Prompt Engineering for AI App Builders

The quality of your AI-generated application depends largely on how well you communicate with the AI. Here’s how to write prompts that produce better results.

Be Specific About What You Want

Bad prompt: “Make a website” Good prompt: “Create a landing page for a SaaS product called TaskFlow. Include a hero section with headline, subheadline, and CTA button. Add a features section with 3 feature cards, and a pricing section with 3 tiers.”

Describe the User Experience

Don’t just describe features - describe how users interact with them. “When a user clicks the submit button, show a loading spinner, then display a success message and redirect to the dashboard after 2 seconds.”

Provide Context

Tell the AI about your audience and goals. “This is for non-technical small business owners who need a simple inventory management system. Keep the interface clean and avoid technical jargon.”

Use Examples

Reference known patterns. “Make the navigation similar to Notion’s sidebar” or “Use a card layout like Trello for the task board.”

Iterate Incrementally

Don’t try to describe everything at once. Build your application layer by layer, confirming each piece works before adding more complexity.

This matters in tools such as Lovable and Base44, where repeated fixes can consume the development budget. Specify what must stay unchanged, and check the actual user flow after a revision. If you want a visual workflow alongside prompts, include Figma Make in your comparison.

Common Patterns That Work

• “Add a [component] that [action] when [trigger]”
• “Make the [element] look like [reference]”
• “When [event], the app should [behavior]”
• “Include error handling for [scenario]”

Handling Unsatisfactory Results

If the output isn’t right, don’t start over. Point out specific issues: “The button color should be blue, not green” or “Move the sidebar to the left side of the screen.”