Create a React landing page with AI (2/3): from prompt to components

In part one of this series you picked an archetype, a tier and wrote your first prompt. Now comes the key question: what happens between that prompt and the code you see on screen?

In KitekAI, the prompt does not produce a screenshot or an opaque block. It produces real, modular, readable React + Tailwind components that you can preview, edit and take with you. This part explains how a brief becomes components and which conventions keep the code clean.

What happens when you submit the prompt

The wizard sends your description to the Master Prompts, which inject context and architecture before the model generates. This step is what prevents visual hallucination: instead of improvising, the model receives a structural contract and honors it.

The result is 100% structured precision: the model returns exactly the component type requested, with the expected hierarchy. The same approach cuts latency by 40% compared with a raw prompt, and the environment keeps an average below 180 ms.

Under the hood the platform is 100% native multi-model: it can rely on Anthropic Claude, DeepSeek, Cerebras, Google Gemini, Groq, Mistral or OpenAI, and the model is selected per tier. You never have to manage API keys or pick a provider.

The component as a building block

The unit of work is the modular component. Each archetype defines its own set, and generation returns pieces with recognizable names such as Features, Services, PricingPackages, Testimonial, ProductGrid or SubscriptionPlans.

This has three practical consequences:

• Composition: a landing page is an ordered sum of independent components, not one giant file.
• Reuse: a pricing component works across two different landing pages without a rewrite.
• Maintenance: you can replace one section without touching the rest of the page.

With more than 20 modular, high-conversion components, the catalog covers what a landing page needs: value proposition, services, stats, team, testimonials, pricing and calls to action. A complete landing page comes together in under 10 minutes.

Because the archetype defines the component set, the assembly is predictable: a corporate site starts from services, team and stats; a store from product grids and promotions; a SaaS from modules, integrations and subscription plans. That matrix is reusable, so the same block keeps the same contract from one landing page to the next.

From prompt to component: an example

Returning to the dental clinic brief from part 1, the prompt describes the business and the outcome. Internally, the platform breaks it into concrete components: a ValueProposition summarizing the offer, a Services section for treatments, a Team block for the medical staff, a Testimonial for social proof, and a contact form.

You do not write the JSX. You describe the intent and review the assembly. If something does not fit, you adjust the prompt or reorder the components and generate again.

Conventions that keep the code readable

Clean code is not a slogan; it is a set of consistent decisions. These are the ones you notice first when you open the project.

Naming

Components use PascalCase and descriptive names (ImageSlider, LogoCloud, Stats). Files and sections map clearly to the component name, so searching in the editor does not turn into a hunt.

Semantic Tailwind tokens

Instead of repeating loose values across the markup, the visual layer uses semantic tokens: names that express intent (surface, primary text, accent, border) mapped to Tailwind utilities. The benefit is direct: changing the palette or spacing means touching a few places, not tracing hundreds of classes by hand.

That indirection also keeps components consistent with each other: two sections built weeks apart still share the same surface, accent and border decisions. When the brand shifts, the token changes once and every component follows, which is exactly the leverage that makes a generated project maintainable rather than disposable.

Icons with lucide-react

Iconography is handled with lucide-react, one of the allowed libraries. Icons stay consistent components instead of loose images that break the layout or the page weight.

Because they are vector components, they scale without blurring and are imported only when used, so the page does not carry a folder of unused image files. A single icon family also keeps stroke weight and sizing uniform across every section.

Allowed libraries in the generated code

Part of KitekAI's control is not letting the code fill up with arbitrary dependencies. The allowed set is small and known:

Library	What it is for
react	Base for the component and the UI tree
lucide-react	Iconography
gsap	Premium animation and interaction (ScrollTrigger)
framer-motion	Declarative component animation
axios	HTTP requests when a component needs them
clsx	Conditional class composition
tailwind-merge	Resolving conflicts between Tailwind classes

That boundary is what keeps the output portable: fewer dependencies means a project that is easier to read, audit and deploy wherever you want.

A fixed set also makes the project easier to audit: there are no surprise packages pulled in at generation time, and the dependency list you review is the dependency list you ship. If a component needs nothing from a library, it does not import it.

Structured precision and clean code

Two metrics sum up the result of this stage of the flow:

• 100% clean code — no inherited blocks or filler; components with a clear responsibility and classes with intent.
• 100% structured precision — the returned component matches the requested architecture, with no invented sections.

Together with 0% visual hallucinations, this is what separates controlled generation from an experiment: the model works inside a contract, not on an infinite canvas.

Frequently asked questions

Can I use the components outside KitekAI?

Yes. The generated code is yours: you can download the zip and move it into your own repository. It runs as a standard React + Tailwind app, using the allowed library set.

What if I need a library that is not on the list?

The allowed set is designed to cover the vast majority of a marketing landing page. If your project needs something more, you can add it after exporting the code, inside your own repository.

Are the components reusable across landing pages?

Yes. Because they are independent pieces with clear names, a component such as PricingPackages or Testimonial can be reused in another project without dragging in odd dependencies.

How do I keep the code tidy while iterating?

Work component by component, not in giant files. Change one component, regenerate if needed, and treat the semantic tokens as the single source for color and spacing.

Next step: preview and deploy

You now know how a prompt becomes React + Tailwind components. In part 3 of this series we cover preview, staging and deploy to any hosting.

Generate your components in KitekAI and review the allowed libraries in your own project. If you have questions, email [email protected].