Google's AI building stack is HERE.

I spent a week testing Stitch + AntiGravity on client projects.

The design iteration speed is CRAZY fast.

Here's my honest take on what actually works 👇 1/ What this combo actually is

Stitch = Google's AI design tool (free, powered by Gemini 3 Flash)

AntiGravity = Google's AI coding tool (builds software, automates workflows)

Together they're supposed to replace your entire design + dev stack.

I wanted to see if they actually work for client projects.

I ignored OpenClaw for weeks thinking it was another hype tool.

After 10 days of actually using it, I have 5 automations running 24/7 that save me 5-7 hours every single day.

This is the strongest AI tool I've ever used.

Here are the 5 actual use cases I built ↓ The FULL breakdown with all the prompts is now live.

Watch it here:

This might be the most INSANE OpenClaw setup I've found.

OpenClaw + Kimi K2.5 + Ollama = $0/month AI agents.

Good enough for 70% of daily tasks.

Here's the 2-minute setup ↓ 1/ What this actually is

Kimi K2.5 is an open-source model.

Runs through Ollama, which is a free local AI runner.

But the important part most people miss:
The cloud version runs on THEIR servers, not your laptop.

OpenClaw connects directly to it.

Zero API costs.

And it actually works.

I have 7 AI employees running 24/7 inside OpenClaw.

At some point I realized something:

I had ZERO visibility into what they were actually doing.

So I built my own custom dashboard using @Lovable

Here’s exactly how ↓ 1/ The problem

I first tried building the dashboard inside OpenClaw itself.

Bad idea.

It was hallucinating.
Breaking flows.
Burning tokens.

I needed something stable.

So I switched to Lovable.

You do NOT need expensive hardware or expensive models to run OpenClaw.

You need two things:
→ A VPS
→ OpenRouter

THAT'S IT.

This setup runs your agents 24/7 for $6/month without burning money.

No terminal. No coding. 15 minutes. 👇 1/ First, why a dedicated machine matters

Running OpenClaw on your laptop means:
→ Agent goes offline when you close your lid
→ No access from your phone
→ You're the bottleneck

You need something always-on.
Mac mini if you can. VPS if you're starting out.

Most people try OpenClaw and quit after seeing the bill.

I almost did too.

3 days in, I was burning $35-40/day.

Then I discovered the settings that 90% of users miss.

Here's how to run OpenClaw without going broke ↓ 1/ Why default settings destroy your wallet

OpenClaw sends EVERYTHING to your primary model by default.

Heartbeat checks? Opus.
Calendar lookups? Opus.
Sub-agents doing parallel work? All Opus.

It’s like hiring a neurosurgeon to check if you have a pulse.

It works, but it makes ZERO financial sense.

Claude Code + AntiGravity is the most slept-on AI coding setup right now.

Most people are still using basic terminals.

This combo completely changed how I build.

Here’s the full breakdown ↓ 1/ why this setup actually matters

Claude Code is powerful. But most people use it in a basic terminal.

AntiGravity makes it BETTER.

→ Built-in Claude integration
→ Skills system for smarter output
→ Full VS Code environment
→ Better context management

It’s like giving Claude Code the workspace it actually needs.

This is NOT normal.

I built the entire UI of this SaaS in 45 minutes 💀

A year ago this took days. Now I describe what I want and @Lovable builds it.

Most people still don’t realize how FAST you can move now.

Here’s the EXACT workflow ↓ 1/ Your landing page is your design system

Before touching app screens:

Build a simple landing page first.

Why?

Because it becomes your:
- Colors
- Fonts
- Spacing
- Vibe
- Layout language

Every screen after this just says:

“Match the landing page.”

That’s the cheat code.

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.

After 45+ MVPs and using Lovable almost daily, here's everything I wish I knew on day one.

These tips will save you hours of struggle.

↓ 1/ Don't skip planning.

Before you open Lovable, have these ready:
• PRD
• DB design
• UI dev plan
• Implementation plan

Generate them in ChatGPT or Gemini. Paste them as .md files into Lovable.
Now it has full context about your product from the start.

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.