Learn what vibe coding is, how the workflow works in plain steps, and see 3 practical examples (web app, API, mobile) you can copy.
Vibe coding is building software by telling an AI what you want in normal language, then iterating on the result until it works the way you expect.
The goal is simple: get to working screens, APIs, and features faster by describing intent instead of starting from a blank code file. You describe what the app should do, what data it uses, and what “done” looks like. The AI turns that into code and project structure, and you steer with feedback like “make the login simpler” or “store orders with a status and timestamps.”
Think of it like directing a very fast junior developer. It can write a lot of code quickly, but it still needs clear instructions and occasional corrections. On a platform like Koder.ai, the chat is the main interface: you describe the app, it generates a React web UI, a Go backend, and a PostgreSQL database setup when needed. You can then review changes, roll back if something goes wrong, and export the source code when you want full control.
A few guardrails help set expectations:
Vibe coding tends to help two kinds of people most: non-technical builders who have a clear idea but don’t want to learn a full dev stack first, and busy teams that want a faster path from concept to a usable prototype or internal tool. If you can explain what you want in plain sentences, you can start.
Vibe coding is a loop. You describe what you want, the system generates the project and code, you run it to see what happened, then you adjust the request until it matches your idea. The work shifts from typing every line to making clear decisions and giving good feedback.
Start with the smallest useful slice, not the whole dream product. Say what the app is for, who uses it, and what “done” looks like.
A simple way to phrase it is: “Build X for Y, it must do A and B, and it must not do C.” Humans still lead here. You choose the features, the rules, and what matters first.
The system creates the boring parts for you: project setup, routing, database wiring, basic UI, and the first version of the logic. With a vibe-coding tool like Koder.ai, it can feel like chatting your way through what used to be hours of setup and boilerplate.
Ask for structure in plain words: “Create three screens,” “Add login,” “Store items in a PostgreSQL table,” or “Expose an endpoint that returns JSON.” Don’t chase perfect code on the first try. Aim for a working draft you can touch.
Don’t only read the chat output. Run the app and look for real signals.
Start with what users notice first (do screens look right and behave right?), then verify the less visible parts (is data saved and loaded correctly?). After that, try a few edge cases: empty inputs, duplicates, and clearly bad values.
If you have time, add a couple of simple tests for the rules you care about most so they don’t quietly break later.
Now respond like a product owner and a reviewer. Tell it what’s wrong, what to change, and what to keep. Be specific: “Keep the layout, but move the button to the header,” or “Reject negative amounts with a 400 error.”
After a few loops, you end up with something that fits your intent, not just a pile of generated code. The speed is the “vibe,” but the quality comes from your choices and your review.
Vibe coding works best when the goal is clear enough to describe in plain language, and the cost of being “almost right” is low. You want fast feedback, not a perfect system on the first try. If you can point at the result and say “yes, that’s it” or “change this part,” you’re in the right zone.
A good fit is anything where speed matters more than long planning. For example, a small team might need an internal dashboard to review sales calls. You can describe the screens, the fields, and a few rules, then iterate until it matches how the team actually works.
It often shines for prototypes, internal tools (dashboards, admin panels, simple automations), and narrow MVPs with standard flows like login and CRUD. It can also work well for “glue” apps that connect a few services, because you can define the inputs and outputs and verify them quickly.
It gets harder when requirements are strict, deep, or full of exceptions. That includes complex compliance rules (where exact wording matters), heavy performance tuning (where small choices have big cost), and large legacy systems (where hidden dependencies are everywhere). You can still use vibe coding there, but the work shifts toward careful specs, reviews, and testing, not just chatting.
A practical way to decide is to start small and expand only if the output stays predictable. Build one thin slice end to end (one screen, one API route, one data table). If that slice comes together cleanly, add the next slice.
Signs you should slow down and tighten the plan:
If you see these, pause and write clearer rules, example inputs and outputs, and a few “must pass” tests. On platforms like Koder.ai, planning mode and snapshots can help you iterate without losing a working version.
Good vibe coding starts before you type your first message. If your prompt is fuzzy, the build will be fuzzy. If your prompt is specific, the AI can make solid choices and you spend your time reviewing instead of rewriting.
Start with a short project brief you can paste into the chat. Keep it concrete: the goal (one sentence), who the users are, the few screens you expect to click through, the main data you store (and the fields that matter), and any hard constraints (mobile-friendly, dates in UTC, dark mode, and so on).
Then describe features using examples, not slogans. “Users can manage tasks” is vague. “A user can create a task with title, due date, and priority; mark it done; and filter by status” gives the AI something testable.
If you want code you can maintain, ask for a simple structure up front: which pages exist, what tables are needed, and which API endpoints connect them. You don’t need to be technical to ask for this. Plain words are enough.
Here is a prompt you can adapt (works well in tools like the Koder.ai platform):
Build a small web app called “Team Tasks”.
Users: Admin, Member.
Goal: track tasks for a small team.
Screens:
1) Login
2) Task list (filter: All, Open, Done)
3) Task details
4) Admin: Users list
Data:
Task(id, title, description, status, due_date, created_by, assigned_to)
User(id, name, email, role)
Rules:
- Members can only edit tasks they created.
- Admin can view and edit everything.
Please propose:
- Pages/components
- Database tables
- API endpoints (CRUD)
Then generate the first working version.
To keep scope under control, limit your “v1” to a short feature list. One useful line to add is: “If anything is unclear, ask up to 5 questions before building.” That reduces guessing and prevents surprise features you never asked for.
A simple rhythm that works on most builds:
Start with a one-paragraph brief: who it’s for, the main job it does, and what “done” means. Add two or three must-haves and two or three nice-to-haves, then stop. Too much detail early usually creates confusion.
Next, ask for the smallest runnable version: one core flow end to end, even if it looks plain. For a booking app, that might be a service list page, a time selection page, and a confirmation screen with the booking saved.
Test the happy path first, then widen slowly. Click through the main flow and only fix what blocks it. After that, add one edge case at a time: double-booking prevention, timezone handling, missing fields, closed days.
When something works, capture a checkpoint (snapshot, tag, or whatever your tool supports) so you can roll back if the next change breaks things. This is where tools like Koder.ai are handy in practice: snapshots and rollback make experimentation feel low-risk.
Finally, polish before you pile on features. Clear validation messages, loading states, friendly errors, and sensible defaults are what make an app feel real.
Picture a small task tracker you use on your laptop: you sign in, see your list, add a task, edit it, and delete it when you’re done. In vibe coding, you start by describing that flow in plain sentences, then you ask the builder to turn it into working screens and data.
Start with the pages and actions, not the tech. For example: a sign-in page (email + password, sign out), a tasks page (list tasks, create, edit, delete), and optionally a task details view (notes, due date, status) and a basic settings screen.
Next, describe the data in human terms. Instead of “design a schema,” say what a task must store: a title, optional notes, a status (todo/doing/done), an optional due date, and timestamps for when it was created and updated. Also note that tasks belong to a user.
If you’re using a vibe-coding platform like Koder.ai, ask for a small first version that runs end to end: React screens, a Go backend, and a PostgreSQL database with the fields you described. Keep the first pass tight: sign in, view tasks, add a task. Once that works, iterate.
A practical rhythm is “make it work, then make it nicer.” One realistic sequence:
Each round is another chat request that builds on what’s already there. The key is to be specific about the change and what must not break.
Even for a small web app, a few details decide whether it feels solid:
A good iteration request sounds like: “Add a status filter with tabs (All, Todo, Doing, Done). Keep the database the same. Update the API so it can filter by status, and show a loading state when switching tabs.” Short, testable, and hard to misunderstand.
An API is one of the easiest places to use vibe coding because the work is mostly rules: what data you store, what actions are allowed, and what the responses should look like.
Imagine a small store system with two things: customers and orders. Your “sentences” can be as simple as: “Customers have name and email. Orders belong to a customer, have items, total price, and a status like draft, paid, shipped.” That’s enough to start.
Keep it concrete: what you can do, what you must send, and what you get back.
You can outline the basics (create, list, get one, update, delete) for customers and orders, then add the few filters you know you’ll need (for example: list orders by customer_id and status). After that, define how errors should behave for “not found,” “bad input,” and “not allowed,” plus which endpoints require login.
Then add input rules and error responses. Example rules: email must be valid and unique; order items must be at least 1; total must match sum of items; status can only move forward (draft -> paid -> shipped).
If you care about basic security early, ask for token auth (bearer token), simple roles (admin vs support), and rate limiting (for example, 60 requests per minute per token). If you use Koder.ai, planning mode can help you agree on these rules before any code is generated.
Don’t aim for exhaustive testing at first. You just want proof the API behaves as specified.
# Create customer
curl -X POST http://localhost:8080/customers \
-H "Authorization: Bearer <token>" \
-H "Content-Type: application/json" \
-d '{"name":"Mina Lee","email":"[email protected]"}'
# Expected: 201 + JSON with id, name, email
# Create order
curl -X POST http://localhost:8080/orders \
-H "Authorization: Bearer <token>" \
-H "Content-Type: application/json" \
-d '{"customer_id":1,"items":[{"sku":"A1","qty":2,"price":12.50}]}'
# Expected: 201 + status "draft" + computed total 25.00
# Bad input example (invalid email)
# Expected: 400 + {"error":"invalid_email"}
If those calls return the right status codes and fields, you have a working baseline. From there, iterate: add pagination, better filtering, and clearer error messages before you add more features.
A good mobile example is a simple habit tracker. Mobile apps feel “hard” because of small screens, offline use, and device features. You’ll get better results when you state those constraints before the first build, not after bugs show up.
Start by naming the app and the one thing it must do on day one: “Track daily habits with quick check-ins.” Then list the screens you expect. Keeping that list small helps the AI pick a clean navigation structure.
A solid first version:
Next, be clear about offline and syncing. Many mobile apps are used with weak data. If you care about offline first, say so: “Everything should work offline. If the user signs in later, sync in the background and resolve conflicts by keeping the most recent change.” If you don’t need syncing yet, say that too. A local-only first release is often faster and less risky.
Then call out any device features, even if you’re not sure you’ll use them, because they change the app structure: notifications (daily reminders, timezone handling), camera (optional photo attachments), location (often not needed), and biometrics (if notes are sensitive).
To keep it simple, pick one platform direction and expand later. For example: “Build Android first with basic notifications. iOS can come next.” If you’re using Koder.ai, asking for a Flutter mobile app is a practical default because it keeps one codebase while you explore the idea.
A concrete prompt that usually works well:
“Build a Flutter habit tracker app with 4 screens: Onboarding, Daily List, Add Habit, Stats. Offline first using local storage. No login for v1. Daily reminder notification at a user-chosen time. Keep the UI clean with a bottom nav. Generate sample data for testing.”
From there, iterate in small steps: check navigation, check offline behavior, add reminders, then polish the stats. Small loops beat big rewrites.
The fastest way to get value from vibe coding is to treat it like a series of small, testable bets. Most problems happen when you jump straight to a “finished product” without locking down what “working” means.
A quick scenario: you’re building a booking web app. You ask for “a calendar and payments,” and the tool generates screens, a database, and a payment stub. It looks complete, but you never defined what happens when a day is fully booked, when a card fails, or when a user tries to book in the past. Those “small” gaps become big bugs.
Whether you build on Koder.ai or any other tool, check these basics early (not at the end):
Keep scope small, prompts specific, and changes incremental. That’s how vibe coding stays fun and productive instead of confusing.
Before you keep building, do a quick “is this real yet?” pass. Vibe coding moves fast, but small misses (a broken button, a field that never saves) can hide until the last minute.
Start with the main flow. Click through it like a first-time user and don’t “help” the app by doing steps in a special order.
Then do a release reality check. If you ship and something goes wrong, you want a safe way back.
Pick a first project that is small but complete. A good starter is a single-purpose tool with one main screen and one database table (for example: a simple booking list, a lightweight CRM, or a habit tracker). Keep it narrow so you can finish the full loop.
If you’re using Koder.ai (koder.ai), start in planning mode so the build stays organized before code is generated. Build a small slice, use snapshots often so you can compare changes and roll back if needed, then export the source code when you want full control.
Write down your “definition of done” in one sentence (example: “A user can add an item, see it in a list, and it stays after refresh”). That one sentence keeps vibe coding focused and stops the build from turning into endless tweaks.
Vibe coding is building software by describing what you want in plain language, letting an AI generate code and structure, and then iterating with clear feedback until it behaves correctly.
You’re still responsible for decisions and review—the “vibe” is speed, not autopilot.
A simple loop works best:
Aim for “working draft” first, then polish.
Start with a mini-brief you can paste into chat:
Then add: “If anything is unclear, ask up to 5 questions before building.”
Don’t start with the full product. Start with one thin slice end to end:
Example: “Login → list items → add item.” If that slice is stable, add the next slice. This keeps changes understandable and reduces recurring bugs.
Do quick, real checks in this order:
If something is important, ask for a small test so it doesn’t regress later.
Use tight, testable feedback. Good examples:
Avoid vague requests like “make it modern” unless you add concrete examples (spacing, colors, components, error text).
Slow down and add clarity if you see patterns like:
At that point, write a short spec: example inputs/outputs, “must pass” rules, and 2–3 key tests. Then iterate one change at a time.
Planning mode is useful when you want agreement before code changes. Ask for:
Once that plan matches your intent, generate the first runnable version and iterate from there.
Use snapshots as checkpoints after something works (for example, after login + list + add is stable). If a new change breaks things, rollback to the last good snapshot and re-apply the change more narrowly.
This lets you experiment without losing a working version.
Export when you want full control over the project: deeper customization, custom tooling, strict reviews, or moving to your own pipeline.
A practical approach is: build and iterate quickly on the platform, then export once the structure and core flows are stable.