Who are we designing for now?

"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. But besides the current momentum, we still have to focus on real problems that bring real value as of now. This balance is sometimes challenging, but also creates opportunities to reform our thinking and approaches."

"As AI agents become embedded collaborators in our systems, designers face a powerful and pressing question: Who are we designing for now? Suddenly, we find ourselves in the middle of a new Experience dilemma: designing for both people and programs. That means exploring new personas and reconciling different approaches: emotional intuition, logical execution, and the coherence of both. Let's have a look at the pitfalls of this dilemma and explore what we have to consider while designing for both humans and machines."

"Product Design 101 is all about understanding human experiences: how something feels, how intuitive it is, how it delights. But agents don't feel. They parse. They tokenize. They operate on pattern recognition, context, probability, and strict interpretation. Designing for agents means building interfaces that are accessible and intuitive but speak clearly to non-human readers. Think structured data, semantic HTML, accessible roles, predictable metadata, and context."

AI is rapidly transforming design practice beyond software, shifting priorities from pixel-level fidelity to anticipating future needs. Designers now balance conceptual foresight—sensing trends, building future-proof systems, and thinking years ahead—with solving present, practical problems that deliver immediate value. AI agents are emerging as embedded collaborators, creating a dual-user landscape requiring interfaces that serve both humans and programs. Agents parse, tokenize, and rely on pattern recognition, context, probability, and strict interpretation. Designing for agents demands new UX abstractions: structured data, semantic HTML, accessible roles, predictable metadata, and clear context. Interfaces must remain intuitive for humans while remaining unambiguous for machine readers.

Read at Medium