What I Learned Letting AI Vibe Code a Landing Page for Real Clients

Lessons from Letting AI Vibe Code a Landing Page

An AI-powered experiment in copywriting, audience research, and vibe coding delivered faster results, fewer revisions, and some unexpected challenges.

Copywriting and marketing strategy are familiar territory. The real bottleneck often appears when sending copy to developers without a UX designer’s input. Without a clear visual reference, back-and-forth exchanges multiply, stalling creative momentum.

For a recent project, AI was used to "vibe code"—that is, generate code from natural language—to create a sample landing page. The goal wasn’t perfection but speed: could AI handle research, writing, and layout well enough to produce a rough live draft without spending days in design tools and wrestling with decision fatigue? The answer was yes, with some caveats, late-night debugging, and a few clear limits along the way.

Using AI for Audience and Competitor Research

The starting point was Claude, prompted to develop a focused landing page around AI offerings. The input included past drafts, audience personas, and competitor positioning statements. Claude returned a positioning framework that was solid and clarified key messages previously debated for weeks.

Some misunderstandings required back-and-forth adjustments, but the end result was a clear articulation of core differentiators aligned with the target audience. This step saved time by consolidating research and messaging into a usable foundation.

Collaborating with AI on Copywriting

Next came ChatGPT for copy generation. The prompt asked for multiple headline, subhead, and CTA variations based on Claude’s positioning. The output varied: some phrases felt too formal or hype-heavy, but valuable CTAs emerged quickly.

One standout benefit was the variety in CTAs, breaking free from the usual “Learn more” default. Iterative prompting helped nudge ChatGPT towards the desired tone. For example, a generic “Accelerate your marketing with the power of AI” was refined into “Work smarter, not louder” after a few rounds.

This iterative process produced paragraphs needing minimal cleanup, speeding up copy development significantly.

The Big Pivot to Vibe Coding the Layout

Instead of wireframing in design tools, the next step was to vibe code the page layout — using AI to produce HTML based on natural language prompts. Lovable, a tool that generates HTML from text, was chosen.

To optimize cost and efficiency, all copy and design instructions were combined into one detailed prompt. ChatGPT helped craft this prompt, referencing a screenshot of a preferred design style and specifying brand colors, tone, and required page sections.

The prompt called for a clean, modern SaaS look with friendly typography, generous whitespace, and clear hierarchy. It included key elements like headlines, CTAs, self-segmentation sections, social proof, thought leadership carousels, and closing CTAs.

The AI-generated HTML wasn't production-ready but close enough to visualize a real page. This approach offered a new way to sculpt a landing page—less pixel-perfect and more about capturing the overall vibe and energy.

However, vibe coding has its limits. A layout bug caused a CTA button to disappear, and despite an hour of AI-based troubleshooting, the fix required a developer’s manual intervention. This highlighted that while AI accelerates many tasks, some problems still need human problem-solving.

Where AI Shone and Where It Fell Short

Delivering the copy and layout as a live URL impressed the client and reduced revision cycles. It was a big win to provide something tangible early on, speeding up collaboration.

AI gave strong momentum, producing about 70% of the final output. The remaining 30%—refining tone, clarifying messages, and perfecting brand fit—still depended on human judgment. Knowing when to stop tweaking and publish was key.

Next time, clearer prompts and more tone examples will help, along with recognizing AI’s boundaries sooner.

Practical Recommendations for Marketers

• Set realistic expectations: AI won’t deliver a finished product but will improve results beyond just copy.
• Lead with content, then move to layout.
• Describe the vibe you want for the page, not just the structure. Phrases like “welcoming,” “modern,” and “focused” work well.
• Upload reference pages when possible to guide AI’s output.
• Know when to stop tweaking. Endless adjustments cost time and money.
• Publish, test, learn, and iterate.

AI sped up the creative process by lifting the burden of scaffolding and letting marketers focus on strategy. It enabled a faster move from zero to a live concept that sparked richer conversations. This opens up a powerful new way to bring marketing visions to life.