This is how I made Cursor 10x more accurate.

GitMCP turns any GitHub repo into an MCP server.

Here’s how ↓ 1/ Cursor breaks when the context is messy

When you link a GitHub repo, Cursor loads everything even the junk.

That overloads the model.

And you get:

- Confused completions
- Useless suggestions
- Wrong assumptions

I’ve vibe coded 18+ MVPs for clients using Cursor.

Security was the one lesson I learned the hard way.

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

Cursor just got 100x more powerful.

And it wasn’t because I used a bigger model.

It was because I gave it better memory.

Here’s how I fixed it with Context 7 MCP ↓ 1. The core problem: outdated context kills your agent

Every LLM has a training cutoff.

Ask it to install expo and it runs a broken command.

Not because the model is bad. It just doesn’t know recent changes.

What I learned after building 2 MVPs with Claude Code (and why I might not go back to Cursor)

Here’s what I wish someone told me earlier ↓ 1/ Claude isn’t a one-shot coder

Don’t just ask it to “add feature X.”

Start in plan mode.

Let it think first.

Then review the plan and run it.

It’s slower, but the code is way cleaner.

How I Make Cursor Write Perfect Code Every Time

This thread breaks down how I generate rules that make Cursor code cleaner, faster, and way more accurate ↓ TLDR:

• Set Global Rules for coding style
• Generate Project Rules using /generate cursor rules
• Use 5–6 custom .mdc files per MVP
• Attach rules as “Always”
• Let Cursor code with real context

The workflow I wish I had when I started building MVPs

I use this to plan, design, build, and ship full MVPs in 2-3 weeks.

After 18 builds, here’s the exact system that works.

Bookmark this ↓ 1/ Plan with ChatGPT or Gemini

Before diving into the code, fully grasp the idea.

This phase is about achieving clarity. By its end, you should understand every aspect of the idea: the tech stack, core features, target audience, EVERYTHING.

Use ChatGPT or Gemini to create these docs:
- PRD/ MVP Plan
- UI Development Plan
- Database Design
- Implementation Plan
- Launch Checklist (you can generate this later, but use the same conversation)

Spend time here; it saves you from chaos later.

This is the most efficient Cursor workflow I’ve used.

If you’re building MVPs fast, this combo is unbeatable:

TaskMaster + Cursor + CodeRabbit

Bookmark this. 1/ Why you need TaskMaster

Cursor is powerful, but as your MVP grows, you’re juggling:

• Feature backlog
• Refactors
• Bugs
• AI forgetting context

TaskMaster fixes that.

It acts like a project manager inside your terminal.

GitHub Link: github.com/eyaltoledano/c…

Want to 10x your Cursor workflow?
Stop prompting like a developer.
Start thinking like a product manager.
Here’s how ↓ 1. AI tools are developers, not product managers

Cursor, Windsurf, Lovable, they’re great at execution.

But they can’t make product decisions for you.

If your prompt lacks clarity or structure, the output will suck. Every single time.

If you’re using lovable 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.

I ditched “vibe coding.”

And suddenly, building with Cursor felt calm again.

Here’s how I ship faster without burning out ↓ 1/ The workflow (quick summary)

This is the system that works:

- Plan clearly (PRD) @ChatGPTapp
- Break it down with TaskMaster
- Execute one task at a time in @cursor_ai
- Review everything with @coderabbitai

Let’s go deeper ↓

I built 18+ MVPs, scaled my agency to $20K/month, and got acquired.

This is the exact AI dev workflow that made it happen ↓ 1/ The Problem With Traditional Agencies

Traditional dev agencies:
- Spend weeks on UI/UX before writing a single line of code
- Operate with large teams, slowing down decision-making
- Have high costs before validating an idea

The modern dev agency:
- Skips lengthy design phases and builds while iterating
- Uses small, efficient teams powered by AI
- Optimizes costs so founders can validate first
- Launches MVPs in under 4 weeks

I started @ignytlabs as a solo founder and delivered my first 6–7 MVPs alone.

Only after proving the model did I bring in other developers without bloated processes.

How I use @lovable_dev + @cursor_ai to build MVPs 10x faster

I’ve used this exact combo to ship 18+ real products. Here’s how it works ↓ 1/ Start in Lovable

Every MVP starts inside Lovable.

Why? It lets me build full apps visually with:
• Supabase auth (email, Google, magic links)
• Stripe integration (checkout, subscriptions)
• OpenAI-powered features
• Fully responsive frontend flows

This saves me days of manual coding.

I’ve vibe coded 18+ MVPs for clients using Cursor.
Security was the one lesson I learned the hard way.

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’re not using /generate cursor rules, you’re leaving 80% of Cursor’s power on the table.

Here’s how to actually make it code like a real dev: 👇 1/ Why Cursor Rules Matter

Most people think Cursor just writes code for you.

But the truth is: the AI only works well when you train it right.

Cursor Rules are how you do that.

They tell the AI how to behave, what your project is about, and how you like your code written.

Every AI Tool I Use to Build MVPs FAST for My Clients

As someone running an AI-first dev agency, speed is everything.

Here’s my go-to AI stack that has revolutionized how I build MVPs: 1/ @boltdotnew

I now start all my builds inside Bolt.

It lets me:
• Build full UIs with routing and logic
• Sync with Supabase for backend
• Integrate Stripe, FAST

It’s the fastest way to scaffold a functional MVP UI.

Example:
Built a subscription web app with auth, payments, and dashboards in under an hour. It would’ve taken days manually.

How to start vibe coding (the right way)

This is the beginner’s guide I wish I had when I started.

This guide walks you through how to build smart, fast, and clean with Cursor, Bolt, and more.

Bookmark this ↓ 1. Treat AI like a new programming language

You're not writing code. You're giving instructions.

The better your prompt, the better the result.

This is the core skill every dev needs to master now. AI is only as useful as the input you give it

Cursor just got 100x more powerful.

And it wasn’t because I used a bigger model.

It was because I gave it better memory.

Here’s how I fixed it with Context 7 MCP ↓ 1. The core problem: outdated context kills your agent

Every LLM has a training cutoff.

Ask it to install expo and it runs a broken command.

Not because the model is bad. It just doesn’t know recent changes.

If you’re new to Cursor, this will help you get started right.

Here are a few lessons I wish I knew earlier while building MVPs with Cursor, Bolt, and MCP.

Not everything I know, but enough to save you weeks of trial and error ↓ 1. The wrong stack will break your MVP

AI doesn’t code like humans. It replicates patterns it’s seen before.

So if your stack is rare or messy, it’ll hallucinate.

What works for me:
• Next/ React for frontend
• Supabase for backend
• Stripe for payments
• Vercel for deploying

AI flows clean when your stack is AI-native.

Cursor + Supabase + MCP = AI-powered MVP development at its best.

This is how I’m shipping client MVPs faster, cheaper, and smarter with AI handling the backend, database, and migrations.

Let’s break it down. 1/ The Problem with Traditional Development

Building MVPs the old way takes too much time:

- Setting up the database
- Writing boilerplate code
- Managing API integrations
- Handling migrations manually

But with Cursor + Supabase + MCP, AI automates most of this, letting you focus on shipping fast.

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.

The only UI/UX workflow you need (ChatGPT + UX Pilot)

Design your full MVP UI and design system in under 1 hour using AI.

Here’s the exact workflow ↓ 1/ My updated UI/UX workflow for client MVPs

Clients often want a “design phase” before development.

In the past, this used to take weeks. First build the design system. Then design every screen. Then send for feedback. Then iterate.

Now?

You can do all of this in under an hour using AI.

Here’s how ↓