Now you can sing along with America’s Founding Fathers as you crush your opponents under oppressive rents and market domination.
The Op Games, a publisher of board games and puzzles, is releasing a new version of Monopoly based on the hit Broadway musical Hamilton, marking the latest iteration of the classic economics game that has been a staple of family game nights for many decades.
The Op Games plans to announce the new version today, a spokesperson told Fast Company.
The game commemorates the 10th anniversary of Lin-Manuel Miranda’s rap-infused retelling of America’s origin story, which made its Broadway debut in the summer of 2015 and went on to win 11 Tony Awards and the Pulitzer Prize for Drama.
In Monopoly: Hamilton, hotels become Federalist Papers, houses become Letters, and the familiar Chance and Community Chest cards are named after the musical’s dueling protagonists: Alexander Hamilton and Aaron Burr.
Instead of boot or thimble, players can choose between an assortment of Hamilton-themed pieces, including a microphone, crown, or tricornered hat.
[Photo: 1935, 2025 Hasbro. Hamilton by Lin-Manuel Miranda.]
Can you say no to this?
California-based The Op Games has carved out quite a niche for itself with cobranded versions of popular board games, such as a Jaws-inspired riff on Operation or a Trivial Pursuit edition that lets you test your knowledge of HBO’s Game of Thrones franchise.
It licenses Monopoly from toy giant Hasbro, which has touted a “franchise-first approach” to IP as a cornerstone of its success. For instance, the Monopoly Go! mobile game, published by developer Scopely, has been an enormous success, contributing $126 million in revenue to Hasbro so far this year as of the third quarter.
You could argue that all these variations cheapen the Monpoly brand (we’ll leave it up to you to decide if the world needs a Guy Fieri edition), but a Hamilton version of the capitalist-forward game makes more sense than most.
[Photo: 1935, 2025 Hasbro. Hamilton by Lin-Manuel Miranda.]
The title character, after all, played a key role in creating America’s financial system, and at least four of the musical’s characters are still pictured on our money today.
While the cultural legacy of Hamilton has been rigorously debated and reassessed over the yearscritics have accused it of perpetuating a “founders chic” view of American history, or of being an overly earnest relic of the Obama erathe show remains a money-making juggernaut.
Ten years on, it’s still playing at full capacity at the Richard Rodgers Theatre, where just last week it earned $3.9 million at the box office, more than any other show on Broadway.
Monopoly: Hamilton will be available for purchase at the theater, on the Hamilton website, and at Barnes & Noble bookstores, retailing for $45.
Just remember to collect 20 Hamiltons every time you pass Go.
The X of Y frameworkWere the Uber of healthcare or the Airbnb of financehas become a kind of startup reflex. Its useful, even comforting, to anchor a new idea to something people already understand. But what feels like clarity can become constraint.
When you define your business through another companys success, you risk adopting their playbook instead of rewriting the rules. The best disruptors learn to move past comparison. They articulate what makes their idea not just different, but inevitable. Thats how you build conviction from your team, your investors, and your customers.
Why comparison shrinks your story
From a branding perspective, letting investors, consumers, or even your own team see your business through the lens of another company is risky. It narrows imagination and compresses potential before the company ever takes off.
In Teddy Roosevelts words, comparison is the thief of joy. In the entrepreneurial world, comparison is the thief of innovation. The moment you define yourself through someone elses success, youre not building a new world; youre borrowing a corner of an old one.
True disruptors dont emulate, they innovate. And not just in the product, but in how they communicate that product to the world. The biggest tech companies by market capFacebook, Apple, Amazon, Netflix, Google, Nvidiaarent the X of Y. They just are. They didnt build by reference; they built by invention.
Yesterdays playbook wont win tomorrows game
From a business model standpoint, the X of Y approach doesnt simplify, it hamstrings. What worked in one context often fails in another because conditions change faster than most disruptors realize.
YouTubes monetization strategy, for example, only succeeded after the platform reached massive scale. Trying to apply that same model to a niche content business at launch would likely fail. OpenAI trained on freely available web data thats now largely cut off. Imitators entering the space today cant replicate those conditions, nor their success.
Timing and first-mover advantage matter. Once a model exists, the data access, regulation, even consumer behavior conditions that allowed it to thrive are already evolving. The world moves on. What worked before doesnt necessarily work now.
For disruptors, the takeaway is simple: Learn from others, but dont lean on them. The best leaders translate insight into original structure, a model built for todays conditions, not yesterdays advantages.
Create a category: Lessons from Figures IPO
I saw this dynamic play out firsthand during Figures IPO. With no natural comparison, we didnt fit into a familiar box. Yet, investors tried; they labeled us a blockchain company, a fintech lender, a financial marketplace. And each comparison carried its own limitations: valuation ceilings, volatility, market constraints.
Bringing something truly new to market requires more than a great product. It demands changing perception. You have to teach the market how to think differently and convince them theyre ready for it.
At Figure, we had to educate investors that what we were buildingblockchain-based capital marketswasnt a futuristic concept; it was a present-tense opportunity. We emphasized not just what we built, but why it mattered: faster, more transparent capital flows that could unlock a massive market. Once that clicked, investors stopped searching for a comparison and started seeing the scale of the opportunity. That shift made all the difference in a successful offering.
Comparisons fall flat faster in todays world
Were in an evolutionary moment. Like mobile did before, AI and blockchain are changing the rules of the game. Business models built around past infrastructure will quickly feel dated.
Anchoring yourself to yesterdays success stories is like hitching your wagon to Craiglists star in 2008. It looked brilliant, until mobile changed everything.
The X of Y mindset is its own kind of entrepreneurial Waiting for Godot. Leaders get stuck in a comparison loop, waiting for validation, for precedent, for permission to move. But the future never arrives for those who wait on it.
Pioneering beyond precedent, especially when precedent itself is shifting, is hard. But thats where the opportunity lies. Leaders who thrive in this environment wont ask, Who are we like? Theyll ask, What are we building that no one else has imagined yet?
Because real disruptors dont wait for Godot. They build the world everyone else is still waiting for.
Michael Tannenbaum is the CEO of Figure.
Bitcoin is having a horrible week.
Until yesterday, the cryptocurrency had declined by roughly 2.5% over the preceding five days. But in the last 24 hours alone, the coin has taken a major hitdown more than 10%.
Worse, fear and greed indices, which measure the emotional state of investors who buy and sell Bitcoin, are near historic lows. Heres what you need to know.
Why is Bitcoin sinking?
Bitcoin has dropped precipitously over the past 24 hours. As of the time of this writing, it’s down more than 10% to $82,185 per token. Thats a low the coin has not seen since April.
But why has Bitcoin been falling so much over the past 24 hours? There are two major factors at play.
The first has to do with what happened in the stock market yesterday. When markets opened, AI-related stocks were flying high due to the previous days news that Nvidia Corporation (Nasdaq: NVDA) had exceeded expectations for its Q3 2026 earnings.
This good news, momentarily, gave investors a confidence boost. Nvidias results were a sign, many argued, that the AI bubble people have been talking about for months was perhaps overstated.
But as the day continued, those bubble fears resurfaced, and investors sold Nvidia heavily, along with other AI stocks and other tech stocks. This selloff contributed to a steep decline in the markets, which ended down for the day.
Unfortunately for cryptocurrencies, many people who invest in volatile AI stocks also invest in crypto. And when one of those assets declines, they tend to sell off the other asset to lock in any accumulated profits and buffer against losses elsewhere in their portfolio.
However, you cant blame Nvidia and the tech stock slide yesterday for all of Bitcoins woes.
A second factor likely influencing Bitcoins massive 24-hour drop is that, as CNBC notes, America’s job numbers for September were released, and they showed stronger-than-expected job growth data (119,000 new jobs versus the roughly 50,000 analysts expected).
Why would good job numbers send Bitcoins price down?
Because those better-than-expected jobs numbers sent the probability of a December rate cut by the Federal Reserve down from 50% to about 40%. Rate cuts are generally seen as good news for the prices of assets like Bitcoin because the cuts boost liquidity in the markets.
At the beginning of November, many analysts expected there was a 90% chance of Fed rate cuts in December. By mid-November, that chance had been slashed to 50%. Now its down to 40%. This increasing likelihood that the Fed will not cut rates is likely weighing heavily on Bitcoins price today.
Crypto fear and greed indices near historic lows
A fear and greed index measures the emotional state of investors in a particular asset. Several crypto-focused platforms maintain their own Fear and Greed Indexes, including CoinMarketCap and Binance.
As CoinMarketCap notes, its fear and greed index measures the prevailing sentiment in the cryptocurrency market on a scale of 0 (extreme fear) to 100 (extreme greed).
This index helps investors understand the emotional state of the market, which can influence buying and selling behaviors.
Currently, CoinMarketCaps Crypto Fear and Greed Index is at an 11. Thats the lowest level it’s recorded since June 2023, the farthest back the index goes.
At 11, the index is currently lower than the 15 it was at on March 11, 2025, when crypto markets were also tumbling. This suggests that the emotional state of cryptocurrency investors right now is extremely fearful.
Similarly, Binance’s Crypto Fear & Greed Index is also at an 11 (it ranges from 0 to 100). Thats four points lower than where it was yesterday, and 50% lower than where it was last week.
While seeing the historic lows of the fear range of the index might further alarm Bitcoin investors, it should be noted that these indices can help track periods of over-selling (fear side of the spectrum) or when the token may be over-bought (greed side of the spectrum).
However, these indices cant predict whether any token will continue to be sold off or if its price will rebound.
Other cryptocurrencies are seeing a large selloff, too
As the crypto Fear and Greed indices suggest, its not just Bitcoin that is seeing major selloffs as of late. Other cryptocurrencies are also down significantly across the board.
This includes Ethereum (down 12% to $2,650), XRP (down 12.25% to $1.85), BNB (down 11.4% to $797), Solana (down 13.45% to $122.73), and Dogecoin (down 14.7% to $0.134).
Hi again, and welcome back to Fast Companys Plugged In.
On November 18, Google announced a new product. More precisely, it declared that it was ushering in a new erawhich is what tech companies do when they really want you to pay attention.
The product in question is Gemini 3 Pro, the latest version of Googles LLM. Its not just the foundation of Googles ChatGPT-like chatbot, also called Gemini. It underlies vast quantities of features in flagship offerings such as Google Search, Gmail, and Android. It powers Antigravity, a new Google AI coding platform that debuted on the same day. And thanks to Google Cloud, the model is also available to third-party developers as an ingredient for their apps.
In short, Gemini 3 Pro could hardly be more essential to Googles aspiration to be AIs most important player. As Google DeepMind CEO Demis Hassabis said in the announcement, the company sees it as a big step on the path toward AGIAI thats at least as capable as humans are at most cognitive tasks. Already, the announcement stated, Gemini 3 Pro demonstrates PhD-level reasoning.
Google supported its claims with a table listing 20 AI benchmarks in which Gemini 3 Pro beatand often just plain trouncedGemini 2 Pro, OpenAIs GPT-5.1, and Anthropics Claude Sonnet 4.5. Humanitys Last Exam, for example, is a 2,500-question test covering mathematics, physics, the humanities, and other topics. Its designed to be remarkably difficult (hence the name) and there has been debate over whether its so nebulous that some of the theoretically correct answers are nuanced or wrong. According to Googles table, GPT-5.1 achieved a score of 26.5%, while Claude Sonnet 4.5 managed only 13.7%. By contrast, Gemini 3 Pro scored 37.5%, and did even better when allowed to do searches and run code, with a score of 45.8%.
Outside the lab, Gemini 3 Pro has been received as enthusiastically as any new AI model I can remember. Ethan Mollick, one of my favorite providers of AI analysis based on hands-on usage, pronounced it very good. Others said it delivered on the great expectations that OpenAIs GPT-5 stoked but failed to satisfy.
As I write, Ive been playing with the Gemini chatbot for just a few days. Much of that experience has been positive. Two writing assignments I gave it came out exceptionally well: an article on the future of the penny, and a detailed report on pricing for Digital Equipment Corp.s 1960s minicomputers. Its first pass at a simple vibe coding projectbuilding a search engine for Fast Companys Next Big Things in Techwas a bit of a mess, but when I explicitly put it into Build mode, it nailed the assignment in a few minutes. It also excelled at figuring out what was going on in an assortment of photos I uploaded.
Yet for all thats gone right so far, I also encountered significant glitches with Gemini 3 Pro from almost the moment I tried it. They left me particularly wary of Googles blanket claims about the LLM being ready to help users learn anything and delivering responses that are smart, concise and direct, trading cliché and flattery for genuine insight.
My interactions gone wrong were mostly about animation and comics, topics I turn to when fooling around with new AI because I know them well enough to spot mistakes. Asked about these subjects, Gemini repeatedly spewed hallucinations.
For instance, when I asked if Walt Disney himself had ever worked on the Mickey Mouse comic strip, the LLM gave a correct answer (yes, though only briefly) but then volunteered a bunch of facts I hadnt asked for that werent actually factual. For example, it said that when the strips longtime artist retired, his final panel showed Mickey and Minnie gazing into a sunset, a subtle way of marking his departure. (No such strip appeared.) In a different chat, it manufactured an elaborate, entirely fictional backstory involving a different cartoonist also being a noted animation historian, which it told me was well-documented and recognized.
It wasnt just that Gemini hallucinated. ChatGPT and Claude still do that, too. But more than other models, Gemini tended to compound its failures by gaslighting me. Helpfully pointing out its gaffes led to some of the strangest exchanges Ive had with AI since February 2023, when Microsofts Bing said it didnt want to talk to me anymore.
(Full disclosure: I understand that AI is just stringing together a sequence of words it doesnt understand. All of its human-seeming qualities, be they impressive or annoying, are simulated. But its hard to write about them without slipping into a certain degree of anthropomorphizing!)
Repeatedly, Gemini acknowledged its inaccuracies but insisted they were lore, common misconceptions, or examples of my own confusion. In one case, it eventually confessed: I have failed you in this conversation by fabricating details to cover up previous errors. In another instance, it continued to insist that it was right, providing citations that didnt even mention the topic at hand.
Im not arguing that the fate of AI hangs on how much the technology knows about old cartoons. However, if any company is burdened with the responsibility of ensuring that its LLM is a trustworthy source of general information, its Google. That I tumbled into an abyss of AI-generated misinformation so quickly isnt an encouraging sign.
Part of the problem lies in the fact that Gemini 3 Pro offers two modes, Fast and Thinking. The first is the default and was responsible for the prevarications I encountered, at least one of which involved it conflating two separate topics Id brought up. So far, Thinking mode has worked better in my experiments. But even the speediest of AI models should meet a baseline of accuracy and good behavior, at leastif theyre being presented as a way to learn anything. (Like many AI tools, the Gemini chatbot does carry a mistakes-are-possible disclaimer.)
To repeat myself, Gemini 3 Pro is impressive in many ways. Still, its launch is yet another example of the AI industry presenting an overly rosy portrait of what it has achieved. It also underlines that benchmarks tell us only so much about a models real-world performance.
When OpenAI introduced ChatGPT three years ago this month, it did so in a brief blog post that took pains to detail the bots limitations and avoid grand pronouncements about its future. Letting its breakthrough new product speak for itself turned out to be a pretty effective marketing strategy. Even as AIs giants jostle for bragging rights in what may be the most hypercompetitive tech category of all time, they should remember that lesson.
Youve been reading Plugged In, Fast Companys weekly tech newsletter from me, global technology editor Harry McCracken. If a friend or colleague forwarded this edition to youor if you’re reading it on fastcompany.comyou can check out previous issues and sign up to get it yourself every Friday morning. I love hearing from you: Ping me at hmccracken@fastcompany.com with your feedback and ideas for future newsletters. I’m also on Bluesky, Mastodon, and Threads, and you can follow Plugged In on Flipboard.
More top tech stories from Fast Company
A battle against the AI oligarchy is brewing in this wealthy New York districtTwo congressional candidates have made AI a major issue in the campaign. Read More Crypto’s path to legitimacy depends on the industry itself, not just politiciansOnly an internal cultural shift and rigorous self-policing can deliver mainstream approval. Read More AI chatbots won’t save the media. But what powers them mightPublisher-built agents grounded in trusted archives may turn years of reporting into real products instead of just another chat widget. Read More This massive new data center is powered by used EV batteriesA new project from battery recycling startup Redwood Materials and data center builder Crusoe shows that it’s possible to build data centers cheaper and faster while also slashing emissions.Read More Why Trump’s AI diplomacy is doomed to failThis week, chips were on the menu in the White House Read More Even (especially) in the age of AI, here’s why I hire for character over skillBecause that’s what reveals true talent. Read More
Before Wicked opened on Broadway in October 2003, the musicals production team took the show to the Curran Theatre in San Francisco for whats called an out of town tryout. The five-week run allowed the producers, writers, and director to work out the kinks ahead of the shows Broadway debut.
During the San Francisco run, University of Southern California film student Jon M. Chu happened to be home for the weekend visiting his parents, who owned a Chinese restaurant called Chef Chus in Los Altos, California, just outside Silicon Valley. Chu was the youngest of five children growing up in a family that spent their free time playing instruments or going to the ballet, the opera, musicals, and the movies. It was the time of Michael Jordan on TV, and Steven Spielberg movies, Chu recalls. Michael Jackson videos were like mini musicals.
Chu was raised on what he calls this beautiful idea of story, and went to film school with an inner theater geek driving his desire to learn the craft. So it wasnt a surprise when his mom, Ruth, suggested they catch the show at the Curran.
Also at the show was Marc Platt, Wickeds producer, who spent those five weeks in San Francisco putting the finishing touches on what would eventually become one of Broadways biggest hits.
Little did either of these men know that nearly 20 years later theyd pair up to bring Wicked to the big screen. I waited 20 some years to make the movie after I produced the stage show, Platt says. There were many reasons I waited; destiny was calling me to wait until Jon was available.
Director Jon M. Chu on the set of Wicked: For Good with Ariana Grande as Glinda [Photo: Universal Studios]
Their partnership is now one of Hollywoods great success stories. Together, Chu and Platt delivered a giant blockbuster that grossed $114 million in box-office sales on its opening weekend in November 2024 (it went on to gross nearly $750 million). Now theyre poised to do it again with the release of part two, Wicked: For Good.
The Wicked films represent a big gamble for Universal Picturestwo lavish movie musicals released back-to-back with an estimated combined budget of roughly $300 million. All this in an era when studios are cutting costs and audiences are distracted by content that requires them to do nothing more than scroll their phones or stream TV from the living room couch.
Still, Chu says he’s more optimistic about filmmaking than ever. Now is the moment, he says, to fight for big stories that can break through in a business thats increasingly driven by algorithms and a focus on the bottom line.
I think if you want to fight that fight, youve got to play by the rules of this game, he says. You have to entertain the hell out of people.
Jeff Goldblum (the Wizard of Oz) and Cynthia Erivo (Elphaba) in Wicked: For Good [Photo: Universal Studios]
The Silicon Valley Showman meets the Hollywood Machine
Chu grew up inside two great American experimentsthe immigrant dream and Silicon Valley innovation. His parents have run Chef Chus for decades. In fact, thats where he was gifted his first camera and editing software from some thoughtful customers who worked in the movie industry.
In high school Chu convinced his teachers to allow him to turn in short edited videos rather than written papers, which provided him the opportunity to develop a fluency with the software hed inherited at the restaurant. He also landed gigs shooting weddings and bar mitzvahs in his hometown. He was an early adopter from adolescence, learning how to master After Effects and Pro Tools.
In 2002, while at USC, Chu gained some notoriety for a short film called When the Kids Are Away, which he made with a grant from the Princess Grace Foundation. It was a full-blown movie musical with singing and dancing, all about how stay-at-home-mothers spend their time when children are in school and spouses are at work. To work on it with him, he pulled in film school classmate and budding cinematographer Alice Brooks. They would later reunite on the Wicked films.
Chu had an early run of films that cemented his approach to musical storytelling. In his first studio film, 2008s Step Up 2 the Streets, Chu learned how to turn ideas into an actual production by marrying choreography and character. Then, as director of Justin Bieber: Never Say Never, Chu gained an understanding of how powerful internet culture can be as a storytelling mechanism. It wasnt until he directed Crazy Rich Asians, though, that Chu truly turned a corner in his career. The film allowed him to blend cultural nuance, authentic storytelling, and mass appeal. All of this leveled up into Wicked, which is Chus most ambitious film by far.
The movie required him to stretch beyond his creative instincts. Donna Langley, chairperson of Universal Pictures, says Chu is as much a whip-smart executive as he is a creative: He thrives at the intersection of commerce and art. He is deeply empathetic, pragmatic, and innovative. He sees challenges as opportunities, is extremely methodical in his planning, and yet remains flexible in his execution.
[Photo: Universal Studios]
Storytelling as empathy
Chu sees storytelling as a kind of transcendent currency in the current age of filmmaking. It is one of the most powerful empathy engines we have other than travel, he says. It helps, of course, that with Wicked Chu happens to be telling a uniquely magical story, in a land that feels so fantastical and vibrant you cannot help but be transported.
But Chus singular power in bringing Wicked to life is his ability to think like a storyteller and work like an engineer. Chus creative system is deliberate and disciplined. He recalls how in his early years of editing, he devised a system for nonlinear storytelling logic that helped him organize his ideas. He would assemble thousands of screenshots, textures, and notes and organize them into folders. These folders became a creative pantry of sorts that he began drawing from when developing a new film.
[Photo: Universal Studios]
When Chu and cinematographer Brooks were classmates at USC they bonded over their love of musicals. I think both of us are really emotional storytellers, says Brooks, who worked with Chu on both In the Heights and Wicked (among others). It’s about breaking a story from the inside out. She describes Chus process as incredibly intentional.
[Photo: Universal Studios]
She and Chu move at their own pace during the early stages of production and planning, trusting one anothers instincts as they go. When we first get a script, we break down each scene with one word, emotional intention, and every single camera choice and lighting choice comes from those intentions, Brooks says. It’s a long marinating process of letting ideas grow first, and then the technical ideas come very much as a secondary.
On the set of Wicked: For Good, Chu implemented a process that required the actors to speak their lines while rolling before official filming began. While rehearsing the song For Good, actors Ariana Grande and Cynthia Erivo began to ad lib, singing to one another through a closet door. It was totally unplanned, but also part of Chus usual process ahead of a scene, so he let it go and the captured moment ended up one of the most memorable in the film.
Process is how genius happens, he says.
[Photo: Universal Studios]
During the development of a movie, Chu doesnt think about box-office sales. Instead, hes locked in on making sure the film is as entertaining as possible. He views movies as a portal into another world, where the audience can experience things from someone elses perspective. To me, that is what we need to protect most in our culture, Chu says. I feel great responsibility that I have a microphone to be in that space.
Chu began shooting both Wicked films in 2022 before AI really became a thing. He and the movies team of more than 700 visual effects experts were deeply focused on building a tactile but imperfect world. He wanted tables that wobbled and doors with cracks in them. For Wicked to work, nothing could feel overly manufactured or make believe.
[Photo: Universal Studios]
He insisted the world be touchable, that we could feel the scratches and dirt, says Platt. That quality is what allows the audience to feel the high stakes in Glinda and Elphabas relationship, Chu says, noting that everything on set within 40 feet was physically built. The imperfections enabled a kind of intimacy with the audience that AI could never replicate. This couldnt feel like a dream, because we were talking about real things and were digging at real truth, he says.
Platt says this unwavering commitment to emotional resonance is what makes Chu unique at this moment in time. Even when it was challenging to make changes, or we had disagreements with the writers, there was always joy in the process, Platt says. When your director feels that way, it permeates all those working on a production. But also it made me confident in our collaboration, and in the outcome.
In many ways, Chu represents a blueprint for what the movie business will need as technology continues to infuse cinma. Chu believes that as AI becomes a bigger part of how creatives make their work, it will only put more value on human curiosity. In the end, he says, its about building something people can feeleven in a world made of pixels.
AI has made us faster and more productive at work. It drafts our emails, summarizes our meetings, and even reminds us to take breaks. But heres the problem: in our rush to embrace AI, its quietly eroding our relationships and how we build human connections at work and in our everyday lives. People are increasingly using tools like ChatGPT to help them write, coach, and communicate. And many are also turning to it for therapy and relationship advice.
The problem is, AI doesnt truly understand people as unique individuals. It can mimic empathy, but it cant understand it. It can predict tone, but it cant sense intent.
The way we communicate with one person shouldnt be the same as the way we communicate with the next, yet thats exactly what happens when we hand over the nuances of being human to a machine. And its showing up at work: 82% of employees now report burnout, and 85% have experienced conflict at work. The majority trace it back to miscommunication, misunderstandings, or feeling unseen.
AI is teaching us to write better, but not necessarily to understand better. Written communication has never been more polished. Yet the more we optimize our words, the more disconnected we seem to feel from one another.
The importance of respecting human nuance
AI can help us communicate, but it shouldnt act as a crutch. The real opportunity lies in using it as a mirror, which helps us better understand ourselves and the people we work with. Rather than replacing emotional intelligence (EQ), many teams are turning to personality science, such as the Five-Factor Model, to help leaders recognize how different teammates prefer feedback, how they handle stress, or why two colleagues interpret the same message in completely different ways.
For teams, and for counselors and coaches, the goal is similar: not to have AI communicate for us, but to help us communicate better with each individual that we engage with. Because no two people hear, feel, communicate, or respond to information in the same way. And while the best communicators already know this instinctively, in todays era of chatbots and synthetic personas, we often abandon that awareness. We need to go back to giving each message, each meeting, and each moment the same level of consideration. Whos on the other side? What do they value? How do they process information or emotion?
Leaders who take the time to personalize their communication build trust faster and resolve conflict sooner. When we adapt our style to meet people where they are, we only get better outcomes and make sure that people feel seen.
Why we need to leverage EQ to optimize communications and outcomes
Emotional intelligence isnt disappearing because people lack empathy. Its slipping because were letting machines do more of the communicating unilaterally. A new study by the Wharton School and GBK Collective found that 43% of leaders warn of skill atrophy as automation takes over routine work. This includes how we communicate.
Leadership happens in the spaces algorithms cannot see: a pause in a meeting, the tension after a missed deadline, or the silence that signals someone doesnt feel safe speaking up. When we lose sensitivity to those cues, collaboration breaks down. Teams still communicate, but they stop connecting, and thats when misunderstandings quietly multiply into conflict and burnout.
Heres how to keep the balance of efficiency and connection at work:
Pause before you send. Before you hit “approve” on an AI-generated message, ask yourself: Does this sound like me? Does this reflect what the other person needs to hear? Sometimes, a call or short message will land better than a polished paragraph.
Use AI for preparation, not delivery. Let technology help you structure the what, but you bring in the who with the persons history, style, and emotional context in mind.
Listen and follow up. After sending feedback or direction, prioritize follow-up and check-ins to make sure you keep building the relationship, while listening and applying feedback.
Prioritize taking a relationship-first approach. Remember that every person interprets messages differently. Landing the right tone and approach, depending on the relationship, shows respect and builds your connection.
The leaders who thrive wont be those who use AI to talk more. Theyll be the ones who use it to listen more intentionally, understand people, and communicate with individuals uniquely. Because in the end, our progress, happiness, and success depend on the quality of relationships that we have with one another.
The modern workplace runs on a dangerous myth: that constant motion equals maximum productivity. We’ve built entire corporate cultures around this fallacy, glorifying the “always on” mentality while our teams quietly unravel. The result? A burnout crisis that’s costing companies billions in turnover, absenteeism, and lost innovation.
But here’s what the dataand our own exhausted bodiesare trying to tell us: emotional recovery isn’t a luxury. It’s the most strategic investment a leader can make.
The Real Cost of Running on Empty
Burnout isn’t just about feeling tired. It’s a systematic depletion that manifests as cynicism, detachment, and plummeting professional efficacy. When leaders and teams operate without adequate recovery, they’re not just less productivethey’re fundamentally less capable of the creative thinking and empathetic connection that drives innovation.
The science is clear: failing to detach from work triggers rumination, which prevents the replenishment of our cognitive and emotional resources. It’s like trying to run a marathon on an empty tankeventually, the system fails. And when it does, the costs are staggering: disengaged teams, toxic cultures, and the loss of top talent who refuse to sacrifice their well-being for outdated notions of “commitment.”
Enter Move. Think. Rest: Your Operating System for Human Sustainability
The move, think, rest, or MTR framework I developedpronounced “motor”offers a refreshingly simple yet scientifically grounded approach to emotional recovery. The MTR framework recognizes that our bodies and minds operate as an integrated system, where physical movement, cognitive engagement, and intentional rest work together to create resilience.
Here’s how each element powers recovery:
Movement recalibrates your system. Physical activity doesn’t just burn off stressit fundamentally changes your biochemistry. Exercise reduces cortisol while flooding your system with mood-enhancing endorphins. But this isn’t about mandatory gym memberships or corporate fitness challenges. It’s about recognizing that even simple movementa walk around the block, stretching between meetings, taking the stairs instead of the elevatorhelps reset our nervous system and prepares us for deeper rest.
Thought creates internal space. Reflection and mindfulness aren’t just wellness buzzwordsthey’re tools for strengthening attention and emotional regulation. When we create space for intentional thinking, we develop the self-awareness needed to recognize depletion before it becomes a crisis. This cognitive recovery is where insights emerge and where we reconnect with the purpose that initially drew us to our work.
Rest is where integration happens. Here’s the counterintuitive truth: some of our most productive work happens when we’re doing nothing. Rest provides the liminal space where our minds process, integrate, and make connections that conscious effort can’t force. It’s not lazinessit’s essential maintenance. Sometimes doing less really is doing better.
From Surviving to Flourishing
The goal of MTR isn’t just to prevent burnoutit’s to enable flourishing. This is the state where productivity becomes a natural byproduct of being fully engaged and authentically yourself. It’s where innovation thrives, where teams genuinely collaborate, and where the “unlimited potential of the Imagination Era” actually becomes accessible.
This shift from survival to flourishing isn’t just good for employees, it’s also a competitive advantage. In an AI-driven economy where routine tasks are increasingly automated, the uniquely human capacities for creativity, empathy, and strategic thinking become paramount. But these capacities only emerge when people have the emotional bandwidth to access them.
Making Recovery Real: Your Action Plan
If you are ready to transform your organization’s approach to emotional recovery, here’s where to start. Keep in mind that it’s not a linear processit is situational and integrated throughout the work day, week, and year.:
1. Institute Strategic Microbreaks Build recovery into the rhythm of the workday, not just the weekend. Implement 15-minute “reset breaks” between back-to-back meetings. Create “No Meeting Thursday Mornings” to give teams uninterrupted time for deep workand genuine rest. Research shows these small reprieves sustain performance far better than pushing through exhaustion.
2. Lead with Visible Vulnerability Recovery will only become culturally acceptable when leaders model it. Take your vacation daysall of them! Talk openly about your own emotional recovery practices in team meetings. Share when you’re taking a walk to clear your head or blocking time for reflection. When senior leaders demonstrate that recovery is valued, not penalized, it gives everyone permission to prioritize their well-being.
3. Measure What Matters Beyond Output Expand your performance metrics to include recovery indicators. Track when teams are taking breaks, using PTO, and maintaining sustainable work rhythms. Celebrate leaders who help their teams achieve results while maintaining healthy boundaries. What gets measured gets managedso start measuring recovery as rigorously as you measure revenue.
The Bottom Line
The organizations that will thrive in the coming decades won’t be those that extract the most from their peoplethey’ll be those that invest most wisely in their people’s capacity to think, create, and connect. MTR isn’t just a framework for emotional recovery; it’s a blueprint for building companies where human potential can actually flourish.
The hustle culture isn’t just outdated, it’s actively undermining your most valuable asset: the full humanity of your workforce. It’s time to build a new model, one that recognizes that our best work emerges not from relentless grinding, but from the dynamic interplay of movement, thought, and rest.
The recovery revolution starts now. Are you ready to power down so you can truly power up?
Google has 44 data centers in operation or in development around the world, but as demand for AI and the need for compute capacity grows, the company is already getting started on three more.
This latest batch is destined for Texas, where Google already has a pair of data centers in operation just south of Dallas. One of the new centers will be located outside of Amarillo in Armstrong County, with the other two headed to Haskell County, about three and a half hours west of Dallas.
The $40 billion investment in the Lone Star State will help the company build additional infrastructure for its cloud and AI units. The company expects the centers to be operational by the end of 2027.
This will be Google’s largest single investment in any individual state, according to Texas Governor Greg Abbott. It follows data center announcements in Texas by Anthropic and Microsoft last week.
“This is a Texas-sized investment in the future of our great state,” he said in a statement. Google’s $40-billion investment makes Texas Google’s largest investment in any state in the country and supports energy efficiency and workforce development in our state.”
Despite Abbott’s claim about AI development, Texas isn’t quite the epicenter of data centers. With these three new ones, however, the state solidifies its bragging rights as having the second most in the country with approximately 415. Texas is still far behind Virginia, however, which has more than 660, mostly in a concentrated area in the Northern part of the state known as “Data Center Alley”.
Data centers are essential to the AI efforts of Google and other leaders in that field, but environmentalists have sounded a warning bell about the climate ramifications of the facilities.
The power requirements of data centers in North America increased from 2,688 megawatts at the end of 2022 to 5,341 megawatts at the end of 2023, according to MIT. And demand is only growing. (Energy Secretary Chris Wright, in February, called for more nuclear power plants to meet the growing demands of AI companies.)
The demand for new data centers cannot be met in a sustainable way, said Noman Bashir, a Computing and Climate Impact Fellow at MIT’s Climate and Sustainability Consortium. “The pace at which companies are building new data centers means the bulk of the electricity to power them must come from fossil fuel-based power plants.”
By 2030, Cornell forecasts, the public health burden of AI data centers will be double that of the U.S. steelmaking industry. And it could be on par with all the cars, buses, and trucks in California.
Google says its new data centers in Texas will be built responsibly, bringing new energy resources onto the grid and supporting community energy efficiency initiatives. That will include a $30 million Energy Impact Fund to scale and accelerate energy initiatives.
One of the Haskell County data centers, the company says, will be built alongside a new solar and battery storage plant.
Beyond the short-term job bump that comes with the creation of these centers, Texas will also see a rise in the number of electrical workers. Google says it will train existing electrical workers and more than 1,700 apprentices in Texas by 2030, which will double the pipeline of new electricians in the state, which could encourage other companies to build there.
They say that everything is bigger in Texas and that certainly applies to the golden opportunity with AI, said Alphabet CEO Sundar Pichai.
Google has 44 data centers in operation or in development around the world, but as demand for AI and the need for compute capacity grows, the company is getting started on three more.
This latest batch is destined for Texas, where Google already has a pair of data centers in operation just south of Dallas. One of the new centers will be located outside of Amarillo in Armstrong County, with the other two headed to Haskell County, about three and a half hours west of Dallas.
The $40 billion investment in the Lone Star State will help the company build additional infrastructure for its cloud and AI units. The company expects the centers to be operational by the end of 2027.
This will be Google’s largest single investment in any individual state, according to Texas Governor Greg Abbott. It follows data center announcements in Texas by Anthropic and Microsoft earlier this month.
“This is a Texas-sized investment in the future of our great state,” Abbott said in a statement.
Despite Abbott’s claim about AI development, Texas isn’t quite the epicenter of data centers. With these three new ones, however, the state solidifies its bragging rights as having the second most in the country with approximately 415. Texas is still far behind Virginia, however, which has more than 660, mostly in a concentrated area in the Northern part of the state known as “Data Center Alley.”
Data centers are essential to the AI efforts of Google and other leaders in that field, but environmentalists have sounded a warning bell about the climate ramifications of the facilities.
The power requirements of data centers in North America increased from 2,688 megawatts at the end of 2022 to 5,341 megawatts at the end of 2023, according to the Massachusetts Institute of Technology. And demand is only growing. (In February, Energy Secretary Chris Wright called for more nuclear power plants to meet the growing demands of AI companies.)
“The pace at which companies are building new data centers means the bulk of the electricity to power them must come from fossil-fuel-based power plants,” said Noman Bashir, a computing and climate impact fellow at MIT’s Climate and Sustainability Consortium.
Cornell forecasts that by 2030 the public health burden of AI data centers will be double that of the U.S. steelmaking industry. And it could be on par with all the cars, buses, and trucks in California.
Google says its new data centers in Texas will be built responsibly, bringing new energy resources onto the grid and supporting community energy-efficiency initiatives. That will include a $30 million Energy Impact Fund to scale and accelerate energy initiatives.
One of the Haskell County data centers, the company says, will be built alongside a new solar and battery storage plant.
Beyond the short-term job bump that comes with the creation of these centers, Texas will also see a rise in the number of electrical workers. Google says it will train existing electrical workers and more than 1,700 apprentices in Texas by 2030, which will double the pipeline of new electricians in the statethat, in turn, could encourage other companies to build there.
They say that everything is bigger in Texasand that certainly applies to the golden opportunity with AI, Alphabet CEO Sundar Pichai said.
With little more than a coat of paint, buildings could soon make the air around them cooler and harvest gallons of water directly from the atmosphere.
Researchers at the University of Sydney in Australia have created a nanoengineered polymer coating that passively cools building surfaces while enabling them to collect water like dew-coated leaves. It’s a material solution that could help combat rising heat and water insecurity in places all over the world.
The white coating, a porous paint-like material, reflects up to 97% of sunlight and radiates heat, making surfaces up to 10 degrees cooler than the surrounding air, even under direct sun. This cooler condition allows water vapor in the air to condense like dew on the smooth coating surface, where it can be collected. In a recent test, a roughly 10-square-foot area treated with the coating was able to harvest 1.6 cups of water over the course of single day.
Prof. Chiara Neto and Dr. Ming Chiu [Photo: University of Sydney]
This research was led by Chiara Neto, a professor at the University of Sydney’s Nano Institute and School of Chemistry. Neto is also cofounder of a startup that’s commercializing this coating, called Dewpoint Innovations. “Our main goal in designing this new material is to address water scarcity, providing a sustainable and delocalized source of water that is entirely passive,” she says.
[Photo: University of Sydney]
Reflective paint 2.0
Solar-reflective paint is hardly new to the world of sustainability, and it’s been used widely to reduce heat gain on everything from buildings to UPS trucks to playgrounds. This new coating builds on those applications by taking more advantage of the cooler air produced by bouncing heat off a building, creating a surface onto which water vapor can condense in the cooler ambient temperatures. The coating’s porous nature makes it more durable than typical reflective paints, which enables it to better collect dew than other surface coverings that quickly degrade.
The cooling and water harvesting potential of the coating could be substantial, according to a study recently published in the journal Advanced Functional Materials. The researchers measured the coating’s performance in six months of outdoor tests on the roof of a building on the campus of the University of Sydney. Specially designed surfaces and measurement tools tracked surface temperature and dew water collected on a minute-by-minute basis alongside weather and climate data to better understand when the coating would perform best.
[Photo: University of Sydney]
A theoretical model extended that data to create a water capture prediction for the rest of Australia, suggesting the highest water capture rates in the tropical northeast of the country. Neto says this model could be used by extension in the rest of the world, and has identified places where the coating could be especially useful.
“The areas most suited to the passive cooling effect are areas in which the sky is often clear of clouds, and the amount of water in the air is not too high and not too low (ideally around 80% relative humidity), to obtain the highest cooling of the surface and the highest water condensation,” Neto explains.
She notes that the coatings need to be clearly exposed to the sky to be most effective. “If used on the walls of buildings, they would still bring some cooling, but not as much as on the roof,” she adds. The ideal configuration is at a small tilt, a roof angled at about 30 degrees, to enable the roll-off of water droplets.
[Photo: University of Sydney]
But even in places where the humidity is too low to harvest much dew, the reflectivity of the coating will still provide the benefit of lower ambient temperatures and reduced energy requirements for buildings. The coating is not designed to be used as a ground cover, but Neto says it could be used in tilted and flat areas around sport courts, fields, on tents, on animals sheds, and other spaces.
If it were to be implemented widely, the coating could provide a steady source of water, albeit a small one. The study found that a one-square-meter section of roof treated with the coating could harvest up to 390 milliliters of water per day, a little more than a cup and a half of water from about 10 square feet of surface. Scaling up to the size of a building, that could add up to several gallons worth of water a day. That may not seem like a lot when the average person in the U.S. uses more than 150 gallons per day, but the volume could easily add up as more buildings are retrofitted, or even designed specifically, to use this coating.
This passive approach to water collection “opens the door to sustainable, low-cost, and decentralized sources of fresh watera critical need in the face of climate change and growing water scarcity,” Neto says.
