Lovable Prompting Guide: Build Apps with AI (2026)

Last month, I watched someone build a full SaaS app in 3 hours. Not a prototype. Not a mockup. A working, database-backed, authentication-enabled application that looked like it took weeks to build.

The secret? They knew how to prompt Lovable.

Here’s the thing most people get wrong: they treat Lovable like ChatGPT. They write vague requests, get frustrated when the output doesn’t match their vision, and give up thinking AI app builders “aren’t there yet.”

But Lovable isn’t ChatGPT. It’s not about having a conversation—it’s about architecting an application through natural language. And once you understand that difference, everything changes.

This guide will teach you everything I wish I knew before my first Lovable prompt. We’ll cover 30+ topics, from basic prompt anatomy to advanced debugging techniques, with ready-to-use templates for every major app type. Whether you’re building a simple CRUD app or a complex multi-tenant SaaS platform, you’ll find exactly what you need here.

Let’s dive in.

What “Prompting in Lovable” Really Means

If you’ve used ChatGPT or Claude, you already know how to prompt AI. But learn prompt engineering basics for chat is fundamentally different from prompting for app building.

With chat AI, you’re having a conversation. You ask a question, get an answer, maybe follow up. Each exchange is relatively independent.

With Lovable, you’re describing a product. Your prompt isn’t a question—it’s a blueprint. You’re not asking “How do I build a login page?” You’re saying “Build me a login page with email/password fields, a ‘Remember Me’ checkbox, and password reset functionality, styled with a modern dark theme.”

The difference is crucial. Chat prompting is about what you want to know. App-building prompting is about what you want to exist.

Here’s what makes Lovable unique:

• Full-stack generation: One prompt can create your database schema, API endpoints, and UI components simultaneously
• Iterative refinement: Lovable expects you to refine. Your first prompt is a starting point, not the finish line
• Context retention: Lovable remembers your previous prompts and builds on them
• Component thinking: The best results come from prompting by component (buttons, forms, cards) rather than entire pages

Think of it this way: if ChatGPT is a conversation partner, Lovable is a construction crew. You need to give them detailed blueprints, not casual suggestions.

How Lovable Interprets Prompts (Mental Model)

Before you write a single prompt, you need to understand what Lovable is looking for. A good prompt should include eight key elements:

1. What to build - The product goal in one sentence
2. Who it’s for - Your target user persona
3. Core workflows - What users will actually do in the app
4. Screens/pages required - The main views users will see
5. Data model - What information needs to be stored
6. Actions/logic - What happens when users interact
7. Constraints - Technical requirements, style preferences, branding
8. Success criteria - What “done” looks like for this iteration

Miss one of these, and Lovable has to guess. And AI guesses aren’t always what you want.

For example, here’s a vague prompt:

“Build me a task management app”

Lovable will build something, but it won’t be what you envisioned. You’ll get generic styling, basic CRUD operations, and no sense of your specific use case.

Now here’s a complete prompt:

“Build a task management app for freelancers managing client projects. Users should be able to create projects, add tasks with due dates and priority levels, and mark tasks complete. Main screens: Dashboard (showing all projects), Project Detail (showing tasks for one project), and Task Form. Store projects (name, client, status) and tasks (title, description, due date, priority, completed status). When a task is marked complete, show a success toast and update the project progress bar. Use a clean, professional design with a blue/white color scheme. MVP scope: just the core CRUD operations, no team collaboration yet.”

See the difference? The second prompt gives Lovable everything it needs to build exactly what you want.

Prompt Anatomy: The Perfect Structure Template

Let me give you a template you can copy-paste and customize for any project. This is the structure I use for every new Lovable app:

# [App Name]: [One-sentence purpose]

## Target Users
[Who will use this? Be specific: "Freelance designers managing client projects" not just "designers"]

## Core Features (MVP)
1. [Feature 1 - be specific about what it does]
2. [Feature 2]
3. [Feature 3]
[Limit to 3-5 for MVP]

## Pages & Navigation
- **[Page Name]**: [What's on this page, what can users do]
- **[Page Name]**: [Description]
[List all main screens]

## Database Schema
### [Entity 1] (e.g., Projects)
- field_name (type, required/optional, validation rules)
- field_name (type, default value)

### [Entity 2] (e.g., Tasks)
- field_name (type)
- relationship to [Entity 1]

## User Roles & Permissions
- **[Role Name]**: Can [action], can [action], cannot [action]
[If single-user app, you can skip this]

## Design & Branding
- **Style**: [Modern/Minimal/Professional/Playful]
- **Colors**: [Primary color, secondary color, or "use your judgment"]
- **Typography**: [Specific font or "clean sans-serif"]
- **Components**: [Any specific UI patterns you want]

## Key Workflows
1. **[Workflow Name]**: User does [step 1] → [step 2] → [result]
[Describe 2-3 critical user journeys]

## Edge Cases & Validations
- [What happens if user tries to X?]
- [Required field validations]
- [Error messages to show]

## Out of Scope (for now)
- [Feature you explicitly DON'T want yet]
- [This prevents Lovable from over-building]

Here’s a filled example for a freelancer CRM:

# FreelanceHub: Simple CRM for independent consultants

## Target Users
Freelance consultants and service providers who need to track clients, projects, and invoices without enterprise CRM complexity.

## Core Features (MVP)
1. Client management (add, edit, view client details)
2. Project tracking (link projects to clients, track status)
3. Simple invoicing (create invoices, mark as paid/unpaid)

## Pages & Navigation
- **Dashboard**: Overview of active projects, recent invoices, quick stats
- **Clients List**: Table of all clients with search and filters
- **Client Detail**: Individual client page showing their projects and invoices
- **Projects List**: All projects with status filters
- **Invoice Creator**: Form to generate new invoices

## Database Schema
### Clients
- name (string, required)
- email (string, required, must be valid email)
- company (string, optional)
- phone (string, optional)
- status (enum: active/inactive, default: active)
- created_at (timestamp, auto)

### Projects
- title (string, required)
- client_id (foreign key to Clients, required)
- description (text, optional)
- status (enum: planning/active/completed/on-hold, default: planning)
- budget (decimal, optional)
- start_date (date, required)
- end_date (date, optional)

### Invoices
- invoice_number (string, auto-generated, format: INV-YYYY-001)
- client_id (foreign key to Clients, required)
- project_id (foreign key to Projects, optional)
- amount (decimal, required, must be positive)
- status (enum: draft/sent/paid, default: draft)
- due_date (date, required)
- created_at (timestamp, auto)

## User Roles & Permissions
Single-user app (just the freelancer), no role system needed.

## Design & Branding
- **Style**: Clean, professional, not overly corporate
- **Colors**: Deep blue primary (#2563EB), light gray backgrounds (#F9FAFB)
- **Typography**: Modern sans-serif (Inter or similar)
- **Components**: Use card-based layouts, rounded corners, subtle shadows

## Key Workflows
1. **Add New Client**: Dashboard → "New Client" button → Fill form (name, email, company) → Save → Redirect to Client Detail page
2. **Create Invoice**: Client Detail page → "New Invoice" button → Select project (optional) → Enter amount and due date → Generate PDF preview → Save as draft or mark as sent
3. **Track Project**: Projects List → Click project → See linked client, status, dates → Update status with dropdown → Show success toast

## Edge Cases & Validations
- Can't delete a client if they have active projects (show error message)
- Invoice numbers must be unique (auto-increment)
- Email validation on client form
- Can't set project end_date before start_date
- Show empty states with helpful CTAs when no clients/projects exist

## Out of Scope (for now)
- Time tracking
- Team collaboration
- Payment processing integration
- Recurring invoices
- Email sending

Copy this template, fill in your details, and you’ll get 80% better results on your first prompt.

Prompting for Different Stages of Building

Here’s something I learned the hard way: the prompt you use for your MVP should be completely different from the prompt you use when scaling to production.

MVP Prompting: Speed Over Perfection

When you’re building an MVP, your goal is to validate an idea as fast as possible. Your prompt should reflect that:

Do:

• Focus on ONE core workflow
• Use simple data models
• Accept Lovable’s default styling choices
• Skip edge cases for now
• Explicitly say “MVP” or “simplest version”

Don’t:

• Try to build every feature at once
• Over-specify implementation details
• Worry about performance optimization
• Add complex role systems
• Include “nice-to-have” features

Example MVP prompt:

“Build the simplest version of a habit tracker. Users can add habits (just a name), mark them complete for today, and see a 7-day streak counter. One page, minimal styling, no user accounts yet—just localStorage. I want to test if people will actually use this before building more.”

Iteration Prompting: Refine Without Breaking

Once your MVP works, you’ll want to add features. This is where most people break their app. The key is being explicit about what NOT to change:

The magic phrase: “Add X without changing Y”

Example iteration prompts:

“Add user authentication with email/password. Keep all existing habit functionality exactly as is. Don’t change the database schema for habits—just add a users table and link habits to user_id.”

“Add a calendar view showing the last 30 days of habit completions. Keep the existing list view as the default. Add a toggle button to switch between views. Don’t modify the habit completion logic.”

“Improve the styling to look more professional. Use a calming green color scheme. Keep all existing functionality and layouts—just update colors, fonts, and spacing.”

See the pattern? You’re giving Lovable permission to change one thing while protecting everything else.

Production Prompting: The Details Matter

When you’re ready for real users, your prompts need to cover the unglamorous but critical details:

Production checklist prompts:

“Add proper error handling: show user-friendly error messages for network failures, validation errors, and server errors. Log errors to console for debugging.”

“Implement loading states for all data fetching. Show skeleton loaders for lists, spinner for buttons, and disable forms while submitting.”

“Add database indexes on user_id and created_at fields for the habits table. Implement pagination showing 20 habits per page.”

“Set up proper authentication: password must be 8+ characters, implement password reset via email, add ‘Remember Me’ functionality, auto-logout after 30 days.”

These aren’t exciting prompts, but they’re what separates a demo from a product.

UI/UX Prompting: Making Apps Beautiful

I’ve seen people build functionally perfect apps that look like they’re from 2005. The problem? Vague design prompts.

“Make it look good” doesn’t work. Lovable needs specifics.

Here’s how to prompt for professional UI:

Design System Prompt:

Create a consistent design system:
- Primary color: #6366F1 (indigo)
- Secondary color: #EC4899 (pink)
- Background: #F9FAFB (light gray)
- Text: #111827 (near black)
- Font: Inter for UI, Merriweather for content
- Border radius: 8px for cards, 4px for buttons
- Shadows: subtle (0 1px 3px rgba(0,0,0,0.1))
- Spacing: 4px base unit (use multiples: 8px, 16px, 24px, 32px)

Component-Specific Prompts:

For buttons:

“Primary buttons: solid indigo background, white text, 8px padding, hover state darkens by 10%. Secondary buttons: white background, indigo border and text, same hover behavior.”

For forms:

“Form inputs: light gray background, 1px gray border, focus state shows indigo border and subtle shadow. Labels above inputs in medium gray. Required fields have red asterisk. Show validation errors below field in red text.”

For empty states:

“When no data exists, show a centered illustration (use a simple SVG icon), a helpful message like ‘No projects yet’, and a prominent CTA button to create the first item.”

For loading states:

“Use skeleton loaders for list items: gray animated rectangles matching the final content layout. For buttons, show a spinner icon and disable the button with reduced opacity.”

Mobile Responsiveness:

Don’t assume Lovable knows you want mobile support. Be explicit:

“Make fully responsive for mobile, tablet, and desktop. On mobile (<640px): stack all columns vertically, use full-width buttons, hide sidebar in a hamburger menu. On tablet (640-1024px): 2-column grid. On desktop (>1024px): 3-column grid with persistent sidebar.”

Accessibility Prompts:

When building for real users, accessibility isn’t optional. According to WCAG 2.1 AA standards, your apps should meet specific accessibility requirements:

“Ensure all interactive elements are keyboard accessible with visible focus indicators. Add ARIA labels to icon-only buttons. Maintain 4.5:1 color contrast ratio for all text. Include skip-to-content link for screen readers.”

The more specific you are about design, the less time you’ll spend iterating on styling later.

Database & Data Modeling Prompting

Bad data models are the #1 reason Lovable apps break when you try to scale them. Get this right from the start.

I learned this lesson when I had to rebuild an entire app because I didn’t properly define relationships in my initial prompt. Three days of work, gone.

Entity Relationship Prompts:

For one-to-many relationships:

“A User can have many Projects. A Project belongs to one User. Store user_id as a foreign key in the projects table. When a user is deleted, also delete all their projects (cascade delete).”

For many-to-many relationships:

“Projects can have many Tags, and Tags can be on many Projects. Create a project_tags join table with project_id and tag_id. Allow users to add/remove tags from projects.”

Field Validation Prompts:

“Email field: must match email regex pattern, show error ‘Please enter a valid email’ if invalid. Required on signup, optional on profile update.”

“Password field: minimum 8 characters, must contain at least one number and one special character. Show strength indicator (weak/medium/strong) as user types.”

“Budget field: decimal with 2 decimal places, must be positive, default to 0. Format display with currency symbol and commas.”

Default Values & Timestamps:

“All tables should have created_at and updated_at timestamps that auto-populate. Status fields should default to the first option (e.g., ‘draft’ for invoices, ‘active’ for projects). Boolean fields like is_completed should default to false.”

Seed Data for Testing:

“Create 5 sample clients with realistic names and emails, 10 sample projects linked to these clients with varied statuses, and 15 sample invoices with different payment statuses. This helps me test the UI with realistic data.”

A well-designed data model makes everything else easier. A poorly designed one will haunt you forever.

Authentication & Authorization Prompting

Every production app needs proper authentication. Here’s how to prompt for it effectively.

Basic Email/Password Authentication:

“Implement user authentication with email and password. Users should be able to sign up with email, password (minimum 8 characters), and full name. On signup, send a verification email. Login requires verified email. Include ‘Remember Me’ checkbox that keeps users logged in for 30 days. Add password reset flow: user enters email, receives reset link, can set new password. Show appropriate error messages for invalid credentials, unverified email, or expired reset links.”

Social Login:

“Add Google and GitHub social login options. On the login page, show ‘Continue with Google’ and ‘Continue with GitHub’ buttons above the email/password form. On first social login, create user account automatically using their email and name from the provider. Link social accounts to existing users if email matches. Store provider info (google/github) and provider user ID for future logins.”

Role-Based Access Control:

“Implement three user roles: Admin, Manager, and User. Admins can: create/edit/delete all data, manage users, change user roles. Managers can: create/edit their own data, view all data, cannot delete or manage users. Users can: create/edit only their own data, view only their own data. Add a ‘role’ field to users table (enum: admin/manager/user, default: user). Protect routes based on role: /admin/* requires admin, /dashboard requires any authenticated user. Show/hide UI elements based on role (e.g., delete buttons only for admins).”

Permissions Matrix Prompt:

“Create a permissions system for a project management app. Define permissions: projects.create, projects.view, projects.edit, projects.delete, tasks.create, tasks.edit, tasks.delete, team.invite, team.remove. Admins have all permissions. Managers have all except team.remove. Users have projects.view, tasks.create, tasks.edit (own tasks only). Store permissions in a permissions table linked to roles. Check permissions before allowing actions. Show ‘Access Denied’ message if user lacks permission.”

The key is being explicit about who can do what. Don’t assume Lovable knows your security requirements.

Prompting for Integrations

Integrations are where Lovable really shines. Here’s how to prompt for the most common ones.

Stripe Payment Integration

“Integrate Stripe for subscription payments. Add three pricing tiers: Free ($0/month), Pro ($29/month), Enterprise ($99/month). On the pricing page, show tier comparison table with features. When user clicks ‘Subscribe to Pro’, redirect to Stripe Checkout with the pro_monthly price ID. After successful payment, Stripe webhook updates user’s subscription_tier and subscription_status in database. Show current plan on account settings page with ‘Manage Subscription’ button that opens Stripe customer portal. Handle subscription cancellation: keep access until period end, then downgrade to Free.”

Environment Variables for API Keys:

“Store Stripe API keys in environment variables: STRIPE_SECRET_KEY and STRIPE_PUBLISHABLE_KEY. Never hardcode keys in the code. Use the secret key for server-side operations, publishable key for client-side Stripe.js. Add a .env.example file showing which environment variables are needed without actual values.”

Email Integration

“Integrate Resend for transactional emails. Send welcome email on signup with subject ‘Welcome to [App Name]’ containing user’s name and a getting started guide link. Send password reset email with a secure token link valid for 1 hour. Send invoice email when invoice status changes to ‘sent’ with PDF attachment. Use environment variable RESEND_API_KEY for the API key. Create email templates with your brand colors and logo.”

Webhook Configuration

“Add webhook endpoint at /api/webhooks/stripe that receives Stripe events. Verify webhook signature using Stripe webhook secret. Handle these events: checkout.session.completed (create subscription), customer.subscription.updated (update subscription status), customer.subscription.deleted (cancel subscription). Log all webhook events to database for debugging. Return 200 status immediately, process events asynchronously to avoid timeouts.”

API Integration Pattern

“Integrate with [External API Name]. Store API key in environment variable API_KEY. Create an API client module that handles authentication, rate limiting, and error handling. When user triggers [action], call the API endpoint, handle success/error responses, and update UI accordingly. Cache API responses for 5 minutes to reduce API calls. Show loading state while API call is in progress. Display user-friendly error messages if API is down or rate limit is hit.”

I’ve integrated dozens of APIs with Lovable, and the pattern is always the same: be explicit about authentication, error handling, and environment variables.

Debugging & Fixing Broken Prompts

Things will go wrong. Here’s how to fix them without starting over.

Broken UI Layout

Problem: Elements are overlapping or positioned incorrectly.

Fix Prompt:

“Fix the dashboard layout. The sidebar is overlapping the main content on mobile. Change the layout to: on mobile (<768px), hide sidebar by default and show hamburger menu icon. When hamburger is clicked, sidebar slides in from left as overlay. On desktop (≥768px), sidebar is always visible, positioned fixed on the left, main content has left margin to account for sidebar width. Don’t change any functionality or data fetching logic.”

Wrong Database Relationships

Problem: Data isn’t linking correctly between tables.

Fix Prompt:

“Fix the project-client relationship. Currently projects aren’t properly linked to clients. Update the projects table: ensure client_id is a foreign key referencing clients.id. When displaying a project, fetch and show the related client name. When deleting a client, either prevent deletion if they have projects (show error: ‘Cannot delete client with active projects’) or cascade delete all their projects (ask user to confirm). Don’t change the projects or clients table structures otherwise.”

Missing Validations

Problem: Users can submit invalid data.

Fix Prompt:

“Add validation to the invoice form. Amount must be a positive number greater than 0. Due date must be today or in the future, not in the past. Client must be selected (required field). Show validation errors in red text below each field. Disable submit button until all validations pass. If user tries to submit invalid form, highlight invalid fields and scroll to first error.”

Performance Issues

Problem: Page loads slowly with lots of data.

Fix Prompt:

“Optimize the projects list page performance. Currently loading all projects at once is slow. Implement pagination: show 20 projects per page, add Previous/Next buttons at bottom. Add loading skeleton while fetching data. Implement search filter: add search input that filters projects by name or client name in real-time (debounced by 300ms). Add database index on projects.created_at and projects.client_id for faster queries.”

The Magic Debugging Phrase:

“Fix [specific issue] without changing [everything else that works]”

This tells Lovable exactly what to fix while protecting the rest of your app.

Common Prompting Mistakes (And How to Avoid Them)

I’ve seen these mistakes cost people hours of frustration. Learn from them.

Mistake #1: Being Too Vague

Bad Prompt:

“Build me a dashboard”

Why It Fails: Lovable has to guess what data to show, how to organize it, what actions users can take.

Good Prompt:

“Build an analytics dashboard showing: total revenue (big number at top), revenue trend chart (last 30 days), top 5 products by sales (bar chart), recent orders table (last 10, with customer name, amount, status). Use card-based layout, charts in 2-column grid on desktop, stacked on mobile.”

Lesson: Specify exactly what you want to see and how it should be organized.

Mistake #2: Over-Specifying Implementation Details

Bad Prompt:

“Use React Query for data fetching, implement custom hooks for each API call, use Zustand for state management, create a custom axios instance with interceptors…”

Why It Fails: Lovable has its own tech stack and patterns. Over-specifying implementation details conflicts with its architecture.

Good Prompt:

“Fetch projects from the API when the dashboard loads. Show loading state while fetching. Cache the data so it doesn’t refetch on every page visit. Refresh data when user clicks a refresh button.”

Lesson: Describe what you want to happen, not how to implement it technically.

Mistake #3: Not Defining Data Relationships

Bad Prompt:

“Create tables for users, projects, and tasks”

Why It Fails: Lovable doesn’t know how these tables relate to each other.

Good Prompt:

“Create three tables: Users (id, name, email), Projects (id, name, user_id as foreign key to Users), Tasks (id, title, project_id as foreign key to Projects). A user can have many projects. A project belongs to one user and can have many tasks. A task belongs to one project.”

Lesson: Always explicitly define relationships between entities.

Mistake #4: Forgetting Edge Cases

Bad Prompt:

“Add a delete button for projects”

Why It Fails: What happens if the project has tasks? What if it’s the user’s last project? No confirmation?

Good Prompt:

“Add delete button to each project. Before deleting, show confirmation dialog: ‘Delete [project name]? This will also delete all X tasks in this project. This cannot be undone.’ If user confirms, delete project and all associated tasks (cascade delete). If project has no tasks, just show ‘Delete [project name]? This cannot be undone.’ After deletion, show success toast and refresh project list.”

Lesson: Think through edge cases and error states upfront.

Mistake #5: Trying to Build Everything at Once

Bad Prompt:

“Build a complete project management app with projects, tasks, subtasks, comments, file attachments, time tracking, invoicing, team collaboration, notifications, calendar view, Gantt charts, and reporting dashboard.”

Why It Fails: Too much complexity in one prompt leads to bugs, missing features, and a confused AI.

Good Prompt (MVP):

“Build the simplest version: users can create projects (just name and description), add tasks to projects (title, description, due date, status: todo/in-progress/done), and mark tasks complete. One dashboard showing all projects, click project to see its tasks. That’s it for now.”

Lesson: Start with MVP, iterate to add features one at a time.

Mistake #6: Ignoring Mobile Responsiveness

Bad Prompt:

“Create a three-column layout with sidebar, main content, and activity feed”

Why It Fails: This works on desktop but breaks on mobile.

Good Prompt:

“Create a responsive layout: on desktop (≥1024px), show three columns (sidebar 250px, main content flexible, activity feed 300px). On tablet (768-1023px), hide activity feed, show two columns (sidebar 200px, main content flexible). On mobile (<768px), hide sidebar in hamburger menu, show only main content full-width.”

Lesson: Always specify responsive behavior for mobile, tablet, and desktop.

Mistake #7: Not Specifying Error Handling

Bad Prompt:

“Add a form to create new clients”

Why It Fails: What happens if the API fails? If email is invalid? If user is offline?

Good Prompt:

“Add client creation form with name (required), email (required, must be valid email), phone (optional). Validate on submit: show error messages below fields if invalid. On submit, show loading spinner on button. If successful, show success toast ‘Client created!’ and redirect to client detail page. If API error, show error toast ‘Failed to create client. Please try again.’ and keep form data so user doesn’t lose their input.”

Lesson: Explicitly define success states, error states, and loading states.

Mistake #8: Assuming Lovable Knows Your Domain

Bad Prompt:

“Build a CRM for real estate agents”

Why It Fails: Lovable doesn’t know real estate terminology or workflows.

Good Prompt:

“Build a CRM for real estate agents. Track Leads (potential buyers: name, email, phone, budget, preferred location), Properties (listings: address, price, bedrooms, bathrooms, status: available/pending/sold), and Showings (appointments: lead_id, property_id, date/time, notes). Agents can schedule showings by selecting a lead and property, mark properties as sold, and see all upcoming showings on a calendar view.”

Lesson: Explain domain-specific concepts and workflows explicitly.

Mistake #9: Not Testing Incrementally

Bad Approach: Write a massive prompt, hit enter, hope it works perfectly.

Why It Fails: When something breaks, you don’t know which part of the prompt caused it.

Good Approach:

1. Start with basic structure (MVP prompt)
2. Test it works
3. Add one feature (iteration prompt)
4. Test it works
5. Add next feature
6. Repeat

Lesson: Build and test incrementally, not all at once.

Mistake #10: Not Saving Successful Prompts

Bad Habit: Write prompts, get them working, forget what you wrote.

Why It Fails: You’ll need similar prompts later and have to start from scratch.

Good Habit: Keep a prompt library. When a prompt works well, save it:

prompts/
  auth/
    - email-password-signup.md
    - social-login.md
    - password-reset.md
  integrations/
    - stripe-subscription.md
    - email-sending.md
  ui/
    - responsive-dashboard.md
    - data-table-with-filters.md

Lesson: Build a reusable prompt library for future projects.

Real Case Studies: Prompts That Worked

Let me show you real examples of apps built with Lovable, including the exact prompts used and lessons learned.

Case Study 1: FreelanceHub CRM (3 iterations, 2 hours)

Initial Prompt (MVP):

“Build a simple CRM for freelance consultants. Track Clients (name, email, company, phone, status: active/inactive) and Projects (title, client_id, description, status: planning/active/completed, start_date, end_date, budget). Dashboard shows active projects count, recent clients, and project status breakdown. Clients page has searchable table. Client detail page shows their projects. Clean, professional design with blue/white color scheme.”

Result: Basic CRUD working, but missing key features.

Iteration 2 Prompt:

“Add invoicing feature. Create Invoices table (invoice_number auto-generated as INV-YYYY-001, client_id, project_id optional, amount, status: draft/sent/paid, due_date). On client detail page, add ‘New Invoice’ button. Invoice form lets you select project (optional), enter amount and due date. After creating invoice, show it in a list on client detail page. Add invoice status badges (draft=gray, sent=blue, paid=green).”

Result: Invoicing works, but UX needs improvement.

Iteration 3 Prompt:

“Improve invoice UX. On invoice list, add quick actions: ‘Mark as Sent’ button for draft invoices, ‘Mark as Paid’ button for sent invoices. Add filters: show all/draft/sent/paid invoices. Add total amount summary at top showing total unpaid amount. Make invoice numbers clickable to view invoice detail page showing all fields and client info.”

Final Result:

• Fully functional CRM
• 3 prompts total
• 2 hours from idea to working app
• Deployed to production, used by 5 freelancers

Lessons Learned:

1. Start with core entities and relationships
2. Add features one at a time
3. UX improvements come after functionality works
4. Specific color schemes and design details matter

Time Saved: Would have taken 2 weeks to code from scratch.

Case Study 2: Habit Tracker (5 iterations, 3 hours)

Initial Prompt:

“Build a habit tracker. Users can add habits (name, description, frequency: daily/weekly), mark them complete for today, and see a 7-day streak counter. One page showing all habits as cards. Each card shows habit name, current streak, and a checkmark button to mark complete for today. If already completed today, show green checkmark (disabled). Use calming green/white color scheme.”

Iteration 2:

“Add user authentication. Email/password signup and login. Each user sees only their own habits. Add user_id foreign key to habits table. Redirect to login if not authenticated. After login, redirect to habits dashboard.”

Iteration 3:

“Add calendar view. Show last 30 days in a grid (like GitHub contribution graph). Each day is a small square: green if habit was completed that day, gray if not. Click a day to see which habits were completed. Add toggle button to switch between list view and calendar view.”

Iteration 4:

“Add habit categories. Create Categories table (name, color). Add category_id to habits. On habits page, add filter dropdown to show all habits or filter by category. Show category color as a small dot next to habit name.”

Iteration 5:

“Add statistics page. Show: total habits, total completions, current longest streak (across all habits), completion rate this week (percentage). Show a chart of completions over last 30 days. Add navigation: Dashboard, Calendar, Stats.”

Final Result:

• Full-featured habit tracker
• 5 iterations over 3 hours
• Deployed and used by 50+ users

Lessons Learned:

1. Authentication should be iteration 2, not in MVP
2. Visual features (calendar, charts) are easier than expected
3. Categories/filtering add a lot of value
4. Users love stats and visualizations

Iteration Count Breakdown:

• MVP: Core functionality
• +1: Auth (critical for multi-user)
• +1: Calendar view (user request)
• +1: Categories (organization)
• +1: Stats (engagement boost)

Time Saved: Would have taken 1 week to code from scratch.

Case Study 3: Invoice Generator (2 iterations, 1 hour)

Initial Prompt:

“Build an invoice generator. User enters: client name, client email, invoice date, due date, line items (description, quantity, rate). Calculate total automatically. Generate PDF preview. Allow download as PDF. Store invoices in database with status (draft/sent). Simple, clean design.”

Iteration 2:

“Add invoice templates. Create 3 templates: Professional (blue header, formal), Creative (colorful, modern), Minimal (black and white, simple). Let user select template before generating PDF. Save template preference per user. Add company logo upload (user can upload their logo, shows on invoice). Add company details form (company name, address, phone, email) that auto-fills on invoices.”

Final Result:

• Professional invoice generator
• 2 iterations in 1 hour
• Used to generate $50K+ in invoices

Lessons Learned:

1. PDF generation works out of the box
2. Templates add huge perceived value
3. Auto-calculations are reliable
4. Simple tools can solve real problems

Why It Worked:

• Focused on one thing (invoices)
• Clear, specific requirements
• Didn’t over-complicate

Time Saved: Would have taken 3-4 days to code from scratch.

Key Patterns Across All Case Studies

1. MVP First: All started with simplest version
2. Iteration Count: 2-5 iterations is normal
3. Time Investment: 1-3 hours to working app
4. Prompt Specificity: More specific = better results
5. One Feature at a Time: Never added multiple complex features in one prompt
6. Real Usage: All deployed to production and actively used

Common Success Factors

• ✅ Clear data model from the start
• ✅ Specific design preferences (colors, layout)
• ✅ Explicit relationships between entities
• ✅ Edge cases defined upfront
• ✅ Incremental feature additions
• ✅ Testing after each iteration

Common Failure Factors (From Projects That Struggled)

• ❌ Vague initial prompt
• ❌ Trying to build too much at once
• ❌ Not defining data relationships
• ❌ Changing requirements mid-iteration
• ❌ Not testing incrementally
• ❌ Over-specifying technical implementation

The pattern is clear: start simple, be specific, iterate methodically.

Frequently Asked Questions

How long should a Lovable prompt be?

There’s no strict limit, but aim for clarity over length. A good prompt is typically 100-500 words. Include all essential details (data model, pages, workflows) but avoid unnecessary fluff. Use the prompt anatomy template from earlier as a guide—if you’ve covered those 8 key elements, you’re probably good.

Can I use Lovable for production apps?

Yes! Many production apps are built with Lovable. However, consider exporting the code for mission-critical applications, adding custom security layers if needed, and implementing proper testing and monitoring. Have a backup plan if you need to migrate away from Lovable later.

What if Lovable doesn’t understand my prompt?

Break it down into smaller, more specific prompts. Use the prompt anatomy template to ensure you’re covering all necessary elements. Be more explicit about data relationships and provide examples or reference apps. If Lovable builds something close but not quite right, use iteration prompts: “That’s close, but change X to Y.”

How do I handle complex business logic?

Start with Lovable for scaffolding and UI, then use prompts to define the logic flow step-by-step. For highly specialized logic, consider exporting the code and adding custom implementation. Break complex logic into smaller, manageable pieces and prompt for each piece separately.

Can I export code from Lovable?

Yes, Lovable allows code export. This is useful when you need to add highly custom logic, integrate with legacy systems, optimize performance, or transition to traditional development. Export when Lovable has built 80% of what you need and you want to hand-code the remaining 20%.

How many iterations does it typically take?

For most apps: simple CRUD apps take 2-5 prompts, medium complexity apps take 5-15 prompts, and complex apps take 15-30+ prompts. Expect iteration—it’s part of the process. Each refinement gets you closer to your vision.

What’s the best way to learn Lovable prompting?

Start with simple projects (a to-do list or habit tracker), study the case studies in this guide, use the prompt templates provided, join the Lovable community, iterate and learn from mistakes, and build a personal prompt library of what works for you.

How do I prompt for mobile responsiveness?

Be explicit: “Make the app fully responsive for mobile, tablet, and desktop. Use mobile-first design approach. Ensure touch-friendly buttons (minimum 44x44px). Test on viewport sizes: 375px (mobile), 768px (tablet), 1024px (small desktop), 1440px (large desktop).”

Can Lovable handle authentication and authorization?

Yes! Specify in your prompt: authentication method (email/password, social login), user roles (admin, manager, user), permissions matrix (who can view/edit/delete what), and which routes and pages should be protected. Lovable can implement standard auth patterns effectively.

What are the limitations of Lovable?

Lovable may struggle with highly specialized algorithms, complex integrations might need custom code, performance optimization may require manual tuning, domain-specific logic might need clarification, and it’s best for web apps (not native mobile apps yet). For these cases, use Lovable for the foundation and add custom code where needed.

Your Prompting Journey: Next Steps

You now have everything you need to build professional apps with Lovable. But knowledge without action is just entertainment.

Here’s what I recommend:

Start small. Don’t try to build your dream SaaS on day one. Build a simple habit tracker or to-do list. Get comfortable with the prompt → iterate → refine cycle. Learn what “good enough” looks like for an MVP.

Build your prompt library. Every time you write a prompt that works well, save it. Organize by app type (CRUD, SaaS, marketplace). Document what worked and what didn’t. Future you will thank present you.

Join the community. The Lovable Discord is full of builders sharing prompts, debugging together, and showcasing what they’ve built. You’ll learn faster by seeing what others are doing.

Know when to level up. Lovable is incredible for getting to 80% quickly. But sometimes you need that last 20% to be custom-coded. Don’t be afraid to export your code and add the specialized logic yourself. The best builders use Lovable for scaffolding and code for the complex stuff.

The future of app development isn’t “AI or developers.” It’s AI-assisted developers building 10x faster than before. Lovable is your force multiplier.

Now go build something.

And if you want to dive deeper into AI skills to learn in 2026, check out our comprehensive guide on the essential capabilities every builder needs to master.