Vibe coding means telling a computer what you want to build, in plain English, and having it build the app for you.

You don't write code. You don't hire a developer. You type something like "I want an app where freelancers can submit invoices and clients can approve them"  and a few minutes later, you have a working application with real user accounts, a database storing the data, and a URL you can share.

That's the whole idea.

I built my first vibe-coded product on a Saturday morning. By Sunday evening, I had something I could show people. Not a mockup. Not a sketch. A deployed link that real people could sign up for and use.

The catch, and there is one, is that the quality of what you get out depends almost entirely on the quality of what you put in. The AI can build whatever you describe. The work is learning to describe it precisely. That's what this guide covers.

What you need before you start (it's not technical skills)

The most important thing I can tell you about vibe coding is that the constraint limiting your output is not a technical skill. It's clarity.

Before I built anything that worked, I spent about three months in what I now think of as the pre-execution phase. The MBA had given me permission to think of myself as someone who starts things, but I kept hitting the same wall. I had a spreadsheet of features and a Notion doc with the full product thesis, yet I still couldn't articulate what the app did in a single sentence. Not what problem it solved. What it literally did: who logs in, what they see, what they can do, and what happens to the data.

This is where most non-technical founders get stuck, and it has nothing to do with code.

Before you open any vibe coding platform, build a spec in a spreadsheet. I know it sounds absurd, but why would a spreadsheet help you build an app? But the discipline of putting your product into rows and columns filters out roughly 60% of bad ideas before they become wasted builds. The features you can't describe specifically enough to enter into a cell are features you haven't thought through. The user flows that don't fit into a table are the flows that will confuse the AI later.

Your spec should cover four things: who uses your app (and if there are multiple user types, what each one can see and do); what data your app stores (not technically, just what information it needs to remember); what the main actions are (create an invoice, approve a request, send a message); and what happens after each action (the invoice goes into a list, the approval sends an email).

That document is what turns a vague prompt into a useful one.

How to write a prompt that actually works

Prompt quality is the skill vibe coding actually requires. It took me a couple of builds to understand this.

My first attempts produced outputs that were sort of right but mostly generic. I'd typed things like "build me a client management tool" and gotten a competent but directionless result that bore little resemblance to the tool I'd been imagining. The AI hadn't failed. I had. I'd given it the equivalent of "make me something nice" and been surprised when it guessed wrong.

The prompts that produced useful outputs shared the same structure. They described who the users are and what roles they have; the app's core action; which data needs to be stored and which users it connects to; and any specific integrations (login, payments, notifications).

Here's the difference in practice. Compare these two prompts:

Weak: "Build a tool for managing client feedback."

Stronger: "Build a client feedback tool. There are two user types: clients and account managers. Clients can log in, view a list of their active projects, and leave structured feedback on each one: a rating, a text comment, and a status tag (Approved, Changes Needed, On Hold). Account managers can see all projects across all clients, view the feedback, and update the status. Store everything in a database. Send an email notification to the account manager when a client submits feedback."

The second prompt took me about four minutes to write. The output was 80% of what I eventually deployed. The first would have given me something I'd spend hours correcting.

The underlying skill here is product thinking, not technical knowledge. Founders who get the best outputs from vibe coding are the ones who can write a decent project brief. If you've ever written a client spec or a structured proposal, you already have the muscle. That's actually a consulting skill I didn't expect to use here — though my MBA professors would probably call it "requirements definition" and charge a day rate for it.

What to do when the first output isn't quite right

It rarely is. This is the part that frustrates most beginners, and it frustrated me too until I stopped treating the first output as finished.

Vibe coding is a conversation. The first build is the AI's interpretation of your prompt. Your job is to look at it as a product manager would: what's right, what's wrong, what's missing. Then describe the corrections in plain language.

The worst thing you can do is start over from scratch every time something is off. Each time you re-prompt from zero, you lose the context the AI has been building. Treat corrections as iterations instead:

"The client list is showing all projects from all clients. It should only show projects belonging to the logged-in client."

"Remove the status dropdown from the client view. Only account managers should be able to change the status."

"The email notification isn't working. Add a trigger: when a client submits feedback, send an email to account-manager@gtmready.com with the project name and a link to the feedback."

Specific, scoped, one thing at a time. That's the cadence.

I had one build that took nine rounds of iteration before I was happy with it. That sounds like a lot until you remember that nine rounds of feedback is what you'd give a developer over a two-week sprint. The turnaround here was minutes, not days.

One thing I had to learn: when the output drifts far from what you wanted, the problem is usually the original prompt, not the AI. Go back to your spec. Figure out what you didn't say clearly the first time. A good correction starts with "I didn't describe this properly. Here's what I actually meant."

Connecting the pieces: auth, database, payments, and other integrations

This is where many vibe coding platforms reveal their limits, and where the choice of platform matters more than most beginners expect.

I want to be honest about how I learned this. My first serious build started on a platform that produced exactly the kind of impressive-looking output I've been describing. Slick interface. Responsive design. The client could log in, or so it appeared. But the login was cosmetic. There was no real authentication layer. The database wasn't persisting data between sessions. It looked ready to ship and wasn't. I discovered this when I shared the URL with a colleague and asked her to create an account. The account "created." Then disappeared.

The problem was architectural: some platforms generate frontend interfaces connected to temporary or simulated backends. The app works when you test it in a single session, but breaks when real users interact with it.

For my actual deployed product, I used Mayson, specifically because I needed auth that worked, a database that persisted, and a Razorpay integration that processed real payments rather than a demo toggle. The consultant in me needed the thing to work end-to-end, not just look like it did. 

When you're adding integrations through a prompt, you describe them in the same plain language as everything else:

"Users should be able to sign up with email and password. Store their details in the database."

"Add a Stripe payment step before users can access the dashboard."

"Send a confirmation email when a user completes onboarding."

On a production-ready platform, the auth is real, the Stripe keys are configured, and the email trigger is wired correctly. On a prototype-focused platform, you'll get something that looks right until you test it with another person.

The test I now run before investing time in any build: create an account, log out, close the browser, reopen it, log back in. If your data is still there, you have a real backend. If it isn't, you have a demo.

Testing your app before you show it to anyone

A deployed URL is not the same as a working app. Worth separating those two things clearly.

Before you share your link with anyone, go through every user flow as if you were a user encountering it for the first time. Create an account with a test email address you haven't used before. Do the main action. Check that the data persisted. Log out. Log back in. Confirm the data is still there. Create a second user account. Confirm the two accounts can't see each other's data.

If your app has payments, use Stripe's test card numbers (4242 4242 4242 4242 works for most standard flows). Complete a transaction. Check that the right thing happened in the app afterwards: the user got access, the record updated, whatever the designed outcome was.

Try to break it. What happens if you leave a required field blank? What happens if you enter a very long string in a text field? You don't need to test every edge case. You need to know that the common flows work and that basic errors produce a reasonable message rather than a crash.

Write down what breaks. Then go back to the platform and describe the fixes one at a time, as you'd raise bugs with a developer.

Deploying and sharing your first vibe-coded app

Most vibe coding platforms handle deployment automatically and give you a URL at the end of your build session. A few things worth checking before you share it:

Make sure you're sharing the production environment, not a preview. If someone creates an account in your preview environment, it won't carry over.

Check your loading state from a fresh browser tab with no cached data. The first visit sometimes takes a few seconds if the app has been dormant. Know what that looks like before someone else encounters it.

Think about who you're sharing it with first. Your first share should go to someone who will break it, not someone you're trying to impress. Bug reports before validation.

Look at what a first-time visitor sees on the screen. If it's just a login form with no context, add a line of text explaining what the app is and what the user should do. Describe it to the AI: "Add a short welcome message on the homepage that explains what this tool is for and prompts the user to create an account."

The goal for your first share is not a polished product. It's one real user completing one real flow. That's worth more than three weeks of additional building before you've shown it to anyone. 

The mistakes first-timers make and how to avoid them

I made most of these. Some I made twice.

Skipping the spec. The most common reason a first build ends in frustration is that the builder started prompting before they knew what they were building. Twenty minutes in a spreadsheet before you open the platform is not wasted time. It's the build.

Expecting one prompt to do everything. The first prompt describes the app's shape. The subsequent prompts refine it. Founders who treat an imperfect first output as a failure are misunderstanding the workflow. The workflow is iterative by design.

Choosing a platform without testing the backend. Some platforms produce demo-quality outputs that look compelling until real users arrive. Test authentication and data persistence before you build anything substantial. Create an account, log out, reopen the browser, log back in. Five minutes. Do it before you invest hours.

Building too much before testing. My operations professor at business school, Dr Wendy Alderton, used to say, "Strategy without execution is hallucination." The product version of that is: don't build ten features before you've validated one. Build the smallest thing that tests your core assumption, share it with one person, and build from there. Perfectionism is the dominant failure mode of non-technical founders. More deadly, in my experience, than any technical gap.

Confusing prompting skill with product clarity. Vibe coding removes the technical barrier to building. It doesn't replace the need to know what you're building. If your product isn't clear in your own head, the AI will produce something generic. Clarity first, prompting second.

Frequently asked questions

Abhishek writes about the non-technical founder journey — the false starts, the financial lessons, and what actually changes when you ship something with real users. He consults during the week and builds on weekends.