What Is Vibe Coding? A 2026 Guide for Developers

Per Harald Borgen -

In February 2025, Andrej Karpathy fired off what he later called a "throwaway tweet" and accidentally named an era. "There's a new kind of coding I call 'vibe coding'," he wrote, "where you fully give in to the vibes, embrace exponentials, and forget that the code even exists." Within a year, vibe coding was Collins Dictionary's Word of the Year for 2025.

The line that made it famous is also the line that makes it risky. In the same post, Karpathy described his workflow with disarming honesty: "I 'Accept All' always, I don't read the diffs anymore." That is the whole idea, and the whole problem, in a single sentence.

This guide explains vibe coding in plain language: what it actually means, where the term came from, how the workflow goes, which tools enable it, and the honest benefits and risks. It ends with the question every learner is really asking - is vibe coding a good way to learn to code, or a fast way to skip the part that matters?

What Is Vibe Coding?

Vibe coding is a way of building software where you describe what you want in natural language and let an AI write the code, often without reading or reviewing it.

The "without reviewing" part is not a side detail. It is the definition. The clearest line on this comes from developer Simon Willison, who argued that "when I talk about vibe coding I mean building software with an LLM without reviewing the code it writes." By that standard, if an LLM writes every line but you read, test, and understand it all, you are not vibe coding. You are using the model as a fast typing assistant. The vibe is gone the moment you start checking the diffs.

That distinction sounds pedantic until you feel its consequences. Reading code is a skill, and whether you have it decides whether vibe coding is a superpower or a trap. The term went mainstream fast, with Collins crowning it Word of the Year for 2025, but the mainstream version often blurs the line that Willison drew so sharply.

Where Did the Term Vibe Coding Come From?

Vibe coding was coined by Andrej Karpathy, a founding member of OpenAI, in a short post on February 2, 2025, that unexpectedly went viral.

His original framing is worth reading in full, because most later definitions drift from it. As Karpathy put it, "I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works." He described talking to the AI by voice, accepting every suggestion, and pasting error messages straight back to the model until problems went away, all without reading the underlying changes.

The detail people forget is the scope he gave it. Karpathy was describing weekend projects and throwaway experiments, "where you fully give in to the vibes" and "forget that the code even exists." It was a description of a playful mode, not a production methodology. The term then did what good terms do: it escaped its author. A shower-thought tweet became an industry buzzword, then a dictionary entry, and somewhere along the way the "it's for throwaway projects" caveat fell off.

How Does Vibe Coding Work?

Vibe coding works through a short loop: you describe what you want, the AI generates code, you run it, and you nudge the AI to fix what broke, usually without reading the code.

This pattern can be named The Vibe Coding Loop, and it has four steps:

  1. Describe. You state your intent in plain language: "build me a landing page with a signup form" or "add dark mode."
  2. Generate. The AI writes or changes the code, frequently across several files at once.
  3. Run. You execute the result and see what happens in the browser or terminal.
  4. Nudge. When something breaks, you paste the error back to the AI and ask for a fix, then loop again until it works.

The defining trait is what is missing from that loop: a step where you read and understand the code. Skip that step and you are vibe coding. Add it back, and you are doing disciplined AI-assisted development, which Willison pointedly says is something else entirely.

Under the hood, many vibe-coding tools run on coding agents, systems that plan a task, use tools to edit files and run commands, and revise their own work in a loop. That autonomous engine is what makes "say stuff, run stuff" feel like magic. If you want the mechanism rather than the vibe, What Is Agentic Coding? breaks down how those agents actually operate.

Vibe Coding vs Traditional Coding

Vibe coding trades understanding for speed: you get a working first version fast, but give up the deep familiarity with your code that traditional coding forces on you.

The two are not really rivals so much as different points on a spectrum of how much you read. Vibe coding optimizes for getting something running. Traditional coding, whether you type every line yourself or review what an AI writes, optimizes for knowing exactly what is running and why.

Dimension Vibe coding Traditional coding
How you express intent Plain-language prompts Code you write or carefully review
Who writes the code The AI, start to finish You, or an AI you supervise line by line
Do you read the code? Often not Yes, that is the point
Speed to a first working version Very fast Slower, more deliberate
Maintainability over time Fragile once it grows Stronger; you understand what you built
Best suited for Prototypes, demos, learning to build Production apps, teams, anything you must maintain

The honest summary: vibe coding is unbeatable for going from idea to a clickable prototype in an afternoon. Traditional coding, or reviewed AI-assisted coding, is what you want the moment other people, real users, or real data depend on the result. The dividing line, once again, is whether anyone read the code.

What Are the Best Vibe Coding Tools in 2026?

The main vibe coding tools in 2026 fall into three categories: natural-language app builders, AI-first code editors, and the terminal or cloud coding agents underneath them.

You do not need a leaderboard to understand the landscape. The tools differ mostly in how much of the project they generate and how much you ever see.

  • Natural-language app builders turn a prompt into a running web app, often with a visual preview and a hosted deployment. Tools in the Lovable, Bolt, and v0 category aim this squarely at people who want a product, not a codebase.
  • AI-first code editors put a powerful agent inside the editor. Cursor is the best-known example: you describe a change and it rewrites across your files, which you can review or simply accept.
  • Terminal and cloud coding agents are the engines many of the above run on. OpenAI Codex and Claude Code take a task and work through it autonomously, in your terminal or in the cloud.

One clarification matters for learners: no Scrimba course is named for vibe coding, Cursor, Codex, or Claude Code, and you should be skeptical of any site that claims one. What Scrimba teaches is the foundation underneath these tools, the ability to read and judge the code they produce. For complete beginners who want to build with AI assistance from day one, the free Learn to Code with AI course covers HTML, CSS, and JavaScript while using ChatGPT to generate and debug code. To go further with using generative AI, including Anthropic's Claude, to write and debug code, Scrimba's "AI for Web Developers" specialization on Coursera teaches exactly that. For a direct tool-by-tool comparison, see Claude Code vs Codex vs Cursor, and for the wider field, the best AI coding assistants in 2026.

Is Vibe Coding Good or Bad? The Benefits and Risks

Vibe coding is good for prototypes and learning to build fast, and risky for anything you must maintain or secure, because code you never read is code you cannot trust.

That is the core trade-off, and it is worth stating plainly once: vibe coding moves the bottleneck from writing code to trusting code you did not read. Everything else follows from that.

The benefits are real. You can go from a sentence to a working prototype faster than ever, and you can do it with little or no coding background. It is genuinely motivating for beginners, and it saves time on the parts you understand. Among developers who use AI agents, 70.7% report spending less time on tasks, according to the 2025 Stack Overflow Developer Survey. Karpathy's original use case, throwaway weekend projects, is exactly where vibe coding shines.

The risks show up the moment the project stops being throwaway:

  • Security. Unread code hides unread mistakes. CodeRabbit's December 2025 State of AI vs Human Code Generation report found that AI co-authored pull requests carried roughly 1.7 times more issues overall, and 2.74 times more security vulnerabilities, than human-written code.
  • Maintainability. A codebase you did not read is a codebase you cannot confidently change. Small features pile up into something nobody understands, including the person who "wrote" it.
  • Trust. Developers already sense this. In the same Stack Overflow survey, only 32.7% said they trust the accuracy of AI output, and that is from people who use these tools every day.
Vibe coding does not remove the hard part of software. It relocates it. The work used to be writing correct code. Now the work is judging whether the code you were handed is correct, and you cannot judge what you never read.

It is also not as effortless as the name suggests. Andrew Ng, who has been blunt about the hype, told an AI conference that "vibe coding" is a bad name for what is actually "a deeply intellectual exercise." His own experience: "When I'm coding for a day with AI assistance, I'm frankly exhausted by the end of the day." Steering a model toward working software takes constant judgment, not just good vibes.

Is Vibe Coding a Good Way to Learn to Code?

Vibe coding is a good way to start building and stay motivated, but a poor way to learn fundamentals, because skipping code review skips the moment when understanding forms.

Here is the tension for anyone learning. Shipping a working app on day one feels incredible, and that momentum carries people past the point where dry tutorials lose them. But if you never read the code, you build a dependence, not a skill. The first time the AI gets stuck on a real bug, and it will, you have no way to help it, because you never learned what any of it does.

The fix is not to swear off AI. It is to learn to read what it writes, so you can drop into vibe mode for a prototype and switch back to understanding when it counts. That is a teachable skill, and it is best learned by doing rather than watching. Scrimba's scrim format is built around that difference: instead of watching code scroll past in a video, you pause and edit the instructor's code directly in the browser, which is the same read-and-judge muscle that separates a developer who directs AI from one who is at its mercy.

A sensible learning path looks like this:

  • Build with AI from the start. The free Learn to Code with AI course teaches HTML, CSS, and JavaScript while using ChatGPT to generate and debug code, the closest thing to a guided, honest version of vibe coding.
  • Learn the language AI writes most. The free Learn JavaScript course (9.4 hours, built with Mozilla's MDN) gives you the fluency to read what an AI produces for the web.
  • Then build AI-powered apps yourself. The AI Engineer Path (Pro) covers agents, RAG, and context engineering for when you want to build the tools, not just use them.

For a broader look at fitting AI into your workflow without losing the plot, How Web Developers Can Use AI goes deeper on the practical habits.

Frequently Asked Questions

Who coined the term vibe coding?

Andrej Karpathy, a founding member of OpenAI and former head of AI at Tesla, coined "vibe coding" in a post on February 2, 2025. He described it as fully giving in to the vibes, accepting all AI suggestions, and no longer reading the code diffs. The term went viral and became Collins Dictionary's Word of the Year for 2025.

Is vibe coding the same as AI-assisted coding?

No. AI-assisted coding is a broad category that includes reviewing and understanding the code the AI writes. Vibe coding is the specific subset where you do not review the code, accepting and shipping it based on whether it appears to work. Reviewed AI output is closer to using the model as a typing assistant.

Is vibe coding good for production apps?

It is risky. Production apps need to be secure, maintainable, and debuggable, and code that nobody has read tends to fail on all three. Studies show AI-generated code carries more security vulnerabilities than human-written code. Vibe coding suits prototypes, demos, and learning to build, not systems real users depend on.

Do you need to know how to code to vibe code?

No, you can vibe code with no coding background, which is much of its appeal. But you cannot safely ship or maintain the result without reading the code. The moment something breaks in a way the AI cannot fix, you need real understanding to step in, which is why fundamentals still matter.

Will vibe coding replace developers?

No. Vibe coding shifts a developer's effort from writing code to specifying tasks and judging output, both of which still require skill. Someone has to decide whether the generated code is correct, secure, and maintainable. That judgment becomes more valuable as the typing becomes cheaper.

Key Takeaways

  • Vibe coding means building software by describing it to an AI in natural language and accepting the code without reading or reviewing it.
  • The term was coined by Andrej Karpathy in February 2025 and named Collins Dictionary's Word of the Year for 2025.
  • It works through a loop, describe, generate, run, nudge, with the telltale missing step being reading the code.
  • Reviewing the code is the dividing line: reviewed AI output is disciplined AI-assisted coding, not vibe coding.
  • Benefits are real for prototypes and beginners, including faster builds and a low barrier to entry; risks land hardest on security and maintainability, with AI-authored code showing 2.74x more security vulnerabilities in one 2025 study.
  • Vibe coding is a strong way to start building but a weak way to learn fundamentals, because skipping review skips understanding.
  • Scrimba's interactive courses, from free Learn to Code with AI to the AI Engineer Path, build the read-and-judge skills that make AI a tool instead of a crutch.

Vibe coding is not going anywhere. The name is too good and the workflow too fun for prototyping. The developers who thrive with it are the ones who can switch modes: vibe their way to a quick demo, then read the code the moment it has to be real. The way to earn that second gear has not changed. Learn the fundamentals by doing, get fluent at reading code, and let the AI handle the parts you could already do yourself.

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