Practical guide
How to Build an MVP by Chatting With AI (Without the Mess)
A practical way to get a real MVP out of Claude or ChatGPT: how to brief it, what order to build in, and the five prompts that decide whether the result survives real users.
You do not need to learn to code to get a working first version any more. You do need to be good at explaining, and to build in an order that does not paint you into a corner. Here is how to do it so the result is worth keeping.
1. Write the brief before you open the chat
The quality of what you get back is set almost entirely by the first message. Before typing anything, write down four things:
- Who uses it, and what they were doing five minutes before they opened it.
- The one job the product does. Not three. One.
- What already exists — a spreadsheet, a WhatsApp group, a notebook. Most MVPs are replacing something, not inventing.
- What success looks like in a week — “ten people place an order” beats “a great experience”.
2. Ask for the data model first, not the screens
Screens are the tempting part and the wrong place to start. Ask the AI: “Given this brief, propose the database tables and the relationships between them, and tell me what you are assuming.” You will catch the wrong assumptions here, when fixing them costs one message instead of a rewrite.
3. Build one vertical slice end to end
Not all the screens at 40%. One complete path — sign in, do the one job, see the result, get an email. A slice that works end to end tells you what is genuinely hard; ten half-built screens tell you nothing.
4. The five prompts that decide whether it survives
| Ask this | Why it matters |
|---|---|
| “What happens if two people do this at the same time?” | Race conditions never show up in a demo, only in production |
| “Where is user input being trusted? Show me.” | Most AI code trusts the client far too readily |
| “Which of these queries will be slow at 100,000 rows?” | Missing indexes are the number one reason a working app dies at scale |
| “What happens if the payment succeeds but the app crashes?” | The single most expensive bug in Indian e-commerce |
| “Write down every assumption you made that I did not state.” | This is where the surprises live |
5. Put it in front of ten people before adding anything
The purpose of the whole exercise is a real reaction. Ship the slice, watch ten people use it without your help, and only then decide what to build next. Almost every founder we work with discovers their second feature was not the one they planned.
What to expect at the end
Done well, this gets you a real product that proves the idea and that early users tolerate. What it does not get you is something ready to carry other people's money quietly for two years — that is a different job, and we wrote about that in AI built your MVP, who ships the real thing.
Questions
Which AI is best for building an MVP?
For chat-driven building, Claude and ChatGPT are both strong; tools like Cursor and Lovable wrap them in a project. The differences matter far less than your brief and the order you build in.
Do I need to know how to code at all?
To get a working first version, no. To judge whether it is safe to put in front of paying users, yes — or borrow someone who can read it for you. That review takes an engineer about half an hour.
Kya AI se bana MVP asli customers ke liye theek hai?
Idea test karne ke liye bilkul. Paise lene aur roz chalane ke liye usme auth, database migrations, payment reconciliation aur monitoring dalna padta hai — wahi hissa aam taur par dobara likhna padta hai.
