Vibe Coding: What It Actually Means

The term caught on faster than a clear definition did. Here is what stands behind it in practice, and where the limits begin.

What it actually is

Vibe coding is development where you state the task and a model writes the code, shifting your role from typing to framing and checking.

The key word is shifting, not disappearing. You still decide what to do, in what order, and what counts as done. What changes is where the time goes: it used to be writing code, now it is framing and verifying.

Understand one thing early: writing speed has stopped being the bottleneck, and checking speed has not. Every real problem with this approach grows from there.

How it differs from completion

Three levels that often get blurred together.

Completion. Suggests the next lines in the editor. You write, the tool guesses the continuation. It speeds up typing without changing how you work.

Chat with a model. You carry code to a separate window and back. The model cannot see the project as a whole and does not know whether what it wrote works.

An agent. It walks the files, runs commands, reads test output and keeps going. This is where the way of working genuinely changes: you describe a task rather than edit a file.

The third level is what people usually mean by vibe coding. Tool-by-tool detail is in neural networks for code and agents.

What changes in the work

Framing becomes the core skill. A vague task yields a vague result, and no more expensive model fixes that. A precise address and a clear definition of done buy more than switching tools.

Reading code matters more than writing it. You read more code than before, and it is somebody else’s. Anyone who cannot judge a diff loses control of the project faster than they notice.

Verifiability decides quality. “Fix the failing test” goes well because the criterion is unambiguous. “Make it nice” goes badly for the same reason.

The cost of mistakes shifts. Bad code used to be slow to write and therefore rare. Now it can be written very fast and in quantity.

The limits

An honest list:

• Anywhere you cannot check. No tests and no way to see the result means no way to tell working from plausible.
• In an unfamiliar domain. The model will write code and will not tell you that you are solving the wrong problem.
• In architectural decisions. It proposes an option; you carry the consequences.
• In anything requiring taste. Interfaces, copy, product decisions.
• Without git. No way to roll back is the worst possible setup.

On security specifically: an agent with shell access has access to everything you do. That is solved by a sandbox, not by care.

Where to go next

A practical order:

1. How it actually works - what happens under the hood and why the model errs.
2. Neural networks for writing code and choosing the best one for the task.
3. Agents, sandboxing and permissions - before granting project access.
4. Choosing a model per task - once cost starts to matter.

Specific topics: Python specifics, Cursor in Russia and Cursor alternatives, what to learn and in what order, an MVP built this way.

The long version on the approach itself is on the blog: what vibe coding is. If you want the result rather than the explanation - a prototype or MVP built this way - see the services page.