That Copilot subscription is actively rotting your brain.
I've watched it happen in real-time. Developers who could once architect systems from scratch now can't write a for-loop without Claude holding their hand. And somehow, we're all pretending this is "productivity."
It's not. It's atrophy with extra steps.
The Uncomfortable Pattern I Keep Seeing
I've been reviewing code from teams across three different companies this year. The pattern is unmistakable.
Developers who joined after 2023 write fundamentally different code than those who came before. Not better. Not worse in obvious ways. Just... hollow.
The code compiles. It passes tests. It even follows conventions. But ask them why they chose that approach, and you get blank stares. Or worse: "That's what Claude suggested."
They've outsourced their judgment to a statistical model.
Last month, I watched a developer with "3 years experience" spend four hours debugging a race condition. The AI kept suggesting fixes. He kept applying them. None worked because he didn't understand what a race condition actually was.
He'd never had to learn. The AI had always just... handled it.
The Three Skills That Are Dying
First: Reading documentation. When's the last time you actually read the docs for a library you use daily? Not skimmed. Not asked AI to summarize. Actually read them.
I asked this at a team standup recently. Twelve developers. Zero hands went up.
We've created a generation of engineers who treat official documentation like ancient Sanskrit. Why read when you can prompt?
Second: Debugging through reasoning. Real debugging is hypothesis-driven. You form a mental model. You predict behavior. You test predictions. You refine the model.
AI-assisted debugging is just slot machine pulls. Try this fix. Nope. Try this one. Nope. Try this one. Oh, it works! Ship it.
You never learned why it works. So you'll hit the same bug again. And again.
Third: System design intuition. This one terrifies me most. The ability to look at a problem and instinctively know the right architectural approach. That comes from years of making mistakes and understanding consequences.
You can't develop intuition by accepting AI suggestions. Intuition requires struggle. It requires failure. It requires that painful moment of realizing your approach was fundamentally wrong.
AI removes all of that. And with it, the learning.
Here's What Nobody's Saying Out Loud
The dirty secret is that AI coding tools are optimized for short-term velocity, not long-term capability.
Every time you accept a suggestion without understanding it, you're trading future competence for present convenience. You're taking out a loan against your own skills.
And the interest rate is brutal.
I've seen "senior" engineers in 2026 who can't implement a basic sorting algorithm without assistance. Not because they're stupid. Because they never had to. The AI was always there, like a calculator that made them forget arithmetic.
Companies love this in the short term. Tickets close faster. Features ship quicker. Metrics go up.
Then they hit a genuinely hard problem. The kind AI can't solve because it requires deep understanding of their specific system. And suddenly their team of "10x developers" is completely stuck.
I've watched this happen three times this year alone.
The Prediction That Will Age Well
In 2-3 years, we're going to see a massive skill bifurcation in the industry.
One group will be developers who used AI as a tool while maintaining their fundamental skills. They'll command premium salaries because they can actually think about code.
The other group will be prompt engineers cosplaying as developers. They'll produce volume but crumble under complexity. They'll be the first laid off when companies realize their "AI-augmented" team can't solve real problems.
The irony is savage: the people most dependent on AI will be the most replaceable by it.
If your only skill is translating requirements into prompts, you're not an engineer. You're a middleman. And middlemen get cut.
What You Should Actually Do
Before you rage-quit this newsletter, I'm not saying delete Copilot. I use AI tools. They're genuinely useful for boilerplate and exploration.
But here's my rule: Never accept code you couldn't have written yourself.
If AI suggests something and you don't fully understand it, that's not a gift. That's a trap. Stop. Read. Learn. Then decide whether to use it.
Once a week, code without AI. Completely. Feel that friction. That discomfort is your brain actually working.
When you hit a bug, try to solve it yourself for at least 30 minutes before asking AI. Form hypotheses. Test them. Build that mental model.
Read documentation for one tool you use regularly. Not AI summaries. The actual docs. You'll be shocked what you've been missing.
Ask yourself: when was the last time you solved a hard problem through pure reasoning? If you can't remember, that should terrify you.
The Real Test
Here's a challenge. Tomorrow, try to explain your last three AI-assisted code changes to a junior developer. Not what the code does. Why that approach. Why those patterns. Why those tradeoffs.
If you can't do it fluently, you didn't write that code. You just transcribed it.
And transcription isn't engineering.
The tools aren't going away. They're getting better. Which means the gap between developers who use AI wisely and those who depend on it will only grow.
Choose which group you're in. Before the market chooses for you.
Hit reply and tell me I'm wrong. Or tell me you've noticed the same thing. Either way, I want to hear it.
— DevOffScript
P.S. If you felt personally attacked by this, good. That discomfort is the first step toward actually fixing the problem.