Vibecoding: What It Is and Why You Need to Know About It Now

Can you create web services and applications without deep programming knowledge? With the advent of powerful language models and AI assistants — yes. All you need is to clearly formulate the task. This approach is called vibecoding (vibe coding).

It gained particular popularity after OpenAI co-founder Andrej Karpathy publicly demonstrated in February 2025 how he fully delegates programming to neural network agents. His workflow requires almost no manual code input. He formulates an idea — the model writes, checks, and refines the project.

In this article, we will:

• Explain what vibecoding is and how it works.
• Show which tools vibecoders use in 2025.
• Explain how to choose an AI model.
• Determine for whom this approach is suitable and who is not yet ready to rely on it.
• Try to create a Telegram bot with a real example without writing a single line of code manually.

Our goal in this material is not just to describe the trend, but to give a practical understanding of how to use vibe coding in work or business, what limitations and opportunities it offers, and why this direction is becoming part of the future of technology.

What is Vibecoding?

Vibecoding (vibe coding) is a programming style where the developer does not write code manually, but describes the task in natural language, and artificial intelligence itself creates the working code. This approach lowers the technical barrier: there's no need to know language syntax, understand architecture, or manually debug the project — these tasks are performed by an AI assistant.

How Vibecoding Works

1. A person formulates an idea or function — "Create a Telegram bot that analyzes GitHub repositories."
2. The model (e.g., GPT‑4, Claude Code, or Cursor Agent) generates the necessary code, creates the project structure, files, dependencies.
3. If errors occur — they can be pasted back into the chat, and the AI will fix them automatically.
4. The project can be launched immediately — without manual editing or debugging.

This approach is called "code by vibe" because the basis is not compiler logic, but the context, intent, and result that the developer describes as a thought, goal, or command.

Who Invented Vibecoding and Why

The term "vibecoding" was introduced by Andrej Karpathy — a scientist, developer, and co-founder of OpenAI. In 2025, he described his methodology where the code is not important, the result is, and the entire process can be delegated to AI.

"I don't touch the keyboard. I say: 'reduce the left indents by half' — and the agent does everything itself. I even process errors through chat, without diving in."

-- Andrej Karpathy, February 2025

He claims that development becomes similar to managing an interface through dialogue, rather than writing lines manually. For example, his project MenuGen (a web service that generates dish images from a menu photo) is completely written by AI: from authorization to the payment system.

Vibecoding Tools

To start using vibecoding, you need an editor or development environment with AI support. Below is a list of popular tools in 2025 that allow you to generate code, create applications, fix errors, and run projects directly in the browser or on a local machine.

Cursor – The Foundation for Vibecoders

• Function: Generates and edits code, understands project structure, makes changes across multiple files simultaneously.
• Features: Built on Visual Studio Code but with integration of models from OpenAI, Google, Anthropic, and others.
• Benefits: Familiar interface, deep context support, works with natural language prompts.
• Platforms: Windows, macOS, Linux, web.
• Price: From $20/month, free version available.

Windsurf – Minimalism and Speed

• Function: Code generation and editing, AI chat.
• Key Feature: Lightweight interface without clutter — great for beginners and non-technical users.
• Platforms: Windows, macOS, Linux, IDE plugins.
• Price: From $15, free tier available.

Replit – Online Development Environment

• Function: Codes, runs, and hosts projects directly in the browser.
• Distinction: You can program even from a smartphone.
• Support: Language models, editor, terminal, database, deployment — all built-in.
• Platforms: Browser.
• Price: From $20, free tier available.

Devin AI – The AI Programmer on Your Team

• Capabilities: Solves tasks from issue trackers (tickets), analyzes databases, generates code, and commits to Git.
• Platforms: Web.
• Price: From $20.

Claude Code – Code Generation in Terminal

• Model: Claude Opus 4.
• Interface: CLI.
• Level: Suitable for experienced developers.
• Price: From $17/month.
• Platforms: Windows (via WSL), macOS, Linux.

Cline – Plugin Mediator

• Function: Connects any language models to editors.
• Feature: Open source, free.
• Support: VS Code, Cursor, Windsurf.

JetBrains AI

• Tools:

Junie – Assistant for code snippets. AI Assistant – Programming chat.

• Support: Works in all JetBrains IDEs (PyCharm, IntelliJ IDEA, etc.).
• Price: From $10, free tier available.

How to Choose a Language Model for Vibecoding

You can connect different language models in each vibecoding tool. But not all are equally good with code. Some are better for text generation, others for development, others for bug fixing and API work.

For a quick guide, here is a comparison of the most popular models for vibecoding:

Model Best For Advantages Limitations Where Used

| Model | Suitable for | Advantages | Restrictions | Where is it used | | ------ | ------ | ------ | ------ | ------ | | GPT‑4o | Daily tasks, routine code | Stable, fast, understands prompts well | Limited context window | Cursor, Replit, JetBrains AI | | GPT‑4.1 | Full-scale programming | Deep analysis, creates architecture | Slower, more expensive | Devin AI, Cursor (Pro, Ultra) | | Claude Code (Opus 4) | Code generation & refactoring | Writes excellent code | CLI interface, not for beginners | Claude Code CLI | | DeepSeek-Coder | Research, structural tasks | Generates complex queries and SQL | Less known, unstable | Cursor, via Cline | | Gemini (Google) | Web interfaces, API integration | Strong logic, API knowledge | Can "hallucinate" | Via Cline or Replit | | GPT‑3.5-turbo | Quick prototypes, pet projects | Lightweight, cheap, good with basic tasks | Weak on architecture and complex logic | Free mode in Cursor, Replit |

Practical Vibecoding: Creating a Telegram Bot

The fastest way to understand vibecoding is to try it yourself. Below is a step-by-step guide on how to create a Telegram bot that, given a link to a GitHub repository, sends a brief summary: name, author, stars, release, and other data.

We'll use the Cursor editor with the GPT‑3.5 model. Everything is done right in the editor — no manual coding required.

Step 1: Set up the environment. Install Cursor, choose a plan (Pro recommended for full access), and enable Agent mode with the GPT‑3.5 model. Step 2: Describe the task. Formulate a clear prompt in the chat, specifying the bot's function, language (Python), and libraries (Aiogram, requests). Step 3: Generate the project. The AI assistant creates the project structure: bot.py, requirements.txt, README.md, .env.example. Step 4: Correct errors. If errors appear when running, copy the terminal text into the chat with the words: "Fix the errors." The AI will make corrections. Step 5: Launch. Run the bot with python bot.py. It will successfully start and respond to links in Telegram. Step 6: Study and improve. The finished project can be uploaded to GitHub, deployed (e.g., via Replit), and extended with features.

Pros and Cons of Vibecoding

✅ Advantages:

1. Automation of routine tasks (boilerplate code, error fixing, documentation).
2. Rapid idea implementation (prototypes in hours, not weeks).
3. Low barrier to entry (no deep programming knowledge required, just clear formulation).
4. Flexibility (quick changes, alternative implementations, A/B testing).

❌ Disadvantages:

1. Security concerns (corporate data leakage risks when using external AI services).
2. Hallucinations and non-existent code (models can invent libraries or commands).
3. Poor scalability (currently best for small projects, MVPs, not complex architectures like social networks or microservices platforms).
4. Requires AI communication skills (prompt formulation is key; vague prompts yield unpredictable results).

Tips for Getting Started with Vibecoding

1. Formulate requests precisely. Write prompts like a technical specification: specify languages, libraries, structure, APIs, constraints.
2. Use paid versions of editors. They offer larger context windows, access to powerful models (GPT‑4.1, Claude), and handle complex queries better.
3. Break large tasks into stages. The AI performs better with step-by-step instructions (e.g., first layout, then authorization, then payment integration).
4. Check everything the AI generates. Test all code in a sandbox or staging environment, even if it looks correct.
5. Try different models. If one model struggles, switch to another (e.g., from GPT‑4o to DeepSeek or Claude Opus for specific tasks).
6. Get feedback and learn from mistakes. Vibecoding is a new way of interacting with AI. Analyze errors, refine prompts, and share experiences to improve.