The Figma AI Debate: Are Product Designers Really ‘First to Go’?
When Figma investor Gokul Rajaram argued that AI would make product design the first function eliminated, designers pushed back hard. In a widely shared post, he predicted that companies would stop hiring full-time designers, instead paying consultants to build a design system once, then letting product managers and engineers use AI design tools to generate prototypes. He suggested this shift could mark the end of product design as a standalone role, especially in lean startups that refresh design systems only occasionally. The backlash from the design community and wider tech industry was immediate. Critics argued that equating design with plugging a system into AI ignores research, strategy, and human insight. For Malaysian designers watching this debate, the key takeaway is not that design is doomed, but that the definition of a “designer” is being contested by investors who see workflows primarily through an efficiency lens.
Claude Code, Figma MCP and the New Human–AI Design Pairing
Real-world experiments with AI design tools tell a more nuanced story than the hype. A Creative Bloq reviewer tested Claude Code connected to Figma MCP to turn Figma modules into React components. The tool proved powerful, but only after a full day of feeding it detailed project, design and build context—similar to onboarding a junior developer. Designs in Figma had to be carefully built and annotated so the AI could interpret and implement them accurately. The results were strong: clean file structures, accurate visual builds and generally good code, though still requiring iterations and senior developer oversight for complex integrations. This shows that AI for designers currently behaves like a capable assistant, not an autonomous creative director. It amplifies the skills of people who already understand design systems and front-end development, rather than letting generalists bypass designers entirely.
The Canva AI Problem: When Tools Change Your Words
If AI can assist, it can also misfire—sometimes in politically sensitive ways. Canva recently had to fix an issue in its Magic Layers feature after users reported that the tool changed the phrase “Cats for Palestine” to “Cats for Ukraine” inside a design without being asked. Reports noted that the problem appeared specific to the word “Palestine”, while terms like “Gaza” and “Israel” were not affected. Canva apologised, launched an internal audit and stressed that the issue was isolated rather than affecting all designs. The incident is particularly striking because Magic Layers is marketed as a way to convert flat designs into editable layers, with users retaining control. When AI silently alters text, it raises questions about bias, moderation logic and reliability. For designers, especially those working on social or political content, this highlights a new responsibility: auditing AI outputs as carefully as you proofread copy or check colours.
What AI Will Automate in Design—and What It Can’t Replace
Across tools like Figma-integrated AI, Claude Code and Canva’s Magic Layers, a pattern is clear: repetitive execution is easiest to automate. Layout exploration, resizing assets for different screens, generating component variants or exporting front-end boilerplate are all increasingly handled by AI design tools. They save time in production-heavy phases and reduce the need for purely mechanical tasks. But the work that anchors the future of design jobs remains stubbornly human. Understanding a Malaysian brand’s cultural context, translating client objectives into stories, and balancing business constraints with user empathy are not just prompts—they require judgment and negotiation. AI struggles with ambiguous briefs, stakeholder politics and the subtle cues of local audiences. For many teams, this means fewer roles focused solely on pixel pushing, and more roles where designers orchestrate systems, test assumptions and guide AI to produce work that actually fits real users and markets.
How Malaysian Designers Can Adapt: From AI Users to Creative Directors
Instead of treating AI as a threat, Malaysian designers can treat it as a new design medium. Becoming fluent in AI-literate workflows—prompting image generators for moodboards, using Figma plugins to generate variant layouts, or pairing Claude Code with Figma MCP for component builds—can free time for higher-level thinking. Use AI as a brainstorming partner for visual directions, but always refine outputs to reflect local culture, language and brand nuance. When building portfolios, shift emphasis from polished screens to case studies that show how you framed problems, tested ideas and measured impact. Document how you directed AI tools rather than simply what they produced. This positions you closer to a creative director role, even if your title remains “designer”. In an AI-augmented ecosystem, the most resilient careers will belong to people who can combine taste, strategy and technical literacy into a single, adaptable practice.