When you type "an appointment book for my barbershop," a working app does not simply appear seconds later; a few smart steps happen in between. Knowing those steps helps you steer the process and get better results.
The process has four stages: understanding your intent, filling gaps with questions, compiling everything into a brief, and building once you approve.
1. It understands your intent
First, the AI works out the job behind your sentence. When you say "appointment book," it infers this involves customers, time slots, services, maybe prices, and probably a daily calendar view. You name the job; it lists what the job requires.
2. It asks smart questions
Every business runs differently; the model knows this and asks instead of guessing. How many chairs do you have, how long is a typical appointment, do you reach customers by phone — a few short questions like these make the app your shop's, not a generic template.
These questions are not friction; they are insurance. One answer given up front prevents three corrections later.
3. It compiles a brief, you approve it
With your answers in hand, the model compiles the app's plan into a single brief: which screens exist, what data is stored, how the workflow runs. That brief comes to you for approval.
The approval screen is the most valuable moment in the process. Fixing a misunderstood detail here takes one sentence; fixing it after generation takes much longer. Actually read the brief — check that the scope and the data fields match your reality.
4. It generates screens, data, and flows
Once you approve, the model turns the brief into a complete app: the interface screens, the data layer that holds your records, and the flows connecting them are generated together. What comes out is not a fragmentary prototype but a whole, working tool.
Treat the first build as a strong first version, not the final product. Start using it, note what is missing; later lessons show how to fix those things just by describing them.