Vibe Coding: Is It the Future or a Fancy Shortcut?

The Dev Twitter Discourse No One Can Agree On

A few weeks ago, I was deep in a cPanel debug session, SSH open in one tab, error logs scrolling like a horror film in another, when a colleague sent me a DM. It read something like: "Just vibe coded an entire SaaS in a weekend. Didn't write a single line manually."

My first reaction? Eye-roll. My second reaction after I actually shipped the fix and sat down was curiosity. Because honestly, the replies were not full of mockery. They were full of other developers saying, "same."

Vibe coding is the term that's exploded in early 2025, coined (or at least popularized) by Andrej Karpathy in a post where he described a new mode of working with AI: you don't carefully engineer prompts or review every token, you just vibe. You describe what you want in plain language, the AI generates it, you run it, tweak it by feel, and iterate fast. Less architecture, more energy.

Now, is this genius, laziness, or something in between? I've been testing it seriously for the last couple of months across Laravel backends, quick JS utilities, and some Flutter UI work. Here's my honest, no-hype take.

What Exactly Is Vibe Coding?

Let's be precise, because the term gets thrown around loosely.

Vibe coding is a workflow where the developer primarily communicates intent to an AI (like Claude, GPT-4o, or GitHub Copilot) in natural language, accepts large chunks of generated code with minimal manual editing, and iterates by describing problems rather than directly debugging them.

It's distinct from:

• AI-assisted coding, where you still write most of the code, but use AI for autocomplete or suggestions
• Low-code/no-code, which abstracts away code entirely into visual interfaces
• Prompt engineering, which focuses on crafting precise instructions for predictable outputs

Karpathy's original framing was almost meditative: you're not fighting the code, you're flowing with it. You describe the vibe of what you want, the AI materializes it, and you course-correct like a film director giving notes rather than an actor learning lines.

The tools most associated with this workflow right now are Cursor, Windsurf, GitHub Copilot (Agent Mode), Bolt.new, and Claude (especially via Projects or the API). All of them share one thing: they're designed to take large contextual instructions and produce working, runnable code, not just snippets.

How It Actually Works in Practice

Here's a real example from my own workflow last month. I needed a quick internal tool, a Laravel + Livewire dashboard that pulled server metrics from a few VPSes via SSH and displayed them in a table with color-coded status indicators.

Old me would have: scaffolded the Laravel project, set up the models, written the SSH command handler, built the Livewire component, styled the table, debugged CORS on the API endpoint, etc. Maybe 6–8 hours of focused work.

Vibe coding me opened Cursor, set up a project context, and typed something like:

Build a Laravel 12 Livewire dashboard that:
- Connects to 3 remote servers via SSH using credentials stored in .env
- Runs `df -h`, `free -m`, and `uptime` on each
- Displays results in a responsive table with green/yellow/red status badges
- Refreshes every 30 seconds automatically
- Has a "Last checked" timestamp per server

What came back wasn't perfect. The SSH library it chose (phpseclib) needed a version tweak for Laravel 12 compatibility. The polling interval used a Livewire method I'd have done differently. But here's the thing, it was 80% done in under 10 minutes. The remaining 20% took me maybe 45 minutes of review, correction, and hardening.

That's not magic. That's a genuinely different productivity curve.

The workflow typically looks like this:

1. Set context aggressively:- Paste in your stack, constraints, and existing code structure
2. Describe outcome, not implementation:- "I want a dashboard that does X", not "write a Livewire component with a poll method."
3. Run fast, fail fast:- Execute the code immediately, don't read every line first
4. Report errors as-is:- Copy-paste the exact error back to the AI without paraphrasing
5. Iterate by feel:- "This works, but the table looks off, make it more compact and add pagination."
6. Review before shipping:- This step is non-negotiable (more on that below)

Where Vibe Coding Shines (And Where I've Used It)

I won't pretend every use case is equal. Here's where I've found genuine leverage:

✅ Internal tools and prototypes

The SSH dashboard I mentioned above. Also, a quick admin panel for a client using RadSystems that needed custom extensions. A Flutter screen I built to demo an idea before committing engineering hours to it. These are all low-stakes, high-speed scenarios where vibe coding absolutely earns its name.

✅ Boilerplate-heavy tasks

Laravel resource controllers, migration files, API route groups, Docker Compose setups, anything where you know what you want but the writing is tedious. I've started treating these like dictation rather than composition.

✅ Debugging with context

Pasting a 50-line function and saying "this is supposed to do X, it's doing Y, here's the error" is surprisingly effective. The AI doesn't vibe at your code, it diagnoses it. Faster than Stack Overflow for non-obscure issues.

✅ Learning unfamiliar territory

I'm not a Flutter expert. I'm a 55% Flutter guy. Vibe coding has let me build real Flutter UIs while absorbing patterns I'd otherwise spend days reading docs to understand. It's like pair programming with someone who's read every Flutter doc ever written.

The Traps I've Fallen Into (So You Don't Have To)

Here's where I have to be honest, because a lot of the discourse around vibe coding is suspiciously positive.

❌ Security blindspots are real

AI-generated code will use patterns that work but aren't hardened. I've generated Laravel code that:

• Stored sensitive config values in ways that'd leak in logs
• Skipped CSRF validation on an internal-only route (still bad practice)
• Used a deprecated cryptography method that was technically functional, but shouldn't be in production

None of these were catastrophic. All of them required human review to catch. If you vibe code and ship without reading, that's on you, not the AI.

❌ Architecture debt accumulates fast

Vibe coding optimizes for working now, not scalable later. I've seen generated code that created tight coupling between classes, skipped interfaces, mixed concerns that should be separated, and named things in ways that'd confuse a team. If you're building something that'll outlive the weekend, the architect in you still needs to show up.

❌ The hallucination tax

AI will occasionally invent a function, library method, or config option that doesn't exist. In my experience, this happens more with niche packages. I've had it reference a phpseclib method signature that was from an older version, and a Docker Compose directive that was subtly wrong. Always verify against actual docs for anything that doesn't immediately work.

❌ You can lose the thread

When you're vibing hard and iterating fast, it's easy to end up with code you don't fully understand. I've caught myself 45 minutes into a session thinking, "wait, how is this actually working?" That's a sign to slow down, read the code, and make sure you could explain it if asked.

Vibe Coding vs. Traditional Development: A Practical Comparison

My honest read: these aren't competing approaches. They're different modes for different contexts. A senior dev who vibes codes intelligently, sets context well, reviews output critically, and knows when to take the wheel manually is genuinely more productive than one who refuses to engage with AI at all. But a junior dev who vibes codes without understanding what's being generated is building on sand.

My Current Workflow (The Hybrid Approach)

After months of experimenting, here's where I've landed:

I vibe code the scaffolding. I write the critical logic.

• Need a new API endpoint with CRUD operations? Vibe it.
• Do I need the authentication middleware that the endpoint uses? I'm writing that manually.
• Need a migration file for a new table? Vibe it.
• Need the query that runs a financial report? I'm writing and reviewing that myself.
• Need a Docker Compose for a new service? Vibe it.
• Need the deployment script that touches production? Manual, reviewed, and tested.

The pattern: the further from production consequences, the more I vibe. The closer to real data, real money, or real users, the more deliberate I get.

Conclusion & Key Takeaways

Vibe coding is real, it's genuinely useful, and it's not going away. But the internet discourse has a tendency to frame it as either the death of programming or a dangerous toy for amateurs. It's neither.

Here's what I'd leave you with:

• Vibe coding is a workflow, not a replacement for skill: The devs getting the most from it are experienced ones who know when the output is wrong
• Context is everything: The quality of what you get is directly proportional to how well you describe your stack, constraints, and goals
• Security and architecture don't vibe themselves: Build a review habit into the workflow, not an afterthought
• Use it to go faster on the boring stuff: Save your deep focus for the decisions that actually matter
• You still need to understand your code: If you can't explain it in a PR review, you're not done yet

What's next: If you want to try this seriously, start with Cursor or Windsurf on a personal project, not a client system. Set up a .cursorrules system prompt that describes your stack and coding standards. Run one week, comparing your output speed. I think you'll surprise yourself.

Are you already vibe coding, or are you skeptical? I'm genuinely curious whether you've had it save you or burn you, drop it in the comments. The more specific the story, the better.