"The best way to predict the future is to invent it." — Alan Kay
For the past few months, one question keeps circling back to me, and I still can't answer it: am I still necessary?
Not the reckless, late-night kind of anxiety you get from reading a sensational tweet. Something quieter. A low hum that shows up in the moments when I hand off a whole task to an agent — not a single line, but the entire thing: read the codebase, plan, write, run the tests, fix what broke — and it just... does it. I gave a nudge, a sentence or two of direction, and watched it carry the work to the end. A strange feeling: relief and a small grief, at the same time.
This post isn't a prediction about the future. I don't have the authority for that. It's just what one ordinary developer has been thinking, fearing, and — eventually — making peace with.
Part 1: The moment things shifted
I remember the first time I handed an agent a real task — not a snippet, a whole task. Not to show off — because a deadline was breathing down my neck.
I needed a feature added across an unfamiliar codebase: a new endpoint, the data layer behind it, validation, tests. Normally this would cost me a couple of days: trace how the existing code is wired, read the docs, try, fail, Google, copy something off Stack Overflow, then bend it all to fit. This time, I wrote a few sentences describing what I wanted, and let it run. It read the codebase on its own. It made a plan. It wrote the code, ran the tests, saw two of them fail, and fixed them — without me. I mostly watched.
It wasn't perfect. I nudged it once or twice. But it carried the work to the end, to a degree that was almost unsettling.
In that moment, I didn't feel as happy as I'd expected. I felt something closer to sadness. Those couple of days of "wrestling" — the thing I secretly took pride in, the feeling of conquering a hard problem — had just collapsed into a few minutes of me reading a diff. The struggle wasn't shrunk; it was handed off entirely. The emotional reward was gone. Only the result remained, and a question of where, exactly, I had been in all of it.
And I asked myself: if the hard part, the part that makes me feel like a programmer, is being done for me by a machine — what's left of me?
Part 2: Opportunity — easy to talk about, hard to feel
Everyone talks about the opportunities. And they're not wrong.
AI removes the friction tax of starting. The hardest part of many tasks isn't the doing — it's overcoming the initial inertia: the blank screen, the syntax you've forgotten, the boring boilerplate. AI swallows that part whole. I prototype faster. I dare to try things I used to avoid simply because they were "too much hassle."
It raises a person's ceiling. A developer who knows a little frontend can now stand up a respectable backend. Someone shaky on DevOps can read a Terraform file with AI sitting beside them, explaining as they go. The lines between "roles" are blurring. Personally, I feel wider than before — though not necessarily deeper.
It's the most patient teacher I've ever had. I can ask a dumb question at 2 a.m. without fear of judgment. "Explain it to me like I'm five" — and it does, for the tenth time, without ever getting annoyed.
But here's the thing few people say out loud: this opportunity is not distributed evenly.
The person who benefits most from AI isn't the beginner — it's the one already skilled enough to know when the agent is wrong. It does the work, but I'm still the one who signs my name to the result. That ability to smell a bad piece of code, to sense an architecture that'll collapse in six months, to read a diff and feel that something is off — that still lives in humans, and it comes from experience, from those days of wrestling.
The irony: AI needs me to have lived through the very struggle it just took away from the next generation.
Part 3: Crisis — not the one we think
When people say "crisis," they usually mean losing their jobs. Robots replacing humans. I think that fear is aimed at the wrong target.
The real crisis, for me, is subtler.
The crisis of understanding
When code comes too easily, we risk operating systems we don't truly understand. The code runs, the tests are green, we ship. But when it catches fire at 3 a.m., who understands it deeply enough to save it? There's a vast difference between "this code works" and "I understand why this code works." AI makes that gap easier to ignore than ever before.
The crisis of identity
For years, I defined myself by my ability to write code. It was a skill, a source of pride, the thing that set me apart from outsiders. Now the skill of "writing" is becoming a commodity. My value is shifting from writing to judgment — knowing what to build, why, and how to build it right. That's an uncomfortable shift, because it asks me to let go of part of the person I used to be.
The crisis of quiet erosion
This is the one I fear most. Skills don't vanish overnight. They atrophy slowly — the way I forgot how to read a paper map after ten years of GPS. Every time I let AI handle something I should have thought through myself, I'm trading a sliver of future capability for present convenience. Most of the time, that trade is worth it. But if I don't make it consciously, one day I'll wake up and realize I've become someone who only knows how to press buttons.
Part 4: What I'm trying to believe
I don't have a tidy conclusion. But I have a few things I keep reminding myself.
One — distinguish between being lazy and being freed up. AI handling the boring work isn't permission to rest; it's an invitation to spend my energy on what only humans can do: understanding the user's real problem, making hard trade-offs, taking responsibility. If I use that freed-up time to coast, that's on me — not the tool.
Two — deliberately keep my "muscles." Now and then I turn off autocomplete on purpose and write something from scratch. Not for efficiency, but for training — like an athlete who still runs even though cars exist. Deep understanding is a muscle, and muscles need to be used.
Three — the best student is the one who asks the right questions. In an age where answers are dirt cheap, value moves toward the question. Knowing what to ask, which answers to distrust, when "good enough" is enough and when it isn't — that's the skill of the future. And fortunately, it's a very human one.
Four — the tools change, the craft doesn't. My job was never "typing code." It was always solving problems with software. The keyboard, the IDE, the language, the framework — all temporary tools. AI is one too. A good craftsperson doesn't fear a new tool; they learn to wield it.
A final word: a human is still needed here
Let me return to the question I opened with: am I still necessary?
I think the answer is yes — but "necessary" in a different sense than before.
Not necessary as a fast typing machine. Necessary as someone who cares — cares whether the thing I'm building actually helps anyone, whether it's safe, whether it's kind. AI can generate an endless stream of code. It doesn't know why something should be built, and it doesn't bear the consequences when things go wrong.
That void — the void of meaning, of judgment, of responsibility — still needs a human to stand in it.
And I don't think that's a bad thing at all.
What about you?
Top comments (0)