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On Wednesday, Cisco Systems announced impressive quarterly earnings alongside nearly 4,000 job cuts. The dichotomy stemmed from the hardware and networking company’s embrace of a rapidly growing trend in tech: openly admitting that layoffs are due to AI adoption rather than poor performance. “The companies that will win in the AI era will be those with focus, urgency, and the discipline to continuously shift investment toward the areas where demand and long-term value creation are strongest,” Cisco CEO Chuck Robbins told employees in a publicly shared email. “I’m confident Cisco will be one of those winners. This means making hard decisions—about where we invest, how we’re organized, and how our cost structure reflects the opportunity in front of us.” With his announcement, Robbins follows in the footsteps of tech leaders including Block CEO Jack Dorsey and Snap CEO Evan Spiegel, who made similar moves this year. Robbins emphasized that the company will further invest in employees’ AI use throughout their jobs. Meanwhile, employees will start getting notifications if they’ve been laid off on Thursday. Cisco says the job cuts make up less than 5% of its total workforce. Shares of Cisco Systems Inc. (Nasdaq: CSCO) were up more than 16% on Thursday morning. The stock had already been trading at record highs this month. How did Cisco perform during its third quarter? Cisco reported $15.8 billion in revenue for the quarter ending on April 25. That figure represents a 12% jump year-over-year (YOY) and beats Wall Street’s predicted $15.56 billion, according to consensus estimates cited by CNBC. The company also surpassed expectations of $1.04 earnings per share with $1.06 adjusted. In a post-earnings call, Robbins highlighted AI-centric business with companies like Nexus and Nvidia, as well as a significant increase in revenue from AI. For instance, this quarter, Cisco shared plans to expand its secure AI factory with Nvidia. Cisco’s product revenue rose 17%, something Robbins attributes to “robust demand for our AI infrastructure and campus networking solutions.” Cisco expects its revenue to reach $16.7 billion to $16.9 billion in quarter four and $62.8 billion to $63 billion for fiscal year 2026. In comparison, it saw $56.7 billion in revenue for fiscal year 2025. View the full article

Today is an important day in the 2026 IPO landscape: Cerebras Systems Inc. is making its much-anticipated market debut. While not a household name like Nvidia, Intel, or TSMC, Cerebras is a chipmaker that is rapidly becoming a critical player in the AI semiconductor space. And investors will be casting a keen eye on how its stock performs in the early days of trading, looking for hints about how other, even more anticipated AI-related listings may play out later this year. Here’s what you need to know about Cerebras and its initial public offering: What is Cerebras Systems? Cerebras Systems is an AI semiconductor company headquartered in Sunnyvale, California. It was founded in 2015 by Andrew Feldman, Gary Lauterbach, Michael James, Sean Lie, and Jean-Philippe Fricker. Feldman is the company’s CEO. The company specializes in making the largest—quite literally—computer chips in the world, chips that are optimized for running AI tasks. While most computer chips are made from large wafers that are then divided to make smaller, individual chips, a single Cerebras chip is the entire wafer. As Fast Company previously reported when it named Cerebras one of the most innovative AI companies of 2026, the large size of its chips means they can perform AI tasks much more quickly—up to 70 times faster than the GPUs that many AI systems run on today. “The large square chip packs a lot of processing power and memory on one piece of silicon, so almost no time is wasted routing data between separate chips,” Fast Company’s Mark Sullivan previously noted. “That makes it highly effective at processing data from commercial AI applications that require massive throughput and very fast response times.” Cerebras’s customers include pharmaceutical companies like AstraZeneca and GlaxoSmithKline, as well as tech firms like G42, IBM, Meta, Mistral, Notion, and Perplexity. Most recently, Cerebras inked a $20 billion deal with ChatGPT maker OpenAI. When is Cerebras Systems’ IPO? Cerebras Systems priced its shares on Wednesday. It is expected to list on Thursday, May 14, 2026. What is Cerebras Systems’ stock ticker? Cerebras Systems’ shares will trade under the stock ticker “CBRS.” The stock will trade on the Nasdaq Global Select Market. What is the IPO share price of CBRS? The initial public offering price for CBRS shares is $185 per share. This final IPO price is remarkably higher than the IPO share price Cerebras said it would pursue just a few weeks earlier. On May 4, the company announced it would initiate the road show for its upcoming IPO. At that time, Cerebras said that the initial public offering price was expected to be between $115 to $125 per share. While it is not uncommon for a company to tweak its IPO price in the days leading up to the actual IPO, the final $185 IPO share price is around 60% higher than the low end of the original range. This suggests that demand for shares was much greater than initially anticipated. How many CBRS shares are available in its IPO? Upon its IPO listing, Cerebras Systems made 30 million shares of its Class A common stock available. The company’s underwriters, which include Morgan Stanley, Citigroup, Barclays, and UBS Investment Bank, also have a 30-day option to buy an additional 4.5 million shares. How much did Cerebras Systems raise in its IPO? Selling 30 million shares at $185 each means Cerebras raised $5.5 billion in its IPO. As noted by CNBC, that makes this offering one of the largest U.S. tech IPOs in recent memory. It puts Cerebras above the $3.8 billion that Snowflake raised in its 2020 IPO, and behind the roughly $8 billion Uber raised in its 2019 IPO. How much is Cerebras Systems worth? At its IPO price, Cerebras is now valued at around $56.4 billion, according to CNBC. 2026 is shaping up to be the year of AI IPOs Given all the hype and hope around AI, it’s little surprise Cerebras’s IPO shares went for significantly higher than the company had originally forecast. And the successful IPO also bodes well for other AI companies that are likely to go public this year. Two of the most anticipated AI-related IPOs of 2026 include Claude maker Anthropic and ChatGPT maker OpenAI. Current rumblings point to Anthropic debuting first, followed by OpenAI by the end of the year. Of course, AI companies aren’t the only tech firms expected to go public in 2026. Another big tech company that will likely IPO this year, perhaps as soon as this summer, is Elon Musk’s SpaceX. Taken all together, 2026 could be one of the biggest years on record when it comes to the total valuation of all tech IPOs scheduled to go public. View the full article

Dozens of brands are using the 2026 FIFA World Cup as a chance to cash in on themed ads, products, and brand collaborations. But the home goods giant Lowe’s is doing something unique: debuting a 10-foot-tall inflatable of Lionel Messi for fans to put in their front yards. Lowe’s is running a series of activations for the world’s biggest soccer moment, all of which center on its limited-edition, $99 Messi inflatable, made in collaboration with Messi himself. The inflatable, which will start to pop up in a 20-foot version around several U.S. host cities in mid-May, will be available online to Lowe’s rewards members starting on May 18, followed by a limited release in select stores on May 20. According to Jen Wilson, Lowe’s chief marketing officer, the company is planning to release only about 5,200 inflatable Messis—and it expects them all to sell out. The reason for Wilson’s confidence is twofold: First, she says, while plenty of brands will be planning their own activations for the World Cup, not many others could even attempt a product in this niche. And, second, the move is backed up by company data that yard decor—especially personalized decor—is becoming more popular among consumers, even outside of the typical holiday windows. It’s a trend that, oddly enough, might just trace all the way back to a giant skeleton that stole the internet’s heart in 2020. What in the world is going on with yard decor? Over the past few years, I’ve been noticing a trend in my Chicago neighborhood. Outside the typical festive months of October through January, I’m seeing more and more holiday decorations left out in people’s yards and stylized for each new season. Oftentimes, that takes the form of a giant skeleton dressed up in a personalized outfit or performing some kind of goofy stunt. There’s a very real subculture to back this up, and it all stems from a giant Home Depot decoration. In 2020, Home Depot released a 12-foot-tall skeleton decoration that almost instantly went viral, earning the internet moniker “Skelly.” In the years since then, Skelly has become the only Halloween product that Home Depot brings back year after year, consistently selling out to its legion of fans. Skelly has amassed a cult-like following, and, in turn, inspired a small but committed group of decorators to keep their skeleton decor up year-round, giving them customized outfits and accessories for events like back to school and arranging them in silly poses like a staged flag football game. Skelly’s popularity seems to point to a broader shift in how Americans view their yard space. Wilson says that Lowe’s also saw consumers’ interest in out-of-the-box yard decor spike starting back in 2020—and the trend has only grown since then. “For us it was really this explosion of both all things mini and all things giant,” Wilson says. She believes Lowe’s was one of the first companies experimenting with products like mini buckets or mini toolboxes, which have become huge fan favorites. On the other end of the spectrum, like Home Depot, Lowe’s has begun investing in new giant animatronics, including its popular 10-foot Abominable Snowman, 8-foot Skelly-esque skeleton, and 12-foot-tall Immortal Nightwalker. Outside of the holidays, the brand has noticed and capitalized on year-round yard trends, like the “porch goose,” a TikTok-viral concept wherein customers buy a concrete goose and dress it up seasonally—just like some Home Depot fans with their beloved Skellies. “We do absolutely see a rising trend in outdoor decor and consumers either keeping outdoor decor up longer or participating in trends like the porch goose,” Wilson says. “It’s all really interconnected to expressing your own sense of style and culture and just being a part of something.” She attributes the rising consumer interest in these novelty products to something she describes as “similar to the lipstick effect,” or the idea that consumers will increase spending on small luxuries during moments of economic strain. “People still want indulgences, even if there’s a pressured economy,” Wilson says. “A larger-than-life item in their front yard is something that just makes them feel joyous, and that’s what people are looking for.” With the Messi inflatable, Lowe’s is betting that the same theory will apply to World Cup fans who are watching the games from their homes, but want a way to let their whole neighborhood know that they’re part of a larger moment. The Skelly of soccer Given Lowe’s “affordable indulgences” decor theory, one of the in-house design team’s key considerations when building the inflatable Messi was cost. “We wanted it to be under $100, particularly as people are paying attention to their wallets and obviously the rising costs of gas,” Wilson says. “When we know that the consumer is super focused on essentials, if they’re going to make this splurge, we want to make sure that it’s affordable. We typically look at engineering most of our gigantic items somewhere in the under-$300 range.” That price constraint helped Wilson’s team to determine the actual height of the inflatable, opting for 10 feet rather than 15 or 20 in order to conserve materials and lower costs. Then, to get every detail just right, the team went directly to Messi to determine how the inflatable should look: each aspect, from the length of his hair to his beard, tattoos, and the look of his arms and legs, was given Messi’s final approval. “We just wanted it to feel authentic and for him to be proud if he was driving down a neighborhood in Miami and saw himself outside of a home,” Wilson says. “He loved where we landed, and we’re thrilled.” View the full article

“Who are your enemies?” I was asked this interview question throughout my entire career. And I’d always come up blank. Every time. No enemies. And when I failed to produce an impressive enemy list, the reaction was always the same: How can you claim to be competent if you haven’t made powerful enemies? I came to understand this enemy thing was rooted in the male idea of power. That men tend to see winning and power like this: For me to win, you need to lose. I came to realize that this advice to be powerful enough to have enemies was basically an invitation to turn into an aggressive bully to advance my career. But here’s the catch. I was bullied as a kid. And it was awful. So, early on, I decided that I was never going to choose to be like the bullies who hurt me. And if that was not good for my career, so be it. I would find another way. I often wondered if I was limiting my career by being too nice. And worried if I was supposed to feel powerful? Am I supposed to act powerful even if I don’t feel powerful? Am I doing the job of a leader wrong because I don’t feel powerful? Even when I was in my biggest roles, where I had actual power at my fingertips — thousands of employees under my watch, millions of dollars of budget to manage, billions of dollars of revenue to keep growing — I never felt personally powerful. Mostly, I personally felt crushing responsibility. I felt insecure about the power thing for years. The VP Bully Then one day, what I needed to do about this idea of acting powerful like the men became very clear to me. I was at a client’s office on Long Island. Sitting in a small conference room were the VP of technology, who was a large, dominant type, and one of his direct reports, whom I’ll call Seth. The VP told me, “The reason we are having this problem is that Seth makes stupid mistakes. He’s not good at his job. No one listens to Seth. He screws everything up.” Seth looked small and mortified. I was cringing and heartbroken for him. I knew what it felt like to be bullied like this. “Little Patty,” who had been bullied herself, could feel her childhood insecurities and fears bubble up watching this VP berate Seth. I had worked with Seth on prior occasions. Seth knew a hundred times more than this VP. The problem was not Seth. This VP was a bully. But then a really weird, creepy thing happened a bit later, when the VP walked me out, and we ran into his boss in the lobby: this bully instantly became a cowering suck up to his boss. I was appalled. He needed to abuse Seth to feel powerful, but he was afraid to be powerful with his boss. Watching this scenario, a new thought started to brew: Wait a minute, if I am still the same insecure little kid on the inside, probably so is this jerk. And once I saw it, I couldn’t unsee it. Forever after leaving that lobby, whenever I see a big, scary man acting like a powerful bully, I see the hurt little boy, as plain as day. I want to reach over, gently squeeze his forearm, and say, “Aw, did somebody steal your ball? Did your father yell at you for crying about it? Poor thing.” A better way Seeing the big bullies as fragile little boys was my first step toward understanding that there was a better way to show up as a leader than “powerful.” And with this insight, when I got bullied at work, I could mostly just step aside and let the aggression roll by instead of being crushed by it. My mom had given me the key to keeping my self-esteem intact with bullies all those years ago. And I have used her advice for the entirety of my career and life: Bullies need to make you feel worse than they feel on the inside. It’s always about them. It’s never about you. Once I saw these men as their own little version of Kevin or Harold, struggling with their own insecurities, I was no longer worried that they were innately gifted with a kind of power that I didn’t have access to. It made me stop worrying once and for all about feeling or even acting powerful. It just didn’t matter. I chose to be a leader who was first and foremost kind and respectful to people. People are not productive when they are self-protecting. I focused on making people feel safe. My teams executed on our commitments. We grew the business. My organizations got more capable over time because I invested in and cared about the people. For me, real power is not personally owned. The aggressive, bullying version of personal power is just insecurity masquerading as strength. Sharing power with others so you can get big, amazing things done together is true power. That was the sort of power I chose to cultivate and the kind of leader I chose to be. Do aggressive bullies get ahead? Yes, of course they do. But I learned it’s not the only option. You can make a different choice. I made a different choice. I chose not to model the idea of power that was being shown to me by the men. You might say I chose to stay “too nice”. And you know what? It did not limit my career. If anything, it accelerated it. I was able to build a highly capable team of people who were productive and motivated because I chose to make them feel powerful. And the idea of being or acting powerful personally didn’t confuse me anymore. I had no interest in the win-lose version of power. I just let the men duke it out among themselves, and I created my own path forward that was true to my belief that kindness and strength can go hand in hand. Because making people feel respected and safe makes them wildly productive. And on the enemies thing, I just think, if I can win and you can win, why is that not better? View the full article

Over the past day or so, I am seeing a large spike in signs that there is Google search ranking movement and volatility. This is between the SEO community chatter spiking, as well as some of the tools showing some big volatility swings.View the full article

Google announced that GA4, Google Analytics, has a new AI Assistant traffic measurement. This allows you to track AI chatbot traffic, like from ChatGPT, Gemini, and Claude. This is through a new AI Assistant channel in your Default Channel Group reports.View the full article

The critical challenge is to build institutions that protect us from tech companies and the stateView the full article

Google is expanding its vehicle ads to support more vehicles in the United States. Specifically, All-Terrain Vehicles (ATVs), RV's Utility Task Vehicles (UTVs), and non-motorized trailers, such as travel trailers and campers are now supported in Google Vehicle Ads.View the full article

A new AI citation study sparked a familiar SEO debate: the difference between a ranking factor and a symptom of ranking success. The post Direct Traffic & Popularity – Correlation, Not Causation appeared first on Search Engine Journal. View the full article

Google sent out emails to some advertisers notifying them that after June 10, 2026 they will automatically link your Google Ads account with your YouTube channel. Linking them will give Google Ads data on your YouTube channel.View the full article

Google has released version 24.1 of the Google Ads API, this is a minor release with dozens of updates. This update includes features like mobile device platform segment, classic images in DemandGen, support for passkeys, revamped support of experiments, and support for the new data retention policy.View the full article

Disclosure: I’m the co-founder of Optmyzr. I’ll use one of our open-source skills as the example below, but the frameworks here apply to anything you install or build. If you’ve used Claude, ChatGPT, or Gemini for marketing work in the last six months, you’ve probably hit the same wall I have. The chat is great until you need the same thing done the same way every week. Then you’re back to copying a prompt template into a fresh window, hoping you didn’t forget a step, wondering why a tool this powerful still feels this manual. Skills are what bring that wall down. I’ve written before about skills as scalable systems for PPC and why agents are useless without access to your marketing data. This piece zooms out. What is a skill, actually? Where do you find them? How do they work across the three big AI platforms? But perhaps most importantly for agency owners: how do you take an existing skill and brand it as your own? What are ‘skills’ in AI A skill is a small bundle of files that teaches an AI assistant how to do one specific job well, every time. In Claude, a skill is literally a folder containing a SKILL.md file with instructions, alongside optional code scripts and reference files the AI can process. Install the folder once, and from then on, when a task matches the skill, the assistant loads the playbook and follows it. It’s the difference between telling a new hire “audit this account” and handing them your agency’s documented audit process. The output gets much more consistent. While the concept is universal, implementation varies by platform. Claude offers the most seamless experience, allowing you to install and use skills directly within the interface. ChatGPT makes similar capabilities available though generally only on paid Business or Enterprise plans. Gemini remains the most developer-focused, often requiring the Gemini CLI or specialized environments, which makes it less accessible for the average marketer. Because of its ease of use, I mostly use skills with Claude, and that’s where we’ll focus. Where to find prebuilt skills for PPC Most account managers prefer copy-pasting scripts over writing their own. They’ll also like grabbing skills someone else already built. But finding them can be tricky. There’s no single App Store for skills, and most of the good ones are on GitHub. For Claude, the Anthropic team ships official skills for working with things like PDFs, and Microsoft Office programs. Beyond that, you’ll find growing collections on GitHub from individual developers and software vendors. A lot of companies are publishing their own. Ours live at github.com/optmyzr-skills. Optmyzr’s free Google Ads audit skill. Screenshot by author of Github.com. May 2026 A practical rule I’ve landed on: a skill is only as trustworthy as the team that built it. A skill from a known software vendor with its methodology is different from a one-off prompt repackaged as a skill by someone you’ve never heard of. Ensuring skill usage is consistent across your organization This is where it gets interesting for agencies and in-house teams. On a solo plan, you install a skill in your own account and you’re the only one using it. Fine for a freelancer. Painful for a team, because everyone has to install everything separately, and versions drift the moment one person updates and another doesn’t. On Team and Enterprise plans, an admin can deploy skills across the whole organization. Claude has org-level skill management on Claude for Work and Enterprise. The practical benefit is that, with a five-person PPC team, you install a shared audit skill at the org level once, and every account manager gets the same version on day one. When you improve it, everyone gets the improvement automatically. No more “which version are you running” on team calls. How to install a skill in Claude. Screenshot by author of claude.ai. May 2026 I think of it like the moment ad scripts stopped living in each individual ad account and moved to Enhanced Scripts from Optmyzr, which lets advertisers deploy a generic script code to all accounts and shifts script versioning and settings into a centralized management system maintained by Optmyzr. Easy, maintainable, and scalable; all things that matter a lot to account teams who promise a standard of quality to their stakeholders. The hidden white-labeling engine: Why forkable skills are an agency’s best friend Here’s the part that should perk up agency owners. Most well-built skills are folders, and the open-source ones live on GitHub. Which means you can fork them, edit them, brand them, and use your modified version with your own clients. Let me walk you through an example for a 15-person agency. I find an open-source Google Ads audit skill (we’ll get to the one I’m thinking of in a second). The default report it generates has “Google Ads Audit” at the top in plain text. Useful, but generic and probably not shareable with the client. What I can do in about an hour: Clone or download the skill folder. Open SKILL.md and edit the report-generation instructions to swap in my agency’s name, reference my logo, and use my brand colors. Drop my logo into the skill folder so the assistant can use it when generating PDFs or HTML reports. Add or remove checks based on what I actually care about — if I run only ecommerce accounts, I can tell the skill to weight Performance Max, Merchant Center, and feed health more heavily. Repackage and install for my team. What comes out the other side is a branded, agency-specific audit tool that produces client-ready PDFs with my name on them. I didn’t have to build the underlying methodology. The original author already did that. I just added the last 10% that makes the output feel like mine. Scripts were powerful because you could tweak them. Skills have the same power. Agencies are no longer capped by what software vendors choose to white-label. If a skill is open source, you can white-label it yourself in an afternoon. A worked example: the Google Ads Audit skill Since I keep alluding to it: we recently released a free, open-source Google Ads audit skill at github.com/optmyzr-skills/google-ads-audit. Apache 2.0 license, no Optmyzr login required. A sample of the audit score the Optmyzr audit skill produces. Screenshot by author, May 2026. Briefly, what it does. It runs through 14 categories and roughly 42 best-practice checks: Account settings Conversion tracking Campaign structure Performance Max Budgets Bidding Targeting Audiences Keywords Quality Score Search terms RSAs Extensions Landing pages Industry benchmarks Competitor analysis It asks three calibration questions at the start (primary goal, target CPA or ROAS, account maturity) so the scoring matches the kind of account it’s looking at. If you don’t want to connect anything, there’s a four-paste flow: pull four CSVs from the Google Ads UI, paste them into Claude, and the skill runs the diagnostic. The output is a top-5 findings list with monthly dollar impact, an A/B/C grade with per-category breakdowns, a 7-day action plan, and a wasted-spend estimate. A sample of the next steps the Optmyzr audit skill suggests to address key shortcomings of a Google Ads account. Screenshot by author, May 2026. All the principles I described above apply to it. You can install it for free. You can deploy it across your agency. You can fork it, brand it, and have it generate client PDFs with your logo and your methodology framing. The Apache license explicitly allows that. If you want it to also pull live account data instead of CSVs, run multi-account portfolio rollups, and trigger automated remediation, that’s where Optmyzr’s MCP server comes in — and that’s the paid layer. But the audit logic itself is yours to use, modify, and brand. What to do with this Pick one repeatable workflow your team does manually right now. Audits, search term reviews, ad copy generation, weekly report drafting — anything that runs the same shape every time is a candidate. Find or build a skill for it. Then move it from individual installs to team deployment. That single change kills a surprising amount of version drift across a team. Brand at least one skill as your own, even if you never ship the branded version to clients. Going through the fork-and-modify process once changes how you think about what counts as “tooling” for your agency. It’s lighter than you’d expect. Skills are how a generic chatbot starts to behave like your team’s documented operating system. The agencies that get fluent with installing, deploying, and forking them over the next 12 months are going to operate noticeably differently than the ones still copying prompts into chat windows. The Optmyzr audit is one example. There will be hundreds. How to install the audit skill There are two paths; pick the one that fits your team: If you have someone technical on the team — an in-house dev, a power-user analyst, anyone comfortable with a GitHub URL — install it as a Claude plugin straight from the repo. One command. The skill stays in sync. When we ship a new check, tighten a benchmark, or add a category, your install picks it up automatically. For an agency running this across a team, this is the right path. Everyone runs the same version. If you’re a marketer who just wants the thing to work — no GitHub, no command line — download the zip from the repo’s releases page and upload it via Settings > Capabilities > Skills inside Claude Desktop or claude.ai. Up and running in under a minute. The tradeoff: it’s a snapshot. When we improve the skill, you’ll need to grab a new zip and re-upload. For a solo practitioner running monthly audits, that’s usually fine. Either way, the repo is at github.com/optmyzr-skills/google-ads-audit. Once it’s installed, type /audit in any Claude conversation, answer a few guiding questions, and then receive the audit. View the full article

Custom AI models are not just for the AI giants anymore. Because the 37-person startup Krea is releasing its first generative AI model as the design tools startup repositions itself as a full-fledged AI research lab. The move is significant for Krea, but it also seems to tease an almost inevitable moment in the rapidly evolving AI market, where smaller players in the industry can make more disruptive bets. On one hand, Krea can hardly call itself a bootstrapped startup anymore. It’s now raised $83 million through its Series B at a $500 million valuation. On the other, it’s tiny compared to the leading frontier model companies, which constantly raise more money to ensure they have an unlimited war chest to train the next best model: OpenAI and Anthropic, which have raised $180 billion and $72 billion, respectively. But to Krea’s co-founder, Diego Rodriguez, it’s invigorating to be small, nimble, and, by one significant measure, no less successful than any frontier model company as a core business. “Until there’s a winner—until OpenAI or someone is profitable—the Olympic Games are on,” he says with a mischievous smile. The evolution of Krea Krea launched in 2023 to be something like the Adobe of the AI age, a creative platform designed from scratch to allow you to not just generate media with AI, but to tune those outputs, with controls that feel more like a synthesizer than a drafting table. They were the first to offer real-time AI editing tools and the first to put APIs from other AI models into their own app (a practice that has now become standard). And they were quickly profitable. But over time, the team has recognized a distinct ceiling to their work: Krea can only be as open-ended as the models it sits upon. Image models of today are amazing at specific prompts that often go viral, but they can also feel like they are built on rails. Creative phrasings can still lead you down the same old paths, as models fail to reproduce what’s in your mind’s eye. “The models are trained not to fail and to always give you a good image,” says Krea’s co-founder, Victor Perez. “And I feel like that takes away a lot of the creative uses—breaking the barriers and letting people go off-road, letting [you] make ‘bad’ images, stuff that looks more artistic that a creative might appreciate more.” Indeed, image models are amazing when it comes to what these companies have been prioritizing: photorealism. But any designer reading this knows that when it comes to graphic design and illustration, you can hit the boundaries faster than you’d think. In a demo, Krea pulls up comparisons of the prompt “a cat riding a bicycle” between itself and Google’s Nano Banana. In Krea’s case, the first outputs are funky and varied, with some exhibiting a hand-drawn feel. In Google’s, no matter how you adjust the prompt, you get a similar coloring-book-looking image presented in the same way. It’s the difference between eating at McDonald’s or a Michelin burger joint. One will always aim to please, while the other may polarize. “I think that the kind of stuff that we are interested in is more niche,” says Perez. “It’s a much smaller market, but we’re fine with it.” Spending 15 minutes prompting Krea’s new image model K2 on my own, and I’m impressed by its breadth. It generates surreal photorealistic scenes, but also grainy VHS-style filtered images and a variety of illustrative techniques (word marks, manga, anime, hand sketching, and sharpie cartoons) well. The examples I saw from Krea were also impressive—and wildly so given the gulf in resources between Krea and the giants. Perez attributes this success to his team’s own taste. They’ve spent the last seven months building their own data set (no, they aren’t disclosing the sources), labeling it by hand, and creating their own unique workflows to train their own generative AI system. As Perez explains, most big models start the same in development to build a functional neural net, but mid- and post-training steps in particular are what give the model a point of view. I’ve heard from people in the industry that there are only about 200 true post-training experts in the world, which is why the market is so competitive. “That’s when the artistic direction on the model takes place,” says Perez. “At the end of the day, building a model is almost like crafting a sculpture.” That final layer of training, where a model develops its visual or verbal voice, is where taste comes in. Making the AI do one thing better can often make it do another thing worse, and balancing those priorities is particularly tricky when trying to build a model that makes cool, personally expressive stuff. “This is like the nemesis of an AI researcher, because what researchers are really good at optimizing for [is] metrics,” says Perez. “But what is this metric that we are optimizing for? Like, it’s something so subjective.” The user interface K2, Krea’s new model, seems impressive on its own. But what makes it so attractive is how Krea will let you use it. On the baseline, Krea promises that just describing what you want will get you better results with K2 than its competitors. Then Krea’s user interface lets you really get your hands dirty in tuning the output. You can drag one or multiple images you want into the prompt bar, to use that to influence the style it generates. Then you can drag a slider up or down on those images, to signal how much you want them to influence the visual style. You can even build a mood board to inform the aesthetic that you’re after. (After generating some images, Krea will proactively produce a sort of personalized Pinterest board with more images it thinks you’ll like.) Because this system is built for creatives, Krea is also being careful with how it frames up IP. As you ostensibly train your own model inside Krea, you can remove that from Krea’s own model training. And all IP generated is your own. So if you are an oil painter who has a very particular style that you want to use within gen AI media, you can upload your work to reproduce it without worrying that Krea is about to sell that as a filter to someone else. Longer term, Krea is considering if there are ways to credit artists whose IP measurably influences a piece of media, and they’re experimenting with using AI to do just that to create a more sustainable royalties system. Rodriguez admits some confusion as to why, in an industry dominated by OpenAI, Anthropic, and Google, smaller AI companies aren’t banding together in order to build bigger ideas and share the wealth. Originally, Krea tried partnering with a model company that refused to offer even a small split of revenue, which led them to develop the technology completely in-house. But now, I can’t help but notice how much Krea’s ambitions have grown. Perez declares that this launch product, K2, is “conservative.” The GPU cluster Krea is using for a year, over which time it will have trained K2 and two future Krea models, will cost the company $20 million. Krea couldn’t afford to faceplant with an experimental approach that might not work. However, with a success under their belts, they feel more confident to take more risks and challenge training norms. “We just wanted to make it work,” says Perez. “It worked way better than we expected, but this was an extremely risky bet. We’d never trained a model before. We didn’t know how hard it would be. And it was it was fucking hard, but at the end of the day we figured it out. And now we know so many things—because there’s so many things about training a model that you can only learn through training a model.” View the full article

If you were to travel back in time to 1996 with a 2TB thumb drive, you’d be able to fit the entire World Wide Web on it. Of course, that kind of storage didn’t exist in the ’90s, so it’s never been that simple for the Internet Archive. The nonprofit site, which launched three decades ago this year, went from making copies of the web on tape drives to storing more than 1 trillion pages worth of Internet history at data centers around the world. Using its Wayback Machine, anyone can look back to what a web page used to look like, which means you can browse through old GeoCities websites, view Google’s original Code of Conduct (back when it still said “Don’t Be Evil”), or read the EPA’s climate change indicators before the The President administration scrubbed them. All that’s on top of the Archive’s vast collection of other digital resources, from live concert tapings and public domain e-books to troves of forgotten DOS games. Roughly 2 million people access the site’s resources every day. “We want it all,” says Brewster Kahle, the Internet Archive’s founder and chairman. “We want all the public works of human beings. So if we don’t have it, we want it.” But while the Internet Archive hasn’t fundamentally changed over the years, the Internet itself is transforming in ways that jeopardize the nonprofit’s mission. Web publishers have started blocking the Wayback Machine out of fear that AI companies are scraping the material. A legal battle with book publishers ended with the Archive paying a settlement and removing more than 500,000 books from its collection. Meanwhile, the cost of storing humanity’s digital footprint keeps going up, as demand from AI data centers drives up storage and memory prices. All of which makes Kahle wistful for how things used to be for the Internet Archive, before book publishers, tech giants, and the legal system got in the way. “We have to still try to make a library work, even though it’s a difficult, difficult time for libraries,” he says. The Internet Archive isn’t just a way to access old web pages, important as that may be. It’s also a repository for information and culture that anyone can access, download, and do what they please with. In a world where digital content is increasingly licensed rather than owned, that in itself seems like something worth preserving. How it started Kahle had been dreaming of something like the Internet Archive long before it became feasible. In the early 1980s, he studied AI at MIT and became a lead engineer on supercomputers at Thinking Machines. The modern internet wasn’t born yet, but he recalls imagining that these supercomputers would someday make reference materials readily available to anyone. “For me, back in 1980, the idea was to try to build this thing that we’d long since promised by then, which was the Library of Congress on your desk,” he says. The real epiphany, though, came in 1995 while Kahle was visiting the offices of AltaVista, one of the first Internet search engines. While early work on the internet had focused on decentralized protocols, AltaVista had built something useful by providing a hub of all the Internet’s knowledge. Kahle realized the same crawling technology could help make full copies of web pages for archival purposes, which AltaVista wasn’t interested in doing. “I thought that the key was making sure that the works of humankind would be preserved, so we went off to collect it,” he says. Kahle kicked in some of his own money to start the Internet Archive—he’d sold an early web publishing system called WAIS to AOL for shares worth $15 million, after spinning it off from his work at Thinking Machines—and got some help from outside backers. But the real heavy lifting came from Alexa Internet, the for-profit traffic analysis company that he founded at the same time as the Internet Archive. For every web page that Alexa crawled, it donated a copy to the Internet Archive, and Kahle made sure that arrangement endured even after Amazon acquired Alexa for $250 million in 1999. Amazon quietly contributed to the Wayback Machine for more than 20 years, until it shut down Alexa Internet in 2021. (The Alexa name, which was based on the Library of Alexandria, lives on as the name of Amazon’s virtual assistant.) “My hat is off to Amazon,” Kahle says. “They could have figured out how to get out of that contract, but they didn’t. So it really gave the Internet Archive, when it was a very young nonprofit, a content set.” Running the Archive The Wayback Machine was rudimentary at first, relying on simple automations to capture the code behind each webpage, preserving what they said and looked like at that moment. Over time, it’s become increasingly sophisticated, with new crawling engines aimed at capturing the growing complexities of the modern web. These days, the Wayback Machine takes snapshots of roughly 1 billion URLs per day. It maintains copies of more than 1 trillion web pages, and stores 100 terabytes of new data per day in the process. Still, Kahle says the Wayback Machine represents only about 60% of the Internet Archive’s data. The rest comes from its vast digital collections, including radio shows, podcasts, defunct mobile apps, DOS games, CD-ROM software, publicly available scientific research, scans of vintage magazines, classic TV shows, past cable news broadcasts, documents scanned from microfiche, and more. Both sides of the Internet Archive share the same computing resources. Despite the scale at which it operates, running the Archive is a surprisingly human endeavor. While the site has tens of thousands of automated processes for archiving the web, its resources are ultimately limited, and it often needs to set priorities, says Mark Graham, the Wayback Machine’s director. “Part of what I do every day is pay attention to this process, through conversations, through examining what we’re archiving and maybe what we’re not archiving,” Graham says. Graham recalls a recent example in which the State Department revealed plans to delete its posts on X from before Donald The President returned to office. He quickly spun up a project with his team and ultimately saved more than 2 million posts, hundreds of thousands of which have since vanished from their original URLs. Graham’s team has also made emergency copies of online publications whose shutdown is imminent, as he did recently with a prominent gaming site (which he declined to identify). “We’re notified almost every day about certain web properties that are going to be shut down,” Graham says. “Often we’ll get weeks or months of advance notice, but sometimes we don’t.” The Internet Archive doesn’t undertake all the work on its own. The group partners with more than 1,400 other groups, including libraries, universities, and museums that help decide what’s worth saving at any given time, and it operates a paid service called Archive-It for groups that want to maintain their own digital collections. Individual users can also archive pages manually through a web form or browser extension, and can even upload files for the Internet Archive’s digital collections. “It’s a healthy mixture of different methodologies, different motivations, different agency,” Graham says. Threats to the archive For most of its existence, the Internet Archive hummed along without much conflict. That’s started to change over the past few years. For the Wayback Machine, the web itself has become harder to archive. The Internet Archive doesn’t save paywalled articles, so it’s missing large swaths of content from major publishers. “It’s gotten a lot harder to do a good job of archiving the public web, because more and more of the web is not public,” Graham says. Some of those publishers have also started blocking the Internet Archive to prevent AI companies from scraping their content. Nieman Lab reported in January that 241 news sites explicitly block at least one of the Internet Archive’s crawling bots, most owned by the newspaper conglomerate USA Today Co. The French newspaper Le Monde has blocked the site as well, while The Guardian has filtered its articles from the main Wayback Machine interface. Reddit also began blocking the Internet Archive last year. Graham says the Internet Archive employs a variety of tactics to turn away AI scrapers, but acknowledges that this requires “nearly constant care and feeding.” Jack Cushman, director of the Harvard Library Innovation Lab, says publishers may be largely indifferent to the work of archivists, at least compared with the more immediate threat of AI repurposing content or putting a strain on their servers. (Cushman’s lab has developed its own archiving tool, called Perma.cc, that it offers to individuals and institutions.) “The upshot is that the doors are slamming shut, incidentally keeping us out, when they don’t really care about us in the first place,” Cushman says. Meanwhile, AI is posing a threat in another way, in that demand from AI data centers is driving up the cost of storage. Kahle says the Internet Archive’s hard drive costs have already tripled to quadrupled as result. “We’re going to have to start becoming really clever about how to go and continue to archive,” he says. And as the cost of storage is going up, a growing proportion of what people consume online involves video on sites like YouTube and TikTok, taking up more space than static images and text. That means the Internet Archive must become even more selective about what it saves. Its YouTube collection is only in the millions of pages, versus more than a trillion web pages overall. “There’s other cases where there is just so much material on a given platform or service that we don’t have the capacity,” Graham says. Outside the realm of archiving the web, the Internet Archive’s digital collections have become a source of legal trouble. Book publishers sued the group in 2020, after it started lending out digital scans of physical books as a response to the COVID-19 pandemic. That resulted in an undisclosed settlement and the removal of 500,000 books from the Internet Archive’s collection. The group also settled a separate record label lawsuit over its collection of digitized 78 rpm records, though those remain available. Cushman says that those lawsuits have drawn attention to the well-intentioned risks that archivists take with copyrighted material. While the Internet Archive has typically avoided things that might upset copyright holders, that’s started to change in recent years. “They’ve moved into some things—especially with the pandemic—that really did anger some people with deep pockets, and great lawyers, and so on,” he says. “It makes the edifice a bit tippier in a way that I think that no one would have wanted.” Kahle and the Internet Archive see those lawsuits as a major detriment to its mission, one that further moves all content consumption to a model of licensing and surveillance, rather than ownership. “The United States has just kind of descended into just lawsuits, where in the ’90s, the United States was interested in innovation, and having a game with many winners,” Kahle says. The Internet Archive remains an indispensable resource, Cushman says, one that’s regarded among archivists as something of a benevolent monolith. There’s a playfulness in how it operates—for instance, in offering a playable collection of LCD gaming handhelds—that no one else is doing. But its challenges also make him wish there were more organizations trying to do similar things. “It’s different from anything else that we have,” Cushman says. “So I think we look at it with a mix of gratitude, where we’re fortunate that it happened, and then apprehension because there’s only one of it.” Looking ahead Kahle built his life’s work around digitizing the world’s knowledge and even using AI to make it more accessible. Now that future is finally materializing, but in a way that is, ironically, concentrated around a handful of well-funded tech companies, media conglomerates, and publishing giants. As a young engineer, that possibility was never on his radar. “I didn’t predict the monopolies,” he said. Kahle still sees AI as an opportunity to sort through the Internet Archive’s vast stores of data. Researchers are already using it, for instance, to do things like interpret key talking points on Russian newscasts, and the Internet Archive has been leaning on AI to help digitize and translate more content. But those opportunities, he says, are increasingly happening outside the United States, where there’s more legal certainty around what libraries can collect and digitize. The European Commission, for instance, is pursuing the concept of AI for the public good, promoting tools that tackle specific challenges like climate change and health care. The Internet Archive Europe, a separate group on which Kahle is a board member, has been backing a open-source tool called ClimateGPT that applies large language models to climate research. “There could be hundreds of innovative organizations going and conquering all sorts of niches, if they had the same kinds of policies in the United States that we had in the 1990s when we let search engines happen here,” Kahle says. Still, Kahle says he’s not discouraged, because fundamentally people want their works to be read and preserved. They also want good information that’s easily accessible, which is why the Internet Archive is being used now more than ever. And while the Internet Archive was born from the idea of centralizing the world’s knowledge, lately it’s been sponsoring conferences on ways to decentralize the web again. It’s early days, but he’s hopeful that this will lead to new business models that recapture what once seemed possible 30 years ago. “Let’s build systems that support communities,” Kahle says. “Let’s make tools for participation. Let’s build democracy’s library out of all the works that can and should be shared, so we’re all building on a common commons of information.” View the full article

Wendy’s is feeling blue. Light blue, to be exact. In April, a new design concept accompanied the opening of the burger chain’s 100th store in the Philippines. In addition to its digital-first layout, the new Wendy’s boasts a light blue facade instead of a red one. The refreshed restaurants are now available to franchisees across the company’s international markets. Wendy’s tells Fast Company that locations are also open in Chile, England, and Scotland, but there are currently none in the U.S. The blue color scheme is part of an initiative Wendy’s is calling “Future Fresh” that could make one of the brand’s secondary colors more primary if adopted widely. On the company’s May 8 earnings call, CFO Ken Cook, who is also currently serving as Wendy’s interim CEO, said the new store format makes the brand stand out from the competition—and he’s not wrong. Though the shades are different, Wendy’s shares a main brand color with plenty of other fast-food chains, like McDonald’s, Burger King, Jack in the Box, In N Out, and Chick-fil-A. There’s good reason so many fast-food companies are branded with ketchup-colored red: The color can make you hungry. For Wendy’s, though, cool blue isn’t such a leap. Its long-used cartoon mascot (inspired by founder Dave Thomas’s red-headed daughter) is accented in blue, and in the past the company has used the hue for its blue-and-white-striped worker uniforms. Wendy’s new digital-first layout is one that many chains are embracing, as in the rise of self-serve kiosks at McDonald’s or Chick-fil-A’s mobile-only store in New York City. Starbucks, on the other hand, has moved away from the grab-and-go concept with café renovations designed to entice customers to stick around. The coffee chain announced last year it’s closing its pickup-only locations in favor of a new store concept with cushier seating and laptop-friendly tables ideal for remote workers. Instead of investing in a cozier dining room or bringing back its salad bar, Wendy’s is catering to mobile orders and grab-and-go customers with its new store design. Wendy’s announced last year that it would close hundreds of U.S. restaurants, and there’s an effort to try and take the company private. Internationally, though, the Ohio-based chain is still expanding, meaning more locations overseas could open with the blue building. Cook said last week the company signed new franchise agreements to build up to 1,000 restaurants in China over the next decade. Wendy’s last rebranded in 2012, removing long-running brand identifiers like the color yellow, vintage-style typography, and its “Old Fashioned Hamburgers” tagline. The modernized logo and sterile restaurant designs fit trends at the time, but also lost the nostalgic feel of a fast-food chain where you could once enjoy Frosties and chili served in bright yellow cups while sitting in a sunroom. Architecturally, the sanitized, modern “Future Fresh” building doesn’t unbland what Wendy’s has blanded—but at least light blue isn’t greige. Wendy’s didn’t respond to a question about how widely the blue color scheme might be adopted, but by making the color more prominent, Wendy’s would at least ensure its restaurants are never confused for those of its competitors. View the full article

For most of the last century, we believed human potential could be measured through intelligence, and we built whole institutions around that belief. IQ was the metric. If you were analytical enough, technically proficient enough, quick enough on your feet, doors opened, schools rewarded it, employers screened for it, and entire industries grew up around identifying and elevating it. Then we noticed what intelligence alone couldn’t do. Technical brilliance without humanity tended to create distance rather than trust, and a generation of leaders who were brilliant on paper proved unable to inspire the people around them. So we elevated a second form of intelligence, emotional intelligence (EQ), the capacity to listen, to empathize, to read a room, to understand people and not just information. For a while it felt as though we’d found the right equation. Artificial intelligence is forcing us to rethink the equation again. For the first time in modern history, we are dealing with systems that can outperform aspects of our own intelligence at scale. AI can synthesize enormous bodies of knowledge in seconds, and it can simulate emotional fluency convincingly enough that the line between authentic empathy and a well-tuned response is starting to blur. That raises an uncomfortable question: if intelligence can be generated and emotional fluency can be simulated, what’s left that is distinctly human? My answer is that the future will belong to people who cultivate not two quotients but five, IQ, EQ, TQ, WQ, and most importantly VQ, the Vision Quotient. In an age of artificial intelligence, vision may turn out to be the defining human advantage. TQ: The Trust Quotient Trust has become one of the most undervalued forces in modern life, partly because we talk about it as though it were something soft, likability, familiarity, a warm handshake. It’s none of those things. Trust is earned credibility under pressure. It is the confidence other people place in you when uncertainty rises and the stakes get real, and it is built slowly and lost quickly. In an environment flooded with misinformation, manipulated narratives, deepfakes, and algorithmic distortion, trust is no longer soft currency, it is closer to infrastructure. Institutions run on it, markets depend on it, and leadership without it doesn’t survive contact with a real crisis. AI may eventually simulate reliability in narrow ways, but it cannot carry moral accountability. Machines do not wrestle with conscience or sacrifice or the cost of being wrong. Human beings still decide whom to trust when the outcome actually matters, and they make that decision based on a track record only another human can build. WQ: The Work Quotient Hard work has quietly fallen out of fashion. We celebrate optimization, leverage, automation, and balance, and all of those are real virtues, but somewhere along the way many people started mistaking convenience for achievement. Work ethic isn’t performative exhaustion or the cult of the grind. It’s the discipline to carry a piece of work all the way through to completion, long after the excitement of starting it has worn off. Ideas are abundant; execution is rare; the gap between the two is almost always filled by someone willing to do unglamorous work for a long time. AI complicates this picture, because artificial intelligence has, for practical purposes, infinite stamina. It runs continuously, at speeds no human can rival, and it doesn’t get tired or distracted or discouraged. So if machines can outwork us mechanically, what becomes valuable about human work? Not volume. Commitment. Human work carries judgment and ownership, the ability to notice when something feels wrong even when the metrics say it’s fine, the willingness to take responsibility for an outcome rather than a task. A machine can process indefinitely, but it cannot care about a mission, and that turns out to be the part that matters. A lot of people are approaching AI exactly backwards. They are trying to beat machines at the things machines are being optimized to do: faster analysis, faster synthesis, faster production, faster output. That is a race no human will win, and it isn’t the race worth running. The real opportunity is to deepen the human capacities machines cannot meaningfully replicate, judgment, intuition, ingenuity, foresight, the ability to imagine possibilities before the evidence has caught up. This is where the conversation actually changes. VQ: The Vision Quotient Every transformational leap in civilization began with someone seeing what other people couldn’t yet see. An inventor pursued what colleagues told him was impossible. An entrepreneur built for a market that didn’t exist. A scientist trusted a hypothesis years before the data could confirm it. A statesman imagined reconciliation in a place where everyone else saw permanent enmity. History does not move forward because we process information efficiently. It moves because certain people can see around corners, and that capacity is what I mean by VQ. The Vision Quotient is the human ability to perceive possibility before proof exists, to connect intuition with imagination, to sense an emerging reality before the world has named it, to commit to something that data alone could never predict. AI may eventually generate sophisticated questions by detecting patterns in massive datasets, but generating questions is not the same as envisioning a future. Machines optimize the known. Human beings create what has not existed before. That distinction matters more than it might first appear. Artificial intelligence is trained on existing patterns and existing realities, and its outputs, however impressive, are extrapolations from what already is. Human vision often works by defying what is. The greatest discoveries in history rarely began with consensus; they began with people willing to imagine past what the world believed was possible at the time. No machine independently dreamed of flight. No algorithm envisioned democracy. No software set out to cure a disease before science understood the mechanism. Humans did, and they did it without infinite information, they did it with imagination, conviction, and the willingness to be wrong in public for a long time. The New Test of Leadership The leaders who thrive in the coming era will not just be the smartest people in the room or simply the most emotionally polished. They will be the ones who can hold all five quotients at once: IQ to understand complexity, EQ to connect with people, TQ to earn lasting confidence, WQ to execute with discipline, and VQ to imagine futures others cannot yet see. That combination is rare, but history has always belonged to rare combinations. Artificial intelligence will probably, in time, write faster than we, calculate faster than we, diagnose faster than we, and persuade faster than we. It will generate endless answers and reasonable simulations. What it will not do is independently envision a future that does not exist and summon the courage and sacrifice required to bring that future into being. That is why VQ will ultimately become the most important quotient of all. Because while AI may help optimize the future, only human beings can truly create it. View the full article

Layoffs used to be something that made a company’s stock tank. But after Block announced layoffs recently, its stock went up. And they weren’t the only ones: Snap did the same thing a few months earlier, as did Meta and Amazon. The common thread? They all cited AI as their reason for cuts. For CEOs staring down investor pressure, the playbook has become clear: invoke AI, slash headcount, and watch the ticker go up. I’m a CEO, and I’ve been laid off before. I now advise HR and benefits leaders at Fortune 500 companies as they plan, execute, and move forward after making workforce cuts. Here’s why I’m cautioning fellow executives against jumping on the “AI” layoffs bandwagon without thinking about it from every angle. Many ‘AI-driven layoffs’ aren’t really about AI A recent Goldman Sachs survey found that only 11% of clients were reportedly cutting jobs due to AI, while LinkedIn’s hiring data signals that AI isn’t directly leading to the hiring slowdown… yet. Some of the cuts we’re watching this year are mostly about overhiring in 2021 and 2022, a cooling economy, softer consumer demand, and product bets that haven’t paid off. But those reasons don’t sound all that glamorous on an earnings call; AI does. As Tech investor Terrence Rohan put it plainly in a recent interview: “Pointing to AI makes a better blog post. Or it at least doesn’t make you seem as much the bad guy who just wants to cut people for cost-effectiveness.” It’s hard to tell today where AI is the root cause of layoffs and where it’s basically a nice narrative wrapper. But here’s the problem: Your layoff story travels further than your stock pop. Having personally experienced a layoff, I know how painful and disruptive an involuntary exit can be. And, as a CEO who reports to a board every quarter, I still have to make hard calls like any executive. But how you make them and what you say about them is the part that matters. With that in mind, this is what leaders need to keep in mind when they are faced with communicating these difficult decisions.\ Remember what a layoff really means for all your employees How you explain a layoff matters more than the explanation gets credit for. For departing employees, remember they haven’t just lost a job and their income. They’ve also lost, in most cases, many other fundamental lifelines: health insurance, life insurance, retirement contributions, disability protections, and more. That’s before you count their daily routine, sense of purpose, and community. For the remaining employees: They know which teams got cut and what those people were working on. They’re nervous and they’re watching. The story you put in front of the market is directly telling your team what kind of company you are now and in the future. So how you talk about the decision and how you treat their departing colleagues speaks volumes, and directly translates into morale for the weeks and months ahead. In communicating any cut, the best leaders treat both classes of employees with the seriousness and respect they deserve, not as a transaction that might give them a stock boost. Your internal and external story should be one and the same If you told the market the layoff was about AI, and your people know it was about a missed product launch, you’ve just taught your company that leadership says what’s useful, not what’s true. That lesson doesn’t stay contained to one announcement. With the companies I see handling layoff announcements well, the words on the earnings call match the words in the exit packet. Departing and remaining employees alike see and hear an explanation they can understand and that makes sense to them, no matter how painful. And they also experience and witness a compassionate exit process, because treating them with dignity softens the pain of being on the receiving end of this decision. Remember: Investor praise ≠ public perception Most of us can recall a cringe-worthy public layoff gone awry. But when Perplexity’s CEO brushed off the severity of layoffs, the public backlash was swift. The counterintuitive truth about AI’s rise is that the stakes on brand perception are only on the up and up. As more companies build on the same small set of foundational AI tools, product output is starting to look the same. What you say and how you behave matters more, not less. While ChatGPT emerged as the dominant force, now Claude is making considerable headway, especially in enterprise sales. The consensus for why this is largely points to how the two position themselves and what they stand for, from Anthropic’s public fight with the Defense Department over model guardrails to OpenAI’s decision to run ads in ChatGPT. Buyers paid attention and they moved their money. Buzzwords and bandwagons are tempting to jump on, especially when every company is racing to prove it’s “AI-ready,” but they don’t always resonate with customers, employees, and enterprise buyers paying attention to a lot more than your earnings call. Be honest about what’s really driving these cuts If your cut is driven by macro conditions, say that. If a product was a total flop, say that. If you overhired during a bullish period, say that. The reality is, layoffs are a regular thing for any corporation, and none of those reasons are disqualifying. To Terrence Rohan’s point: saying it’s just AI may make you feel like less of the bad guy, but the effect is actually the opposite. What erodes trust is dressing up legitimate reasons in a scapegoat explanation because the market prefers that version. If AI is genuinely part of your cut, be specific about it It’s very possible, even likely, that AI plays some role in the cuts you’re making. But there’s rarely a time when it’s defensible to make your people feel replaceable. There’s a real difference between saying “we’ve invested heavily into AI and are restructuring around that shift” and “we’re replacing 400 human support roles with a trained model.” Most companies are doing the former but signalling it’s the latter. That’s where the trust breaks down. AI will reshape a lot of work over the next decade, and as the market absorbs it we’ll see more layoffs legitimately tied to it. That’s why it’s even more critical to be honest, clear, and specific now. For better or worse, most of us in leadership will have many more of these moments for quarters and years to come. If you make a habit of dressing up normal business decisions with a glitzier costume, sooner or later it will come back to bite you. How you talk about making cuts is the part that people actually remember, long after your stock is back to normal. And in the meantime, the people inside your company are listening. View the full article

Tor Myhren is going to kind of hate this article. Because it’s about him, not his entire team. Because I want to talk about his shift from agency chief creative officer to leading marketing for the most pristine marketer on the planet, not to mention one of the world’s most valuable companies. Because I want to talk about how he’s been doing it for 10 years in an industry where brands change senior marketing executives as frequently as their socks. And because I want to start with the worst moment of his decade at Apple. At the time, Myhren had a singular focus. In early 2024, Apple’s VP of marketing communications was sitting with his team, thinking about how they should approach the rollout of the new iPad Pro, Apple’s thinnest and most powerful iPad to date. Myhren, whose job it is to help sell the products of one of the world’s most profitable and beloved gadget makers, zeroed in on an idea. “The idea was about the thinnest product we have ever made, and in the making of it, all I could see was thin, thin, thin,” Myhren says. The team ended up releasing a spot in May 2024 called “Crush.” It depicted a collection of creative tools—turntables, a piano, The Presidentet, cans of paint, a sculptured bust, an old arcade game, a mannequin for fashion design, a writing desk, camera lenses—all piled up in an industrial compactor. Then, to the melancholy tune of Sonny & Cher’s “All I Ever Need Is You,” the objects were slowly and methodically crushed into the iPad Pro. The ad bombed. It went viral for all the wrong reasons, and exposed a major blind spot for Apple. “Crush” aired in the early days of the AI hype cycle, and the ad fueled fears that new technological capabilities would replace creative professionals of all stripes and lead to massive job losses. Barely 48 hours later, Myhren publicly apologized for the spot and it was pulled. “When the world saw something other than what we intended in it, it was impossible to unsee,” Myhren recalls. Apple isn’t accustomed to making bad advertising. Ever since Steve Jobs and TBW\Chiat\Day’s Lee Clow created the iconic “1984” Super Bowl ad, Apple has been thought of as a world-class brand marketer. “Crush” was both a reality check and a gut punch. Soon after the ad was pulled, Myhren gathered his team in Menlo Park, and many of the global teams virtually, to talk about it. His message? This wasn’t the end of the world. More important: It wasn’t the end of creative experimentation at the brand. “If we start to play this game with fear, or get soft on our marketing, it’s going to hurt the brand a lot more,” Myhren told his team at the time. The pep talk wasn’t just for show; it was Myhren replanting the flag for how he expected his team to operate. When Myhren started in 2016, Apple was roughly a $540 billion company. Today, it’s worth around $4.3 trillion. He has overseen the marketing department during a period of hyper-growth for the company. As Apple’s products and ambitions have expanded into new categories like TV, headphones, watches, and services, its marketing efforts have kept pace. Myhren has built his success on ambitious creative consistency, and yet as he enters a new decade at Apple, he’s staring down big changes. In the fall, John Ternus will replace Tim Cook as CEO. At the same time, Myhren—like all heads of marketing—must grapple with AI-driven technologies that are upending traditional marketing and advertising. In this exclusive interview, I talk to Myhren about his first moves to meet the demand for faster brand work, why he believes in the “nail theory” of effective product advertising, the magic formula for AirPods advertising, and the one thing he didn’t change about how Apple works—even after “Crush.” “I’m super optimistic about the future of marketing,” Myhren says. “Forget five years. I think it’s going to be radically different in three years. Radically, radically different. And anyone who says they know what that’s going to be, they’re lying.” The Beginning When Myhren joined Apple as its VP of marketing communications in 2016, it came as a bit of a shock to the ad industry. Over the previous decade, Myhren, as chief creative officer, had transformed Grey Advertising, with its stodgy, old-school reputation, into one of the leading creative agencies on the planet, thanks to work like the now-legendary long-running E-Trade baby campaign. “At that time, there was no real precedent of an agency creative making a move like this,” Myhren says. “I foolishly thought my global role in a big agency network would prepare me for the size of Apple. I was wrong. It was a totally different scale and scope.” Michael Houston—former CEO at Grey, and currently the outgoing U.S. president of WPP—was Myhren’s boss at the time. He remembers exactly when Myhren told him he was leaving the agency. It was late 2015, and they were in a car skirting Switzerland’s Lake Geneva. They had just finished their annual “top-to-top” meetings with the leadership of Nestlé. By all measures, it had been a wildly successful meeting. When Myhren joined Grey New York in 2007 it was known as a Death Star of old-school advertising. By 2015, at the height of the agency’s turnaround, Grey had won 113 Cannes Lions across its offices in 18 countries. Everything was clicking. But on that drive, Myhren turned to Houston and told him he’d been speaking with Apple CEO Tim Cook. He was going to Apple. And that he wouldn’t have left the team at Grey for any other company. “Beyond processing the shock of the news, I remember sitting there thinking that the very things that had just made our . . . meeting so successful were the exact things that would make him right for Apple,” Houston says. A few months after Myhren returned from the Geneva trip, he packed his bags and moved to Cupertino, where he took over one of the most sophisticated marketing machines on the planet. Media coverage of the move aligned with Myhren’s assessment: It was an unusual move for an agency creative. But at the time, fellow ad legend David Droga told Adweek, “I think it’s a really great move for both parties, and only good things can come from this.” Apple could have gone in any number of directions in 2016 when looking for a new leader for its marketing communications division. R/GA was on a hot streak, and Nick Law, its chief creative officer, would’ve been an option. (Myhren brought on Law at Apple in 2019, where Law worked until late 2021.) Airbnb CMO Jonathan Mildenhall was also ascendant; he had joined the Silicon Valley company in 2014 after leading marketing and design for Coca-Cola in North America. But Myhren was a rare mix: He was an incredibly successful advertising creative who also grew his clients’ business, won all the awards, and did it in a quietly efficient way that never made him the star or focal point, which Apple undoubtedly appreciated. Houston describes Myhren as an exceptional listener, an introvert, a leader who understands the value of creative risk and that great work is a team sport. “More than anything, he’s one of the most effective motivators I’ve ever worked with,” Houston says. “He creates direction. Clarity. Which makes others willing to take the journey with him.” Solid Foundation In 1997, Steve Jobs introduced Apple’s “Think Different” tagline and its now iconic “Crazy Ones” ad campaign at an internal company meeting. As he spoke to a small audience about the campaign, Jobs articulated perfectly the role of marketing and advertising for the brand. “This is a very complicated world. It’s a very noisy world, and we’re not going to get a chance to get people to remember much about us. No company is,” he said to a half-full auditorium. Jobs and his creative team knew they had one shot to make an impact. The brand would have to be very clear in what it wanted people to remember. Instead of focusing on speeds, feeds, and other product details, Jobs said the brand’s core values would be at the center of everything. “Apple’s core value is that we believe that people with passion can change the world for the better,” he said. Jobs instilled that value into the brand work—so much so that it became part of the company’s DNA. And it was still going strong when Myhren got there. Myhren says his start at Apple was unique in that he wasn’t brought in to fix a stalled or sinking ship, as so many new marketers are. “I stepped into a company that, from a marketing standpoint, has just been rock solid forever, which in some ways is a little intimidating,” he says. His job was not only to steer the ship, but also to make sure it was being prepared for the future before it had to be. He points to the long-term relationship with Apple’s primary agency partners TBWA\Media Arts Lab (MAL) and OMD, as a huge reason he was able to settle in so quickly. “That working relationship was already solid, and I had come from that world, so I do think I was able to help instigate some changes that made MAL an even better fit for marcomm [marketing communications] that I was envisioning going forward, and the kinds of skills that we were going to need,” he says. Preparing for the future in 2016 meant supplementing agency work by building out internal advertising and content capabilities to match the ever-growing, always-on demand of a modern global brand. Soon, Myhren was enacting that vision and adding those skills. “I inherited the best design team in the world, and an incredible interactive team,” he says. “What I was able to bring to it was to build on the advertising side of things. So we did bring in some advertising folks after I got here and started doing a lot more advertising out of marcomm.” In order to keep up with the ever-increasing pace of brand work, he also brought in more “makers”—including CGI artists, directors, and editors—and established a production warehouse to create more content internally rather than relying solely on outside agencies. The first piece of work that really had his stamp on it was 2017’s “Stroll,” for AirPods. While it paid homage to the classic DNA of Apple’s music marketing—specifically the dancing and neon of the iPod/iTunes era—it added a modern edge, featuring street dancer Lil Buck in black and white. It was also the start of a clear formula for AirPods advertising. “If you think about all the spots, it’s music-plus-magic-plus-dance-equals-AirPods,” Myhren says. “It started with ‘Stroll,’ but then think about ‘Bounce,’ think about Pedro [2025’s “Someday”], and that’s what it is.” One thing Myhren didn’t change—and still hasn’t—is that Apple doesn’t market test its advertising. “You might not believe this, but we make almost all of our decisions through gut instinct,” he says. “When you talk about brand guardrails, there’s no book that says this is right or wrong. It is all gut. And I think it always has been, because we don’t test our work. At the end of the day, we put something into the world and it is gut, ‘This feels like us.’ This is capturing the product in a way that we want to, and we feel really good about.” For Myhren, and Apple more broadly, no one knows the brand better than the brand itself. Many, like Myhren now, have been at the company for many years. Even its primary agency partner TBWA has been working with Apple since 1984. “There are a lot of really smart people at Apple that have been at Apple for a long time,” Myhren says. “And so you’re always bouncing ideas off folks that have been there, that really know it, and do have their own set of guardrails.” That often leads to work that still does what Jobs set out to do—cutting through the noise in a complicated world. The flip side of instinct, however, is that sometimes the gut is wrong. Case in point: “Crush.” “The only other thing I will say about that is it was a bit heartbreaking to me as someone who has spent so much of my career trying to empower creatives and creative people and creative thinking,” he says. “To have something be seen as potentially harmful to the creative spirit was really tough for me.” A decade of work Apple’s marketing has always been product-led, but Myhren’s run has evolved the idea of the elevated product demo to unprecedented heights. “Crush” clearly stands out for its own reasons, and I’m on record for being no fan of 2023’s “Mother Nature,” or the Bella Ramsey AI spots in 2024. But over his decade at Apple, Myhren has steered more hits than misses, and has kept the company a step ahead and above most major marketers. He credits an almost maniacal commitment to making the product the star of any ad or brand work. “So many brands will start with culture and say, ‘What’s happening in culture? What’s happening in pop culture? What’s the trend right now?’ And that’s actually the starting point, and they work backwards,” he says. “We always start with the product. What is it about the product? One of the reasons we do that is we don’t want to do stuff where you remember the ad, but you don’t remember the product. In our best work, those two things are just synonymous together. When you’re talking about the piece, you’re talking about the product.” This approach shines in work like 2019’s “The Underdogs,” a tech ad-as-sitcom that seamlessly weaves an insane number of products into an impressive level of entertainment value. But Myhren also points to “Relax, It’s iPhone” which originally launched in 2021. “What stands out to me is taking one feature of a new phone that has 20 great new features and just zeroing in on it,” he says. He credits Tracy Wong at Wongdoody, who told him once that ads are like when you step on a bed of nails: Nothing penetrates because there are too many nails. It’s the same with advertising. If you step on that one nail, it’s going to make an impact. For 2022’s “The Greatest,” director Kim Gehrig beautifully dramatized Apple’s accessibility features across its products like VoiceOver, AssistiveTouch, Live Captions, Magnifier for Mac, and Braille Access. “These are seemingly small features that are radically changing people’s lives, and that’s what we try to bring to life,” Myhren says. “There’s an old belief that too much product makes for boring advertising, but I just don’t buy it. Again, I think that the product is like a character in the story. You couldn’t pull that product out and have the same story.” The ultimate product demo campaign is, of course, “Shot on iPhone,” which began in 2015 as an outdoor campaign that featured 77 photos from 73 iPhone users in 25 countries on billboards around the world. Under Myhren, it evolved to include full short films directed by Oscar-winning filmmakers. But despite the talent pedigree involved, it’s still a product demo. “Every single element of it and every piece we put out is evidence, not advertising,” Myhren says. “It’s just evidence of an amazing camera.” Myhren’s latest push on the brand’s edges is its move to finally have something to say on TikTok. The recent work made a splash aimed at Gen Alpha for the new Macbook Neo. It’s cute, colorful, and has spawned a new brand mascot people are calling Lil’ Finder Guy. “We’re not in the volume game; we try to stay in the quality game,” Myhren says. “I’m not saying that it always works and that it’s always great, but we kind of want to speak when we have something to say. And I think the MacBook Neo launch is a perfect example of that, of a perfect time and perfect audience to do a real deep dive into TikTok and pick our moment.” Perhaps one of the most underrated strengths of Apple’s marketing and advertising is its consistency. It doesn’t bounce around from vibe to vibe, trend to trend. It speaks its own language at its own pace. “Shot on iPhone” has been running for more than a decade, “The Underdogs” went for seven years, the brand’s privacy campaign has been going for seven years, and “Relax, it’s iPhone” is clocking in at six years. In an increasingly ephemeral culture, at its best brand consistency breeds familiarity, trust, and legacy. That is what Apple will need to draw on as its markets quickly evolve across new challenges, in AI and beyond. Collaboration and consistency One of the first things Myhren says when we start talking about his decade at Apple is that this milestone is definitely not just about him. He sees himself as a collaborative leader, someone who is able to bring together a variety of elements to create something successful. Brent Anderson, global chief creative officer at TBWA\Media Arts Lab, says that when presenting work to Myhren, he can regularly be heard asking any number of direct, sharp, and clarifying questions. “He’ll bluntly ask why anyone would care or pay attention to the idea in question, or how your idea is different than what someone else other than Apple could do. Or he’ll say that he thinks a particular idea could be good but will ask if we really think it can ever be great,” Anderson says. “If an idea survives this gauntlet of interrogation, he then provides the support and the trust that our teams need in order for the creative output to get to great.” Internally at Apple, getting to great has meant growing international creative teams as well as the brand strategy team. Myhren has added more internal editors, writers, and other makers. He also knows that it’s a blessing to be at a brand that major Hollywood directors and global artists actually want to work with. He sees collaborators like directors Spike Jonze, Damien Chazelle, David Shane, Mark Molloy, and Kim Gehrig, and artists like Billie Eilish, Lady Gaga, and Olivia Rodrigo as essential to maintaining the brand’s “human touch” in a technology-saturated market. The success of Apple’s brand work is down to a collective of these big names, his internal team, and the external agency partners like MAL and OMD. “What’s most impressive about his run at Apple is that he’s proven something very few people can—that creativity doesn’t have to get diluted at scale,” says Houston, his former boss. “In the right hands, it can actually get stronger.” Most chief marketers who have come over from the ad agency world do so from account management, the folks who are the bridge between the brand’s business and its creative. But in hiring a CCO like Myhren, Apple knew it was getting a guy who liked to be as close to the work as possible. Someone with the creative eye and instincts to build on the foundation it already had. When I ask him to explain his longevity at Apple, Myhren says one key aspect is that it’s actually a very patient company. “I’ve learned a lot from that because I wasn’t a patient person coming into Apple,” he says. “And then you realize, hey, you don’t have to always be first; you have to be best. Take your time. No big rush. It does help to know that you can let it play out a little bit.” In an industry and culture overwhelmed by a spinning news and culture cycle, now awash in the onslaught of AI-infused work, that’s definitely still thinking different. View the full article

A review of the overnight sleeper train service from Hanoi (Vietnam) to Nanning (China). The Hanoi to Nanning train is the only international service from Vietnam, and one of the few international train services in Southeast Asia. There is also a Hanoi to Beijing train that is a continuation of the Nanning service. For this article I am reviewing the Hanoi to Nanning section, which includes details on the border crossing. Buy tickets for the Hanoi-Nanning train Tickets can be bought online at the official site (dsvn.vn) and at Baolau (Nomadic Notes is an affiliate of Baolau). If you are booking on the dsvn.vn website, look for Gia Lam (for Hanoi) and Nam Ninh (for Nanning). Baolau also allows you to book the onward service to Beijing. Usually when you buy tickets online in Vietnam, you will get a PDF copy of the ticket sent to you by email. For the train to Nanning, you need to collect the ticket at the station. The ticket office will check your passport and make sure you have a visa (if required). China has expanded visa-free travel for more countries, so if you are eligible you no longer need to apply for a visa. The tickets are in Vietnamese, Chinese, and Russian. This is a real relic of the past to have a ticket with no English on it. The ticket is also old-school with the stapled booklet of multi-page carbon paper tickets. Gia Lam (Ha Noi) The train departs from Gia Lam Station and not Ha Noi Station. The easiest way to get there is by Grab taxi, and allow about 30 minutes to get there from the old city. Gia Lam Station is an unassuming station in a small street. There aren’t many food options in this area, so have dinner before you arrive and stock up on snacks. It’s a small waiting room with no cafe, so it’s not the best station to hang out at. Passengers are allowed on 40 minutes before departure, so I was glad to be there early to claim my bed. Note the dual gauge railway track. Vietnam Railways operates on the metre gauge, while this train from China is on the standard gauge (1435 mm). The obligatory photo in front of the destination plate. Onboard Vietnam railway stations are not accessible if you have mobility issues, and it’s a steep step to get into the carriage at Gia Lam. The ticket inspector takes your ticket and puts it in a little folder, and swaps it for a boarding card. You get your ticket back before arriving in Nanning (just in case you wanted to keep the ticket). The train is all sleeper cabins, so there are no seats if you were looking for a cheaper option. The tickets are Soft Sleeper 4-Berth, and there is no price difference for upper or lower. I requested a Lower Berth when booking on Baolau. I was surprised to see that you get two pillows and a duvet (unlike the one pillow and blanket combination that you get on Vietnam Railways). There are power outlets under the communal table, so this is a slight advantage for the lower berth passengers. The mattress was comfortable, and I was able to fit in the bed without touching the wall. I’m 185 cm (6’1″) and I don’t fit in some Thailand sleeper trains. There is also enough room to sit up on the upper and lower beds. The beds are permanent (like Vietnam and unlike Thailand where they are folded away in the day time). There is no food service on this train, so come prepared. I had dinner in Hanoi and brought some snacks. I was sharing the cabin with a young Chinese couple, and they asked if it was ok if they eat noodles in the room. They also bought me a packet of chips, so it was nice to be travelling with these polite youngsters. Pot noodles are the national travel food in China, and you will always find hot water at airports, train stations, and on trains. The toilet was clean and spacious. And there is also a separate wash area. Vietnam to China border crossing I would have slept well on this train if it wasn’t for the fact that it is interrupted by a long border-crossing procedure in the middle of the night. I saw the timetable at Gia Lam, and I couldn’t work out why there were such long gaps at the border crossing. The train departs Gia Lam at 21.20 and arrives at Dong Dang at 00.55 (3h 35m). At Dong Dang Station, you get off the train with all of your luggage and go through Vietnam immigration. I estimate there were about 100 passengers on the train, and everyone was processed within an hour. Perhaps they have scheduled a 1h 55m stop in case the train is full and there are processing delays. The train leaves Dong Dang at 2.50 and arrives at Pingxiang (Bang Tuong in Vietnamese) in China at 4.31. China is 1 hour ahead, so that is a 41 minute trip. At Pingxiang Station, you get off the train again with all of your luggage and go through Chinese immigration. Visa-free travel for Australians made this trip much easier, but no one mentioned that there is an online arrival form to fill out (it would have been handy if this was mentioned in Hanoi). I activated my esim but it took a while to activate. An immigration officer told a foreigner standing next to me to share his internet with me (thanks random traveller!) Here is the online arrival card. Most of the passengers were single men (Vietnamese and Chinese workers), so the random handful of westerners were interviewed while waiting to go through immigration. The interviewers had translation devices and asked the usual questions (where are you going? how long are you staying?) The train leaves Pingxiang at 6.05 (a 1h 34m stop), so overall it took 4 hours and 10 minutes to cross the border. By the time the train leaves Pingxiang it is sunrise and there is 4h 1m left on the journey. Pingxiang to Nanning The Pingxiang to Nanning section is the only daylight section of the trip, so I wanted to see some scenery. The train goes through the region of Guangxi (officially the Guangxi Zhuang Autonomous Region), and it is a scenic trip through limestone mountains (similar to Ninh Binh and Ha Long in Northern Vietnam). Every square metre of flat land is given over to agriculture. I think I nodded off for 30 minutes, but by now the train was getting close to Nanning. The train passed a high-speed train on the way into Nanning. Most of China is connected by high-speed rail by now, so it was good to be on one of these slower green trains. I was talking to a businessman from northern China while waiting for the train at Gia Lam. He was happy to practice his English on someone, and I was happy to get an insight on why someone would get this slow sleeper train. He was setting up a tech business in Hanoi and prefers to travel by train, even though it took him over a day to get there. I did hardly any research about Nanning before I arrived, apart from saving Nanning Station and my hotel in my AMap app. Nanning has a population of over 5 million people, so I was looking forward for some urban exploration. I will have a separate report on my trip to Nanning. Nanning Railway Station The train from Hanoi arrives at Nanning Railway Station. This is the old main station in the middle of the city, and there are plenty of hotels nearby. The main high-speed station is at Nanning East (Nanning Dong Railway Station). Unlike Gia Lam, the platform is level with the train door, so it is possible to place a ramp on the train door. While the train was waiting at Pingxiang, some more carriages were added to the train. These are “Hard Seat” carriages, which are padded bench seats that don’t recline. It’s a shame there isn’t a day train from Nanning to Hanoi with this seating option, as that would be a cheap way to travel to China. At Nanning I got a glimpse of the connecting train that continues to Beijing. I wanted to visit Nanning so I had no plan to continue to Beijing, but I am now curious about getting the Hanoi-Nanning-Beijing service another time. After a few days in Nanning, I continued to Hong Kong on the direct Nanning-Hong Kong service. A foreign couple I met on the train were going straight through to Hong Kong. It’s a tight schedule but it can be done, so I will post another article about how to go from Hanoi to Hong Kong by train. The future of the Hanoi to Nanning train service One of the reasons I got this train (apart from it being a cool travel experience) was that I wanted to experience it in its current form before it is eventually upgraded. It will be years before that happens, but plans are already in motion. Vietnam has invited China to help build three railways to connect the two countries. Two of the railways will be upgrades of old lines (Lao Cai-Hanoi-Haiphong and Hanoi-Dong Dang) and there will be a new line from Haiphong to Mong Cai. China have already built standard-gauge railways to meet these three railways at the border. In addition to the slow train that goes from Nanning to Pingxiang, there is a high-speed railway that operates in the same corridor on another line. I checked for tickets between Pingxiang and Nanning, and the options include the slow train and high-speed railway. The high-speed service is 1h 10m while the sleeper train is 4h 1m. The distance from Pingxiang to Gia Lam is 176 km, so that trip could be feasibly done in an hour. [Train distance table at Gia Lam Station.] If the new train line is built so that the immigration facilities for both countries are in one station, then the border stoppage time could be reduced to one hour. That would then make it a 3-hour trip from Hanoi to Nanning. Until that happens, enjoy the sleepover to China. Read more railways of Vietnam and train travel stories from around the world. Also follow my other site dedicated to rail travel in Vietnam. View the full article

Below, Dan Pontefract shares five key insights from his new book, The Future of Work Is Grey: The Untapped Value of Age in the Workforce. Pontefract is a six-time award-winning author and a leadership and corporate culture strategist. He has spent more than 20 years in senior leadership roles at TELUS, SAP, and BCIT, serving as a chief learning officer and chief envisioner. In 2018, he founded his own firm, the Pontefract Group, to help leaders and organizations improve leadership and corporate culture. What’s the big idea? Organizations are overlooking a major, unavoidable shift—the aging workforce—and those that learn to value and integrate people of all ages will outperform those that ignore it. Listen to the audio version of this Book Bite—read by Pontefract himself—in the Next Big Idea app, or buy the book. 1. Demographics don’t care about your organization’s strategy. According to the World Economic Forum, workers aged 55 and older will make up more than 25 percent of the G7 workforce by 2031. That’s roughly a 10-point jump from 2011. And between you and me, I think the forum is underselling the number. My money says it will be higher. Here’s what nags at me. Every boardroom, leadership room, and workshop I’ve sat in over the last few years has been obsessed with two topics: artificial intelligence and cost control. Remarkably, neither conversation has included the one demographic fact already reshaping the labor market: The workforce is greying, and it’s happening fast. Organizations are bracing for a robot revolution while quietly ignoring (or not even knowing about) the humans that are about to reshape them. Demographic reality is the one trend you cannot disrupt, downsize, or delay. Older workers are not optional. They are the scaffolding holding up skills transfer, institutional memory, and cultural continuity across every workplace on the planet. You cannot and will not automate your way out of a people problem. The future of work will be grey. 2. Meet the rivers, rocks, and rubies. While writing this book, I kept bumping into the same clumsy intergenerational dance. Younger workers were dismissed as naive. Older workers were dismissed as obsolete. And the folks in the middle were catching friendly fire from both directions as part of the sandwich generation in the workplace. So, I thought a metaphor might make more sense, particularly given how unhelpful it is to classify workers by generations in the workplace: Rivers are your early-career employees. They move fast, change course often, and make some mistakes, but they carry the kind of energy your organization desperately needs—what psychologists call fluid intelligence. Rocks are your mid-career professionals. They are the load-bearing walls of the organization. They are steady, thoughtful, and quietly carrying execution on their backs. Rubies are your seasoned employees, full of what psychologists call crystallized intelligence. They hold institutional memory, hard-earned judgment, and a phone book of relationships worth more than any CRM. Most organizations get policy design wrong. They build programs, perks, and promotions for one cohort at a time, as though rivers, rocks, and rubies exist on separate floors breathing different air. Well, they don’t. A healthy organization looks like a riverbed. Rivers flowing over rocks, polishing rubies, shaping one another by proximity. When you treat a ruby as an expense to be managed rather than an asset to be mined, you lose a library disguised as an employee. When you treat a river as an intern instead of a colleague, you lose the one question that would’ve exposed your outdated assumptions. And when your rocks burn out from mediating between rivers and rubies, while also tending to young kids and older parents outside of work, then you have lost the plot. The age crisis is real. The generational labels we keep using are not. Stop sorting people by decade of birth and start paying attention to the riverbed. 3. Ageism cuts both ways. At 27 years old, I walked into a university faculty washroom during my first week on a new job. An older gentleman at the sink looked me up and down and said, “What are you doing here?” I held up my lanyard. “I work here,” I replied, with a face somewhere between puzzled and iridescent. He dried his hands and said, “Interesting. I didn’t know we were hiring such young people these days.” What a shame. I said nothing and went to my meeting, but the comment obviously still lingers because I’m telling the story a quarter of a century later. Ageism does not only point in one direction. We discriminate against the grey and we discriminate against the green. In 2007, Mark Zuckerberg of Facebook told an audience at Stanford, with a perfectly straight face, that “young people are just smarter.” One year later, he hired Sheryl Sandberg, 15 years his senior, to help him run the company. Or how about 2019, when the “Okay boomer” meme started trending? It did nothing to help the cause. It just added a digital raspberry to a stale conversation. Every major study and research paper on the subject tells the same story. Age-biased workplaces lose more talent, innovate less, and collapse faster under demographic pressure than organizations that treat age as neutral or even positive. And yet, I would wager that every listener right now has witnessed an age-coded remark this year about a junior colleague, a senior colleague, or a middle-aged professional trying to keep it together—or themselves. Ageism is rampant. It may also be the last of the isms we are willing to admit to. 4. Mentorship is multidirectional. The year was 2009. The Black Eyed Peas were crushing it with their song “I Gotta Feeling.” I was 38 years old. I was mid-career at TELUS as the chief learning officer, overseeing leadership development and corporate culture. That year, I discovered a cluster of so-called older employees quietly producing some of the most useful internal learning content for the organization. They were using video cameras and our in-house habitat video system, which was kind of like YouTube. No prompt, no playbook. These people were just all about purpose. I’d be lying if I said I had proactively considered it because I hadn’t. I was supposed to be guiding the organization, but it turned out they were teaching me. The real lesson is not who teaches whom. It is that knowledge transfer in the modern organization runs like a roundabout, not a one-way escalator. Every era holds a lane. Rubies carry judgment and networks. Rocks carry execution and memory. Rivers carry fresh eyes and new concepts, and they may break stuff, but that’s okay because we’re all learning. When you build your organization around a single direction of mentorship, you’re going to break three out of every four knowledge flows available to you. The most intergenerationally healthy organizations I studied did something beautifully boring. They intentionally paired people across age groups. A 24-year-old would coach a 56-year-old on AI tools, and a 56-year-old would coach the 24-year-old on customer empathy and how to recover from a bad boss. Flatten your org chart by age, and you will create a fabulous culture. You may be surprised by who the real students are, too. 5. From grey to gold. A few years ago, I sat down with one of my mentors, Roger L. Martin, one of the finest management thinkers alive and the former Dean of the Rotman School of Management at the University of Toronto. We were stress testing the argument of this book. He listened, he nodded, and then he said something I have not been able to shake. He said, “Organizations recognize the aging workforce challenge. They see it clearly, Dan, yet they lack the tools to meaningfully respond. It’s like the drunk searching for keys under the streetlight, because that’s where the light is, even if the keys aren’t there.” I took that from Roger as a challenge. There is a path for leaders who know the demographics are shifting and who want to stop fumbling in the dark. The age crisis is not a problem to be solved once and shelved. It is a standing commitment, renewed daily, monthly, quarterly, yearly, and visible in how you hire, develop, compensate, and, importantly, how you shape the culture that holds it all together. Here is the promise hiding inside the age crisis: Organizations that treat age as a strategic advantage, rather than a scheduling headache or worse, nothing at all, will outperform their peers on retention, innovation, engagement, and trust. Teams that deliberately mix their rivers, rocks, and rubies will make better decisions, probably faster. Countries that invest in older workers will build more productive, stable, and prepared economies. The firm that stops exacerbating age debt and starts shifting toward inculcating the experience dividend will be the firm that future-proofs itself. In sum, the future of work is grey. It is inevitable. It’s happening. But when organizations and leaders, and maybe you, agree to treat the grey as a golden opportunity, that age debt will become a handsome experience dividend. Enjoy our full library of Book Bites—read by the authors!—in the Next Big Idea app. This article originally appeared in Next Big Idea Club magazine and is reprinted with permission. View the full article

On May 12, Unitree Robotics founder Wang Xingxing climbed into the chest cavity of a 9.8-foot-tall metal robot, walked around, and destroyed a concrete brick wall. One punch. Wall gone. The Chinese media reaction was instant: “Unitree really built a ‘Gundam’!” That was a wild exaggeration, but there’s a kernel of truth to it. The GD01 feels like the first version of something much bigger. Not in size, but in scope. China is waging a full-spectrum push into embodied AI—“digital brains” with physical bodies that perceive and act on the real world—and it’s playing out simultaneously across daily life, logistics, heavy industry, medical care, and military applications. Behind the spectacle of this new giant robot an entire industrial ecosystem is already quietly reshaping the country’s mining, manufacturing infrastructure, airport terminals, and high-voltage power grids. We are at the very beginning of this shift, and its practical consequences are only starting to surface. Built from a skeleton of titanium alloy and aerospace-grade aluminum with a carbon fiber shell, the GD01 is designed and engineered almost entirely in-house by Unitree—a company that, alongside fellow Chinese startup AgiBot, has emerged as arguably the world’s most consequential robotics manufacturer. First of many GD01 weighs 1,102 pounds and is priced at roughly $574,000. The company calls it the “world’s first mass-produced transformable mecha,” a title that is accurate. While some amateur fans have built mechas before, those units weren’t designed for work but rather for show, and none of them had the extraordinary capabilities and dexterity that GD01 shows. The robot transitions between two movement modes: upright on two legs or down on all fours. That four-legged mode works exactly like you’d expect: Drop the center of gravity, spread the weight across four contact points, and the machine stays stable over rough terrain that would tip a bipedal rig flat on its face. Watching it advancing in that mode (the demo footage shown in the launch video runs at normal, unedited speed) makes me feel strangely uneasy. The way it advances like a hellish predator freaks me out. An integrated AI system handles the spatial awareness and real-time limb coordination required to pull this off without the pilot needing to drive it manually. In bipedal mode, it works like any other humanoid bot you may have seen so far. Unitree claims it’s targeting the GD01 at “high-value markets” at this point: cultural tourism, private use, emergency rescue, and “industrial special operations.” But the shape of what comes next is obvious. A piloted exo-frame that can walk, transform, and punch through walls is a direct ancestor of machines that could operate construction sites, perform heavy maintenance on bridges and dams, work inside nuclear plants or collapsed mine shafts, and move massive loads in industrial ports. And given how thoroughly the People’s Liberation Army is embedded in Chinese companies like Unitree, a military evolution of this platform—autonomous or copiloted, armed or not—isn’t a stretch of the imagination. Eating everyone’s lunch The GD01 is the splashiest product in a portfolio that’s leaving Western robotics competitors behind. In 2025, Chinese companies captured almost 90% of global humanoid robot sales, according to research firm Omdia. Unitree alone shipped more than 5,500 humanoid robots—exclusively counting actual deliveries to end customers, per the company’s own official clarification—making it the world’s top shipper of humanoid robots for the year. Over that same period, American competitors Tesla, Figure AI, and Agility Robotics each managed to deliver roughly 150 units. The price gap tells the rest of the story. Unitree sells its base bipedal G1 and R1 models directly to international buyers through AliExpress, targeting customers in North America, Europe, and Japan, with the R1 starting at under $5,000 in some configurations. Elon Musk has publicly estimated his Tesla Optimus will eventually land somewhere between $20,000 and $30,000. Plus, Chinese humanoids are already doing real work in global infrastructure. Japan Airlines, in partnership with GMO AI & Robotics, is running live trials of Unitree’s G1 robot at Tokyo’s Haneda Airport to physically handle passenger bags and cargo on the tarmac, with the testing phase set to run through 2028. In December 2025, CATL—the world’s largest battery manufacturer—launched what it calls the first large-scale humanoid robot deployment in a commercial factory, at its plant in Luoyang, China. Last week, the State Grid Corp. of China kicked off a $1 billion plan to deploy a humanoid workforce to maintain its electrical grid autonomously. And just a few days ago, across the East China Sea, Japan Airlines began testing humanoid robots to handle luggage at Haneda Airport. Perhaps now that President The President is in Beijing, Chinese authorities will show him an impressive demo that will prompt his administration to make robotics a strategic industry for the United States. Otherwise, we are seriously risking both our future economy and security. There is no doubt that embodied AI will be the fastest-growing industry in the coming years, taking over every aspect of our lives. The Western world can’t afford to stay out of the most important technology race since the industrial revolution. View the full article

For decades, the conversation around gender equality at work has been dominated by one glittering metaphor: the glass ceiling. We count women in boardrooms, track female CEOs, and debate the glass cliff awaiting women promoted during crises. But for millions of women over 45, the problem isn’t getting to the top. It’s getting unstuck from the bottom. While elite professional careers dominate headlines, the reality for much of the female workforce is the sticky floor: a structural trap that keeps women concentrated in low-paid, low-mobility jobs America depends on but refuses to properly value. And with age, the glue hardens. The intersection of sexism, ageism, and unpaid caregiving creates a cumulative vulnerability that threatens women’s financial security precisely when they should be consolidating it. When midlife turns into economic decline In theory, experience should increase a worker’s value. In practice, this is more often true for men than for women. Research shows that gender inequalities widen dramatically with age. In France, where I studied the sticky floor in a report for the Fondation des Femmes, we calculated that women between 45 and 65 lose roughly €157,000 (or $184,000) in earnings over 20 years compared with men their age. The same pattern exists in the United States. Highly educated professional women have made gains. But women without college degrees—especially Black and Hispanic women—remain heavily concentrated in low-paid “aging work”: home care, retail, hospitality, administrative support, and personal services. The sticky floor is not simply about earning less at one moment in time. It is a system of low lifetime mobility. By 55, many women have already absorbed decades of the motherhood penalty. Then comes the menopause penalty, followed by a pension shortfall. America depends on work it refuses to value The sectors growing fastest in the U.S.—eldercare, healthcare support, and social assistance—are precisely where the sticky floor is strongest. These jobs are deemed essential. They are also systematically underpaid because they are associated with historically feminized labor: caring, cleaning, emotional regulation, and coordination. In these sectors, experience rarely translates into meaningful wage progression. A woman may spend 20 years as a home health aide and still earn close to entry-level pay. Professional careers reward seniority. Service work often punishes it—with more physical strain, unstable schedules, and burnout. Your back is broken before your experience is valued. The care trap just never ends The engine of the sticky floor is unpaid care work. The motherhood penalty is well documented. But the care penalty continues long after children grow up. Women between 45 and 65 often belong to the “sandwich generation,” supporting adult children while caring for aging parents, sick spouses, and/or grandchildren. Grandmotherhood itself remains a major blind spot in workplace discussions. Many women become grandmothers while still fully active professionally. In a country with insufficient childcare infrastructure, grandmothers often become the invisible shock absorbers of family life. They reduce hours, reject promotions, or move into more flexible (but lower-paid) jobs in order to provide unpaid care so that their daughters are able to work full time. Of course, this work is performed out of love. But it comes with a brutal economic price tag. Women represent 60% of part-time workers in the United States—not necessarily because they prefer reduced hours but because it is the only way to manage caregiving responsibilities. Part-time work creates a triple penalty: lower immediate income fewer promotion opportunities permanently reduced retirement savings and Social Security benefits The consequences accumulate over decades. The double jeopardy of aging Ageism is not gender-neutral. Women suffer a “double standard of aging”: Older men are often perceived as experienced and authoritative, while older women are more likely to be seen as obsolete, expensive, or less adaptable. In many customer-facing jobs, women also face pressure to conceal visible signs of aging in ways men rarely do. The result is a form of double jeopardy: gender discrimination compounded by age discrimination. A woman over 50 who loses her job after a caregiving interruption, health issue, or layoff often discovers that the labor market no longer “sees” her. The ultimate consequence of the sticky floor is a growing gray zone of women who are neither fully employed nor fully retired. This is called the NER zone (neither employed nor retired). These women have often been pushed out of work by caregiving demands, health issues, or age discrimination, but they’re still years away from pension eligibility. This won’t come as a surprise: A majority of people in this category are women. This period is a form of economic purgatory that cements poverty later in life. Because their careers were fragmented by part-time work and unpaid caregiving, many lack the earnings history necessary for financial security in retirement. Cleaning the sticky floor The solution will not come from hustle culture or individual empowerment alone, though these may help individual women. But when a labor market systematically undervalues feminized work, telling women to “lean in” often simply produces more exhaustion. The sticky floor requires structural solutions. Wage floors should be raised in feminized sectors like home care and eldercare. If care work is essential, compensation should reflect its social value. Maybe the market sometimes corrects this when labor shortages become severe; but in many cases, the invisible hand does not reprice undervalued care work on its own. Retirement systems and households must recognize the economic dimension of caregiving. Social Security calculations should account for years spent caring for parents, spouses, or grandchildren. Employers need to rethink workplace design for an aging workforce. Universal design—ergonomic flexibility, better acoustics, hybrid work, predictable scheduling—benefits everyone, but becomes essential as workforces age. Organizations must address the intersection of gender and age bias directly, especially in hiring and customer-facing roles. We need more ambitious models of part-time and hybrid work. Flexibility should not automatically mean career stagnation. The demographic revolution is already on its way. Americans are living longer, working longer, and caring longer. They can no longer afford to treat midlife women as an invisible safety net for a failing care system—and as disposable talent once they pass 50. It is time to stop focusing only on the glass ceiling and start cleaning the sticky floor. Because if we don’t, we are weakening the future of work in its entirety. View the full article

Imagine hiring every all-star on the market, paying top dollar, and then finishing sixth in your division. That’s not a hypothetical. It’s what happened to Sinan Aral’s beloved Liverpool F.C. last season, and it’s also, he argues, an almost perfect metaphor for how most organizations are deploying AI right now. Aral is a professor at MIT’s Sloan School of Management and one of the leading researchers on human-AI collaboration. His lab has spent the last several years running large-scale, real-world experiments on what actually happens when humans and AI work together… and the results should give every leader pause. “In about 85% of the studies we’ve seen,” he told me, “while adding AI to human beings improves human beings alone, most of the time it’s better to just let the AI do it alone.” That data point is what Aral calls the rational fork in the road: if AI alone outperforms human-AI teams, the logical managerial move is to replace employees with automation. But that, he insists, is exactly where the logic goes wrong. When good enough becomes a trap In one landmark study, Aral’s team randomized roughly 2,000 teams (some human-AI and some human-human) to create marketing ads for a real organization. The human-AI teams produced 50% more ads per worker, with higher-quality text. By conventional productivity metrics, that would be a clear win. But the ads also looked strikingly similar to one another. “Ad copy starts sounding the same. Ad images start looking the same,” Aral explained. He calls this “diversity collapse”, the slow homogenization of output that occurs when AI, trained on the same publicly available internet, starts flattening the edges that make creative work distinctive. The more a team delegated to AI, the more productive they became- and the more vulnerable they were to this collapse. Short-term gains masked long-term creative erosion. Diversity collapse is a thinking problem. The skills we’re quietly losing Aral’s most recent paper, which he calls the “AI Augmentation Trap,” reveals something even more unsettling. Cognitive offloading to AI (the act of outsourcing tasks you could do yourself) erodes the very skills you’re handing off. Workers who lean heavily on AI for writing lose writing fluency. Junior employees de-skill faster than experienced ones, who have the professional reserves to retain their capabilities. “It leaves the worker worse off than if AI had never been adopted” in the long run, Aral said. The short-term productivity boost is real. So is the long-run trap. This maps directly onto what I’ve been writing about in my own work: productivity, as we’ve inherited it from the First Industrial Revolution, is an either/or model that values speed, efficiency, and measurable output. It misses what happens during dormancy- the marination, the synthesis, the slow cultivation of judgment that makes truly original thinking possible. Aral’s research gives that perspective empirical teeth. What leaders should do instead The fix, Aral argues, isn’t to avoid AI because that’s not a real option. “This is possibly the most disruptive technology ever developed in human history,” he said, and burying your head in the sand is not a strategy. The fix is to get intentional about human-AI collaboration design. His prescriptions are practical: measure human skill levels independently of AI output; build in structured, unassisted practice so workers regularly perform tasks without AI assistance; extend performance evaluation windows so managers aren’t seduced by short-term productivity spikes at the expense of long-run capability; and design workflows where workers review, evaluate, and reshape AI outputs rather than simply accepting them. Keep human judgment in the loop, not as a formality, but as a discipline. And I’d go one step further- incentivize that human judgement during review periods. A second line of Aral’s research offers another lever: personality pairing. When his team matched approximately 1,300 participants with AI personalized to complementary Big Five personality traits (not mirroring, but complementing) both productivity and creative output improved, and diversity collapse was reduced. Just as with human teaming, who you pair together matters. The best partners aren’t identical, they’re complementary. This appears to be true even when one of those partners is an algorithm. The counterintuitive imperative Here’s what Aral’s data ultimately points to, and what I think every leader needs to hear: the organizations that will win in the Imagination Era are not those that replace the most humans with AI, but those that become genuinely excellent at human-AI collaboration. That’s a skill. It requires investment, design, and a willingness to resist the seduction of the easy productivity win. Creativity has always required what I call the rigor of ambiguity: the courage to sit with uncertainty rather than reaching for the fastest, most frictionless answer. AI offers a very compelling shortcut. The leaders who understand that the shortcut is also a risk, and who build organizations capable of holding both the power of AI and the irreplaceable texture of human thought, will be the ones who are still competitive a decade from now. Liverpool, Aral notes, is figuring out how to make their expensive roster fit together. So should we. View the full article

Ship anchored north-east of Fujairah outside Strait of Hormuz taken by ‘unauthorised personnel’View the full article

All writing is autobiographical. Even if you’re not explicitly writing about your own experience, it shows up in the topics you choose, the details you focus on, even the things you leave out. Key example from my trove of nearly 3,000 articles here on Inc. over the years: a study I latched onto a decade ago about the single thing wealthy families do to give their kids a leg up on the world. The answer, drawn from University of Southern California research, was straightforward: They buy the neighborhood. The insight wasn’t so much about money as it was about what money makes possible. Stable schools, stable peer groups, and stable environments. The specific advice for parents who couldn’t afford the nicest neighborhood was to buy the smallest house in the best one they could. I cared about this because I had just become a parent for the first time, and I was on a tear to find as much research-based advice as possible about how not to mess up my child’s life. Later, when my wife and I were ready to leave our city apartment, that article was genuinely part of the conversation. We ended up with one of the smaller houses in a fairly affluent town. So far it has felt like a good decision. Knock on wood, I don’t think I’ve done a terrible job as a parent. Still, I pay close attention to parenting advice that makes sense. The latest find: Harvard researchers recently published something that reframes the idea from a decade ago and makes it considerably more powerful. A web of stability The paper, released in March by Harvard’s Early Childhood Scientific Council on Equity and the Environment, is titled From Resources to Routines: The Importance of Stability in the Developmental Environment. It synthesizes a wide body of research on what children need to develop healthy brains and bodies, and its central finding is that stability is important, but it’s not just one thing. It’s more of a web. Housing, finances, caregiver relationships, sleep routines, daily schedules—they aren’t separate variables so much as interconnected threads. When one frays, others tend to follow. An unexpected drop in family income, for example, often leads to loss of housing, which disrupts routines, which affects sleep, which impairs learning, which compounds everything else. The multiplier effect The paper calls this the multiplier effect, and it runs in both directions. Strengthen stability in one area, and it tends to support stability in others. While the 2016 study was fundamentally about resources—what wealthy parents can buy—the Harvard paper is about something more fundamental: what the brain needs in order to develop properly, and why instability at the wrong moment is so costly. Beginning before birth, children’s brains develop in response to patterns in their environment. Consistent, predictable interactions with caregivers—what the researchers call “serve and return” exchanges—build the neural circuits that support language, emotional regulation, and learning. When those patterns are disrupted repeatedly, it triggers a stress response that is protective in the short term but harmful if it persists: hormones, inflammation, and ultimately an increased risk of cardiovascular disease, anxiety, and depression. The paper also makes a point that surprised me: Instability can accelerate puberty. When young children perceive their environment as harsh and unpredictable, the resulting stress can trigger earlier pubertal development, which carries its own downstream health risks. Unpredictability and resilience The most useful reframe in the paper is the distinction between stability and novelty. It’s not that children need a perfectly static world. Novel experiences are essential for learning and curiosity. A child conquering a higher slide, a family moving to a better school district, a parent leaving a bad situation—these disruptions can ultimately be beneficial, if a foundation of consistent adult support is in place. Some unpredictability builds resilience. However, chronic unpredictability, especially when it comes from things families can’t control—unstable work schedules, housing insecurity, and climate-driven displacement—is what does the damage. The thread from 2016 Ten years ago, the takeaway was essentially that if you can afford stability, buy it. The Harvard paper suggests the stakes are even higher than that, and the mechanisms are clearer. Developing brains are literally built or disrupted by the patterns of predictability they encounter in their earliest years. For parents who can’t buy the neighborhood, the paper’s most actionable message is about what’s still within reach: the routines. Consistent mealtimes, predictable bedtimes, and reliable responses to a child’s needs aren’t consolation prizes. According to the research, they’re the mechanism—the way stability actually works at the level of developing neurology. The multiplier runs through whatever thread you can actually hold. —Bill Murphy Jr., Founder of Understandably and Contributing Editor This article originally appeared on Fast Company’s sister website, Inc.com. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy. View the full article