How to Build Generative UI with Gemini 3 Pro: A Complete Guide

The way we interact with digital interfaces is undergoing a profound transformation.

Instead of navigating through pre-designed menus and static pages, imagine describing what you need and having an AI instantly create a custom interface tailored to your exact requirements.

Gemini 3 Pro can process text, images, code, and other formats simultaneously to grasp full context, while its agentic coding ability autonomously plans and executes complete coding tasks from a single prompt

It not just generates snippets, but architects entire functional applications.

Its generative UI designs and codes custom interfaces in real-time based on your specific query, rather than assembling pre-built templates. So, if you give a specific prompt asking about Van Gogh paintings, it might trigger an interactive gallery. If you provide the right prompt asking about mortgage calculations, it can generate a working calculator.

Sounds astonishing, right?

Let’s dive deeper into this new tool and understand how it works and what it can do.

The Generative UI Revolution

Generative UI represents a paradigm shift where AI models finally move past just generating and analyzing content. They can now create entire user experiences including web pages, games, tools, and applications, all dynamically generated inside AI Chat in response to user prompts.

Greg Isenberg, a prominent designer on YouTube, tested and rated Gemini 3.0 Pro in Google AI Studio across different use cases:

• Redesigning his personal website Windows XP style (9/10)
• A restaurant analytics SaaS dashboard ("Chef OS") (8.5/10)
• A workout mobile app (8.3/10)​​

He concluded that Gemini 3.0 is 'scary good' when paired with strong references and taste. He argues we’ve exited the era where no-code/vibe-coded tools produced generic, unattractive apps; now you can get to 'extremely well designed' experiences without a traditional designer.

The data speaks volumes about user preferences.

According to Google's research, users “strongly preferred” Generative UI experiences over traditional websites. In direct comparisons between expert human designers and Gemini 3 Pro's Generative UI capabilities, humans maintained a narrow lead with users preferring human-designed solutions 56% of the time versus AI-designed solutions 43% of the time. However, experts predict this gap will close rapidly as AI capabilities advance exponentially.

Understanding Gemini 3 and Its Capabilities

Gemini 3 represents Google's most intelligent model to date, combining state-of-the-art reasoning with multimodal understanding. What makes it particularly powerful for Generative UI is its breakthrough "vibe coding" capability.

Ethan Mollick, author of One Useful Thing, tried Gemini 3 Pro and had this to say:

“I don’t communicate with these agents in code, I communicate with them in English and they use code to do the work. Because Gemini 3 is good at planning, it is capable of figuring out what to do, and also when to ask my approval.”

But what makes Gemini 3 Pro so effective? Let’s have a look.

Key Features That Enable Generative UI

It is not some single feature, but a combination of multiple small abilities that make this model so special.

• The model boasts a 1-million token context window, allowing it to maintain context across complex interactions.
• Its multimodal capabilities mean it can process and generate responses incorporating text, images, video, audio, and code simultaneously. Industry leaders have taken notice of these capabilities.

Mikhail Parakhin, Chief Technology Officer at Shopify, was quoted in a Linkedin article saying:

“Gemini 3 is a major leap forward for agentic AI. It follows complex instructions with minimal prompt tuning and reliably calls tools, which are critical capabilities to build truly helpful agents.”

How Generative UI Works Under the Hood

Google's implementation relies on three key components:

• tool access (providing the model with image generation and web search capabilities)
• carefully crafted system instructions that guide the AI with goals, examples, and technical specifications
• post-processing that addresses common issues before presenting the interface to users.

The system uses intent detection and pattern matching to determine when to generate interactive surfaces. Research shows that prompts beginning with phrases like "Make an interactive..." trigger generative UI responses 94% of the time. The model can render most interfaces in just 1.2-2.8 seconds, making the experience feel instantaneous to users.

How to Get Started with Development on Gemini 3 Pro?

Flawless execution requires in depth understanding and analysis of the tool and feature. Here is something to get you started.

1. Setting Up Your Environment

Building with Gemini 3 starts with obtaining an API key through Google AI Studio. For enterprise applications, you can choose between Google AI Studio for rapid prototyping and Vertex AI for production-grade deployments with enhanced security and compliance features.

The model naming convention is straightforward:

• use gemini-3-pro-preview to access the latest capabilities.
• When configuring your API calls, pay attention to key parameters like thinking_level, which controls reasoning depth.
• Set it to "low" for speed-critical applications or "high" when tackling complex problems requiring deep reasoning.

2. Integrating with Vercel AI SDK

The Vercel AI SDK has emerged as the preferred toolkit for building Generative UI applications with Gemini 3.

From Vercel's testing, Gemini 3 Pro Preview delivers substantial improvements, showing almost a 17% increase in correctness over its predecessor on Next.js evaluations, placing it in the top 2 models on the leaderboard.

Set up your environment variables:

export GOOGLE_GENERATIVE_AI_API_KEY="your-api-key-here”

The SDK provides a unified API that works seamlessly across multiple AI providers, meaning you can switch between models without rewriting your core logic.

Aparna Sinha from Vercel emphasized:

"Our internal benchmarking of Gemini 3 Pro showed immense improvements in reasoning and code generation, with almost a 17% increase in success rate over Gemini 2.5 Pro placing it in the top 2 of the Next.js leaderboard."

3. Core Functions You'll Use

The AI SDK provides several essential functions for Generative UI:

• generateText and streamText: For generating both static and streaming text responses
• streamUI: For creating React Server Components that progressively render
• generateObject: For structured data generation using Zod schemas

The framework-agnostic hooks like useChat make it simple to build conversational interfaces that integrate Generative UI seamlessly.

What Dynamic User Interfaces Can You Build With Gemini 3 Pro?

One of the most effective use cases is financial tools.

You can prompt Gemini 3 to:

"Create an interactive compound interest calculator with sliders for principal, rate, and time period,"

It will generate a fully functional calculator with real-time updates. When asked about loans, the system generates a calculator tailored to the specific details mentioned in your prompt.

Physics teachers can request:

"Simulate projectile motion with adjustable angle, velocity, and gravity toggles,"

They will receive an interactive visualization that helps students understand complex concepts through hands-on manipulation.

For travel planning, you might ask for

"an editable kanban-style board for organizing a two-week European trip,"

This will result in a drag-and-drop interface with columns for different cities, activities, and logistics.

Prompting Strategies for Best Results

The key to triggering Generative UI lies in your prompt structure. Effective patterns include:

• "Make an interactive..." (highest success rate)
• "Simulate... with adjustable..."
• "Compare X vs Y with filters for..."

For cleaner layouts, specify 2-4 controls in your prompt. Too many options can create cluttered interfaces. Focus on goal-oriented prompts that clearly articulate what the user needs to accomplish.

Building with React and Next.js

Setting Up Next.js Integration

React Server Components (RSCs) and Server Actions provide the foundation for server-side rendering of Generative UI. Start by creating a Next.js application and setting up the necessary API routes:

// app/api/chat/route.ts
import { google } from '@ai-sdk/google';
import { streamUI } from 'ai'; import { google } from '@ai-sdk/google';
import { streamUI } from 'ai'; export async function POST(req: Request) {
const { messages } = await req.json();
const result = await streamUI({
model: google('gemini-3-pro-preview'),
messages,
text: ({ content }) => <div>{content}</div>,
});
return result.toAIStreamResponse();
}

The useChat hook in your component handles the client-side interaction:

const { messages, input, handleSubmit } = useChat();

Streaming for Better Performance

Streaming is crucial for user experience. Instead of waiting for the entire interface to generate, users see progressive rendering as components become available. This perceived speed improvement keeps users engaged and makes the application feel responsive even when generating complex interfaces.

Handle streaming errors gracefully with fallback components. If generation fails partway through, display what has been rendered successfully and provide clear error messages for the missing pieces.

Structured Outputs for UI Components

One of Gemini 3's most powerful features is its ability to generate structured outputs that conform to JSON Schema. This capability is essential for creating predictable, type-safe UI components.

Using Zod for TypeScript or Pydantic for Python, you can define schemas that describe the structure of your UI components:

import { z } from 'zod';
import { generateObject } from 'ai'; const FormSchema = z.object({
fields: z.array(z.object({
name: z.string(),
type: z.enum(['text', 'number', 'email']),
label: z.string(),
required: z.boolean(),
})),
submitButtonText: z.string(),
}); const result = await generateObject({
model: google('gemini-3-pro-preview'),
schema: FormSchema,
prompt: 'Create a user registration form',
});

The model can combine structured outputs with built-in tools like Google Search grounding to ensure your UI displays current, accurate information.

Leveraging Google AI Studio

Google AI Studio serves as an excellent prototyping environment.

You can test prompts, iterate on designs, and compare Gemini 3's output against other models before committing to production code. The playground features allow you to adjust generation parameters, test different prompt variations, and export working code directly.

Advanced features include enabling Google Search grounding for real-time information, code execution capabilities for computational tasks, and multimodal support for processing images, PDFs, and other file types alongside text.

What are Real-World Applications of Gemini 3 Pro’s Generative UI?

Generative UI is beginning to reshape how teams build, refine, and ship digital products. Its ability to instantly translate ideas into functional interfaces is unlocking new possibilities across industries.

1. Rapid Prototyping and Client Demos

Developers report testing product ideas by generating functional prototypes in minutes rather than days. Industry observers predict that generative UI will lead to applications where "common app functionality can be invoked and curated to create a specific experience as the user requires it", moving from requiring multiple app visits to having everything in one dynamically generated place.

2. Custom Dashboards and Educational Tools

Data teams are creating visualization interfaces tailored to specific metrics on demand. Instead of building generic dashboards that serve everyone moderately well, teams can generate interfaces optimized for each user's exact analytical needs.

In education, teachers are generating interactive simulations and personalized study guides that adapt to individual learning styles. The ability to create bespoke educational experiences at scale represents a significant leap forward in personalized learning.

3. Internal Business Tools

Organizations are using Generative UI to build admin panels, workflow managers, and form builders without dedicated frontend development. This democratization of interface creation allows domain experts to generate the tools they need without depending on engineering resources.

Troubleshooting and Best Practices

Using generative UI effectively requires knowing how to diagnose issues and fine-tune model behavior. A few practical checks can prevent most errors and keep your workflows running smoothly.

1. When UI Doesn't Trigger

If Gemini 3 isn't generating interactive interfaces, check your prompts for intent keywords like "interactive," "create," or "build." Be explicit about wanting a user interface rather than just information.

2. Performance Optimization

Balance quality against latency by adjusting thinking levels appropriately. For user-facing applications where speed matters, use low thinking levels. Reserve high thinking levels for complex back-office applications where accuracy trumps speed.

Manage token consumption carefully. The 1-million token context window is generous, but unnecessary context can slow responses and increase costs. Include only relevant state and history in your API calls.

3. API Limitations and Considerations

Jerry Liu from LlamaIndex noted that:

"Gemini 3 Pro outperformed previous generations in handling complex tool calls and maintaining context. It provides the high-accuracy foundation developers need to build reliable knowledge agents."

But developers should still be aware of rate limits and quota management.

The schema limitations in the API mean you can't use advanced features like unions in structured outputs. Consider this when designing your data models.

The Future of Interface Design

We've entered an era where the phrase "describe it and it's built" has become reality. Nielsen observes that:

"AI scales; humans don't. While humans still barely beat AI in the quality of design for a specific user query, it is not feasible for human designers to create individualized designs for each user".

The economic implications are profound as businesses can now provide personalized interfaces to every user at a cost that was previously impossible.

The technology is also reshaping developer roles.

Industry leaders note that Gemini 3 Pro truly stands out for its design capabilities, offering an unprecedented level of flexibility while creating apps. Like a skilled UI designer, it can range from well-organized wireframes to stunning high-fidelity prototypes.

This suggests that developers will increasingly focus on orchestrating AI capabilities rather than hand-coding every interface.

Start Building Today

The barrier to entry has never been lower. With a free API key from Google AI Studio and the Vercel AI SDK, you can start experimenting with Generative UI immediately. Begin with simple interactive elements (calculators, comparison tools, or data visualizations) and progressively build toward more complex applications.

The community is rapidly sharing templates, examples, and best practices. Vercel offers starter templates with authentication and data persistence built in. The AI SDK documentation at ai-sdk.dev provides comprehensive guides on everything from basic chat interfaces to advanced Retrieval-Augmented Generation patterns.

As you experiment, remember that we're at the beginning of this paradigm shift. The interfaces you create today are helping define what's possible tomorrow. Every successful pattern you discover, every creative prompt technique you develop, contributes to our collective understanding of how humans and AI can collaborate to build better digital experiences.