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Bringing AI in at Figma

Cluster Make feedback without losing the evidence behind it

You’re the product manager. Your team is in the room. Printed Oct 15, 2026.

Feedback about design-to-code quality is arriving faster than PMs can turn it into a shared problem statement.

Fast synthesis protects discovery time, while traceable evidence protects the judgment behind a spec draft.

Who you’d be doing this for

“I tagged three examples of the same drift, and I’m still being asked which one matters most.”

Almaz Eshetu · UI/UX Designer

Uses Figma Make to turn approved Figma designs into interactive prototypes for a digital product team.

What is at stake

PMs are reading similar design-to-code complaints as different problems, slowing the path to a usable spec. You have to weigh faster synthesis against the evidence PMs need to trust a theme.

Why it isn’t already fixed

Every obvious fix costs something else. That’s the part you’d have to decide.

  • faster synthesis vs traceable evidence
  • recurring feedback vs distinct user needs
  • AI grouping vs PM problem framing
  • pilot speed vs durable handover

Why Figma

Figma Make sits at the handoff between Figma designs and production codebases, where an unclear feedback signal obscures what must improve.

Written with these in mind

evidence-minded forward deployed engineerAI workflow designertechnical product discovery partner

Not your kind of problem? 45 more at Figma, or browse every organization.

This is the setup. The work is inside.

Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.