A practical comparison of AI-powered design tools — Figma AI, Galileo, v0, and Framer AI — covering what they actually do, what they're good for, and how they fit into a real design-to-code workflow.
AI Design Tools in 2025: Figma AI, Galileo, and the Future of UI Prototyping
AI has entered the design tool space with varying degrees of actual usefulness. Some tools have integrated AI in ways that genuinely change the workflow; others have added AI features that look impressive in demos but don’t survive contact with real projects.
This guide takes a practical look at the tools that matter for frontend developers and designers working together in 2025 — Figma AI, Galileo, v0, and Framer AI — covering what they actually do, where they work well, and how they fit into a real design-to-development workflow.
Why This Matters for Frontend Developers
AI design tools sit at the intersection of design and development in a way that directly affects how frontend developers work. When a designer generates a UI with an AI tool, the developer inherits the output. Understanding the tools means:
- Knowing what kind of output to expect (and how to evaluate its implementability)
- Being able to participate in design conversations with more context
- Knowing which tools can accelerate the design-to-code handoff and which create more work
Figma AI
Figma integrated AI features progressively through 2024, and the toolset has matured into something genuinely useful for design and design handoff.
What Figma AI Does
Auto Layout suggestions. Figma AI can suggest Auto Layout structures for existing frames, which is useful for retrofitting responsive behaviour onto manually designed components.
Component property suggestions. When working with component variants, Figma AI can suggest additional properties and states based on patterns it identifies in the component.
Design-to-code (Dev Mode AI). The most relevant feature for frontend developers: in Dev Mode, Figma AI generates code snippets for selected elements. The output quality is variable — basic components translate reasonably well, complex nested layouts less so.
Rename layers and components. Figma AI can rename messy, auto-generated layer names into more descriptive names — small but genuinely useful for developers reading the file.
Fill with content. Auto-populate designs with realistic placeholder content (names, addresses, product descriptions) rather than lorem ipsum. This makes designs more evaluable and catches layout issues that lorem ipsum hides.
Where Figma AI Falls Short
The code generation in Dev Mode is useful as a starting point but rarely production-ready. It doesn’t know your component library, your styling system, or your project’s naming conventions. Treat it as a rough draft that tells you the structure and approximate styles, not as something to copy directly.
Figma AI is also better at tasks within existing designs than at generating designs from scratch. It’s a design assistant, not a design generator.
Practical Recommendation
For teams already using Figma, the AI features are worth enabling and exploring — they improve the design handoff workflow without requiring a change in tools. The Dev Mode AI is most useful for developers trying to understand a design’s intended CSS values.
Galileo AI
Galileo is a dedicated AI design generation tool — you describe a UI in text, and Galileo generates a Figma-compatible design.
What Galileo Does
Galileo’s core capability is generating UI screens from natural language descriptions. Describe a dashboard, a landing page, or a settings screen, and Galileo generates a design file with components, layouts, and content.
The output quality has improved significantly since Galileo’s early releases. Generated designs use recognisable UI patterns, appropriate hierarchy, and reasonable typography. The output isn’t production-ready design, but it’s a useful starting point for exploration.
Galileo exports to Figma, which means the generated designs can be refined in a familiar tool and then handed off to developers through the normal Figma workflow.
Where Galileo Works
Early exploration. When a project brief is vague and you need to show stakeholders multiple directions quickly, Galileo can generate three or four design directions in the time it would take to sketch one manually.
Screen types you haven’t designed before. If a project requires an admin dashboard and you haven’t designed one before, Galileo’s output gives you a reference point for common patterns — table layouts, filter panels, status indicators.
Bridging non-designers into design conversations. Developers and product managers can generate rough concepts in Galileo to communicate ideas to designers, without requiring design tool proficiency.
Where Galileo Falls Short
Generated designs don’t know your brand, your existing design system, or the constraints of your specific platform. Every Galileo output requires significant adaptation before it’s useful in a real project. The more specific and constrained your design requirements, the less useful Galileo’s output is.
It’s also important to note that Galileo generates designs, not code. The design-to-code step still requires a frontend developer.
v0 by Vercel
v0 generates React components from text or image descriptions — it sits on the code side of the design-to-code boundary rather than the design side. We covered it in detail in Building UI with v0 by Vercel, but the key comparison point:
v0 generates code (React + Tailwind + shadcn) directly, skipping the design tool step entirely. This makes it most useful for developers who want to go straight from idea to component, and for projects that don’t have a designer involved.
For teams with a designer, the workflow is typically Figma first, then v0 or manual implementation. For solo developers or small teams without dedicated design resources, v0 lets you iterate directly in code.
Framer AI
Framer is a visual website builder with AI generation features. It occupies a different space from Figma and Galileo — it generates both design and production-ready, hosted websites rather than design files or component code.
What Framer AI Does
Site generation from text. Describe a website in text — “a portfolio site for a Brisbane-based frontend developer with a dark theme and minimal aesthetic” — and Framer generates a complete, hosted site.
Section generation. Add AI-generated sections to an existing Framer site: “add a services section with three columns and icon-based feature cards.”
Copywriting assistance. Framer AI can generate and refine website copy within the design context.
The Trade-offs
Framer’s output is high-quality and genuinely faster to launch than a custom-built site. The trade-off is that you’re working within Framer’s constraints — the design system, the component model, and the hosting are all Framer’s. For a truly custom build with specific technical requirements, Framer AI is the wrong tool.
For a small business that needs a professional website quickly without a budget for custom development, Framer AI (with some customisation) is a legitimate option.
Relevance for Frontend Developers
Framer AI is less a tool for frontend developers than a tool that competes with lower-end frontend development projects. Understanding it helps you articulate where custom development adds value over Framer — typically: complex interactivity, specific performance requirements, custom data integration, and brand-specific design that Framer templates can’t accommodate.
How These Tools Fit Together in a Real Workflow
The most effective AI-augmented design workflow in 2025 looks something like this:
1. Brief and exploration: Use Galileo or Framer AI to quickly generate rough directions. Show stakeholders options without spending days in Figma.
2. Design refinement: Take the best direction into Figma. Refine with real brand values, actual components, and specific constraints. Figma AI assists with Auto Layout, content population, and layer organisation.
3. Handoff: Use Figma Dev Mode (with AI code suggestions as a reference point) to communicate design intent to developers.
4. Implementation: Use v0 for standard UI patterns to get a code baseline quickly. Use Cursor or Copilot for component refinement and integration work.
This workflow removes friction at each stage without removing the human judgment that keeps the output quality high.
The Honest Assessment
AI design tools in 2025 are most useful as accelerators, not replacements. None of these tools produce final, production-quality output without significant human intervention. All of them reduce the time from idea to usable starting point.
The most significant shift they represent is in who can participate in design conversations. Developers can now rough out UI concepts, product managers can communicate ideas visually, and early stakeholder alignment happens faster. This is genuinely valuable, even if the downstream design and development work remains human-led.
TL;DR
- Figma AI: best for teams already in Figma — assists existing designs, Dev Mode code suggestions useful for developers reading handoff files
- Galileo: best for early-stage exploration, generating screen concepts quickly, non-designer communication of ideas
- v0: best for going directly from idea to code — skips the design tool entirely; ideal for developers without a designer
- Framer AI: best for fast, hosted website launches within Framer’s ecosystem; competes with lower-budget custom dev
- Effective workflow: Galileo for exploration → Figma for refinement → v0 or Cursor for implementation
- All tools accelerate the starting point; human judgment on the final 40% remains essential