How to Use Galileo AI and Figma Together in a Real Design Sprint

A design sprint gives you five days. The temptation with Galileo AI is to generate everything on day three and call it prototyping. That works for about half the screens and fails badly for the rest. This is a workflow for deciding which half.

The rule I use: generate screens where layout is the open question, draw by hand where the content is the open question.

Which screens should AI generate?

Onboarding, empty states, profile pages, and marketing landing screens. These are structurally similar across products, so a generated layout is a useful starting point rather than a random guess. A prompt like “onboarding step two, email verification, code input, resend link, mobile” returns something close enough to edit in fifteen minutes.

Which screens should you never generate?

Anything with your domain logic baked into the layout. A trading screen, a permissions matrix, an editor with a custom toolbar. Galileo does not know your data model, so it invents plausible-looking rows that mean nothing. You will spend longer deleting than drawing.

• Generate: onboarding, settings, empty states, landing pages
• Draw: data tables, custom editors, permission grids, anything with real numbers
• Negotiate: dashboards, which sit in between

How do you keep generated screens consistent?

Painful truth: Galileo AI does not read your Figma library, so two generations will not share tokens. The fix is a cleanup pass, not a prompt trick. Run the Figma plugin, then apply your colour, type, and spacing styles to the imported frame before anyone sees it. Reusing the same three-sentence prompt structure across screens helps styling stay in the same family, but it is not a substitute for tokens.

What does Galileo AI cost for a sprint?

There is no permanent free plan, only a trial. Pricing is quoted per team and gated behind a sales conversation, so assume a paid tier for any real sprint. Compare that against the alternative: a designer spending day one redrawing the same onboarding flow for the fourth time. For a product with standard flows, the trade is usually worth it.

When to skip the tool entirely

If your team has a mature component library and a designer who prototypes in Figma fast, AI generation adds a cleanup step without saving the drawing step. Same story if the product is highly specialised, like CAD or developer tooling, where generic layouts actively mislead stakeholders.

Key Takeaways

• Use Galileo AI for structurally common screens; draw domain-heavy screens by hand.
• Imported frames do not inherit your Figma tokens, so budget a styling pass.
• Consistent prompt structure keeps generations in the same visual family but is not a design system.
• No permanent free tier; pricing is custom and sales-gated.
• Skip it when your team already prototypes quickly in Figma.