Vibe Coding, Explained — and How to Do It Without Regret
The term took over tech in 2025. Here's what vibe coding actually means, where it shines, and how to use AI to build real software you can still trust.
In February 2025, Andrej Karpathy — OpenAI co-founder and former AI lead at Tesla — described a new way of building software: “fully give in to the vibes, embrace exponentials, and forget that the code even exists.” He called it vibe coding. The phrase detonated. Merriam-Webster flagged it as trending within weeks, and Collins Dictionary named it Word of the Year for 2025.
As someone whose whole brand is built on it, let me cut through the hype: vibe coding is real, it’s powerful, and it’s also widely misunderstood. Here’s the honest version.
What vibe coding actually is
At its core, vibe coding means describing what you want in plain language and letting a large language model write the code — then guiding, testing, and reshaping the result through follow-up prompts rather than typing the code yourself. You operate on intent and feedback; the model handles syntax.
The crucial nuance, as developer Simon Willison pointed out, is that not all AI-assisted programming is vibe coding. If you’re carefully reviewing every line the AI produces, that’s just… programming with a faster typist. True vibe coding, in Karpathy’s original sense, means accepting code you haven’t fully read and steering by results. That distinction matters enormously for when it’s safe.
Where it shines — and where it bites
Vibe coding is a superpower for the right job:
- Prototypes and throwaways — spin up an idea in minutes to see if it’s worth building properly.
- Personal tools and scripts — the stakes are low; if it works, it works.
- Learning and exploration — watch how a model solves something, then dig into the parts you don’t understand.
It gets dangerous in exactly one situation: code you’ll depend on but don’t understand. Production systems, anything touching money, auth, or user data, anything a teammate will maintain. AI-generated code can be confidently wrong, subtly insecure, or quietly inefficient — and if you never read it, you won’t catch it until it breaks. The machine still has to emit real, correct output; clean structure and semantic HTML don’t stop mattering just because a model typed them.
Vibe code the prototype. Read the code before it ships. The skill isn’t avoiding AI — it’s knowing which mode you’re in.
2026: from vibe coding to “agentic engineering”
The term is already evolving. By 2026, the frontier has shifted from a human prompting a single model to a human orchestrating multiple AI agents — Karpathy now favors the phrase “agentic engineering.” The default is no longer that you write the code; it’s that you direct agents who do, while you act as architect and reviewer.
That shift is why a quiet piece of infrastructure suddenly matters so much: for agents to do useful work, they need to reach your tools, files, and data safely. That’s exactly the problem the Model Context Protocol solves — and it’s becoming the backbone of agentic development.
How to vibe code without regret
A few rules I actually follow:
- Match the mode to the stakes. Full vibes for prototypes; careful review for anything that ships or persists data.
- Make the AI explain itself. “Why this approach? What are the failure modes?” A model that can justify its code is easier to trust than one that just produces it.
- Keep tests as your safety net. When you’re not reading every line, tests become the thing that tells you the truth. Have the AI write them — then read those.
- Stay fluent. The developers who thrive with AI are the ones who could write the code themselves. Vibe coding amplifies skill; it doesn’t replace it. (This is part of why fundamentals still pay — see why I still value the CompTIA basics.)
- Own the output. “The AI wrote it” is not a defense when it breaks in production. You shipped it; it’s yours.
The honest take
Vibe coding isn’t a gimmick and it isn’t the end of programming — it’s a new layer of abstraction, the way compilers and frameworks were before it. The people getting the most out of it aren’t the ones who stopped thinking; they’re the ones who learned to think at a higher altitude: describing intent precisely, reviewing ruthlessly, and knowing exactly when to drop down and read the code. Embrace the vibes — just keep one hand on the wheel.