Google's Material Design 3 popularised dynamic, token-based theming back in 2021, and it's still what most design-system setups get measured against. If you're building variables in Figma or tokens in Penpot, M3's structure is worth studying, not because it's new, but because it's proven.
open Material 3's token docs and compare their primitive-vs-role token split against your own Figma or Penpot library — note one gap you could fix this week.
Creative Market's 2026 trend forecast flags 'Glasscore' — blur, glow and translucent layers — as a rising visual style. For teams running token-based design systems, that means more theming flexibility, not just flat colour tokens.
Open your team's (or a starter) design system file and check whether blur/elevation tokens exist — if not, sketch one variant using Figma or Penpot's effect styles.
Some teams are wiring AI coding assistants into their design token workflow, using rules and MCP connections to keep components consistent. It's promising but still fragile in practice.
pick one component in your (or a practice) design system and check whether its tokens are named consistently enough that an AI tool could use them without guessing.
As canvas agents and coding agents start operating directly on design files, how well-structured your tokens are starts to matter for machines, not just humans. It's early signal, not proven best practice yet.
open your current Figma or Penpot file and check whether your colours and spacing are real tokens/styles or just hardcoded hex values — fix one screen's worth.
MCP servers built for design tools increasingly let coding agents pull tokens straight out of Figma/Penpot files to generate code, so loose token naming now breaks AI output too, not just human handoff. Design system teams are starting to treat token hygiene as an AI-readiness problem, not just a documentation nicety.
Audit one component in your Figma or Penpot library — rename any vague token (like "blue2") to something a machine, and a new teammate, could understand without asking you.
GitHub confirmed Copilot can pull Figma design context into code via MCP, then send rendered UI back to Figma as editable frames — a two-way bridge with real implications for spotting design system drift.
Loosely named layers and undocumented variables already confuse humans; they confuse AI agents generating or editing UI even more. Teams tidying up token naming are seeing more consistent output from any AI tool pointed at their design system.
audit one component in your Figma or Penpot library — check if its variables are named clearly enough that a stranger (human or AI) could guess what each one is for.
Designers are wiring Figma's MCP server into Cursor to auto-check tokens and components are used consistently across files, catching drift that AI-generated screens introduce. It's a working setup, not a demo reel.
Figma's new Motion tool exports through its MCP server, extending the design-token pattern (already standard for colour, spacing, type) to animation timing and easing.
Open your team's (or a personal) design system file and note whether motion/easing values are documented anywhere — if not, flag it as a gap worth raising.
As AI agents get write access to design files, teams are doubling down on strict token naming and component governance so automated edits don't quietly break consistency. It's a shift from "nice to have" documentation to enforced structure.
Pick one component in your Figma or Penpot library and check its naming and token structure against your team's docs — fix the gaps before an agent (or a teammate) trips over them.
As MCP-connected agents generate assets straight from a prompt, tools are being sold on how well they 'follow your brand kit' — meaning your tokens, components and naming now double as machine-readable rules, not just a Figma library.
pick one component in your Figma or Penpot library and check whether its naming and constraints are clear enough that an AI — or a new hire — could use it without guessing.
A designer asked an AI agent to audit a Figma button component and found 450 variants across 2,161 layers. Cutting the count to 45 wasn't actually the fix — the real problem was somewhere else entirely.
Open your most-reused component in Figma or Penpot, count the variants, and ask honestly — do you know what each one is for? If not, that's your next cleanup task.
Figma's Config 2026 session on agentic workflows showed teams connecting design tokens straight to code via MCP, using what it called 'hyper tokens' and reusable style fragments. Sloppy token naming is now a machine-readability problem, not just a designer-handoff one.
Pick one component in your design system and check whether its token names (colour, spacing, type) are clear enough that an agent — or a new teammate — could infer their purpose without asking you.
As AI agents increasingly read Figma files through MCP, messy naming and unbound tokens are becoming a real blocker. Design systems are quietly being pushed to get more legible - for agents as much as humans.
Creative Market's 2026 trend forecast argues design culture is rejecting flawless, safe defaults for bolder, more human-feeling work — a real tension for design systems built for consistency above all. Treat it as an early signal, not settled practice.
Material Design's token-based colour, type and spacing architecture lets one system scale across very different brand 'expressions' while staying structurally consistent. It's one of the clearest public examples of design-systems thinking done at scale.
Figma's Dev Mode MCP server (beta) feeds your file's components and variables straight to AI coding tools, so generated code matches your design system. It's live now on Dev/Full seats — Penpot has no equivalent yet.
open one component in Dev Mode, check whether its variables and styles are named clearly enough that a stranger (or an AI) could use them correctly — tidy up one if not.
Figma's MCP server exposes your actual components and tokens to connected AI agents, meaning generated screens and code are only as on-brand as your library is well-organised. Sloppy naming or orphaned styles now show up directly in AI output.
As AI agents start reading design systems directly through MCP-style integrations, teams are cleaning up token naming and documentation so agents (and humans) don't misread intent. It's a quieter but real shift in design-system hygiene.
IMG.LY's August roundup of AI design agents notes that Figma and Canva both now expose design generation through MCP — meaning agents can read and write into your actual design files, tokens included.
Open your most-used Figma or Penpot component and check if its name and variants would make sense to someone (or something) that's never seen your file before.
