Does the AI replace the need for code review?

It does not. AI-generated code still has to pass through the same quality gates as hand-written code, including testing and professional review, before it is deployed.

Is this method suitable for all types of software projects?

It is most effective for prototyping and scaffolding features rather than complex business logic or compliance-heavy systems. Professional teams use it as part of a larger workflow, not a replacement for structured development.

How do I know if the AI understood my request?

You confirm it through the live preview and the review step. If the output does not match your goal, you iterate with clearer, more specific instructions.

Are there terms worth knowing to follow this process?

Prompt, agent, sandbox and context window come up often. All are defined in the glossary on this site.

Reference · 02 of 06

How vibe coding works

Vibe coding works through a repeating loop: a person describes a goal in plain language, and an AI model generates, previews and iterates on the resulting code. The human stays responsible for defining requirements, checking the output and managing what actually gets deployed.

A clean line-art diagram showing a circular five-step process loop rendered as connected nodes.

What does the loop actually look like?

The process follows a repeating five-step loop, in this order.

01
Prompt
The person describes what they want, in plain language.
02
Build
The AI generates or edits the actual code across one or more files.
03
Preview
The running result is shown, often live in-browser.
04
Iterate
The person refines the prompt or points out what is wrong.
05
Review
The person checks the code and its behaviour, including testing, before it ships.

What does the model do?

It interprets the request to translate natural language into functioning code. It manages file-level edits, often inside a sandboxed environment that provides a live preview. When errors occur, it can also apply fixes based on specific feedback given during the iterate step.

What does the human still do?

The person defines the scope, requirements and edge cases of the project. They judge whether the output is correct and safe, test real usage paths, and hold final accountability for the finished product. Domain judgement, business decisions and strict compliance checks sit entirely outside the loop.

Where does this fit in a real workflow?

It is most often used to prototype ideas quickly or scaffold a new feature for fast validation. In professional teams it complements existing practice rather than replacing it: the code produced still passes through version control, automated testing and manual review before it ships, same as anything hand-written. Several tools in the tool landscape build this loop directly into their interface, with the preview and the edit sitting side by side.

Common questions

Does the AI replace the need for code review?: It does not. AI-generated code still has to pass through the same quality gates as hand-written code, including testing and professional review, before it is deployed.
Is this method suitable for all types of software projects?: It is most effective for prototyping and scaffolding features rather than complex business logic or compliance-heavy systems. Professional teams use it as part of a larger workflow, not a replacement for structured development.
How do I know if the AI understood my request?: You confirm it through the live preview and the review step. If the output does not match your goal, you iterate with clearer, more specific instructions.
Are there terms worth knowing to follow this process?: Prompt, agent, sandbox and context window come up often. All are defined in the glossary on this site.