Master Kong (known internationally as Tingyi Holding Corporation) is number one in market share in both instant noodles and ready-to-drink teas, with over $10 billion USD in annual revenue. While China has a rich tea culture, most sugar-free bottled tea on store shelves markets itself as “healthy” and “tasty.” Wanting to set itself apart from the competition by uncovering new consumer needs, Master Kong reached out to IDEO. Together, Master Kong and IDEO immersed themselves in modern Chinese tea culture and built a new, premium, sugar-free bottled tea brand that resonates deeply with contemporary tea drinkers. ‍

During research, the combined IDEO/Master Kong team took a two-pronged approach to uncovering new opportunities: industry exploration and consumer research. The team visited various tea-related businesses, from traditional tea houses to modern beverage shops, as well as “third place” tea spaces outside of home or work. They also conducted in-depth, in-home interviews with consumers with various levels of interest in tea, delving deeply into their daily routines to better understand their lifestyles and any emotional or functional needs related to tea.

The team discovered that the essence of Chinese tea culture resonated with contemporary consumers’ longing for authenticity, simplicity, and physical rejuvenation in their fast-paced lives. This insight presented a unique opportunity for Master Kong. Instead of positioning its new sugar-free tea brand as merely a “healthy alternative” to other beverages,  it could spark a meaningful connection to tea culture, seamlessly integrating into various moments of modern life.  

Armed with this insight, IDEO designers and dozens of Master Kong beverage team members participated in a series of immersive, hands-on tea innovation workshops. Teams of experts from R&D, marketing, supply chain, and other company departments temporarily set aside their job titles to explore, iterate, and refine dozens of new tea concepts that were commercially viable, feasible for mass production, and aligned with consumer needs. The cross-departmental collaboration allowed for a broad mix of perspectives, experiences, and expertise, enriching the innovation process.

The co-creation sessions led to a new sugar-free tea product and flagship brand called Cha De Chuan Ren (“Descendants of the Tea”), which celebrates fine, origin-sourced tea and the passion and dedication of tea farmers. The novel concept resonated strongly with consumers and was validated during subsequent rounds of quantitative market testing, ensuring its relevance and market potential.

Cha De Chuan Ren launched with two signature flavors: Tieguanyin (green tea) from Fujian and Pu’er (black tea) from Yunnan. The unique mottled bottle design pays tribute to traditional handcrafted glass containers and the handiwork of tea farmers. The tactile paper label, which features Jia Ma-inspired woodblock illustrations of local tea fields and tea farmers’ hands, nods to the artisanal craft of tea making and the source of the tea inside.

“Descendants of the Tea” debuted on Tmall in April 2024. It claimed the top spot on the commerce site’s Tea Beverage V-List in August and September. Offline, it launched in FamilyMart convenience stores in May and has since expanded nationwide. The new brand received a 2024 Red Dot Award for “Brands & Communication Design.”

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“We are honored to collaborate with IDEO, a global leader in innovation, as our strategic partner. ‘Descendants of the Tea’ is not just an exceptional product but also a tribute to the rich heritage of tea culture. Only by continuously integrating culinary traditions with innovation can we sustainably meet consumers’ true needs.”

Richard Chen
‍CEO, Master Kong (Tingyi Holding Corporation)

“Innovation is incredibly fragile. If even one leader is unsupportive or hesitant, the culture of innovation can collapse. I always encourage my team to take risks, as long as they’re not high stakes. After all, what’s the worst that can happen? At the very least, we’ll have a fair chance at creating something new.”

Wei Hong-Chen
‍Chairman of Master Kong Beverage Holdings Co., Ltd.

Sugary bottled teas were once very popular in China. Today, rising consumer demand for healthier beverage options has expanded the market for sugar-free tea.

#1

on Tmall’s Tea Beverage V-List, August- September 2024

2024 Red Dot Award Winner

‍for Brands & Communication Design

Twenty years ago, carrying a single-use plastic water bottle was a status symbol—no more. Growing awareness of the negative environmental impact of plastic pollution, combined with the adoption of healthier lifestyles and social media influencer trends, has made reusable water bottles “it” accessories for on-the-go consumers. While brands such as Stanley, Yeti, S’well, and Hydro Flask own the under-$100 market, fashion brands such as Louis Vuitton, Chanel, Dior, and Prada have etched out a new and growing market for high-end bottles that appeal to discerning, trend-conscious young people looking to perfect their hydration habits.

Spotting an opportunity to disrupt the predominantly utilitarian water bottle market, Steinmann partnered closely with IDEO, tasking the team with developing an industrial design that perfected the tactile and sensory user experience, from drinking and carrying to disassembling and cleaning thoroughly. The collaboration deepened over time, with Steinmann and IDEO working together to develop the high-level engineering concept, the OKAPA logo mark, and packaging ideas.

Key user-centered features of the OKAPA bottle include a medical-grade German borosilicate glass interior for superior taste of hot or cold beverages with no lingering odors; a Swiss-engineered thermoplastic lockable and leak-proof tilt cap that can be easily operated with one hand when driving or doing other activities; and an ergonomically shaped mouthpiece for a pleasurable drinking experience. Precision-engineered for maximum longevity, the inner glass bottle is suspended via a shock-absorbing system inside a bead-blasted, extruded, and anodized aluminum outer shell. Eight modular parts come apart easily for either a quick or thorough cleaning.

At its core, the OKAPA bottle elevates an everyday ritual through meticulous design and uncompromising engineering. Launched in January 2025, the new bottles are available in eight contemporary colorways curated by renowned color and materials specialist Beatrice Santiccioli (BSD), including Misti Pinku, Goldie Samba, and Fetishe Noir, among others.

In the US, the reusable water bottle market is estimated to increase from $10.2B in 2024 to $14.1B by 2031, with 69 percent of Gen Zers owning at least one. Customization trends, such as personalized design and branding, are anticipated to boost the market, ripe territory for disruptive startups such as OKAPA. (Persistence Market Research)

Once a practical accessory for hikers and outdoor enthusiasts, reusable water bottles have gone mainstream. Yet none check all the boxes in terms of purity of taste, hygiene, durability, functionality, and beauty.

8

modular pieces ensure hygienic cleaning is quick and easy

100%

recyclable materials in each bottle

The Cornell Lab of Ornithology’s mission is to interpret and conserve the earth’s biological diversity through research, education, and citizen science. Over its 110-plus-year history, its offerings grew to include everything from a quarterly magazine, popular websites and apps with millions of users (Merlin, eBird), partnerships with outside organizations, and the world’s largest database of photographs and audio recordings of birds. This abundance is a testament to the passionate enthusiasm of its employees. Still, it confused potential members and led to siloed internal efforts, preventing the Lab from advancing its urgent collective vision. “Birds and biodiversity are in peril,” said Executive Director Dr. Ian Owens. “We must take radical action with a coherent vision, united voice, and purpose.”

IDEO began by helping the Lab better define its audience. While primarily composed of people passionate about birds, IDEO discovered its larger audience was nature lovers interested in biodiversity, bioacoustics, conservation, and science. From there, IDEO created a brand strategy and architecture focused on helping the Lab streamline its efforts under the “One Lab” brand. The brand architecture visually articulated the relationship between Cornell University, the Cornell Lab of Ornithology, and the Lab’s many products and offerings. IDEO designed a comprehensive brand identity system to work across mediums, including a simplified logo system, new colors, type, graphic language, voice and tone, and key messaging.

When the Lab’s design team began implementing the new branding elements across its website and many digital products, it became clear that the organization also needed IDEO’s help in creating tools to facilitate cross-department collaboration. To better understand the day-to-day nuances of the organization, IDEO designers worked out of the Lab, co-creating a brand activation playbook. The playbook, launched in 2023, contains recommendations for new cross-functional working groups (partnerships, visual identity, and brand voice), as well as exercises and interactive tools designed to build trusting relationships, gain alignment, foster collaboration, and manage change at scale.

Post-collaboration, the Lab has applied the new brand across its website, apps including Merlin and eBird, Living Bird magazine, email and newsletter templates, and its line of merchandise. A new internal brand guidelines site has become central to employee onboarding, while new working groups are helping to bring down barriers between teams and spur collective action. Like a flock of birds, the Lab now sings one collective song.

The Cornell Lab’s 300+ scientists, professors, staff, and students were passionately dedicated to their individual team’s unique conservation projects, but segmented internal systems could stymie their collective impact.

1 brand

unifying 300+ employees and 8 departments

Founded in 2008, Ascend Public Charter Network prides itself on providing “rich, joyful learning experiences that unlock lives of boundless choice” for its students, 93 percent of whom identify as Black or Latinx. The organization is also proud of being Black-led: 78 percent of staff and 80 percent of the executive team are people of color. Using co-design and joy, IDEO held a mirror up to Ascend’s core optimistic spirit during a moment of anxiety and change, helping its new CEO, staff, students, and parents reflect a dynamic, collectively imagined vision.

While the project’s goal was serious, the combined team centered the collaboration on bringing back fun, beauty, and imagination to those who could use it most: educators. Through engaging interactive activities, the IDEO team invited principals, PTA members, student council representatives, and board members to join “organizationally sanctioned play” moments like creating collaged vision boards and writing poems about Ascend’s impact. These interventions helped burned-out educators escape the day-to-day tasks of running schools and dream expansively about Ascend’s future. The team also solicited written, visual, and audio stories, asking community members to describe Ascend at its very best.

Stitching together submissions from 551 students, 75 parents, and 16 staff members, the co-design sessions resulted in a powerful new purpose, mission, and values, as well as a vibrant visual language and activation tools to bring Ascend’s vision of a “dope,” “unapologetically Brooklyn” charter network to life. The joyful, eye-catching visuals are embedded throughout its 17 Brooklyn schools, staff recruiting and training materials, and digital presence.

Shortly after the collaboration with IDEO, Ascend received an unsolicited  $11 million donation from MacKenzie Scott's foundation, Yield Giving, the most significant gift the then-14-year-old institution had ever received. The pivotal funding will allow the organization, with its bold new “grown-up” vision, to focus on becoming the school of choice in Brooklyn by 2027.

In the summer of 2021, one in four K-12 teachers was ready to quit. Pandemic stressors and increased curriculum scrutiny were to blame, according to a 2021 Rand Survey.

In 2022, 44% of K-12 workers reported burnout, the most of any US professions the time, according to a Gallup Poll.

Pandemic exhaustion and leadership turnover left Ascend’s new CEO eager to align staff around an exciting new vision.

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$11M grant

Ascend received an $11M grant from the MacKenzie Scott Foundation a few months after the collaboration

1 collective vision

to guide a network of 17 schools

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What will it mean when an algorithm can handle 90 percent of your job? What will working with dozens of agents be like?  When anyone can build enterprise tools—instantaneously? 

That future has already arrived at the major AI labs—and faster than almost everyone expected, even Anthropic. Founded in 2021 by a group of researchers who set out to build AI that is safe and useful, it’s now used by millions and was valued at $965 billion in its most recent funding round.

The company operates on the assumption that AI capabilities will keep improving quickly—and that its own internal ways of working have to keep pace. That means fomenting and accepting exponential change. Speaking to Joel Lewenstein, Anthropic’s refreshingly honest head of product design, provides a visceral sense of what the future we’re all heading toward feels like—both exhilarating and, occasionally, overwhelming. 

I spoke with Lewenstein about why protecting our thinking matters more than ever, why his team members don’t feel AI is atrophying their craft skills, and why enterprise collaboration is the next frontier for research and product.

Ed White (EW): Do you remember a moment when you first realized AI’s true potential?

Joel Lewenstein (JL):  My wife is an appellate lawyer. It was around 2023, and she was trying to explain this extremely dense legal case to me. After three tries, I still didn’t understand it. So one night, while she was asleep, I pulled out my phone and asked a gen AI to explain the case. It got two-thirds right, but then it started hallucinating, providing incorrect but insistently confident information. I remember having this conspiracy theorist-like out-of-body experience. I felt so alive because I’m learning this deep thing, and I felt so scared and confused because I’m being lied to, but it was insistent. I remember thinking that there’s so much good here, along with confusion and complexity that would be interesting to work on. 

The second moment was hearing Dario [Amodei, CEO of Anthropic] on the Dwarkesh Podcast. This was also in 2023. Dwarkesh asked him: “If we reach AGI [artificial general intelligence] and it cures cancer, should it be governed by a company, the US government, or the international government?” I thought it was a crazy premise. But Dario launched into a deep reflection on governance, ethics, and international order. I realized these people fully believed in the goodness of AI. That made me very excited.  

EW: What’s your role at Anthropic?

JL: I lead the product design, user research, and content design teams. There are about 30 folks, and we basically put a product designer, a user researcher, and a content designer on our platform API business (Claude Code, Cowork), our consumer apps, and our enterprise and growth areas. Our designers are deeply embedded and trying to figure out what the hell this role is in 2026. 

EW: Having come from more classic product design roles at organizations like Airtable and Quora, how is this experience different?

JL: The most interesting dimension here is speed. You hear this constantly, right? But the weird part is the time compression. There’s a measure-twice-cut-once quality to the work. You do a lot more preparation, thinking, and consideration before you build because the time to build is so short. The question is: How do we keep up in an environment where everyone’s shipping all the time?  

We also build a ton of internal tools. Our content design team created a GitHub agent that monitors strings sent to production. It checks for adherence to our content guidelines and opens PRs [pull requests] for any that don’t comply. That’s crazy because this used to be 50 percent of the job. Now it’s just 5 percent, allowing us to focus on other things. All of our designers are writing code.  

EW: Where does the design or craft bit fit in, then?

JL: With design, there are three steps to the process. Step one: determining what we should build, why we’re building it, and what problem we’re solving. Step two: creating user flows and ensuring the basic components are in place. Step three: crafting the last mile of delight, those little details that many people may not notice, but subtly make a difference. Step two is now gone. We just prompt Claude, and it just does it. Step one—deciding whether we should build something, why we should do it, and where it leads—is still a very human and messy process. As for the last step of getting all of those little interactions and visual details right, our designers are still better than the models. Maybe that won’t be the case forever, but for now, it is.  

EW: Tim Brown, IDEO’s former CEO, co-authored an article about this recently titled “The AI dividend.” Now that AI has reduced a task that used to take 50 percent of your time to 5 percent, what do you feel it’s allowing you to do?  

JL: I would love to tell you that all the boring tasks have been automated, allowing the designers to sit at whiteboards thinking bigger, more ambitious thoughts. But our Slack and GitHub are flooded with PRs from dozens of engineers. We’re juggling 17 different Claude Code instances, and each one is pinging, “I’m done! Can you review this?” It’s a cacophony of tiny projects. It’s similar to the attention-economy notification overload we experienced in our personal and social media lives. Now, it feels the same way in our work life. We’re fighting harder than ever for half a day or a day to just think, dream, and explore.  

EW: Do you think the pendulum will eventually swing back? 

JL: It has to because the human condition will require it. I think two things will happen. First, we haven’t invented an interface for managing hundreds or thousands of Claude instances.  There’s still an unsolved UX problem. The best analogy is the American presidency. There are hundreds, thousands, or even millions of staffers running around making big and small decisions, producing piles of status updates. A human chief of staff manages all that. Eventually, we’ll need a digital equivalent who will serve up a concise summary from a few of your SVPs [senior vice presidents] on Monday morning—agents who have dealt with 10,000 individual contributors—so that you don’t have to think about each task.

EW: How else are you seeing designers’ roles change?  

JL: Being close to the code and adopting a code-first, prototype-first mindset is really central. We’re not too precious about our work. If something has a decent UX, we put it out there in a beta and collect feedback. 

As someone who has always worked in the digital space, I think about how creative professionals in the past, like musicians, operated: once an album was finished and the record was pressed, that was it. I could never have worked that way creatively. Back when I started, in the Ruby on Rails era, we could simply deploy again next week and fix any issues. But for AI native folks, if something goes wrong on a Tuesday night, they just submit a PR on Wednesday morning to fix it. Everything is malleable and adaptable all the time.

This lack of preciousness, the idea that “done and shipped” is better than “perfect,” is crucial. Of course, there are challenges. Sometimes the coded output doesn’t look great, but we accept we’re going to learn from this vibe-coded thing and get on with it. We refer to this approach as “intentional craft,” meaning that if we need to make this outstanding, we still have the chops to do it, but we also need the discipline and the judgment to recognize when it’s appropriate to let a rough version go out.

User expectations are changing fast. During the heart of the mobile app era, people had incredibly high bars for their experience. We’re no longer in that era. When we put out these vibe-coded, early experimental things, we get feedback like, “Guys, this broke three times, and this button is called three different things.” But they also say, “I love it. Please make it better, and I'll keep using it.” We’re in a part of the S-curve where users have a lot of tolerance for jank. Eventually, this field will mature.  

EW: How do you maintain your craft in a world where models can perform many design tasks?

JL: Collaboration with these models is not a replacement story. You get better as a writer, editor, and thinker with a creative partner who pushes you, asks questions, and explores alternative theories. There’s a nice sparring partner quality to collaborating with AI that I appreciate.  

The models aren’t doing anything better than a thoughtful designer can with enough time. In a head-to-head competition between Claude and an outstanding designer, the designer still wins most of the time. I don’t hear our designers being concerned about skill atrophy. They’re worried about not having the time and mental space to practice the skills they already have and care about.   

EW: That’s very heartening to hear, to be honest. With so many options of what to build and many more people who can do many more things, how do you find a sense of direction? Do you and Mike [Krieger, co-lead of Anthropic Labs] share an ethos on product development?

JL: We’re letting the model lead the way. For example, in the pre-AI era, a product like Claude Design would have emerged through a TAM [total addressable market] analysis: evaluating our position as market leaders in coding, identifying adjacent spaces, interviewing stakeholders, spinning up a team, and committing to a 6- to 18-month timeline. 

In reality, the complete opposite unfolded. People using Claude Code were organically making UIs [user interfaces]. One of our designers noticed that these URIs [uniform resource identifiers] were pretty good and wrote a skill to coax the models into producing even better front-end designs, specifically using our design system. He realized it was useful and spoke with our researchers, who confirmed it wasn’t a fluke. He then refined the skill into a standalone app. That’s the genesis of Claude Design. We felt comfortable launching it at a research preview because we believe the models will continue to advance. 

EW: That’s interesting because organizations don’t generally use what I’m going to call “academic research” as a way of thinking about how products come about. 

JL: It’s crazy because at any other place that I worked, nothing changes on a product unless you assign an engineering team to change it. If your product engineers all went on vacation, no features would launch. But at Anthropic, if our product team went on vacation, the models would just keep improving.

EW: What’s it like working alongside agents daily, and how does it impact the organization?

JL: Everyone at Anthropic has dozens of Claude Code agents running in the background. We recently worked on a navigation IA [information architecture] refresh. Anyone who’s done a navigation redesign knows there are a million questions in the kickoff meeting: Are people really using this tab? Are the users of this tab and this tab the same, etc. In my old-school, pre-AI brain, I’m like, “We’ll need a week to explore, a follow-up meeting, and then we’ll come back with all these questions.” But in the meeting, the designers are just tap, tap, tapping on their Claude Code agents, asking, “Will you look at our internal documents, Slack, and our data to figure out how many people click on this tab?” And 45 seconds later, someone chimes in, “Hey, it turns out that tab is still used a lot.” It’s like everybody has a team of research assistants behind them, finding answers for them in real time. 

EW: What’s inspiring you right now? 

JL: I’m curious what the next three to five years hold for the unit of computing. We learned how to use websites, then apps, and now chatbots. What will be the next unit, and will it be vibe-coded or developed by individuals, corporations, or models that generate it in real time?

EW: Looking ahead, what’s most exciting to you and your team?

JL: We’re thinking a lot about teams and team productivity. Claude is amazing in single-player mode. But while we’ve become more productive individually, the collaborative aspect of work hasn’t changed dramatically. Right now, we have a World Cup collection of individual superstars producing amazing things, but their collective chemistry remains unmediated by AI. But then again, you and I are speaking right now completely unmediated by AI, and that’s also beautiful.  

EW: What advice would you give designers? What should they be doing and thinking about?  

JL: When users have a problem, our instinct as designers is to create a new feature—design the rectangles and the flows—and let AI build it. We’ve started to invert that approach. If users have a problem, we ask, “Can Claude solve it on its own with prompting?” Then, if it can’t or needs additional structure, we add a feature or product architecture. 

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“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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“Being close to the code and adopting a code-first, prototype-first mindset is really central.”

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Travel is fundamentally a human experience, and personalization has always been the ideal: the concierge who remembers your name, the host who anticipates your needs, the perfect room tailored to your preferences. 

But true personalization has traditionally been a luxury, reserved for those with wealth and elite status. Even as technology has enabled mass travel and big data and CRM systems have laid the foundation for personalization, brands have struggled to scale hyperpersonalization to everyone. Loyalty programs have become the industry’s best attempt at bridging this gap: Points and tiers quantify who deserves what, with status serving as a proxy for real relationships and customer understanding. 

Until now. With the introduction of AI agents, hyperpersonalization can scale from the segment level to the individual traveler. Done right, it has the potential to democratize what was once a luxury good: the experience of being recognized. 

Of course, serendipity and delight remain a huge part of the travel experience: unsolicited dinner recommendations from local shopkeepers, wrong turns that lead to hidden gems, and conversations with strangers that become core memories. Our research shows that, especially for Gen Z customers, agency and spontaneity play a big part in shaping their tastes and identities. The opportunity is for AI to know travelers well enough to make their experience feel personal—but also to know when to get out of their way.

Capturing this opportunity means redesigning loyalty so that rewards are legible to agents, personalization scales to the individual, and the system delivers an ecosystem of value matched to what each traveler actually cares about. In doing so, brands can finally deliver the kind of personalization that has always been the industry’s ideal.

The dual audiences challenge

Every travel brand is now designing for two distinct audiences. The first is the person who is comfortably waking up in their hotel bed, enjoying the aroma of morning coffee from the lobby brunch, or grabbing a beer with their new Scottish best friend by Fenway Park. The other is an AI agent that’s handling the searching, comparing, and booking tasks on that person’s behalf. 

These two audiences have different priorities, attention spans, and methods for evaluating information. Hyper-optimize a webpage for one audience, and you may inadvertently block traffic coming from the other.

It’s tempting to treat these dual audiences as a marketing problem—a matter of making pages readable to agents without alienating people. And that is part of it. Stripe has already built a wallet for agents, and AI coworkers are beginning to handle multi-step bookings. But the consumer trust gap is wider than the technology gap. The travel industry has not gathered enough data to determine whether travelers will allow an agent to optimize their preferences about brand, travel occasion, or loyalty points.

As brands strive to cater to both audiences, agents in the funnel are revealing three outdated assumptions baked into the way most travel and hospitality loyalty programs operate. First: transactions are the best measure of loyalty. Second: personalization doesn’t scale. Third: points are the primary reward. Once these assumptions are challenged, a different kind of reward emerges: the reward of travel itself. In the age of AI, loyalty programs should be designed with enough emotional intelligence to preserve the romance of travel while harnessing the superpowers of machine intelligence. 

False assumption 1: Transactions are the best measure of loyalty

When American Airlines launched its AAdvantage program in 1981, it introduced the first large-scale frequent-flyer program by mining its reservation system for recurring phone numbers. This marked the first time the airline could identify returning customers and begin building direct relationships with them rather than with their travel agents. The airline built the program on the data it had at the time: transactions. Forty-five years later, most loyalty programs still follow a similar structure—offering points for spending, tiers for hotel nights, and miles for distance traveled. 

This transactional dynamic is increasingly ineffective. The average American belongs to 17.4 loyalty programs, but actively engages in fewer than half. Many brands claim loyalty membership sizes that rival the entire adult population of the United States. These transactions may look like loyalty, but are they really?

The next generation of travelers will have an agent doing the work that only the most dedicated points gurus do today: discerning what each traveler finds valuable and surfacing the options that match. Imagine a Gold-tier member with a brutal travel schedule who is looking for a hotel close to tourist attractions. In a regular search, they filter by price, reviews, and location. An agent can do that, plus spot the perks that actually matter at six in the morning after a red-eye: early check-in and a quiet room away from the elevators. 

Now, the measure of loyalty broadens beyond the transactional into the experiential and emotional utility of being seen and cared for. Agents simultaneously reveal which programs offer real value and match them to what each traveler values for each and every trip. 

False assumption 2: Personalization doesn't scale

Top loyalty programs like Amazon Prime offer around 30 distinct benefits. They range from free next-day shipping to cash-back options and streaming media subscriptions. Brands surface long lists of these perks because they can’t possibly know which one will land with a given member. The list is often a coping mechanism for the brand’s inability to fully personalize and the consumer’s inability to remember everything the brand offers.

Marketers often use robust quantitative surveys, such as conjoint analyses, to gain insight into consumer preferences. Run enough permutations with enough travelers, and you can statistically estimate which combination of benefits they value most. Marketing teams still debate granular tactics, like the order of perks to list in an email. But those debates are entirely unnecessary when agents can just choose based on the traveler’s preferences.

Consider the scale this can reach. Expedia Group alone encompasses more than 3.5 million lodging and vacation rental properties. One can imagine that in the near future, by analyzing a traveler’s bookings and reviews across this vast selection, an agent can ensure that a guest’s preferences are prioritized for every booking, regardless of who operates the property.

Personalization scales when agents do the matching. The new design challenge is enabling agents to interpret hundreds of personal preference variations and reward ecosystems, making offerings sufficiently readable for an agent to match and communicate well on the consumer’s behalf.

False assumption 3: The points are the reward

Ask anyone who has been a road warrior what real loyalty feels like, and the answer is rarely the points. It’s often Shirley at the front desk, who remembers you like a higher floor, a firm pillow, and a bigger room rather than a view. The recognition itself was the reward, a relationship rather than a transaction. But for too long, it was too expensive to offer to anyone beyond elite travelers. 

Now, the behaviors that used to earn that recognition are fading just as technology is emerging to recognize customers without them. Today’s consumers are less loyal and less inclined to align themselves with a specific loyalty program or brand because they value choice, flexibility, simplicity, and convenience. The number of people who used to go on mileage status runs in December just to hit status is decreasing. Instead, they’re seeking something more, and brands are increasingly able to provide it, thanks to advancements in AI.

Expedia’s recent partnership with CLEAR offers a glimpse into the future of travel loyalty: It is evolving from individual brand perks to an integrated ecosystem of complementary benefits that enhance each step of the journey (think: Apple ecosystem logic, but applied to travel). For example, CLEAR offers Expedia members discounted memberships to CLEAR+ lanes and access to its Concierge services, providing VIP treatment as they head to their next destination. What stitches the ecosystem together is the underlying agent layer. It reads each traveler’s  preferences across the partner brands and surfaces the right benefit at the right moment, without the traveler having to coordinate it themselves. No longer just a perk for road warriors, recognition becomes an experience any traveler can enjoy at every stage of their journey.

The opportunity to make travel more human

People often talk about compound interest when it comes to money. You invest a small amount, it grows over time—that’s the magic of compound interest. But we believe the memories, stories, and friendships formed through travel compound even harder. Years later, a distinctive smell, a friend, a menu item—whatever—can magically transport you back to that travel moment. 

Loyalty has never really been about earning points. It’s about the memories of being cared for while away from home, discovering something new and unexpected, and feeling seen and recognized. It’s about the desire to return because those memories capture the joy of travel.

Nights, miles, and dollars are the receipts for a trip. They are not what the trip leaves behind, which is more sensorial and more personal than anything a tier structure has ever captured. The next era of travel loyalty will be about making travel more human, powered by the combined strengths of machine intelligence and emotional intelligence.

“In the age of AI, loyalty programs should be designed with enough emotional intelligence to preserve the romance of travel while harnessing the superpowers of machine intelligence."

I’ve never been a big fan of medical dramas, but I couldn’t stop watching The Pitt, the HBO Max show about a fictional Pittsburgh ER at a public teaching hospital. The high-stakes medical cases, relentless pace, and scrappy, sleep-deprived team you can’t help but root for had millions of viewers counting down to Thursday nights earlier this year. But for me, it was about watching the work itself. 

Apparently, I’m not alone. The Washington Post called the Emmy-winning show “perhaps the purest example of ‘competency porn’ on TV”—a term that surged into the cultural vocabulary this year to name the satisfaction of watching people who are really, really good at their jobs. 

But what they’re really good at goes beyond the practice of medicine. They excel at teaching and learning on the job. They think out loud, trust learners with calls that matter, and dissect what just happened before moving on to what’s next. I find it inspiring to watch.

Here are three lessons on teaching and learning in the workplace that we can take from The Pitt, and ways to activate them in your own work. 

Make mastery observable

Every scene on The Pitt has two things going on: someone doing the work, and someone learning to do the work. A recent nursing school grad shadows as the charge nurse guides a survivor through a rape kit exam—every choice a lesson in how to move at the patient’s pace. A resident observes as the attending decides out loud whether a procedure is worth trying if it might cost their patient her sight. A specialist performs an emergency procedure the attending has never seen before, teaching the room as she does it. Watching people at the top of their game work out a problem from beginning to end—including the messy middle, not just the outcome—is a sight to behold.

Most of us don’t work in a teaching hospital, but “see one, do one, teach one”—the century-old learning model attributed to Johns Hopkins co-founder and surgeon William Stewart Halsted—is how most of us pick up a craft, medical or otherwise. But that kind of learning is harder to come by these days. For years, most knowledge work has been evolving to a less readily observable state. Increased remote work makes it challenging to know what other people are working on, receive mentorship, get feedback from peers, or signal when you need help. The explosion of single-player AI tools has increased output, but made the thinking that informed it harder to see and, some research suggests, to trust. 

When my San Francisco colleague Thomas Overthun worked at Philips early in his career, he would pass by hundreds of drawing boards on his way out of the studio, displaying an amazing range of work in progress. Our workplaces look very different now, but it’s entirely possible to design tools, rituals, and ways of working that can help us see and get inspired by one another’s in-process work.

Here are a few practices that are helping us tilt our work toward each other:

• Use video shares: Kaii Tu in our Shanghai studio records short Loom videos to walk his team through the design choices he made—and why. The format forces him to make his reasoning legible, and makes it possible to share across time zones.
• Host “Screen Share Fridays”: On Fridays at our Cambridge studio, the studio-wide Slack channel explodes with screenshots of work in progress, sketches, project Post-it Notes, photography from the field, and presentation decks. Questions naturally follow, which then leads to dialogue about the work.
• Think in public: My Chicago colleague Leah Marcus builds incredible FigJam boards at the start of each project with relevant research, inspiration, and connections she’s making across our digital product portfolio. She uses plain language, bringing others who don’t share her business design discipline into her thinking.

Let the learner try

The best teachers I’ve observed share one hard-earned skill: they show restraint, letting learners grapple and find their feet with just the right amount of support. In The Pitt, when a new patient arrives in critical condition, the attending physician, Dr. Robby, turns to a resident and asks, “What’s your plan?” He doesn’t jump in, even when the clock is ticking. As a viewer, you feel the pressure that the resident is under and wonder, “Is he trusting a beginner with too much?” Turns out, this is an important part of the learning process.

This is the “do one” part of Halsted’s model, and it’s harder than it sounds. We know from decades of research that learning happens when we reach the edges of what we know how to do, and it happens even faster with scaffolding: a gradual release of responsibility from teacher to student. Instead of just telling residents to do the procedure on their own, Dr. Robby asks them questions, nudges them to consider alternatives, and fills in information they miss if it will have consequences for the patient. He lets them try first, then steps in when they get stuck. The scaffolding makes the risk survivable but not invisible. 

As a firstborn, Virgo, recovering perfectionist, I’ll be the first to admit that it is hard to use suggesting mode when you can just use editing mode. But the shortcut has real implications for my colleagues and the work. While I may get a cleaner draft, we both skip the interesting part that could help someone else grow, and probably get the draft to a better place than I could alone.

How might we demonstrate restraint and let learners try?

• Provide feedback in the margins: Suggest, don’t edit. Offer comments over rewrites. The extra friction is the point—it forces a conversation about the choice you would have made, instead of making it.
• Design it now: My colleague Bri Patawaran in our San Francisco studio is a huge fan of design-it-now moments to get a team out of swirl and uplift viewpoints that haven’t been heard. She asks, “What would you do if you had to deliver this today?” Everyone goes heads-down and then presents.
• Ask, don’t answer: When your team is stuck or a direct report brings you a challenge, resist the urge to solve it. Ask, “What's your first take?” and stay in question-asking mode as long as you can to help them explore their own thinking, giving you a chance to see their problem-solving skills in the process. 

Tell the story

The story we tell about what just happened is how we absorb what we’ve learned. On The Pitt, residents present each case to the attending after their patient is discharged. They walk through what the patient came in with, the diagnoses they considered and ruled out, the call they made, and the result. It’s a small ritual with an outsized effect—the resident consolidates what they learned by teaching it, and everyone within earshot learns alongside them. 

Reflection doesn’t have to be formal. Christopher Myers, a researcher at Johns Hopkins, studied medical transport teams—paramedics and nurses who fly in helicopters to accident scenes and rush patients back to the hospital. On any given day, they have no idea what they’ll encounter, and no single person can accumulate enough experience to be ready for all of it. What Myers found is that the crews built shared expertise through vicarious learning: telling each other stories, informally, between calls. These stories—casual, unscheduled, and recounted in whatever time they had—were how the whole team became more prepared together.

There are plenty of ways to build reflection into your work. The harder—and more interesting—work is building it into your culture. 

Here are a few practices we use across IDEO to encourage reflective storytelling.

• Ask “What are you working on?” The deceptively simple five-word question is a reflective invitation dressed up as small talk. Ask it in hallways, on Slack, at the start of one-on-ones. Half the time people just answer. The other half, they tell you something they didn’t realize they’d learned.
• Never skip a retro: It’s easy to nix a project post-mortem when you’re running short of time. But “I liked…,” “I learned…,” “I lacked…,” and “I longed for…,” is an easy and effective feedback framework to prompt everyone to share their ah-has and takeaways from the work. 
• Host a “Wrap Party”: Once a month, we host a virtual IDEO-wide “Wrap Party” where teams share three behind-the-scenes stories about recently completed work, giving everyone an opportunity to learn and get inspired together.

At one point while watching The Pitt, I said to my husband, “Wow, if I’d seen this when I was younger, I might have wanted to become a doctor.” (He gently reminded me that I have to avert my eyes every time I see blood.) Though what we see on screen may seem aspirational, none of the lessons The Pitt shares about teaching and learning on the job is exclusive to an emergency room. Observability, restraint, and storytelling are choices—small ones, mostly—that we can put into practice every day wherever we work. None of them require a shift change.

Curious about how to improve ways of working at your organization? Get in touch.

“The best teachers I’ve observed share one hard-earned skill: they show restraint, letting learners grapple and find their feet with just the right amount of support.”

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Imagine an engine that generates alternative endings for stories, a 2x2 visual tool for choosing which films to watch,  or a digital game of telephone that transforms a poem into something altogether different, like a location on a map. For Khyati Trehan, a Design Lead at Google Creative Lab, these are the weird, improbable, delightful explorations that AI is catalyzing.

Trehan’s lifelong curiosity for making began at Mirambika, a progressive school in New Delhi, the city where she was born and raised. “When you give children complete freedom, they choose to learn,” she says. That love of learning took her from the National Institute of Design to a globetrotting creative career spanning interning at a type foundry, creating AR experiences for Snapchat Spectacles and Instagram, producing 3D editorial illustrations for The New Yorker, The New York Times, and WIRED, working as a communication designer at IDEO’s former Munich studio, and “one crazy Oscars’ project the year of Will Smith and Chris Rock.” 

She’s now at Google Creative Lab in New York, working on projects that “humanize complex technology and remind people why they love Google.” She collaborates with a diverse team of designers, writers, and technologists, united by a desire for creative freedom and a novel approach to problem-solving.

‍I spoke to Trehan recently about how AI enhances her creativity, her evolving mindset as a designer who embraces coding, and the importance of fostering play and experimentation in organizations to promote AI adoption.

‍Ed White (EW): Do you remember when you first started using AI?‍

Khyati Trehan (KT): I got early access to DALL-E before it launched in 2021. Ironically, I remember liking the blurry loading states more than the final images. The results never quite stuck because nothing that came from my prompts felt like…me. There wasn’t much control over the output. I was looking for tools that would feed my creative process, and “one-shot AI”  didn’t do it for me.

An interest in using LLMs to turn natural language into software code happened more recently. My friend Pedro Sanches, a brilliant creative technologist, designer, and Creative Lab alumnus, came over for tea and shared some sketches he’d made using what he called “coding sans coding.” (This was before “vibe coding” was a term.) I was much more excited by that approach because it felt like something I could incorporate into my practice by building tools to help me explore new places without them feeling completely unfamiliar.

Those early experiments provided initial insights into my personal philosophy on how and when I use AI. My goal has never been to rely on AI to do all the work; instead, it’s about exploring how AI can help me supercharge and advance existing ideas.

EW: How is AI changing your team and Google as an organization?

KT: As the boundaries around our disciplines blur, the number of hybrid creatives is growing. Writers are making films, graphic designers are building writing tools, animators are engaging in creative coding, and developers are designing interfaces. There’s still a distinct difference between the vision and “flavor” of what I might design and develop as a graphic designer and what a creative technologist might create using the new capabilities that AI unlocks for both of us. Our individual experiences, values, core strengths, skills, and knowledge still define what makes us unique, even when we have the same tools at our disposal. 

EW: What are the things you and your team are learning, as designers, about using this technology?

KT: I think we’re realizing that regardless of how you look at the creative process, the shape of it remains the same. We still start by playing and experimenting to explore the edges of technology. We engineer every aspect of the applications we create, ensuring that we consider people’s needs. In fact, we now spend even more time and energy focusing on what matters to people and asking ourselves: “When we can make anything, what do we choose to make?”

While engineers are trained to focus on efficiency and optimization—and form the backbone of Google—creatives, when given the opportunity to lead research and gain early insights, instinctively seek out emotion and play. We naturally discover the right metaphors and interfaces that make complex systems clear.

EW: What’s worrying you about AI and design, and why?

KT: With every big shift, it’s wise to be cautiously optimistic. I often reflect on how we studied design in school: manually painting a color wheel and using our judgment to create the right shade of orange that would sit between red and yellow, even when the Blend Tool existed in Illustrator. Putting time and effort into these exercises sharpened our skills and helped us develop a strong foundation, which remains useful regardless of the tools we use. We shouldn’t forget that. You can use AI as a crutch, or you can use it to unlock or supercharge your existing skills, expertise, and ideas. To me, that’s the distinction between an effective use of AI and slop.

EW: What are the really concrete ways AI has changed your craft as a designer at Google? 

KT: The tools you use change the way you think. When I was learning 3D modeling and texturing years ago, it quite literally unlocked a new dimension in my graphic design practice. I’d surprise myself with the ideas that came to me and what I was capable of with this new ability.

This holds true for using AI. I’ve added surfaces like Gemini Canvas, AI Studio, and Flow to my toolkit to choreograph Google’s models and APIs. Mindset-wise, it’s made a lot of us hybrids. Now that we can build things, I find that in meetings, designers show more often than they tell.

I still design using traditional tools, except now, once I translate the visual and the flow into a clickable prototype, I can iterate in the same environment, and the work becomes more lived-in. 

EW: How has that changed you as a creative, and why?

KT: It’s definitely a leap. It’s like the difference between learning about qualitative interviews versus being in the room yourself. You can understand both objectively, but with the latter, you feel more connected to the learnings. For example, I’ve designed loading states plenty of times, but now that I’m closer to the front end, I’m bringing so much more of my design flavor and delight to them. I feel more comfortable taking risks and taking departures from what’s deemed standard in the space. 

EW: What’s an example of that?

KT: I’ve been designing digital experiences for very personal, everyday, specific, and idiosyncratic needs. For example, I got my hands on Ted Chiang’s Exhalation, a collection of short stories, and fell in love with them. I’ve been inventing alternate endings for some of them and extending his beautiful worldbuilding.

This led to the creation of Story Arc Engine, a narrative-building tool that allows users to deconstruct stories using a five-part narrative arc. By tweaking one part of the arc, users can see how a change in the plot affects the rest of the story and generate new narratives based on their own plot ideas.

EW: How else does AI change what you’re designing? 

KT: Because I’m now building both the final output and the intermediary tools that help me get there, I share both: the final product and the tool I vibe-coded to create it. This means that others can use the tools I make, often in unexpected ways. For example, someone once used Story Arc Engine to draft their next career move, hiding a sabbatical in the narrative. 

EW: What other examples of these types of projects have you been working on?

KT: I’ve recently made several tools for myself. Around the World in Good News is a digital newspaper that explores uplifting historical events and stories of human achievement from across the globe and throughout time. Another project, 2x2 Anything, emerged from my desire to make more informed decisions for movie night. It's a concept-mapping experiment where you define two conceptual axes, set the context, and click anywhere on the coordinate map to generate a fitting concept or summon an existing result. My most recent sketch, Machine Telephone, is a playful game in which you enter an input, pass it sequentially through different media and models, and observe how context shifts, translates, or gets misunderstood over time. For example, you might see a poem translated to a specific location on the map or a song transformed into a spherical material. Now that mediums feel less siloed, and those that remain siloed are easier to learn about, my first instinct is no longer to dismiss an idea just because it initially seems unfeasible.

EW: What advice would you give leaders who want their orgs to use AI effectively?

KT: An urgent tone from execs and leadership, coupled with a top-down mandate and a lack of concrete guidance, isn’t helpful. It only leads to confusion and stress, and, ironically, slows down the actual work

Instead, explicitly give people permission to play. Play is a powerful tool, especially when you’re faced with ambiguity. Give people access to a variety of tools and functions, and offer learning resources. Let people stumble upon new paths, and figure out which tedious parts of their process AI can take off their plates. 

EW: How do you think AI will transform your industry over the next five years?

KT: AI is already transforming industries by narrowing the gap between different disciplines. When the mechanics of creation are no longer a bottleneck, and the effort it takes to make things decreases, where does our time and attention go? It comes down to the core of why we create: our taste, the sum total of our experiences, our irrationality, our perspective, and our vision. Maybe we’ll just learn more about what makes us uniquely human along the way.

“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.

“My goal has never been to rely on AI to do all the work; instead, it’s about exploring how AI can help me supercharge and advance existing ideas."

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.