Lovable Prompting Guide: Best Practices for AI App Building

The Golden Rule: Be Specific

Vague prompts produce vague results. Specific prompts produce specific results.

Bad Prompt:

Build me a todo app

Good Prompt:

Build a task management app with:
- User authentication (email/password)
- Tasks with: title, description, due date, priority (low/medium/high), status (todo/in-progress/done)
- Dashboard showing tasks grouped by status in columns (Kanban style)
- Ability to drag tasks between columns
- Filter tasks by priority and due date
- Use a clean, minimal design with a blue accent color

The good prompt tells Lovable exactly what to build, eliminating guesswork.

Structure Your Prompts

Use a consistent structure for complex requests:

The CFDS Framework:

• Context: What are you building?
• Features: What should it do?
• Data: What data is involved?
• Style: How should it look?

Example:

Context: I'm building a SaaS for freelancers to track invoices.

Features:
- Create invoices with line items
- Mark invoices as paid/unpaid
- Dashboard showing total revenue and outstanding amount
- Client management

Data:
- Clients: name, email, company
- Invoices: client_id, items (array), total, status, due_date
- Invoice items: description, quantity, unit_price

Style: Clean, professional, use green for positive amounts, red for overdue

Iterate in Small Steps

Don't try to build everything at once. Build incrementally:

1. Start with structure — Navigation, layout, basic pages
2. Add auth — User signup, login, protected routes
3. Build core feature — The main thing users come for
4. Add supporting features — Settings, analytics, etc.
5. Polish — Error handling, loading states, mobile

Why This Works:

• Each step builds on a working foundation
• Easier to catch and fix issues early
• Less context for AI to manage at once
• Clearer feedback on what's working

Common Mistakes to Avoid

1. Too Much at Once

Wrong: "Build me a complete CRM with contacts, deals, pipelines, email integration, reporting, team permissions, and API access."

Right: Start with contacts only, then add features one by one.

2. Ambiguous Requirements

Wrong: "Make the dashboard look better."

Right: "Add more whitespace between cards, use a softer shadow, and increase the font size of the numbers."

3. Ignoring Errors

When something breaks, don't just re-prompt. Read the error message and address it specifically.

4. Not Testing Between Steps

After each change, actually test the app. Don't stack up multiple changes before checking if they work.

Prompt Templates That Work

New Feature:

Add [feature name] to [location]. It should:
1. [First requirement]
2. [Second requirement]
3. [Third requirement]
Store data in [table name] with fields: [field list].
Style it to match the existing [reference component].

Bug Fix:

There's an issue with [feature]. When I [action], [unexpected behavior] happens. It should [expected behavior] instead. The relevant code is probably in [file/component if known].

UI Change:

Update the [component] to:
- Change [specific element] to [new state]
- Add [new element] that [does what]
- Remove [element to remove]
Keep everything else the same.

Advanced Techniques

Reference External Examples

"Style the pricing page similar to Linear's pricing page — minimal, with a toggle between monthly/annual and feature comparison table."

Specify Technology Choices

"Use React Query for data fetching and Zustand for client state. Don't use Redux."

Ask for Explanations

"After building this, explain how the authentication flow works so I can modify it later."

Request Tests

"Add unit tests for the invoice calculation logic using Vitest."

Quick Reference Checklist

Before sending a prompt, check:

• Is the goal clear?
• Are requirements specific?
• Is this a reasonable scope for one prompt?
• Have I specified data structures?
• Have I mentioned styling preferences?
• Did I test the previous change first?

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