After using @Lovable on 50+ projects, this is how I make sure the UI never looks mid.

AI can design just fine. You are just prompting it wrong.

Here is my actual workflow for shipping clean UI with Lovable.

👇 1/ Start with a reference, not a description

Describing layouts from scratch almost always leads to messy output.

I take a screenshot from Dribbble, drop it into ChatGPT, and ask it to generate a design.json that includes colors, spacing, typography, and layout rules.

Then I tell Lovable to use it for styling only.

This gives me consistent output from the very first screen.

Cursor + Opus 4.5 is the fastest way to build right now.

But here's the problem no one talks about:
AI-generated code has 1.7x more issues than human-written code.

Here's how to stop shipping broken apps. 👇 1/ The real problem with vibe coding

AI writes clean-looking code. You deploy it. Users find bugs you missed.
1.75x more logic errors. 1.4x more critical issues. 2.74x more XSS vulnerabilities.

Speed is useless if the code breaks at 10 users.
coderabbit.ai/blog/state-of-…

I reverse-engineered how Lovable's top users build apps 10x faster.

Turns out, It's not about writing longer prompts.

It's about this structured prompting system nobody talks about ↓ 1/ Create a Knowledge Base before you build

Include these in your project settings:

• Project Requirements Document (PRD)
• User flow explanation
• Tech stack details
• Design guidelines
• Backend structure

The clearer your context, the better your results.

Most AI websites still look mid.

Not because AI can't design. Because people skip the basics.

Here's my actual workflow for building beautiful websites with Cursor/ Claude. 👇 1/ Decide your colors before you write a single prompt

Most people jump straight into Claude and wonder why everything looks inconsistent.

I spend 5 minutes on Coolors first. Pick a palette. Export it.

This one decision saves hours of "make it look better" prompts later.

Cursor's new Plan Mode is INSANE.

Combine it with CodeRabbit and you can build anything.

Here's the full workflow I use to ship MVPs fast and stress-free ↓ 1/ The workflow (quick summary)

This is the system that actually works for me:

Plan clearly with a PRD using @ChatGPTapp
Break it down with Cursor’s Plan Mode
Execute one task at a time in @cursor_ai
Review everything with @coderabbitai

Let’s go deeper ↓

This is huge.

@Lovable just added n8n MCP integration.

You can now turn any n8n automation into a SaaS app.

Full breakdown 👇 1/ The old way was painful

Before this update, connecting a frontend to n8n was messy.

You had to explain everything to the AI.

“This is the webhook URL.”
“This is the payload structure.”
“This is the response format.”

It worked, but it was slow and brittle.

How to actually make your AI-built apps secure (from someone who ships MVPs for a living)

We’ve shipped 45+ AI-built MVPs and learned security the hard way.

If you’re building with Cursor this is how to stay safe 👇 1/ Don’t blindly trust the agent

Cursor flies through code, which is great… until it isn’t.

One of our client projects looked perfect on the surface. @coderabbitai flagged a race condition in the payment system that was actually double-charging users.

The dev thought everything was fine. In production that would have been a disaster.

Let AI write code.
Let another AI review it.
You still approve the changes.

12 months ago I started using AI to build software.

Today: 45+ MVPs shipped, $200K+ generated.

This is the exact system behind it all. ↓ @ignytlabs @aimvpbuilders 🎥 Full walkthrough:

If you want your SaaS to survive launch day, read this.

Most vibe coders ship unsecure, unoptimized apps that break the moment real users show up.

Here’s the checklist I wish I had from day one. ↓ 1. Rate limit your endpoints

If you skip this, bots or bad actors can hit your backend 100s of times per second.

This can:
• Crash your database
• Drain your Supabase usage
• Spike costs or open you to attacks

Tools to use:
• Supabase Edge Functions with a rate limiter
• Vercel Middleware
• Basic IP throttling with Next.js middleware

If you can’t make good websites with AI, it’s a skill issue.

Here’s how to actually make them look good. 👇 1/ Stop saying “make this UI beautiful.”

That’s exactly why your site looks messy and inconsistent.

Here’s what I do instead:
→ Take a screenshot of any site I love
→ Drop it into ChatGPT
→ Ask it to create a design.json that captures the layout, colors, spacing, typography

Then I tell Cursor:
“Use this design.json for styling only.”

Works insanely well.

Top 5 MCP Servers for Vibe Coding

If you’re building with AI and still doing everything manually, this thread will change your workflow forever.

Bookmark this ↓ 1. What’s an MCP?

MCP = Model Context Protocol

Think of MCP like USB-C, but for AI.

It connects your AI agent to tools, databases, docs, and services in one clean setup.

Just like USB-C lets one cable do it all, MCP gives Cursor clean access to what it needs so it can actually work like a real dev.

No more dumping context manually.

This is how AI actually gets useful.

I just reverse-engineered how Lovable's top users build apps 10x faster.

Turns out, It's not about writing longer prompts.

It's about this structured prompting system nobody talks about ↓ @lovable_dev 1/ Create a Knowledge Base before you build

Include these in your project settings:

• Project Requirements Document (PRD)
• User flow explanation
• Tech stack details
• Design guidelines
• Backend structure

The clearer your context, the better your results.

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.

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 ↓

Want to turn your MVP into a mobile app without rebuilding the backend?

START HERE.

Most founders waste months rebuilding for iOS + Android.

This is the exact workflow I used to take BrainDump from web (Lovable + Supabase) → mobile (Rocket) in hours. 1/ Start with a working web app

I built BrainDump’s MVP using Lovable + Supabase.

Auth, DB, UI, RLS policies, all live and working.

Your web app is the foundation. Don’t touch the backend yet.

Want your SaaS to survive launch day?

START HERE.

The biggest problem with vibe coding is security. Too many people ship unsecure, unoptimized apps that get hacked or run painfully slow.

Here’s how to make sure your SaaS is launch-ready before you hit publish ↓ 1. Rate limit your endpoints

If you skip this, bots or bad actors can hit your backend 100s of times per second.

This can:
• Crash your database
• Drain your Supabase usage
• Spike costs or open you to attacks

Tools to use:
• Supabase Edge Functions with a rate limiter
• Vercel Middleware
• Basic IP throttling with Next.js middleware

My full vibe coding workflow to build MVPs faster

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

CodeRabbit + MCP = game-changing code reviews 🤯

They just cracked the biggest problem in AI code reviews.

Here’s how MCP integration changes everything ↓ 1/ The problem with most AI reviews

AI tools usually check code in isolation.
They can flag syntax, style, and structure, but they don’t know:

• Why the feature exists
• How it fits into your product
• What rules your team follows

It’s like having a reviewer who has never seen your app.

Lovable with MidJourney is scary good.

I can’t stop building beautiful hero sections in minutes inside @lovable_dev.

Full breakdown below 👇 Disclaimer: This is just for learning. I didn’t make extra changes on top of the original design. Always take inspiration, never copy someone’s work exactly :)

1/ Start with visual inspiration

I found this layout from Dann Petty’s portfolio and instantly knew I wanted to rebuild it.

Great structure. Clean font. Strong first impression.

x.com/DannPetty/stat…

CodeRabbit CLI is here 🤯

Paired with Claude Code, it turns AI-generated code into safe, clean, production-ready software in minutes.

Here is how it works ↓ 1/ The problem

Most people build with Claude Code, ship what looks fine, and hope it works.

→ AI writes clean-looking code
→ You deploy it
→ Users find bugs you missed
→ You spend hours debugging

Speed is useless if the code breaks.

Claude Code + Playwright MCP can now design, debug, and ship production-ready landing pages in minutes.

I’ve tested this workflow on real projects and it’s faster than any manual setup I’ve ever tried.

Here’s the full breakdown ↓ 1/ Why this matters

Most people see Claude Code as a tool for creating the backend.

With Playwright MCP, it turns into a front-end engine:
• Builds layouts from prompts
• Opens a real browser to preview results
• Tests every breakpoint automatically
• Finds bugs, fixes them, and retests

This is design, testing, and QA happening in one place.