Has AI work moved designers upstream from screens?
Salesforce Design claims AI systems require designers to shift focus from creating user interfaces to architecting the invisible orchestration and semantic foundations that precede them. The question asks whether this represents a genuine and necessary change in design practice.
Salesforce Design's year-end retrospective opens with the claim that "design sets the foundation for trustworthy AI" because "designers help establish the semantic foundation that teaches AI what things mean and how humans work." Hsiao-Ching Chou, writing for Salesforce Design, frames the throughline of the company's 2025 design work as a shift in what designers actually do: "to borrow the words of a colleague who's a principal AI architect, design used to be about creating screens. Now, it's about deciding what happens before the screen appears." Kat Holmes, Salesforce's Chief Experience Officer, names this shift "agent experience design, where AI agents are treated as a new kind of user."
The reasoning the piece gives is that AI systems are "dynamic" and have "no need to have a single user journey or click path," so the old unit of design work — a screen, a flow — stops being where the leverage is. Design Director JoEllen Kames describes product designers having to architect "the 'invisible' scaffolding that enables AI systems to respond in real time" and to "create experiences that surface the right things at the right time and in the right places." Principal Product Designer Hervé Mischler makes the same point from the gap it leaves: "traditional UX design doesn't have frameworks for coding assistants and multi-agent orchestration," which is why designers must build "experiences that harness coordinated AI agents across platforms while maintaining human agency and understanding." Former Salesforce designer Min Chang generalizes it as systems thinking: "instead of designing for isolated screens, I'm now designing how a system moves between states."
This gives a practitioner-side name to work that How should AI interfaces handle the shift from doing to supervising? formalizes into an explicit architecture: Nielsen's Orchestration Surface, the layer where an agent reveal[s] its proposed plan and seeks consent before acting, is a concrete design answer to the same "before the screen appears" territory Chou's colleagues describe informally, and his Direct-Manipulation Surface is the GUI that Salesforce's designers say is no longer the primary unit of design. Against that backdrop, How should AI systems be designed across different interaction phases? is the guideline set this piece implicitly argues has been outgrown: Amershi's guidelines still assume a graphical interface to correct and calibrate, where Chou's retrospective describes designers working one layer upstream of that interface, on orchestration and semantics rather than on-screen correction.
What the excerpt does not establish is whether this shift actually improves outcomes for users or businesses. It is a company blog's retrospective, assembling quotes from named Salesforce employees and executives about their own year of work — not a study, and not independently validated: there is no usability data, adoption figure, or comparison showing that "agent experience design" or "invisible scaffolding" work produces better agent experiences than screen-first design would. The piece is also specific to one vendor's product context (Salesforce's Agentforce platform and Lightning-based SLDS 2 design system), so the generalization to design practice outside Salesforce is an extrapolation the source itself does not make. The implication, held at that strength, is that this vocabulary shift — from screens to scaffolding — describes how one company's design organization narrates its own 2025 work, not yet a demonstrated change in what makes AI products usable.
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How should AI interfaces handle the shift from doing to supervising?
Nielsen explores what UI architecture allows users to oversee AI work rather than perform it themselves. This matters because intent-based systems fundamentally change the user's role from operator to supervisor.
formalizes the same "before the screen appears" work this retrospective describes informally into a named Orchestration Surface
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How should AI systems be designed across different interaction phases?
Can a small set of general guidelines help practitioners design better AI-infused products across different moments—initial setup, active use, error handling, and long-term adaptation?
the GUI-correction-era guideline set this retrospective's "new UX paradigm" implicitly argues has been outgrown
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What design skills do teams need for the AI era?
Explores whether experience architecture, agent collaboration, conversation design, and context mapping represent essential competencies for design teams building AI systems, and why these skills matter for organizational readiness.
the skills framework this same retrospective proposes for doing the "before the screen" work described here
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Can familiar software terms gain new meaning for AI agents?
Explores whether old vocabulary like prompt, context, and guardrails can be repurposed as design surfaces for agentic AI systems. Matters because designers need shared language to build autonomous systems responsibly.
Extends the scaffolding claim: a companion glossary defines prompt, context, and guardrails as concrete design surfaces for it
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- 2025 in Review: Design Gives AI Meaning
- The Designer's AI Glossary: Familiar Words, New Meanings
- Get 5 Insider Design Tips for Building Your AI Agents
- Designs for the frontier future
- Designing for Autonomy: UX Principles for Agentic AI
- A Framework of User Experience Principles for Human-AI Agent Interaction in the Workplace
- How AI is transforming work at Anthropic
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Original note title
Salesforce Design argues design shifted from creating screens to deciding what happens before the screen appears