Exploring the future of product design with AI
From calibrated trust to agentive UX: practical insights and frameworks for designing products in the next era of AI
The conversation around artificial intelligence in product design has reached a turning point. We’ve officially moved past the hype into an era where AI is deeply integrated into complex systems. As AI becomes part of our daily work, designers are facing real challenges, from rising anti-AI sentiment to flawed research synthesis. Navigating this shift requires more than just better prompts; it demands scalable design systems, resilient component architectures, and robust interaction guardrails.
To navigate this next phase, our design community gathered for Zalando Design Day, a full day event focused on the practical side of AI in design, cutting through the noise to share real-world insights. Featuring talks and workshops from industry expert Vitaly Friedman alongside our own designers, the event gave us actionable frameworks to use in our daily projects.
Read on for a deep dive into the practical strategies, interaction patterns, and mindset shifts that will help shape the future of product design.
Moving beyond AI hype to calibrated trust
When generative AI first exploded in 2022, the digital design landscape changed overnight. But as the initial novelty wears off, designers are encountering a very different reality. Kicking off the day with his keynote, “State of AI 2026,” Vitaly Friedman — founder of Smashing Magazine and Senior UX Lead at the European Parliament — explored how this shift is playing out on the ground. His primary takeaway? Designers are now facing a critical challenge: a growing “anti-AI” sentiment driven by confusion and a lack of trust.
“Designers are facing a critical challenge: a growing “anti-AI” sentiment driven by confusion and a lack of trust.”
Despite significant technical improvements, many users perceive AI as unreliable, especially when it comes to using it for work. Common pain points include increasingly subtle hallucinations, the heavy cognitive load of fixing AI errors, and a growing ‘AI fatigue’, backed up by research, where users often prefer non-AI labelled products, or products including “smart features” over explicitly labeled “AI features”. “AI-first” products are often perceived as being “cheap” or “untrustworthy” rather than innovative.
Building people’s trust: The designer’s new north star
To bridge this gap, Vitaly explained, the focus must shift from maximising trust to calibrated trust. This means designing interfaces that allow users to rely on AI when it is right, but easily verify and override it when it is wrong. Key strategies for building this trust include:
- Verifiable outputs: Instead of providing a “wall of text,” AI responses should include clear, navigable sources that point directly to specific segments of data.
- Keeping humans in the loop: Designers should avoid experiences providing full autonomy to agents. Instead, involve users even in small, approved steps to maintain a sense of control. Research shows that user resistance to AI labels disappears when features are framed as enhancing personal autonomy rather than taking away control.
- Context-aware interfaces: Moving beyond the blank chat box, the UI should change based on user intent — for example, shifting to a code editor when the user needs to write a script.
“Trust doesn’t emerge by default. It comes from understanding the product, interacting with it successfully, achieving goals — and then expanding usage. It’s all about consistent reliability.” — Shared Vitaly
Emerging design patterns for AI
The “2022 way” of manual prompt engineering is increasingly obsolete. Modern design patterns are evolving away from manual prompt engineering toward fluid multimodal inputs (voice, AI-enabled cursors), intent-based pre-prompts, and structured task builders.
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Ultimately, the goal for designers in 2026 is not to replace human judgment but to determine when AI is truly valuable and when deterministic, reliable software is the better choice. By focusing on transparency and accountability, we can design AI experiences that people actually value and trust.
The paradigm shift: Designing interfaces for autonomous agents
In his session “Designing for no one”, Principal Product Designer Sriram Venugopal explored how the definition of a “user” is rapidly expanding to encompass both humans and autonomous AI agents acting on their behalf. We are entering the era of agentive design — crafting software that acts on our behalf rather than software we manually operate.
When the entity navigating your product isn’t human, traditional design playbooks break down:
- Agents have zero FOMO: Banners flashing “WOW Deal,” “Only 4 left in stock,” or urgency-driving countdowns have zero emotional impact on an agent. The agent executes the parameters requested and discards the visual noise.
- Agents do not reconsider: Agents don’t hesitate, they do what they are told to do. Safeguards and friction designed to slow down a human in their decision-making process do not work on an agent.
- Agents do not wander: They don’t leisurely browse lookbooks, stumble on things they didn’t know they wanted or explore casually. They need to be told up-front exactly what to look for; they don’t get distracted.
While we are not yet at the point where humans completely rely on agents to manage all of their daily tasks and purchases, more products are being built with this capability in mind. So, how do we design for an autonomous agent while keeping human trust at the core?
Designing for accessibility is the superpower for agent readiness
What an agent reads is the accessibility tree of your product. It values clean data, clear labels, and clear semantic structure over visual flair.
Internal testing reveals a stark trend: an agent’s task completion rate sits at 78% under standard operating conditions, but crashes to just 28% when structural accessibility is broken. The clean code, semantic labels, and accessible systems we build today are the exact frameworks AI agents will rely on tomorrow.
As designers, we play a crucial role in defining what an agent is allowed to do within our products. We know what the agent needs to navigate, as well as what the human user wants: to feel confident delegating tasks, to trust the agent’s actions, and to maintain control.
“We have two users with different needs. Designing for both is the work we need to do now” Sriram concluded.
Practical playbooks: Take these AI design insights further
Navigating this next era of AI requires both big-picture vision and day-to-day tactical shifts. If you want to explore the hands-on methodologies presented at Design Day, check out the dedicated playbooks published by our speakers:
- Why your generative customer insights are probably wrong (and how to fix them)
Emilie Alonso, Principal Product Designer, pulled back the curtain on the hidden pitfalls of using generative AI for qualitative discovery. In her guide, she breaks down the 5 cognitive AI flaws in research synthesis and shares a system prompt framework to enforce data grounding. - Beyond the prompt: mastering Figma Make for pixel-perfect design
Yuls Walters, Product Designer, brought a wave of practical optimisation to the canvas with her talk, “Beyond the Prompt: Mastering Figma Make for Pixel-Perfect Design.” She introduces her “3Cs” framework (Content, Context, Correction) to help designers structure clean Auto Layout files, avoid prompt ambiguity, and escape generative loops.
Designing the next chapter of product design
AI isn’t here to replace us as designers; it is here to help scale, amplify, and empower the systems and structural thinking that already live within us. The real opportunity ahead lies in bridging the gap between human intuition and machine capability: defining ethical guardrails, building resilient systems, and creating intentional experiences that foster genuine trust.
How is your team navigating AI integration into your daily design process? Have you experimented with agentic UX or designing for both human and AI users? We’d love to hear how you’re approaching these shifts!
