Reference · 04 of 06
Vibe coding best practices
Successful vibe coding relies on clear intent, small iterative steps, and human oversight.
These habits prevent the small misunderstandings that compound into a real mess when an AI is left to guess at what you meant.
How precise should your prompts be?
Specific, concrete prompts that state the desired behaviour, the constraints and the edge cases produce far more reliable output than vague requests. Vagueness is the single biggest cause of bad results, because it forces the model to fill the gaps with assumptions you never intended. Describe the outcome in detail and the code that comes back is easier to check against what you asked for.
Why work in small iterations rather than one big prompt?
Small, reviewable steps let you catch a wrong turn early, before it shapes everything built on top of it. One giant prompt compounds small misunderstandings into a large mess that is much harder to unpick later. Breaking work into granular steps keeps each piece of logic small enough to actually verify.
What should you actually check when you read the diff?
Read every changed file in the diff before accepting it. Look for logic that does not match what you asked for, unexpected new dependencies, and deleted code that still mattered. Check too for secrets or credentials that have been hardcoded into the new lines by mistake.
Why does testing still matter?
An AI cannot verify that its own output actually works. Running the app, exercising the real user paths, and keeping automated tests remain the developer's job, not an optional extra. These checks are the only way to confirm the generated code holds up once someone is actually using it.
What guardrails keep the process safe?
Use version control with frequent commits, so any step can be rolled back on its own. Work in a sandboxed or disposable environment before touching anything live. Limit what credentials and permissions the AI or its environment can reach, so a mistake stays small.
When should you take the wheel yourself?
Security-sensitive code, anything touching payments or personal data, and complex business logic are all moments to stop generating and write or review the code by hand. The same applies the instant you no longer understand what the code in front of you actually does, covered further in the risks and limits of vibe coding.
Common questions
- Is it fine to accept AI-generated code without reading it if you're in a hurry?
- No. Review it regardless of time pressure, since flaws in logic or security can look correct at a glance.
- How often should you commit when working this way?
- After every small, working step, so that any regression is easy to isolate and roll back.
- Can automated tests replace manual review?
- No. Tests catch some errors, but not a mismatch with what you actually meant, or a maintainability problem building up underneath.
- What should you do when the AI keeps getting the same thing wrong?
- Stop iterating blindly. Rewrite the prompt with clearer constraints, or make the change by hand.