AI Will Take Your Job — But Not in the Way You Expect

First, full disclosure: I’m sharing my honest opinions on where I believe the tech industry is heading. You’re free to disagree — but having worked in infrastructure engineering both before and after the rise of publicly available generative AI, I’ve drawn some conclusions worth considering. While I’m speaking from my own sphere of work, I don’t believe this applies only to my domain, I think a lot of us are going to face the same issues.

Let’s start with something I think is clear: we’re living in both the best and worst time to get into development, coding, and the tech industry as a whole.

Back in 2008, the world saw a major financial crash. In the UK, this triggered a decade of cutbacks, austerity, and recession. But one industry kept growing rapidly — tech. That era saw the rise of giants like Netflix, Twitter, and Meta. More recently, companies like OpenAI and Anthropic have developed wildly popular transformer-based AI tools. And from what I’ve seen firsthand, these tools are already transforming how people work.

That’s where the “best time” comes in. This wave of AI-driven innovation is creating new opportunities, and companies need to hire skilled engineers fast — great news if you’re just starting out or looking for fresh opportunities.

But here’s the key word: Skilled.

Skill is becoming harder to measure — because of these very tools. It used to be about how quickly you could solve problems. Engineers were valued because they’d built experience through years of hands-on work. But now, with so many people hooked on the AI Kool-Aid, something important is being lost: the hard-won experience that builds long-term capability.

Both individuals and companies need to understand this: productivity — how fast you can ship a fix or feature — is being prioritised above all else. But pure productivity comes at a cost.

Short-term gains often mean long-term loss.

Picture this: You’ve done your STEM degree and just landed your first job in tech. With today’s AI tools, you can write code and fix problems in almost any language. So you do just that — copy, paste, test, deploy. Job done.

But what you’ve missed is the struggle — the painful, frustrating, hair-pulling effort that actually builds lasting knowledge. Without that, you’re absorbing knowledge like jelly — wobbly and shallow. You’ve read an answer, not earned one.

Now imagine you’ve been at the company three more years, approaching the end of your junior phase. A critical issue hits production, and panic sets in. But this time, AI can’t help — the problem is too complex, too specific. Worse, the AI’s suggestions could actually make things worse.

And now that jelly knowledge fails you. Suddenly, you’re not the person the team turns to — you’re the person looking around, wishing you’d built more depth.

And that brings us back to the title of this post.

AI will take your job — not the one you have now, but the one you hoped to grow into.

Not because that future role no longer exists, but because you won’t have the real experience to qualify for it. No one wants a senior or lead engineer who doesn’t really understand the tech. Over time, the people who are truly valuable will be the ones who know what to do when AI falls short.

That’s my concern — that we may end up with a generation of engineers who skipped the pain, and with it, skipped the wisdom. I might be among the last of those infrastructure engineers who had to build that deep knowledge — simply because AI wasn’t there when Stack Overflow failed me.

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And to end on a positive note:

I’m not saying don’t use AI — I use it every day. The key thing, same as many other things, is how you use it. I actively now push myself to rely on it when I already understand the problem and just want to accelerate the process of generating code I’ll later refine.

What really matters here is being aware of the double-edged nature of these tools. Growth happens in discomfort — in the struggle of not knowing. Embrace that.

Try to create your own boundaries around relying on AI too heavily. And finally, take a step back and ask yourself: “Does the future version of me have the solid knowledge and experience to truly deserve that senior role?”