Vibe Coding – A Beginner’s Guide: Building Software with AI Instead of Code

Vibe coding is the big trend in software development for 2025/2026. The term was coined in early 2025 by Andrej Karpathy, one of the co-founders of OpenAI and the former head of AI at Tesla. The idea: you describe in plain language what you want, and an AI writes the code for you. No programming in the classical sense. No memorizing syntax. Just talk, test, iterate.

Sounds too good to be true? Partly, it is. In this guide I will give you an honest look at what vibe coding can really do, which tools are out there, who it is for, and where the limits are. No hype, no nonsense.

What is vibe coding, actually?

The name goes back to Karpathy’s original tweet: you give in to the “vibes”, forget that the code even exists, and let the AI do its thing. In concrete terms, you open an AI tool, type something like “Build me a web app to track my expenses”, and the AI generates the complete code. HTML, CSS, JavaScript, database wiring, all of it.

The crucial part: you do not have to understand the code. You only judge the result. Does the app run? Does it look good? Does it do what it should? If not, you tell the AI what is wrong, and it fixes it. Software emerges from a dialogue instead of from manual typing.

One important distinction: vibe coding is not the same as “AI-assisted programming”. There is a whole spectrum. At one end sits pure vibe coding, where you accept everything blindly and only look at the outcome. At the other end sits AI-assisted engineering, where you use AI as a tool, review the code, and make deliberate architecture decisions. Most professionals operate somewhere in between. Understanding that gradient is the key.

The 70 percent problem: why vibe coding alone is not enough

Here comes the reality check that most vibe coding articles conveniently skip. In practice, vibe coding gets you to a working first version extremely fast, roughly 70 percent of the way. The app runs, looks okay, the core features work. It feels like magic.

But the last 30 percent? They are brutal. Typical patterns emerge: you fix one bug and the AI produces two new ones. You want to add a feature and suddenly something else falls apart. The AI proposes solutions that miss the actual problem. You go around in circles. This is the so-called “two steps back” pattern, and it costs you more time than the first 70 percent combined.

The reason is that complexity grows exponentially. At the beginning, the tasks are isolated: a form here, a table there. But as soon as features have to work together, you need a real understanding of data flows, state management and side effects. That is exactly what pure vibe coding cannot deliver.

The good news: for many use cases, those 70 percent are entirely sufficient. An internal tool, a prototype, a weekend project. There, “good enough” really is good enough.

Who is vibe coding for?

This is where it gets interesting. Vibe coding is not equally useful for everyone. Think of two axes: how technically experienced are you, and how much control do you hand over to the AI?

A perfect fit if you: are a marketer, an SEO professional, a founder or a designer and want to test an idea quickly. You need a prototype, an internal tool or a small project, but you have no budget for a developer. Or you are simply curious and want to understand what is possible. This is where vibe coding unfolds its full potential: the AI handles the entire implementation, and you only steer the direction.

Be careful if you: want to build a production-ready app for real users, work with sensitive data, or need something that must be maintained over the long term. Vibe-coded apps demonstrably contain more bugs and security holes and are harder to maintain. A CodeRabbit study from late 2025 found that AI-generated code has 1.7x more severe issues than human-written code, with a 2.74x higher rate of security vulnerabilities.

Interesting for experienced developers: Even if you can program, vibe coding has its place. For rapid prototyping, generating boilerplate or exploring new frameworks, “vibe mode” can save an enormous amount of time. The trick is to switch deliberately between full vibe and controlled engineering, depending on the task.

The vibe coding tool landscape in 2026

There is a whole range of tools by now. I sort them into two categories: app builders (you describe, the AI builds the whole thing) and AI IDEs (you work in a development environment while the AI assists). These are the most important ones:

App builders: from prompt to finished app

Bolt.new is my favorite for quick prototypes. You type your prompt and Bolt generates a complete web app right in the browser. React, Next.js, Tailwind, all included. You see a live preview and can iterate. Perfect for landing pages, small tools or MVPs. The free tier is enough to try it out. Bolt also has an “Enhance” button that automatically turns your rough prompt into a structured specification, which is extremely helpful for beginners.

Lovable is a Swedish startup, similar to Bolt, but with a focus on beautiful UIs. It generates React + Tailwind apps with a Supabase backend. Especially good for people who care about design. It also supports importing Figma designs; you read that correctly, you can upload a Figma mockup and Lovable builds the app from it. That said, there were reports in 2025 about security vulnerabilities in generated apps, so do not use it blindly for production.

Replit Agent lives inside Replit, an online development environment, and its agent mode lets you build apps via chat. Big advantage: hosting is built right in. Downside: in mid 2025 there was a prominent case in which the agent deleted a production database even though it had been explicitly instructed not to change anything. So be careful, and make sure you use the sandbox feature.

GitHub Copilot Agent Mode is Microsoft’s answer to the vibe coding wave. It is integrated directly into VS Code. Less “magical” than Bolt or Lovable, but more solid for people who already have some experience.

AI IDEs: for more control

Cursor is the top dog among AI IDEs. It is built on VS Code, but with AI deeply integrated. Composer mode is essentially vibe coding inside a professional IDE. Karpathy himself mentioned Cursor in his original tweet. Ideal if you want to switch between “full vibe” and controlled coding.

Windsurf (Codeium) is an alternative to Cursor with a similar feature set. It has an agent mode called “Cascade” that can edit multiple files on its own. You can start for free.

Claude Code is Anthropic’s terminal-based tool. No GUI, no IDE, pure command line. That sounds intimidating, but it is extremely powerful for people who like working in the terminal. Claude Code reads your entire project, understands the context and can make large changes across many files. Since 30 June 2026 it ships with Sonnet 5 (claude-sonnet-5) as its default model. If you want to go deeper, have a look at my Claude Code cheat sheet.

The most important rule: plan first, prompt second

This is the biggest mistake beginners make: they open a tool and start typing straight away. “Build me an app for XY.” The result? Usually chaos. The AI makes a hundred decisions for you, from the technology stack to the database structure to the UI design, and most of them are not what you wanted.

The better way: write yourself a small specification first. It does not have to be a novel. A short description is enough. In the industry this is called a mini PRD (Product Requirements Document), or simply a SPEC. Nine times out of ten, the AI will suggest a needlessly complicated approach if you do not steer it in the right direction beforehand.

# How to plan before your first prompt:

# 1. Write a mini spec (3-5 minutes is enough)
# ------------------------------------
# Project: Expense tracker
# Goal: Simple tool to record monthly expenses
# Audience: Just me (personal use)
#
# Features (in priority order):
# - Add an expense: amount, category, date, note
# - Overview: table + bar chart per category
# - Export as CSV
#
# Technical constraints:
# - No backend, localStorage is enough
# - Responsive, dark design
#
# Deliberately NOT included:
# - No login/auth
# - No cloud sync
# - No multi-user

# 2. Use your tool's plan mode
# ------------------------------------
# Many tools (Cursor, Cline, Claude Code) have an
# explicit plan mode. Use it!
# Prompt: "Here is my spec. First create a plan of which
# files and components you would set up.
# Do not code yet, just explain the approach."

This one intermediate step saves you hours of debugging later. When the AI starts from a clear plan, it makes better decisions. And you can spot problems before any code gets written.

What vibe coding looks like in practice

Enough theory. Let me show you what a typical vibe coding workflow looks like. We will build a simple expense tracker app, step by step.

Step 1: The first prompt

You open a tool like Bolt.new or Lovable and type your first prompt. The most important thing here: be as specific as possible. A vague prompt gives you vague results.

# Bad (too vague):
"Build me an expense app"

# Good (specific):
"Create a web app for tracking expenses.
Features:
- Form with fields: amount, category (dropdown), date, description
- Categories: Food, Transport, Housing, Leisure, Other
- Table with all expenses, sortable by date
- Total per category as a simple bar chart
- Store data in localStorage (no backend)
- Modern dark design with Tailwind CSS"

The second prompt is ten times better because the AI knows exactly what it is supposed to build. The more context you provide, the fewer iterations you need afterwards. That is the core principle: garbage in, garbage out. Or, put positively: good context in, good result out.

Step 2: Use visual context

A hugely underrated trick: screenshots. If you have an idea of how your app should look, take a screenshot of a similar app or draw a rough sketch. Upload the image directly with your prompt. Most tools (Bolt, Lovable, Cursor) can process images, and the result is dramatically better than text alone.

This works for debugging too. If the app looks off, take a screenshot and add “The button overlaps the table, do you see that? Please fix it.” AI models understand visual context surprisingly well these days.

Step 3: Review the result and iterate

The AI generates the app. You take a look. Usually 80 percent is right on the first attempt, but something is always off. The chart shows the wrong values, the sorting does not work properly, the design is weird. This is where the iteration loop begins:

# Feedback prompts, or how to iterate effectively:

# Visual feedback:
"The bar chart shows wrong values. The Food category has
150 euros in expenses, but the bar only shows a tiny
fraction of that. Please fix it."

# Feature extension:
"Add an export button that downloads all expenses as CSV.
Format: Date;Category;Amount;Description"

# Bug report (Karpathy style, just paste the error in):
"When I delete an expense, the app crashes with this
error: TypeError: Cannot read properties of undefined
(reading 'amount'). Please fix it."

Remember this: you are the product manager, the AI is the developer. You test, give feedback and prioritize. The AI implements. That is the heart of vibe coding.

One critical habit: test after every change. Open the browser console (F12 or Cmd+Option+J) and check whether errors show up. Small, incremental tests prevent problems from piling up until you find yourself in front of an unsolvable mess.

Step 4: Set checkpoints

This is the step almost every beginner skips, and the one they regret the most. Before you request a big change, save the current state. Every single time. In Bolt you can set checkpoints. In Cursor or Claude Code you use Git:

# Git basics for vibe coders, the three commands you need:

# Save the current state (before every big change!):
git add .
git commit -m "Expense app: base version works"

# When everything is broken, go back to the last good state:
git checkout .

# Show all previous versions:
git log --oneline

# Pro tip: set checkpoints at feature boundaries.
# "Login works" -> commit
# "Dashboard shows data" -> commit
# That way you can always return to a stable point.

Without checkpoints, you will eventually face this situation: the app was perfect yesterday, today it is broken, and there is no way back. That is the fastest way to start hating vibe coding.

The 7 most common beginner mistakes

I see these mistakes constantly among people who are just starting out with vibe coding. Save yourself the frustration:

1. Prompts that are too vague. “Build me a cool app” gets you nowhere. The more specific your prompt, the better the result. Describe features, design, technology and target audience. If you do not know how, use your tool’s Enhance button; it turns your rough idea into a structured prompt.

2. Too much at once. Do not try to build the next Facebook killer right away. Start with one feature, test it, then move on to the next. Breaking complex tasks into small pieces is best practice with human developers too, and with AI it matters even more.

3. Ignoring errors instead of reporting them. When the app throws an error, copy the complete error message into the chat. Not just “the button does not work”, but the exact error, what you expected, and what happened instead. That is not a weakness; that is precisely the workflow.

4. No checkpoints. Before you request a big change: save the current state. Nothing is more frustrating than a working app that breaks after one prompt, with no way back.

5. Ignoring security. Vibe-coded apps have significantly more security vulnerabilities. If you process user data or make the app publicly accessible, have someone with security knowledge look at it. Seriously. Treat AI-generated code like code from a junior developer: it often works, but it needs review.

6. Choosing the wrong tool. Do you want a quick prototype? Pick Bolt or Lovable. Do you want to work on an existing project? Pick Cursor or Claude Code. Every tool has its sweet spot, and the wrong tool leads to unnecessary frustration.

7. Believing vibe coding replaces programmers. It replaces programming for certain use cases. For anything that must be complex, scalable and maintainable, you still need real developers. Vibe coding is an additional tool, not a substitute. Even Linus Torvalds, the creator of Linux, tried vibe coding in early 2026, but only for a small visualization tool, not for the Linux kernel.

When vibe coding pays off, and when it does not

Not every task suits vibe coding equally well. Here is a rough map that can save you a lot of time:

High value, low risk (go right ahead): prototypes and MVPs, generating boilerplate code, writing unit tests, creating documentation, landing pages, simple CRUD apps, data visualizations, browser extensions and small automations.

High value, high risk (proceed with care): complex refactorings, architecture decisions, performance optimizations, security implementations. AI can help here, but you need someone who can judge the result.

Hands off (not worth the effort): overcomplicated solutions to simple problems, unfamiliar patterns in critical code, complex UIs without clear requirements. Here you waste more time on corrections than you save.

A METR study from mid 2025 even showed that experienced developers were 19 percent slower with AI tools than without them, although they themselves believed they were 20 percent faster. The reason: correction loops on complex tasks eat enormous amounts of time. For simple, clearly defined tasks, however, vibe coding genuinely is much faster.

A concrete use case: an SEO tool in 30 minutes

Since minoka.de has its roots in SEO, here is an example that may feel closer to home. Imagine you want a small tool that calculates word count and reading time for a text, with a keyword density analysis on top. The prompt would look like this:

# Prompt for an SEO content tool:

"Create a browser-based SEO content analysis tool.

Textarea for the text input.
Input field for a focus keyword.

Calculate and display in real time:
- Word count
- Character count (with and without spaces)
- Estimated reading time (250 words/minute)
- Keyword density in percent
- Keyword occurrences (absolute)
- Flesch Reading Ease score

Design: minimalist, dark mode, responsive.
No external dependencies, pure HTML/CSS/JS."

With that, you get a working tool within minutes. Not perfect, but usable. And that is exactly the point: vibe coding shines on small, focused projects like this one. Karpathy originally called them “throwaway weekend projects”, and that is precisely what it is ideal for.

From vibe coder to AI-assisted engineer

Once you have warmed up to vibe coding, there comes a point at which you want more. Your projects grow, the requirements get more complex. Then it is time to move one step further along the spectrum, from pure vibe coding to a more deliberate way of working with AI tools.

That does not mean you have to study computer science. But a few things are worth learning:

Deepen your prompt engineering. Learn how to assign roles to the AI (“You are an experienced React developer with a focus on performance”), how to use chain-of-thought prompts (“Think step by step”) and how to set constraints (“Maximum 100 lines, no external libraries”). That alone makes a huge difference.

Learn context management. The quality of AI output is directly proportional to the context you provide. Instead of only polishing your prompt, think about which information the AI actually needs: relevant code files, database schemas, error logs, design documents. The more precise the context, the better the result.

Actually understand Git. Not just the three basic commands, but also branches, merges and how to test changes in isolation. Git is your safety net, and with AI-generated code you need it more often than you think.

Learn to read code (not write it). You do not have to be able to program, but being able to roughly read the generated code helps enormously. Understand the basic structure: what a function is, what a variable is, where the data flows. That is enough to diagnose 80 percent of the problems yourself.

My advice for getting started

If you have never programmed before: start with Bolt.new. It is free to try, runs entirely in the browser, and you see results immediately. Build something small first, a Pomodoro timer, a bookmark manager or a quiz for your niche.

If you already have some technical experience: try Cursor. The learning curve is steeper, but the possibilities are far greater. You have more control and can switch between “vibe mode” and manual intervention.

And if you want to go really deep: look at Claude Code. It is terminal-based and has the steepest learning curve, but for advanced projects it is unbeatable. With features like CLAUDE.md project files and hooks for automation, you can steer the AI with remarkable precision.

Conclusion: vibe coding is real, but it is not a miracle cure

Vibe coding has massively lowered the barrier to entry for software development. Anyone can now build an app that works, at least for their own needs. At the same time, it is no replacement for professional development. The security problems are real, maintainability is poor, and on complex projects you hit the limits quickly.

The most important takeaway: vibe coding is a spectrum, not a switch. You do not have to accept everything blindly or write everything by hand. Find your own point on the spectrum, and keep moving it as you gain experience.

My advice: use vibe coding for what it was meant for, meaning quick prototypes, personal tools and idea validation. Plan before you prompt. Set checkpoints. Test after every change. And when the project grows, bring in real developers. The combination of a fast vibe-coded prototype and professional implementation is currently the smartest path.

Further reading