As the curtain parted on moooi’s 2022 exhibit, the audience was treated to a multi-sensory performance unlike any other: four synchronized robot scent diffusers telling a story through dance. As the robots—called Piro—swayed and dipped to the beats of a custom-designed soundscape, it was easy to forget the performers were made by a team of industrial designers and engineers in San Francisco.

The work expressed a future vision for what it means to humanize technology. Rather than design technology to make our lives more efficient, what if instead we designed technology to make life more beautiful?

For twenty years, moooi has seduced the world with bold, imaginative design. The firm, named after the Dutch word for beautiful, made its name by designing furniture and home goods that appeal to an interest in pushing the edges of form as much as function. Moooi came to IDEO looking to create an exhibit for the largest furniture fair in the world that might provoke the audience to imagine a world where design’s primary function was to inspire joy.

“Defy Gravity”: one of several experiential “worlds” moooi created for the 2022 Salone del Mobile. Each room had its own scent, soundscape, color, and digital experience.

Our process started by going wide. We presented 20 potential conceptual designs to the team, one of which moooi founder Marcel Wanders lovingly referred to as the “farting pet,” a robot scent diffuser that could walk around the home.

A scented smoke ring lingers in the air after Piro’s final crescendo.

From there, a team of IDEO designers enlisted the support of Catie Cuan, a choreographer who specializes in human-robot interaction, and Dutch sound design firm KLOAQ, to refine the concept into a four-minute performance piece.

Piro learned to mimic balletic human gestures.

The final result was technically involved: four robots moved independently, controlled by custom electronics and software designed to mimic the movements and grace of ballerinas. But in the performance itself, the complex mechanics disappeared, allowing the audience to experience not just what technology can do, but how it can make us feel.

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What happens when a designer and a classically-trained choreographer collaborate? Attendees of Salone del Mobile.Milano, the largest furniture fair in the world, got to see for themselves.

To build a climate-resilient future, we need an all-hands-on-deck approach across industries and organizations, as well as the leadership and collaboration of frontline communities themselves. 

To that end, IDEO and CSAA Insurance Group worked together to unite nine partner organizations, including Aon and the Environmental Defense Fund, to launch an open call for solutions to help communities prevent, prepare for, and recover from climate-related disasters. The goal of the Challenge was to surface actionable and scalable ideas that experiment with new technologies, models, and partnerships, then provide innovators with the support and funding they need to get their ideas off the ground and into the hands of frontline communities.

IDEO set these entrepreneurs up for success throughout the submission process, holding one-on-one conversations with participants, sharing constructive feedback on potential solutions, and developing their ideas and skill sets. The team also hosted workshop and panel sessions to grow community bonds and provide expertise on critical topics, including assessing climate risk and storytelling for impact. Hundreds of ideas came in from around the world, ranging from harnessing the power of AI, to building resilient infrastructures, to democratizing access to climate data, and more.

Once all of the ideas were in, a cohort of judges with a wide diversity of work and lived experience screened for concepts that were relevant, impactful, novel, community-informed, and equitable. At the end of the Challenge, the team chose 13 winning concepts with high potential for impact and partnerships, including Reef Rocket, which seeks to fabricate natural biocement reefs that reduce coastal flooding and erosion, and BurnBot, which is working to prevent wildfires by conducting controlled burns at scale.  

For these winning entrepreneurs, the end of the Challenge is just the beginning. Now, they are equipped with critical early funding, as well as a cohort of climate entrepreneurs, along with mentorship from IDEO, CSAA, and the other organizations. It’s a big step forward as they introduce new forms of equitable and transparent data, promote the voices of BIPOC communities, and bring to market new technologies that will protect and support frontline communities through this ongoing crisis. 

Read the Challenge Impact Report to learn more.

In the US alone, climate-related disasters cause $120 billion in damages annually. That figure is five times greater than 50 years ago, and projections are $2 trillion by the end of the century.

Nearly 90% of counties in the US declared a natural disaster over the last decade.

418

submissions

13

winners

$1M

in prizes

Every year, the NSF provides around 30 teams with up to $750,000 and a year’s worth of coaching, training, and collaboration to develop solutions for research areas like sustainable ocean use or combating fake news. Over the course of nine months, the teams learn how to uncover insights about human needs and design durable solutions for end users. But many of the scientists and experts in the program felt stretched by the idea of putting the needs of end users in the mix with their scientific testing—something few of them have been trained to do in their previous work.

To make that process feel more achievable, the teams built out prototypes and received guidance on refining and pitching their ideas along the way. IDEO joined the project as an innovation partner, facilitating hands-on workshops and creating “Science TV” episodes that could help the program reach a broader audience, deepening its impact now and in the future.

To help grantees get vulnerable, and evolve their ways of working, IDEO sent grantees to improv training  so that they could learn to build off each other. The team also took them to magic shows and on ghost tours in downtown San Francisco to learn the value of compelling storytelling in their work. The fun was part of the plan—gelling as a team and building relationships meant participants could make mistakes in front of one another. Being wrong doesn’t come naturally to academics, but it’s a key part of the design process, and a crucial part of solving complex problems .

Each year, a select group of teams move onto the next phase of the “coop-etition,” receiving up to $5 million in additional funding. And all of the participants leave with valuable new skills they can use to break out of their own silos and create human-centered, ground-breaking solutions for the rest of their careers.

When the NSF launched the Convergence Accelerator and made the radical move of bringing together teams from different disciplines, these academics, scientists, and industry partners didn’t have a shared language to move their ideas forward, and needed a structured approach to coming up with new solutions.

164

trained research teams

$200M

in federal support granted to AI-driven innovation, quantum technology, food security, sustainable materials, opportunities for people with disabilities, and more

IDEO and The Earthshot Prize built a nine-month Fellowship program and a five-day, in-person retreat to give Finalists the best shot at reaching the Prize’s ultimate goal: to scale the solutions that will repair our planet this decade.

To build out the new Fellowship, IDEO took a deep dive with the previous year’s Finalists to uncover where they needed critical support. This research revealed that the Finalists needed more ways to leverage the Earthshot platform, connect with potential partners to help scale their ideas, and build community with each other. The IDEO team then used those insights to create a set of recommendations The Earthshot Prize team could implement to create a more supportive and structured experience. Ideas they took forward included assigning a designated “Leap Advisor” who could provide guidance and assistance for each Finalist, as well as an advisor from the Prize’s Global Alliance Network who could partner on specific growth initiatives, like scaling product design, or policy change. 

Next up: the design of the retreat itself. Together, IDEO and the Earthshot team had three goals for the cohort’s week together in Windsor: focus on new forms of leadership and movement building, spur action through storytelling, and foster community.

The team developed the curriculum with leaders from Google X and Speed & Scale, alongside startups like UPSIDE Foods. They designed moments to build community, like paired walks and a chocolate-making workshop where Finalists could get to know each other away from the noise of meetings. 

Photographers captured the event to create assets for Finalists to use when pitching their ideas, and Finalists honed their storytelling skills. But what most remember is the magical moments of coming together as a cohort of next generation climate leaders who will help each other make an impact on the problems facing our planet, long after The Earthshot Prize has concluded.

The problems facing our planet are enormous, spanning industries, borders, currencies, and regulatory environments. Meaningful solutions will require leaders who can work across those lines.

30

climate solutions accelerated in first two years

If you ask consumers whether they trust their bank or health insurer, the answer is often lukewarm at best. Traditional financial institutions are seen as opaque, distant, and—in the worst cases—extractive. In a recent survey, barely a third of people thought their bank was being honest and transparent about costs and fees. But this narrative misses a subtler, more hopeful trend: The very technologies customers once feared as “creepy” are now opening a path toward rebuilding trust—not by hiding behind compliance and branding, but by providing real, personal value that people experience every day.

At the heart of that opportunity is AI. But not the generic, algorithm-as-black-box that so often gets headlines in the press. I’m talking about AI designed to help people, surfaced in ways that feel insightful rather than intrusive, and that elevates the relationship between individual and institution. It has the potential to rewrite our skepticism of digital products. 

The myth of the “creepy algorithm”

We’ve long assumed that consumers recoil at AI and the use of personal data. But emerging evidence and our own work at IDEO suggest a more nuanced truth: People don’t mind institutions using their data if the outcome is genuinely helpful.

What consumers resist is not personalization per se, but value extraction masquerading as personalization. They reject opaque upsells, hidden fees, and pricing strategies that leverage data solely to maximize profit. Anyone who has filed their taxes with the most popular online filing software can attest to the repeated (and difficult to decline) requests to use their tax data and share it with third parties, or to pay for add-on features of dubious value. But consumers welcome insights that feel like guidance—a personalized budget forecast that suggests paying down a mortgage faster, or a care recommendation that anticipates a chronic condition based on patterns in medical claims.

Financial institutions need to know their customers to help them meet their goals, not just the company’s bottom line.

When AI becomes a bridge, not a barrier

This distinction reframes the role of AI from a technical feature to a trust-building mechanism across two dimensions:

Predictive empathy: AI can surface insights that anticipate people’s needs before they articulate them. Imagine a health insurer that detects early patterns of risk in claims data and nudges members toward preventive care—with clear explanations and options—rather than waiting for a crisis.

Clarifying complexity: Financial and health decisions are inherently complicated. Consumers often feel alone with high-stakes choices—choosing a plan, managing costs, planning a life event. AI can simplify decision pathways, outline “what good looks like,” and benchmark personal choices against broader patterns of positive outcomes.

This is not theoretical. Customers are more open to institution-driven AI guidance than third-party general-purpose AI tools, precisely because of contextual relevance. While 79 percent of US consumers are uncomfortable with AI providing medical advice, a majority are open to AI supporting tasks like after-visit summaries and follow-ups.

In recent work we completed for a network of financial advisors, for example, we found that a customer’s trust in their financial advisor alone was not enough. They needed to believe that the plan presented to them met their needs and was likely to succeed, given the current market and their own financial situation. Unfortunately, too many financial institutions are seeing an opportunity to replace people with machines. When, in fact, there’s now an entirely new opportunity space of using generative AI to show, rather than tell, customers why they should have confidence in the path forward. People build trust. Digital tools can build confidence through what-if scenario planning, natural-language explanations, and the ability to have back-and-forth conversations whenever people want, without fear of asking “stupid” questions.

The unleveraged assets: contextual data and human intent

Banks service millions of accounts across life stages. Health insurers care for diverse populations across care journeys. These institutions are regulated to protect consumers, and in theory, succeed when their customers succeed. Yet traditionally, the relationship has been transactional: accounts, premiums, claims, and products.

AI changes that calculus. With careful design, institutions can translate the data they already hold into guidance that feels humane and useful. What might that look like?

• A bank dashboard that explains how spending patterns today impact long-term financial goals tomorrow in plain language, with actionable suggestions.

• A health insurance experience that models likely care pathways based on clinical evidence, population outcomes, and expected out-of-pocket costs, helping members choose care confidently.

• Alerts that not only flag risk—say, missed medication adherence—but also provide contextual support options, such as care coaches or financial assistance resources.

We don’t have to imagine far into the future to see what this looks like—we can actually see it in the not-too-distant past. When IDEO worked with PNC to develop their online banking platform, Virtual Wallet, one of the most compelling features for customers was a calendar that visualized “Danger Days”—days when their balances would be low, and they were most likely to overdraft. During a time when banks were making big profits by optimizing their technology to increase overdraft fees, PNC went in the opposite direction, helping customers avoid fees they despised and improve their financial lives. The result was an award-winning product that led to millions of new accounts.

This reframes data use from an internal optimization tool to a shared resource that benefits the member first. As banks bring generative and agentic AI to the masses, that could start to look like suggesting specific actions customers can take to reduce spending when cash flow is tight, or automatically splitting bills that fluctuate in cost, such as groceries and utilities.

Why incumbents have a strategic advantage

New fintech and health tech startups often don’t have to contend with years of technology debt and legacy systems, but they do suffer from a cold-start problem: They lack deep context. They may ask users to upload data, recreate history, or deduce preferences from limited interactions. Meanwhile, incumbent banks and insurers already have longitudinal data spanning life events, regulatory frameworks ensuring baseline protections, and direct experience managing risk at scale.

These are more than just advantages—they are assets waiting to be mobilized to build trust.

A new contract between people and financial institutions

Rebuilding trust in financial services and health insurance isn’t just a matter of better algorithms. It’s about redesigning relationships and using AI to make institutions advocates for individual success.

It’s easy to imagine continuing with the status quo: adding a chat interface to a mobile banking app that relies on existing functionality, for example, or offloading the most commonly-requested customer support tasks to an agent to reduce call center volume. 

That’s not to say that there isn’t merit in some of those approaches. But, in a world where AI can feel impersonal and inscrutable, there is an opportunity for these institutions to shine by making AI personal. That’s not only good design. It’s good business, and it’s good for society. The question isn’t whether AI can help. It’s whether we will use AI to help people—boldly, compassionately, and with trust at the center.

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Working to build trust with your customers? We’d love to help. Get in touch.

“People don’t mind institutions using their data if the outcome is genuinely helpful."

For decades, the typical relationship between humans and hardware was a straightforward one of command and control. We pushed buttons; machines performed tasks. But as AI migrates from our screens into our physical environments, the nature of that relationship is shifting: Computation is becoming a nondeterministic presence.

So far, the industry seems to be caught between what users actually want and the sci-fi fantasies currently captivating the tech community. Rather than marrying what’s technologically feasible with what people need, companies are bolting AI onto everything, shipping tech demos as finished products. The result is half-baked experiences traded for focus, and speed traded for agency and privacy. A better path means establishing a new standard in which trusted, useful intelligence serves the physical world.

For us, it means designing under these seven principles for good AI hardware, inspired by the timeless rigor of Dieter Rams, and setting the conditions to put them into practice. 

1. Good AI hardware is mutualistic

AI is not a deterministic layer of software trapped in plastic. Designed well, it is a partner in human flourishing. We build hardware rooted in mutualism: the device learns from the perpetually shifting nuances of human intention, and the human grows through what the device makes possible. More than optimization, it is a shared evolution between person and machine.

What might that look like?

The Household Reflection Mirror

A bathroom mirror is designed without predetermined health goals. It comes equipped with sensors, models, and processing power, but without a built-in definition of what “better” means for you. That definition emerges through use.

In the first few weeks, the mirror observes your behaviors without interpreting them. Over time, patterns surface that you implicitly confirm or contradict through your actions. You linger on certain readouts. You ignore others. Slowly, the device constructs a model of what matters to you, not what a wellness framework says you should care about.

After three months, the mirror notices your sleep quality degrades during a particular recurring time of the week. On Monday morning it surfaces a single line beneath your reflection: “Sleep is typically shorter on Mondays.” The next Sunday, you go to bed an hour earlier. The mirror notices. Over time it learns what kind of attention you actually respond to, because you taught it through the way you live and react. The device you have at the end of the year is not the one you started with—and neither are you.

Without your input, it is a capable system with no inherent sense of purpose. Without it, you miss a form of self-knowledge you didn’t know you needed. Closing that gap together is the essence of mutualism.

2. Good AI hardware is off by default

Truly human-centered hardware requires intentional consent to engage. Privacy isn’t an afterthought; it is a foundational design requirement. Until there is consent and utility, we reject the always-on model of technology. We design to respect the privacy of our homes and lives, so that technology enters our cognitive space or observes our physical space only when we consent. Good AI hardware is something you want around, that makes you feel safe.

What might that look like? 

The Consent Door

A front door knob has a small illuminated ring at its base. When you arrive home, the ring pulses once, dimly and unhurried. It is asking for your attention.

Twist the knob the way you normally would to unlock the door, and the ring goes dark. The house stays quiet. No sensors wake. No systems are activated. You are home, yet the home does not know it.

Twist the knob the opposite way before you enter, and the ring glows brightly. The AI features of the home come online. The thermostat starts learning. The mirror observes. The kitchen listens. You’ve made a conscious choice with your body before you crossed the threshold.

Guests see the same dim, illuminated ring when they arrive. They face the same choice. The house never assumes.

3. Good AI hardware is aesthetic

A piece of hardware should improve the aesthetic or emotional vibe of a space or interaction. With all the focus on the AI, it’s easy to lose sight of how intentional and sensorial the hardware has to be to provide value. We lean into creativity by using ergonomic forms, tactile textures, and haptics to create objects that feel like art or furniture while having capabilities suited to their use. The best AI hardware is crafted with intention for its role in our environments. 

What might that look like? 

Climate-Aware Window Glass

A sheet of AI-embedded  glass replaces a traditional living room window. The glass learns sunlight patterns, outside temperatures, and occupants’ daily rhythms. When the afternoon sun becomes harsh, the glass subtly softens and diffuses the light, giving the room a warm, painterly glow. On cold winter mornings, it lets in full sunlight to warm the space. There are no visible controls and no notifications. The window functions as an intelligent material, shaping light and heat in ways that feel natural, healthy, and beautiful.

4. Good AI hardware makes the invisible honest

AI hardware should communicate its state, data usage, and limitations through intuitive physical cues. Sensors now extend far beyond cameras and microphones into biosignals, radar, emotion recognition, and neural intent. Technology can understand us in unprecedented ways, which creates unprecedented room for distrust. It’s crucial that we replace vague terms and conditions and labyrinth privacy settings with transparent, real-time feedback, and make the invisible visible. Honesty is the only foundation for a lasting relationship with intelligent technology.

What might that look like? 

Visible Cognition Display

A small home security camera sits near the front door. Inside the door is a narrow strip that displays what the AI believes it sees in plain language. When someone approaches at night, it writes: “Face scan attempted. Low light. Result unreliable. Door stayed locked.”

The system reaches the edge of what it can confidently do and stops there, telling you exactly why—and that restraint is the point. A device that surfaces its own limitations in real time is making a fundamentally different promise than one that acts with false confidence and hides its reasoning. That promise, repeated across thousands of small moments, is how trust is genuinely built.

5. Good AI hardware is minimally intrusive

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The ultimate goal is to improve our lives in the physical world, not to keep us tethered to a digital one. We need to design for the disappearing act by ruthlessly stripping away unnecessary screens and notifications, and removing friction between humans and their environments. We need to design to follow user intent, using the superpowers of AI to understand user needs and respond in simple, clear ways. Whenever possible, we embed AI into existing rhythms and daily flows, rather than requiring people to pick up new habits. 

What might that look like?

The Context-Aware Notification Pebble

A small, smooth stone is connected to your devices. When something truly important comes in—a call from family, a hard-to-get dinner reservation, a flight deal on a trip you’ve been planning—the pebble gently glows. There are no sounds. No vibrations. No screens. Just light.

If you pick it up, the message is faintly projected onto the desk. For matters that require a decision, the system has already done the legwork. It held the reservation. It queued the flight deal. The pebble presents you with a choice, not a task. A single tap confirms your decision. The pebble stops glowing, and life continues as normal.

If you choose to ignore it, the pebble turns off on its own. The system respects your attention instead of competing for it.

6. Good AI hardware is honest about its capabilities 

We design hardware that delivers on what technology can actually do, while meeting real user needs. Good design speculates and continues to evolve as technology improves, but it does not hinge on speculative promises it can’t meet (and which inevitably let users down). We focus on the high-fidelity reality of what a device can do now, making the hardware a reliable anchor as technology improves rather than a vessel of far-reaching hype.

What might that look like? 

The Tutor Tablet for Children

A child asks the intelligent tablet a complicated science question. The device pauses and displays the message: “I am not certain about this answer…  Would you like me to look it up with you?” When the model is unsure, it offers sources or invites the child to explore the topic together. Sometimes it even says: “I might be wrong. Let’s test it…”

In this way, the child learns two important lessons: the scientific method and the understanding that intelligence, whether human or artificial, involves humility.

7. Good AI hardware respects the Earth

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We reject creating unnecessary devices that contribute to the global e-waste crisis by staying attuned to real user needs. When we build, we design for longevity through repairability, modularity, and circularity. From the selection of materials to the ease of recycling at the end of a product’s life, good AI hardware takes responsibility for its physical footprint. We build tools that are meant to last, not to be discarded when the next software update arrives.

What might that look like?

The Modular Home Intelligence Hub

A small wood and aluminum hub sits on a shelf, running local AI models for the home. Each component slides out like a drawer: Compute, Storage, Radio, Battery, and Sensor Array. While these modules are functionally co-dependent, each one is discrete. For instance, whenever new AI chips are released, the owner can simply replace only the Compute drawer.

The device also maintains a lifetime material dashboard:

Operational life: 8 years
Upgraded components: 2
Material saved vs. replaced: 4.3 kg
Energy used this month: 2.1 kWh

The hub processes most workloads locally to minimize unnecessary cloud energy consumption. Instead of being replaced every few years, it ages alongside the household.

Putting the principles into practice 

It’s one thing to create a list of principles. It’s another to make them part of our work. To uncover real human needs, we do research with people in their homes, learning where they want machines to help and where they want to stay in control. Leveraging emerging tools like 3D printing, AI-accelerated prototyping, and generative design, we move from insight to artifact quickly. Rather than just rendering a sensor, we build it. Rather than speculating about how friction feels, we test a physical interface in someone’s home and let their reaction tell us what to do next. We hold creativity accountable to what’s technically viable and commercially scalable, so the visions we make are ones businesses can actually act on.

We are moving past the era of experimental AI and into the era of specialized, high-performance hardware that permeates our everyday lives. The only way to succeed in the market is to earn a permanent place in people’s  lives through trust and utility. By anchoring what we build in these principles, we move beyond the hype and into producing hardware that people actually want around. That is the standard we are building toward.

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(Looking for a partner to build AI products with? Get in touch.)

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"A better path means establishing a new standard in which trusted, useful intelligence serves the physical world."

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Founded in 2021, Callimacus is a small collective of mathematicians, engineers, artists, and philosophers exploring how new technologies can rewrite the web experience. Their guiding principle, “human artificial intelligence,” emphasizes designing systems that complement human values, highlight emotional nuance, and enhance human presence. 

So far, so San-Francisco-based-start-up, you might say. But, in fact, Callimacus swaps the hills of the Bay for the slopes of Solomeo, a medieval village in Perugia, Italy. Instead of a tech billionaire, its patron is a titan of luxury fashion: Brunello Cucinelli. 

‍As unexpected as that might sound, Cucinelli himself has been a passionate advocate of what he’s called the “humanistic enterprise,” born of his deep interest in philosophy. So while Callimacus might be pioneering a radical rethinking of e-commerce by challenging traditional established web and user experience norms, that’s firmly grounded in the brand’s human-centered DNA.

Callimacus's first product is an AI-native software development kit aptly called Callimacus, which powers Brunello Cucinelli’s new digital experience. Named after the ancient Greek poet and curator of the Great Library of Alexandria, Callimacus uses custom AI agents to dynamically generate the user experience based on user intent. For instance, the site’s agents can determine that a visitor is looking to learn about the story behind the brand (and serve them content, accordingly) or that they’re here to see the latest collection. It’s a custom experience very different from a traditional page-and-container website structure. 

I spoke with Francesco Bottigliero, Brunello Cucinelli’s Chief of Humanistic Technology and the CEO of Callimacus, to understand why the brand created the start-up, the importance of keeping humans at the heart of innovation, and reimagining UX and engineering for the AI era.

Ed White (EW): What was the inspiration behind Callimacus?

Francesco Bottigliero (FB): The French philosopher Voltaire once said, “Doubt is not an agreeable condition, but certainty is an absurd one.” This led us to think, “Our friends from Silicon Valley believe AI will be a game-changer, so let’s take the time to understand it.”

At Brunello Cucinelli, we’re focused on learning and staying current in our industry, rather than simply following trends. We choose technologies that align with our values, ensuring we don’t compromise the craftsmanship and brand positioning we’ve built over more than 40 years. In our boutiques, we aim to make technology invisible so there’s no barrier between sales associates and customers.  

We’re investing heavily in our brick-and-mortar distribution to stand out and nurture our brand identity, while also enhancing and developing our online identity. 

‍EW: Callimacus emphasizes “human artificial intelligence.” Can you explain what you mean by that?

FB: We view technology as a companion of humanity. We want human beings at the helm, steering the boat. However, if there are tools that can help people steering the boat make better decisions, we are ready to embrace them. 

EW: You recently launched an AI-driven web experience for Brunello Cucinelli using the Callimacus software development kit, which enables brands to create AI-native web experiences. Where did the idea for that come from? 

FB: When we looked at traditional e-commerce, we analyzed the navigation of six sites from six brands. We masked the brand names and placed the sites side by side. They all looked the same.

We decided to experiment with new ways to communicate our story more effectively. Today, when people talk about applying AI to e-commerce websites, they typically mean adding a chatbot. However, the underlying infrastructure remains the same, relying on page formats—whether product, listing, or article pages.

EW: Why are traditional web pages such a problem?

FB: Websites continue to be designed and developed using a typographic approach that has been in use for more than 30 years, dating back to the beginnings of the internet at CERN in Geneva. Users shared research papers online, and they were read as if they were physical books. The interaction mimicked print media by incorporating pages and menus people were already familiar with. Likewise, when I visit Corriere della Sera, Italy’s leading online newspaper, all its content is locked within a traditional page-and-container structure, making it difficult for me to search for something using natural language. The same issues apply to e-commerce sites.

Callimacus offers a completely different approach to website design. It functions like an orchestra, integrating multiple agents running on different large language models.

Callimacus is based on three fundamental ideas: First, we eliminated content containers, allowing content to flow and be recombined. We call it “page-less design.” Second, instead of starting with user interfaces or framework templates filled with placeholder text, we began by spotting signals of the customer’s intent and the experience and journey we wanted to offer. Third, enabled by the first two ideas, we created a personalization engine that delivers a tailored experience for each user. 

EW: How does that work?

FB: One of our agents, Thamyr, named after the ancient Greek painter, continuously analyzes the user’s intent—for example, getting inspired or product search—and updates the website in real time. Each interaction the user has with the website refines this intent. Thamyr might say, “It seems like this user is more interested in product search or is seeking inspiration.” She then goes to our agent, Socrates, and says, “Hey, please provide me with products the customer might be interested in.” However, it turns out the user is not really into the product but rather wants to explore the brand. So Thamyr decides to feature fewer products, but more editorial content. She then references the design system, selects the appropriate components, and builds the interface accordingly.

EW: How does all this “intelligence” impact the back end?

FB: One of the advantages of the platform is that editing websites can become a conversational experience. For example, you can say to Callimacus, “Hey, we just received the new capsule tennis collection.” Callimacus replies, “Okay, do you have pictures?” You say, “Yes, they’re here in this Dropbox folder.” Callimacus then asks, “Okay, do you have the prices?” “Yes,” you reply, “this is the spreadsheet with prices.” Once the files are uploaded, Callimacus says, “I’m ready to publish.” Then you confirm, tell it to publish, and it’s done. Since Callimacus generates the interface, it decides which content is displayed to the user. 

You can also interact with Callimacus by asking it how the collection campaign is performing in Japan, for example. Callimacus might reply, “It seems we are performing worse than last week.” In which case, you could ask it for suggestions on how to improve. It might respond, “Perhaps we could increase the frequency of displaying these collection banners in specific customer journeys?” If you agree, you simply tell it to execute that plan.

EW: What’s been the response to the new Brunello Cucinelli experience? 

FB: The initial reactions are very positive, and the metrics reflect this. We’re seeing increases in engagement rate, time spent on the website, and items added to the cart.

‍EW: Given your successes so far, what are you hoping to see next?

FB: In five years, I envision an experience that feels more like shopping in a physical boutique. I want to be able to interact with the system using voice commands and have it understand what I’m looking for, rather than forcing me to search endlessly for the right item. It should respect my privacy, personalizing the experience without relying on third-party data. The process should be quick and intelligent, recognizing that I’m either on my phone and in a hurry, needing to buy a last-minute birthday gift for my wife, or that I’m relaxing in an airport lounge and would like to learn more about the new collection, or about the hamlet of Solomeo, or do a deep dive into craftsmanship. 

We finally have the chance to go beyond decision trees and pre-defined rule-based logic, to make digital applications more intelligent and genuinely respectful of people. It’s a great chance to rethink, from the foundation up, how digital technology works and the business models we have adopted to run it.

“Design in the Age of AI” is a series of conversations with designers and makers from across industries and disciplines, building the future with AI, today.

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“We want human beings at the helm, steering the boat. However, if there are tools that can help people steering the boat make better decisions, we are ready to embrace them."

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Becoming a caregiver can happen overnight. A change in condition, an unexpected accident, a life-changing diagnosis. For many of us, it’s a job with no prep time: Someone who was once just a partner, child, sibling, son, daughter, or friend is suddenly a caregiver. It’s already happened to 63 million informal caregivers in the US. It’s also happened to both of us.  

Caregiving is incredibly complex. We know what it’s like to constantly navigate tools that fail to meet our needs, as well as the systemic issues in our healthcare system that overlook and undervalue us, while expecting us to live up to an identity we stepped into by circumstance. Our needs shift based on the conditions of those we care for, the quality of the systems we engage with, and the gaps in experience and confidence that we continue to discover. 

As designers, we’ve partnered with companies to better serve the needs of this growing population. And out in the world, we’re seeing the emergence of many new services, from AI companions with emotional intelligence (like ElliQ) to robots that assist with manual tasks (like E-BAR). As the number of caregivers continues to increase, it’s essential that we get these products, services, and experiences right. Here are five principles for designing solutions that truly meet caregivers’ needs. 

1. Design for people who did not choose this role—and were not trained for it

During our research for a recent project, a caregiver told us, “Like most people, I didn’t even think about caregiving until my father was diagnosed with cancer.” Informal caregivers are unpaid and without professional training. They have to learn as they go, performing medical tasks, navigating complex systems, and advocating for their loved ones, all without the preparation or recognition that this role deserves. 

We need to prioritize designing tools and systems that make stepping into caregiving feel less like being thrown into the deep end, and more like having a calm guide by your side. (Particularly when 40 percent of caregivers provide high-intensity care, like administering injections and managing equipment, yet only 22 percent receive any kind of training.) That includes speaking in plain language and avoiding medical jargon, designing inclusive digital tools for people who may not be tech-savvy, and using simple visuals to summarize health data and make it actionable. Ultimately, it’s about designing for reassurance, not just task completion. 

What might that look like? Something like Abbott's FreeStyle Libre continuous glucose monitors. They quickly condense a constant stream of data into just a few colors that are easy to understand at a glance: green indicates that glucose levels are within the normal range, while orange or red signals that levels are dangerously low or high.

Another good example of designing for reassurance is The Sandwich Club, a community support network for parents and caregivers where anyone can find answers to caregiving questions, big or small. Designed by The Holding Co. to be as accessible as possible, it costs only $1 a month (free for regular contributors). The club fosters an active community of peers who share their knowledge, and it includes a helpful AI that provides immediate responses and highlights insights from the community. It’s an incredible resource for questions like, “Am I doing enough for my aging parent?” to “How can I encourage a disabled person to exercise regularly?” 

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2. Healthcare tools need to be accessible to patients—and everyone involved in their care 

Healthcare systems are designed to be patient-centered. That’s a good thing, but it can have unintended consequences. When caregivers need to talk with a provider or insurer on behalf of the patient, those systems often don’t recognize the caregiver and may even restrict their access. Many caregivers have spent countless hours on the phone with a call center simply to reset a patient’s password, only to use the patient’s login instead of their own to manage care. Caregivers should be authorized partners in care by default—not mere visitors who must repeatedly prove their legitimacy. Imagine how much more seamless the experience could be if every patient portal had a “care circle” view—where designated caregivers could see what patients need, message providers, manage tasks, and coordinate—without navigating permission mazes. 

These tools could draw inspiration from location sharing. When we can’t find a friend in a crowded place, we flip on our live location feature in a messaging app, Google Maps, or a service like Life360. While it shares highly precise GPS data, you can control how long you share that data—just an hour, or forever—and with whom. The New York Times also offers a simple model for shared accounts: each user receives a personalized experience, while collaboration is encouraged. 

3. Assume caregiving is a secondary role with primary consequences 

Sixty-one percent of family caregivers also work, according to AARP and the National Alliance for Caregiving. This means caregivers often have to make important decisions while managing complex schedules, fitting care in between meetings, late at night, or early in the morning.

Designers need to create tools for users with other roles, limited time and attention, and irregular usage patterns. Caregiving tools should allow users to pause, resume, and re-enter tasks without penalty. We need to facilitate decision-making in short time frames from anywhere—on a lunch break, in a parking lot, or at the grocery store.

We can draw inspiration from TurboTax’s save-and-return feature, which allows users to pause their tax prep and pick up where they left off. This feature respects people’s busy lives, lets them move at their own pace, and reduces anxiety about making mistakes or losing their progress while tackling complex tasks. 

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4. The true cost of care transcends medical bills 

Being a caregiver can be expensive. In addition to the physical and emotional toll, caregivers spend an average of more than $7,000 per year on out-of-pocket expenses, according to the Caregiver Action Network and AARP. These costs can include home modifications, medications, and transportation. Then there are the opportunity costs for careers, and income potential: nearly a third of workers, including senior executives, report their careers have been adversely affected by their caregiving responsibilities, according to a Harvard Business School study. 

Instead of assuming cost is incidental to care, health systems need to treat it as a primary factor in the patient experience. Caregivers need tools that clearly explain potential costs—from medical expenses to time tradeoffs—as well as help navigate them more easily. 

Rocket Money’s Subscription Finder is a strikingly simple tool that makes the invisible visible. Once you link your accounts, it surfaces auto-renewing expenses that you might have forgotten about, from subscriptions to streaming services, and then helps you cancel them (sometimes a multi-step rigamarole). No more missing yet another auto-renewal deadline.

5. Caregivers are emotionally exhausted long before they are visibly overwhelmed

More than 60 percent of caregivers report symptoms of burnout, yet much of that strain remains hidden. Support should not only reduce friction but also create moments of reassurance and self-efficacy. Improving the experience of being a caregiver is a necessary part of sustaining care over time.

We need to build systems that not only track patients’ health, but also caregiver strain. Shared portals between patients and caregivers could offer tools for mental health care—meditation, counseling options, and help managing big sources of stress, like paying bills or understanding medical care. They could also include message boards where patients and caregivers could ask questions and share their experiences. 

We’re inspired by Soluna, a digital mental health platform for California youth, co-designed by IDEO and Kooth with 150 young people. Soluna integrates supportive conversations, self-reflection tools, and community connections to support users in moments when they feel vulnerable, uncertain, or overwhelmed. This approach serves as a model for caregiving tools, emphasizing the importance of treating emotional labor as essential infrastructure.

We know from personal experience how important interventions that reduce caregiver burdens are. We also know from our work in the health sector that this need will only continue to grow. By 2030, 73 million Americans will be over 65, and 70 percent of them will require care. Meanwhile, there is already a shortage of paid caregivers. More and more of us will need support to fulfill this role. And more and more of us will need designers to get it right. 

Looking back, early in our journeys, we didn’t think of ourselves as caregivers. Then things shifted. Our family members needed more support, and somewhere along the way, we realized we needed more, too. Now, with hindsight and the lens of human-centered design, we have a better sense of how health systems and care services need to improve, especially for informal caregivers. If we can do this, we believe we can improve care for everyone. Because more likely than not, we’ll all serve as caregivers one day. 

Looking to redesign your own products and services to benefit caregivers? Get in touch.

Healthcare systems are designed to be patient-centered. That’s a good thing, but it can have unintended consequences.

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I help organizations cut through complexity by shaping how they show up, through brand strategy, identity, and storytelling.

Working at the intersection of brand and business, I bring an editorial eye and a bias toward making—turning ideas into tangible experiences that people can understand, trust, and believe in.

My work spans government, healthcare, financial services, media, and consumer goods, from launching Gen Z-focused ventures to building innovation labs and reimagining legacy brands. I relish moments of ambiguity and enjoy translating across teams, perspectives, and priorities to move ideas forward.

I started my career in editorial and digital design, shaping cross-platform experiences and identity systems in publishing and agency environments. That foundation still shapes how I work today: I’m detail-oriented, collaborative, and overreliant on the Oxford comma. I hold a BFA in Visual Communication from the School of the Art Institute of Chicago.

For 25 years, I've asked the same question: Who does this design exclude—and what are we going to do about it?

My work spans human-centered strategy, inclusive design, and qualitative research, with clients ranging from Microsoft, Google, and Verizon to the National Science Foundation, and San Francisco Unified School District.

Before IDEO, I taught elementary school in East Palo Alto and spent a decade doing design work with social service organizations—where I learned firsthand what it costs people when systems are built without them in mind.

I am currently writing User Error, a nonfiction book about digital access and the design decisions behind it. I live in Oakland, California.

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My expertise spans brand, communication, and product design across tech, education, the arts, and social impact.

I believe great work demands both high-level vision and obsessive attention to detail, and only happens through collaboration.

I bring an inclusive, hands-on approach and a deep understanding of business, which enables me to consistently deliver excellence while always asking why.

Before joining IDEO, I worked at the brand firms Pentagram and VSA Partners. I began my career as a designer, leading teams at the School of the Art Institute of Chicago and the Milwaukee Art Museum. I hold an MFA in graphic design from Maryland Institute College of Art and a BFA in communication design from the Milwaukee Institute of Art & Design, and have taught at some of the best design schools in the US.

I am responsible for IDEO’s long-term success in China and working with clients to use design as a tool to enable growth. Specifically, I have helped Chinese companies design holistic brand solutions through the development of their products, communication, services, and innovation teams, and I have helped multinationals expand their presence and influence in China.

I advise global leaders on developing China-led innovation and capabilities.

In over 15 years in IDEO Shanghai, I have worked on projects that use design to elevate the quality of the experience of healthcare products and services, streamline processes that increase productivity, create spaces and programs that promote and enable inclusive communities, and build next generation mobility solutions that are planet-positive.

Before joining IDEO, I worked at Philips Electronics and the Electrolux Group in Italy, the Netherlands, and Singapore on a number of breakthrough commercial products. I am a member of the Young President Organization in Shanghai.