#machine-experience-design

#machine-experience-design

Santa Cruz de Tenerife is one of the most idyllic cities in the Canary Islands. At its heart stands the jewel - the Auditorio. It's a place where talent from both worlds, New and Old, comes together. A theatre, opera, dance, and music heaven.

For decades in SAAS, products reduced ambiguity. Users supplied constrained inputs, and the system handled the output. It's never been Minority Report cinematic, but it was predictable. By providing predictable environments for manipulating data, users learned by moving things, adjusting variables - and the outcome emerged through interaction.

Instructions I created. Instructions I am continuing to hone - instructions that required me to study my own old essays, identifying what I do when I write. The sentence rhythms. The way I move between timescales. The zooming in and out from concept to detail. The instructions tell Claude how I would like ideas composed. I pull together concepts and experiences from my lived expertise to formulate a point of view - in this case, on this new AI technology.

The normative form for interacting with what we think of as "AI" is something like this: there's a chat you type a question you wait for a few seconds you start seeing an answer. you start reading it you read or scan some more tens of seconds longer, while the rest of the response appears you maybe study the response in more detail you respond the loop continues

LLMs have made AI assistants a standard feature across SaaS. AI assistants allow users to instantly retrieve information and interact with a system through text-based prompts. Mathias Biilmann, in his article " Introducing AX: Why Agent Experience Matters," discusses two distinct approaches to building AI assistants. The Closed Approach involves a conversational assistant embedded directly within a single SaaS product. Examples include Zoom's AI Companion, Salesforce CRM's Einstein, and Microsoft's Copilot. The Open Approach involves external conversational assistants, such as Claude, ChatGPT, and Gemini,

Something's been slowly shifting in the design zeitgeist. I've been watching my feed on X and the vibe has changed. More and more, I see designers sharing finished experiments or prototypes they coded themselves, rather than static Figma files. Moving from working on a canvas to talking to an LLM. The conversation isn't "here's a design I made" anymore... it's "here's something I shipped this afternoon."

AI is disrupting more than the software industry, and is doing so at a breakneck speed. Not long ago, designers were deep in Figma variables and pixel-perfect mockups. Now, tools like v0, Lovable, and Cursor are enabling instant, vibe-based prototyping that makes old methods feel almost quaint. What's coming into sharper focus isn't fidelity, it's foresight. Part of the work of Product Design today is conceptual: sensing trends, building future-proof systems, and thinking years ahead.

Your junior designer spins up a prototype in Lovable before lunch. Your PM shows you a "working" MVP built entirely with Cursor within a day. And your CEO forwards you a LinkedIn post about how AI will replace 80% of UI work by 2026. And it seems like anyone can now make an app to solve a specific problem. Has the graphical interface really died, as Jakob Nielsen provocatively suggests?