What Is Vibe Coding? AI-Powered Coding Explained (2026)
Vibe coding is a way of building software where you describe what you want in plain English, let an AI write the code, and stay focused on what you want to build instead of how each line gets written. The term was popularized by Andrej Karpathy in early 2025. It is blazing fast for prototypes, demos, and landing pages - but the biggest trap is "AI slop": code that runs yet is hard to maintain and easy to ship with security holes when you never read what the AI wrote.
by Jasmine, a dev who vibe codes with Claude Code every day.
What is vibe coding?
Vibe coding is a style of programming where you describe what you want in natural language and let an AI write, run, and fix the code for you - you steer by the "vibe" of the result rather than reading every line. Put another way, the human owns the WHAT (what the app should do) and the AI owns the HOW (how it gets written). You look at the output, and when something is off you tell the AI "move this button to the right," "add dark mode," "why does it still break on submit" - and you keep looping until it feels right.
The core difference from ordinary AI assistance: with pure vibe coding, you accept that you will not read all the code. You trust the loop of "describe, run, look, fix in words." That is what makes vibe coding so fast and so approachable, even for people who do not code professionally - and it is also the root of every risk it carries.
The term was coined and popularized by Andrej Karpathy - OpenAI co-founder and former Director of AI at Tesla - in early February 2025 (source: Karpathy's tweet, 02/2025). What started as a half-joking post quickly became a real trend, because it landed right when AI coding agents like Claude Code, Cursor, and Lovable got good enough to turn an idea into a working app in minutes.
Who came up with "vibe coding"? Where the term comes from
"Vibe coding" was coined by Andrej Karpathy, in a post on X (Twitter) in early February 2025. He described a new way of working with AI: "give in to the vibes, embrace exponentials, and forget that the code even exists."
In that post, Karpathy said he mostly gave commands by voice, accepted almost every AI suggestion without reading the diff, and when he hit an error he just pasted the message back for the AI to fix. That is the original spirit of vibe coding: optimize for speed and flow, trading away fine-grained control. Getting this context right matters, because a lot of coverage has flattened "vibe coding" into a "you don't need to know how to code" slogan - something Karpathy never actually said.
How does vibe coding work? (the 5-step loop)
At its core, vibe coding is a conversational loop. Here are the five steps I run over and over, every single day:
- Describe the idea in words. Tell the AI what you want, as specifically as you can: "build me a landing page to sell a course, with an email signup form, in a green color scheme."
- The AI generates code. The agent creates files, writes the HTML/CSS/JS (or React, or a backend), and usually gives you the folder structure and a command to run it.
- Run / preview. You run the app or open a preview to see the real result - this is the "seeing the vibe" moment.
- Describe the fix or tweak in words. Not happy yet? Keep talking: "the submit button does nothing," "the text is too small on mobile," "switch it to English." You do not edit by hand - you describe.
- Loop until it feels right. Go back to steps 3-4 until the result matches the picture in your head.
Illustrative example: one evening I wanted a character counter for meta descriptions. I typed into Claude Code: "create a single-file HTML page with a text box that shows the character count in real time and flashes red if it goes over 160." About 30 seconds later I had a working file; I added "throw in a copy button" and "turn it yellow when it passes 150" - two more rounds and it was done. The whole thing took under five minutes, and I barely read a single line of code.
You: single-file HTML character counter, real-time, flash red if > 160
AI: created char-counter.html (textarea + counter + color warning)
You: add a Copy button and turn yellow when it passes 150
AI: updated - added copy button + 150/160 warning thresholdsThat is the bare-bones picture. If you want to turn this loop into a disciplined process (write clear requirements, let the AI plan, review before you merge), I have a dedicated deep dive: the vibe coding workflow, step by step.
How is vibe coding different from traditional and AI-assisted coding?
A lot of articles lump everything AI-related together and call it "vibe coding." In reality there are three quite different tiers, separated by how much control you keep:
| Criteria | Traditional coding | AI-assisted / spec-driven | Pure vibe coding |
|---|---|---|---|
| Who writes the code | Humans write every line | AI writes, human reviews & edits | AI writes almost all of it |
| Do you read the code? | Yes, deeply | Yes, you read & stay in control | Almost never |
| Speed to a working build | Slow | Fast | Very fast |
| Quality control | High | High (specs, tests, review) | Low |
| Best for | Large, long-lived systems | Real products, team work | Prototypes, demos, testing ideas |
The dividing line is one word: discipline. Pure vibe coding is "go with the flow," while AI-assisted coding still uses AI for speed but keeps you in control - clear requirements (a spec), reading the diff, writing tests, reviewing before you ship. I dig into this spec-first approach in what spec-driven development is. In practice, strong devs move fluidly between all three tiers depending on how risky the work in front of them is.
Popular vibe coding tools in 2026
You can group the vibe coding tools of 2026 into three buckets based on how you interact with them:
- Agents in the terminal (CLI):
- Claude Code - Anthropic's command-line agent, strong on multi-file projects and editing code directly in your repo. If you are not sure what it is, read what Claude Code is.
- OpenAI Codex CLI - a similar terminal agent, integrated with the OpenAI ecosystem.
- AI-native IDEs:
- Cursor - a VS Code-based editor that lets you chat with and edit code right inside the IDE, good for people who still want to see the code.
- GitHub Copilot - a code-suggestion and chat assistant, deeply integrated into your editor and GitHub.
- No-code / app builders (describe an app):
- Lovable, v0, Bolt - type a description and get a web app with a UI immediately, geared toward prototypes and landing pages.
- Replit Agent - build and deploy an app right in the browser, no local setup needed.
Rule of thumb: if you need control and are building something real, go CLI or IDE; if you need a super-fast demo or MVP for a non-coder, use an app builder. Exact pricing for each tool shifts over time, so check it directly before you commit.
The upsides of vibe coding
Why did vibe coding blow up the way it did? Because the benefits are very real:
- Speed. Things that used to take days (standing up a landing page, a small internal tool) can now be done in hours, sometimes minutes. MVPs reach users far sooner.
- Lower barrier to entry. Founders, PMs, and marketers who do not code professionally can build their own prototype to validate an idea, instead of waiting on the engineering team.
- Dirt-cheap prototyping. If it is wrong, throw it away and redo it - the cost of experimenting is close to zero, which is perfect for the product-market-fit stage.
- Learning by doing. Beginners see real code run, then read back what the AI wrote to understand it gradually - a hands-on way to learn, if you take the time to review.
Let me be blunt: these benefits are real and worth having. The problem is not using AI - it is what you use it for and whether you have the discipline to review.
The real downsides and risks (when vibe coding fails)
This is the part most articles dodge, or only graze with a throwaway "watch out for tech debt." Here it is in concrete terms:
- Junk code - "AI slop." The AI produces code that runs but is messy, duplicated, and hard to read. As the codebase grows, adding new features gets slow and fragile. That is the hidden cost of speed. I have a dedicated piece on how to avoid AI slop when you vibe code.
- Accumulating tech debt. Because nobody reads carefully, bad design decisions stack on top of each other. By the time you need to fix the root, you are basically rewriting.
- Security risk. Vague prompts make it easy for the AI to generate vulnerable code (leaked API keys, no input validation, broken authorization). The UK's cyber security agency (NCSC) has warned about the risks of AI-generated code that is not carefully reviewed.
- Hard to debug. When something breaks and you do not understand the code the AI wrote, you are stuck - you do not know where to start, and all you can do is paste the error back and hope.
- Skill atrophy for beginners. If a junior only ever vibe codes and never reads or understands the output, their foundation thins out and it gets harder to level up.
Bottom line: vibe coding is not "bad," it is just not right for every kind of work. Knowing that boundary is what separates the smart AI user from the one who buys the hype.
When you SHOULD and SHOULD NOT vibe code
| DO vibe code | DON'T vibe code |
|---|---|
| Prototypes / MVPs to validate an idea | Revenue-generating production products with many users |
| Landing pages, portfolios, intro sites | Complex systems with many integrations |
| Small internal tools, automation scripts | Handling sensitive data (payments, health, personal) |
| Learning, trying new tech, building demos | Team projects that need shared standards, review, long-term maintenance |
My simple rule: the higher the stakes, the higher the discipline. For throwaway work, vibe away. For anything that touches money, user data, or has to live a long time - switch into AI-assisted mode with specs, tests, and review.
Vibe code with more discipline using a good process and toolkit
The way to patch vibe coding's biggest weakness is not "stop using AI," it is to add a frame of discipline to the loop: write clear requirements, let the AI plan before it codes, and always review before you merge (see the detailed vibe coding workflow). Some devs go further and use AgentKit kits for Claude Code - prebuilt skills, subagents, and review workflows - to force a tighter process instead of letting go entirely. If you want to try it, take a look at the AgentKit bundle — now $149 (from $198); if not, even writing yourself a few review rules already cuts down the slop noticeably.
Frequently asked questions (FAQ)
Do you need to know how to code to vibe code?
Not to get a first working build - that is exactly why it appeals to non-coders. But to ship a real product and keep it maintainable, knowing how to code (even the basics) helps you review, catch bugs, and fix things when the AI gets stuck. "You don't need to know how to code" is only true for prototypes.
How is vibe coding different from no-code?
No-code is drag-and-drop inside a predefined interface, so you are limited to the blocks you are given. Vibe coding produces real code from natural language, so it is far more flexible - but in exchange you have to deal with the code when something goes wrong.
Is vibe coding safe for real products?
Only if you add discipline: review the code, write tests, and check security before you ship. Pure vibe coding (never reading the code) is not suitable for revenue-generating products or anything handling sensitive data.
Where do you start learning vibe coding?
Pick one tool (Claude Code, Cursor, or Lovable) and build a small, throwaway project like a landing page or a personal tool. Practice the loop of describe, run, fix in words - then gradually read back the code the AI wrote to understand it.
Which vibe coding tool is best in 2026?
There is no absolute "best": Claude Code is strong for multi-file projects in the terminal, Cursor suits people who like an IDE, and Lovable/v0/Bolt are great for fast web demos for non-coders. Choose based on the work you do and how much control you want.
Will vibe coding replace programmers?
No. It replaces the repetitive typing of code and lowers the barrier for prototypes, but system design, architecture judgment, security, and decision-making still need humans who understand the code. The role shifts toward review and direction - it does not disappear.
Conclusion and next steps
Vibe coding is a genuine leap in speed: fantastic for prototypes, demos, and learning, but it needs discipline once you build something real, to avoid junk code and security risks. Understanding the boundary - when to go with the vibe and when to tighten up - matters more than which tool you pick. For your next step, read the vibe coding workflow, step by step to do it properly, and how to avoid AI slop when you vibe code to keep your codebase clean from day one.