Best AI Prompts for Website UI Design with Galileo AI

TL;DR

Galileo AI generates UI mockups from text descriptions, translating natural language into structured website layouts with impressive speed
The most effective Galileo prompts describe the page purpose, audience, key content elements, and visual tone — not just the visual layout
Iteration prompts refine generated mockups by providing specific feedback on what to change in subsequent generations
Galileo works best as a exploration tool — generating multiple concepts quickly, then refining the strongest one
Export prompts produce designs that translate well to Figma for further refinement and design system implementation
Prompt chaining (generating a wireframe, then refining it) produces more controlled results than trying to get a final design in one prompt

Introduction

Galileo AI positions itself as a generative UI tool that transforms text descriptions into website mockups. Unlike tools that generate individual assets, Galileo attempts to understand the full context of a website page — its purpose, its audience, and its content structure — and produce a coherent design.

The tool is particularly valuable in the early stages of a design project when you need to explore concepts quickly. Instead of spending hours building wireframes in Figma, you describe what you want and Galileo generates multiple variations in minutes. You then take the strongest direction into Figma for detailed implementation.

Getting good results from Galileo requires understanding what the tool does well and how to prompt it accordingly. This guide covers the prompt patterns that produce the best outputs.

What Galileo AI Does Well
Landing Page Generation Prompts
Dashboard and App UI Prompts
Iteration and Refinement Prompts
Prompt Chaining Workflows
Export and Handoff Prompts
Common Galileo Mistakes
FAQ

What Galileo AI Does Well {#what-galileo-ai-does-well}

Galileo AI specializes in generating complete page layouts from descriptive prompts. Its strengths are:

Speed of exploration: Galileo generates multiple design variations in seconds, making it ideal for the early brainstorming phase where you want to see many directions quickly.

Layout intelligence: Unlike a collage of random elements, Galileo understands layout principles — visual hierarchy, content grouping, responsive behavior — and applies them to generated designs.

Text-to-UI translation: You describe what a page does, and Galileo generates the UI structure. This is faster than building from scratch, particularly for standard page types that follow familiar patterns.

Style application: Galileo can apply different visual styles — minimalist, bold, modern, professional — based on descriptive input.

Its limitations are precision (the generated designs are starting points, not pixel-perfect implementations), brand consistency (you need to refine to match existing brand guidelines), and complexity (very specific or unconventional layouts can confuse the tool).

Landing Page Generation Prompts {#landing-page-generation-prompts}

Landing pages are Galileo’s strongest use case because they follow predictable structures that the tool understands well.

Prompt:

Generate a landing page for [PRODUCT/SERVICE NAME] targeting [TARGET AUDIENCE — e.g., "small business owners who need accounting software", "enterprise CTOs evaluating security tools"].

Page objective: [PRIMARY GOAL — e.g., "get users to start a free trial", "collect email signups for beta access", "schedule a demo call"]

Above the fold (hero section):
- Main headline: [MESSAGE — what problem does this solve or what outcome does it deliver?]
- Subheadline: [ELABORATION — 1-2 sentences expanding on the headline]
- Primary CTA: [WHAT THE MAIN BUTTON SAYS]
- Supporting visual: [HERO ILLUSTRATION DIRECTION — e.g., "product screenshot with gradient background", "abstract geometric representing data flow"]

Key sections to include (in order):
1. [SECTION NAME — e.g., "Social proof logos"] — [CONTENT BRIEF]
2. [SECTION NAME — e.g., "Features overview"] — [3-4 FEATURES WITH BRIEF DESCRIPTIONS]
3. [SECTION NAME — e.g., "How it works" or "Process steps"] — [3-4 STEPS]
4. [SECTION NAME — e.g., "Testimonial"] — [WHAT TYPE OF SOCIAL PROOF]
5. [SECTION NAME — e.g., "Pricing preview" or "CTA banner"] — [FINAL CONVERSION SECTION]

Visual style: [STYLE DIRECTION — e.g., "clean and minimal with generous whitespace", "bold and high-contrast with strong color blocks", "warm and approachable with rounded elements"]

Color direction: [COLOR MOOD — e.g., "trustworthy blue primary with orange accent", "earthy greens and natural tones", "dark mode with neon accents"]

Output: 3 distinct layout variations showing different approaches to organizing the content above and below the fold.

For A/B testing variations:

Generate 3 variations of the hero section for [PAGE PURPOSE] targeting [AUDIENCE].

Each variation should test a different value proposition framing:
1. Outcome-focused: [WHAT SUCCESS LOOKS LIKE — e.g., "Close 50% more deals in 30 days"]
2. Problem-focused: [WHAT PAIN THIS SOLVES — e.g., "Stop losing leads because your follow-up is too slow"]
3. Social-proof-focused: [HOW TO BORROW CREDIBILITY — e.g., "Used by teams at [COMPANY TYPE] to achieve [RESULT]"]

Keep the visual style consistent across all three. Each hero should be distinctly different in copy and layout structure while maintaining the same overall aesthetic.

Generate as a full-width hero section with mobile and desktop views.

Dashboard and App UI Prompts {#dashboard-app-ui-prompts}

Dashboard and application interfaces are more complex than landing pages because they have data structures, user interactions, and information hierarchies to communicate.

Prompt:

Generate a [DASHBOARD TYPE — analytics, project management, CRM, admin panel] dashboard for [USER TYPE — e.g., "SaaS account managers", "marketing teams tracking campaigns"].

Primary user goal: [WHAT THE USER ACCOMPLISHES WITH THIS DASHBOARD]

Key data to display:
1. [DATA TYPE 1 — e.g., "Active deals pipeline with value and stage"]
2. [DATA TYPE 2 — e.g., "Tasks due this week with assignee and priority"]
3. [DATA TYPE 3 — e.g., "Recent activity feed with timestamp and user"]
4. [DATA TYPE 4 — e.g., "Key metric cards with trend indicators"]

Layout preference:
- [SIDEBAR NAVIGATION / TOP NAVIGATION / NO NAVIGATION — dashboard only]
- [PRIMARY ACTION LOCATION — where should the main CTA or summary live?]
- [DENSITY PREFERENCE — data-dense with compact tables, or spacious with card-based layout]

Interactions to support:
- [INTERACTION 1 — e.g., "Filter by date range"]
- [INTERACTION 2 — e.g., "Sort table columns"]
- [INTERACTION 3 — e.g., "Click row to expand details"]

Visual style: [PROFESSIONAL AND DATA-FOCUSED / MODERN AND CARD-BASED / MINIMAL WITH FOCUS ON METRICS]

Color coding: [ANY COLOR-CODED STATUSES OR CATEGORIES — e.g., "green for positive, red for negative, yellow for in-progress"]

Output: 2 variations with different layout approaches. Show how primary metrics, secondary data, and navigation are organized.

For mobile-first app screens:

Generate a [SCREEN TYPE — e.g., "user profile", "settings", "content feed", "checkout flow"] mobile screen for [APP CONTEXT].

Screen purpose: [WHAT THE USER DOES ON THIS SCREEN]

Content elements:
1. [ELEMENT — e.g., "Profile photo with edit option"]
2. [ELEMENT — e.g., "Name and title"]
3. [ELEMENT — e.g., "Settings toggles for notification preferences"]

Interaction flow: [DESCRIBE THE FLOW — e.g., "user lands on screen, can scroll to see all settings, toggles persist on tap"]

Mobile-specific considerations:
- Touch targets minimum 44x44pt
- [ANY SPECIFIC MOBILE UX REQUIREMENTS]
- [GESTURES TO SUPPORT — swipe, pull-to-refresh, etc.]

Generate 2 screen variations showing different approaches to organizing the same content and functionality.

The first output from Galileo is rarely the final design. Use iteration prompts to guide refinement toward your target.

Prompt:

I have a generated design for [PAGE/SCREEN TYPE] that needs refinement.

Current design direction: [WHAT THE CURRENT GENERATION LOOKS LIKE — or attach reference]

Issues to address:
1. [ISSUE 1 — e.g., "The hero section feels too text-heavy, needs stronger visual hierarchy"]
2. [ISSUE 2 — e.g., "The CTA button does not stand out enough from surrounding elements"]
3. [ISSUE 3 — e.g., "The testimonials section looks generic, needs more specific copy direction"]

What is working well: [ASPECTS TO PRESERVE — e.g., "the feature grid layout is strong", "the color palette is right"]

Visual style to maintain: [STYLE CONSTRAINTS — e.g., "clean and minimal, same colors as current"]

Generate revised versions of sections [1, 2, 3] addressing each issue while maintaining what is working.

After revision, provide a brief explanation of what changed and why it addresses the issue.

For style pivots:

I have a generated design that is functionally correct but needs a style update.

Current style: [WHAT IT LOOKS LIKE NOW — e.g., "corporate and formal with dark blues"]
Target style: [WHAT IT SHOULD LOOK LIKE — e.g., "modern and playful with vibrant gradients and rounded corners"]

Sections to update:
[LIST SECTIONS THAT NEED STYLE CHANGES]

Preserve:
- [LAYOUT STRUCTURE — the arrangement of elements should stay similar]
- [CONTENT AND COPY — the actual text should remain]
- [FUNCTIONALITY — the interactions and CTAs should remain]

Generate the design with the new visual style applied consistently across all sections.

Iteration is where Galileo becomes genuinely useful. A first generation is exploration. Your feedback guides the second generation toward something closer to your vision. The third generation may be close enough to take into Figma for final refinement.

Prompt Chaining Workflows {#prompt-chaining-workflows}

Prompt chaining — generating a wireframe first, then using that wireframe as input for refinement — produces more controlled results than trying to generate a final design in one step.

Step 1 — Wireframe generation:

Generate a wireframe for [PAGE TYPE] on [PLATFORM — web, mobile, tablet].

Page goal: [WHAT THE PAGE ACCOMPLISHES]

Content requirements:
[LIST ALL CONTENT ELEMENTS AND THEIR PRIORITY — what must be on this page]

Layout constraints:
- [ANY SPECIFIC LAYOUT REQUIREMENTS — e.g., "sidebar must be on left", "3-column grid for features"]
- [RESPONSIVE BEHAVIOR — desktop-first, mobile-first, or responsive]
- [NAVIGATION REQUIREMENTS — what nav elements are needed]

Generate a low-fidelity wireframe showing:
1. Content hierarchy (what gets the most visual weight)
2. Layout structure (how elements are arranged)
3. Navigation and interaction points
4. Responsive breakpoints

Use simple shapes and labels. No styling — pure layout communication.

Step 2 — Style application:

Apply a visual style to this wireframe for [PAGE TYPE].

Wireframe: [ATTACH OR DESCRIBE THE WIREFRAME]

Style direction:
- Overall mood: [MOOD — e.g., "professional and trustworthy", "energetic and bold", "calm and minimal"]
- Color palette: [3-5 COLORS WITH HEX CODES — primary, secondary, accent, background, text]
- Typography direction: [TYPEFACE MOOD — e.g., "geometric sans-serif", "humanist with warmth", "modern and technical"]
- Spacing and rhythm: [DENSE AND COMPACT / GENEROUS AND AIRY / MODULAR AND GRID-BASED]

Component-level details:
- [FOR EACH MAJOR COMPONENT: button style, card style, input style, etc.]

Generate the styled design maintaining the wireframe structure.

Step 3 — Component refinement:

Refine specific sections of this design for better visual hierarchy and user experience.

Design to refine: [ATTACHED OR DESCRIBED DESIGN]

Sections to refine:
1. [SECTION — e.g., "Hero section"] — Problem: [WHAT IS NOT WORKING] — Goal: [WHAT IT SHOULD ACHIEVE]
2. [SECTION] — Problem: [WHAT IS NOT WORKING] — Goal: [WHAT IT SHOULD ACHIEVE]

Visual constraints: [ANY BRAND OR STYLE CONSTRAINTS TO MAINTAIN]

Generate improved versions of each section. After generation, explain the design decisions behind the changes.

This chaining approach gives you progressive control over the output. Wireframe establishes structure. Style application establishes look and feel. Component refinement polishes the details.

Export and Handoff Prompts {#export-handoff-prompts}

When a Galileo design is ready to move to Figma for detailed implementation, these prompts help structure the export and handoff.

Prompt:

Prepare this Galileo design for Figma handoff.

Design: [ATTACHED OR LINKED GALILEO DESIGN]

Design system context:
- Existing components to use: [LIST ANY COMPONENTS FROM YOUR DESIGN SYSTEM TO INCORPORATE]
- Tokens to apply: [COLOR TOKENS, TYPOGRAPHY TOKENS, SPACING VALUES]
- Naming convention: [HOW COMPONENTS SHOULD BE NAMED IN FIGMA]

Preparation tasks:
1. Break the design into logical Figma frame structure: [DESCRIBE FRAME ORGANIZATION]
2. Identify components that map to existing design system: [LIST MAPPINGS]
3. Identify new components that need to be built: [LIST NEW COMPONENTS]
4. Flag any elements that may be difficult to implement: [AREAS OF POTENTIAL DEVT CHALLENGE]

Generate a component inventory listing each distinct element in the design, whether it already exists in the design system, and if not, what needs to be built.

For dev handoff: note any CSS/technical considerations that designers should flag to developers (animation specs, responsive behavior, hover states not shown in static mockups).

Common Galileo Mistakes {#common-galileo-mistakes}

The most common mistake is treating Galileo output as final rather than exploratory. Generated designs are starting points — they need refinement, brand alignment, and user testing before they are production-ready. Expect to iterate multiple times.

Another common mistake is over-constraining prompts. Trying to specify every detail in one prompt produces incoherent results. It is better to generate broadly first, then refine specific sections in follow-up prompts.

A third mistake is not maintaining style consistency across iterations. Each generation prompt should reference the style decisions made in previous prompts. Keep a style brief open and paste relevant details into each new prompt.

FAQ {#faq}

How does Galileo AI compare to other AI design tools like Figma’s native AI or Uizard?

Galileo is more focused on generating complete page layouts from text descriptions than individual components or assets. Figma AI plugins excel at component-level generation and refinement. Uizard is strongest at converting hand-drawn wireframes or screenshots into digital designs. Use Galileo for page-level exploration and layout ideation, Figma AI for component refinement, and Uizard for rapid prototyping from existing sketches.

Can Galileo AI generate designs that match my existing brand guidelines?

Galileo can incorporate brand colors, typography preferences, and style descriptions, but it does not have access to your actual design system. The workflow is: generate a design that approximates your brand direction, then refine it in Figma using your actual brand components and tokens. Do not expect Galileo to produce pixel-perfect brand matches directly.

What types of pages does Galileo handle best?

Galileo handles standard page types well: landing pages, marketing pages, simple dashboards, settings pages, and profile screens. It struggles with highly complex application interfaces, unconventional layouts, and pages that require specific interaction patterns. For complex projects, generate the standard sections with Galileo and build the complex sections manually or with Figma AI.

How do I evaluate the quality of a Galileo-generated design?

Evaluate generated designs against three criteria: Does it communicate the right message? (If someone sees only this design, do they understand what the product does?) Does it guide the user toward the primary action? (Is the hierarchy clear, is the CTA prominent?) Does it fit the brand? (Would this look at home next to your existing marketing materials?) If the answer to all three is yes, the design is worth refining. If not, iterate.

Conclusion

Galileo AI accelerates the earliest phase of UI design — concept exploration — by generating multiple layout directions from text descriptions in seconds. The key is treating it as an exploration tool and using prompt chaining to progressively refine toward your vision.

Key takeaways:

Start with descriptive prompts that cover page purpose, audience, content elements, and visual tone — not just layout instructions
Use prompt chaining: wireframe first, then style, then component refinement — rather than trying to specify everything in one prompt
Generate multiple variations for exploration, then iterate on the strongest direction
Export to Figma for brand alignment and detailed implementation — Galileo designs are starting points, not final deliverables
Maintain a style brief across iterations to ensure consistency

Your next step: take a page you are planning to design and run it through the landing page or dashboard prompt. Generate the wireframe first, apply style second, and identify which sections need refinement in Galileo versus which should be handled in Figma.

Best AI Prompts for Website UI Design with Galileo AI