Who Are You When Your Job Is Taken by Code?

The question “What do you do?” functions as a silent sorter. AI is crushing entry-level professions and exposing a wound we used to cover up with a business card. But your value was never your position. All it takes is reframing a single question, and your whole life changes.

At parties, it comes right after your name and even before your second sip from the welcome glass. “So, what do you do?” It pretends to be a courtesy, but it is a sorter. Hidden behind those four words is an entire battery of silent questions: what is your status, how much do you make, what did you study, are you even worth me wasting my time on. You answer, and the other party slots you into a pigeonhole before you even finish saying the name of your company.

Psychology has a name for this fusion. Enmeshment. Originally a term for an unhealthy blurring of boundaries in close relationships, where you no longer know where you end and the other person begins. It fits a person’s relationship with their own work with uncomfortable precision. Sometimes we fuse with our position so deeply that we have no idea who we are without it. As long as no one takes it away from us, we do not have to find out. It is convenient. It is also the largest unsecured loan we can ever take out on ourselves.

Code is not taking your job; it is exposing the question

Then comes AI. Dario Amodei, the head of one of the major companies building AI, keeps repeating a warning that few people will likely take to heart from his extensive essays. In them, he speaks of a serious matter. Over a horizon of one to five years, artificial intelligence could eliminate up to half of all entry-level positions for so-called white-collar workers.

The term “white-collar” refers to people working in offices who perform intellectual work. This includes, for example, clerks, lawyers, accountants, or IT specialists. Most of these people, however, hear this as a very distant thunder and return to the work they have been doing for years. So what, they think to themselves, I will do the same thing, just with the resolution to do it a bit more productively.

And that is the big mistake. It is not about AI replacing you overnight. It is about the fact that to even stay in the game, you must become someone who works differently. To co-exist with AI, to learn how to prompt it, to verify its outputs, and, above all, to learn how to reformulate what it is you actually want from it.

Issuing requests to a machine is a new craft skill with its own learning curve, one where people simply stumble occasionally, so it takes everyone a while to master it. That very curve is the dividing line between the work of today and the work of tomorrow. Anyone who believes it is enough to carry on the old way, just faster, will be the first to fall into that fifty percent statistic of those who potentially lose their jobs.

And this is precisely where the wound we used to cover with a business card opens up. Kelly McMenamin worked as a financial analyst and walked around Manhattan, as she herself admits, dressed like a boss for interviews with executives. When she left that prestigious world and started her own small business, she describes it without sugarcoating.

On day one, you are self-employed, no one calls you back, and from “somebody,” you suddenly become “nobody.” Code did not cause this emptiness. It just shone a bit more light on it. It is not taking our work; it is exposing a question we have been putting off for a long time. Who are we when we stop being defined by performance?

Traps we fell into voluntarily

We did not get into this question by accident. A triple trap leads to it, and we set all three of them ourselves. A rather brutal paradox.

The first is the equal sign between value and performance. We have learned to measure what we are worth by what we deliver at work. This logic is seductive and murderous at the same time. If output is what makes me valuable, then without output, I am not valuable at all. Writer Derek Thompson calls this overgrown cult workism, in which work is elevated to a substitute religion. A faith meant to give your labor purpose, belonging, and salvation. The catch is that no religion promises, nor has ever executed, a restructuring.

The second trap is the costume. We do not just wear a position on a resume; we wear it on ourselves like a suit and as a social crutch. McMenamin dressing up for executives is not an anecdote; it is a diagnosis. Clothes tell those around us where we belong socially, and they confirm to ourselves that we have a right to that place. Take off the costume, and the question remains whether there is even anyone underneath it.

The third trap is a single word. Former. Rachel Fortenberry-Deutschel, previously a top manager in the automotive industry, refuses to say it. According to her, “former” sounds too sad, and she is not ready to accept that reality. She is right about how insidiously that word works. It does not stick to what you are doing now; it sticks to what you have ceased to be, quietly whispering that your best chapter has already been written.

From knowledge worker to wisdom worker

This is where the turn comes that I personally am betting on. The new thing you are learning to survive in the workplace of tomorrow is not the faster processing of a task. In speed and data volume, AI will beat you every single time. What you are truly learning is judgment. When to rely on the machine’s output and when not to believe a single word it says. What direction and choice of topic even give meaning to the output in the first place.

What to do with all this in a real world full of real people who need you to be there for them, not to deliver a faster spreadsheet to them. That is not called knowledge work — work with knowledge that anyone can share. That is wisdom work — work with wisdom, with context, and with presence. And so far, no model can design, copy, or download that.

A human being’s value was never a metric. It is their body, their emotions, and their mind together — three inseparable axes on which you stand whole, and which do not fit into a performance column. I have written elsewhere about how yesterday’s world has already ended thanks to AI, as well as about the digital footprint we all drag behind us.

The point comes out the same every time. When we allow ourselves to be turned into a working tool, we cannot be surprised when we are one day replaced by a better tool. The machine only pushed us toward this question sooner than we wanted to answer it.

The work of tomorrow wants you to reformulate what you input into the machine. Life wants you to do exactly the same thing, just looking inward. It is one and the same skill turned one hundred and eighty degrees. Outwardly, you reformulate the prompt. Inwardly, you reformulate the question about the meaning of what you do, which you ask yourself.

So try it right now. Instead of the usual “what do I do,” quietly ask yourself a new version: “what do I like to do?” Your brain and your heart will love this question because it immediately turns to the good within you.

You reformulate the prompt for the machine, and the question for yourself. Same movement, just the opposite direction. You change just one word — like — and you change your whole life. AI never took away who you are. And it never will. It just finally allowed you to ask. Again and out loud: “Who are you?”

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