AI can build landing pages, but most look generic.
Here’s my structured approach using @lovable_dev + 21stdev to create high-converting, polished designs, FAST.
A complete breakdown:
1. Start with Design Inspiration & Structure
Before touching Lovable, I gather design references from Dribbble, Behance, and top SaaS landing pages.
I focus on:
- Clean typography and spacing
- High-converting CTAs
- Smooth animations and interactions
Good design starts with understanding what works.
2. Convert Ideas into a Structured Layout
Instead of randomly prompting Lovable, I generate a detailed landing page structure using a custom GPT prompt generator (will share the prompt tomorrow along with the video based on this topic)
This includes:
- Page sections (hero, features, CTA, FAQ, footer)
- UI elements, colors, and typography
- Hover states, animations, and micro-interactions
This ensures AI creates something well-planned, not random.
3. Generate the First Draft in @lovable_dev
I feed Lovable two things:
- A detailed textual description of the page
- A design reference screenshot
This leads to a much more accurate output compared to vague prompts.
4. Refine with 21stdev for High-Quality UI
Lovable speeds up the base design, but I fine-tune it using 21stdev’s UI components to polish the final look.
AI-generated layouts always need refinement. I fix:
- Branding & colors (Lovable defaults to blue, I align it to the brand)
- Spacing & layout (proper padding and margins)
- Typography (ensuring readability and consistency)
- Backgrounds & depth (subtle gradients > flat colors)
This step makes the design feel intentional, not AI-generated.
6. Mobile Optimization is Non-Negotiable
Most users browse on mobile, so I make sure:
- Input fields go full-width for better usability
- Font sizes adjust for readability
- Buttons are tap-friendly
- Sections stack smoothly
Skipping this step kills conversions.
7. Add Subtle Animations for a Modern Feel
A static page feels outdated. I add:
- Smooth fade-ins for hero sections
- Button hover effects
- Feature sections that slide in on scroll
- Background animations for depth
This makes the page feel polished without being overwhelming.
8. Deploy with a single click
Lovable lets you launch your web app instantly. Once tested, connect a custom domain via Netlify, and your site is live, no extra setup needed.
Why This Works Better Than Relying Purely on AI
Most people expect AI to generate a perfect design on its own. It doesn’t work like that.
With a structured approach:
- The AI output is much closer to the final version from the start
- I spend less time fixing errors
- The page has a clear layout instead of random sections thrown together
Lovable + 21stdev lets me build fast without sacrificing quality.
Key Takeaways
- AI-generated designs need structure before prompting
- Lovable + 21stdev is a game-changer for AI-powered landing pages
- AI speeds up development, but manual refinements are still necessary
- Animations & interactions elevate the user experience
This is the fastest and most effective way I’ve found to build landing pages that look great and convert well.
A detailed video on this is coming tomorrow. Stay tuned!
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Over the last six months, I’ve built 16+ SaaS products using Cursor.
If you’re a beginner, this thread has everything you need to get started and make the most of Cursor
1/ Plan Before Coding
Always start with a solid plan. Use ChatGPT to create your PRD, database design, color palette, and structure. Save these as .md files in Cursor to keep everything consistent. A clear roadmap saves time.
2/ Start with a Strong Foundation
Cursor shines when it’s building on something. Use tools like V0/Lovable to generate the initial UI code, then refine in Cursor. This approach improves accuracy and reduces rework.
MCP + Cursor: AI That Codes, Debugs, and Automates
Here’s how it changes the game.
1/ What is MCP
AI coding assistants have come a long way. But most are still just autocomplete on steroids.
They suggest code, but when something breaks, you’re left troubleshooting manually.
What if AI could connect to databases, debug web apps, and manage GitHub repos, all by itself?
That’s exactly what MCP (Model Context Protocol) enables inside Cursor
2/ What Makes MCP Different?
Traditional APIs are like an old-school assembly line, efficient, but rigid.
They expect specific inputs and outputs, and if something changes unexpectedly, the whole process grinds to a halt.
MCP, on the other hand, is like a seasoned engineer. It doesn’t just follow instructions, it assesses the situation, adapts, and finds alternative solutions.