AI at Work: Design Systems
Design systems have always been about finding the right balance between rules and freedom, structure and speed.
22 Results
Design systems have always been about finding the right balance between rules and freedom, structure and speed.
Building AI skills taught me that the most valuable part is not the prompt itself, but the thinking, structure, and refinement behind it.
AI coding tools are making it possible to build software faster than ever before. But speed alone is not enough. Leveraging AI alongside good development practices helps us move faster without sacrificing quality.
AI agents are only as good as the context you give them. To shape how your agent behaves and what it knows how to do, there are two concepts at your disposal. Rules and skills allow you to spend less time repeating yourself and more time getting better results.
By framing the current landscape as a “New Polyglot Wave,” I’ve moved past the anxiety of finding the “perfect” tool. Instead, I focus on building an intentional workflow where the best AI tool is sometimes three (or none).
Using AI Can Help Streamline and Enhance UX Competitive Audits
If you try asking an LLM something specific about the content and data that matters to you every day, you may receive an answer even if the LLM doesn’t actually know. RAG workflows can reduce hallucinations and guesses by providing an LLM with contextually-specific data and expert know-how.
We had a terrific UnConference in February focused on the intersection of AI and Human Expertise. If you weren’t able to join us, you can find everything on YouTube. Links below!
Although AI is often seen as a tool for increasing speed, its real value lies in the space it creates for judgment, collaboration, and intentional work.
What’s the difference between agents, models, and tools? How do they all work together?

Katie Jennings
Vice President of Business Development