Looking to understand the role of instant noodles in middle-class Chinese life, the IDEO team conducted in-home research with consumers across a range of life stages and levels of attachment to noodle culture and convenience foods. The first finding was reassuring: Everyone kept instant noodles at home. The category still had a place in middle-class kitchens. But beneath that was a more complicated, emotional story—and an unmet need for convenience and quality to coexist in a single product.

The team discovered that instant noodles are more than just a quick, on-the-go meal; they are a nostalgic comfort food that evokes fond memories. But since their heyday, their role in daily life has evolved. Once a complete meal in itself, instant noodles now often function as a versatile flavor base or culinary accent in other dishes. Because they don’t align with the healthier, higher-quality, and more novel food choices that middle-class consumers aspire to, noodle shops, delivery noodles, or fresh-cooked instant options often win out. Yet, even these alternatives come with trade-offs. Delivered noodles lose texture during transport. Sit-down noodle shops preserve quality but offer limited flavors.  Cooking from scratch meets the bar for both texture and flavor, but requires a significant time investment. As one young mother said, “If I could get the texture of fresh-cooked noodles without turning on the stove, I’d buy that instant noodle for sure.”

The research inspired the creation of a new category, which the team termed “fresh-brewed noodles.” More than just a noodle or broth upgrade, Master Kong’s fresh-brewed noodles would offer the speed of instant noodles with the quality of freshly cooked options, plus flavors not found in traditional noodle shops. The strategic positioning was clear. Executing it by making fresh-brewed noodles mass-producible, affordable, and eventually profitable presented a category-innovation challenge. To get there, IDEO designed a series of dual-track co-creation workshops with the Master Kong team and consumers.

One track focused on prototyping the core product experience: noodles, broth, and toppings. IDEO and Master Kong’s R&D team began by studying the traditional craft of Chinese noodle-making, starting in Shanxi, a region renowned for its noodles. Through successive rounds of prototyping and consumer tasting, the team identified a critical insight: for “fresh-brewed noodles” to be convincing, the innovation had to be centered on the noodles themselves.

Texture alone was not enough. Consumers needed to see a meaningful difference before they tasted the product. IDEO translated this insight into a distinctive noodle profile: irregular, dimensional shapes designed to remain springy, hold sauce and broth, and mimic the resilience of freshly cooked noodles using only hot water. Because this visible shape represented the product’s core value proposition, it became a hero feature on the packaging. The graphic design made a bold visual statement about the noodle form, turning a technical R&D breakthrough into an immediately legible consumer promise: these are not ordinary instant noodles.

A parallel track explored the broader commercial experience: trend-forward and reimagined classic flavor profiles, light yet deeply satisfying broths, carefully selected toppings, and packaging that signals a new level of quality on store shelves. One key insight was that utensils carry meaning. Conventional instant noodles are often associated with disposable plastic forks, while higher-quality noodles are eaten with chopsticks. IDEO translated this cultural cue into the design of the bowl’s lid.

Instead of treating utensils as an afterthought, the team designed a solid, rounded, heat-retaining lid that embeds a pair of small wooden chopsticks. The gesture creates a small ritual of anticipation and reframes the product—not just a convenient instant meal, but a more considered noodle experience. Once opened, the product fulfills that promise with satisfyingly bouncy noodles, a rich liquid broth pouch that replaces the traditional oil-and-powder packet, and a vegetable packet reformulated with more premium whole ingredients.

The first batch of “Te Bie Te” Fresh-Brewed Noodles—Chinese wordplay that emphasizes “special”—launched in August 2025 with three trendy and tried-and-true flavors. Within just three days, sales exceeded 100,000 bowls. Within a week, “Te Bie Te” topped the instant noodle category sales ranking on Douyin, China’s domestic counterpart to TikTok. The outcome was bigger than a product launch—it served as proof that a mature, declining category could be fundamentally reinvented to meet consumers’ real needs. For Master Kong, the project became a North Star and a model for internal category innovation in beverages, ready-to-eat foods, and beyond.

Once a popular, affordable staple, the instant noodle category in China has been declining rapidly due to shifting demographics, rising food delivery options, and increasing customer demand for healthier, more nutritious meals.

‍

According to the World Instant Noodles Association, between 2020 and 2023, China’s instant noodle consumption fell by 4 billion packs.

100,000+

“Te Bie Te” bowls sold in the first 3 days on the market

#1

on Douyin’s instant noodle category ranking within one week of launch

Taylor’s legacy began in 1969 with the founding of Taylor’s College and soon expanded to include Taylor’s University, one of Southeast Asia’s top private universities, as well as many other institutions that serve 35,000 students per year. The family-owned group also operates Taylor’s International Schools, Garden International School, and Nexus International School for students ages 4 to 18. In Kuala Lumpur, Malaysia’s capital city, annual tuition at premium private schools like these ranges from about $10,000 to $25,000 USD. Taylor’s wanted to do something different: provide the same level of academic rigor and immersive learning experiences at one-third the cost.

IDEO began by speaking with over three dozen students, parents, teachers, and experts across the capital to understand what was working, what wasn’t, and what was missing from such moderately priced international schools.

A few themes quickly emerged. Families, students, and teachers were worried about the stability of these new private schools, which tended to have higher-than-normal teacher turnover rates and were plagued by financial instability, negatively impacting talent attraction and retention, as well as student learning. Parents appreciated that the schools offered holistic learning experiences, such as field trips to rural areas, including jungles, but wished they were more consistently part of the curriculum. And now, the looming challenge of AI—how to use it, how to teach it, and how to teach with it—was in the background, a persistent cause for concern. The big unmet need? Reassurance that Taylor’s was thinking long-term and systematically about developing the skills, knowledge, and mindsets that would prepare students for an ever-changing world. Parents wanted a school that measured growth in academic, social, and character terms over generations, not just school semesters.

With these insights in hand, IDEO began developing a design Playbook for Taylor’s new brand—Lexel International Schools. A combination of “lexicon” and “excellence,” Lexel’s mission is “building what lasts, learning for life.”

The schools are centered around three key differentiators: 

• Always Ahead: Lexel schools commit to staying current with the topics and subject matter they teach, as well as the tools they provide to students, parents, and teachers.s.  
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• Learning That Builds for Life: The schools ensure programmatic, systemic, and consistent learning experiences from Pre-K to Year 11. Interested students can even continue their post-secondary journey in partnership with Taylor’s University and other higher education institutions within the Taylor’s ecosystem.
  
  
• Educators for the Long Run: These schools commit to ongoing investments in professional growth opportunities for teachers and stable learning environments for students.

Four Lexel Literacies—AI, Digital, Financial, and Nutrition—integrated into the Cambridge Curriculum bring the school’s vision and mission to life.

By systematically integrating AI literacy into its spiral education framework, in particular, an approach where major topics are revisited multiple times through a curriculum to build fluency over time, Lexel ensures parents that the school is thinking a decade ahead from Day One, setting the school apart. In addition to enhancing AI fluency, Lexel offers unique end-of-term experiences called Jungles & Junctions.

Combining three important strands of learning—community engagement, nature-based personal and interpersonal development, and career and university exploration—Jungles & Junctions leverages Taylor’s extended educational network and Lexel’s strategic founding campus within the Gamuda Gardens development in Selangor. Surrounded by tropical rainforests, the township’s residential neighborhoods, theme park, and various sports facilities, including an Olympic-length swimming pool, are transformed into an extended Lexel campus, with a GenAI-driven planner to help teachers streamline the organization of class outings. “The Township is Your Campus” became the tagline for this approach.

In September 2025, just months after IDEO’s collaboration ended, Taylor’s began classes at its first Lexel International School. By mid-year, the new school had achieved 115% of its year-one student enrollment target, with significant inbound demand for Year 2 already demonstrating the school’s market resonance.

The modern campus features spacious classrooms, science and technology labs, a library, a multipurpose hall, and a canteen. Annual tuition ranges from about $2,800 USD for pre-K students to about $6,100 USD for secondary students.

Most importantly, by combining Taylor’s deep academic expertise, Gamuda Land’s development prowess, and IDEO’s innovative design Playbook, Lexel brings quality, affordable international education closer to home for Malaysian families. According to one parent, “My daughter looks forward to going to school every day … and has a lot of opportunities to express herself. On a scale of 1 to 10, I give [Lexel] an 11.” Based on the IDEO Playbook, a second flagship campus in the Southern Klang Valley, which is scheduled to open in September 2026, has already exceeded its year-one target enrollment expectations, with plans to continue extending the Lexel network to other parts of Malaysia and the wider Southeast Asian region in the near future.

Malaysia’s private international school sector has grown significantly as parents seek quality English-language education. However, high tuition fees and limited access to reputable schools are continual challenges for those in the emerging middle class.

115%

of Lexel’s student enrollment target reached during the launch year of its first campus
‍

Year 1 enrollment target exceeded

at Lexel's second campus several months ahead of classes commencing

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The American news industry has long been a competitive and saturated market. This has only intensified with the emergence of social media outlets and AI-generated news. Even so, SAN’s rigorously unbiased, fact-based reporting style and rich video storytelling had enabled the ambitious startup to rise above the media fray in just three short years.

With a strong foundation to build on, IDEO sought to further differentiate SAN’s cutting-edge news product and build deeper engagement with a wider audience through a new user experience.

‍Collaborating closely, IDEO and SAN began by delving deeply into media consumption habits. They met with early SAN superfans, news consumers who spent hours a day absorbing content from traditional outlets like Fox and USA Today, and those who looked to their Ring doorbell app or Reddit for news. The takeaways? People were tired of clickbait and clunky interfaces. They sought clear, factual news that was easily accessible, with additional context to help them interpret events and understand their significance. They craved more than one perspective on important topics, so stories felt balanced rather than polarized. They also valued having control over how they consumed news, so making it easy to switch between text, video, and audio formats was crucial.

Together, IDEO and SAN created features across SAN’s website and app that put facts, trust, and transparency at the core of the product experience. Fact Cards distill key data points into clear, shareable units, while the Sources feature allows readers to trace information directly back to its original source. To make complex stories easier to grasp, Big Picture insights drill down into why events matter, surfacing underlying themes, historical parallels, differences in reporting, and common ground. The Why This Story Matters section provides readers with clear framing and sets the story within a broader context, while the Timeline illustrates how events unfold over days, months, or even years. An antidote to news polarization, See All Sides presents left, right, and center narratives for key topics side-by-side, and Media Landscape visualizations reveal how coverage varies across outlets. Finally, to ensure SAN fits seamlessly into readers’ daily lives, the redesigned Today Page is organized into three highly scannable sections: Latest News, Top Stories, and SAN Originals. The combined features create a balanced, clear, and non-polarizing news experience, making it easy for readers to delve deeper into the sources of their news.

SAN now delivers a news experience as modern, dynamic, and trustworthy as its journalism. A month after its debut, the SAN app’s page views increased 1,170 percent year over year compared to June 2024, while active users rose 700 percent. Readers also give the updated mobile experience a 4.8 rating on the Apple App Store. “Our team is delivering reporting that’s both deeply factual and accessible,” said Derek Mead, SAN’s Chief Content Officer. “This redesign is pivotal to the direction journalism needs to take and the leadership role Straight Arrow News is taking on as we help guide the news industry into a brighter future.”

SAN built a loyal readership and gained recognition for its unbiased reporting. To expand and stand out from legacy media, SAN  wanted a redesigned user experience that reflected its commitment to fact-based journalism.

1,170%

increase in app page views YoY 

700%

increase in active users

4.8 rating

on the Apple App Store

Sanofi was the first company to supply the polio vaccine worldwide. Because of the global fight against the disease, endemic wild poliovirus transmission is now limited to just two countries. However, attitudes toward vaccines and immunizations have shifted significantly. To ensure a smooth launch of Beyfortus in a time of increased vaccine hesitancy, Sanofi asked IDEO to conduct research across four important and very different healthcare markets: Germany, Spain, China, and the US.

IDEO worked with parents, caregivers, healthcare professionals, and healthcare administrators to identify potential barriers to vaccine adoption and understand the emotional needs of all stakeholders involved in the immunization process. Navigating cultural differences and diverse healthcare environments, the team uncovered a set of insights.

For healthcare professionals, the team discovered there was no one-size-fits-all approach to immunization training across Sanofi’s 20-plus global markets. While consistency of key information was important, trainings needed to be flexible and customizable. This way, regardless of whether the vaccine was administered by midwives, OB-GYNs, nurses, or doctors, they could  confidently discuss the pros and cons across cultural contexts and administer the drug correctly.
‍
For new parents, receiving information about a new immunization immediately after giving birth could be too stressful. But simply leaving pamphlets about Beyfortus in waiting rooms didn't address their real concerns, either. Caregivers needed to engage in conversations earlier in their pregnancies and continue them after leaving the hospital, when they might have additional questions.

IDEO translated these research insights into a highly accessible global communication toolkit that uses simple, straightforward language, metaphors, and illustrations to support informed conversations between healthcare providers and parents before, during, and after a child is born. IDEO then conducted a series of market-fit co-design workshops with representatives of Sanofi’s global immunization business to iterate on the print and digital tools, make them more resonant with regional customers, and ensure compliance with local regulations. IDEO handed the toolkits over for development to support the launch of Beyfortus in January 2024, just in time for RSV season.

Beyfortus saw enormous demand in its first year, demonstrating strong efficacy in real-world applications and achieving blockbuster status as a $1.8 billion therapy. Sanofi’s global launch team credits the patient-centric toolkit with increased requests for communication materials from its regional markets as well as from healthcare and government organizations that have typically been hard to reach, key goals of its global-local launch strategy.

Since its development, Beyfortus has received swift regulatory approval from the US, EU, China, and Japan, with patient demand causing Sanofi to triple its worldwide manufacturing capacity to meet the needs of the 2024-25 RSV season. Ahead of the larger global distribution of Beyfortus, IDEO and Sanofi partnered with equity expert consultants, Fearless Futures, to conduct a DEI review and worked with doctors and nurses who participated in the initial drug launch to make the materials even more accessible, relevant, and successful for 2025 and beyond. To date, six million babies—and counting—have been immunized with Beyfortus.

Worldwide, childhood vaccination hesitancy among parents fluctuates between 25-45%, according to the World Health Organization (WHO), a trend it considers one of the biggest global threats to public health.

85.9%

‍reduction in hospitalizations for infants who received Beyfortus compared to those who did not (2023–24 RSV season)

$1.8B

in first-year sales of Beyfortus

‍

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.

Ed White has a rule he's tested on his own writing: hold yourself as the writer, and let AI be your editor. Ed is a Senior Design Director at IDEO's London studio, where he co-leads the firm's AI portfolio across Europe. Before IDEO, he spent 12 years as a writer and editor at the Financial Times, Wired, and Contagious. So when he talks about when to use AI for storytelling and when not to, it comes from two decades of crafting his storytelling skills.

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In this episode, Mina Seetharaman talks with Ed about two specific tools he uses to keep AI in an editor's seat: a "roasting agent" prompted to critique his drafts without any sugarcoating, and a simulated audience he rehearses pitches on before the real thing. They also get into what Ed is hearing from design leaders at Anthropic, Lovable, Shopify, and Google Creative Lab about how creative work is changing, and why he thinks the friction of writing something yourself is worth protecting rather than automating away.

Most AI products today are built for work—a space with clear problems and established systems. One founder noticed a gap: personal life is messier, harder to systematize, and mostly left behind by the AI boom. So she built Cue, a personal AI that lives inside iMessage and group chats, to go where the other tools haven't.

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In this episode, Becca Carroll, IDEO's Chief Strategy Officer, talks with Sida Li, co-founder and CEO of Shared Context Lab, about staying anchored to a human need while the technology around her keeps changing shape, why she treats her business model with the same rigor she'd bring to a product, and what it feels like to build a company at this particular, disorienting moment in AI.

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The conversation also gets into how Sida makes design decisions: the language Cue uses to describe itself, the tradeoffs behind building inside iMessage instead of a new app, and a real story about a business idea that didn’t pan out.

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This is the second in a two-part series profiling founders from IDEO's Startups-in-Residence program. The first conversation is with Johannes Seemann, founder of Sooner, on designing GenAI for the emotional side of money.

Most personal financial tools are built to run the numbers and optimize towards a budget. While that works for some, most people experience money as a lived relationship that does not neatly fit into a spreadsheet. Johannes Seemann and Becca Carroll discuss why money is emotional before it is mathematical, and what a human-centered approach to building a generative AI financial product looks like in practice.

Mina Seetharaman talks with Scott Shigeoka, author of Seek and Head of Curiosity Cultivation at the Eames Institute, about what distinguishes genuinely curious leadership from performative curiosity, how power dynamics shape curiosity, and why practicing curiosity can restore energy rather than drain it.