AI can help prepare critiques, generate focused review prompts, summarize comments and client feedback, cluster feedback themes, model stakeholder perspectives, and turn long review threads into actionable next steps inside the design workflow or directly around the design file.
Designers still provide project context, interpret stakeholder tradeoffs, judge the quality of feedback, prioritize competing input, and decide which changes should be implemented and why.
AI condenses long frame-level comment chains into a short summary of key issues, decisions, and unresolved questions for the designer.
Figma AI / ChatGPTAI converts mixed stakeholder feedback into a prioritized action list with next steps, rationale, and follow-up questions for the next iteration.
Notion AI / ChatGPTAI summarizes how product, engineering, marketing, and legal feedback differ and proposes revision paths that address the biggest conflicts.
Claude / ChatGPTI help companies navigate AI adoption -- from strategy to production. Whether you are building your first LLM-powered feature or scaling an agentic system, I can help you get it right.
Design and build LLM-powered products and agentic systems
Go from idea to production with a clear implementation roadmap
Build AI with human-in-the-loop in regulated environments
Four practical ways I use AI in my Squarespace design business: wireframing in Claude Design, prototyping in Figma Make, cleaning up client feedback, and building small apps in Base44.
https://www.figma.com/blog/the-figma-agent-is-here/
Looks pretty good, anyone use it yet?
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Claude summary:
Figma's design agent launched today — it lives directly on the canvas and in the left rail, no separate setup required.
It's design-system-aware — the agent has deep context on your components, tokens, variables, and standards, unlike third-party tools that lack that native access.
Key canvas interactions: start a prompt from any design layer, run parallel prompts to explore multiple ideas simultaneously, and make manual edits while the agent iterates alongside you.
Explore directions faster — generate multiple stylistic approaches or information architectures at once; steer outputs by `@`-mentioning specific tokens, variables, or components.
Automate bulk busywork — rename variables, swap components across screens, repeat padding changes across flows, populate frames with realistic content, convert screens to dark mode.
Design system maintenance — bulk-update descriptions, tags, naming conventions, and auto-document components with all their states and variants.
Works with feedback — summarize comments, identify themes, model stakeholder perspectives, distill long comment threads into action plans.
MCP server relationship: the agent is for canvas work; the MCP server + `use_figma` is for moving work between code and Figma.
Currently in beta rollout — no credits consumed during beta; AI credits apply at GA. Available for Full seat users on Professional, Organization, and Enterprise plans.
Starting today, work with an agent that is built for Figma—directly on the canvas.
From exploring new directions to making bulk edits and implementing feedback, here's how Figma's agent will fit into your design workflow today.