I was helping a developer debug their Vue app last week. The entire thing was written by Claude. Not "assisted by" or "pair-programmed with"—just straight-up written by an AI from a series of prompts.
The bug? A classic race condition that anyone who's written async JavaScript would spot immediately. But here's the thing—they'd never written async JavaScript. They'd only ever prompted for it.
And honestly? I'm not even surprised. There's been copy-paste developers since the dawn of programming. They just changed where they copy it from.
The StackOverflow Era (2008-2020)
Remember when StackOverflow was the dirty little secret of professional development? We'd have it open in another tab, frantically searching for that one answer with the green checkmark.
// copied from StackOverflow
uuid: function () {
return "xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx".replace(/[xy]/g, function (c) {
var r = Math.random() * 16 | 0, v = c == "x" ? r : (r & 0x3 | 0x8);
return v.toString(16);
});
}
I've been copy-pasting this little guy for years.
At least with StackOverflow, you got to see other developers arguing in the comments about why the solution was wrong. Educational, in a way. You'd learn that your code was bad, but also why it was bad, usually from someone with strong opinions about semicolons.
The GitHub Copilot Transition (2021-2023)
Then came Copilot, and suddenly we were copying code before we even knew we needed it. It was like having that one senior developer who types faster than they think, except it was trained on every npm package that ever existed, including the ones with critical security vulnerabilities.
The weird part about Copilot was how it made you feel like you were still writing code. You'd type a comment, hit tab, and boom—instant function. You were "programming" in the same way that heating up a frozen dinner is "cooking."
// Function to validate email
function validateEmail(email) {
// Copilot autocompleted this regex I'll never understand
const re = /^(([^<>()\[\]\\.,;:\s@"]+(\.[^<>()\[\]\\.,;:\s@"]+)*)|(".+"))@((\[[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\])|(([a-zA-Z\-0-9]+\.)+[a-zA-Z]{2,}))$/;
return re.test(String(email).toLowerCase());
}
We went from copying whole functions to copying whole files. Progress?
The ChatGPT Revolution (2023-Present)
Now we don't even pretend to write code. We just describe what we want in plain English and hope for the best. It's called "prompt engineering," which is like calling yourself a "search engineer" because you're good at Google.
The modern development workflow:
I watched a junior developer build an entire e-commerce site this way. They couldn't explain what useEffect did, but they could prompt their way through implementing Stripe payments. It's simultaneously impressive and terrifying.
The Plot Twist: AI-Generated Bugs Need AI-Powered Debugging
Here's the thing nobody talks about: when AI writes your code, traditional debugging becomes nearly impossible. You can't debug code you don't understand. It's like trying to fix a car when you don't know what an engine is.
Last month, we saw a production issue where React was throwing hydration mismatch errors. The developer who wrote it (or rather, prompted for it) had no idea what hydration even meant. They just knew that ChatGPT said to use Date.now() in their component and now production was on fire.
This is exactly why we built an AI code debugger at TrackJS. Not because we wanted to—I actually hate that we need this—but because it's the logical conclusion of where we are. If AI is writing the bugs, AI needs to fix them too.
The debugger sees the full error context: stack traces, browser info, user actions, network requests. It's like having a senior developer who actually understands the code review it, except this senior developer has read every JavaScript error that ever existed and doesn't judge you for not knowing what a Promise is.
The Uncomfortable Truth
We've gone from copying code we don't understand from StackOverflow to copying code we don't understand from AI. The only real difference is the AI doesn't passive-aggressively tell us our question is a duplicate.
But here's what actually bothers me: we're creating a generation of developers who can build anything but fix nothing. They can prompt their way through creating a complex app but can't debug a simple race condition. They know how to ask for code but not how to read it.
What Happens Next?
I don't think we're going back. The genie's out of the bottle, and honestly, the productivity gains are too good to give up. I can build prototypes in hours that used to take days.
The difference is that now the entire stack is becoming opaque. We're building on foundations we don't understand, with code we didn't write, debugging errors we can't comprehend. It's turtles all the way down, except the turtles are language models trained on Reddit comments.
Maybe that's fine. Maybe understanding your code is overrated. Maybe we're entering an era where software development is more about knowing what to build than how to build it.
Or maybe we're setting ourselves up for a spectacular failure when all these AI-generated codebases need to be maintained by humans who've never actually written a for loop.
Either way, at least the debugging tools are keeping up. Our AI code debugger can explain why your AI-generated code is failing, complete with examples and fixes. It's AI all the way down, and I hate that it works so well.
What's your take? Are we evolving or devolving as developers? Have you shipped AI-generated code you don't understand? Drop a comment below—I promise I won't judge. We're all just trying to ship features and go home.
Top comments (4)
This track resonates hard. It’s funny how we’ve traded copy-pasting StackOverflow snippets for copy-pasting AI outputs, and many devs end up in codebases where they don’t really understand what runs under the hood. I’ve been there. When I built orchestration around Claude and launched ScrumBuddy, one of the core lessons was: velocity without comprehension is fragile.
What really bothers me is how quickly errors accumulate once you stop asking “why” or “how,” and just let the model finish what you started. Promise of speed is seductive, but I’ve found the bigger wins come from making small bets on clarity; code reviews, incremental PRs, context validation. Those practices don’t feel glamorous, but they’re what save future you from a night chasing hydration mismatches or weird side-effects.
We should treat understanding as a first-class dev tool. If you can’t trace through what your AI-generated code is doing, you own the maintenance pain later. Maybe the future includes codebases where most stuff is AI-written, but the people maintaining them better really understand their flows now, because the debts run deep when they don’t. Thanks for pointing this out so clearly
Funny and so relevant. I can't wait for a generation that won't even be able to understand what's going on. Maybe we will be gone by that time, though
Fixing Vibe-coder bullshit is my retirement plan.
This is exactly what I needed to hear