My IxDF certificate: “AI for Designers”

Experience counts — and that is no different when AI becomes a design tool

I have been working with AI for a while and mainly use Claude for programming apps, so at the start of the course I expected little that was new. I was pleasantly surprised: Ioana Teleanu approaches the subject in a way that is both informative and broad for designers. All IxDF courses also include a practical part in which you tackle your own projects. For me that led to an intensive engagement with Figma Agents and the Figma MCP Server, which opened up a series of efficient methods for creation, for producing wireframe variants and for design alternatives. Ethical questions were covered too, along with measures and methods for developing human-centred, ethical products and services.

Demonstrated mastery of how to

• Design AI-powered experiences responsibly by setting accurate user expectations, increasing system transparency, and accounting for privacy, safety, and ethical risks.
• Apply the National Institute of Standards and Technology’s (NIST) seven characteristics of a trustworthy AI system (valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with harmful bias managed) to evaluate and strengthen AI product decisions.
• Automate repetitive design tasks with AI and make deliberate decisions about what to automate and what to keep human-led to protect quality, intent, and user outcomes.
• Write AI-assisted problem statements and apply the AI workflow framework across the design thinking process and delivery.
• Generate and iterate on high-fidelity UI directions with AI, then apply human judgment to refine them, including AI-assisted UX copy, microcopy, and content variations that fit the product voice.
• Produce multiple wireframe options with AI and apply the generate, test, and refine loop to ground layout decisions in early user feedback.
• Use AI to process and synthesize research data, cleaning inputs, extracting themes, and turning raw notes and transcripts into structured insights the team can act on.
• Apply Microsoft’s HAX interaction guidelines to design AI products that are transparent, trustworthy, and user-controllable.
• Interpret AI-generated heatmaps, clarity metrics, and heuristic audits to catch usability issues before recruiting for live testing.
• Conduct market research and competitive analysis with AI, then validate findings against real user data.
• Build and interact with synthetic AI personas and research-backed interactive personas to pressure-test ideas and surface usability issues before formal testing.
• Use an adapted version of the Google PAIR framework, including Wizard-of-Oz prototyping and a confusion matrix, to design responsibly with machine learning.
• Produce launch-ready supporting assets with AI, from marketing copy and app icons to pitch deck content, that communicate a product’s value clearly and efficiently.
• Frame AI prompts using zero-shot, one-shot, few-shot, role, and chain-of-thought techniques to get precise, usable outputs across text, image, and task-based models.