A Bad Time to Plan Your Life

I can still remember those career days we used to have at school. Sometimes we'd go somewhere, sometimes people would come to our school and tell us about their jobs. The path was almost always the same. It started with school, then university or an apprenticeship. After that came the first job, maybe a few more jobs after that, and eventually people started calling it a career.

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.

The boring answer is probably that most jobs won't disappear overnight. They'll change.

And that still creates a problem. The job you prepared for might still exist. It might not be the job you thought you'd be doing at this point.

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 is mostly because they're hiring fewer young people. That doesn't prove AI caused it. But I think it shows why replacement might not even be the most interesting question.

Maybe AI doesn't have to replace developers to completely change the career. Maybe it just changes who gets the chance to become one.

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.

And that's a pretty good argument. If React disappears tomorrow, my computer science degree doesn't become useless. But I think that only solves part of the problem.

At some point, education has to turn into skills that someone is willing to pay for. And if those skills can change significantly within a few years, then maybe our idea of education has to change with them.

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.

Ok, so maybe AI will create more jobs than it destroys. That's good. It just doesn't make planning your career any easier. An 18-year-old can't exactly study for a job that doesn't exist yet.

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 we should be asking different questions. What kind of problems do you want to become good at solving? What do you actually want to understand? What kind of environment will push you to learn? And maybe most importantly: What gives you options later?

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. 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. I'm not sure what my role in building it will be.

So what are you supposed to do?

The obvious answer would probably be something like: learn AI. But that seems a little ironic.

If the problem is that technology changes too quickly to plan your entire career around one set of skills, betting everything on the current technology doesn't really solve it. So I don't think there's a list of five skills that'll make your career future-proof.

"Future-proof" might be the wrong idea in the first place. Maybe the best thing you can do is get good at learning new things. Understand the fundamentals well enough that changing tools doesn't mean starting from zero. Actually build things instead of only reading about them. Learn how to tell whether something is actually good instead of only learning how to produce it.

And probably accept that you'll have to do this 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. If the tools keep changing, being good at one tool can only get you so far. Maybe the more useful skill is being able to change with them.

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'm starting to think that's not the right way to look at it. Maybe your twenties aren't the decade where you're supposed to figure out what you're going to do for the rest of your life. Maybe that's impossible.

You might make the right decision at 18 and still have to reinvent yourself at 25. And then again at 30. That doesn't mean the decision is pointless. You still have to make a choice. You've still got to start somewhere. It just means that the decision isn't permanent. And maybe that's what makes this such a bad time to plan your life.

It's not like there's no future worth planning for. And it's not like AI is going to take everyone's job. But because 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.

So maybe the goal isn't to correctly predict what you'll be doing in ten years. Maybe it's becoming someone who'll be fine when that prediction is wrong.