Walk into any CS lab right now. How many of us are actually typing out boilerplate from scratch? Exactly. We’re "vibecoding."
If you haven't heard the term, vibecoding is when you give an AI (like ChatGPT, Copilot, or Gemini) the high-level vibes of what you want, and let it handle the messy syntax. It feels like an absolute superpower. We’re spinning up full-stack web apps and complex databases faster than anyone thought possible.
But as placement season starts creeping up, a terrifying question is floating around the lab: Is this actually preparing us for the real world, or are we just getting really good at writing prompts?
I decided to stop guessing and actually ask around. I surveyed 23 of us across different tech degrees to see if our AI addiction is helping or hurting. The results? A little bit of both.
*We Are Completely Hooked *
Let's be real: AI is carrying us. A massive 95.6% of you admitted to using AI "Frequently" or "Always" on coding assignments and projects.
And we aren't just using it to center a div or spin up a quick Express backend for a hackathon. Over half of us (56.5%) are letting AI write our complex algorithms and core logic. We aren't really coders anymore; we are tech managers for AI.
The Whiteboard Panic
Here’s where it gets spicy. When I asked if you felt confident building a full-blown app with AI by your side, 60.9% of you were like, "Bring it on." With an LLM, we feel invincible.
But then I brought up the dreaded whiteboard interview—you know, writing actual logic with a dry-erase marker, where Copilot can't save you? Total panic. 82.6% of us are sweating, feeling anxious, or totally unprepared to explain our code from scratch. We know how to build the app, but we don't necessarily know how the app works.
*"Tech Guilt" and the Debugging Crisis *
So we’re shipping crazy projects, but do we feel good about it? Nope. A whopping 82.6% of us are battling "tech guilt"—that nagging imposter syndrome whispering that we aren't real programmers because AI wrote the heavy logic.
And honestly, our debugging habits aren't helping our case. When the AI code breaks, 56.5% of us don't even look at the error log. We just copy-paste the red text right back into the chat box like, "Fix it, please."
In the industry, code review is everything. But right now, only 17.4% of us actually read and review every line of AI-generated code. The vast majority (65.2%) just kinda skim it, see if it compiles, and move on. We’ve become editors who don't actually read the manuscript.
So... Are We Doomed?
Not exactly. The tech industry is using AI to code faster. But they don't want prompt-jockeys; they want engineers. They want people who can do Code Review, Security Auditing, and System Architecture.
If you use AI to write a sorting algorithm or a complex API route, cool. But you better know why it chose that specific pattern, and you better know if it left a massive security hole in your project.
The Takeaway
Vibecoding is here to stay, and honestly, it's awesome. But we have to stop treating AI like a vending machine that spits out finished projects.
Treat it like a super-smart pair programmer. Let it write the boring syntax, but you have to own the logic. If we don't, that technical interview is going to humble us real quick.
But wait... what do our professors think about this?
We know what we are doing in the labs, but do our instructors actually know we're vibecoding? Are they actively shifting how they grade us, or do they think we just got magically faster at writing boilerplate this semester?
I am taking this investigation straight to the faculty next. Make sure to hit Follow so you don't miss Part 2: The Faculty Strikes Back, where I’ll be dropping the anonymous truth about how our professors view AI in the classroom.
Until then, what’s your take? Are you feeling the tech guilt too, or is this just the new way to work? Drop a comment below and let's debate!
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