Vibe coding prompts: a request structure that produces working code

A vibe coding prompt is not a plea to "build me a website" — it is a short spec: what should work, for whom, on what stack, and how you will tell it's done. The numbers from the section itself show why this matters: across 597 vibe coding chats on NeuralSpace over the section's entire history, the median first project description is 91 characters — a single phrase. In chats that started this way the user writes 1.7 messages on average — the conversation dies after the first reply. Where the description runs longer than 800 characters, it's 3.0 user messages on average: the project lives and gets refined (source — anonymized generation history of the vibe coding section, aggregates only, no account linkage). Below: a request structure that produces working code within the first iterations, a breakdown on one example, and ready-made phrasings for edits.

Why "build me a site" doesn't work

For one message from you, the vibe coding agent takes dozens of steps: writes files, starts a server, hits errors, fixes them, restarts. In the same history, an average chat holds 16 agent messages against 2 from the human — all the routine is on its side. But autonomy has a price: everything you didn't specify, the model fills with defaults — generic design, generic structure, placeholder text instead of your data. Defaults rarely match what you imagined. The job of a prompt is to take away the model's room for bad defaults: the less it has to guess, the closer the first result is to your intent.

Six blocks of a working prompt

A good vibe coding request is assembled from six blocks. Not all of them are mandatory — but the more ambitious the project, the more each one matters.

• Outcome and behavior. What the app should do, not how it's built inside: "a visitor picks a date and leaves a request; the request is saved and visible to me on a separate page".
• Context and audience. Who it's for: "a site for a bike repair shop, visitors come from phones, aged 25–45".
• Stack and constraints. What to use and what to avoid: "a single HTML page, no build step or frameworks", "store data in localStorage", "no external paid APIs".
• Data and examples. Real names, texts and numbers instead of filler: three actual services with prices, the real about-text. On real data the agent builds something plausible, and you don't have to replace placeholders by hand.
• Definition of done. How you'll know it works: "done when: opens on a phone, the form shows a confirmation after submitting, requests are visible on a hidden /admin page".
• Stop list. What not to do: "no sign-up or login, no payment integration, no dark theme".

Beginners skip the last block most often — and pay for it. By default the agent loves to over-engineer: login systems, animations, extra pages. One line of "don't do X" saves several iterations and tokens.

One project, two prompts

Take a habit tracker. The weak request: "Make a habit tracker". The agent will produce something average: unclear which habits, where data lives, what "done" means.

A strong version of the same project: "Make a single-page habit tracker app without frameworks, plain HTML+JS, data in localStorage. Up to 10 habits, each with a name and a color. The main screen is a grid of cards: clicking a card marks the habit done for today, a day-streak counter grows with daily check-ins and resets on a miss. At the bottom — simple weekly stats: how many days out of 7 were completed. Light style, large font, everything must work at 390 px width. Done when: a habit can be added, checked off and deleted, and data survives a page reload. No auth, no server sync". The second request is ten times longer — and it's the one that usually yields working code within the first or second iteration, because the model has nowhere left to guess.

Follow-up prompts: edits without breakage

The first reply is a draft. From there you steer the project with short, precise requests — and they have their own grammar too.

• Edit = screen + element + desired behavior. Not "redo the homepage", but "on the main screen the 'Mark done' button is too pale — make it high-contrast and bigger". Surgical edits don't touch what already works.
• Error = the full error text. If something breaks, paste the error message into the chat and add what you were doing: "clicking 'Save' shows a TypeError, reproduced in Chrome". The agent fixes from a stack trace far more precisely than from "it doesn't work".
• Extension = "add", not "redo". "Add a monthly chart to the stats" keeps working code; "redo the stats" risks breaking a week of it.
• Rollback = project versions. If an edit breaks things, rolling back to the previous working build in Project Versions is faster than explaining to the agent what fell off.

How to try it on NeuralSpace

All of this works in the vibe coding section on the Code page. The flow: sign up, hit "Create project", paste your six-block prompt into the description field — you can take the example above and swap in your own project. Pick a model and run: the agent writes the code, starts a server and publishes the app at a public link. Then you steer it with the follow-ups from the previous section; there is no environment or hosting setup. There is no subscription: new users get starter tokens, after that you pay only for the tokens you spend, and the generation price is shown before you run it.

Which model fits your prompt

The model choice also affects how many iterations you'll need. Across the entire history of NeuralSpace vibe coding chats (662 chats), 62% of dialogs run on Kimi K2.5 — 410 chats, with another ~9% on Claude Sonnet 4.5 (source — anonymized generation history of the section). That folk statistics didn't come from nowhere: Kimi K2.5 is markedly cheaper and fully sufficient for typical projects — landing pages, trackers, dashboards, simple games. For projects with non-trivial logic (states, calculations, many screens), take Claude Sonnet 4.5: pricier, but it holds the intent more precisely in long dialogs. Switching is one click in the same interface, so a sensible scheme is: draft on the cheap model, final assembly on the strong one. A detailed price-vs-quality comparison is in the article "Which AI to choose for vibe coding", and a first project from scratch is covered in "Vibe coding from zero".

FAQ

Can I write the prompt in my own language?

Yes. Models in the vibe coding section handle English fine and reply in it; the site interface is localized too. The structure "outcome — context — constraints — data — definition of done — stop list" works in any language.

How long should a prompt be?

Long enough that the model has nothing left to guess. For a landing page, 5–8 lines suffice; for an app with logic, 15–25. The benchmark isn't characters but blocks: if behavior, constraints and the definition of done are described, the length is enough.

The agent did something wrong. What do I write?

A surgical edit: screen, element, desired behavior. "Redo everything" is the worst possible phrasing — it wipes out what worked too. If an edit broke the project, roll back via Project Versions.

Can I reuse one prompt across projects?

The template — yes: the six blocks are universal, only the content changes. But a finished text for one specific project is pointless to paste into another: their definitions of done and stop lists differ.