🤖 Vibe Coding: The New Coding Craze or Just Hype?
Here’s a fun fact for you: “vibe coding” is officially a thing now—no joke, Merriam-Webster even gave it a shoutout! It’s defined as "writing computer code in a somewhat careless fashion, with AI assistance." Sounds like the wild west of coding, right? Cowboy hats off to all the vibe coders out there riding that AI wave.
But hold up—before you start letting AI write your next big project while you relax, let’s press pause and think: is vibe coding really where the software industry wants to head? Spoiler alert: It’s complicated.
🚀 The AI Hype Train: All Aboard, But Destination Unknown
You've seen the headlines: AI writes 25% of Google's code, some say it might replace entire product teams... hype, hype, hype! While these stats sound like the future is now, the reality from someone neck-deep in AI-assisted testing is that current Large Language Models (LLMs) are not quite there yet.
I do use AI regularly—for tiny prototypes or auto-filling mock data in tests—but ask it to help tackle real coding struggles? That's where the magic fizzles out.
Just last week I wrestled with a gnarly Node subprocess issue involving Playwright (aka "ESM hell")—and guess what? No matter which AI model I tossed at the problem, nothing beat good ol’ StackOverflow or my own debugging.
🎯 Takeaway: AI is great at the boring, boilerplate stuff. But the tricky, one-off edge cases that eat your calendar? AI’s still waving a white flag.
🤯 Reviewing AI-Generated Code: A Headache Waiting to Happen
Think AI code is hassle-free? Fear not, friend — reviewing AI’s handiwork might just become your new cardio.
There’s an infamous Reddit saga where folks giggled (and cringed) at PRs opened by GitHub Copilot on the .NET runtime—some truly bizarre, bonkers stuff.
Source: Reddit
You see, if you want to actually trust AI code, you’ve gotta fully understand the problem it’s trying to solve—often more than you’d need for a teammate’s code.
Check this wild GitHub comment chain showcasing a classic Copilot hallucination—AI confidently making stuff up in a convoluted PR debate!
Source: GitHub
🎉 Fun, but also terrifying reminder: AI isn’t a flawless coder... yet.
🧪 Testing AI-Generated Chaos: The Recipe for Disaster?
So where does all this AI excitement leave testing? Here’s the hot take: using AI to test AI-generated code without any human touch is a big no-no.
Imagine this scenario — your AI-made app gets tested by AI-made tests that were created by AI. Infinite loop of AI patting its own back. You smell the meme-worthy disaster? Yep, like those classic Spider-Man pointing-at-Spider-Man memes describing relationship dramas but in code form.
Science backs us here too: it’s called model collapse — when AI trained only on AI outputs gets worse and worse over time. Kind of like playing “telephone” with robots.
So: humans must be the gatekeepers, the final approvers. AI-assisted testing is fab, but full buy-off? That’s gotta be you.
🤝 So, What’s the Balanced Way Forward?
At my startup Octomind, we have AI believers and AI skeptics. The consensus? AI is a powerful tool, nothing more.
Used thoughtfully, it speeds up the grunt work, helps with tricky automations, and sprinkles some AI magic on test locators and visualization. But left unchecked, it can backfire spectacularly.
🚦 Be excited, but cautious.
It’s not doublethink — it’s just keeping your feet on the ground while your eyes scan the sky for the AI stars.
💡 If You’re Curious...
Check out Octomind’s app — a free platform aiming to make end-to-end testing smarter and smoother, with AI helping out where it truly counts.
Wanna debate vibe coding, AI, or testing headaches? Find me here:
- Tweet me: @Germandrummer92
- Peek my GitHub: @Germandrummer92
- Join us at the Octomind Discord with @daniel.draper
Cheers,
Daniel Draper Lead Octoneer at Octomind
Remember: AI can be your co-pilot, but don't hand over the steering wheel just yet! 😎