Tired of the AI hype letting programmers slack off? Meet Freecoding — a rebellious approach to programming that values deep learning, minimal tooling, and hands-on craftsmanship over fast and flaky AI-generated “vibes.” Say goodbye to sloppy code and vendor lock-in!

🚫 What Is Vibe Coding, Anyway?

If you’ve been lurking around Twitter threads or hacker spaces lately, you’ve probably heard about this hot new trend called vibe coding — basically, letting AI (large language models aka LLMs) do the heavy lifting while you chill and ride the wave of “efficiency.” Sounds dreamy, right?

Well, hold your horses, because that efficiency often comes with a nasty side of junky spaghetti code, confusing system architecture, and a rapidly eroding programming skill set. It’s like trading your bike for a Tesla that randomly stalls.

🛠️ The Freecoding Manifesto: Swing That Hammer Yourself!

Meet freecoding — a term I’m coining (yes, I’m that guy) as the antidote to vibe coding. Inspired by the thrill and discipline of free climbing, freecoding means:

Producing software using the minimum tooling necessary, constantly questioning what’s truly essential to your workflow, and, above all, learning deeply rather than outsourcing your brainpower.

Imagine pruning your dev setup back to basics — no fancy autocomplete, no AI copilots, just your wits, docs, your terminal, a solid editor (hello Neovim!), and a relentless spirit.

🧗‍♂️ Why I Tried Freecoding (And You Should Too)

My first flirtation with vibe coding was... well, let’s say messy.

At a hackathon, I tried to let an AI helper scaffold a CLI tool for a version control system. The results? Confident AI nonsense that barely worked, chock full of outdated API calls, bad design choices, and a head-scratching amount of frustration.

The funny (or tragic) part? I spent way more time debugging AI’s mistakes than writing the code myself.

Freecoding felt like swinging the hammer yourself: slower, maybe, but you don’t miss the nail. You learn why the code is broken when it is — rather than just praying the AI spits magic this time.

💡 The AI Reality Check: Next-Token Predictors Aren’t Thinking

Here’s a fun fact: despite the hype, LLMs like ChatGPT are just glorified next-word predictors. They guess what token comes next based on training data — but they don’t understand semantics or program logic.

That means they can confidently generate wrong code and leave you with a delightful mess of bugs and technical debt.

Consider this:

Even a 0.01% chance per token of error accumulates quickly over thousands of tokens.
Errors cascade, causing semantic drift that sends your code off the rails.
Tests generated by AI can be wrong, passing you flawed code that’ll haunt you later.

So no, your AI buddy isn’t a genius — it’s a gambling addict on a slot machine, hoping you’ll hit “Generate” one more time.

⚔️ Old School Programmers: The True Heroes

I tip my hat to the coders before us who survived without AI crutches, digging into system design and debugging by hand.

They learned first principles, understood their tools inside out, and built reliable software that you could trust.

I found freedom trying freecoding on projects involving Zig and Nix — two bleeding-edge tech stacks with barely any AI training data. AI kept hallucinating nonsense or throwing syntax errors.

So I stopped leaning on AI and started walking the hard but rewarding path of actually learning.

💸 The Hidden Cost of Vibe Coding: Vendor Lock-In and Wallet Drain

Spoiler alert: vibe coding doesn’t come cheap.

Take tools like Cursor IDE — they lure you in with “free” prompts, then charge $20/month for 500 requests and $0.04 per extra request. That’s literally paying per AI-generated line of code.

And when the investor hype fizzles? Expect prices to skyrocket as AI companies scramble to stay afloat, squeezing every ounce of cash out of “vibe coders.”

It’s the classic vendor lock-in trap — become dependent on AI tools, then be extorted to keep using them.

Meanwhile, real programmers who actually know their craft will keep thriving.

🤝 Can Freecoding and Vibe Coding Coexist?

Maybe.

If you’re a master craftsman who understands your tech deeply, AI can be a turbo boost — a tool to speed up certain tasks while you still learn and think critically.

But the moment you outsource learning and problem-solving to AI without understanding, you’re just setting yourself up for a crash and burn.

Vibe coding is for those who want quick cash with minimal effort — the low-code equivalent of watermark theft in art.

Freecoding is for those who want to respect the craft, build real skills, and produce quality code.

📝 Final Thoughts: Respect the Process, Choose Your Path

I’m firmly in the freecoding camp, calling out vibe coding for what it is: a shortcut that ruins your skillset and hands over your hard-earned knowledge and cash to faceless corporations.

Sure, AI is a powerful instrument, but just like any tool, it’s only as good as the person wielding it.

So next time you’re tempted to press that “Generate” button, remember: muscles aren’t built by robot lifters. They’re forged by you, swinging that hammer, making mistakes, learning, and growing.

Freecoding isn’t just a style; it’s a rebellion against lazy programming.

— Varun Narravula

Huge shoutout to friends Zachary Howe and Vignesh Guruswami for the feedback that polished this rant into a manifesto.

📚 Further Reading and Footnotes

If you’re curious about some of the references and deeper thoughts, the original article linked plenty of gems including dissection of AI economics, quotes from programming classics, and some hilarious venting on the state of modern dev tools.

P.S. I’m looking at you, Copilot — sometimes you’re more of a headache than a helper. 😜