Turn Any Idea Into an AI-Powered Site With Lovable

Start with the idea in plain English. Explain the problem, the finished experience, and the visual reference you want to use. The goal is to give ChatGPT enough context to ask useful questions before you start building.

For this example, attach the reference card and describe Method as a simple app that accepts a recipe, turns it into a visual card, lets the user review or edit the result, and saves it to a library.

Use a prompt like this:

I want to build a small app called [APP_NAME]. A user pastes [INPUT], and the app turns it into [OUTPUT] inspired by the attached reference. The user can review or edit the result, then save it to a library.

Help me think through the idea. Ask only the questions that would materially improve the first version. Keep the product focused on one core journey, and do not write the build brief yet.

Answer the questions that change the product experience. For Method, those decisions included preserving the original recipe where possible, allowing the user to edit or reorder steps, and flagging guesses instead of silently presenting them as facts.

Keep this conversation separate from the build brief. You are using it to find the important product decisions, not to produce a technical specification.

Pro tip: Start with an interview, then ask for the build brief. This gives you a chance to catch missing product decisions before the app builder starts making them for you.

Once the core journey is clear, ask ChatGPT to compress the conversation into a short handoff. This is the document you will give Lovable.

Ask for four things:

• A one-paragraph product summary.
• The first-version feature requirements and user flow.
• The required screens and important states.
• The brand feel, color palette, and suggested typography.

Use this prompt in the same conversation:

Based on our conversation, write the handoff I can give to an AI app builder.

Include:
1. One-paragraph product summary
2. First-version feature requirements and user flow
3. Required screens and important states
4. Brand feel, color palette, and suggested typography

Keep it concise and implementation-agnostic. Do not prescribe a framework, database schema, component library, or API architecture. Mention that the attached image is the visual and information-design reference.

Read the result once before copying it. Remove features that do not support the first loop. For Method, that loop is paste, convert, review, edit, save, and reopen.

Keep the handoff focused on what the product should do and how it should feel. Lovable can choose the implementation details it is built to support.

Create a new Lovable project and attach the same visual reference. Paste the ChatGPT handoff with a second prompt that asks for the complete first version.

Use an outcome-first request:

Build the complete first version of [APP_NAME] from the requirements and brand brief below.

Use the attached image as inspiration for the information design, but create an original product and visual identity. Keep the first version focused on the core journey and make sensible product decisions when details are not specified.

Use the AI capability available in this Lovable project to turn [INPUT] into the structured, editable [OUTPUT] described in the brief. Preserve stated values, flag ambiguity for review, and show a useful loading state and error state that preserves the original input.

Build the complete experience in one pass, including the main screen, the generated result, editing, saving, and reopening the saved result.

[PASTE THE CHATGPT REQUIREMENTS AND BRAND BRIEF]

Select Plan before you approve the build. Read the proposed screens, states, and core flow. This is the point where you can catch a missing feature or a wrong assumption while the product is still easy to change.

When the plan is right, approve it and let Lovable build the first version. In Connectors, open Cloud AI and enable Lovable’s built-in AI. That is what the recorded workflow used, so the recipe conversion did not require a ChatGPT integration or an OpenAI API key. Lovable’s current documentation describes Cloud as its built-in backend with AI, Secrets, and server-side Edge Functions available from the project. You can review the current Lovable connectors (https://docs.lovable.dev/integrations/introduction) and Lovable Cloud (https://docs.lovable.dev/features/cloud) documentation as the labels change.

Pro tip: Attach the visual reference to Lovable before you approve the plan. The finished design is much closer when the builder can see the information hierarchy instead of trying to infer it from prose alone.

Let the first build finish before adding refinements. Judge it against the core journey and the reference, not against an imagined technical stack. If one visible part misses, ask for one focused correction.

Test the product as a user:

• Paste a recipe with a clear title, ingredient list, and ordered instructions.
• Start the conversion and wait for the generated card.
• Compare quantities, temperatures, timing, and other important source details.
• Edit one label or operation.
• Save the card and reopen it from the library.
• Check the result at a narrow screen width.
• Test blank input and an AI or provider failure.
• Set an AI-token limit before publishing if you plan to make the app public.
• Run Lovable’s security checks before publishing, then smoke-test the live URL.

The recorded Method build showed why the review step matters. A first recipe paste could not be structured. A more clearly organized recipe produced a usable card. The app should give the reader a result to review, rather than forcing them to manually format every field before seeing the payoff.

Use a reusable test prompt like this:

Test the complete [APP_NAME] journey in the browser: paste [TEST_RECIPE], convert it, review the source values, edit one label, save it, reopen it from the library, and check the result at mobile width.

Also test blank input and an AI or provider failure. The pasted input must not disappear on error. Run the platform’s security checks and report any blocker before publishing. Fix only issues in the core flow; do not add features.

Pro tip: If the input cannot be structured, improve the source text before changing the app. A clear title, ingredient list, and ordered steps give the converter enough structure to produce a useful first draft.

Do not treat the generated card as authoritative just because it looks polished. Verify the source values first, then save the edited result.