After officials released millions of pages of documents related to the late sex offender Jeffrey Epstein, revelations in his emails and other files have led to the resignations of multiple corporate executives, new investigations into abuses by Epstein and potential accomplices, and even the arrest of the United Kingdoms former Prince Andrew.
For those looking to research Epsteins vast correspondence and web of connections across industry, government, and academia, some of the most effective tools have been built not by federal investigators or big-name news organizations but by a scrappy team of volunteer developers.
Starting with a website called Jmail, which made Epsteins publicly released emails searchable through an interface cheekily copied from Gmail, they have since built a set of web apps modeled after familiar sites like Google Drive, Wikipedia, Amazon, and YouTube. The goal: to turn messy PDFs and other files released in bulk by federal officials into something members of the publicincluding journalistscan more easily search and understand.
Key to the projects speedy success is the technical talent of the team of around 15 named core contributors. But equally vital, they say, is the current wave of AI tools that helped them rapidly generate code and process huge troves of data.
So not only do we have an app that we were able to make very quickly, we have data that can populate that app with real content, says Luke Igel, among the projects initial creators. Both those things had to come together; both of those were not possible a few years ago.
Igel, an MIT grad who is cofounder and CEO of video software company Kino, says the inspiration for the project came after he and a friend were discussing an initial tranche of Epstein-related documents released by members of Congress in November. They were struck by the extent of Epsteins ties to political figures across party lines and around the world but questioned whether the public would be able to fully understand the story as the data was initially presented.
Igel then reached out to Riley Walz, a developer and entrepreneur known for creative internet projects (including a recent parody of Apples Find My interface that tracked San Francisco parking enforcement officers) about collecting the emails in a Gmail-style interface.
Thanks to AI development tools like Cursor and Anthropics Claude models, the pair was able to put together the first version of Jmail in just a few hours, Igel says. We cloned Gmail, except you’re logged in as Epstein and can see his emails, Walz announced in a viral X post in November.
When the Department of Justice released an additional trove of files in December, spurred by the Epstein Files Transparency Act passed by Congress the previous month, a group of about 10 collaborators gathered at Igels San Francisco home and via video conference to build the next iteration of the software.
The team also had help from a company called Reductoa maker of software that turns messy PDFs and other complex documents into structured datato parse the newly released files, which had become too complex for general-purpose AI tools to decipher reliably.
A lot of these PDFs are scans of printouts or handwriting, says Adel Wu, who works on growth at Reducto. It was actually very messy.
The companywhich is located in the same building as Kinohad already been considering doing something with the Epstein files and quickly decided to support the Jmail effort after hearing about it, says founding engineer Omar Alhait, noting, We very quickly went through all of the documents and parsed out all relevant email information from them.
Reductos software helped accurately render redactions within the documents and even let the team extract complex information like Epsteins flight data, which was made available in a Google Flights-style interface called JFlights. Again, AIincluding Anthropics then-new Claude Opus 4.5 modelhelped the Jmail team rapidly develop new features and apps and merge thousands of code updates in a short time.
So much of what I thought was core to software engineering is actually something that this model can help you with and help you blast through very quickly, Igel says.
The teams investment in infrastructure let them quickly import, process, and share additional documents released just before Christmas, though the project drew even more attention after a massive DOJ release of millions of Epstein-related files on January 30. Handling that release required not only processing the new documentsAlhait says it took Reducto about three days to crunch through the databut also beefing up the projects infrastructure to handle an influx of traffic as public interest in the files continued to grow.
Tons of people came to the house again, and this time we really just had to make it scale, Igel says. Everything broke. Tons of scaling issues we thought we had solved, with database outages and caching failing, came through again.
With the help of AI tools, the team stabilized the site, which has now served more than 500 million page requests to more than 50 million unique visitors. The project has also expanded beyond Jmail and JFlights to include an AI guide to the files called Jemini, a video repository called JeffTube, a file repository known as JDrive, and even a searchable log of Epsteins Amazon orders called Jamazon.
The team works to ensure information in the files is properly redacted to protect sensitive details, taking care to update the sites available materials to reflect any new redactions by federal officials. It’s very, very important to us to be as responsible as possible when surfacing information to the public, says Melissa Du, an AI research engineer who works on the project. We obviously don’t want to be over-redacting, but also the privacy of the victims is of utmost importance.
Du, another MIT grad, says she became morbidly fascinated by the first set of files released on Jmail, including documents referencing MIT-linked academics such as former Media Lab director Joi Ito and professor emeritus Noam Chomsky. She has since worked on aspects of the project such as JDrive for data management and the Wikipedia-style Jwiki, which was first populated with write-ups of key Epstein-linked figures generated by AI and then carefully vetted before publication.
Perhaps most striking about the project is that a small group of developers was able to do what major media organizations had done in organizing previous viral data repositories, like former intelligence contractor Edward Snowdens revelations about government surveillance or the offshore finance leaks known as the Panama Papers.
The team has received about $32,000 in donations to cover various costs, along with donated technical services from Reducto, Kino, and cloud provider Vercel. But the core work has been carried out by developers with their own day jobs and startups.
Though at times Igel wondered whether the project would be effectively scooped by big news organizations building their own Epstein data explorers, data from the Jmail project has actually been cited by news outlets including The Economist. The team has also been in touch with congressional staffers about passing on crowdsourced requests for release of potentially excessively redacted files.
And additional features are being considered, including a Google Calendar-style interface to explore calendar data in the repository, says Igel, who notes that the underlying code from the project will also likely be released as open source in the future.
Already the project stands as an example of whats possible for a talented team equipped with the latest in AI development and data processing tools. We’ve really relied on the new AI models, Du says. “And we’ve also just had a very high level of trust across the team.
With uncertainty as the new norm, leaders are understandably searching for psychological anchors. Theyre looking for ideas that can steady people and sustain energy through change. One of those anchors is hope.
Across corporate mission statements, fresh publications from thought leaders, and HR manifestos, corporations have elevated hope from a state of being to a strategic imperative. But what happens when an emotion becomes a business model?
How to define hope in an organizational context
Psychologically, hope is a cognitive and motivational state defined by three elements: agency (belief in your capacity to shape outcomes), pathways (the ability to identify routes toward goals), and goals themselves. Psychologist C.R. Snyder conducted research in the 1990s that reframed hope as a measurable construct. Snyder correlated the concept with performance, well-being, and perseverance.
Hopes modern strategic allure has deep cultural roots. In ancient philosophy, hope oscillated between virtue and vice. The Greeks saw it as both a comfort and a trap. When they opened Pandoras box, hope was the last thing left inside, which they ambiguously positioned between salvation and delusion.
By the 20th century, hope became a secular virtue central to progress and humanism. In psychology, post-war theorists viewed hope as a coping mechanism that could inoculate individuals and societies against despair. More recently, the positive psychology movement of the early 2000s further codified hope as a measurable, trainable mindset.
Today, in a world shaped by disruptiontechnological, social, and ecologicalhope has reemerged as a leadership commodity. In the absence of predictability, its a currency of cohesion.
The upside of hope at work
In organizational life, hope can offer the following tangible benefits:
Motivational fuel: Hope maintains focus on goals when there are distant or ambiguous outcomes.
Resilience amplifier: Employees with strong hope scores typically recover faster from setbacks and see alternative routes when plans fail.
Cultural glue: Hope-based narratives can create psychological safety. This allows people to see themselves as coauthors of a positive future rather than passive recipients of corporate fate.
Innovation driver: Hope enables experimentation by reframing failure as learning, not loss.
In these ways, hope can act as a psychological lubricant, reducing the friction caused by doubt, fatigue, and fear. So why does hope in a corporate setting leave a bad taste in my mouth?
Hopes hidden downsides
Hopes fierce glow can be blinding. When hope decouples from reality, it risks morphing into delusion or denial. This is particularly dangerous in workplace cultures that prize positivity over honesty.
Untampered, hope can produce three organizational distortions:
Deferred reality: Leaders may avoid confronting hard truths, preferring to hope things improve. This delays critical decisions about restructuring, investment, or strategic pivoting.
Toxic positivity: Teams pressured to stay hopeful may feel unable to surface legitimate concerns or dissenting views. The result is conformity disguised as belief.
Chronic stress and burnout: Sustaining high levels of hope in the face of repeated setbacks can exhaust employees, which produces emotional dissonance when ones lived experience doesnt match the optimistic messaging.
In essence, hope without realism becomes institutionalized avoidance.
Why hope isnt strategic
The current corporate positioning of hope as a strategy often stems from crisis communication. During market downturns, layoffs, or rapid transformation, hope becomes both a message and a salve. Yet, when you wield hope as a rhetoric rather than a practice, it erodes trust. Employees can sense when a message from leadership is inconsistent with conditions on the ground. The gap between them declaring hope and observable action breeds cynicism. This is a core component of workplace burnout, and a form of psychological corrosion that is far more damaging than pessimism.
The case for realistic optimism
A more sustainable alternative is realistic optimisma mindset that balances hopeful vision with clear assessment. Martin Seligman, one of positive psychologys founders, described optimism as the expectation that good things can happen, while realism ensures those expectations align with evidence and constraints.
Realistic optimism doesnt deny difficulty: it contextualizes it. Leaders who embody realistic optimism model three habits:
Evidence-based hope: They openly acknowledge setbacks and uncertainties while identifying genuine paths forward.
Transparent communication: They link belief with action by showing how theyre addressing challenges, not merely stating that things will get better.
Adaptive goal-setting: They recalibrate expectations when circumstances change, preserving motivation through clarity rather than blind positivity.
For example, a startup facing funding shortfalls might cultivate realistic optimism by acknowledging fiscal pressure while outlining tangible cost-saving measures and revised growth trajectories.
Realistic optimism transforms hope from sentiment into discipline. It requires intellectual honesty, emotional agility, and the courage to engage with uncertainty without succumbing to fantasy. In cultivating this balance, leaders create cultures that are not only hopeful, but credible.
A quick guide to leading with realistic optimism
If youre a leader and you want to know how to go about leading in a way that combines optimism and reality, start with the following steps below:
Start with the facts. Before inspiring your team, ensure the data supports your message. Sustainable morale begins with credibility.
Name the challenge, then the path. Hope grows when people see a route forward, not just a reason to believe. Pair optimism with concrete steps.
Model uncertainty tolerance. Encourage dialogue about whats unclear. When leaders admit they dont have all the answers, hope becomes collective rather than performative.
In an era when believing in better has become a hollow corporate refrain, leaders who master realistic optimism stand apart. They demonstrate that the most enduring form of hope is not a declaration, but a practice. And its one that they build with clarity, accountability, and shared ownership of reality.
Snapple might be gearing up for a long-awaited comeback by taking a page out of its 90s playbook.
On February 18, Snapples parent company, Keurig Dr Pepper, announced that the beloved tea brand is unveiling a refreshed visual identity designed to return the Snapple brand to icon-status. The new look, which will roll out beginning this March, includes new graphics, a logo inspired by the brands 90s look, and an updated bottle design that hearkens back to its original glass packaging. At the same time, Keurig Dr Pepper told Fast Company that its reinvesting in marketing efforts for Snapple, including through an ongoing campaign focused on the drink’s hometown of New York City.
For Snapple, the new look and marketing boost represent a return to form thats been a long time coming. After Snapples heyday in the 90scharacterized by its scrappy roots, funky packaging, and wacky ad strategythe brand has struggled to hold onto cultural relevance amidst a catastrophic sale, ownership changes, and several ill-advised rebrands.
Now, its looking to tap back into the playful energy that once made it the beverage of choice for 90s kids.
Current packaging (left) and 2026 refresh (right) [Image: Keurig Dr Pepper]
Snapple’s rollercoaster of a brand history
Snapple was founded in 1972 in Long Island, New York, by three friends. Their initial idea was for a company called Unadulterated Food Products, which would capitalize on a new wave of interest in better-for-you foods by selling fruit juices to health stores. One founder, Leaonrd Marsh, would later say of the venture that he knew as much about juice as about making an atom bomb.
As The New York Times noted in Marshs 2013 obituary, the three men did wind up making a bomb of sorts: a batch of carbonated apple juice that accidentally fermented, shooting scores of bottle caps skyward. Thankfully, this happy accident sparked a transition from the name Unadulterated Food Products to Snapple, a portmanteau of snappy and apple. Snapples bottles were made from a rounded glass, featured bright colors and a slightly cursive logo, and emitted a satisfying snap sound when the cap released the beverages carbonation.
Snapples original business model involved partnering with independent distributors to stock the beverage in smaller stores. The brand truly took off in the early 90s, when it began to enter the cultural zeitgeist through a series of zany, irreverent ads that emphasized its underdog status compared to big names like Coca Cola and Pepsi.
Undoubtedly, though, its biggest asset was a spokesperson named Wendy Kaufman, who, after appearing in several ads, became a beloved representative known as Wendy the Snapple lady (see this spot and this spot of Kaufman answering fan questions). Between 1992 and 1994, sales jumped from $232 million to $774 million.
Then, in 1994, Quaker Oats acquired Snapple in a $1.7 billion transaction that would go down in marketing textbooks as a prime example of how not to make a deal. Quaker swooped in, sanded down Snapples edgy personality, made its bottles bigger, relegated Kaufman to the back burner, and scrapped its independent distribution model, only to sell the company just three years later to Triarc Companies for $300 million. A brand disaster, indeed.
A post-“Quakergate” challenge
Since Quakergate, Snapple has been fighting an uphill battle to maintain cultural relevancea journey thats involved multiple rebrands and several ownership changes. Along the way, it has shed many of the brand assets that originally made it an outlier on grocery store shelves.
In 2008, Snapple became part of the Dr Pepper Snapple Group when Cadbury spun off its beverage business. Then, in 2018, Snapple joined Keurig Dr Pepper through a merger of Dr Pepper Snapple Group and Keurig Green Mountain. Between 2016 and 2017, Dr Pepper Snapple reported a 3% decline in the sale of Snapple products. According to Derek Dabrowski, SVP of brand marketing at Keurig Dr Pepper, Snapple has seen overall retail sales growth since the 2018 merger, but more recently that momentum slowed as shelf presence declined and marketing support eased.
Undoubtedly, a not insignificant part of the brands struggles has emerged from the fact that Snapple has lost its quirk. The brand got refreshes in both 2008 and 2015, and in 2021 Keurig Dr Pepper gave it a full-on rebrand. Snapples new logo was ultra-modernized into a blue-and-white sans serif; its glass bottles were replaced with recycled plastic; and its charmingly kitschy graphics were swapped for more commercial imagery. The company also attempted to reach younger consumers with a new line called Snapple Elements, which ultimately fizzled out.
Longtime fans of the brand bemoaned the changes,with many claiming that Snapple tasted better out of glass. Gone was the quintessential Snapple snap, replaced with a quotidian plastic sigh.
Snapple’s vintage logo (top), current (middle), and 2026 refresh (bottom). [Image: Keurig Dr Pepper]
A return to Snapple’s quirky form
Now, it seems, Keurig Dr Pepper is realizing that its rebrand may have been a bit too hasty.
Looking back, some of these efforts, especially chasing multiple trends at once, left the brand feeling a bit fragmented, Dabrowski says.
Snapples upcoming brand refresh spans graphics, logo, packaging communication, and bottle design. The bottles illustrations will call back to earlier iterations of Snapple with bolder colors and a slightly more retro look. Flavor signalers like Real Tea and Real Juice will take center stage on the packaging, connecting to the brands origins as a healthy beverage. And the sans serif logo will be replaced with a modernized version of the Snapple logo that defined the brand in the 90s.
The new Snapple logo isnt a carbon copy of the one from the late 80s and early 2000s, but its very intentionally inspired by that era, Dabrowski says. We brought back the iconic racetrack shape and heritage cues people recognize, then refined them to work better on todays shelveswith clearer readability, bolder color, and stronger flavor storytelling.
Marketing to match
Snapple has also been slowly tapping back into its irreverent advertising roots. Last fall, the brand launched a new campaign called Snapsolutely Refreshing with a media buy in its NYC hometown, including out-of-home placements across subways, street panels, office elevators and Times Square. It ran a one-day bodega takeover featuring free Snapple and branded merch. For a limited time, the brand even brought back glass Snapple bottles at a few retailers across the city.
And the ad accompanying Snapsolutely Refreshing feels charmingly similar to something Snapple might have made in its 90s underdog glory days: A man in an NYC bodega is confronted by a series of slightly creepy, talking wellness culture beverages, like kombucha and probiotic soda, before ultimately choosing to sip a Snapple instead.
Still, for diehard Snapple fans, a key question remains: Will the glass bottle ever make a real comeback?
That remains a bit of a mystery. Dabrowski says that in September, Snapple will roll out a new plastic bottle that mimics the originals shape and embossed logo. And, when pressed, a spokesperson shared that the brand is continuing to test glass bottles and learn from consumer response.
Whether Snapple ever gets its snap back remains to be seenbut, for now, the brand is at least looking (and sounding) a little more like itself.
A CEO sits in a boardroom, staring at a strategy deck generated overnight by AI. The analysis is sharp. The recommendations are confident. The numbers line up.
And yet something feels off. It feels flat, almost a little too perfect . . .
This moment is becoming increasingly common for leaders. Artificial intelligence is now one of the most powerful management tools ever created. It can analyze markets in seconds, surface patterns no human team could find, and generate plans on demand. For many executives, AI already feels indispensable.
But as intelligence scales at unprecedented speed, a quieter question is emerging inside organizations: How do we ensure AI is focused on human flourishing?
Intelligence Is Scaling. Wisdom Is Not
AI excels at intelligence. It detects patterns, predicts outcomes, and optimizes for efficiency. What it does not possess is contextual wisdom: the ability to understand why a decision matters, how it will land emotionally and culturally, or what it reinforces over time.
Leadership has never been about having the most information. It has always been about deciding what matters when information conflicts.
In an AI-rich environment, where intelligence is being commoditized, leaders face a subtle temptation to outsource judgement itself. When dashboards look precise and recommendations feel objective, optimization can easily be mistaken for wisdom.
But AI cannot answer the questions leaders are increasingly accountable for:
How is this affecting the precious humans in my care?
What values are driving this decision?
Is this decision indicative of the kind of world we are trying to build together?
These are not computational questions. They are human ones.
The Real Risk: Abdicated Leadership
Much of the public conversation about AI risk focuses on bias or misuse. Those concerns are real. But inside organizations, a quieter risk is emerging: outsourcing thinking that affects humans to the machine.
When leaders defer too often to AI-generated recommendations, they slowly lose confidence in their own judgment. Leadership shifts from sense-making to system-monitoring. Teams stop debating. Leaders stop interpreting reality and start validating outputs.
The result isnt better leadership. Its thinner leadership.
Over time, this shows up as cultural drift, ethical blind spots, employee disengagement, and loss of trustespecially during moments like layoffs, restructures, or major strategic shifts. When leaders cant clearly explain why a decision was made, people feel optimized instead of led.
Strong leaders dont just decide what to do. They articulate why it matters. They connect decisions to shared meaning, values, and narrative. They help teams understand how todays choices fit into a longer human arc of transformation and evolution.
AI can propose solutions. Only humans can author meaning.
Why Clarity Is Becoming a Core Leadership Skill
In an AI-saturated world, clarity is a force multiplier.
Clarity about purpose.Clarity about values.Clarity about what not to optimize.
Put simply: Clarity is deciding what you refuse to let AI optimize.
AI will happily optimize for speed, efficiency, engagement, or cost reduction. It will not ask whether those optimizations erode trust, creativity, resilience, or long-term cohesion. Leaders must.
This is why clarity, not charisma or technical expertise, is becoming one of the most critical leadership capabilities of the next decade.
Clarity allows leaders to:
Set boundaries around how and where AI is used
Frame AI insights within human context
Decide when efficiency should yield to ethics
Protect creativity where optimization would flatten it
Without clarity, leaders risk becoming reactive to machine intelligence instead of responsible for human outcomes.
How Effective Leaders Use AI Without Becoming Dependent on It
The goal is not to resist AI. It is to place AI correctly within leadership practice.
Three principles can help leaders do that:
Treat AI as an advisor, not an authority.Use AI to surface options, test assumptions, and explore scenariosbut make it explicit that final judgment remains human. In practice, this means leaders own decisions in their own words, not by pointing to an algorithm.
Slow down at meaning-making moments.When decisions affect people, culture, or identity (hiring, layoffs, strategy shifts, values) pause. Ask not only What does the data suggest? but What does this decision communicate about who we are?
Invest in judgment, not just AI literacy.AI skills matter. But judgment skills matter more. Organizations that thrive will be led by people trained to reason ethically, think systemically, and articulate values under pressurenot just operate tools efficiently.
Meaning Is the Leadership Advantage AI Cant Touch
In moments of uncertainty, people dont look to leaders for perfect predictions. They look for orientation.
They want to know:
What matters now?
What should I focus on?
How does my work connect to something meaningful?
AI cannot provide that orientation. Leadership can.
As machine intelligence accelerates, meaning potentially becomes more scarce and more valuable. Leaders who offer clarity amid complexity and purpose amid acceleration dont just build better cultures. They drive stronger innovation, greater organizational resilience, and long-term value creation.
The Capability That Endures
Every technological shift reshapes leadership. This one is no exception.
But the core truth remains: leadership is not about knowing more. It is about seeing more clearly and exercising wisdom under pressure.
AI will continue to evolve. Capabilities will expand. Tools will improve.
What must deepen alongside them is human leaderships capacity for clarity, judgment, and meaning-making.
Because in an AI world, the leaders who matter most wont be the ones who rely on the smartest machines.
Theyll be the ones who remember in wisdom what it means to be human while using them.
If you walk into a grocery store in the Netherlands or Germany, you might not realize youre being steered toward plant-based protein, from vegan tortellini to plant-based yogurt. But across Europe and the UK, major retailers are quietly driving that shift. And theyre seeing results at a time when plant-based sales are struggling in the US.
Lidl, a budget supermarket, grew UK sales of its private-label plant-based line by nearly 700% from 2020 to 2025. In Germany, France, and Italy, plant-based retail sales are growing across multiple categories, with most of that growth coming from supermarkets own brands.
Lidl is one of several retailers with a deliberate strategy to nudge consumers away from meat and dairy and toward plant-based food. In the Netherlands, major supermarkets now have an ambitious target: by 2030, they’re aiming for plant-based protein sales to outweigh animal-based food, in a 60-40 split.
Meat (left) and plant-based meat (right) on display at a Lidl market. [Photo: Lidl]
Climate is the biggest motivation. As grocery stores look at their own carbon footprintsdriven by policies like the EUs climate reporting rulesnearly all of the impact comes from food production in their supply chains. And nearly half of those emissions come from meat and dairy.
Its hugethis is the biggest lever for a retailer in terms of reducing the climate impact, says Joanna Trewern, director of partnerships at ProVeg International, a Berlin-based nonprofit that advocates for grocery stores to prioritize plant-based protein.
In the Netherlands, where stores have gone farthest to adopt new strategies, the organization co-founded a working group that helped retailers plan the transition. The Dutch government also issued a policy paper saying that the population was consuming more protein from animal sources than they should for a healthy dietthe opposite of the new dietary guidelines in the U.S.
Stores have taken several steps to boost plant-based sales. First, since the cost of plant-based alternatives is still a barrier, theyve built up their own low-cost, private-label offerings. A core element of our strategy is ensuring that plantbased foods are just as affordable as animalbased alternatives, a spokesperson for Lidl Netherlands told Fast Company. At Lidl, the prices of our plantbased staple items are already equal to or even lower than their animalbased counterparts. This price parity ensures that cost is never a barrier for customers who want to make a more sustainable choice.
Lower costs are critical for plant-based protein to grow, and private label products offer the biggest opportunity, Trewern says. “Retailers have more control over ingredient sourcing, it’s easiest for them to scale, and there’s more they can do in terms of price and investing in categories to bring the price down for the consumer,” she says.
As plant-based sales have grown, Lidl keeps adding more products to its range. That includes more traditional plant-based protein, like tofu or chickpea-based products. The initial innovation in this space was very focused on convenienceproducts that really mimic meat, says Trewern. Now what were seeing is consumers are looking for something else. Thats led a lot of people to say plant-based is not doing well, the categorys failing. Actually, what were seeing now in many European countries is theyre starting to come back and the category is consolidating with a different type of product. More clean-label, whole-food product sales are going up massively. (Sales of tofu and tempeh are also growing in the U.S., though in both locations, they’re still a small fraction of overall plant-based meat.)
[Photo: Lidl]
Some stores are also offering new hybrid products. Lidl was the first to start selling a partly plant-based burger60% beef, 40% pea proteinthat tastes like beef but is priced lower than its regular ground beef and has a much lower carbon footprint. The store has also cut back on promotions on meat; twice a year, it makes sure its promotional flyers are meat-free and feature plant-based products instead. It’s also tested other strategies, like placing vegan meat next to animal-based products in the meat aisle.
Partnerships with other brands can also help. The French retailer Carrefour worked with manufacturers like Danone and Unilever to bring new plant-based products to market, and met its original sales target seven years ahead of schedule. “Real behavior change happens when retailers and manufacturers work together to deliver products people love that reach price and taste parity with conventional options,” says Abby Sewell, corporate engagement manager at the Good Food Institute, an American nonprofit focused on the industry.
The work can’t guarantee on its own that plant-based protein sales always growcountry-wide sales dipped in the Netherlands in 2024, for example, while some other markets expanded. But it’s a useful tool. In the U.S., supermarkets don’t yet have similar goals and strategies. And the growth of private-label brands offers more evidence that price is key.
There’s still a large opportunity for more affordable, better-tasting products; almost three-quarters of American consumers are open to eating more plant-based food. “U.S. consumers say the most important factors that would make them more willing to eat plant-based meat are if it tasted better and was more affordable,” says Jody Kirchner, associate director of market insights at the Good Food Instiute. “This is an opportunity for the plant-based meat industry to continue to evolve and position itself for the next wave of growth.”
“Weve seen this before with electric cars and solar panelsearly hype, a dip, then a return to growth,” Kirchner adds. “With the right investment and innovation, plant-based meat can find that same curve.”
Corporate culture isnt built by policies. Its built by momentsthe unscripted experiences that catch us off guard, bring us closer, and quietly shape how we show up for one another.
But many efforts labeled culture-building, including onboarding programs, leadership retreats, and all-hands meetings, still feel like productivity theater: tightly scheduled and heavy on performance. Today, its worth asking whether that model has simply run its course.
Consider this: what if the future of culture-building isnt about managing people, but about designing experiences that allow people to feel something real together? What if awe, story, and shared creativity werent treated as indulgences, but as foundational elements of how trust, courage, and belonging actually form?
Beyond the Mission Statement
While leaders like to bring up the idea of team culture, few can describe what theirs feels like in practice. Thats because culture doesnt live in a mission statement or a values deck. It lives in the stories people tell when no one is watching. It lives in how they feel after a team gathering. It lives in the space between intention and lived experience.
The data reinforces this gap. Deloitte reports that only 23% of organizations believe their employees are strongly aligned with corporate purpose. Gallup finds that just two in ten employees feel connected to their companys culture on a daily basis.
These arent engagement or communication problems; they are failures of experience design. When culture is reduced to language and artifacts, it stays abstract. When its shaped through shared experience, it becomes something people carry with them.
Designing a Culture People Can Actually Feel
Imagine replacing a traditional all-hands meeting with a creative exercise in which each team member contributes a visual expression of what matters most to them at work. Or imagine a leadership offsite that trades breakout rooms for a story circle, where leaders share pivotal moments that shaped how they lead today. People may forget the fourth bullet on slide 37, but they remember the moment they felt genuinely seen. Thats where culture actually forms.
Across my work with teams and leaders ranging from early-stage companies to established organizations navigating change, the most durable cultural shifts dont come from tighter processes or clearer messaging. They come from intentionally designed experiences built around three elements humans have relied on for connection long before modern organizations existed: art, ritual, and awe. These lay the grounds for emotional experienceswhich can determine trust, risk-taking, and follow-through.
Art as a Medium for Meaning
When teams create something togetherwithout relying on wordshierarchies soften, safety increases, and unspoken dynamics surface naturally. Art invites play and perspective, two capacities most workplaces quietly suppress.
At a recent leadership offsite, I facilitated a collaborative art experience where each participant expressed a core value visually, without explanation. What emerged was more than a collective artwork; it was a shared mirror. People recognized one another in new ways. Long after the offsite ended, the exercise continued to shape conversations. Art creates space for truth to surface without requiring debate or performance.
Ritual as Emotional Architecture
Ritual has a way of slowing us down and signaling significance. Simple, intentional gesturesopening a meeting with a shared intention, closing an offsite with a moment of gratitude, marking transitions with presenceturn routine interactions into moments of coherence.
In my Campfires of Connection work, gatherings begin and end with ritual: lighting a fire, sharing a single word, or pausing together in silence. These gestures dont demand belief or explanation; they communicate something more fundamental: this moment matters.
One of my clients began opening weekly meetings with a 60-second pause and a single prompt: What are you bringing here today? Over time, that slight shift deepened trust more effectively than any formal team-building program. Ritual isnt soft; its the emotional structure. It creates the container in which change becomes possible.
Awe as a Catalyst for Connection
Modern workplaces are loud, fast, and cognitively overloaded. Many people arent disengaged because they dont care; theyre overstimulated and starved of wonder. Awe interrupts that pattern. It resets the nervous system and expands perspective.
In one of my facilitation sessions, participants were invited to sketch places from their childhood and share the stories behind them. The drawings were simple and imperfect, yet deeply personal. As each was revealed, the room changed. Colleagues who had known one another only through polished professional roles suddenly encountered one another as whole people with layered histories.
That collective pause created a sense of awe. These moments dont happen accidentally. Theyre carefully designed to allow people to encounter something beyond their roles. In environments driven by metrics and deadlines, awe reminds us why collaboration matters and why people choose to stay, contribute, and stretch together rather than simply comply.
When Culture-Building Falls Flat
To understand why this approach matters, it helps to consider the alternative. I once observed a leadership retreat that checked every conventional box. The agenda featured well-known speakers, the breakout sessions were smartly facilitated, and participants left entertained, informed, and exhausted. But within weeks, nothing had changed. The retreat generated momentum but not meaning.
What was missing wasnt effort; it was emotional resonance. There was no moment when people could set aside the performance of leadership and engage with one another more honestly. The experience was efficient, but forgettable.
Months later, a much smaller intervention with the same group, a single evening structured around reflection, had a disproportionate impact. Leaders spoke openly about uncertainty, named tensions they had been avoiding, and listened without trying to fix or impress. That evening reshaped how they worked together more than any previous retreat had. Culture doesnt shift because information is delivered; it shifts when people feel something together that changes how they see one another.
For leaders designing their next team gathering, the most useful questions may not be logistical at all. What do we want people to feel when they leave this room? What truth needs space to surface here? What has been rushed past that deserves reverence? What might become possible if we slowed down just enough to let meaning catch up?
The organizations people love working for arent those with the slickest branding or the most polished values decks. Theyre the ones where people leave a meeting or retreat feeling more alive, more trusted, and more willing to take risks together.
Our capacity to juggle several tasks at once is among the most important capabilities of the human cognitive system.
Just consider a typical day in the life of a modern human: you glance at your phone while waiting for coffee to brew, skim headlines while half-listening to a podcast, mentally rehearse a client pitch while walking your child to school, reply noted on Slack during a meeting while updating a slide deck, check your bank balance while standing in line, and, in a moment of entirely optional productivity theatre, scroll through a friends Facebook feed to see what their cat had for breakfast (admittedly, not the most important addition to our already heavy repertoire of multi-tasks).
If these familiar episodes of multitasking barely register as effort, it is because they have been absorbed into habit, woven into the fabric of daily life, quietly showing how often we coordinate competing goals, priorities, and impulses at once. For all the noise about AI agents, it is worth remembering that human agents remain remarkably capable.
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That said, generative AI and AI agents add yet another layer of temptation to multitask, and a respectable excuse for doing so. Now we can draft an email while an agent prepares slides, ask a chatbot to summarize a report while we skim LinkedIn, generate code while answering Slack, or prompt three models at once while half-editing a memo. This feels like augmented productivity, but often becomes cognitive diffusion or an increase in work intensity. As I illustrated in I, Human, when machines take over fragments of thinking, we become supervisors of many shallow streams rather than authors of one coherent argument. The result is not just intellectual sloppiness, but a steady erosion of focus, as attention shifts from solving a problem to managing tools that promise to solve it for us.
A bad rap
To be sure, multitasking tends to get a bad rap, especially among cognitive psychologists and behavioral scientists. This skepticism is well grounded. In a widely cited meta-analysis, researchers showed that alternating between tasks produces measurable switch costs in both speed and accuracy, even when tasks are simple. Subsequent research also found that heavy media multitaskers performed worse on tests of attention control and working memory, suggesting that frequent task-switching may erode the very cognitive filters that make focus possible. A more recent synthesis including examination of social media effects linked media multitasking during studying to significantly poorer academic outcomes. More recent neuroscientific evidence also shows that habitual multitasking is associated with reduced grey-matter density in regions linked to cognitive control, and some scholars have pointed out that multitasking deducts the equivalent of 10-IQ points from our performance and is therefore more debilitating than smoking weed (presumably minus the benefits or self-perceived creativity!).
Taken together, the evidence is rather compelling: multitasking is not a sign of superior efficiency but a tax on attention, trading depth for the comforting illusion of productivity. It makes us feel busy, sometimes even clever, yet especially for complex, analytical, or creative work it is usually worse than doing one thing well at a time, or learning to focus.
Supertaskers
And yet, that is not to say that we are all equally bad at multitasking. In fact, as in most areas of cognition, there are meaningful individual differences. A small but influential line of research has even identified a group sometimes labelled supertaskers.
In a dual-task experiment involving simulated driving and mental arithmetic, researchers identified a minority of participants who showed virtually no performance drop when handling two demanding tasks at once. These individuals tended to score higher on measures of working memory capacity and executive control (proxies for higher IQ), suggesting that cognitive resources, more than motivation or confidence, set the ceiling on multitasking ability.
Working memory is analogous to a computers RAM, in that it determines how many pieces of information can be actively held and processed at once. Individuals with greater working-memory capacity possess more cognitive bandwidth to manage competing demands, though the limits remain real for everyone. In line, studies consistently show that people with higher working memory capacity, stronger attentional control, and better fluid intelligence incur smaller task-switching costs. Working memory capacity predicts resistance to distraction, while Unsworth and Engle (2007) linked it to superior performance in complex attention tasks, and executive attention explains substantial variance in multitasking performance.
The role of personality
Unsurprisingly, personality also plays a role: most notably, traits linked to self-regulation and planning, such as conscientiousness, tend to buffer against the negative effects of multitasking, while impulsivity and related tendencies are associated with poorer performance. Broader Big Five traits such as extraversion, neuroticism, and openness show mixed effect, often influencing how people approach multitasking rather than how well they actually perform it. Even training and domain expertise matter. Air-traffic controllers, surgeons, and experienced gamers show reduced switching costs in their domains because practice automates sub-tasks, freeing cognitive bandwidth.
This does not mean that people know how good they actually are at multitasking. As in most domains of competence, the share of people who claim to excel far exceeds the share who truly do. In a classic experiment, researchers found that heavy media multitaskers rated themselves as effective jugglers of attention yet performed worse on tests of working memory and attentional control. The pattern echoes a broader principle from behavioral science, familiar from the DunningKruger literature: when a skill is poorly understood and rarely measured, confidence tends to rise as competence falls. Multi-tasking, like leadership or emotional intelligence, is easy to overestimate because busyness looks like effectiveness, and we remember the rare occasions when juggling worked, not the many when it quietly degraded our thinking.
Taken together, the evidence paints a nuanced picture. The average human is indeed a poor multi-tasker, especially when tasks are novel or cognitively demanding. But some individuals, by virtue of higher executive capacity (raw mental horsepower), disciplined habits, specialized training, and the right personality, are less bad at it. That distinction matters for leadership and talent assessment, because it reminds us that multitasking ability is not a universal virtue or vice. It is a measurable cognitive skill, unevenly distributed across people, and often confused with confidence, busyness, or the social theatre of productivity.
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If you have ever interviewed for a job, there is a non-trivial probability that you have encountered tricky or quirky interview questions. These are questions that are intentionally unexpected, abstract, or only loosely related to the actual requirements of the role. Rather than systematically assessing job-relevant skills, they are designed to surprise candidates, test composure, or signal creativity.
Interviewers often defend these questions as clever ways to evaluate problem-solving ability, cultural fit, or performance under pressure. The evidence tells a different story. Decades of research in industrial-organizational psychology show that unstructured, brainteaser-style interviews have low predictive validity. They generate noise, not insight. At best, they measure how comfortable someone is with improvisation. At worst, they measure how similar the candidate is to the interviewer.
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Cases in point
To illustrate the point, here are some common examples, ordered from least absurd, or at least somewhat defensible, to most absurd:
1. What is your biggest weakness?Nominally job-related, though usually answered strategically rather than honestly. The only rational way to respond is to disguise a strength as a flaw. It is less a test of self-awareness than an audition for plausible humility.
2. Sell me this pen.Some relevance for sales roles, but still an artificial performance detached from real context. Popularized by The Wolf of Wall Street, it reinforces the myth that great sales is about fast talk rather than listening, diagnosing needs, and building trust.
3. Tell me about a time you failed.In principle, a legitimate behavioral question. In practice, often an invitation to narrate a carefully curated setback that highlights resilience, grit, and eventual triumph. It rewards storytelling ability more than learning agility.
4. How many tennis balls can fit inside a Boeing 747?A classic guesstimate puzzle meant to test structured thinking. Geeks may love it, but it predicts little beyond prior exposure to similar puzzles. If you want to measure cognitive ability, there are far more reliable and validated tools.
5. How many windows are there in New York City?Same logic, further removed from any realistic job task. For what its worth, large language models estimate the number in the tens of millions, depending on assumptions. Which illustrates the deeper point: if ChatGPT can answer it in seconds, why are we using it to judge human potential?
6. If you were an animal, which one would you be and why?A thinly veiled personality quiz. It feels like a BuzzFeed throwback disguised as talent assessment. The answer often reveals more about the interviewers projections than the candidates traits.
7. If you could have dinner with any historical figure, who would it be?A pleasant icebreaker masquerading as a values assessment. It doubles as a signaling exercise: how curious, cultured, contrarian, or provocative can you appear in under 30 seconds? Say Nelson Mandela and you signal virtue. Say Steve Jobs and you signal ambition. Say Machiavelli and you signal strategic depth. But say Stalin and suddenly the interview turns into a moral inquiry. Was that intellectual curiosity, dark humor, or deeply questionable judgment? The question reveals less about your leadership potential than about your risk appetite for reputational self-sabotage.
8. If you were a kitchen utensil, which one would you be?At this point, the exercise has drifted into sheer parody shows like The Office come to mind. Spoon suggests reliability. Knife signals edge. Spork implies versatility. The real variable being tested may simply be how badly you want the job, signaled by the fact that you havent just walked out of the room.
The science
So, what does the actual science of interviewing say?
First, there is evidence that some interviewers are not merely misguided, but derive a certain Machiavellian pleasure from putting candidates on the spot. Research on interviewer behavior shows that individuals higher in everyday sadism or dominance are more likely to ask stress-inducing or intentionally uncomfortable questions. In other words, the brainteaser may sometimes be less about assessing you and more about interviewers enjoying the deviant power dynamic.
Second, the predictive validity of unstructured interviews is consistently low. Meta-analyses spanning decades show that traditional, free-flowing interviews correlate only modestly with later job performance. The problem is not conversation per se, but inconsistency. Different candidates get different questions. Interviewers rely on intuition. Evaluation criteria shift midstream. The result is noise, bias, and overconfidence, and unfortunately, these issues often go undetected because of the subsequent confirmation bias or failure to admit mistakes by hiring managers. In essence, if an interviewer likes you, they will either continue to like you after you are hired or pretend you are doing a great job to avoid looking like a fool.
By contrast, structured interviews work. The formula is hardly mysterious: define the competencies that matter for the job; ask all candidates the same job-relevant questions; anchor evaluations to predefined scoring rubrics; and combine interview data with other validated predictors such as cognitive ability or work samples. Behavioral questions about past actions and situational questions tied to realistic job scenarios consistently outperform seemingly clever riddles and quirky brain teasers.
The role of AI
And then there is AI, not so much the elephant in the room as the bull in the china shop, already rearranging the furniture while we are still debating the seating plan.
In a world where candidates can rehearse flawless answers with generative tools, the theatrical interview becomes even more obsolete. Chatbots can generate polished responses to biggest weakness or sell me this pen in seconds. Ironically, the more predictable and formulaic the question, the easier it is to game. This raises the bar for employers: assessment must shift toward observable skills, simulations, job trials, and multi-source data.
This does not mean interviews become irrelevant. It means they must evolve. When information is abundant and answers are cheap, the premium shifts from rehearsed narratives to demonstrated capability. Instead of asking candidates what they would do, employers can observe what they actually do: solve a real problem, analyze a live case, critique a flawed strategy, or collaborate with a future teammate. AI can help candidates prepare, but it cannot fully fake sustained performance in a realistic simulation.
There is also a deeper irony. The very tools that allow candidates to polish their answers can help employers design better assessments. AI can assist in standardizing questions, generating competency-based scenarios, flagging bias in evaluation, and even predicting which interview questions correlate with outcomes. In other words, AI exposes the weakness of theatrical interviewing while simultaneously offering the tools to fix it. The real risk is not that candidates use AI. It is that employers fail to upgrade their methods accordingly.
In sum, the future of interviewing is not about trickier questions. It is about better design. The uncomfortable truth is that quirky interview questions persist because they are fun, easy, and ego-affirming. But hiring is too important to be left to entertainment. If organizations are serious about talent, they must replace improvisational theatre with evidence-based assessments, and have the humility and self-critical honesty to truly test the outcome of their decisions to acknowledge when they are wrong, and make an effort to tweak things and improve.
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The workplace presents a distinctive set of disclosure dilemmas, beginning with the strange fan dance of interviewing. We are trying to put our best foot forward; to convince our potential employer were a perfect fit and consummate professional, yet were asked, What are your weaknesses? and What are the biggest mistakes youve made? Even the seemingly laidback So, tell me about yourself can feel like a trap. Where should we start?
There has been a lot of buzz in recent years about the benefits of bringing your whole self to work. Theres some evidence for those benefits. Letting others see more of you than you might ordinarily show them forges bonds, including in the workplace. We saw this in the early pandemic, when hardened leaders suddenly turned into endearing softies the moment their toddlers mischievously ran into their home offices.
But for compartmentalizers who prefer to keep work and personal life separate, the bring your whole self to work movement can be something of a nightmare. For others, like me, its freeing. But this new terrain is filled with land mines, and it can be hard to know when youre going to step on one.
The question of how much of our authentic selves to share at work is a pivotal one. Its also a difficult one to answer. We want to share enough to feel understood and connected to others, but not so much that we alienate people or cause them to question our competence or our seriousness.
Making matters even more complicated, each workplace has its own culture and its own norms about the degree of self-disclosure thats deemed appropriate. That doesnt mean theyre clearly articulated, usually far from it. We must discover them. And by no means should everyone decide to simply conform to those norms; bucking them might be good not only for ones own happiness and engagement at work, but for the whole team and for society at large.
So how do we find the right balance? What are the trade-offs between being a little more open at work and keeping strict professional boundaries intact? How much backstage access can we give to our colleagues and our bosses without risking our workplace image?
Backstage versus Front Stage: transparency versus vulnerability
According to my colleague Monique Burns Thompson, who works closely with members of Gen Z, Todays generation craves a level of openness that is different from when I was a young professional. New York University organizational scientist Julianna Pillemers research suggests that revealing aspects of our backstage selves at work, when done thoughtfully, can help us build rapport and stand out in a good way. In workplace contexts, she recommends what Id call discerning authenticitya balancing act that involves giving colleagues some, but not total, access to our inner lives. When done well, Pillemer argues, it helps build trust and sparks more meaningful conversations. Over time, this kind of thoughtful openness can deepen workplace relationships, enhance collaboration, and even improve performance.
What does it mean to be discerningly authenticto be open in a thoughtful way? Pillemer specifies two types of backstage access. The first, which she calls transparency, involves conveying openness by giving people a window into your thoughts, beliefs, or preferences. For example, you might say, Ive always been more drawn to the creative side of things, even though Im technically in a data-heavy role. This kind of sharing can carry some riskespecially if your perspective is unpopular or unexpectedbut it generally offers only a glimpse beneath the surface.
The second level of access, which Pillemer calls vulnerability, goes deeper and carries more risk. It involves sharing potentially sensitive inner states such as intimate emotions, especially negative oneslike admitting that you feel insecure about public speaking or disclosing a disability that might lead others to underestimate you.
For instance, someone might say, I get nervous presenting in front of senior leadership, even when I know the material cold (revealing a performance-related insecurity), or This kind of ambiguity is tough for me. I like having more structure, and Im trying to get more comfortable with the gray area (revealing a trait that might not align with organizational norms).
One shortcut I find helpful is to think of transparency as cognitive openness and vulnerability as emotional openness. In contexts where impressions really matter, the line between transparency and vulnerability becomes a strategic one. Pillemer doesnt draw a hard line, but she emphasizes that vulnerability is riskierespecially in high stakes, evaluative settings like job interviews, where disclosing insecurities might chip away at perceptions of competence. If in doubt, transparency is the safer bet.
Vulnerability should generally be avoided in those contexts unless, say, its framed as a story of growth or overcoming a challenge (I used to struggle with public speaking, so I joined Toastmasters). Even when youre explicitly invited to share something personallike in the dreaded tell me about a weakness questiontransparency often does the trick. You might offer cognitive openness: I think better in writing than I do speaking off the cuff. You could also frame it as growth: Ive learned to prep more deliberately for meetings so I can articulate my ideas clearly in real time. But if you give me a moment to organize my thoughts, Ill always bring sharper insight.
This kind of thoughtful disclosure lines up with what Pillemer would call transparency: revealing how your mind works in a way thats candid but not risky. Vulnerability, by contrast, might involve admitting that you often doubt your abilities or fear being judgeddisclosures that could raise red flags unless carefully framed. Still, even in high-stakes settings, being a bit more open can help.
From Revealing: The Underrated Power of Oversharing by Leslie John published on February 24, 2026 by Riverhead Books, an imprint of Penguin Publishing Group, a division of Penguin Random House LLC. Copyright 2026 by Leslie John
Youre interested in AI but youre human: Youve got emails to answer, deadlines to meet, and you dont have 40 hours a week to sift through academic papers on large language models.
You just want to know whats happening, why it matters, and maybe how to use it to get home a little earlier.
In that spirit, here are five AI podcasts to help you get smarter and stay informed without wasting your time.
The AI Daily Brief
For the busy professional who needs the headlines fast, theres The AI Daily Brief. Its usually about 20 minutes, which is perfect for the commute or while youre brewing that second pot of coffee.
Host Nathaniel Whittemore does a great job of cutting through the noise, but he doesnt just read the news. He analyzes what the big moves by OpenAI, Google, and Microsoft actually mean for the rest of us.
AI for Humans
AI for Humans is for the “rest of us” who just want to have a good time learning.
Hosted by Kevin Pereira and Gavin Purcell, this show is exactly what it says on the tin: AI news and tools explained by two guys whove been in the tech and media world forever but dont take themselves too seriously.
They demo new tools, they crack jokes, and they make the whole “impending robot takeover” feel a lot less scary. If you want to keep up with the latest without feeling like youre sitting in a lecture hall, give this one a shot.
Practical AI
If youre looking to actually get stuff done, check out Practical AI.
The name says it all. Hosts Chris Benson and Daniel Whitenack aren’t here to wax poetic about the singularity. Instead, they talk about real-world applications.
They interview people who are actually shipping AI products and solving real problems. Their podcast is accessible enough for enthusiasts but technical enough to be useful if youre trying to implement this tech in your business.
The Artificial Intelligence Show
For marketers and business leaders, The Artificial Intelligence Show is required listening.
Hosts Paul Roetzer and Mike Kaput from the Marketing AI Institute were beating the AI drum long before ChatGPT showed up.
They look at AI through a business lens: How does the latest news change your career? How does it change your company? If youre in marketing or management and youre trying to figure out how to navigate the next five years, youd be crazy not to listen.
Eye On AI
Eye On AI is a podcast for anyone interested in seeing the bigger picture.
Hosted by longtime New York Times correspondent Craig S. Smith, this one slows things down a bit. Its biweekly, and the interviews are deep.
Smith talks to the researchers and people building AI systems to better understand the “why” and the “how.” Its less about the “tool of the week” and more about understanding the fundamental shifts in the technology. Its a great weekend listen when youve got a little more headspace.
