Prototyping with AI: from an interface to a working function

The session begins by requesting an application through chat and adjusting the output. To give that process direction, define a main action: what the user provides, what the application does and which result they receive.

For a thumbnail tool, start with a specific journey rather than a catalogue of features. State what is excluded too. This helps review the output and prevents a polished interface from hiding a task that does not yet exist.

In the demonstration, a button has no prepared destination, so I request that screen. Later, I distinguish the visible part from what needs to work behind it. That distinction matters when showing a prototype to someone else.

Check each journey using sample data. Label simulated results. To call it functional, verify the actual operation, response and behaviour when information is missing or an error occurs.

The class also covers environment files and repositories. One explanation needs clarification: naming a file .env does not protect its contents by itself. What matters is where it is used, what is published and what can reach the browser.

Store secrets in the server environment or the provider's designated system, and exclude them from the repository. Before publishing, review included files and variables exposed to the client. An already shared key needs revoking or rotating; renaming the file afterwards does not undo exposure.

The class shows different creation and hosting tools. Their plans and prices belong to the video's date, so I do not use them as current budgets here. Actual cost also depends on the services the application consumes.

Before delivery, test the published version: routes, forms, permissions and main operations. Check another session and a different user. A local prototype may depend on configuration that does not yet exist on the host.

The session emphasises testing and correcting. A request for help is more useful when it explains what you tried, what happened and what you expected. Include a small reproduction and avoid sharing credentials or client data.

The aim is to retain control of what you build. AI can help you progress, but delivery needs a clear scope and tests you can explain. That ability to review is part of the service you offer.