Imagine: you ask ChatGPT to "make a landing page for a coffee shop with a booking form," and a minute later you get HTML with CSS and JavaScript. You copy it into a file, open it in your browser — it works. The delight lasts exactly until the first "add payment" or "why is everything broken on mobile." Vibe Coding is an approach where you formulate a task in natural language and AI generates the code. It sounds like magic, but in practice it all comes down to the ability to manage context and debug the result.
The "Vibe Coding" course on asibiont.com promises to teach you how to create applications with AI without programming skills. But before signing up, it's worth understanding what lies behind the facade.
How it actually works
AI models (ChatGPT, Claude, Cursor, Copilot) are trained on millions of lines of code and can predict the next tokens. When you write "create a function to sort an array," the model generates probabilistic code that is often syntactically correct but may contain logical errors or vulnerabilities. The key difference between vibe coding and classical programming is that you don't write code by hand — you iterate on prompts, checking the result.
A practitioner does it like this: breaks the task into small steps, formulates a clear prompt with context for each (language, framework, constraints), then runs the code in a sandbox and looks at the errors. If the AI generated non-working code, you don't try to "fix" it manually — you refine the prompt by adding the error message.
One walkthrough: from idea to a working prototype
Suppose you want to make a page with a feedback form that sends data to Telegram. Without programming experience, you'll most likely ask the AI to "make a form that sends to Telegram" and get HTML code with JavaScript that... doesn't work, because sending requires a bot token and a server-side component.
A practitioner would do it differently. First, they'd clarify: "I need an HTML form with fields for name, phone, and message. On submit, the data should go to a Telegram bot. Suggest two options: via a server-side Python script (Flask) and via a third-party service (e.g., Formspree). For each, describe the steps and limitations." The AI will produce two solutions. The choice depends on whether you're ready to set up a server.
If you choose the Flask option, you'll need to: install Python, create a virtual environment, write an app.py file, get a bot token from @BotFather, and run the server. The AI will generate the code, but you'll have to insert your own token and verify that requests are getting through. A typical mistake is forgetting about CORS or specifying the chat_id incorrectly. Without understanding what an HTTP request is and how to read logs, you'll get stuck.
If you choose Formspree, you need to sign up, get an endpoint, and insert it into the form's action attribute. It's simpler, but it depends on an external service and has free-tier limits.
Where the mechanism breaks down
Even with AI, you can fall into traps. Here are three failure scenarios.
-
Context is overloaded. You have a long conversation with the AI, and it starts forgetting earlier instructions. For example, you asked it to use a specific library, and 20 messages later the AI suggests another one. Solution: periodically summarize the requirements in a single message or start a new chat with a clear brief.
-
The model hallucinates an API. The AI may suggest a non-existent method or library. You waste time trying to run it. Check: before using generated code, cross-reference it with the official documentation.
-
The code works but is insecure. AI often generates code without input validation, with SQL injections, or with exposed keys. You can only notice this if you know the basics of security. For example, if the AI suggested storing passwords in plain text — that's a red flag.
Learning paths: self-taught vs structured
You can learn vibe coding on your own if you have the time and the skill of googling. You'll stumble into errors, google every step, and read documentation. It's free but slow: mastering the basic techniques will take several weeks of trial and error.
Courses provide structure and feedback. For example, the "Vibe Coding" course covers real scenarios — from prototype to production, including debugging AI-generated code. You don't just repeat after the instructor; you get assignments that are checked via an AI chat (you can ask for a breakdown). This accelerates learning, but it costs money.
Practice on real projects is the best teacher, but without a mentor you risk reinforcing bad habits. The combination: a course for the basics + your own pet projects to consolidate.
Who it suits and who it doesn't
Vibe coding suits entrepreneurs, marketers, and designers — anyone who wants to quickly test hypotheses and create prototypes without hiring a developer. It will also be useful for beginner developers to speed up routine work.
Don't count on vibe coding if you plan to build a complex system with high loads or work in a regulated industry (fintech, healthcare) where security and code audit requirements are strict. AI won't replace architectural thinking and a deep understanding of algorithms.
The bottom line
Vibe coding is a powerful tool, but not a magic wand. It lowers the entry barrier but requires discipline and basic technical literacy. If you want to master the approach systematically, with real case breakdowns and feedback, check out the Vibe Coding course on asibiont.com. You can start with a free introductory lesson to see if the format suits you.