AI is changing far more than the speed at which designers produce work. In this episode, we talk with Josh Clark and Veronika Kindred about their book Sentient Design, how intelligent interfaces can respond to people in the moment, and why designers need to understand the character of AI before they can use it well.
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Use the code SENTIENT-BOAG to get 20% off the book through Aug 31 at rosenfeldmedia.com.
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Designing With AI as a Material
Josh and Veronika describe AI as a design material, much as paint, paper, code, or the web itself can be materials. Every material has a grain. It has qualities that make some things easy and other things awkward, unreliable, or downright foolish. Designers get better results when they understand those qualities rather than forcing the material to behave like something familiar.
Large language models are probabilistic. They can interpret intent, adapt tone, change formats, and produce many plausible variations, but they may also give different answers to the same question and present shaky information with alarming confidence. That makes them poor choices for some deterministic tasks, especially when a single correct answer matters. Asking one to count letters or provide an exact food-safety temperature without verification rather misses the point of what the material does well.
Designers need enough experience with AI to make an informed choice about when to use it and when to leave it alone. Refusing to engage with it leaves that decision to ignorance, which has rarely been a dependable design system, despite Paul's suspiciously successful career testing the theory!
The comparison with the early web runs throughout the conversation. Print designers initially approached websites with expectations shaped by paper, while the people who learned HTML and understood the new medium found different possibilities. AI creates a similar shift. Its rough edges can feel threatening, particularly when companies use it to cut costs or flatten skilled work into production, but those edges also point toward forms of interaction that were difficult or impossible before.
Moving Beyond the Chatbot
Chat has become the default AI interface, partly because our culture has spent decades imagining intelligent machines as talking machines. It can be useful because both the input and output remain open, but a blank text box also makes the user do a great deal of work. People must know what to ask, how to phrase it, and how to judge the resulting wall of text.
Sentient Design describes 4 broader postures for intelligent experiences:
- Tools accept an input and return a controlled, precise output. Shazam is a familiar example.
- Chat uses a turn-based exchange, although those turns can involve images, interface components, or shared artifacts rather than paragraphs of text.
- Agents receive a goal, plan and perform the work, then return with a result. They still need direction, oversight, and review.
- Copilots remain quietly present, notice context, and offer assistance when useful, much like spellcheck waiting behind the scenes.
These postures allow teams to choose an interaction that fits the task. A conversational box might suit exploration, while a focused tool is better for a clear transaction. An agent can handle delegated work, while a copilot can notice opportunities without demanding constant management.
Josh and Veronika also share examples of AI taking part inside an existing interface. Salesforce's Generative Canvas assembles relevant components using trusted customer and calendar data. Miro's sidekicks can enter a canvas with their own cursors, while Pointer participates in a Google Doc as an editor, using the collaboration patterns people already understand.
The interesting design question is how intelligence participates in an experience, not where to bolt on another chat window.
Defensive Design for Uncertain Systems
Trust becomes a design problem when systems are probabilistic. A generic disclaimer saying that AI can make mistakes does very little for someone deciding whether to believe a specific answer. Confidence scores often fare no better because most people have no useful way to interpret a claim such as “73% likely.”
Defensive design communicates uncertainty through language, interface, and context. A system can present an answer as a signal rather than an unquestionable fact, show nearby possibilities, reveal where information came from, and give the user sensible points for review or intervention.
Veronika describes “spaghetti scenarios,” borrowed from weather forecasting, where several possible paths are shown together. A search interface can do something similar by presenting adjacent questions and contrasting answers. This helps people see how wording, assumptions, and context affect the result.
Tone matters too. Human beings constantly signal confidence through phrasing, body language, and shared cultural habits. AI systems tend to speak with the polished certainty of Silicon Valley, even when the evidence underneath is wobbling like a pub table with one short leg. Designers need to shape that presentation for the domain, audience, and seriousness of the decision.
The pair argue that language models work well as the master of ceremonies for an experience. They can understand intent, coordinate with specialist systems, and present results in a useful format. Facts can come from trusted sources and deterministic tools, while AI handles interpretation and presentation.
AI should communicate uncertainty in a way people can act on, rather than hiding it behind confidence or a disclaimer.
From Doers to Directors
As AI becomes part of the product, designers move toward directing systems that make design decisions in the moment. The book describes them as creative directors for systems that design themselves in real time. They define the available components, language, behavior, constraints, and rules, then guide how the system adapts them to each person's context.
That shift can compress the handoffs between design, development, and product. Josh describes teams working in a common space, often a Git repository, where requirements, design guidance, and code sit closer together. AI can help each discipline contribute beyond its old boundaries, although the resulting overlap creates fresh questions about roles, careers, and management.
The conversation also acknowledges the uncomfortable part. Production work is already being absorbed, and some companies assume that one senior person can manage a fleet of agents instead of developing junior designers. That approach may remove the path by which the next generation gains judgment and becomes senior. It also mistakes design for assembly.
The stronger opportunity lies in behavior design, problem definition, research, creative direction, and the design of intelligent systems themselves. Designers can document why components exist, when to use them, how content should behave, and which outcomes matter. AI can then apply those rules while the designer improves the system through research and observation.
Paul shares an example from his conversion optimization work. Rather than creating a single landing-page template for many audiences and campaigns, he built a component system with detailed guidance covering placement, content, accessibility, funnel stage, and use. AI could assemble a suitable page within those constraints, while the human designer had more time for research and strategy. If you are facing similar questions about moving design beyond production, the free UX Strategy email course offers a useful next step.
The future of design depends on widening our view of the job, from producing screens to shaping behavior, systems, and decisions. That may be less comforting for anyone whose greatest joy is pushing pixels around in Figma, but it also brings design back to understanding problems and exploring possibilities.
Sentient Design
Sentient Design brings together the vocabulary, patterns, and examples emerging around intelligent interfaces. It covers 4 experience postures, 14 experience patterns, defensive design, adaptive interfaces, and the changing relationship between designers, developers, product teams, and AI.
You can find Josh Clark and Veronika Kindred at Big Medium.
Use the code SENTIENT-BOAG to get 20% off the book through Aug 31 at rosenfeldmedia.com.
Marcus' Jokes
Velcro. What a rip-off!
Exit signs. They're on the way out.
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