The clearer your context, the better your results.
2/ Master the 4 levels of prompting
Level 1: Training Wheels
Use labeled sections in your prompts:
- Context (what you're building)
- Task (what you want)
- Guidelines (how to do it)
- Constraints (what to avoid)
Example:
Bad: "Build me a login page"
Good:
Context: I'm building a SaaS app for small businesses
Task: Create a login page with email/password
Guidelines: Use React, make it mobile-friendly
Constraints: Don't use any external auth services
Structure helps AI understand exactly what you want.
Level 2: No Training Wheels (conversational)
Level 3: Meta Prompting (use AI to improve your prompts)
Level 4: Reverse Meta (document solutions for future use)
3/ Use the "Diff & Select" approach
Don't let Lovable rewrite entire files.
Add this to prompts: "Implement modifications while ensuring core functionality remains unaffected. Focus changes solely on [specific component]."
Fewer changes = fewer errors.
4/ Always start with a blank project
Build gradually instead of asking for everything at once.
Follow this order:
• Front-end design (page by page, section by section)
• Backend using Supabase integration
• UX/UI refinements
5/ Chat Mode vs Default Mode
Chat Mode: Planning, debugging, asking questions
Default Mode: High-level feature creation
Use Chat mode to think through problems.
Use Default mode to execute solutions.
6/ Debug like a pro
When errors happen:
→ Use "Try to Fix" button
→ Copy error to Chat mode first
→ Ask: "Use chain-of-thought reasoning to find the root cause"
→ Then switch to Edit mode
7/ Mobile-first prompting
Add this to every prompt:
"Always make things responsive on all breakpoints, with a focus on mobile first. Use shadcn and tailwind built-in breakpoints."
Most users are on mobile anyway.
8/ Step-by-step beats everything at once
Don't assign 5 tasks simultaneously.
The article specifically says: "Avoid assigning five tasks to Lovable simultaneously! This may lead the AI to create confusion."
One task at a time = fewer hallucinations.
9/ Lock files without a locking system
Add to prompts: "Please refrain from altering pages X or Y and focus changes solely on page Z."
For sensitive updates: "This update is delicate and requires precision. Examine all dependencies before implementing changes."
10/ Refactoring that works
When Lovable suggests refactoring:
"Refactor this file while ensuring UI and functionality remain unchanged. Focus on enhancing code structure and maintainability. Test thoroughly to prevent regressions."
Want the full breakdown?
The complete Lovable Prompting Bible covers:
• Advanced debugging strategies (10+ specific prompts)
• Integration with make and n8n
• Stripe setup prompts
• 20+ copy-paste prompts
If you’re using @lovable_dev to build apps, read this first
This is everything I wish I knew before starting ↓
1. Nail your first prompt
I always start inside my custom GPT, SnapPrompt, and get the full prompt for my landing page first.
This includes layout, structure, typography, and design style. I just copy-paste that into Lovable with a design reference attached and it gives me a clean starting point.
2. Always prep your technical docs before starting in Lovable
Don’t dive in blind.
Have your DB design, UI Dev plan, MVP plan, and implementation plan ready.
Keep it simple, generate them during the planning phase using GPT or Gemini.
Then just paste them as .md files into Lovable.
That way, Lovable has full context about your product from the start.
Claude with CodeRabbit + TaskMaster is crazy good.
Now you can Plan with AI, Code with AI, Review with AI.
Here’s the full workflow I use to build MVPs fast and stress-free ↓
1/ The workflow (quick summary)
This is the exact system I follow:
• Plan clearly (PRD) with @ChatGPT
• Break it down using TaskMaster
• Execute one task at a time using Claude Code inside Cursor
• Review everything with @coderabbitai
Let’s go deeper ↓
2/ Vibe coding used to slow me down
I’d give a vague prompt like “build a landing page”
Claude would generate something, but it’d be a mess:
• Half-baked logic
• Features I never asked for
• Debugging spiral
I don’t use Figma.
I don’t write every line of code.
I don’t need big teams.
Here’s the exact AI-powered system I use to plan, build, and launch real MVPs in 3 weeks for clients ↓
1. Plan using ChatGPT
Before building, I plan fast:
- ChatGPT voice to brainstorm the client idea
- Generate docs (PRD, UI Dev Plan, DB design)
- MoSCoW Method to define essentials
This gives:
- A clear feature list
- A lean scope
- Zero ambiguity
2. Skip traditional design, go straight to dev
Most devs waste weeks designing in Figma.
I use @lovable_dev instead.
It:
- Turns text into full responsive UIs
- Connects real data
- Handles auth, forms, routing
Build 70-80% of your MVP inside Lovable, depending on the complexity of your project, and then switch to cursor/claude code.