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Sometimes, it's not the tasks on your to-do list that overwhelm you, but simply the act of sorting them out and figuring out where to start. Before you can prioritize your responsibilities and setting out a schedule for getting everything done (using strategies like "eating the frog" or creating a 1-3-5 to-do list), you have to identify what those big tasks are and what capacity you have to take them on. If you are the type of person that finds it helpful to visualize these things, let me introduce you to a pair of strategies that both involve imagining tasks as rocks: The "pickle jar theory" and the "big rocks theory." What is the pickle jar theory?The pickle jar theory is an excellent mental exercise for anyone who thinks or processes things visually. It was conceptualized by Jeremy Wright in 2002, based on the idea that a pickle jar holds a finite amount of content. So, too, does your day. There is only so much you can do in a day, as there is only so much you can stuff into a pickle jar. When thinking of your day as a pickle jar, imagine it full of three things: Rocks, pebbles, and sand. These represent your daily responsibilities, but as you can see, they’re different sizes. You can fit more of the smaller stuff, like sand and pebbles, than you can rocks, but rocks can still take up half the jar. How does the pickle jar theory work?To use this kind of thinking, you need to categorize your day’s tasks. Start by writing them all down, then prioritizing them using the Eisenhower Matrix, which is useful for figuring out which tasks are urgent and important, urgent and not important, not urgent but important, and not urgent and not important. (Even better: This too is a visual system. You design a matrix and plot your tasks along the graph.) Then, assign each task to a rock, pebble, or sand, like this: Rocks are the big tasks that are important, necessary to get on right away, and/or will take up a major chunk of time. Studying for a test, finalizing a major project at work, or cleaning the house can be rock-sized tasks, for instance. Pebbles are the things that are important to do, but not immediately necessary or massively time-consuming. You can fit quite a few of them in the jar, depending on how many rocks you have in there. Sand represents the small things that you need to do to keep your day moving along or just want to do. It enters the jar last and fills up the gaps between the bigger items. Sand can be anything from answering emails, going to meetings, calling your mom, or relaxing. These aren’t necessarily urgent or time-consuming, but they’re still important to your work or mental wellbeing. Visualize yourself putting one to three rocks in the jar, three to five pebbles, and as much sand as can fit. Understanding that not every single thing you need to do can always fit in there, you can make decisions about which rocks, pebbles, and sand pieces to hold over for the next day’s jar. This works because it gives you a tangible example of your own capacity, but also reminds you that even when your day is full of “rocks” and “pebbles,” you still have room for “sand.” Don’t forget to let some of the sand be enjoyable, because breaks are integral to productivity. Don’t over-stuff your jar with rocks and pebbles to the point that you have no room for sand at all, and don’t forget that other people have their own jars that might not be as full. Consider delegating some “pebble” tasks to a teammate, whether it’s a coworker or your spouse, or eliminating the unnecessary tasks altogether. On your Eisenhower Matrix, these will be the ones that are neither urgent nor important. Finally, you can make a so-called "to-don't" list if you're having a hard time figuring out what not to put in the jar. These can be lists of things you can just ignore, or lists of things to delegate or delay; regardless, knowing what isn't crucial before you start planning will help you fit in what is. What is the big rocks theory?There is a simplified version of the idea above that can work for you, too, if you don't want to categorize your tasks into rocks, pebbles, and sand, but want something a little more streamlined. You might be familiar with the concept of "big rocks" if you've read Stephen Covey's popular book, The Seven Habits of Highly Effective People. Essentially, as with the pickle-jar mindset, you should think of your time, energy, and resources like a big container and the things you need to do as rocks or gravel. You can't fit very many big rocks in there, but you can fit a few and still have room for the smaller tasks. The big ones take away from the space—your resources and time—so you have to be intentional about how many you really try to fit in. Visualizing is important, but you still have to use that to make a plan and get things done. First, write down everything you need to do on one page, whether in a digital word processor or a physical notebook. Then, consider how much time, energy, and other resources each thing will take and mark it as either a rock or gravel. Unlike other task prioritization methods, like the Eisenhower matrix mentioned above, this can be pretty loose. Just put down your best guess about how much each task will drain you. (When you're short on time, opt for this big rocks approach over the pickle jar approach because of its relative simplicity.) Once you have everything designated as a rock or gravel, schedule the rocks first. Here's where you can use time boxing to clearly carve out dedicated time for each thing you have to do. Keep in mind that if you schedule and work on gravel activities—emails, phone calls, doing the dishes, whatever—without taking on the big rocks first, you'll never get around to the big rocks; the smaller tasks are usually pretty endless, so you need to prioritize the big ones. Go back to your visualization: If you put all the gravel into your vessel before the big rocks, you'd fill it up and leave no room, but if you put in the big rocks first, then add the gravel, the gravel will fall between the rocks and settle in where it can. Identifying the resource-heavy, demanding tasks and prioritizing those ahead of the more menial stuff will allow you to actually make time to tackle it so you can fit the rest in where you can. But be a little judicious with that scheduling: Don't load a full day of big rocks into your schedule. You'll burn yourself out. Instead, choose only one or two per day, then allocate the rest of your time to those maintenance tasks. As you get better at incorporating this method into your workflow, you won't really need to think about rocks and jars anymore (unless you want to). You can shift over to a method like a 1-3-5 list, which calls for the pre-planning and completion of one big task, three medium-sized ones, and five little ones each day. Just keep in mind that medium tasks can become big tasks if put off for too long, and that you might need to turn preparation work for larger tasks into one of your smaller tasks. View the full article

Today’s consumers get pulled in a thousand different directions online: Scrolling YouTube Shorts. Tracking TikTok influencer content. Browsing Gmail promotions. Deciding whether the latest viral Facebook video is real or AI. And that’s all before lunch. Once, the path between intent and conversion was nearly a straight line. Now, in our new attention economy, constant advertising noise makes buying decisions much more complex. Most advertisers, however, have not adjusted to this new dynamic. They’re only focused on showing up when intent is obvious in search, missing entire audiences who never reach the search bar. Google’s Demand Gen campaigns help advertisers escape this trap by speeding discovery and shortening the sales funnel. Success isn’t complicated, but it requires mastering three elements: sharp creative, sophisticated audience strategies, and rigorous testing. The Demand Gen opportunity Demand Gen combines Google’s visual placements, including YouTube, Gmail, and Discover, with advanced audience targeting and creative optimization. It’s like social advertising built for Google’s network. These campaigns reach users who are passively browsing rather than actively searching, making them ideal for driving awareness. Consumer behavior has fundamentally shifted toward visual discovery while also requiring more touchpoints before making a buying decision. YouTube, a predominantly visual platform, is now the second-most-used social media platform, with 2.6 billion monthly users worldwide. Across nearly every digital channel, content consumption has become visual first, making the purchase funnel flatter, noisier, and more complicated. Unfortunately, many advertisers approach Demand Gen campaigns like search, expecting immediate conversions. That approach misses the point. Demand Gen isn’t a bottom-of-funnel activity. It’s about interrupting consumption, sparking interest, and building intent over time. Marketers who understand the mindset shift can create compounding performance that grows stronger with every impression. Here’s the search marketer’s playbook for getting Demand Gen campaigns right the first time. Element 1: Creative that commands attention Modern tools have democratized content creation to the point where advertisers no longer need to hire expensive agencies to create high-quality creative assets. This new dynamic matters because great visual content drives conversions. YouTube viewers are twice as likely to buy something they saw in a video and four times as likely to use the platform to find new products. Advertisers must get comfortable creating high-quality visual storytelling, or they won’t be speaking the language of consumers. The four-part framework for Demand Gen creative Developing effective creative assets doesn’t have to be a mystery. The best pieces follow a four-part framework: Grab attention immediately: Don’t assume people will pay attention to you. Earn their attention in the first three seconds to stop the scroll. Build brand recognition: Create a consistent visual identity across all placements to reinforce brand recall when consumers search later. Create emotional resonance: Help people think or feel something meaningful. Provide clear direction: Give viewers a clear next step. What should they do after watching? Testing creative approaches Testing is also an essential part of creative development. Try out different content types, like educational, product-focused, and testimonial content. Educational content might build awareness at the top of the funnel, while testimonials drive consideration mid-funnel and product-focused creative converts at the bottom. Test to find what works for your audience, and optimize the creative for each placement. What works on YouTube may not work on Gmail or Discover. Dig deeper: Google’s Demand Gen upgrade: Key changes and success strategies Element 2: An audience strategy that matches intent Creating an audience strategy goes hand in hand with creative development. Advertisers should not message every audience the same way, and some creative approaches will be more effective at different funnel stages. Before spending money, understand who your audience is and what action you want them to take. To do this, I always begin with the classic reporter’s questions: Who is your target audience? What are you trying to tell them? Where are they getting information? Why would they be interested in your message? Once you’ve defined your audiences, you can begin aligning your messages to their journey stages. Whatever message you send should push them to the next step rather than forcing a conversion. Get the newsletter search marketers rely on. See terms. Audience targeting recommendations Now that you’ve defined your audiences and developed the appropriate creative to message them, you can determine the best way to target them in your Demand Gen campaigns. The options here are nearly endless. Start by creating custom audiences because they offer the most control and specificity. Build them using keywords, URLs, or apps, and go after people who are likely to take the action you want. Lookalike audiences are back in Demand Gen campaigns, so you can target prospects similar to your current customers. You can also target affinity and in-market audiences, enabling you to message people with broad interests and those in the active consideration phase. Campaign structure best practices As you begin launching Demand Gen campaigns, here are a few best practices to follow: Start with both remarketing and prospecting as separate campaigns. They will need different goals, targeting options, and possibly different placements. Let campaigns run for at least 30 days before iterating or expanding. Consider running separate campaigns to target specific placements, like Gmail, Discover, or YouTube. Test shorts-only campaigns. The mobile-first, vertical format converts differently because users make on-the-spot decisions on mobile. Customers need to see consistent messaging and brand visuals across all placements. This consistency builds brand recall and reduces the touchpoints needed before purchase. Dig deeper: Google pushes Demand Gen deeper into performance marketing Element 3: Testing and optimization Now that your Demand Gen ads are up and running, it’s time to start testing and optimization. These campaigns contain numerous variables, making it essential to create a methodical strategy that tests a single variable at a time. Remember, this process isn’t about finding an answer. It’s about continuous optimization. What works today may need refining in three months. Establishing testing parameters Begin your testing by focusing on three different categories. Creative: This process tests which creative elements drive better responses. Think: content types (educational vs. testimonial), hooks or vertical vs. horizontal videos. Placement: Some creative approaches perform differently depending on where people see them. So try testing the same content on Gmail, Discover, and YouTube and track the results. Audience: Compare performance across different audiences, like custom vs. lookalike or remarketing vs. prospecting. As you continue testing, use performance trends to inform future creative, messaging, and placement decisions. When you see an approach consistently working, you can also begin scaling by increasing budgets in a particular placement or audience. Set realistic time horizons Early Demand Gen results won’t reflect long-term impact. Brand awareness needs time to take hold with users. Give campaigns 60 to 90 days to stabilize and begin compounding. Why Demand Gen campaigns fail Most advertisers don’t fail at Demand Gen execution. They fail because they measure it incorrectly and give up too early. This is the number one reason why advertisers avoid Demand Gen entirely. Here are three common mistakes marketers make and how to avoid them. Unrealistic expectations Too many advertisers enter Demand Gen campaigns expecting similar return on ad spend results to those of bottom-of-the-funnel search campaigns. Then, when these Demand Gen campaigns show seemingly disappointing ROI numbers, they abandon them entirely. The fix here is setting appropriate expectations from day one. Demand Gen is brand-building work that fills your sales funnel and delivers compounding results when it’s allowed to work as designed. Measurement myopia This mistake often accompanies unrealistic performance expectations. Relying only on last-click attribution severely undervalues your Demand Gen investment. These campaigns are likely contributing to growth in ways you may not be seeing. So instead of last-click-only, consider these alternatives: Use platform comparables: This new Google Ads metric uses a view-through methodology, much like social ads, and gives a broader picture of campaign performance. Observation mode: Add Demand Gen audiences to search campaigns and track if they drive more branded searches over time. Holistic brand metrics: Is the brand growing across all channels? If so, it’s an indication of increasing brand awareness. If you only look at last-click returns, you’re undervaluing your investment. Unrealistic timelines Don’t pause campaigns before 30 days if they’re not performing as expected, and don’t make dramatic changes too quickly. Commit to a 60- to 90-day evaluation window and build patience into stakeholder expectations. Master discovery to win the future Consumer attention is at its maximum, and the evolution of paid media is visual-first and discovery-driven. Brands that rely only on search will struggle to grow. Success in this new environment depends on three fundamentals: Compelling creative. Strategic audience targeting. Disciplined testing. Together, these elements create compounding performance that builds lasting brand awareness. The competitive advantage belongs to advertisers who master discovery now. Fortunately, getting started doesn’t require massive budgets. All it takes is a commitment to the fundamentals and patience with the results. Demand Gen campaigns are the key to becoming part of your target audience’s daily online life. View the full article

I am seeing some signs of a Google search ranking update over the past day or so but the chatter is super limited right now. Many of the tools spike yesterday but like I said, the SEO community chatter was calm. I wonder if this volatility was related to maybe the Cloudflare outage or Gemini 3 rolling out.View the full article

A court document from the Department of Justice Google monopoly case shows Google internally discussed six different options for giving (or not giving) publishers control over AI usage. The options range from do nothing new to add options to opt out of just AI Overviews (formerly known as SGE).View the full article

Google announced some new features for Google Maps including a big one for reviews, where reviewers can now use nicknames instead of their real names when leaving reviews. Plus, Google added trending places to the explore tab and insider tips/know before you go to the results.View the full article

Only two months ago, Google officially rolled out the follow feature on Google Discover. Now, that feature is no longer active and Google has removed the documentation associated with it.View the full article

Google's Daniel Waisberg announced today at the Google Search Central event in Tel Aviv that Search Console will be gaining brand query filters. Plus, these filters will be AI-assisted, I am told.View the full article

Google is testing shading the background color behind the search ads, sponsored results, and the local pack in the Google Search results. I do like that Google is testing differentiating the organic/free listings with the search ads/sponsored listings.View the full article

From forecasting to post-peak analysis, here’s how advanced PPC teams turn demand volatility into long-term growth. The post How To Manage Demand Fluctuation During Key Ecommerce Shopping Seasons appeared first on Search Engine Journal. View the full article

New York City scaffolding is so commonplace it has become a kind of extra architectural skin covering the city. It’s estimated that there are more than 9,000 of these “construction sheds” (another term for scaffolding) installed across the city, enough to stretch nearly 400 miles if they were put end to end. They do the important work of shielding pedestrians from potential falling debris during building construction and renovation projects, but they also shroud large swaths of sidewalk in dark and cloistered tunnels made of an unfortunate jumble of steel poles and plywood. Construction scaffolding is the city’s ubiquitous, utilitarian, and mostly unpleasant necessary evil. And now, a new effort aims to rethink their form with a series of new, more appealing designs. Six new designs for scaffolding have just been announced by New York City’s Department of Buildings, and they replace the dark and convoluted sheds of today with bright, airy, and open versions. The new scaffolding designs come from two design teams led by the New York-based architecture and urban design firm Practice for Architecture and Urbanism (PAU) and the global design and engineering firm Arup. Simplified and minimal, each of the six designs turns the workaday construction shed into a more open and accessible add-on to the built environment. Time for a makeover The new designs are a result of the “Get Sheds Down” initiative, an effort launched by the city in 2023 to update the look of construction sheds and revise the rules and regulations that govern when and where they’re used. The sheds currently in use in New York—and many other cities—have been largely unchanged since the 1980s. Usually hunter green and made up of a kit of parts consisting largely of steel poles and plywood, the current shed system is a boxy shield, but it’s also an obstacle for people moving down sidewalks, entering buildings, or getting in and out of vehicles on the street. After a public bidding process, the city hired two design teams led by PAU and Arup to reimagine the shed. They were asked to create six designs for alternative sheds that maintain public safety while also improving the pedestrian experience, beautifying the streetscape, and keeping the cost of installing sheds reasonable for building owners. PAU’s three designs use a slanted form, a transparent roof, and a streamlined kit of structural parts to make a much more open and airy shed. “We were very focused on the pedestrian experience,” says Vishaan Chakrabarti, founder of PAU. “The slanted design lets more light and air in. It’s a very simple thing.” Just as important, Chakrabarti says, was the elimination of the cross bracing between columns, X-shaped metal poles that act almost like walls on the existing sheds. PAU’s design makes each column stronger so that only one horizontal beam is needed to connect them. The baseline version of the shed uses this configuration with a transparent roof. A large version can be used for bigger buildings and broader sidewalks with more widely spaced structural columns that double up to provide more strength. And for smaller-scale projects or emergency installations, PAU has designed a version that uses a high-strength netting on its slanted side, offering safety and a nearly clear view to the sky above. A new take on an old form Arup’s three designs also bring in noticeably more light than the existing shed system, while also offering variability for the different conditions found across the city. One design, named the Rigid Shed, uses a grid-based structural system with prefabricated connection nodes, minimizing materials and connections during assembly. Another design, the Flex Shed, has a similar grid approach but with an even simpler set of posts and beams that can be adjusted in three dimensions to accommodate things like street trees, fire escapes, and the dozens of types of street furniture and infrastructure that exists on city sidewalks. Maybe the most elegant of all the six solutions, the Air Shed is a balcony-like cantilever that only anchors to the sidewalk at points alongside the building. Rather than creating a tunnel people have to traverse, it forms a thin canopy overhead that some people might not even notice. “The inspiration for the Air Shed is essentially a wall-mounted shelving system,” says Seth Wolfe, a principal at Arup. Arup has been working on these ideas for more than a decade. The firm first got involved back in 2009 when it partnered with the architecture firm KNE Studio on a submission to another city-led shed redesign effort. KNE Studio’s design was a finalist in that design competition, and the two firms remained in contact and continued to work on new shed designs in conjunction with the shed installing company Core Scaffolding. When the Get Sheds Down initiative launched, the team was primed to participate. “We had momentum going into the RFP,” says Kevin Erickson of KNE Studio. “We had stuff cooking on the backburner.” The six new designs resulting from the “Get Sheds Down” initiative join a range of scaffolding types in use in cities around the world, with a range of materials and price points. The winner of New York City’s 2009 shed design competition, Urban Umbrella, is now a provider of upscale sheds across the city. Simpler approaches are also in use. Chakrabarti notes that scaffolding in Hong Kong is still made from bamboo. He even suggested early on in the Get Sheds Down process that maybe that wouldn’t be such a bad idea in New York. “I actually asked the question,” he says. “I got laughed at.” New York City’s Department of Buildings is now working with PAU and Arup to make the designs available for public use by builders and contractors doing construction and renovation work on buildings across the city. Next, each of the new designs will be made into mockups that can be evaluated and tested. Some of these new shed designs could begin appearing at building sites and on city sidewalks before the end of 2026. The six new designs add to what Chakrabarti calls a “menu” of options for builders in the city, some of whom may still opt to use the existing system. He says providing more choice is a way to achieve the main goal of the initiative, which is to improve the experience of people in New York City who will inevitably encounter construction sheds. “You can use a Lego set to build an ugly thing, or you can use a Lego set to build a beautiful thing,” Chakrabarti says. “But the first thing you’ve got to do is understand the Lego set.” View the full article

For much of its history, marketing thrived on creativity, intuition and an almost magical ability to connect with audiences. Campaigns were conceived in brainstorming sessions, executed over weeks or months and celebrated (or dissected) once the results rolled in. Theodore Levitt’s “The Marketing Imagination” stays on most marketers’ bookcases alongside their team’s awards. Much of the technology we buy inside marketing is mostly isolated and gives fractal views of the customer, never a complete one and never of the customer in motion (with or without us). The one platform to solve it all has been the misnomer we have been hunting for but will never find. The promise of a single point of heuristic overview is as unlikely as a nirvana state. That model is rapidly disappearing. In its place is a new reality for new college entrants, mid careerists and senior management looking to break the glass ceiling into the board room. Marketing as a continuous, data-driven and precision-engineered system. The artistry remains, but it’s wrapped in structures, processes and toolchains more familiar to software developers than to Mad Men. This isn’t theory. It’s the inevitable outcome of digital transformation — the central premise of “The Digital Helix,” which frames modern business as a living, adaptive DNA strand. In this DNA, marketing stops being a series of isolated campaigns and becomes an always-on engine of growth, fueled by data and shaped by customer signals in real time. From campaigns to continuous systems In the analogue era, campaigns had clear beginnings and endings. Teams worked in long arcs — brief, create, launch, measure, repeat. But digital customers don’t wait. They move fluidly across channels, expecting brands to respond instantly to their behaviors and preferences. This forces a shift from episodic campaigns to continuous systems: self-correcting, learning and evolving without the need for a restart. Engineers call this continuous integration; in marketing, it means messaging, content, and offers can change dynamically mid-stream, without pausing for a quarterly review. In this new environment, marketing isn’t just storytelling. It’s system design and it needs constant engineering (sprints, scrums, design, match up and perform and adjust mindsets). How we work — and the skills and mindsets we’re looking for — are going to transform who we are, and fast. Add agents, add GenAI and our teams need to think like learning software engineers, evolving from an MVP launch into something highly tuned and ongoing. Why the shift is happening now There are five key forces pushing marketing into an engineering mindset. 1. Data as the core material In engineering, everything starts with inputs. In marketing, those inputs are data: every click, search, purchase and pause in a video. These signals act like sensors, feeding an engine that decides what happens next. Modern marketing teams use real-time customer telemetry to guide decisions, trigger automated responses the moment certain conditions are met and maintain predictive models the way developers maintain codebases. Data isn’t an afterthought. It’s the raw material from which every experience is built. It is the DNA of these situations and not data as an afterthought from opinion. Not all data is perfect; most is directional but frequent review and adjustments with it gets marketing the north star. Every day, marketing leaders should be looking at the data that signals, shapes and even lets them construct new Origami ideas from it. 2. Modular, reusable assets drive everything. Think Lego, think Tesla, think Amazon — sovereignty over your assets is a moat. Software developers rarely build from scratch. They use libraries and frameworks. Marketing is adopting the same principle. Instead of creating bespoke content for each campaign, brands are building modular content objects: video snippets, dynamic templates, copy blocks — all designed to be reused, recombined and deployed across platforms. Some forward-thinking brands are even developing “APIs for brand” — structured repositories of logos, imagery and copy that partners and products can tap into instantly. And just like engineers, marketers are adopting version control, tracking the evolution of creative so they can roll back or iterate faster. Lego does this extremely well. There are 3,400 different molds and tens of millions of different models or set possibilities. Tesla is 100% dedicated to module design. Software developers use containers to move code around. The world has gone modular. Just look inside an Amazon warehouse. It’s all modular. Marketing has been too slow to embrace this global precedent. 3. Agile becomes the default, not the exception. This means comfort with degrees of success and learning, not winning or losing. Agility is no longer optional. Annual planning cycles can’t keep pace with shifting customer expectations. Marketing teams are moving to sprint-based workflows, borrowing directly from Agile software development. This means Scrum-style stand-ups across creative, analytics, and operations, the ability to deliver rapid prototyping of offers and messages, tested live with small audience segments and most importantly iteration based on performance data, not assumptions or beliefs. Agile marketing turns the department from a lumbering ship into a nimble fleet of fast-moving vessels — sort of your own version of Drake against the Spanish Armadas. 4. Journeys as living architectures require shepherds of the TQM The “funnel” is dead. What we have now is more akin to an experience architecture — an interconnected network of pathways that adjust based on customer behavior. Journey orchestration platforms function like traffic control systems, routing customers to the most relevant touchpoints in real time. When performance dips, marketers diagnose the “experience outage” and reroute flows, much like engineers reroute network traffic. In this model, journeys are not diagrams on a wall. They’re dynamic, reconfigurable systems based on connected moments where a target might enter, abandon, store, or share with others. Think in the target’s journey and the moments of choice, not in the outcome you want. The journey must be stewarded and curated at every point, and everybody owns the quality of that experience and not just the piece they might touch. Think TQM for marketing journeys. 5. AI and automation as the toolchain will lead to agent-to-agent marketing as the norm. In software development, toolchains manage the build, test, and deployment process and invariably vast swathes of the testing. In marketing, AI and automation are becoming our equivalent. Generative AI accelerates creative production and personalization. Predictive AI identifies high-value customers and moments to intervene. Automation frameworks ensure consistent execution across regions and languages. The marketer’s workstation of the future will look as much like a developer’s IDE as a designer’s studio. If this scares you, that is a legitimate concern. Orchestrated machine learning will lead to agent-to-agent futures in marketing where agentic and intelligent agents work together around parameters to deliver work products. Engineers with empathy — Marketing’s new mandate If all this sounds mechanical, it’s worth remembering one of the key truths from “The Digital Helix”: transformation doesn’t erase humanity — it enhances it. Engineering disciplines still require deep user understanding. Marketing’s human touch, empathy and creativity remain essential. The difference is that these qualities now operate inside scalable, measurable systems. Tomorrow’s marketers (as in, truly, tomorrow) will be comfortable discussing APIs, automation triggers and model accuracy. They will need to be fluent in design thinking, data science, and automation logic from a senior and a very junior perspective and they will have to be able to be storytellers who test and refine narratives the way engineers prototype features. A new marketing playbook The parallels between engineering and marketing are striking: Engineering PrincipleMarketing EquivalentExampleModular designReusable campaign componentsA product launch template that auto-localizes for each regionContinuous integrationAlways-on optimizationCreative that self-adjusts daily based on engagementAutomation pipelinesOrchestrated journey flowsTriggered nurture sequences tied to live customer signalsMonitoring & alertsExperience dashboardsInstant alerts when sentiment dropsVersion controlIteration managementTracking every revision of messaging This playbook isn’t theoretical. It’s already in use by leading brands. The Digital Helix in practice and the inevitable future In a true Digital Helix organization, marketing and engineering mindsets merge. Data intelligence and customer empathy twist together in every decision. Systems are designed for continuous improvement, not one-off success. Getting there requires technology investment in modular content systems, automation and analytics, cross-disciplinary learning between marketers, engineers and data scientists, shifting KPIs to measure system health and adaptability, not just campaign ROI. Customer expectations are being set by the smoothest, fastest experiences they encounter — whether ordering a coffee, streaming a show, or booking a ride. Meeting those expectations demands precision, speed, and adaptability. Engineering disciplines have excelled at this for decades. Now, marketing must follow suit. The marketers of tomorrow will think like engineers, design like architects, and create like artists. They’ll build systems that run 24/7, learning and improving in the background, while they focus on what no algorithm can replace: the human connection. That’s the future of marketing — and it’s already being built. View the full article

Strategy textbooks taught us that sustainable competitive advantage that commanded premium prices was best protected by powerful barriers to entry. Build a moat, create switching costs, leverage access to high costs of entry, own distribution channels, and it would be difficult for startups to compete for your markets. But the forces of disruption operate by different rules, systematically destroying the very foundations of pricing power by making the previously difficult and expensive suddenly easy and cheap. The basis of competition changes, from excellence along well understood dimensions of merit to “good enough.” The ‘good enough’ revolution in pricing I have sympathy for incumbents. They’re accustomed to working really hard to deliver on demanding criteria for quality, reliability, and excellence, only to find that fickle customers are spending their money on “good enough” that do just fine. Consider some examples: “Peak book” and the advent of e-readers. E-readers lack the tactile satisfaction of turning pages, the smell of paper, and the aesthetic appeal of a beautifully bound book, not to mention the satisfaction of having an author personally sign your copy (if the latter doesn’t matter to you, please don’t break my heart and tell me). Yet e-books offer instant delivery, the ability to carry thousands of books in one device, adjustable fonts, built-in dictionaries, and search functionality. For many readers, that’s good enough. Further, Amazon can sell bestsellers for $9.99 because the marginal cost is near zero, undermining hardcover pricing power. And we’re now in a world where AI makes it easy for anybody to author a book, commoditizing the authority that being a book author used to convey. Digital Board Games vs. Physical Board Games. Electronic games lack the social ritual of gathering around a table, handling physical pieces, and reading opponents’ body language. But they enable play with friends anywhere in the world, handle all rules automatically, provide instant matchmaking with strangers, and eliminate setup/cleanup time. A $40 board game becomes a $5 app. Of course, there is a big debate about whether becoming subservient to the companies that want you to rent, rather than own, is a good thing or not. Streaming Fitness vs. Gym Memberships. Peloton, Apple Fitness+, and YouTube workouts can’t replicate the full equipment range of a commercial gym, the fine-tuning of a professional coach, or the energy of in-person classes. But they eliminate commute time, remove scheduling constraints, offer unlimited class variety, and provide privacy for self-conscious exercisers. A $30/month digital subscription undermines $150/month premium gym memberships for many users. In the industrial age, you could count on scarcity. It was hard to manufacture with quality at scale. It was hard to do advanced engineering. It was hard to source and assemble materials. For many of us, disruptors change the basis of competition entirely by removing the constraints that once justified premium pricing. The mechanics of price erosion Traditional pricing power rested on three pillars: scarcity, complexity, and friction. Companies could charge premiums because their offerings were hard to access, difficult to replicate, or cumbersome to replace. Disruptive technologies attack all three simultaneously. Take professional photography. The scarcity of skilled photographers, expensive equipment, and darkroom expertise once justified substantial fees. Smartphone cameras and AI-powered editing apps haven’t just reduced these costs—they’ve eliminated entire categories of photographic services. The wedding photographer still commands premiums, but passport photos, real estate listings, and product shots have been democratized beyond recognition. The financial services industry offers another compelling example. Robo-advisors now provide portfolio management that once required expensive human advisors. The algorithms aren’t more sophisticated than what top wealth managers offer, but they’ve made “good enough” portfolio management available for basis points instead of percentage points. When Charles Schwab can offer comprehensive financial planning for free as a customer acquisition tool, traditional advisors’ ability to charge 1-2% annually becomes increasingly tenuous. Strategic implications for incumbents In a world where technology makes everything easier and cheaper, competitive advantage increasingly comes from business model innovation rather than product superiority. Amazon Web Services doesn’t charge premiums because its infrastructure is superior; it dominates because it transformed computing from a capital expense to an operating expense, fundamentally changing how companies think about IT resources. The most successful responses involve three strategic moves. First, companies need to be open to unbundling their offerings, recognizing that customers will no longer pay premiums for features they don’t value. Second, they must shift from product-centric to ecosystem-centric thinking, finding new sources of value in sticky network effects and data rather than in the core product itself. Third, they must embrace the reality that in many categories, the price will trend toward marginal cost—which in digital goods means effectively zero. The new basis of competition As traditional pricing power erodes, new sources of competitive advantage emerge. Speed of innovation, ecosystem orchestration, and customer intimacy become more valuable than product features. Creating stickiness that makes it hard to switch, adding value to the experience and reinforcing new forms of scarcity – perhaps embedded in algorithms – are all powerful ways that digital firms sustain competitive advantage. Spotify, for instance, operates in a world where recorded music is effectively free. Its pricing power doesn’t come from exclusive content but from its recommendation algorithms, social features, and ecosystem integrations. The premium isn’t for the music—it’s for the experience around the music. And for artists, their revenue is increasingly coming from what is scarce – the experience of attending a live performance. The bad news is that for many experts with years of investment in the old paradigms, the good enough revolution will make their experience less valuable. The good news is that democratizing who can create what’s good enough can be a basis for massive growth. View the full article

Timothée Chalamet just posted an 18-minute-long video to his Instagram to promote his upcoming A24 film, Marty Supreme. It might be his best role yet. In the video, Chalamet—sporting a bright yellow tank top, buzz cut, and dainty necklace—joins a Zoom call full of supposed marketing executives who will be leading the promotional campaign ahead of the film’s release on December 25. After awkward introductions, Chalamet proceeds to fill up the meeting’s airtime with increasingly ridiculous suggestions for the film’s marketing efforts, leaving the eight other members of the call scrambling to accommodate his wild ideas. On A24’s YouTube channel, where the video is posted under the title “Timothee_Chalamet_internal_brand_marketing_meeting_MartySupreme,” it’s gained almost 100,000 views. And on Chalamet’s personal Instagram, it’s been watched almost 10 million times. The campaign, which is a parody of an actual marketing meeting, sees Chalamet fully commit to the part of “snobbish actor with no regard for his coworkers”—and clearly, it’s resonating. The meta concept sticks the landing by balancing absurdist humor with an uncanny eye for the moments that make our digital workplaces just a little bit universally awkward. An absurd ad campaign you just might buy into Marty Supreme, directed by Josh Safdie, is a sports-comedy film loosely based on the life of American ping-pong player Marty Reisman. The most information that we have about the film thus far comes from A24’s official trailer, released on November 11, in which Chalamet embodies a version of Marty who’s brash, determined, and extremely self-confident. Those characteristics come out in full force through the new Marty Supreme ad, which plays like a surrealist comedy of errors about how not to behave in a Zoom meeting. Less than two minutes into the call, Chalamet has already taken control of the meeting, explaining that his philosophy for the movie’s marketing is led by three principles: “culmination,” “integration,” and “fruitionizing” (which he admits is not a real word). Things only get weirder from there. First, Chalamet suggests that his character, Marty Supreme, appear on boxes of Wheaties cereal. Then he gears up to introduce something his creative director has been “working on for six months,” only to reveal a single orange color swatch. Finally, he escalates to suggesting that Marty Supreme’s marketing should include a fleet of blimps, an activation at the Statue of Liberty, and an orange Eiffel Tower. As Chalamet’s ideas get more and more grand, the other people on the call are forced to keep a straight face. It’s a particular genre of humor that plays unbelievable absurdity against the everyman, a concept that’s seen success in shows like Nathan for You, The Rehearsal, and I Think You Should Leave. Subtly skewering Zoom meetings for the sake of cinema Where the new Marty Supreme ad really shines, though, is in its subtle dissection of the awkward Zoom call, an experience that almost every remote worker suffered through during the pandemic. From the painfully long introduction sequence to the clunky shift to screen sharing (during which Chalamet reveals a computer background of himself receiving an award), constant interruptions, and sprinklings of corporate-speak, every beat feels like a truly torturous meeting. While it’s unclear exactly why A24 chose to advertise Marty Supreme through advertising parody (considering that it’s a movie that doesn’t seem to have anything to do with the marketing world), the video does seem particularly geared toward an online audience of young Chalamet fans. By balancing the ridiculous with the real, the ad strikes a relatable note that’s perfectly suited to attracting modern viewers. “i feel like I am an imposter in a professional zoom meeting,” one Instagram user wrote under the video. “i know this is supposed to be a joke, but I’ve been in a lot of entertainment marketing meetings, they are exactly like this,” another fan wrote on YouTube. Some may argue that Dune or Call Me by Your Name represent Chalamet’s best work. Marketers everywhere know it’s “Timothee_Chalamet_internal_brand_marketing_meeting_MartySupreme.” View the full article

Here’s the thing about Wellington boots: They’re great when it’s raining, because they keep your toes dry and toasty. But when the rain stops, you feel a little silly stomping around in heavy rubber boots. But what if your rain boots looked like any other fashion-forward boot you’d be comfortable wearing rain or shine? What if they looked like, say, a classic pair of Dr. Martens? I have good news. Dr. Martens has designed a rain boot that mimics one of its most iconic designs, the 1460 eight-hole lace-up boot, which first came to market in 1960. It has a lot of the hallmarks of a Dr. Martens boot, like the heel tab for easy pull-on, the grooved sole, and even the stitching. What’s different though, is that each component is waterproof, ensuring that your feet will stay dry in puddles and downpours. “You style this boot just like you would any other Dr. Martens,” says Adam Meek, Dr. Martens’ chief product officer. “You could wear them to a festival, or a night out on the town.” The Comfort Boot That Became A Sensation Dr. Martens was originally founded by a German doctor, Klaus Martens, in the post-war years. At the time, most boots were made from hard leather and provided very little arch support. After he hurt his ankle in a skiing accident, he began tinkering with the design of a new kind of boot made from softer leather with soles that had air pockets that provided cushioning and bounce. This distinct insole was later branded “Airwair” and has been incorporated into the Dr. Martens logo. The shoes he prototyped were so comfortable that he decided to sell them for £2 (£68.31 or $90 in today’s money). Within five years, the brand was selling so many shoes that Martens decided to open his own factory and sell them globally. In 1960, the brand launched the 1460, a lace-up boot distinctive yellow stitching and a pull tab, which went on to become the brand’s best-selling style, and continues to be popular today. Dr. Martens shoes immediately took off with working class people who needed durable, comfortable everyday shoes. They were quickly adopted by postal and factory workers. But as the brand entered the ’60s and ’70s, the brand became popular with youth subcultures, including mods, punks, goths, new wave musicians, and hippies. And today, Meek says the brand continues to have a very wide range of customers. Last year, the brand generated £787.6 ($1.03 billion) in global revenue, which was a 10% dip from the year before, partly due to the overall slow down in the U.S. market. “From a design perspective, we stick very closely to the brand’s original design principles, which are grounded in simplicity and comfort,” he says. “But that has allowed for enormous versatility, and allows people to use it as a vehicle for self-expression. We sell boots to young people trying to make a statement, and older people just looking for comfort.” Designing a Rain Boot That Doesn’t Look Like One While many Dr. Martens fans wear their boots out in inclement weather, since many styles are fairly water resistant, the brand hasn’t designed many truly waterproof boots in its 78-year history. To design the new 1460 rain boot, Meek went back to the brand’s archive, and found boots that the original Dr. Marten designed before he even launched his brand. He found one that was waterproof, but did not have the silhouette of the Wellington boot, which has become the de facto rain boot design of our time. This inspired the team to think about how to reinvent the rain boot to look more like a traditional Dr Martens boot. “It was obvious there was a need for more rain boots,” he says. “Extreme weather means that it is becoming wetter in many parts of the world. We wanted to create a versatile boot that stayed true to the brand.” The team took the structure of the 1460 boot, but tried to make it fully waterproof. The boot is made from PVC plastic. All elements that would let water seep in have been eliminated, such as laces. And while there appears to be stitching around the heel, these are actually faux stitches: The heel is actually heat sealed to the upper using Goodyear Welting technology used to make tires. And the sole features that same comfy AirWair technology. Fashioning for Durability For the original working class people who embraced Dr Martens, it was important that the boots were durable, because they didn’t have a lot of disposable income to frequently replace footwear. Meek says that that durability continues to be an important design principle. Most boots within the brand’s catalog are designed so they can be easily re-soled by slicing off the sole with a heated knife, and sewing on a new one. In fact, the brand has a resale site where customers can send in old boots, which will be resoled and then resold. The company is in the early stages of developing a system that will allow customers to send in their old shoes to be refurbished so they can hold onto them for longer. These rain boots have been designed along the same principles. They’re made from heavy duty materials that will live up to years of inclement weather, and eventually, when the sole wears out, it will be possible to replace them with a welting process. For Meek, this is important because this encourages more environmentally-friendly behavior. “We approach sustainability through longevity,” he says. “I like to think of our products as something you can hand down to a family member, along with all the stories they carry.” View the full article

Ways to rank in AI Overviews include focusing on long-tail queries, carefully structuring content, etc. View the full article

Spend a few minutes on developer Twitter and you’ll run into it: “vibe coding.” With a name like that, it might sound like a passing internet trend, but it’s become a real, visible part of software culture. It’s shorthand for letting AI generate code from simple language prompts instead of writing it manually. In many ways, it’s great. AI has lowered the barrier to entry for coding, and that’s pulled in a wave of hobbyists, designers, and side-project tinkerers who might never have touched a codebase before. Tools like Warp, Cursor, and Claude Code uplevel even professional developers, making it possible to ship something working in hours instead of weeks. But here’s the flip side: when AI can move faster than you can think, it’s easy to run straight past the guardrails. We’ve already seen how that can go wrong, like with the recent Tea app breach, which shows even polished, fully tested code can hide critical vulnerabilities if humans don’t review it thoroughly. Optimizing for speed over clarity lets AI produce something that works in the moment, but without understanding it, you can’t know what might break later. This isn’t just technical debt anymore; it’s a risk to customer trust. The instinctive reaction to solve this trade-off is to throw more tech at the problem: add automated scans, add a “secure by default” setting. Those things matter. But I’d argue that failure in vibe coding doesn’t start with tooling, it starts with leadership. If you don’t lead your team through this new way of working, they’ll either move too slow to benefit from AI or move so fast they start breaking things in ways a security checklist can’t save you from. The real job is steering, not slowing down When we built agentic coding agent Warp 2.0, we put a simple mandate in place: “Use Warp to build Warp.” That means every coding task started with prompting an AI agent. Sometimes it nailed it in one shot; sometimes we had to drop back to manual coding. But the point wasn’t dogma, it was to force us to learn, as a team, how to work in an agent-driven world. We learned quickly that “more AI” doesn’t automatically mean “better.” AI can write a thousand lines of plausible-looking code before you’ve finished your coffee. Without structure, that’s a recipe for brittle, unmaintainable systems. The real challenge was getting people to treat AI-generated code with the same discipline as code they wrote themselves. That’s a leadership problem. It’s about setting cultural norms and making sure they stick. Three things leaders need to get right 1. Hold developers accountable The biggest mental trap is treating the AI as a second engineer who “owns” what it wrote. It doesn’t. If someone contributes code to a project, they own that code. They need to understand it as deeply as if they typed it out line by line. “AI wrote it” should never be an excuse for a bug. Leaders can’t just say this once; they have to model it. When you review code, ask questions that make it clear you expect comprehension, not just functionality: “Why does this query take so long to run?” “What happens if the input is null?” That’s how you set the standard that understanding is part of shipping. 2. Guide AI with specifics Using large, one-shot prompts is like cooking without tasting as you go: sometimes it works, but usually it’s a mess. AI is far more effective when you request small, testable changes and review them step by step. It’s not just about quality, it also builds a feedback loop that helps your team get better at prompting over time. In practice, this means teaching your team to guide the AI like they’d mentor a junior engineer: explain the architecture, specify where tests should live, and review work in progress. You can even have the AI write tests as it goes as one way to force smaller, verifiable units of work. 3. Build the review culture now In AI workflows, teams move fastest when AI and humans work side by side, generating and reviewing in small steps. The first draft of a feature is the most important one to get eyes on. Have someone review AI-generated work early and focus on the big-picture questions first, like whether it’s secure, reliable, and solves the right problem. The leadership challenge is making reviews a priority without slowing anyone down. Have teams aim to give feedback in hours, not days, and encourage finding ways for work to keep moving while reviews happen. This builds momentum while creating a culture that values careful, early oversight over rushing to get something done. Guardrails only work if people use them Safety tools and checks can help catch mistakes, but they don’t replace good habits. If a team prioritizes speed over care, AI guardrails just get in the way, and people will find ways around them. That’s why the core of leading in the AI era is cultural: you have to teach people how to integrate AI into their workflow without losing sight of the fundamentals. The teams that get this right will be able to take advantage of the speed AI enables without bleeding quality or trust. The ones that don’t will move fast for a while, until they ship something that takes them down. Vibe coding isn’t going away, and I think that’s a good thing. So long as teams lead with people, not just technology, they will come out ahead and create better experiences for users along the way. View the full article

For its 2026 postage stamps, the U.S. Postal Service is going colorful and graphic. USPS gave a first look at some of the stamps set to be released next year, including the latest edition of its Love stamp, stamps commemorating the 250th anniversary of the U.S., and stamps depicting figures including a boxer, a martial artist and actor, and a pair of published poets. The stamps will be released on a rolling basis beginning in January and available at Post Office locations and online. “This early preview of our 2026 stamp program underscores the Postal Service’s commitment to celebrating the artistry and storytelling that make stamps so special,” Stamp Services director Lisa Bobb-Semple said in a statement. “Each stamp is a small work of art — an entryway into a larger story that connects people, places and moments in history.” Many of the stamps are bright or use typography in bold or creative ways. The 2026 Love stamps are a series of four illustrations of stylized red, white, and blue birds by illustrator James Yang that were inspired by midcentury U.S. design and Japanese children’s book illustrations, according to USPS. Stamps for Muhammad Ali designed by USPS art director Antonio Alcalá show an Associated Press photo of the boxer with his gloves up and his last name in big, all-caps, sans-serif type in red and black that evokes a boxing match promotional poster. A painting of Bruce Lee by artist Kam Mak shows the martial artist and actor against a yellow brushstroke background as he kicks the words “USA FOREVER” and “BRUCE LEE,” which were cleverly angled to look like he snapped them in two. For its “Figures of the American Revolution” stamps, multiple artists depict 25 people, from household name Founding Fathers like George Washington and Benjamin Franklin to lesser known figures as Deborah Sampson, the only woman to earn a military pension in the war after she dressed up like a man called Robert. The diverse selection of people were chosen to represent the Revolution as a collective effort, USPS says. “It’s unusual to design a pane of stamps featuring 25 different portraits” USPS art director Ethel Kessler said in a statement. “But that number felt essential. How else could you begin to tell the story of the Revolution’s complexity with fewer?” The typographic “Declaration of Independence” stamp also marks next year’s anniversary with “1776” written out in feather quill pens by typographer Juan Carlos Pagan. The “Lowriders” stamps pay homage to customized lowrider cars with photos by Philip Gordon and Humberto “Beto” Mendoza and gothic-style type paired with flourishes borrowed from lowrider paint jobs. Photographer David Schwartz contributed images for the “Route 66” stamps, which celebrate the 100th anniversary of the iconic highway. Other forthcoming stamps including “International Peace” showing an origami crane by Peace Crane Project founder Sue DiCicco, “Bald Eagle: Hatchling to Adult,” a pane of five stamps depicting the life of America’s national bird, and a stamp commemorating Colorado’s 150th anniversary. Writer Phillis Wheatley, who published what’s believed to be first book by a woman of African descent in the American Colonies, appears on the 49th Black Heritage stamp by artist Kerry James Marshall. Sarah Orne Jewett, a novelist and poet, appears on the 35th Literary Arts series by artist Mark Summers. Next year’s Lunar New Year stamp shows a horse mask by Sally Andersen-Bruce. USPS says more stamp announcements are forthcoming, and it’s also planning to rerelease an old stamp next year as part of its Stamp Encore Contest. View the full article

Finance of America is buying Onity's MSRs and loan pipeline in this niche as PHH retains its role as a subservicer and remains involved in buyout securitization. View the full article

Adobe's purchase of Semrush signals the growing importance of SEO platforms as digital marketing struggles with AI-driven uncertainty. The post SEO Community Reacts To Adobe’s Semrush Acquisition appeared first on Search Engine Journal. View the full article

US president endorses move to restrict regulation by states after lobbying from Silicon Valley View the full article

Tech giants are making grand promises for the AI age. The technology, we are told, might discover a new generation of medical interventions, and possibly answer some of the most difficult questions facing physics and mathematics. Large language models could soon rival human intellectual abilities, they claim, and artificial superintelligence might even best us. This is exciting, but also scary, they say, since the rise of AGI, or artificial general intelligence, could pose an uncontrollable threat to the human species. U.S. government officials working with AI, including those charged with both implementing and regulating the tech in the government, are taking a different tack. They admit that the government is still falling behind the private sector in implementing LLM tech, and there’s a reason for agencies to speed up adoption. Still, many question the hyperbolic terminology used by AI companies to promote the technology. And they warn that the biggest dangers presented by AI are not those associated with AGI that might rival human abilities, but other concerns, including unreliability and the risk that LLMs are eventually used to undercut democratic values and civil rights. Fast Company spoke with seven people who’ve worked at the intersection of government and technology on the hype behind AI—and what excites and worries them about the technology. Here’s what they said. Charles Sun, former federal IT official Sun, a former employee at the Department of Homeland Security, believes AI is, yes, overhyped—especially, he says, when people claim that AI is “bigger than the internet.” He describes the technology simply as “large-scale pattern recognition powered by statistical modeling,” noting “AI’s current wave is impressive but not miraculous.” Sun argues that the tech is “an accelerator of human cognition, not a replacement for it. I prefer to say that AI will out-process us, not outthink us. Systems can already surpass human capacity in data scale and speed, but intelligence is not a linear metric. We created the algorithms, and we define the rules of their operation. “AI in government should be treated as a critical-infrastructure component, not a novelty,” he continues. “The danger isn’t that AI becomes ‘too intelligent,’ but that it becomes too influential without accountability. The real threat is unexamined adoption, not runaway intelligence.” Former White House AI official “I was worried at the beginning of this . . . when we decided that instead of focusing on mundane everyday use cases for workers, we decided at a national security front that we need to wholesale replace much of our critical infrastructure to support and be used by AI,” says the person, who spoke on background. “That creates a massive single point of failure for us that depends largely on compute and data centers never failing, and models being impervious to attacks—neither of which I don’t think anyone, no matter how technical they are or not, would place their faith in.” The former official says they’re not worried about AGI, at least for now: “Next token prediction is not nearly enough for us to model complex behaviors and pattern recognition that we would qualify as general intelligence.” David Nesting, former White House AI and cybersecurity adviser “AI is … fantastic at getting insights out of large amounts of data. Those who have AI will be better capable of using data to make better decisions, and to do so in seconds rather than days or weeks. There’s so much data about us out there that hasn’t really hurt us because nobody’s ever really had the tools to exploit it all, but that’s changing quickly,” Nesting says. “I’m worried about the government turning AI against its own people, and I’m worried about AI being used to deprive people of their rights in ways that they can’t easily understand or appeal.” Nesting adds: “I’m also worried about the government setting requirements for AI models intended to eliminate ‘bias,’ but without a clear definition of what ‘bias’ means. Instead, we get AI models biased toward some ‘official’ ideological viewpoint. We’ve already seen this in China: Ask DeepSeek about Tiananmen Square. Will American AI models be expected to maintain an official viewpoint on the January 6th riots? “I think we’re going to be arguing about what AGI means long after it’s effectively here,” he continues. “Computers have been doing certain tasks better than people for nearly a century. AI is just expanding that set of tasks more quickly. “I think the more alarming milestone will be the point at which AI can be exploited by people to increase their own power and harm others. You don’t need AGI for that, and in some ways we’re already there,” Nesting says. “Americans today are increasingly and unknowingly interacting online with fake accounts run by AI that are indistinguishable from real people—even whole communities of people—confirming every fear and anxiety they have, and validating their outrage and hatred.” Abigail Haddad, former member of the AI Corps at DHS The biggest problem currently, Haddad argues, is that AI is actually being underused in government. An immense amount of work went into making these tools available inside of federal agencies, she notes, but what’s available in the government is still behind what’s available commercially. There are concerns about LLMs training on data, but those tools are operating on cloud systems that follow federal cybersecurity standards. “People who care about public services and state capacity should be irate at how much is still happening manually and in Excel,” she says. Tony Arcadi, former chief information officer of the Treasury Department “Computers are already smarter than us. It’s a very nebulous term. What does that really consist of? At least my computer is smarter than me when it comes to complex mathematical calculations,” Arcadi says. “The sudden emergence of AGI or the singularity, there’s this thing called Roko’s basilisk, where the AI will go back in time and—I don’t remember the exact thing—but kill people who interfered with this development. I don’t really go for all of that.” He adds: “The big challenge that I see leveraging AI in government is less around, if you will, the fear factor of the AI gone rogue, but more around the resiliency, reliability, and dependability of AI, which, today, is not great.” Eric Hysen, former chief information officer at DHS When asked a few months ago about whether AI might become so powerful that the process of governing might be offloaded to software, Hysen shared the following: “I think there is something fundamentally human that Americans expect about their government. . . . Government decision-making, at some level, is fundamentally different than the way private companies make decisions, even if they are of very similar complexity.” Some decisions, he added, “we’re always going to want to be fundamentally made by a human being, even if it’s AI-assisted in a lot of ways. It’s going to look more long term like heavy use of AI that will still ultimately feed for a lot of key things to human decision makers.” Arati Prabhakar, former science and technology adviser to President Biden Prabhakar, who led the Office of Science and Technology Policy under President Joe Biden, is concerned that the conversation about AGI is being used to influence policy around the technology more broadly. She’s also skeptical that the technology is as powerful as people foretell. “I really feel like I’m in a freshman dorm room at 2 in the morning when I start hearing those conversations,” she says. “Your brain is using 20 or 25 watts to do all the things that it does. That includes all kinds of things that are way beyond LLMs. [It’s] about 25 watts compared to the mega data centers that it takes to train and then to use AI models. That’s just one hint that we are so far from anything approximating human intelligence,” she argues. “Most troubling is it puts the focus on the technology rather than the human choices that are being made in companies by policymakers about what to build, where to use it, and what kind of guardrails really will make it effective.” This story was supported by the Tarbell Center for AI Journalism. View the full article

Michelle had barely knotted her apron strings before the day turned ugly. “When I told her I could only serve regular coffee—not the waffle-flavored one she wanted—she threw the boiling-hot pot at me,” she tells Fast Company, recounting one violent encounter with a customer. Working at a popular all-day breakfast chain, Michelle has learned that customer “service” often means surviving other people’s rage: “I’ve been cussed out, had hot food thrown on me…even dodged a plate thrown at my head,” she says. Lately, the sexual comments from male customers have gotten worse. (Workers in this story have been given pseudonyms to protect them from retaliation.) Still, she shows up, because she hopes to save enough to launch her own business soon. Once upon a time, “the customer is king” was a rallying cry for better service. Today, it’s a management mantra gone feral. What began as good business sense, touted by historic retail magnates like Marshall Field and Harry Selfridge, has curdled into a corporate servitude that treats employees as expendable shock absorbers for awful behavior and diva demands. With the holiday rush looming, customer-facing workers in cafés, call centers and car garages are bracing themselves to smile through every client’s tantrum—no matter how absurd. Rampant hostility—and it’s getting worse At Michelle’s workplace, the patron always comes first, while the safety of staff barely makes the list. Even after several viral videos of incidents at the chain’s restaurants, she says her complaints rarely go anywhere. One of her managers will step in if he sees something on the floor that’s out of line, but others just ask what she did to provoke it. “It makes me angry, yet I feel I just have to take it,” she says. “It’s an epidemic.” That dynamic is baked into North American service culture. “The ‘customer is king’ mantra has become a free pass for people to act however they want, with impunity,” says Gordon Sayre, a professor at Emlyon Business School in Lyon, France, who has been studying its impact on employees. “It breeds entitlement—and that entitlement gets abused, leaving workers with almost no room to push back.” The mantra dictates that service staff stay deferential—careful about their every word and gesture—while clients hold the upper hand. With some workers getting all of their take-home pay from tips and gratuity, customers can quite literally decide how much an employee earns. And according to Sayre’s research, that mix of financial power and enforced politeness makes sexual harassment at on the job more likely. The data mirrors reality. In a 2025 survey of 21,000 US frontline workers in healthcare, food service, education, retail, transportation, more than half (53%) said they’d recently faced verbally abusive, threatening or unruly customers. There’s also been a meaningful uptick in customers acting out. According to Arizona State University’s annual National Customer Rage survey, 43% admit to having raised their voice to show displeasure, up from 35% in 2015. And since 2020, the percentage of customers seeking revenge for their hassles has tripled. Such encounters take a toll: employees on the receiving end are twice as likely to report that their jobs are damaging their physical health, and nearly twice as likely to feel unsafe at work, according to analytics platform Perceptyx. ‘Management didn’t back my coworker’ Madison has been a server for more than a decade, bouncing between casual spots and fine dining rooms. These days, she’s at a former Michelin-starred restaurant in New York, and she’s long since accepted the industry’s devotion to ‘customer is always right.’ She sees it play out nightly, usually when someone insists a dish isn’t cooked properly, or worse, admits they just don’t like it. “There’s a specific type of persnickety person who gets drunk on the power of being rude and demanding,” she tells Fast Company. “Once I spot a table with that vibe, I know I’m in for a long night.” The problem is, the mentality rewards bad behavior. Recently, a diner claimed he’d only had one beer—when it was clearly two. “Management didn’t back my coworker, and the guy was charged for just one, which ultimately comes out of our tip pool,” says Madison. “He might have left with a bad taste, but he still got what he wanted.” Most hospitality staff Fast Company spoke with said the same thing: comping drinks, desserts, and even entire checks has become routine when someone complains. That generosity, however, comes at a time when restaurants and bars can least afford it. Across the US, the industry is being squeezed from both sides—soaring labor and ingredient costs on one end, and cautious consumer spending on the other. Growth in 2025 has been even slower than during the pandemic lockdown years. So why are so many establishments still giving freebies to difficult customers? Because in the age of online reviews, every unhappy diner is a one-person marketing department, ready to dish out brutal takedowns. A single post can tank a spot’s reputation, and naming individual staff is common practice. To avoid bad publicity, businesses are trading profit for peace, and making sacrifices to get those all-important five-star ratings. Even a middling three-star review, which most customers equate to a good or average experience, can obliterate visibility on platforms like Yelp or Google. For individual frontline employees, those digital judgments hit harder. A dip in ratings can mean being moved to a slower section or losing a lucrative shift. And in the platform gig economy, where algorithmic rankings rule, a single bad review can mean less work, or none at all. Danielle, a salon owner in Washington, remembers when an unhappy client not only left a bad review, but recruited 200 others to do the same. “I’ve no idea how she found so many people, but it was traumatizing watching one-star reviews just flood in,” she says. Danielle has contacted Google and Yelp in the past, but they refuse to remove reviews. Even on online platforms stuffed with fake and fraudulent bot reviews, the customer is always right, right? ‘Rest assured, we’ll be talking about you behind your back’ The real problem with the beloved slogan isn’t the complaints or stingy tips. It’s the emotional contortion required to stay polite while being treated like a punching bag. Rose Hackman, author of Emotional Labor: The Invisible Work Shaping Our Lives and How to Claim Our Power, interviewed service workers across the industries for her book and found a resounding answer: what counts isn’t the service, it’s the smile. “Emotional labor is highly devalued, feminized and rendered invisible, despite it being one of the most central forms of work in our economy,” says Hackman. “We need to value it more.” Of course, that responsibility sits not just with consumers, but with employers too. Until the culture actually changes, employees cope the best they can. Avery, a server in an upmarket seafood restaurant in Philadelphia, has gotten better at protecting herself with age. “I used to fold like a beach chair to their needs and demands, but I’m less willing now,” she explains. “Outside of this job, I’m a performer, and there are similarities there: I put on a mask, act out a show, then the lights come up, I clock out, and I get to be someone else.” Sadly, no coping strategy is perfect. “Closing yourself off and faking an emotion—also known as surface acting—can look professional, but it impacts your mood,” explains Sayre. “Trying to fix the situation or reframe the customer’s behavior can protect your emotional health, but hurts performance.” Instead, venting with trusted coworkers acts as a vital pressure valve—a place to express real emotions and recover from the constant stress. Jesse, a New York bartender, is amazed by the “rancid” behavior he sees on the daily, but the camaraderie with his team keeps him sane. “If you walk in and make my life harder, talking to me in a way you would never speak to a friend or your mother; babe, you’ve decided what our relationship is gonna be,” he says. “Rest assured, we’ll be talking about you behind your back, laughing and joking about how you’re dressed.”With ‘customer is king’ still reigning, America desperately needs a reminder about the inherent social contract of emotional labor—a contract that only works if respect flows both ways. Without it, the whole system falls apart, leaving behind burnt-out staff and sour customers. As Jesse says: “You’re a guest in my home, so I’m gonna take care of you. All you have to do is enjoy your night, and pay me for the work I do.” View the full article

You’ve just finished a strenuous hike to the top of a mountain. You’re exhausted but elated. The view of the city below is gorgeous, and you want to capture the moment on camera. But it’s already quite dark, and you’re not sure you’ll get a good shot. Fortunately, your phone has an AI-powered night mode that can take stunning photos even after sunset. Here’s something you might not know: That night mode may have been trained on synthetic nighttime images, computer-generated scenes that were never actually photographed. As artificial intelligence researchers exhaust the supply of real data on the web and in digitized archives, they are increasingly turning to synthetic data, artificially generated examples that mimic real ones. But that creates a paradox. In science, making up data is a cardinal sin. Fake data and misinformation are already undermining trust in information online. So how can synthetic data possibly be good? Is it just a polite euphemism for deception? As a machine learning researcher, I think the answer lies in intent and transparency. Synthetic data is generally not created to manipulate results or mislead people. In fact, ethics may require AI companies to use synthetic data: Releasing real human face images, for example, can violate privacy, whereas synthetic faces can offer similar benefit with formal privacy guarantees. There are other reasons that help explain the growing use of synthetic data in training AI models. Some things are so scarce or rare that they are barely represented in real data. Rather than letting these gaps become an Achilles’ heel, researchers can simulate those situations instead. Another motivation is that collecting real data can be costly or even risky. Imagine collecting data for a self-driving car during storms or on unpaved roads. It is often much more efficient, and far safer, to generate such data virtually. Here’s a quick take on what synthetic data is and why researchers and developers use it. How synthetic data is made Training an AI model requires large amounts of data. Like students and athletes, the more an AI is trained, the better its performance tends to be. Researchers have known for a long time that if data is in short supply, they can use a technique known as data augmentation. For example, a given image can be rotated or scaled to yield additional training data. Synthetic data is data augmentation on steroids. Instead of making small alterations to existing images, researchers create entirely new ones. But how do researchers create synthetic data? There are two main approaches. The first approach relies on rule-based or physics-based models. For example, the laws of optics can be used to simulate how a scene would appear given the positions and orientations of objects within it. The second approach uses generative AI to produce data. Modern generative models are trained on vast amounts of data and can now create remarkably realistic text, audio, images, and videos. Generative AI offers a flexible way to produce large and diverse datasets. Both approaches share a common principle: If data does not come directly from the real world, it must come from a realistic model of the world. Downsides and dangers It is also important to remember that while synthetic data can be useful, it is not a panacea. Synthetic data is only as reliable as the models of reality it comes from, and even the best scientific or generative models have weaknesses. Researchers have to be careful about potential biases and inaccuracies in the data they produce. For example, researchers may simulate the home-insurance ecosystem to help detect fraud, but those simulations could embed unfair assumptions about neighborhoods or property types. The benefits of such data must be weighed against risks to fairness and equity. It’s also important to maintain a clear distinction between models and simulations on one hand and the real world on the other. Synthetic data is invaluable for training and testing AI systems, but when an AI model is deployed in the real world, its performance and safety should be proved with real, not simulated, data for both technical and ethical reasons. Future research on synthetic data in AI is likely to face many challenges. Some are ethical, some are scientific, and others are engineering problems. As synthetic data becomes more realistic, it will be more useful for training AI, but it will also be easier to misuse. For example, increasingly realistic synthetic images can be used to create convincing deepfake videos. I believe that researchers and AI companies should keep clear records to show which data is synthetic and why it was created. Clearly disclosing which parts of the training data are real and which are synthetic is a key aspect of responsibly producing AI models. California’s law, “Generative artificial intelligence: training data transparency,” set to take effect on January 1, 2026, requires AI developers to disclose if they used synthetic data in training their models. Researchers should also study how mistakes in simulations or models can lead to bad data. Careful work will help keep synthetic data transparent, trustworthy, and reliable. Keeping it real Most AI systems learn by finding patterns in data. Researchers can improve their ability to do this by adding synthetic data. But AI has no sense of what is real or true. The desire to stay in touch with reality and to seek truth belongs to people, not machines. Human judgment and oversight in the use of synthetic data will remain essential for the future. The next time you use a cool AI feature on your smartphone, think about whether synthetic data might have played a role. Our AIs may learn from synthetic data, but reality remains the ultimate source of our knowledge and the final judge of our creations. Ambuj Tewari is a professor of statistics at the University of Michigan. This article is republished from The Conversation under a Creative Commons license. Read the original article. View the full article

It took the Equinox Group—the parent company of luxury gym chain Equinox, Equinox hotels, and Soulcycle—around five years to recover from COVID. But the company has recovered, claiming that 2025 will be a record year from a profitability perspective. This year, it announced big plans for expansion. Harvey Spevak, executive chairman and managing partner of Equinox Group, tells us about the company’s plan to open 40 clubs in new markets, its expansion into the Middle East, and the real reason it ditched Kiehl’s for Grown Alchemist. In the next couple of years, Equinox plans to open 40 new clubs. What is driving this growth? We’ve always been a high growth company leading up to COVID. COVID was pretty rough. The way we thought about our strategy was to rebound the business and then get back to growth and transformation. We’re back to high growth from a financial perspective. From a growth perspective, there’s tremendous demand for the Equinox brand and the Equinox offering in existing markets, and also in lots of new markets. Over the last 12 months, we’ve built a pretty robust pipeline, like you’ve mentioned. That 40 locations is probably closer to 50 at this point. We’ve opened a bunch of locations in new markets this year. We opened our first in Philadelphia Rittenhouse, which is performing extremely well; better than we expected. We opened our first in Seattle in June, also exceeding our expectations. In the fall, we’re opening our first in San Diego. By the end of the year [we’ll have opened], San Diego, West Loop of Chicago, another one in New York, another one in Los Angeles and Santa Monica. We’re excited about all of these. We’ll open five locations between now and by January. How do you decide which new markets to enter? Our real estate team is very knowledgeable about all the markets where we’ve always wanted to go. When I say the markets, it includes cities as well as zip codes, if not by block. That’s a big part of why our unit economics are so strong. But the world has changed in terms of where there is demand. While there continues to be great demand in some of our existing markets like Manhattan, Southern California, Northern California, there’s new markets where we didn’t exist before. I mentioned Philadelphia or Seattle, but then there’s also the South. We recently announced our first location in Nashville that’ll open next year. We think South Florida will become our third biggest market outside of New York and Los Angeles. And a lot of that’s because of the migration of people from New York and other markets. We’re opening our first location in West Palm Beach next month. We sell memberships in advance of opening, and the response has been absolutely outstanding. In West Palm Beach, we started selling memberships in June—the worst time of the year it could be selling memberships, but we did that because we were going to open in November and we’re going to open with a member count that is higher than what we thought we would achieve in four years. We’ve all read about the migration to Florida, but what do you think are the factors leading for places like Nashville to become new markets? These markets are evolving rapidly and there’s greater desire for health and wellness broadly. It’s become a bigger priority during and coming out of COVID than ever before. That’s a global phenomenon. Then you think about the Equinox offering and the authority the brand has around high-performance living; it’s just kind of a perfect storm. Are you opening more Equinox hotels? We have a pipeline on the hotel side of around 10 to 12 new hotels. The difference is the gestation period for a hotel is much longer, particularly when you’re building a new hotel as compared to a club. It takes years. Our next hotel is opening in the Red Sea in Saudi Arabia in spring of 2026. Why the Red Sea? Because there was demand for our brand, our hotel, our club, our entire offering. We also have branded residential there, which is another part of our offering now. But there was a lot of interest in bringing us to a resort location. It’s a beautiful setting. It’s some of the most magnificent water you’ve seen in the world. It’s an undeveloped piece of real estate in Saudi Arabia. So in partnership with the government there and the Sovereign Wealth Fund, they have built out a big area, a marina. Us and some other hotels are going to be operating there. Ours is designed by David Rockwell, and we’re excited about that. We’ve already announced another hotel in Saudi Arabia. There’s one unannounced that’s coming—there’s potentially one, if not two, more in the region. Then we’ve also announced one in Nashville. There’s one we’re working on the Caribbean. It’s remarkable who stays at our hotel now. It’s literally a who’s-who of Fortune 100 companies to people out of Hollywood or in the music industry. Why is the Middle East an attractive location for you to set up shop? It’s fascinating what’s been going on there over the last four or five years. And it varies by country and city, but there’s so much interest in health and wellness, hospitality, living a healthy lifestyle, and the Equinox brand. The brand awareness is very high because a lot of the 30 and 40 year olds in the Middle East have been educated here in the U.S., and they’re educated in a lot of cities where we have big portfolios of clubs. After billionaire real estate developer Stephen Ross, whose company Related is a majority owner of Equinox, held a fundraiser for then-republican candidate Donald The President in August 2019, a lot of customers boycotted Equinox and Soulcycle clubs. Saudi Arabia doesn’t have a great track record when it comes to respecting human rights. Do you worry about the reputational risk to your brand this might have? Fair question. When Stephen did the fundraiser back in summer of 2019, we definitely [were] given a very hard time by our members, our prospective members, what we call our alumni members. It was a time when cancel culture was a very big thing, and we definitely took our hits during that. But what I would also say is that, [it] is because people are so emotionally attached to the Equinox brand. We got a list of all of corporate America that at that time was donating to Donald The President or the Republican Party. It’s a who’s-who of American household names. We don’t donate to any party. We’ve always been, in effect, Switzerland and we believe we’re an inclusive community. I don’t mean that just by race or gender. Everybody can have their political views, everybody can have their religious views. That’s the magic of Equinox, that it’s such a diverse and inclusive community, both from our employee side and from our member side. What struck me was because people love us, they expect more from us. At CVS where you buy toothpaste, nobody cared that CVS was one of the biggest donors to Donald The President at the time. Nobody was canceling them. Stephen Ross, who is obviously a significant investor and a partner, made a personal decision to do something with supporting Donald The President. It was really from a business perspective more than anything, but that was his decision. It was unfortunate that it affected Equinox and SoulCycle at the time. As we move forward, we’re not going to weigh in on politics, we’re not going to weigh on religion, but people are allowed to have their personal points of view. That’s how America was built. It was an unfun time, but we’re always sensitive about who we partner with, big and small. When you talk about the Middle East, everybody is partnering with a lot of these countries, including Saudi Arabia. And Saudi Arabia is transforming and undergoing substantial reform. We’re not alone in deciding that it’s okay to do business there. Equinox is in the middle of transforming its wellness offerings—last year you launched Optimize, a $40,000-a-year health and longevity program that involves lab testing, personal training, and nutrition and sleep coaching. Tell me about your investments in that category. It’s soon going to be a $10 trillion global category. There’s no brand that’s better positioned than Equinox to take advantage of what we refer to as high-performance living. If you listen to the true respected longevity gurus, they align with this philosophy. We talk about it from a science perspective. How do you live a high-performance lifestyle? We talk about movement, which is working out and being active. We talk about nutrition—I prefer the word nourishment because nutrition is medicinal. Nourishment is just eating well and eating in a way that gives you energy and fuel for the body. Then there’s recovery and sleep is at the core of that, but there’s other aspects to recovery at this point. A lot of the biohacking comes into that. Then there is community. Nobody’s written that narrative more so in the community than we have. We introduced Optimize last year through a partnership with Function Health [which does lab testing]. We take biomarkers [from blood tests] and then you are assigned a concierge who quarterbacks your program with a team of specialists, your personal trainer that is referred to as a coach, your nutrition coach, your sleep coach. Then we retest to see how the progress is going. You also have programs to support members using GLP-1s. Has their increasing prevalence changed the business? I don’t think it’s had a dramatic effect on the business, but I definitely think the needs and wants of certain members have changed. So early on when GLP-1s exploded, there was lots of press out there asking, does this mean gyms are dead? But what the world has learned through lots of science and research and the different experts is if you use that as a kickstart, but then compliment it and move towards living a different lifestyle, meaning all the stuff around being active, strength training, eating well…those are the people that are getting the greatest results from GLP-1. We saw it as an opportunity to create a special GLP-1 training program. I think what’s definitely part of the GLP-1 effect is that people realize strength training is more important than ever before. You’ve mentioned Optimize, your GLP-1 program, and Equinox Living. There’s another chain, Life Time, that has similar offerings. How do you view that competition? There’s some similarities in the programming, but the offerings are very different. They are much more of a rural to suburban play, and we’re much more of an urban play. We’re much more luxury, high touch service oriented and more boutique-oriented versus. But there is some overlap programmatically. I think that at the end of the day though, what I would say is if you want the Equinox experience, you’re not going to get it at Life Time. If they want to follow a lead on some aspects, that’s up to them, that’s flattering. I have a lot of respect for what they’ve been able to accomplish, but what we’re doing is very unique and our community loves what we do. So I don’t really view it as competition; I just view it as someone else operating in the category. And I think there’s plenty of room for both of us and others. Why did you ditch Kiehl’s for Grown Alchemist products in your locker rooms? I am going to be too transparent. I’m going to get yelled at by my team afterwards. Kiehl’s was a very successful relationship for a very long time—since 2009. But through all the changes of their leadership, which seemed to be very frequent, the product was, in our mind, a little stale, and they weren’t innovating around it. And there were some things in the product, which in the world of getting clean were not good ingredients, and they were reluctant to change [them]. So we said, this is not the right product for our members. Despite what they’ve said in the market, we decided to end the relationship. Interestingly, I’m going to point out—and this is where I’m really in trouble—is that other brand that you mentioned, that started in Minnesota… they’ve picked up our sloppy seconds [and started offering Kiehl’s in their locker rooms]. Nobody likes sloppy seconds. That’s certainly not us. So we ended the relationship. We decided to go another direction. There’s no doubt that the other direction caused an uproar. Clean is tricky, and Grown Alchemist is clean, but it comes with issues. It doesn’t suds as much. So anyway, to make a long story short in this regard. I would just say stay tuned for more announcements in the not too distant future. Were your customers asking for clean products? There was some of that, but also we were looking to say, what’s the future here versus what’s yesterday? We felt that Kiehl’s was yesterday, and we wanted something more progressive. And so we went in direction. There’s no doubt a lot of our members love the direction we went in. And other members were like—as you saw on Reddit—what are you doing? This is ridiculous. You’re cheapening out. It’s actually more expensive. Just so we’re clear, it was not us cheapening out. [But] we have some things coming in the not too distant future. What’s your own workout routine? I’ve practiced what I preach. I’ve had the same coach for 20 years who’s been amazing. I strength train with him three times a week. Then separately, I love to sprint. I probably sprint more than I should, but I sprint probably four times a week and do cardio like six times a week. I eat really clean although I believe that pizza’s a separate food group because that is my kryptonite, that’s my weakness. I’m a big believer in the sleep side. I do all the biomarker stuff that I mentioned early on to inform this, but I make sure I get my sleep regardless of what’s happening. Which Equinox club do you visit the most? That’s like asking which is your favorite child. I have twins, and I often joke about when I’m with one or the other, I tell them “you’re my favorite.” And then I tell the other one, she’s my favorite. You’re going to be paying a lot of psychiatry bills down the line. Probably, so far it’s worked out okay. But I like so many clubs for different reasons. Because my offices are at Hudson Yards, I use the Equinox at Hudson Yards most frequently. View the full article

Want more housing market stories from Lance Lambert’s ResiClub in your inbox? Subscribe to the ResiClub newsletter. Earlier this month, the National Association of Realtors (NAR) released its annual survey, which found that the median age of first-time U.S. homebuyers in 2025 climbed to 40. That’s up from 38 in 2024—and far above the median age in 1992, when it was 28. At first glance, it appears that deteriorating housing affordability—driven by the Pandemic Housing Boom and the 2022 mortgage-rate shock—has pushed the age of first-time buyers higher. However, when you look across other data sources, including the Federal Reserve Bank of New York and the U.S. Census Bureau, you don’t see the same spike. ResiClub dug deeper into the data to figure out what’s really going on. According to the Federal Reserve Bank of New York, the average first-time homebuyer in 2024 was 36.3 years old—just a little younger than NAR’s estimate of the median first-time homebuyer age of 38 in 2024. Initially, one might suspect the difference simply stems from the fact that the New York Fed reports an “average” while NAR reports a “median.” However, when you peel back the onion, you’ll see there’s a large historical divergence between the two organizations’ figures. That raises the question: How did they each collect their data? The NAR data series is calculated by an annual survey. For this year’s survey, NAR mailed out a 120-question survey to 173,250 recent homebuyers. The recent homebuyers had to have purchased a primary residence home between July 2024 and June 2025. In total, 6,103 responses were received this year. The New York Fed doesn’t collect its data by survey. Instead, it’s looking at credit report data, which it says has “5% of nationally representative individuals since 1999.” Back in August, ResiClub emailed both NAR and the New York Fed to get their thoughts on the first-time homebuyer data divergence. Jessica Lautz, NAR’s deputy chief economist, told ResiClub on August 14: “The Federal Reserve is basing their data on credit data. The Profile of Home Buyers and Sellers [from NAR] is based on a survey of those who purchased a primary residence home in the last year. Thus, the NAR survey includes the 9% of first-time buyers who paid cash for their home and did not finance their purchase. Excluded are first-time buyers who purchased a vacation home or mom-and-pop rental as their first purchase. A trend which has popularized as young adults are unable to achieve homeownership in the expensive areas they may live in. The NAR data collection is mid 2023 to mid 2024 vs. a calendar year. Lastly, NAR uses medians as a measure of central tendency vs. average.” Donghoon Lee, an economic research adviser in microeconomics at the Federal Reserve Bank of New York, told ResiClub on August 13: “We can’t tell you how the NAR annual survey was constructed, but in our previous blog, we wrote about a comparison between our data and NAR source. Here are some of the unsophisticated differences. New York Fed Consumer Credit Panel is a panel of credit report data where we follow 5% of nationally representative individuals since 1999, and is not a survey. We are not subject to any low response rate issue of the respondents. We identify first-time homebuyers when a mortgage account appears for the first time on the individual’s credit reports. If a home purchase was made without a mortgage (such as a cash purchase) then we don’t see them, and not included in calculating the statistics.” My takeaway? I’m going to take this particular first-time homebuyer data—especially the NAR series—with a grain of salt going forward. Instead, I’ll lean more on generational homeownership rates by age. And when you look at those figures, they clearly confirm that younger generations are entering homeownership more slowly than their older peers. ResiClub also messaged Apartment List to get its latest calculation. See below: Apartment List’s analysis shows that with each successive generation, homeownership rates take longer to ramp up. This pattern isn’t unique to Gen Z—baby boomers were slower to reach key homeownership milestones than the Silent Generation, Gen X was slower than the boomers, millennials were slower than Gen X, and Gen Z is slower still. The fact that each generation takes a little longer to enter homeownership—during both periods of “good” and “poor” housing affordability—suggests an underlying secular shift that isn’t just driven by affordability. In my view, that secular shift largely comes down to lifestyle/cultural shifts. With each new generation, Americans are spending more years in school, marrying later, having children later (and having fewer kids), and ultimately buying homes later. I call this phenomenon “lifestyle delays.” Given how homeownership rates are calculated (the number of owner-occupied housing units divided by the total number of occupied housing units), it’s likely that the gradual slowdown in homeownership by generation is actually understating the true drop-off. In plain English, what do I mean? If someone in their twenties or thirties is still living with their parents, they technically aren’t counted as their own household and therefore aren’t included in the denominator. And when you look closely at the generational data (see the Apartment List analysis above), you’ll note that with each generation, Americans are taking longer to move out of their parents’ homes. If you adjust for this, the “real” homeownership rates by generation—something John Burns Research and Consulting has analyzed—you find that the generational homeownership drop-off is indeed larger than the headline data suggests. View the full article