt.
• Use the ico file format since it allows multiple icons with different resolutions.

Here is the link to the site: https://www.timwehrle.de/labs/favicon-site/

And if you want to see how it works: https://github.com/timwehrle/favicon

It feels uncomfortable to me to say that I'm good at my job. It feels like bragging. It makes it seem like I'm trying to make myself sound more important than I am. At the same time, it wouldn't have been honest to talk down my work. I stood there, realizing that a simple question didn't have a simple answer.

I kept (over-)thinking about it for a while afterwards.

Not about the question itself, but about why he had to ask it in the first place.

My colleague works on a different team. He doesn't see what I work on every day. He doesn't see the problems I solve. He doesn't see the decisions I make or the things I've built. So how would he know if I'm good at my job? On top of that, he obviously has no idea what I actually do all day.

The answer is pretty obvious. If I never talk about it, there's no way he could know.

I think many people know this feeling. You want to do good work, but you don't want to constantly talk about it. You don't want to put every small achievement on display. You don't want to be the person in every meeting bragging about their latest accomplishment. I wouldn't enjoy being that person either.

So you just work and work.

You do your tasks. You solve problems. You help colleagues. You make sure things keep working, and often before they stop working.

At some point, you realize that a large part of that work is basically invisible to everyone else.

For a long time, I thought that good work speaks for itself. It's a nice idea. If you're good at your job, the right people will notice.

But this only works sometimes in small teams.

The bigger an organization gets, though, the less true it becomes.

CEOs don't see eight hours of your workday (and they don't have to care, to be honest). Department heads don't either. Most of the time, they don't see even 1% of it. They only see the results (and that's probably the only thing they want to see). They see the final output of a long chain of work.

All the small decisions you made on the way usually disappear.

Nobody sees the bug you caught in time. No one sees the discussion that prevented a problem. No one sees the hour you spent simplifying something complicated. No one sees the ten things that didn't go wrong because you were paying attention.

And that's not even criticism.

It would be impossible to see everything.

In a company with hundreds or thousands of employees it's impossible to keep track of everyone's work. Sometimes I can't even keep track of my own work. Instead, people form their opinions based on what they can see and hear.

In that scenario, it's not only what you do that matters. It also matters what others know about your work.

In my opinion, that idea just feels wrong.

The work itself should matter, not the story around it.

Eventually, though, I had to admit that the two are connected.

If you never talk about your work you can't really be surprised when people know very little (or nothing) about it.

That doesn't mean you have to become a self-promoter. It doesn't mean celebrating every completed task or constantly marketing yourself.

There's a lot of space between bragging and being completely invisible.

You can talk about what you're working on. You can explain the problems you've solved. You can share things that nobody else gets to see.

Maybe that's actually part of the job even if many of us (or just me) don't like it.

The interesting thing is that we usually notice bragging much faster in ourselves than in other people. When someone explains what they've been working on in an easy-to-understand way, I usually don't think they're showing off. Well, it depends on how they say it, but usually I just think: Oh, that's interesting. I didn't know that.

It still feels different when it's me.

That said, I suppose you sometimes have to step outside your comfort zone and talk to people about your work.

It had its purpose and I would've made the same choice, maybe. But I recognised a pattern where systems introduce a new responsibility, and then, "new responsibility" started sounding suspiciously like "new service".

I like microservices. Which is probably why this stuck with me. Once a team has a few of them, every new idea begins to orbit the architecture. Need a feature? Service. Need a small extension point? Service. Need to store three values and call an API twice? Obviously, service. Preferably with its own repository, wait… We already have a monorepo. Then just a new folder, pipeline and a name that sounds like a Marvel character. I'm looking at you, Galactus.

The uncomfortable part is that microservices are not bad. That would be too easy. They solve real problems: independent scaling, isolated deployments, clearer ownership, fault boundaries. At the right size, with the right team, under the right pressure, they make sense.

But sometimes we seem to skip the boring question: do we actually need this?

A modular component could be enough. A clean boundary inside the existing app could be enough. A plugin-style extension point could be enough. Build it so it can grow later, sure. But maybe don't immediately give it its own infrastructure passport and send it into production as a tiny nation-state.

There is this fantasy that everything will scale massively one day. The classic "when we have millions of users" argument. Which is technically possible, in the same way that I am technically one viral GitHub repo away from becoming a conference keynote speaker. Possible, yes. Planning your entire architecture around it today, questionable.

Modern software has a tendency to confuse seriousness with complexity. If a thing has message queues, distributed tracing, and twelve dashboards, it feels important. A simple module feels almost suspicious.

Maybe that is what bothers me: overengineering often looks responsible from a distance. Nobody gets blamed for choosing the architecture that sounds scalable. "We made it a microservice" has a professional smell to it. "We kept it simple because the problem was simple" sounds almost naive, even when it is probably the more thoughtful decision.

Still, I get the temptation. Microservices are satisfying. They create neat boxes. They promise separation.

Maybe the better question is not "Should this be a microservice?" but "What pain are we trying to avoid?". If the pain is deployment coupling, team ownership, scaling, or reliability boundaries, then maybe yes. If the pain is simply that the codebase feels a bit untidy, maybe the answer is a refactor, not a new distributed system. And yes, I hate refactors as well.

I did not learn anything new today. More like I re-noticed something old: software usually gets complicated one reasonable decision at a time.

I have a Logitech MX Vertical, which travels between my home machine, work laptop and other devices constantly. At some point I looked at it and thought: this thing has a flash memory. It has to, otherwise how does it remember the DPI setting between plugs. So what if I stored something in it?

Yea, I was bored.

The idea was to treat the mouse like a little USB drive. Since it physically travels between computers, it could technically carry data with it.

Logitech mice communicate using something called HID++, a protocol that they built on top of standard USB HID. It's partially documented by Logitech themselves and partly reverse engineered by the open source community. I wrote a Rust tool to enumerate every feature the mouse exposes. There are 33.

HID++ 2.0 works like this: every device has a feature table. Each entry maps a stable feature ID to a device-specific index. The ID is consistent across all Logitech devices. The index varies per model. So you first ask the device "where is feature 0x2201?" and it tells you "index 0x12 on this mouse". Then you use that index for all subsequent calls. Every call is a short packet: report ID, device index, feature index, function ID, and up to 3 bytes of params. The response comes back in the same shape.

Most are undocumented. There are names like EnableHiddenFeatures and TemplateBytesNVS. That second one sounds exactly like what I wanted: non-volatile storage, index 0x1eb0. I couldn't find any info on it in the docs, but I'm guessing it's something to do with configuration blobs for macros or button templates. Unfortunately, the mouse wouldn't respond to anything, so I couldn't find out.

I spent a while on 0x1c00 (the PersistentRemappableAction) first. Six slots, read/write flags, and so on. Turns out macOS's IOHIDManager blocks the longer HID++ report format you need to actually write to it. The OS just drops the packets. There was no error, no explanation, nothing. I found this out after writing a pile of probe code and staring at empty responses for longer than I'd like to admit. Yes, there are ways around IOHIDManager, like talking directly to the USB device via IOKit, but that's a different story.

Then I looked at the device name register. It looked promising and the write calls were accepted. But the mouse kept saying "MX Vertical" regardless of what I sent. It was just ghosting me.

What did worked was the DPI register (0x2201).

You can read two values from it:

• the current (active) DPI
• a fallback/default DPI

Setting DPI works via function 0x03, and reading via 0x02.

Here's the important (and updated) part:

• Writing DPI only updates the active DPI
• The fallback/default DPI remains unchanged
• On power cycles, the device restores the fallback value

So while the DPI register accepts arbitrary u16 values, they are not persisted across power cycles.

However, there is one interesting property:

As long as the mouse stays powered, the value survives switching computers. You can write a value on one device, move the receiver to another, and read it back.

So the "storage" is only:

2 bytes of cross-computer, session-scoped storage (while the mouse remains powered)

So the original idea: "using DPI as persistent storage" doesn't actually hold up. The only solution would be to "cache" and rewrite it on the mouse on power cycles, but that would defeat the idea.

I also tested a range of other features and write paths (including 0x1e, 0x1f, and several 0x18xx config features). None of them affected the fallback DPI or exposed writeable persistent storage.

At this point, it looks like the default DPI is either:

• stored in a part of firmware not exposed via HID++, or
• only writeable through vendor tooling / signed commands

Even though the original goal didn't work out, the process was still worth it.

I learned how HID++ works. I learned how macOS manages HID devices at kernel level and where it draws lines. I learned that "feature table" and "feature index" are different things and that the IFeatureSet reverse lookup is apparently broken on this device. I learned that the device name register will politely accept your writes and then completely ignore them, which is a deeply relatable response.

None of the knowledge came from reading docs. The Logitech hidpp20 docs exist, but half the features are missing, so I had to try it out. It all was trial and error until it worked. But maybe don't do that with your BIOS.

The result is objectively useless. No hidden storage, no secret USB drive in a mouse. But that wasn't really the point. The point was seeing how far I could get.

The 2 bytes are still there. You just have to keep the mouse alive…

I will dig deeper tho, because the default DPI has to be somewhere in my mouse.

Code is here if you want to explore it yourself: https://github.com/timwehrle/mouse-fs.