Seven stages from a sentence to a live app
Stunning is not a single AI call that spits out a page. It is a loop: the model observes the project, acts with a tool, verifies the result, and repeats until the app works.
- 01
You describe the app
You type a request in plain English — a store, a booking system, a dashboard. No spec, no wireframe, no schema. The model also reads the project's saved memory, so it already knows your market, language and currency from earlier conversations.
Input: natural language + project context - 02
The agent reads the project
Before writing anything, the agent inspects what already exists — it lists files, opens the ones it needs, and checks the current data shape. This is why follow-up changes land in the right place instead of rebuilding from scratch.
Tools: list files, read file, search - 03
It plans, then writes real files
The model decides which files to create or edit and writes complete, working source — interface components, styling, and the data layer. It batches independent changes together so a multi-file feature lands in one pass.
Tools: write file, edit file - 04
It installs what it needs
Need animation, icons, routing or charts? The agent installs the library itself, choosing well-maintained packages with proper type definitions rather than hand-rolling fragile code.
Tools: install package - 05
It wires up the data layer
Tables, indexes and the functions that read and write them are generated to match exactly. Because the database is reactive, any screen showing that data updates the instant it changes — no refresh logic to write.
Reactive queries, live updates - 06
It checks its own work
Every change is type-checked against the whole project. If something is wrong, the agent gets the full list of errors back and fixes all of them in one pass — then checks again.
Automatic verification loop - 07
It ships
The backend is pushed live and the preview restarts in one step. You are looking at a running application, not a mock-up — and publishing it to a real URL is a single click.
Live preview + one-click publish
The loop is what makes it reliable
A single AI response can be wrong. A loop that checks its own output and corrects it is what turns a plausible answer into a working application.
Errors get fixed, not shipped
The agent sees the exact failures and corrects them before you ever look at the screen.
Changes are surgical
Because it reads before it writes, a small tweak stays a small tweak.
You stay in control
Every step is visible in the conversation, and you can rewind to any earlier point.