I watched a developer with 4 years of experience struggle to write a basic for loop last week.
Not a complex algorithm. Not some esoteric data structure manipulation. A for loop. The kind of thing you learn in week two of any programming course.
He'd been using Copilot and Claude for everything since 2024. When the AI went down for maintenance, he sat there staring at his screen like a toddler whose iPad died on a long car ride.
This is what we've become.
The Muscle Atrophy Nobody Wants to Discuss
Here's the thing about AI coding assistants in 2026: they're incredible. GitHub Copilot X, Cursor, Claude Code—they can scaffold entire applications, debug complex issues, and write tests that actually make sense.
But incredible tools in the hands of developers who've stopped thinking are creating a generation of professional copy-pasters.
I've been interviewing candidates for six months now. The pattern is unmistakable. Developers who started their careers post-2023 can describe architectures beautifully. They know all the buzzwords. They can prompt their way to working code.
Ask them to whiteboard a solution without their digital crutch? Panic. Pure, visible panic.
Their debugging skills are nonexistent. When the AI-generated code doesn't work, they don't trace through logic or check assumptions. They just re-prompt with "this doesn't work, fix it" until something sticks.
That's not engineering. That's gambling with autocomplete.
The Dirty Secret About AI-Assisted Productivity
Let's be honest: most developers using AI assistants aren't 10x more productive. They're producing 10x more code.
There's a massive difference.
I reviewed a PR last month that was clearly AI-generated. 2,000 lines of "clean" code that did what 200 lines could have done. The developer couldn't explain half of it. When I asked why they used a particular pattern, they said "Copilot suggested it."
We're shipping code we don't understand into production systems. We're accumulating technical debt at unprecedented rates while celebrating our velocity metrics.
The AI doesn't know your system's constraints. It doesn't understand your team's conventions beyond what's in the immediate context. It doesn't know that the "elegant" solution it suggested will cause a cascading failure when it hits your legacy payment processor.
You're supposed to know that. But you won't if you've outsourced your thinking.
Here's What Nobody's Saying Out Loud
The developers who will dominate the next decade aren't the ones who are best at prompting AI. They're the ones who can work without it.
When you understand fundamentals deeply, AI becomes a force multiplier. When you don't, it becomes a wheelchair for your atrophied skills—and wheelchairs don't work when you need to run.
I know senior engineers at FAANG companies who deliberately code without AI assistance for a few hours each week. They call it "mental gym time." They're not Luddites. They're strategically maintaining capabilities they know will matter.
Meanwhile, the developer who can't write a for loop is updating his LinkedIn to say "AI-Native Developer" like it's a badge of honor instead of an admission of dependency.
The Coming Reckoning
In 2-3 years, the market will correct. Hard.
Companies are already realizing that their AI-accelerated teams are shipping faster but debugging slower. That the codebase has become a patchwork of AI-suggested patterns that nobody fully understands. That their "senior" developers can't mentor juniors because they can't explain the fundamentals themselves.
The hiring pendulum will swing back to fundamentals. Companies will start testing for actual problem-solving ability without AI assistance. The developers who've been coasting will be exposed.
I'm already seeing early signs. Google's latest interview loop includes a "no AI" coding section. Amazon's been quietly testing candidates' ability to debug without assistance. The smart companies are preparing for the correction.
Are you?
What You Should Actually Do
Before you rage-quit this newsletter, I'm not saying stop using AI. I use it daily. It's genuinely transformative when used correctly.
But here's what you need to do:
1. Implement "Analog Hours"
Spend at least 5 hours per week coding without any AI assistance. No Copilot. No Claude. No ChatGPT in another tab. Just you and the problem. It will feel slow and frustrating. That discomfort is the feeling of your skills rebuilding.
2. Understand Before You Accept
Never accept AI-generated code you can't fully explain. If you can't trace through every line and justify every decision, you don't understand it well enough to ship it.
3. Debug Manually First
When something breaks, resist the urge to immediately paste the error into your AI. Spend 15 minutes debugging the old-fashioned way. Read the stack trace. Form a hypothesis. Test it. You'll be shocked how much you've forgotten.
4. Teach Without AI
If you mentor anyone, occasionally work through problems together without AI assistance. If you can't explain concepts without leaning on generated examples, you've identified a gap in your own understanding.
The Bottom Line
AI coding assistants are the most powerful tools we've ever had. They're also the most dangerous for your long-term career if you let them replace your thinking instead of augment it.
The developers who thrive will be the ones who use AI as a power tool, not a life support system.
Ask yourself: when was the last time you solved a non-trivial problem without any AI assistance? If you can't remember, that should terrify you.
The best time to rebuild your fundamental skills was two years ago. The second best time is today.
Hit reply and tell me I'm wrong. Or tell me you've noticed the same thing in your team. Either way, I want to hear it.
— DevOffScript
P.S. If reading this made you defensive, that's probably a sign you should try a week without your AI assistant. Just saying.