Create websites with Figma AI Website Generator

Prompt-driven site generation

Use natural language prompts to produce complete website layouts, component hierarchies, and content placeholders that match given tone and brand guidelines. Designers can iterate rapidly by refining prompts, generating alternative variants, and applying consistent spacing and typography scales. The system preserves editable Figma layers so teams can customize outcomes without rebuilding from scratch. A feedback loop between design and generated output shortens prototyping cycles and accelerates handoff to engineers while keeping visual coherence across breakpoints and accessibility.

No-code interactive Code Layers

Code Layers let teams add interactions, animations, and dynamic behavior without writing code by translating simple instructions into reusable, editable layer props. Designers specify triggers, durations, and easing while the tool generates web-ready implementations that maintain design fidelity. Changes to motion or layout propagate through linked components, preserving consistency. This reduces iteration friction for prototypes and production builds, letting stakeholders preview realistic experiences in Figma, validate interaction flows early, and pass actionable specifications to developers with minimal manual annotation effortlessly.

Design-to-code context (MCP)

MCP integration supplies design context directly to coding tools so agents and extensions can reference components, styles, and layout constraints when generating code. Developers receive precise measurements, variable tokens, and asset references tied to frames, allowing automated code generators to produce near-final implementations. Synchronization preserves history and design intent, reducing back-and-forth between teams. By embedding Figma data into developer workflows, the bridge shortens delivery timelines, improves parity between prototype and production, and reduces translation of design decisions into implementation details.

AI image generation and editing

Generate images from text prompts, refine compositions, and edit existing assets inside the design canvas using integrated generative models. Creators can request style, aspect ratio, and focal adjustments, produce multiple variations, and swap outputs while preserving layer structure. Built-in image tools support background removal, masking, and content-aware edits so assets fit responsive layouts. Because images remain native Figma objects, designers adjust positioning, constraints, and export settings without leaving the project, simplifying asset management across breakpoints and production exports and optimization.

Smart layer organization

AI-assisted layer renaming and grouping automatically assign descriptive names based on content and hierarchy, replacing meaningless defaults and speeding navigation inside complex files. The feature analyzes component roles, text content, and visual relationships to create logical folders, consistent naming conventions, and suggested component sets. Teams gain clarity when handing off designs, searching for assets, or generating documentation. Because changes update across instances, designers maintain a tidy file structure that reduces time spent hunting elements and improves onboarding for new collaborators.

AI copywriting and translation

Integrated copy generation produces top-line headlines, descriptive body text, and CTA variations tuned to tone and length constraints, letting designers iterate on messaging without switching tools. The writing assistant can shorten passages, expand explanations, or translate content into multiple languages while preserving context and design fit. Generated text populates native text layers so typography, spacing, and truncation behavior remain testable in layouts. Teams can export content sets or cycle through alternatives during reviews, accelerating content strategy and reducing copy rewrites.

Instant background removal

Remove backgrounds from photos and illustrations with a single action that creates clean, editable masks and transparent exports. The tool detects foreground subjects, applies feathering and edge refinement, and preserves original pixels so designers can fine-tune masks or revert edits. Resulting assets integrate with constraints and responsive rules, making it simple to reuse imagery across breakpoints. Automating this repetitive step eliminates manual masking workflows, accelerates mockups, and lets teams test compositions without relying on external editors or laborious clipping paths.

One-click responsive publishing

Publish responsive websites from Figma with a single action that converts frames and components into live pages hosted by the platform or exported for custom deployment. The publishing flow maps layout constraints to responsive breakpoints, preserves interactive behaviors built with Code Layers, and bundles assets efficiently for fast load times. Editors preview pages across device sizes, update live content, and roll back revisions as needed. This capability shortens time from prototype to public site, reducing handoff friction for small teams.

Sphyngers on Reddit argues in the thread Disappointed in Figma; thoughts that the company prioritized new AI features and Slides while core editor stability suffered. They reported frequent broken components, data overrides, missing properties and severe lag that disrupted team workflows, and criticized seat-based pricing changes that squeeze small teams. The post called for attention to variables, variants and reliability instead of feature glitz. User cite:

mbatt2 on Reddit posted It’s baaaaaaack to warn others about a sharing default that grants edit rights and can auto-add paid seats. The user described being unexpectedly charged after repeatedly sharing files, calling the pattern deceptive and urging vigilance. Several commenters reported billing surprises and labeled the flow a dark pattern that created unnecessary costs for owners. The thread pushed for clearer seat controls and admin approval. User cite:

ismelllikeabaka on Reddit titled Figma full of bugs & a big disappointment described persistent bugs and regressions after recent releases. The user reported component updates not propagating, instances resetting unexpectedly, and general instability that undercut precision work. They framed the trend as rushed releases and poor quality control, arguing the tool now feels unreliable for professional projects and lamenting that priorities seemed skewed toward new offerings rather than fixing long-standing issues. User cite:

exaparsec on Reddit in How to disable AI training... warned about Figma's default opt-in to content training and urged designers to opt out. The poster criticized the opt-out default for letting the platform use team files to train models, calling it unfair to creators who pay for the service. Comments backed toggling settings off and demanded clearer consent mechanics; many users expressed anger at perceived appropriation of community work without compensation. User cite:

Blando-Cartesian on r/UXDesign posted Figma pulls it's AI tool for clearly ripping off Apple's design to call out the Make Designs issue where generated mockups echoed a well-known app. The commenter argued the incident exposed brittle QA and the risks of prebuilt design libraries feeding model outputs that mirror existing interfaces. Many replies framed the episode as evidence that current generative systems can reproduce close copies and stressed legal and ethical hazards for users. User cite:

Andy Allen (@asallen) on X posted sample outputs showing Figma's Make Designs producing a not boring weather app that closely resembled Apple’s Weather UI, sparking alarm among designers. The tweet prompted rapid discovery of the flaw, led to the feature being disabled, and ignited debate about what data and components informed the outputs. The community used the thread to warn others to heavily check any AI-generated designs for similarity risks. User cite:

A Reddit contributor posting Figma team scam (Willing_Present6641) described unexpected billing when collaborators were added and called the seat model misleading. The post recounted attempts to get refunds and widespread anecdotes of surprise charges, with responders noting that seat controls were confusing and refunds were uneven. The thread pressured Figma policy and led to community relief when admin-approval seat changes were later announced. User cite:

FactorHour2173 on Reddit titled Heads Up: Figma's Automatic Opt-In for AI Content Training posted a step-by-step alert about the August 15, 2024 opt-in policy and explained how to toggle content training for different plan types. The author warned that Starter and Professional plans were opted in by default, urged admins to check settings, and recorded frustration that sharing defaults and legal language made consent unclear for many teams. The thread became a practical guide for admins. User cite:

A redditor in Figma Ai- Just a thought in a pessimistic environment (OP on r/FigmaDesign) questioned whether generative features truly add value for professional design work, arguing that AI outputs often pick from shallow component libraries and require heavy human correction. The post noted gaps when applying company design systems and predicted inconsistency across multi-screen workflows, encouraging caution about relying on automated drafts for production-ready interfaces. User cite:

A commenter on Reddit in You are doing it wrong 😑 argued that Figma's default AI settings and rollout prioritized data capture and feature marketing over user control. The post framed the move as risky for proprietary work, urged designers to vote with their wallets, and recommended disabling content training in sensitive environments. Responses discussed practical trade-offs between getting AI features and protecting confidential designs. User cite: