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The past week has been a brutal one for many working in the tech and financial industries. Thousands of jobs have been lost—or will be lost soon—from companies including Block, Morgan Stanley, Capital One, eBay, and, as reported today, software giant Oracle. Here’s what you need to know about the layoffs. Oracle to cut ‘thousands’ of jobs The most recent news of layoffs came yesterday, after Bloomberg reported that the database software giant Oracle Corporation (NYSE: ORCL) is planning to cut “thousands” of jobs as soon as this month. And yes, artificial intelligence is to blame—but not solely because AI is directly taking jobs. Instead, Oracle is reportedly planning job cuts to free up cash for its AI data center expansion, which the company is pursuing to compete with cloud computing giants Amazon and Microsoft. However, Bloomberg’s report noted that some of the jobs lost will be jobs “that the company expects it will need less of due to AI.” It is unknown exactly how many jobs will be lost, with Bloomberg noting that Oracle’s workforce reduction plans are “still active and could change.” Fast Company has reached out to Oracle for comment. As of May 2025, Oracle has around 162,000 employees. Capital One lays off over 1,100 workers On the same day of the Oracle job cuts report, financial giant Capital One (NYSE: COF) said that it was laying off more than 1,100 employees, according to CBS News. But these layoffs have nothing to do with AI. They follow Capital One’s acquisition of credit card giant Discover last year, which cost the company $50 billion. Shortly following that acquisition, 600 employees were laid off. Now, another 1,100 are expected to lose their jobs—primarily those who worked at the former Discover headquarters in Riverwoods, Illinois. A Capital One spokesperson confirmed the layoffs to CBS News, stating, “As part of our continued journey to integrate Discover with Capital One, we announced the difficult decision to eliminate some Discover associate roles across the organization.” Morgan Stanley eliminates 2,500 roles A day before the Capital One layoffs were reported, the Wall Street Journal reported that investment banking giant Morgan Stanley (NYSE: MS) was laying off around 2,500 workers, or about 3% of its roughly 83,000-strong workforce. The job cuts reportedly hit employees in three divisions: investment banking and trading, wealth management, and investment management, and are reportedly “tied to shifting business and location priorities,” according to the Journal, which cited anonymous sources. Fast Company reached out to Morgan Stanley for comment. Block layoffs decimated 4,000 jobs The most significant round of layoffs, however, came from Jack Dorsey’s Block (NYSE: XYZ). Last Friday, the fintech company cofounded by one of Twitter’s original cofounders announced sweeping job cuts totaling 4,000 positions. And Dorsey didn’t beat around the bush as to the reasons for the layoffs: AI. As Fast Company previously reported, Dorsey said his Block workforce was shrinking from 10,000 employees to just 6,000 due to the company’s increasing use of “intelligence tools,” which have allowed it to function with a “significantly smaller team.” “I don’t think we’re early to this realization. I think most companies are late,” Dorsey said in a memo published online. “Within the next year, I believe the majority of companies will reach the same conclusion and make similar structural changes. I’d rather get there honestly and on our own terms than be forced into it reactively.” eBay cuts 800 jobs The Block layoffs came just one day after legacy online shopping giant eBay (Nasdaq: EBAY) announced it was cutting about 6% of its workforce, or around 800 jobs. As Fast Company reported, the layoffs came about a week after eBay acquired the second-hand clothing app Depop from Etsy for $1.2 billion. “We are taking steps to reinvest across our business and align our structure with our strategic priorities, which will affect certain roles across our workforce,” an eBay spokesperson told Fast Company. “We are grateful for the contributions of the employees impacted and are committed to supporting them with care and respect.” Layoff announcements actually fell in February If there’s a silver lining at all to this, it’s that total layoffs appear to have fallen in February by a significant amount, according to a report from the outplacement firm Challenger, Gray & Christmas. The firm said that U.S.-based layoff announcements plunged by 55% in February, to 48,307, versus the month before. However, that dramatic fall is only as sharp as it is because January saw over 108,000 layoff announcements. For the month of February, the firm says the most jobs lost were in the technology sector, with about 11,000 jobs cut. Education came in second place, with around 5,400 jobs lost. Industrial Manufacturing came in third with about 4,100 jobs lost. Yet Challenger, Gray & Christmas cautions that the decline in job cuts might not last. “February’s dip is a nice reprieve from the elevated job cut plans to start the year,” the firm’s chief revenue officer, Andy Challenger, noted. “With U.S. involvement in a growing war in Iran, the end of Q1 may bring more layoff plans as companies tighten belts amid uncertainty and higher costs.” View the full article

In SEO Pulse: AI Overview citations drift further from traditional rankings as AI search expands and platforms clarify how content appears in AI answers. The post AIO Citations Diverge From Rankings, Bing Rewrites Rules – SEO Pulse appeared first on Search Engine Journal. View the full article

Video advertising has never been easier to distribute. Platforms can deliver impressions and views at an enormous scale across YouTube, paid social, short-form video, and connected TV. But distribution isn’t the same as effectiveness. Many campaigns generate impressive platform metrics while producing little measurable business impact. The problem usually isn’t targeting, budget, or platform choice. It’s a deeper strategic issue: campaigns are optimized for outputs like views and impressions rather than outcomes like attention, persuasion, and action. Most video ads fail because they misunderstand attention Poor targeting, limited budgets, and platform choice are rarely the real problem. The bigger issue is that many video ads are still produced as if they’re television commercials. In the early days of online video, distribution was the challenge. Getting a video seen at all felt like a win. Today, distribution is abundant. Attention isn’t. Every major platform — YouTube, paid social, short-form video, connected TV — competes for fragments of cognitive bandwidth. Users arrive with intent, habits, and expectations that have nothing to do with your campaign. We plan for reach, while viewers respond to relevance. I’ve sat in many meetings where success was defined by impressions delivered or views accrued. But when you look downstream — search lift, site engagement, conversion — the connection often disappears. Platforms will reliably deliver impressions. Turning those impressions into memory, persuasion, or action requires a fundamentally different mindset. Dig deeper: From Video Action to Demand Gen: What’s new in YouTube Ads and how to win Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with The first five seconds are the entire negotiation Skippable formats changed video advertising permanently, but many advertisers still haven’t adjusted creatively. Early in my career, I believed strongly in branding up front. Logos, product shots, music cues — everything that signaled professionalism. Those ads looked great in presentations. They underperformed in market. A clear pattern emerged over time. Ads that opened with a recognizable problem, a provocative statement, or an unexpected visual held attention longer — even when branding appeared later. Ads that opened with branding signals were skipped almost reflexively. View-through rate isn’t persuasion. A “view” simply means the platform’s minimum threshold was met. It doesn’t mean the message landed, the brand registered, or the viewer cared. In multiple brand lift analyses, most measurable impact occurred before the skip button appeared. If the opening didn’t earn attention, the rest of the ad didn’t matter. What works: treat the opening frame like a headline, not a preamble. Lead with tension, a question, or a familiar problem. Design for sound-off environments. If the first frame wouldn’t stop a scroll, nothing that follows will matter. Higher production value often correlates with lower performance One of the most counterintuitive lessons in modern video advertising: polished ads frequently underperform scrappier ones. I’ve seen simple, phone-shot videos outperform meticulously produced studio spots across YouTube, paid social, and short-form platforms. Not because quality doesn’t matter — but because perceived authenticity matters more. Audiences are exceptionally good at identifying advertising. When something looks like an ad, they disengage. When it looks like content, they give it a chance. Algorithms reinforce this: they reward watch time, retention, rewatches, and shares. They do not reward lighting setups or production budgets. I’ve seen brands “upgrade” social video to look more premium, only to watch performance decline. The creative looked better. The results were worse. The goal isn’t to look amateurish. It’s to look like you belong. Match the platform’s visual grammar. Prioritize clarity over polish. Use real people and authentic voices whenever possible. Ads that feel native get watched. Ads that feel inserted get skipped. Dig deeper: How to get better results from Meta ads with vertical video formats Get the newsletter search marketers rely on. See terms. Length is a creative decision, not a media constraint “Shorter is better” is one of the most persistent — and misleading — rules in video advertising. Six-second ads can work. So can 60-second ads. I’ve seen both exceed expectations, and I’ve seen both fail badly. The difference was never duration — it was justification. Some messages can be delivered instantly. Others require context, proof, or emotional buildup. Forcing every idea into the same runtime produces predictable results: safe, bland, forgettable ads. I’ve reviewed retention graphs where a 45-second ad held viewers longer than a 15-second version, because the story justified its length. I’ve also seen six-second ads lose half their audience in the first two seconds because they wasted the opening. Test multiple edits, not just multiple lengths. Watch retention curves, not averages. Build modular narratives: hook, then value, then proof, then action. The “right” length is however long it takes to make the viewer feel their time was respected. Metrics are signals Platforms provide more data than ever. The problem isn’t a lack of metrics. It’s confusing metrics with outcomes. I’ve seen campaigns praised for high completion rates that produced no measurable business impact. Strong engagement coexisting with low conversion. Impressive view counts that delivered zero lift. This happens because platforms optimize for their success metrics, not yours. If your goal is to maximize views, the platform can do that easily. If your goal is to influence consideration, preference, or action, things get more complicated. One uncomfortable question I’ve learned to ask early: what would failure look like here? If the answer is vague, the campaign is already at risk. Define success in business terms before launch. Tie video metrics to downstream behavior wherever possible. Use lift studies, holdouts, or assisted conversions when they’re available. If you’re running a brand-building campaign, measure brand lift. If you’re running a performance campaign, measure conversions. Dig deeper: AI for video advertising: 5 best practices for PPC campaigns The brief is usually where things go wrong Creative is often blamed when video ads underperform. In reality, creative usually does exactly what it was asked to do. The problem is the brief. Vague objectives produce generic ads. “Brand awareness” without context leads to unfocused messaging. “Make it engaging” isn’t a strategy. Strong video ads almost always begin with clear answers to three questions: Who is this really for? What do they care about right now? What should they think, feel, or do differently after watching? When those answers are clear, creative decisions become easier. When they aren’t, the work is compromised before production begins. The deeper diagnostic questions are worth keeping close: Are viewers actually paying attention, or just passively present? What are they feeling — and which specific creative choices are driving that response? Will they remember the brand once the ad ends? What will they do next — share it, recommend it, search for the product, or buy? I’ve seen entire campaigns improve simply because the brief forced alignment around audience insight rather than assumptions. Distribution strategy is part of the creative Another common mistake is treating creative and distribution as separate decisions. They aren’t. The way an ad is consumed — fullscreen versus feed, sound-on versus sound-off, lean-back versus lean-forward — should shape how it’s made. A video designed for connected TV shouldn’t simply be resized for mobile. A short-form ad shouldn’t be a truncated long-form story without rethinking the hook entirely. I’ve seen strong ideas underperform because the creative didn’t match the placement. The concept wasn’t wrong. The context was. Design with placement in mind from the start. Create platform-specific versions, not one-size-fits-all assets. Accept that “reuse” often means “rethink,” not “repurpose.” Distribution constraints aren’t limitations — they’re creative inputs. Dig deeper: How to dominate video-driven SERPs Testing should answer questions, not just generate variants Testing is indispensable. It’s also frequently misunderstood. Running endless A/B tests without a hypothesis rarely produces insight. It produces noise. The most effective testing focuses on variables that materially affect attention and comprehension: opening frames, narrative structure, on-screen text versus voiceover, proof points versus emotional appeals. It’s also important to recognize what testing can’t do. Algorithms are excellent at optimizing toward measurable signals. They don’t understand brand equity, long-term memory, or cumulative effect. Testing should inform judgment — not replace it. Ultimately, the only thing that matters for creative effectiveness tools is whether their predictions actually correlate to real media and sales outcomes — reliably enough to inform strategy and media decisions. The question worth asking of any such tool is simple: How often does what it predicts will happen actually happen? For example, I frequently cite data from DAIVID, an AI-driven creative effectiveness platform. Why? Because in independent testing, DAIVID’s predictions aligned with real-world outcomes more than 80% of the time — a meaningful foundation for making creative decisions with greater confidence before a campaign goes live. See the complete picture of your search visibility. Track, optimize, and win in Google and AI search from one platform. Start Free Trial Get started with Optimize for people Platforms will change. Formats will evolve. Algorithms will shift in opaque and sometimes frustrating ways. But attention, curiosity, and trust remain stubbornly human. The best video ads I’ve worked on weren’t optimized for view counts or completion rates. They were optimized for relevance. They respected the viewer’s time. They said something worth hearing. Video ads don’t succeed because they follow platform rules. They succeed because they understand people. And that principle outlasts every algorithm update. View the full article

When considering AI’s impact in cities, many residents and government officials envision a dark future of unbridled surveillance, hollowed-out city halls and unaccountable bots calling the shots based on biased training data. We, on the other hand, embrace a much more optimistic vision. With ambitious local leadership, AI, and especially the coming wave of agentic AI, can offer a profound opportunity not only to make government services more efficient but also to transform how cities fulfill their end of the social contract. As long-time public servants and champions of government innovation at our respective universities, we understand the challenges local governments face, including tight budgets, aging infrastructure and dissatisfied residents accustomed to the speed of Amazon and personalization of Spotify. Most cities still run on a century-old operating system built on bureaucracy, paper files, agency silos and rigid hierarchy. Agentic AI offers a unique opportunity to redesign how cities work, a model we call the “Agentic City.” Agents, city employees, and citizens working together Imagine a city administration where the complexity of navigating government bureaucracy is offloaded to intelligent agents—so routine tasks happen flawlessly, and even complex ones feel simple. A mother reports a broken sidewalk near her child’s school, snaps a photo, and sends it to the city. An AI agent classifies the problem, routes it to the right crew, tracks progress across agencies, proactively updates her until the work is done, and alerts others to similar risks nearby. Imagine a city that fixes pavement cracks before they become potholes, changes street lamps before they burn out, and repairs water lines before they leak. Yet even these dramatic improvements will only constitute steps in a transformation. These tools help reform-minded mayors adopt a system approach that sidesteps the strong headwinds often confronting business reengineering, including efforts to integrate agency functions or disparate data systems. Transportation officials no longer need to tweak signals; an AI traffic agent can balance safety, travel time and emissions. An Agentic City will be one in which agents, public employees and residents work together. Ultimately, all city services will be personalized as residents use an “agentic front door” to state their goals (“want to open a barber shop at 10th and Main”). Agents will walk users through the process or even complete those tasks for them. At the same time, a human monitors the results, troubleshoots and takes on difficult or unusual cases. In fact, this city offers preemptive housing vouchers, rental assistance, and property tax relief to those who qualify, obviating the application maze entirely. A systemic approach Getting there will require strong leadership to overcome gaps in imagination, skill deficits, and employee anxiety, compounded by the complexity of ensuring that AI changes comply with democratic values. Local leaders will need to take a systematic approach, crafting a powerful narrative of the service benefits while using their political and legal skills to negotiate with the city council, union, and employee leaders. AI-driven transformation requires a leadership team supported by academic and other local experts who understand the city’s technical capacity, legal and data limitations, and that stretches the imagination of a bureaucracy accustomed to existing processes. That team should establish a pathway for opportunities for both employees and residents, including the agentic front door, repetitive functions that can be outsourced to AI, and more time for staff to take on higher-value purposes: investigating root causes, engaging communities, and exercising judgment. Third, the leadership team should promote the incorporation of agentic capabilities that help employees identify patterns and causes of recurring problems by making data more easily accessible. Municipal workforces, both union and nonunion, represent a key stakeholder. Mayors need to be clear that AI will complement, not replace, the workforce. An Agentic City initiative would include outreach to labor to set the parameters of a new bargain in which workers, armed with data insights, increase productivity and share in the benefits through pay increases. Data literacy training and a data governance framework should also be essential components. Freed of repetitive tasks, public employees can focus on higher-value work. The data foundation Addressing these concerns responsibly begins with the system’s foundation: the data. Cities must invest in data pipelines that are not merely machine-readable but machine-understandable—structured with rich metadata, shared ontologies, and business-logic context—so that both humans and AI agents can interpret meaning, constraints, and appropriate use. Emerging approaches such as Model Context Protocols (MCPs), which standardize how AI systems access structured data and operational tools, represent a promising step in this direction by helping agents understand not only what data exists but also how it should be used. An agent that can “see” a permit record but not understand the regulatory framework, eligibility rules, or data quality limitations behind it will act inconsistently and require constant human correction. Machine-understandable data reduces that friction and makes agentic systems more reliable, transparent, and scalable. In short, the foundation of an Agentic City is not just smarter algorithms, but smarter data architecture. Implementing an agentic city hall presents substantial challenges. However, now is the time to lead, as mayors cannot afford to maintain the status quo or wait for the AI tsunami. Going forward presents challenges as well. Doing nothing poses a greater risk than getting started, and the evidence will be a city that, through more meaningful work for its employees, becomes more responsive to its residents. View the full article

Google Local Service Ads can be super expensive; each call or click can cost hundreds of dollars. Which is why Google has generally been good about refunding for mistaken leads or issues with those leads. View the full article

Debt markets head for worst week in more than a year after energy price surge sparks inflation fearsView the full article

Google sent out emails to some advertisers about changes coming to the Customer Match uploads in the Google Ads APl. After April 1, 2026, those data uploads are no longer going to work in the Google Ads API and must be done in the Data Manager API instead.View the full article

New York is the latest state to consider a bill that would prohibit AI chatbots from dispensing advice that licensed professionals would normally give, such as medical or legal advice. The bill would also allow people who believe they were harmed by such advice to sue the operator of the chatbot. Senate Bill S7263, introduced by Democratic state Senator Kristen Gonzalez, passed out of a technology committee on a 6–0 vote last week and now advances to a reading on the floor of the Senate. Interestingly, the bill requires operators to clearly label their chatbots as AI, but stipulates that such a label isn’t enough to shield them from lawsuits under the statute. The proposal reflects a growing shift in how policymakers are thinking about AI. While early efforts focused mostly on transparency, lawmakers are beginning to explore something arguably more consequential: whether companies should be legally liable when AI systems give advice that causes real-world harm. The bill applies to chatbots that give advice in the fields of medicine, law, dentistry, veterinary medicine, physical therapy, pharmacy, nursing, podiatry, optometry, engineering, land surveying, geology, architecture, psychology, and social work. New York isn’t acting alone. Other states have passed or are considering similar laws, though with varying scopes and enforcement methods, and they tend to focus primarily on healthcare: California’s AB 489, enacted in 2025, does something similar but with a narrower scope, targeting AI systems that misrepresent their information as coming from licensed healthcare professionals. But AB 489 relies on state healthcare boards for enforcement and doesn’t provide a private right of action (civil suit) for legal recourse. A new Nevada law, AB 406, which went into effect last July, prohibits the advertising and operation of AI systems designed to dispense professional mental and behavioral healthcare therapy. The law also limits how licensed professionals can use AI in their practices. Last August, Illinois passed HB 1806, which prohibits licensed therapists in the state from using AI to make treatment decisions or communicate with clients. The law also prohibits tech companies from advertising or offering AI-powered therapy services in the state without the involvement of a licensed professional. Utah passed a similar law, HB 452, that puts restrictions and disclosure requirements on chatbots that appear to offer an alternative to human mental health therapy or advice. The law went into effect in 2025. Professional medical groups have also begun weighing in on the risks. The American Medical Association doesn’t call for a ban on AI chatbots dispensing health information, but it worries that consumer advice from LLMs might be false or misleading. “Notably, tools such as ChatGPT have shown a not-uncommon tendency to falsify references cited in response to these queries,” the AMA says in a policy paper, adding that AI tools have demonstrated the ability to generate fraudulent scientific or medical literature to support health advice. An especially sensitive area is mental health advice. Mental health advice is a particularly sensitive area, perhaps because many chatbot users, especially younger ones, use AI as a counselor or therapist. A 2025 JAMA Network study found that 13% of all respondents used chatbots for mental health advice, with 22% of those ages 18 to 21 doing so. AI companies have recognized a large and growing addressable market for AI mental health chatbots, in part because many consumers struggle to find an affordable therapist. For some consumers, the argument goes, accessing mental health advice from a chatbot is better than receiving none at all. The American Psychological Association says chatbots could actually be worse than nothing at all. That’s because of AI models’ tendency to relate to humans in a sycophantic way. The group said in a presentation to the Federal Trade Commission that “A.I. chatbots ‘masquerading’ as therapists, but programmed to reinforce, rather than challenge a user’s thinking, could drive vulnerable people to harm themselves or others.” Senator Gonzalez will likely have to explain why her S7263 bill targets chatbots as a source of legal or medical information but not traditional search engines. She might cite a 2025 experimental study showing that people “over-trust” AI. (She declined to comment for this story.) The researchers write that AI chatbots often sound more convincing and trustworthy than search engine results—even when they’re wrong, off-topic, or lacking context. The study also found that participants couldn’t reliably distinguish AI responses from those from real doctors, and often rated AI responses as more trustworthy and complete. Another study by Oxford and MLCommons involving nearly 1,300 participants found that using AI models to evaluate and analyze symptom scenarios led to health decisions (“should I take some aspirin? Should I go to the ER?”) that were no better than decisions based on personal knowledge or information gleaned from traditional internet search. The study also found that users often don’t know what details the AI needs to generate an answer, and that the AI’s outputs often blend correct and incorrect recommendations. The AMA says it would like to see the Federal Trade Commission regulate AI chatbots that dispense health information, but believes the agency currently lacks the resources to take on that role. Instead, it calls on the tech companies behind the chatbots to continually review the accuracy of their models and give users an easy way to report when a chatbot outputs inaccurate health information. View the full article

David Lammy says deploying RAF jets to protect British nationals and staff would be ‘entirely legal’View the full article

Secondary keywords are how you capture that extra traffic. They’re the supporting terms that help your page rank for more searches without creating separate content for each variation. In this guide, you’ll learn what secondary keywords are, how to find…Read more ›View the full article

AI copy guardrails and expanded YouTube non-skip video formats headline this week’s Google Ads updates in PPC Pulse. The post AI Max Brand Controls Expand, VRC Non-Skip Ads Go Global – PPC Pulse appeared first on Search Engine Journal. View the full article

Grocery Outlet is joining the ranks of retailers planning to shutter storefronts this year. The discount grocery store chain announced its fourth-quarter and full 2025 fiscal year results on Wednesday, along with a plan to close 36 stores. This move to close stores follows a previous restructuring plan concluded in the second quarter of fiscal 2025, another attempt to “improve long-term profitability” and optimize growth. The company reported an increase in net sales, but an operating loss of $234.8 million and a net loss of $218.2 million in the fourth quarter of 2025. The optimization plan, which is expected to be largely completed during fiscal year 2026, is estimated to result in $14 million to $25 million in net total restructuring charges. This doesn’t include the company’s estimated gross profit loss due to sales discounts or product markdowns as the impacted locations close. At the same time, the fourth-quarter fiscal report noted seven store openings. Trade publication Grocery Drive reported that 24 of the closing stores are on the East Coast, and the company does not intend to slow its expansion, even as it experiences closures. The California-based chain ended the fourth quarter with 570 stores across 16 states, according to its earnings release. Shares of Grocery Outlet Holding Corp. (Nasdaq: GO) plummeted after its report. The stock closed down more than 27% on Thursday and is down more than 37% year to date. Fast Company reached out to Grocery Outlet for additional information on which stores will face closures and the expected impact on surrounding areas. Food access is a growing concern The ongoing trend of grocery store closures continues to raise concerns about food access. Kroger announced closures last year, sparking conversations in local communities about jobs and grocery deserts. Food deserts, or communities that are both low-income and lack a grocery store, are becoming more common across the United States. It’s an impact from the 1980s, when the government stopped enforcing the Robinson-Patman Act, an antitrust law that prohibited supplier price discrimination. Now millions of Americans live in food deserts. Organizations like the Institute for Local Self-Reliance (ILSR) map these food deserts, which can spread in response to these store closures. More than 280 Grocery Outlet stores are in California, where approximately 2.7 million people live in a food desert, according to ILSR data. View the full article

It sounds like a brag-worthy business coup: not just snagging a high-profile client, but doing so just after your chief rival’s deal with that same client unraveled in a brutally public way. But artificial intelligence pioneer OpenAI’s Pentagon deal didn’t end up being a brand-halo event. To the contrary, “it just looked opportunistic and sloppy”—and that’s the judgment of OpenAI’s CEO, Sam Altman. Given widespread concerns about the potential downsides of AI, ranging from mass layoffs to robot overlords, “opportunistic and sloppy” are just about the last attributes OpenAI wants to be associated with, perhaps especially in the context of a Department of War partnership. But this isn’t just an image headache; the brand backlash has included a surge of signups for the rival OpenAI seemed to have bested, Anthropic, whose Claude AI leapt past OpenAI’s ChatGPT to the top of the app charts. Some of that surge can be attributed to Anthropic’s behavior and rhetoric matching up to its brand image as a thoughtful steward of AI that’s mindful of its possible consequences. It’s a brand image that was tested recently when Anthropic wanted to add some caveats to the Pentagon’s desire to use its tech for “all legal purposes.” Anthropic’s Claude, then the only AI agent cleared for use in classified operations, had already been used to plan the recent military action against Venezuela (and was used in preparing for the attack on Iran.) But this evidently harmonious relationship snagged on Anthropic seeking guardrails that would prevent its technology from being used to enable mass surveillance or autonomous lethality. The Pentagon pushed back, and over a few weeks, this spiraled into an acrimonious and very public split that included petulant criticism from the president. The Department of War not only signalled it wanted more compliance as it added AI partners, but threatened to kneecap Anthropic by labeling it a “supply chain risk.” In sticking to its guns, so to speak, Anthropic stayed true to its brand as the serious, non-reckless AI company. In general, Silicon Valley seemed to rally around Anthropic, with employees at Google, Microsoft, and Amazon circulating petitions and open letters urging corporate leadership to follow Anthropic’s example and “hold the line” against objectionable government uses of AI. That was the backdrop when OpenAI’s deal with the Pentagon was announced. While the Department of War had already been in talks with various AI firms to add them to classified use cases, the timing of the announcement came across as if OpenAI was effectively replacing Anthropic. While Altman promised the company had the same “red lines” as Anthropic, it agreed to Pentagon language that permits the technology’s use for “all lawful purposes.” OpenAI insists the contract details establish guardrails, and Altman has said Anthropic should be offered the same deal, and should not be tagged as a security risk. But the timing and what some observers saw as capitulation led to a backlash. Aside from online sniping at OpenAI, the results were plain enough in the app charts, as Anthropic downloads and paid subscriptions spiked. The big-tech Information Technology Industry Council, whose members include Nvidia and Apple, weighed in with a letter of concern about “the Department of War’s consideration of imposing a supply-chain risk designation in response to a procurement dispute.” Research firm Sensor Tower found ChatGPT mobile uninstalls jumped 295%. It was almost the Anthropic vs. Pentagon story run in reverse: Instead of a client battle oddly burnishing a brand, a prestigious new-client deal seemed to blow up in a brand’s face. Altman has called the backlash “really painful,” and the result of poor optics rather than any substantial capitulation or opportunism. He reportedly told an all-hands meeting that the deal was a “complex” decision with “extremely difficult brand consequences” in the short term, but ultimately the correct decision. And this may prove right in the long run. Anthropic is back in talks with the Pentagon about salvaging their relationship. And its investors reportedly want to see more diplomacy and less ego from the company; the brand won’t mean much without clients. Meanwhile there’s still plenty of room for OpenAI to be opportunistic, but maybe do a better job at not looking opportunistic—because the best way to avoid “difficult brand consequences” is to anticipate them. View the full article

German media group has gatecrashed a proposed acquisition by the owner of the Daily MailView the full article

For the past few years, leaders have been trying to decode what’s happening to attention at work. We’ve debated burnout, quiet quitting, and whether younger employees simply approach productivity differently than previous generations. But new workplace data suggests something far more basic may be happening: many employees aren’t disengaged—they’re visually exhausted. New research from VSP Vision Care and Workplace Intelligence found that desk workers now spend nearly 100 hours each week looking at screens, with most reporting that digital eye strain is directly affecting their productivity. Workers experiencing visual discomfort say it reduces their output by nearly a full workday each week—a number that should give leaders pause. It would be easy to frame this as a wellness story or a benefits conversation. But that misses the bigger picture. The data isn’t just about eye health—it’s about how modern work has been designed, and what leaders choose to normalize. We may be measuring engagement while ignoring endurance When performance dips, organizations often look first at motivation or culture. Are employees committed? Are they resilient enough? Do they care about the work? Those questions matter, but they can distract from a quieter reality: the modern workplace now demands an unprecedented level of visual intensity. According to the research, desk workers spend roughly 93% of their waking weekday hours focused on screens. Think about what that means in practice. Back-to-back video calls. Endless message notifications. Constant toggling between documents, dashboards, and email threads. Even roles that once involved physical movement or conversation have shifted toward screen-based workflows. Over time, that level of visual demand changes how people sustain focus. Fatigue builds slowly, and when it finally shows up as distraction or irritability, leaders often interpret it as disengagement rather than overload. But human attention isn’t limitless. And when work requires uninterrupted visual concentration for hours on end, the issue isn’t necessarily a lack of commitment but rather a lack of thoughtful design. Digital fatigue is a culture issue hiding behind a health statistic One of the most revealing findings in the study isn’t just how much screen time employees report, but how little organizational support exists around it. Only about a third of workers say their company actively encourages eye breaks or provides education about managing digital strain, even though most HR leaders acknowledge more should be done. That gap tells us something important about workplace culture. Many organizations have unintentionally equated productivity with constant digital presence. Being visible online becomes a proxy for being valuable. The result is an environment where stepping away from a screen—even briefly—feels risky. Leaders rarely intend to create this pressure. But when expectations around responsiveness remain unclear, employees fill in the blanks themselves. They stay online longer, respond faster, and push through discomfort to signal commitment. Eventually, that behavior becomes the norm. And when productivity starts to slip, we look for explanations everywhere except the most obvious one: we’ve built a system that asks people to maintain visual intensity longer than is sustainable. Why Gen Z isn’t resisting work—they’re questioning the structure Working closely with Gen Z students and early-career professionals has shown me something important: younger employees aren’t rejecting effort. They’re challenging assumptions about what effective work actually looks like. They question camera-on expectations that prioritize appearances over outcomes. They ask why meetings need to run an hour when decisions could be made in twenty minutes. They push for clearer boundaries around communication instead of constant availability. Some leaders interpret this as impatience or a lack of resilience. I see it differently. Gen Z entered the workforce during a period of rapid digital acceleration, and they’re often the first to notice when systems create friction. Their questions can feel uncomfortable, but they also offer valuable feedback. If an entire generation is pushing back on nonstop screen time, it may be less about generational differences and more about a workplace model that hasn’t caught up with human limits. Leaders don’t need more wellness programs. They need better structure. Addressing digital eye strain doesn’t require a complicated initiative. It requires leaders to rethink how work is organized day to day. That might include: Designing meetings with built-in visual breaks or audio-only segments Leaving intentional gaps between calls so employees can reset their attention Setting clear expectations around response times to reduce the pressure of constant monitoring Modeling healthy digital boundaries rather than praising nonstop availability These shifts may seem small, but they change the message employees receive. Productivity stops being about how long someone stays glued to a screen and starts being about the quality of their contribution. In my own leadership work, I often talk about balancing kindness, fairness, and structure. Visual fatigue sits at the intersection of all three. Acknowledging human limits reflects kindness. Creating clear expectations around availability reflects fairness. And designing workflows that support sustainable focus reflects strong structure. When one of those elements is missing, employees feel it, even if they can’t articulate why. The real risk isn’t eye strain. It’s misreading the signal. When attention dips, leaders often assume disengagement. When someone turns their camera off, we question their commitment. But what if those behaviors aren’t signs of withdrawal at all? What if they’re adaptive responses to an environment that demands more visual endurance than most people can sustain? When leaders misread these signals, they create unnecessary tension. Employees feel misunderstood. Managers feel frustrated. And the real issue—an unsustainable rhythm of work—goes unaddressed. The modern workplace has quietly redefined focus as nonstop visual attention. But people don’t perform at their best by staring at screens longer. They perform better when leaders design work with intention. Digital eye strain isn’t just a health warning. It’s a leadership signal. And the future of work won’t belong to organizations that demand constant presence, but to those that know when it’s time to look up, step back, and lead differently. View the full article

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While some girls dream of getting their first designer handbag, Lela Rose—who grew up in Dallas—dreamt of getting her own pair of boots from Lucchese, the legendary luxury bootmaker founded in 1883 in San Antonio. When she got married, her whole family got fitted in Lucchese boots, blending their formal wear with a nod to their Texas roots. Nearly three decades later, Rose is not just wearing the brand—she’s designing for it. Rose’s eponymous clothing label, which she launched in 1998, and Lucchese, the 143-year-old bootmaker, will launch a collaboration on March 10. It’s a partnership that makes sense: two brands with deep Texas roots finally finding each other. The collection comprises three boots, each bearing Rose’s signature blend of femininity and Western romanticism. The standout is a white boot adorned with a sculptural 3D flower and intricate quilted stitching, which is already creating a stir among brides. The partnership goes beyond footwear: Rose’s team has developed an accompanying clothing line that connects directly to the boots, and both brands will cross-sell in their respective stores. (Boots start at $1,295, and clothes start at $650.) The Cowboy Look Is Here to Stay Rose has always wanted to design boots, but she acknowledges that her team didn’t have the skills to make them at the level of craftsmanship she wanted. So she was thrilled when Lucchese was interested in working together. “We are not experts in footwear,” she says. “This was such a great opportunity to partner with someone who completely knows quality and fit, and then we could bring our design aesthetic to that, and vice versa with clothing.” The collaboration feels timely. Historically, Western style has entered the fashion cycle every decade or so, with brands incorporating cowboy boots and shirts into their collections. But over the last several years, something has changed. The Western look has become embedded within the American aesthetic, alongside the preppy look and sportswear. Beyoncé’s Cowboy Carter tour sent Stetsons and fringe flying off shelves. Louis Vuitton staged a Western-inspired runway show featuring real cowboys. Boot brands like Tecovas and Miron Crosby are growing with remarkable speed. And the customer base has shifted—it’s no longer just Texans and ranchers, but New Yorkers, Angelenos, and Bostonians who are wearing boots year-round. The cowboy boot is beginning to be thought of more like a loafer—a wardrobe staple that transcends region and occasion. Lela Rose Has Always Loved Western Style Rose launched her brand in 1998, creating clothes that appealed to her: dresses for a busy social calendar of parties and events that stand out for their sculptural silhouettes, colorful prints, and unapologetic femininity. (Her pieces are at a luxury price point, with dresses that easily hit $3,000 or $4,000, and tops that start at $400.) For Rose, this focus on ranch style isn’t a pivot. Eighteen years ago, she developed a collection of Western-influenced pieces—bead shirts, intricate Western-chic separates—and tried to sell them to Neiman Marcus, Saks, and Bergdorf Goodman. “They all just looked at us like, ‘what?’” she recalls. The timing was wrong, and the collection was quietly shelved, though she loved the shirt so much that she kept it in her permanent collection. When Rose moved to Jackson Hole, Wyoming, five years ago, she decided it was time to pursue her longtime dream of launching a Western line, called Lela Rose Ranch. She’s opened a shop in Jackson Hole that’s built around her personal vision of Western chic and stocked with vintage Navajo silver, one-of-a-kind pieces sourced from her own travels, and clothing designed entirely according to her instincts. The Ranch collection is now being integrated into the main Lela Rose line. Rose started her namesake label at a time when the only way to be relevant in fashion was to have a rack at Neiman Marcus and a runway show at New York Fashion Week. She did both. One year, the theme was “The Roseminster Dog Show,” a tongue-in-cheek riff on the Westminster Dog Show. “I look back on some of our shows as some of my favorite things that we’ve ever done,” she says. “We’re always trying to entertain you as much as show you the clothing.” But the industry Rose launched into no longer exists. The wholesale model and department stores have been disrupted by e-commerce, then disrupted again by social media, then disrupted yet again by a pandemic. These changes scrambled every assumption about how and where people shop. Rose has navigated all of this without outside investors, bootstrapping from a studio with one seamstress to a brand with three retail stores and two more locations opening this year. Over the last 25 years, she’s cultivated a well-heeled, well-traveled customer—a woman with a full social calendar who jets frequently from fundraisers in big cities to more rural locations like Jackson Hole and Aspen, Colorado. Her collections are designed to help these women look appropriate as they navigate across these different situations. That customer, Rose believes, is exactly the person who has been waiting for this Western moment. The pieces she has designed aren’t supposed to look like a costume from a spaghetti Western, but a nod to the outdoors and the heritage of cowboy style. “It’s not like I’m putting on a holster and wearing chaps every day,” she says. “I love this aesthetic, but I want to weave it seamlessly into the rest of my wardrobe.” A denim skirt, she argues, can be worn with a concho belt in Aspen or with heels in New York or with tennis shoes in Paris. The West, in other words, is not a destination anymore. It’s an aesthetic vocabulary, one that Lela Rose has been speaking her whole life. View the full article

If you walked into Oyuna Uranchimeg’s office at the University of St. Thomas’ emerging media department, you’d see a poster from the Beijing 2022 Olympics and two other tokens of Olympic memorabilia. It’s not something you’d likely think twice about. She’s not the only person to have sports-themed office decorations. What you won’t know—unless you’re told—is that Uranchimeg is herself a Paralympian. She competed in Wheelchair Curling for Team USA in 2022, and will do so again in the 2026 Games. But that hasn’t stopped her from working full-time for the university’s emerging media department as an administrative assistant. She’s the department’s problem solver. People file into Uranchimeg’s office all day with an array of different questions. When the department needed to add adjunct professors to take on an expanding course load, Uranchimeg was the one that was on top of the contracts. If a student or faculty member is having an issue with a new online resource, she’s the one who they go to. “She’s the person that everybody sends their folks to,” department chair Dr. Peter Gregg says. “Let’s see if Oyuna can help, or let’s get in touch with Oyuna. So she’s essential to what we do.” Uranchimeg didn’t start curling until 2016, but within just six years, she was on the biggest stage in the sport. It didn’t surprise Gregg. “Oyuna is a pretty extraordinary person,” Gregg said. “So there’s not a lot that she could do that would surprise me.” And she’s not the only Paralympian who works full time outside of their training. From hobby to Team USA Austin Anderson knew Sean O’Neill from their days at Harvard Law School. He thought of O’Neill as a “successful and competent person,” and recommended him for a position at his law firm, Anderson & Kreiger in Boston. They’d kept up from time to time over the last decade, and Anderson knew that O’Neill had picked up curling as a hobby. “I was thinking more like weekend bowling league level stuff,” Anderson says. In March, O’Neill will be going to the Paralympics as part of Team USA Wheelchair Curling. He’s one of approximately 665 athletes from 50 countries that will compete in one of six adaptive sports at the 14th winter Paralympic Games. His coworkers didn’t know that this was a possibility until he told them that he needed to travel to go to Paralympic tryouts. Another coworker, Libby Bowker, remembers O’Neill telling her that he was into curling around the time they first met, but had to “peel back the layers,” over the next few months to learn he was competing at a world-class level. Just before Thanksgiving, O’Neill was selected for the Paralympic team, and since then, he says he’s been traveling every other week. Whether it’s international trips or trips to Wisconsin or Minnesota, he hasn’t been in the office a ton. Despite spending his mornings on the curling ice when on these trips, O’Neill comes right back to his computer and works asynchronously and remotely. Instead of draining his energy, these weeks are what O’Neill lives for. “Activities can reinforce each other and build momentum of a kind,” O’Neill says. “When I’m at a training camp and have a great day of training, and then the next day I’m working on a brief all day, and then I’m kind of jacked up from doing that and have a great training day the next day. I think it all feeds off of each other.” Kombucha instead of coffee He doesn’t need caffeine. Only a kombucha in the morning. But that powers him to accomplish two full days of work within a single day. “I can curl in the morning until 2 o’clock,” O’Neill says. “And still have plenty of time to put in a full day’s work. I come off the ice not necessarily tired, but often energized, and needing an outlet for that energy. It’s not much else that I’m looking to do at that point other than putting some time working.” He’s just another member of the team. He commutes from Cape Cod to Anderson & Kreiger’s downtown Boston office. When Anderson asks him for help around the office, he doesn’t feel like he’s bothering a world-class athlete, but it certainly impacts the way that he views O’Neill from a general perspective. “I’ve developed a new appreciation for the dedication and that work he’s putting into (curling),” Anderson said. “I think I’m a little bit more in awe of him than I used to be.” The job of a lawyer is high-stakes, high-pressure, and intense. It’s time consuming and stress inducing. Many get sucked into a cycle of endless work and don’t find time for themselves. Watching O’Neill at the Paralympics has proven to his coworkers that your life doesn’t have to be all about work. Bowker has been inspired to find her hobbies again. She rediscovered her love for photography, going outside with the camera and just taking pictures. It won’t take her to the Paralympics, but it doesn’t have to in order to improve her quality of life. “I feel like a lot of people abandon interest and personal pursuits especially in their 30s and 40s,” Bowker says. “It definitely has been an inspiration to go back into what I like to do.” “Seeing how wildly different his life is now than like five years ago or when he was in law school, or when he was doing all this important public interest work on the Cape, this is just a totally different, unexpected thing, and it really is inspiring,” Bowker continued. “It does make me wonder, what else is out there? What more can I do? It seems like potential is really limitless, and he’s kind of a walking-talking example of that.” O’Neill struggles with the idea of being an inspiration simply for being a wheelchair user. But he appreciates when people can draw that feeling from his double passions. “The idea of committing to something, whether it’s a hobby, or something you’re driven to get in at the highest level at, or a hobby that turns into that,” O’Neill says. “I think there’s a lot to be said for finding that commitment, finding that drive. Finding other aspects of life, communities, other spaces where you can flourish.” Part of a larger community This month, Uranchimeg and O’Neill will be teammates for Team USA Wheelchair Curling in the Milan Cortina 2026 Paralympic Games, which begin March 6. Both St. Thomas and Anderson & Kreiger are looking forward to seeing their coworker compete for Paralympic glory. In 2022, NBC reached out to St. Thomas to put a camera in their viewing party so it could be shown over the air. Gregg is expecting to do the same once again. “We got a big room with a large projection screen,” Gregg said. “And we brought in a bunch of faculty and students and members of the community and watched her team play. It was really convivial and exciting, and a great bonding moment for us.” Gregg said that it bonded students and faculty in ways that don’t typically occur in academia, all coming together to cheer for one of their own on the big screen. “That’s an important part of being a member of a community,” he added. “I think it’s in the spirit of the Olympics. This idea that we’re all people, and let’s celebrate our excellence as humans.” Meanwhile, in Boston, the Anderson & Kreiger team has really leaned into it. Van Dyke says that there is a firm function planned for O’Neill to teach his coworkers all about wheelchair curling and show them how to curl. “He promised that he was going to take us curling,” Bowker added. “And I’m going to hold him to it.” Anderson said that there are plans for viewing parties and a send-off celebration before O’Neill goes off on the plane. “Every time it comes up,” Anderson said. “It’s like you’re shaking your head, can’t believe it’s happening, ‘how awesome is that?’ Because again, he’s the last guy you’d expect it from because he’s so down to earth and self-deprecating.” Those two aren’t the only ones that will have their offices buzzing. A few of their Team USA Wheelchair Curling teammates also work full-time jobs. Wisconsin’s Matthew Thums is an accountant, and Montana’s Katie Verderber, like O’Neill, is a lawyer. For a few days, they’ll be the pride and joy of the country, performing on national television for all to see. Then, they’ll fade back into anonymity, back in the office, helping their coworkers. View the full article

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Imagine sitting with friends in front of a charcuterie board and a bottle of Syrah at a French bistro. If you reach for your smartphone, a waiter blows a referee’s whistle, issues you a “penalty card,” and tells you a second infraction will get you eighty-sixed. Such faux-pas enforcement is routine at Le Petit Jardin in Montpellier in southern France, which implemented a strict “no-phone use” policy in 2017. While this approach seems farcically extreme, the idea of restricting phone use in restaurants and bars is gaining traction in the U.S., and not just in the “coastal elite” cities. Sneaky’s Chicken, in Sioux City, Iowa, for example, offers compliance incentives: the long-beloved local fried chicken and wing joint now offers discounts every Wednesday night for diners who put their phones in a box. In Nashville, Tennessee, Monell’s is a family-style all-you-can-eat Southern comfort food restaurant that maintains a “no-phones-at-the-table” rule in order to encourage an authentic communal dining experience. Other places, typically ritzier, are starting to require patrons to relinquish their devices at the door, too. With phones at hand, “all of a sudden you hear the little ding or something, and your attention leaves your dining experience, and you’re in a different place,” says Kara Nielsen, a San Francisco Bay Area-based food trend expert with deep experience in the culinary world. She’s not surprised by the appeal of phone restrictions. “Experiential dining is getting very popular with younger people, and it definitely seems part of the millennials’ and Gen Z’s turn toward the analog. So, I think we’re going to see an increase in this type of phone-free experience in the future.” “Going out is a commitment, and guests are seeking out experiences like this.” “If you can’t possibly deal without your phone for two hours, then this is not the place for you,” celebrity chef Tim Love told NBC not long after opening Caterina’s in Fort Worth, Texas, in 2022. The cozy, upscale Italian restaurant has maintained a strict no-phone policy that doesn’t seem to deter patronage, given the restaurant’s continued popularity. As Love said: “You’re, like, ‘I’m just going to sit here and enjoy myself.’ And that’s what happens. It’s been really refreshing.” Britnee Wentworth is the assistant manager and lead bartender and server at Caterina’s. “I was part of the opening team . . . and at the very beginning, the cellphone policy did get a lot of questionable remarks, but I wouldn’t say that necessarily affected business in a negative way,” she says. “It’s actually been contributing to our business in a positive way, especially in the last year and a half or so. Once in a blue moon, we have somebody who is upset by the policy and chooses not to dine with us because of it. But I would say that’s few and far between at this point.” Despite a common misconception, Wentworth says, the cellphone stays with the guest the entire time, in a locked pouch—“similar to what they use at comedy shows and concerts, so that definitely eases a lot of worry.” Echoing Nielsen, she says younger patrons seem “more excited about locking up their cellphones than the 50-and-above customers.” One of the best parts of her job, Wentworth says, is getting to see the fortuitous outcomes that often occur when people are disconnected from their devices. “We have a lot of tables that leave becoming friends with the table next to them, even when there’s a generational gap between them, just because of the conversations that are started,” she says. “It’s definitely been one of the coolest social experiments to be a part of.” About 250 miles south, in San Antonio, Nicosi Dessert Bar opened in June 2024. The Michelin-starred establishment offers “an 8-course tasting menu of 4 bites and 4 mains” in an “intimate 20-seat venue that wraps around the kitchen, inviting guests into a show-and-tell journey alongside the chefs.” Cellphones and photography are prohibited. One Yelp reviewer remarked: “This all-dessert fine-dining experience was creative, unpretentious, interactive, and full of delicious surprises.” In Phoenix, the Trophy Room opened inside a high-end steakhouse and supper club in 2023. The swanky Arizona cocktail bar features an extensive drink menu, plenty of rich dark-wood paneling, and luxuriant furnishings, and is adorned with antique rifles and taxidermy-mounted animals that convey old-school hunting lodge aesthetics. Guests are instructed to check their phones in locked boxes contained within a vintage library card-catalog system. “The Trophy Room is about intimacy and focusing on [what is] in front of you,” says cofounder and operating partner Thor Nguyen. It’s an “escape where there are no distractions, selfie lights, text vibrations . . . from our digital lives.” As for the policy’s impact on business, Nguyen doesn’t think it “affects the bottom line at all. It actually gives our guests an experience, and for them, that’s value,” he says. “Going out is a commitment, and guests are seeking out experiences like this. For other business owners [considering cellphone restriction policies], if you do it, commit to it. You’ll get pushback, but those will be the guests that don’t get it. And that’s okay. You have to believe the intent and make sure you’re creating a complementary experience.” Antagonist, a cocktail bar in Charlotte, North Carolina, is slated to open later this year, and it promises on its website: “Strong drinks. Sharp dialogue. No phones. No distractions.” The list goes on—and is growing. The future of unplugging Restaurants began introducing QR codes for menu access in response to COVID, but they’ve since become ubiquitous. While they may offer a convenient transaction method for getting fast food or coffee at the airport, they also represent a presumptuous push toward a more automated world that contradicts the industry’s foundational promise, and the experience we so crave: to break bread and connect. Meanwhile, an endless stream of ink continues to track the perils of our cellphone-centric lives. In 2013, studies revealed how reliance on cameras impairs memory—the “photo-taking-impairment effect”—and, in effect, dulls our actual experience of life. Research in 2014 found that cellphone use leads to significant changes in brain activity, reaction time, and sleep patterns, and subsequent research has linked it to higher risks of Alzheimer’s disease. Other studies directly correlate cellphone and social media use with a range of mental health issues, especially for young people. In fact, the current landmark lawsuits against Meta (Instagram) and Google (YouTube) are focused on issues of youth safety and the addictive nature of their platform designs. As noted last year in a Washington Post piece about the positive response to phone bans in local D.C. bars, “there is a dawning realization that this constant exposure to the digital world makes us feel less connected to the real one.” Julio Alvarez is a leadership coach, podcaster, and former tech executive who’s been on both sides of the screen, and he senses a seismic shift underway. “To actually be present with another human being in an exchange, in a real connection—that’s becoming the rarest commodity,” he says. With the advent of AI, Alvarez is hopeful the screen-free trend will expand beyond the food and beverage sector. “We’re going to enter a new phase, with an opportunity to combat our addiction to screens with whatever new tech comes out over the next decade,” he says. “There’s a lot of positioning around not adding new screens, but removing them. And what is that going to do? It’s going to force us to deepen our connectivity skills . . . and be present with one another again.” View the full article

“Sean,” the CEO of a health technology startup, invited Garry to join what he called a strategy offsite. By mid-morning, it had become something else. Six people, a whiteboard, a Series A closing in ninety days. The question on the table: where do we invest next? More engineers? A bigger sales team? Another content hire? Garry set down his coffee and asked a different question. “What if we stopped asking what we can afford to build, and started asking what we can now imagine building—that we genuinely couldn’t have a year ago?” The room shifted. So did the conversation. And that reframe—from resource allocation to possibility expansion—is the strategic inflection point that most leadership teams have not yet reached, and it is the one that will separate the companies that use AI to compete from the ones that use it to lead. The research reinforces this point. A recent report from Deloitte finds only 34% of organizations are using AI to deeply transform their work. Another report from McKinsey confirms that companies using AI to pursue growth are 3.5x more likely to achieve enterprise-level impact than those focused on cost reduction. Drawing on our work with senior leaders—Jenny as an executive coach and leadership development expert, and Garry as a physician-entrepreneur who mentors and advises early-stage startups—we have identified three strategies for leading innovation in the age of AI. 1. Start with the Friction, Not the Platform When Garry first met with the founding team of “Axiom Health,” a startup focused on next-generation cardiometabolic biomarker analytics for early disease detection, their conversations were almost entirely about technology. The platform was front and center; the patient was not. He pushed them to slow down. Before talking about what to build, he asked them to map the real tension their future patients and physicians were living with: Where were clinicians hitting walls? What workarounds revealed unmet needs? And what would need to be true for a better solution to be trusted at scale? This is the discipline Marilee Adams calls “question thinking” in her classic business book Change Your Questions, Change Your Life: the shift from judger questions to learner questions. In an era where AI accelerates execution, the quality of the question matters more, not less. Ask yourself: What are the top ten friction points our customers experience—including the ones they’ve stopped mentioning because they’ve assumed they are unsolvable? What alternatives and workarounds do they use today, and what does that tell us about what they actually value? What would need to be true—operationally, culturally, and technically—for our solution to be trusted and adopted at scale? For the Axiom Health team, working through those questions revealed that the core problem was not inconvenience or cost. It was that existing exams produced qualitative, non-reproducible data that couldn’t add any predictive value, leaving physicians making consequential decisions about asymptomatic patients with instruments designed for acute diagnosis. The technology didn’t drive what came next. The friction did. Pro-tip: Before your next product or strategy cycle, run a structured “friction audit” with customers and frontline staff. Surface the frustrations people have stopped voicing. Those shelved grievances often mark the most significant opportunities—and AI may have already made them solvable. 2. Redesign the Process, Not Just the Speed “Lisa,” chief editor of a healthcare media startup, contacted us to collaborate on a strategic repositioning. The picture was stark: double-digit subscription declines, the loss of two anchor advertising partnerships, and a flagship content collaboration with a medical society that had quietly let its contract lapse. The board was asking hard questions. The team was exhausted. Lisa’s first instinct had been to move faster: more content, tighter timelines, a leaner editorial process. When we began the engagement, a different diagnosis emerged. Her team’s publication, “Pulse,” wasn’t failing because it was slow. It was failing because it was building for a media model that no longer existed. As research documents, digital publishing collapsed the advertising revenues that once sustained medical media, and open-access journals grew from 22 to nearly 17,000 by 2021, diluting any single voice’s authority. At the same time, the underlying market opportunity was growing. The healthcare digital content creation market is projected to reach $32 billion by 2030, driven by video, community, and personalized formats. The window wasn’t closing. It was shifting toward platforms and models that Pulse hadn’t yet built. We helped Lisa and her team ask a different question: not how to produce more content faster, but what a media company genuinely designed around the modern clinician would look like. Drawing on models from industry news outlets, YouTube education channels, and AI-powered consumer newsletters, the framework they developed had three components. 1. Shift from content production to community curation. With AI handling synthesis, editors could instead focus on shaping stories and community. That freed up the team to launch a deferred YouTube channel, specialty newsletters by clinical area, and live case discussions that built a genuine practitioner community. 2. Use AI to personalize at scale. Rather than one newsletter for all physicians, AI-assisted segmentation allowed Pulse to tailor content format and cadence by career specialty, stage, and stated interest, creating the experience of a curated resource rather than a broadcast channel. 3. Look outside the category. Durable media businesses across industries had made the same pivot—from audience to community, from passive readership to active membership. Pulse had the clinical credibility to lead that shift in healthcare. The leaders who win won’t be the ones who optimize their existing model. They’ll be the ones who redesign it around what their audience actually needs. Pro-tip: Map your content’s “jobs to be done” for the practitioner: what decision, conversation, or action does your content help them take? If the answer is unclear, the format and cadence are probably wrong—regardless of how good the underlying journalism is. 3. Innovate in Micro-Pilots, Not Master Plans Six months in, the board wanted a diversified revenue model: events, licensing, CME partnerships, sponsored research summaries. Lisa arrived at our next session with the question many overstretched leaders share: how do you innovate when you’re already running at capacity? We pushed back. Recent research from the MIT Media Lab found that 95% of generative AI pilots delivered no measurable business impact, with most stalling because they were disconnected from real workflows (and lacked feedback loops that could help them learn and adapt). The answer to board pressure for innovation is not a bigger plan. It is a smarter experiment design. What we proposed was a micro-pilot framework: structured, time-boxed experiments designed to generate learning quickly and fail cheaply. For each revenue stream, the team would spend no more than six weeks testing the smallest viable version, with AI accelerating both ideation and iteration. Using AI to accelerate ideation velocity and stress-test format concepts (like sponsored series, CME modules, specialty subscriptions), the team surfaced ten viable ideas in the time it once took to develop a single brief. Lisa’s team launched three micro-pilots in the first cohort to pressure test pricing, licensing, and marketing: A specialty cardiology digest with a paid tier hit break-even subscriber numbers within five weeks. A sponsored research summary format generated strong advertiser interest but poor reader engagement and was modified. A marketing pilot was shelved entirely. The cost of the failure was two weeks of editorial time. The learning it produced shaped the next cohort of experiments. The leadership posture the AI era demands is not the confidence to predict which innovations will succeed—it’s the discipline to find out quickly which ones won’t. AI compresses the time between hypothesis and evidence. Leaders who build that loop into their team’s work gain a structural advantage that compounds. Pro-tip: For each strategic bet, define the smallest version you could test in thirty days with AI-accelerated ideation. Ask: what would we need to learn to make the next decision? That question, not the size of the pilot, is what separates useful experiments from expensive distractions. The Imperative The offsite conversation we opened with didn’t end with a bigger budget. It ended with a better question—and that question changed what the company built. The pattern holds across every engagement: the leaders who make the most meaningful progress are not those with the most resources or the most sophisticated tools. They are the ones willing to slow down long enough to ask what actually needs solving, to redesign instead of accelerate, and to treat a failed experiment as data rather than defeat. Start with the friction. Redesign the process. Experiment at speed. These are not technology strategies. They are leadership disciplines. What has changed is that AI now makes them executable at a scale and pace that was previously out of reach for most organizations. The bottleneck was never the tools. It was the quality of the questions leaders were willing to ask. Efficiency will keep the lights on. Imagination is what decides whose lights are worth watching. View the full article

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