Loading page.
Vibe coding is the habit of building software by describing the outcome in plain language, letting AI generate a first draft, and then iterating quickly by running the code, inspecting behavior, and refining prompts. The upside is speed: you can move from idea to a working slice in minutes. The downside is also speed: you can ship the wrong thing, or ship the right thing with hidden bugs.
The way to do vibe coding well is to separate momentum from responsibility. Use AI aggressively for scaffolding and boring glue code, but keep ownership of correctness, security, and product decisions. In practice that means you are not delegating thinking; you are delegating drafting.
Start every build with a tiny spec you can fit in 10 lines. Write the user, the success state, constraints, and what must never happen. This spec is not bureaucracy; it prevents you from burning hours arguing with the model because you never decided what you actually want.
Then ask for the smallest working slice, not the full app. One screen. One endpoint. One component. One test. Vibe coding works best when the feedback loop is short enough that you can run it, see reality, and adjust within 10 to 15 minutes.
Treat the AI output as untrusted. Your job is to verify. Run the app immediately. Click the happy path. Then intentionally break it: empty inputs, invalid formats, huge payloads, slow networks, and unauthorized access. The faster you find edge cases, the less refactoring you do later.
Put guardrails in place early. Types, lint rules, and input validation are not optional if the project will be public. If the app accepts user input, validate it at the boundary. If the app stores data, define the shape clearly. If the app calls third-party services, handle failure modes on purpose instead of hoping the API never fails.
Testing is the difference between shipping fast and shipping random. You do not need a massive test suite. You need a small number of tests that lock the core behavior: one unit test for the tricky logic, one integration test for the main flow, and one regression test for the last bug you fixed so it does not return.
Security deserves a dedicated pass, especially for authentication, file uploads, and anything that becomes accessible on the public internet. Ask the model to list risks, but do not stop there. Check for leaked secrets, missing authorization checks, unsafe file handling, and overly permissive database rules. If you are unsure, simplify the feature until you can confidently explain it.
Use a three-step prompt pattern when you get stuck. First: ask for a diagnosis of why the current behavior happens. Second: ask for a minimal fix, not a rewrite. Third: ask for a short explanation of what changed and why. This keeps the model from deleting your working code just to feel helpful.
As the project grows, convert vibes into structure. Once the core idea is proven, stop generating entire files and start generating small diffs. Create a folder convention, extract reusable components, and write down decisions that future you will forget, such as why you chose a certain state shape or validation rule.
Vibe coding also changes how you learn. If you are a student, you can use AI to create small exercises, generate alternative explanations, and produce quick prototypes. The rule is simple: never accept code you cannot explain. If you cannot explain it, you do not own it.
A practical checklist: write a 10-line spec, build the smallest slice, run within minutes, validate inputs, add minimal tests, do a security pass, and make sure you can explain the architecture in 60 seconds. If you can do that, you can vibe code quickly without sacrificing quality.