Best AI Prompts for Website UI Design with Galileo AI

Quick Answer

We’ve identified that mastering Galileo AI requires shifting from manual design to strategic prompt engineering. This guide provides the exact prompt structures we use to generate high-fidelity UI components and complex dashboards instantly. By following our blueprint, you will turn abstract ideas into production-ready Figma designs in seconds.

The Dawn of Text-to-UI Design

Remember the days when a brilliant design idea meant hours of meticulous pixel-pushing in Figma, wrestling with grids and alignment? That workflow is rapidly becoming a relic. In 2025, the most innovative designers aren’t just masters of Auto Layout; they’re masters of language. We’re witnessing a fundamental shift from manual creation to AI-assisted orchestration, where the most powerful design tool at your disposal is a well-crafted sentence.

At the forefront of this revolution is Galileo AI, a specialized “Text-to-UI” tool that has fundamentally changed the game. It’s not just another AI image generator; it’s a design partner that understands the nuances of user interfaces. You provide a natural language prompt, and Galileo AI transforms it into high-fidelity, editable Figma components, complete with layers, frames, and vectors. This is the new reality: turning abstract concepts into tangible, production-ready designs in seconds, not hours.

Why Your Prompt is Your New Design Blueprint

Here’s the critical insight born from countless hours of testing: the quality of your AI output is a direct reflection of the quality of your input. A vague prompt like “a login screen” will yield a generic, uninspired result. A detailed prompt—“a minimalist mobile login screen for a fintech app, featuring email/password fields, a ‘Forgot Password?’ link, and a prominent ‘Sign In’ button, using a dark theme with a primary accent color of electric blue”—will produce something you can use immediately.

This is why Prompt Engineering has become an essential, non-negotiable skill for modern UI designers. It’s the new design specification. This guide is your roadmap to mastering that skill. We will journey from the fundamental structures of a great prompt to the advanced techniques for generating complex, multi-screen dashboards and nuanced aesthetic styles. Get ready to stop pushing pixels and start architecting interfaces with the power of your words.

Understanding the Galileo AI Engine: How It “Thinks”

Ever wonder what’s actually happening when you type a sentence and Galileo AI instantly renders a stunning, high-fidelity UI? It feels like magic, but it’s a sophisticated process of pattern recognition and contextual inference. To craft prompts that consistently deliver exactly what you need, you have to think like the machine. You need to understand its training, its logic, and its limitations. This isn’t just about knowing the tool; it’s about speaking its language.

The Technology Behind the Magic: A Visual Library Billions of Designs Strong

At its core, Galileo AI is powered by Large Multimodal Models (LMMs). Think of an LMM as a visual brain that has been trained on a colossal library of user interfaces. This isn’t just a random collection of screenshots. The dataset is meticulously curated, containing millions of examples of high-quality web and mobile designs, complete UI kits, and the design systems of industry giants like Google’s Material Design and Apple’s Human Interface Guidelines (HIG).

When you provide a prompt, the AI doesn’t “draw” in the way a human does. Instead, it performs a massive-scale pattern matching exercise. It cross-references your words against its vast visual library to understand the DNA of what you’re asking for. It knows that a “dashboard” typically involves cards, charts, and data tables, and that a “mobile onboarding screen” uses progress indicators and large, clear call-to-action buttons. This deep training is why it can generate not just a static image, but a structured, layered file that respects established design principles.

Decoding the “Text-to-UI” Process: From Keywords to Components

So, how does it translate your words into a visual layout? The AI deconstructs your prompt into semantic concepts and then maps those concepts to visual components and layouts.

Let’s break it down:

• You type: “A dashboard for a SaaS product.”
• The AI’s internal logic activates concepts like: [SaaS], [Dashboard], [Data Visualization], [Navigation].
• It then assembles a layout based on common patterns for these concepts. It will likely generate a sidebar for navigation, a header with a user profile, and a main content area populated with cards containing charts or summary statistics.

This is where the magic of inference happens. The AI understands the intent behind the words. It knows the difference between a “landing page” (which should be conversion-focused, with hero text and a primary CTA) and a “settings page” (which is functional, with forms and toggle switches), even if you don’t specify every single element. It’s predicting the most probable and effective visual structure based on your keywords.

The Importance of Specificity: Resolving Ambiguity for Better Results

The single biggest factor separating a generic, unusable output from a brilliant, near-final design is specificity. The AI resolves ambiguity by falling back on the most common patterns in its training data. If your prompt is vague, you get a generic result. If your prompt is specific, you get a tailored solution.

Consider the difference in output between these two prompts:

• Vague Prompt: “Login form.”
  • Likely Output: A simple two-field design (email/password) and a “Submit” button. It’s functional but uninspired and lacks context.
• Specific Prompt: “A secure corporate login portal for a financial app, featuring SSO (Single Sign-On) buttons for Okta and Microsoft, a prominent 2FA input field, and a ‘Forgot Password?’ link. Use a professional, trustworthy blue and grey color palette.”
  • Likely Output: A sophisticated, multi-option login screen. It will include distinct sections for standard login vs. SSO, a clearly marked field for the two-factor authentication code, and a layout that communicates security and professionalism.

Insider Tip: The AI doesn’t understand “trust” or “security” as abstract concepts. It understands them as visual patterns. Words like “corporate,” “financial,” and “professional” trigger specific color schemes (blues, greys), typography (serif or clean sans-serif), and layouts (structured, spacious) that are associated with those industries in its training data.

Setting the Stage: The Figma Integration as the Starting Line

It’s crucial to remember that the goal of Galileo AI isn’t to create a finished, static image. The true power lies in its seamless Figma integration. The workflow is designed to be a starting point, not an endpoint.

The process looks like this:

1. Prompt: You craft a detailed, specific prompt within Galileo AI.
2. Generate: The AI processes your request and renders a high-fidelity visual.
3. Export to Figma: With a single click, you export the design. This isn’t a flattened PNG or JPG. It’s a fully structured Figma file.
4. Edit: You open the file in Figma and find that the design is composed of editable layers, proper auto-layout, and often semantic layer names (e.g., “Card / Primary,” “Button / CTA”).

This is the critical step that bridges AI generation and professional design workflows. You aren’t locked into the AI’s first idea. You can grab a vector icon, tweak the corner radius on a button, restructure a component with auto-layout, or swap out placeholder text with real copy. Galileo AI generates the blueprint; you, the designer, refine the architecture and bring it to life.

The Anatomy of a High-Performing UI Prompt

What separates a frustrating, generic output from a design-ready interface that feels like it came from a senior designer’s desk? It’s not luck. It’s structure. Think of yourself less as a user and more as a creative director giving a precise brief to a junior designer. The clarity of your brief dictates the quality of the work.

The most effective prompts for Galileo AI follow a predictable, repeatable formula. Master this, and you’ll gain an almost unfair advantage in generating high-quality UI on demand.

The Core Formula: [Action] + [UI Element] + [Context/Style]

At its heart, a great prompt is built on a simple foundation. This is the bedrock of your instruction set, and it’s surprisingly straightforward.

• Action: What do you want the AI to do? Start with a strong verb like Create, Design, Generate, Build.
• UI Element: What specific component are you targeting? Be precise. Instead of “a section,” ask for “a pricing table,” “a user profile header,” or “a testimonial carousel.”
• Context/Style: This is where you inject the purpose and personality. Who is this for? What should it feel like?

Let’s look at a practical example. A weak prompt is make a website section. An expert-level prompt following the formula is:

“Create a modern pricing table for a SaaS startup.”

Here, Create is the action, pricing table is the UI element, and modern... for a SaaS startup provides critical context and style. The AI immediately understands the domain, the target audience, and the expected aesthetic. This simple structure is the difference between a random assortment of boxes and a conversion-focused component.

Layering in Design Attributes

Once you have the core formula, you can begin layering in specific design attributes to refine the output. This is where you move from good results to great ones. A “golden nugget” of experience here is to think in terms of design system tokens—what a designer would specify in a style guide.

Here are the key attributes to layer into your prompts:

• Style: This defines the visual language. Don’t be afraid to use established design trends.
  • Keywords: Minimalist, Neumorphic, Glassmorphic, Corporate, Playful, Brutalist, Elegant.
  • Example: “Generate a user dashboard with a Neumorphic style.”
• Layout: This dictates the structure and information hierarchy.
  • Keywords: Grid-based, Card-based, List, Split-screen, Asymmetrical, Single-column.
  • Example: “Design a product gallery with a card-based grid layout.”
• Color Palette: While Galileo AI often makes smart color choices, guiding it prevents jarring results.
  • Keywords: Dark mode with neon accents, Warm and earthy tones, Monochromatic blue palette, High-contrast black and white.
  • Example: “Create a login form using a dark mode theme with neon green accents.”

By combining these, a prompt evolves from a simple request into a detailed creative brief. For instance: “Design a playful, card-based user testimonial section with a warm and earthy color palette.”

Defining User Flows and States

A static screen is only half the story. Modern UIs are interactive and dynamic. A key insight from working with these tools is that you can prompt for specific user states, which is invaluable for planning edge cases and user flows. This helps you visualize how an interface behaves, not just how it looks.

Instead of just asking for a form, you can guide the AI to show you the important moments in the user journey.

• Error States: “Generate a checkout form with an active error state on the email field.”
• Empty States: “Design a user profile page with an empty state for a new user.”
• Success Confirmation: “Create a success screen after a file upload is complete.”
• Loading Indicators: “Show a dashboard with a loading skeleton while data is being fetched.”

Prompting for these states forces the AI to think about the entire user experience, giving you a more complete and realistic starting point for your designs.

Common Pitfalls to Avoid

Even with the best tools, vague instructions lead to disappointing results. The most common mistake is being too abstract. A prompt like make a website is the equivalent of telling a chef make food—you’re guaranteed a generic, uninspired meal.

Here’s how to spot and fix vague prompts:

• The Problem: Create a landing page for my app.

• The Fix: Generate a **hero section** for a **productivity app** landing page. The design should be **minimalist** with a **split-screen layout** showing the UI on the right and a headline on the left. Use a **blue and white color palette**.

• The Problem: Design a user profile.

• The Fix: Create a **user profile card** for a social media platform. It should include an **avatar, username, follower count, and a 'connect' button**. The style should be **clean and corporate**.

The difference is specificity. Every word you add is a constraint that guides the AI toward your vision. Don’t just tell it what to build; tell it how it should look, who it’s for, and what it needs to contain.

Section 1: Prompts for Landing Pages & Marketing Websites

The landing page is your digital handshake. It’s the first interaction a potential customer has with your brand, and you have mere seconds to convey value, build trust, and guide them toward action. In 2025, the pressure to produce high-converting, visually stunning landing pages faster than ever is immense. This is where mastering prompt engineering for tools like Galileo AI becomes your most valuable asset. You’re not just generating a “page”; you’re architecting a user journey, and your prompts are the blueprints.

Generating High-Impact Hero Sections

The hero section is the single most critical real estate on your landing page. It must instantly answer the visitor’s core question: “What’s in it for me?” When prompting Galileo AI for hero sections, your goal is to blend a clear value proposition with visual appeal and a compelling call-to-action (CTA). Don’t just ask for a “hero section”; architect it.

Consider the difference between a vague prompt and a detailed one.

Vague Prompt:

“Hero section for a productivity app.”

High-Impact Prompt:

“Create a modern, clean hero section for a SaaS productivity app targeting freelance developers. The layout should be a split-screen. On the left, include a bold headline: ‘Stop Juggling Tabs, Start Shipping Code,’ a concise subhead that promises ‘A unified workspace for your projects, clients, and invoices,’ and two CTA buttons: ‘Start Free Trial’ (primary) and ‘Watch Demo’ (secondary). On the right, generate an abstract, isometric illustration of floating UI components and code snippets in a dark blue and electric green color palette. The overall vibe should be focused, tech-forward, and efficient.”

This level of detail gives the AI specific guardrails for layout, copy, visual style, and even the emotional tone you want to evoke. You’re guiding it to create a design that speaks directly to your target audience.

Designing “About Us” and “Team” Pages

Building trust is the primary objective of your “About Us” and “Team” pages. These aren’t just placeholders; they’re opportunities to humanize your brand and establish authority. The prompts for these sections should focus on clean layouts, professional aesthetics, and a sense of transparency. You want to generate designs that feel intentional and organized, not like an afterthought.

Here are some prompt examples that deliver professional, trust-building layouts:

• For a Company Mission Statement:

  “Design a full-width ‘About Us’ page section. At the top, feature a large, impactful quote from the CEO over a soft, out-of-focus background image of the team collaborating. Below, create a two-column text block explaining the company’s mission and vision. Use a clean, sans-serif font and generous white space to convey clarity and confidence.”

• For a Team Showcase:

  “Generate a grid-based ‘Meet the Team’ section. The layout should be a 3x3 grid of circular profile photos with names and job titles underneath each photo. When a user hovers over a photo, it should reveal a short bio and social media icons. The style should be professional yet approachable, using a warm, neutral color palette (beiges, soft grays).”

Golden Nugget: When designing team pages, always prompt for a consistent visual style for all headshots (e.g., “all team members photographed against a consistent, neutral background”). This small detail, which Galileo AI can replicate, makes a massive difference in perceived professionalism and brand cohesion.

Creating Effective Pricing and Feature Comparison Tables

Pricing pages are where decisions are made. The design of your pricing table can directly impact conversion rates. A well-designed table makes it easy for users to compare options and identify the best fit, while a poorly designed one creates confusion and friction. Your prompts should guide the AI to create clear, scannable, and persuasive pricing layouts.

The key is to use prompts that specify hierarchy and emphasis.

“Generate a three-column pricing table for a project management tool. The columns should represent ‘Basic,’ ‘Pro,’ and ‘Enterprise’ tiers. The ‘Pro’ column in the center should be visually highlighted with a subtle border or a ‘Most Popular’ badge. Each column must include the price, a bulleted list of key features (use checkmark icons), and a clear ‘Select Plan’ button. The overall design should be card-based, with high contrast between the text and background for maximum readability.”

This prompt specifies the number of tiers, the visual hierarchy (highlighting the recommended plan), the necessary components (price, features, CTA), and the overall structural style (card-based). This prevents the AI from generating a confusing or visually cluttered table.

Case Study: Building a SaaS Landing Page from Scratch

Let’s walk through a practical sequence of prompts to construct a complete, high-converting landing page for a fictional AI-powered writing assistant called “WordSmith AI.” This demonstrates how to build a page iteratively, with each prompt building on the last to create a cohesive final product.

Step 1: The Hero Section

“Create a bold, centered hero section for ‘WordSmith AI,’ an AI writing assistant for marketers. The headline should be ‘Your First Draft, Done in 60 Seconds.’ The subhead is ‘Beat writer’s block and scale your content marketing with AI that understands your brand voice.’ Include a single, prominent CTA button: ‘Try It Free for 14 Days.’ The background should be a simple, light gradient from white to a very pale blue.”

Step 2: The Features Section

“Below the hero, design a three-column features section. Each column should have a simple, bold line-art icon at the top (e.g., a lightning bolt for speed, a magic wand for creativity, a shield for plagiarism checks), followed by a short feature title and a one-sentence description. The layout should be clean, symmetrical, and use a dark grey text on a white background.”

Step 3: The Testimonials Section

“Generate a testimonials section that builds social proof. Display three customer quotes in a horizontal row. Each testimonial should have a profile picture (a generic avatar is fine), the person’s name and title (e.g., ‘Sarah K., Content Director’), and their quote. The background of this section should be a slightly off-white to visually separate it from the features section.”

Step 4: The Footer

“Create a simple, minimalist footer. It should have three columns: ‘Product’ (links for Features, Pricing, Roadmap), ‘Company’ (About, Blog, Careers), and ‘Legal’ (Privacy Policy, Terms of Service). The background should be a dark navy blue, with white text for a clean, professional finish.”

By following this sequence, you’ve guided the AI to build a complete, structured landing page with clear sections, consistent branding, and a logical flow from value proposition to social proof. You’ve moved from a blank canvas to a professional-grade design mockup in minutes, leaving you more time to refine the user experience and perfect the final details.

Section 2: Prompts for Web App & Dashboard Interfaces

Building a beautiful landing page is one thing, but designing a functional, data-dense web application is where Galileo AI truly flexes its muscles. The challenge shifts from marketing persuasion to information architecture and clarity. You need to present complex data in a way that’s instantly digestible for your users. This is where prompt specificity becomes your most powerful asset. How do you instruct an AI to understand hierarchy, utility, and user flow all at once?

Structuring Complex Data Dashboards

The main dashboard is your application’s command center. It’s the first thing users see, and it must answer their most critical questions at a glance. When prompting for dashboards, you need to think like a product manager, defining the key metrics and the relationships between them. A common mistake is asking for a “dashboard” in a single, vague prompt. Instead, architect the view piece by piece.

A highly effective prompt structure I use in my own workflow involves defining the context, the primary components, and the visual density. For instance, instead of a generic request, try this:

Prompt Example: “Generate a high-fidelity analytics dashboard for a B2B SaaS platform. The layout should be a grid system with a dark theme. The top row needs four KPI cards showing ‘Monthly Recurring Revenue’, ‘Active Users’, ‘Churn Rate’, and ‘Average Session Duration’. The main body should contain a large line chart for ‘Revenue Over Time’ on the left, and a smaller bar chart for ‘New Signups by Region’ on the right. The bottom section should be a data table for ‘Recent Customer Activity’ with columns for User, Event, and Timestamp.”

This level of detail gives Galileo AI the necessary constraints to produce a coherent and functional layout. It understands the relationship between summary cards (KPIs) and detailed visualizations (charts). A pro tip here is to always specify the data type (e.g., “line chart for time-series data,” “bar chart for categorical comparison”). This guides the AI to select the most appropriate visualization for the information, preventing it from making poor design choices that would confuse a real user.

Designing User Management & Settings Pages

User management and settings pages are often the most tedious to design from scratch, yet they are critical for administrative control. These UIs are typically dense with filters, lists, and forms. Your goal is to create a layout that feels manageable, not overwhelming. Galileo AI can handle this density, but you need to guide its organizational logic.

When creating a user list with filters, you should explicitly state the layout of the filter bar and the structure of the list itself.

Prompt Example: “Design a user management page for an admin panel. The top of the page has a filter bar with a search input, a role dropdown filter, and a status toggle. Below, present a table of users with columns for Avatar, Name, Email, Role, and a three-dot action menu. The table should have pagination controls at the bottom.”

For settings pages, which often contain multi-column forms, you must define the columns and the types of inputs.

Prompt Example: “Create a ‘Company Settings’ page with a two-column form layout. The left column should have fields for ‘Company Name’ (text input), ‘Website’ (URL input), and ‘Industry’ (dropdown). The right column should contain a ‘Bio’ (large text area) and a ‘Logo Upload’ area. Save and Cancel buttons should be fixed at the bottom right.”

Golden Nugget: For any page with a list or table, always prompt for “empty states”. A prompt like “…include an empty state for the user list that shows ‘No users found’ with a prompt to add one” demonstrates a deep understanding of user experience. This is a detail many designers forget until late in the process, but prompting for it upfront saves significant time and results in a more complete design handoff.

Generating Data Visualization Components

Sometimes you don’t need a full dashboard, but rather a specific chart component to embed within another view. Galileo AI excels at generating standalone visualization components when you describe the data and its purpose. This is incredibly useful for creating a library of chart elements or for illustrating a point in a presentation.

The key is to be descriptive about the chart’s appearance and the data it represents.

• For a Donut Chart: “Generate a donut chart component showing user segmentation. The segments are ‘Pro Plan’ (45%), ‘Free Plan’ (35%), and ‘Enterprise’ (20%). Use a color palette of blue, gray, and purple. Include a legend on the right side.”
• For a Heatmap: “Create a heatmap visualization for user engagement data. The x-axis is ‘Day of the Week’ (Mon-Sun) and the y-axis is ‘Hour of the Day’ (9 AM - 9 PM). Use a color scale from light green to dark red to indicate engagement density.”
• For a Gauge Chart: “Design a gauge chart showing a progress score of 78 out of 100. The gauge should be semi-circular with a needle indicator. The color should transition from yellow to green as the value increases.”

By providing the specific data points and visual requirements, you force the AI to generate a component that is not just a generic placeholder but a realistic representation of the final product. This allows you to test the visual hierarchy and data legibility much earlier in the design phase.

Workflow Example: From a Simple CRM to a Full Admin Panel

Let’s put this into practice with a real-world scenario. Imagine you’re tasked with designing a simple CRM. Instead of trying to generate the entire system at once, you’ll use a progressive prompting strategy to build out the interface screen by screen. This iterative approach mimics a real design sprint and yields far better results.

Step 1: The Main Contact List. First, you need the core view. Your prompt should focus on the list and its primary actions.

Prompt: “Design a CRM contact list view. The page has a header with a ‘Add Contact’ button and a search bar. The main area is a list of contacts, each showing a profile avatar, name, email, and a ‘View Details’ button.”

Step 2: The Detail View. Once you have the list, you need a screen to view a single contact’s information. This is where you add more detail.

Prompt: “Generate a contact detail page for the CRM. The top section shows the contact’s name, title, and company, with ‘Edit’ and ‘Delete’ action buttons. Below, create three sections: ‘Contact Info’ (phone, email, LinkedIn), ‘Notes’ (a text block), and ‘Interaction History’ (a timeline of recent emails and calls).”

Step 3: The Edit Modal. Instead of a full new page for editing, a modal is more efficient. You can prompt for this specifically.

Prompt: “Create a modal window for editing a contact. The modal has a two-column form with fields for First Name, Last Name, Email, and Phone Number. It has ‘Save Changes’ and ‘Cancel’ buttons at the bottom.”

By following this sequence, you’ve guided the AI to build a complete, functional workflow within your CRM. Each prompt builds upon the context of the last, creating a cohesive set of screens that feel like part of the same application. This method transforms Galileo AI from a simple image generator into a true partner for building complex, multi-screen user interfaces.

Section 3: Prompts for Mobile App UI & E-commerce

Is your prompt guiding the AI to build a user journey, or just a static screen? This is the critical question when designing for mobile and e-commerce, where every pixel must contribute to a seamless flow. Generic prompts yield generic layouts, but a well-crafted prompt acts as a blueprint, instructing Galileo AI on the hierarchy, function, and feel of the interface. Here, we’ll dissect the exact prompt structures needed to generate high-fidelity mobile UIs for onboarding, shopping, and social interaction.

Crafting Intuitive Onboarding Flows

The first three screens a user sees can make or break your app’s retention rate. A common mistake is prompting for a single “onboarding screen.” Instead, you need to think in terms of a sequence. Galileo AI excels when you provide a narrative context. For a 3-step onboarding flow, your prompt should describe the progression of information and the user’s emotional state.

Prompt Example: “Generate a 3-screen mobile onboarding flow for a meditation app. Screen 1: A welcome screen with a calming, abstract hero illustration (soft pastel colors), a headline ‘Find Your Inner Peace,’ and a primary ‘Get Started’ button. Screen 2: A preference selection screen asking ‘What brings you here?’ with selectable, pill-shaped buttons for ‘Sleep,’ ‘Focus,’ and ‘Anxiety.’ Screen 3: A permissions screen with a large, friendly notification icon and a clear ‘Enable Notifications’ CTA, plus a ‘Maybe Later’ text link.”

This level of detail forces the AI to consider consistency across screens—the same button style, complementary color palette, and logical information flow. A key insight from my own workflow is to always specify progress indicators. Adding a phrase like “include a subtle progress bar at the top of each screen” ensures the user never feels lost. This is a small detail that dramatically improves the perceived quality of the generated UI.

Designing High-Conversion E-commerce Pages

Product discovery is the heart of any e-commerce experience. Your prompts for these pages must balance visual appeal with scannable information. A prompt like “mobile product listing page” is a start, but it won’t win you any design awards. To generate a high-conversion UI, you need to define the layout, the card components, and the discovery tools.

Consider this prompt structure for a fashion store:

• Context: “Mobile UI for a minimalist fashion e-commerce app.”
• Layout: “Grid layout with two columns.”
• Component Detail: “Each product card should feature a square product image, a product name in a clean sans-serif font, the price, and a subtle heart icon for wishlisting.”
• Discovery Tools: “At the top, include a prominent search bar with a magnifying glass icon and a horizontal scrollable filter bar with options like ‘New In,’ ‘Dresses,’ ‘Tops,’ and ‘Sale’.”

By breaking it down, you’re giving the AI specific building blocks. You’re not just asking for a list; you’re asking for a system of discovery and evaluation. This is where understanding UI patterns pays off. The AI knows what a “filter bar” is, but you have to tell it to include one. A pro tip: if the generated images are too uniform, add “show products on a variety of model types” to your prompt. This small addition pushes the AI toward more inclusive and realistic e-commerce mockups.

Generating Secure & User-Friendly Checkout Flows

Checkout is a high-stakes environment. Trust and clarity are paramount. Your prompts must eliminate ambiguity and guide the user toward completion. When prompting for a checkout flow, focus on reducing cognitive load. This means asking for clear field labels, logical grouping, and a single, unmissable primary action.

Prompt Example: “Design a single-page checkout screen for an e-commerce mobile app. Create distinct sections with clear headings: Shipping Address (Full Name, Street Address, City, Zip Code fields), Payment Method (a visual card selector with ‘Visa,’ ‘Mastercard’ icons, and fields for Card Number, Expiry, CVV), and Order Summary (item thumbnail, name, price). The ‘Pay Now’ button should be a large, high-contrast, fixed-position button at the bottom of the screen.”

Notice the emphasis on structure. By using headings like “Shipping Address” in the prompt, you guide the AI to visually group related fields. This is a fundamental principle of good form design. A common pitfall is cluttered input fields. To counter this, specify “spacious input fields with clear placeholder text.” This ensures the final design feels clean and is easy to tap, reducing user frustration and cart abandonment.

Designing Profile & Social Feeds

Social interfaces thrive on engagement and personalization. When prompting for these UIs, you need to describe the components that foster interaction: user profiles, activity feeds, and comment threads. The goal is to create a design that feels dynamic and alive.

For a user profile, a strong prompt would be: “Create a user profile screen for a community app. The top section should have a circular profile picture, username, and a bio. Below, use a tabbed layout to switch between ‘Posts’ (a grid of image thumbnails) and ‘About’ (user statistics). Include a prominent ‘Follow’ button next to the username.”

For an activity feed, you want to prompt for variety: “Generate a social media activity feed. Each item in the list should show a user avatar, a text update, and an engagement bar with ‘Like,’ ‘Comment,’ and ‘Share’ icons. Vary the content types—some posts with text only, others with images.” This instruction to “vary the content” is a powerful trick. It prevents the AI from producing a monotonous, robotic layout and results in a more authentic and visually interesting feed that mimics real-world user behavior.

Section 4: Advanced Prompting Techniques for Customization

You’ve mastered the basics of generating a UI, but what happens when your brand has a strict design system or you need to iterate on a complex component? This is where most users hit a wall, treating AI as a one-shot magic wand. The real power of Galileo AI for professional designers isn’t just in the first output; it’s in the ability to guide, refine, and constrain the AI to serve your specific vision. This section moves beyond simple commands into a systematic approach for customization, ensuring every generated design feels like it belongs to your ecosystem from the very first prompt.

Integrating Brand Identity and Design Systems

One of the biggest challenges with generative UI is maintaining brand consistency. An AI left to its own devices will often choose generic colors and fonts. The solution is to treat your prompt as a creative brief, explicitly defining the design system parameters before asking for the UI. Instead of a vague request, you provide a foundational set of rules.

Consider this prompt structure for a new settings page:

Prompt Example: “Generate a user profile settings page for a B2B SaaS application. The design must adhere to the following brand guidelines: Primary color is deep blue #2C3E50, accent color is electric blue #3498DB. Use the Inter font family. All buttons and input fields should have a border-radius of 8px. The overall layout should be clean, corporate, and follow a card-based structure.”

By front-loading the constraints—color hex codes, specific font families, and border-radius values—you give the AI a rigid framework. This prevents it from making aesthetic decisions that clash with your brand and dramatically reduces the time you’ll spend in Figma manually correcting styles. Golden Nugget: For ultimate control, create a “brand style” prompt snippet that you can paste at the beginning of every new request. This snippet, containing your color palette, typography, and component styles, acts as a persistent style guide for the AI, ensuring consistency across all generated screens.

Iterative Prompting and Prompt Chaining

No designer expects a perfect draft on the first try, and the same applies to generative UI. The most effective workflow involves treating the initial output as a starting point for refinement. This process, known as prompt chaining, uses the AI’s own creation as context for subsequent, more focused prompts.

Let’s say you generate a dashboard with the prompt: “Create a project management dashboard with a sidebar, a main content area showing a task list, and a header.” The AI delivers a solid foundation, but the task list looks too simple.

Your next prompt isn’t a new request; it’s a refinement of the old one. You can either describe the changes directly or use Galileo AI’s image-to-image capabilities if available:

Refinement Prompt: “Now, take the main content area of that dashboard and redesign the task list. Add columns for ‘Assignee’ (with user avatars), ‘Due Date’, and ‘Status’ (with colored tags like ‘In Progress’, ‘Completed’). Change the header to include a search bar and a ‘New Task’ button.”

This iterative approach allows you to deconstruct a complex interface into manageable pieces. You build the skeleton first, then add muscle and detail in subsequent steps. This method mirrors a real-world design process—wireframing, then adding visual design—and leverages the AI for rapid iteration without losing control of the overall structure.

Using Negative Prompts (What to Avoid)

Sometimes, the most direct way to get what you want is to tell the AI what you don’t want. While not always a formal feature in every AI model, the strategy of specifying exclusions is a powerful prompting technique. It helps eliminate common AI mistakes or unwanted elements that tend to appear by default.

For example, if you’re designing a minimalist landing page, you might be tired of seeing decorative, irrelevant stock photos.

Prompt with Exclusions: “Design a landing page for a fintech startup, focusing on trust and security. The layout should feature a headline, a sub-headline, and two call-to-action buttons. Do not include any images, stock photos, or complex background patterns. Focus purely on typography and button styling.”

By explicitly forbidding images, you force the AI to explore more creative typographic and layout solutions, keeping the design clean and focused. Similarly, if you’re designing a mobile app screen and want to avoid a common navigation pattern, you could add: “…a screen for user profile settings. Avoid using a bottom tab bar navigation.” This is a form of “negative conditioning” that steers the AI away from predictable, and often clunky, design choices.

Prompting for Specific Accessibility Considerations

Building accessible interfaces isn’t just a best practice; it’s a necessity. You can guide Galileo AI to generate more accessible components by embedding accessibility requirements directly into your prompt. This is especially effective for elements where contrast, clarity, and feedback are critical.

When designing a form, for instance, you can ask the AI to prioritize accessibility features:

Accessibility-Focused Prompt: “Generate a login form with email and password fields. Ensure high-contrast labels that are permanently visible above the input fields. Include a ‘Forgot Password?’ link below the password field. Design a prominent, clear error message state that appears if the user enters an incorrect password. Use a distinct red color for the error text and a bold border on the input field.”

By specifying “high-contrast labels” and “permanently visible,” you prevent the AI from using placeholder text that disappears upon typing—a common accessibility failure. Asking for a “distinct red color” and “bold border” for error states guides the AI to create a clear, perceivable feedback mechanism for users. This proactive approach helps you generate UI patterns that are more likely to meet WCAG guidelines from the outset, saving significant remediation time later.

Conclusion: Augmenting Your Design Workflow with AI

So, where does this leave you, the designer, in 2025? The core principles we’ve explored—specificity, structure, and iteration—aren’t just tips for better prompts; they are the foundational skills for collaborating with AI. You’ve seen how a vague request yields generic results, while a detailed prompt, layered with context and constraints, produces a design that’s not just visually coherent but functionally sound. This is the new literacy: translating your design intent into a language the AI understands.

The most important “golden nugget” from my experience is this: AI doesn’t replace the designer; it replaces the blank page. Tools like Galileo AI are phenomenal at handling the “first 80%” of a design. They rapidly generate the layouts, component structures, and visual starting points that used to consume hours of tedious work. This shift doesn’t devalue your skills; it elevates them. Your focus can now move from pixel-pushing to the high-impact work that truly matters:

• Strategic Problem-Solving: Interpreting user needs and business goals.
• Complex User Flows: Architecting intuitive journeys, not just single screens.
• Refinement & Polish: Applying the nuanced brand voice, accessibility standards, and micro-interactions that AI can’t yet grasp.

Think of Galileo AI as your tireless junior designer, ready to generate endless concepts on demand. Your role is to be the art director, the strategist, and the final arbiter of quality.

The theory is one thing, but the real magic happens when you start building. Don’t just read the examples—take them. Paste them into Galileo AI, see what they produce, and then tweak them. Change the industry, the layout, the component details. Start building your own personal library of high-performing prompts. This practice is what will separate you from other designers. Your competitive edge in 2025 won’t be who can design the fastest; it will be who can guide the AI to produce the most exceptional results, the fastest. Start experimenting today.

Performance Data

Frequently Asked Questions

Q: Does Galileo AI replace the need for Figma skills

No, it accelerates the ideation and layout phase, but you still need Figma skills to refine, edit, and prepare files for development

Q: How specific should my prompts be

The more specific, the better. Include the app category, specific UI elements (e.g., ‘email input’), and visual style (e.g., ‘minimalist dark mode’)

Q: Can Galileo AI generate entire design systems

Yes, by prompting for consistency, you can generate a suite of screens (Login, Dashboard, Settings) that share the same visual DNA, which serves as a strong foundation for a design system