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A recent Harvard Business Review piece echoes the shift we’re sseeing in the SEO industry: at a macro level, LLMs and Google’s AI-powered SERP features, such as AI Overviews, aren’t just creating a zero-click environment, but also changing user journeys and behavior. They’re collapsing what used to be multi-touch customer journeys into a single synthesized answer. For a more visual and emphatic metaphor, the monolith of “Search” is crumbling. When that happens, brands lose many of the touchpoints they once owned, and your marketing strategy must change accordingly. HBR captures this moment well, arguing that marketing now has a new audience and that algorithms increasingly shape first impressions. That said, while the article points in the right direction on the broader trend, its tactical advice is generic and falls back on shallow tactics. Much of the guidance returns to familiar marketing playbook ideas that sound strategic and innovative but lack real operational depth. That gap matters for the longevity and sustainability of visibility. The narrative may be easy for you to understand and repeat at the executive level, but it glosses over the deeper structural changes you must actually make to adapt to the new search ecosystem. The problem with flock tactics The HBR article centers on schema, authorship signals, and branded concepts. These recommendations risk becoming what I call “flock tactics.” These ideas spread quickly because they’re easy to explain, but they offer little lasting competitive advantage once everyone adopts them. Schema Schema has been one of the most debated topics in LLM and AI optimization. Microsoft Bing confirmed it uses schema for its LLMs, but the relationship between Google’s models and third-party LLMs isn’t as straightforward. While it isn’t necessarily wrong to recommend schema as part of your overall search optimization activities (SEO and AI), positioning it as a table-stakes tactic ignores diminishing returns once competitors implement similar markup and it becomes standard. Another gap is the role of external knowledge systems, such as Wikidata or authoritative publishers. Much of the information LLMs rely on comes from those sources rather than a single company’s website. This is less linear to understand, explain, and demonstrate as a single line item on an activity tracker, but these are nuances you now have to deal with, whether you like it or not. What’s also missing is any exploration — or even a nod — to how models ingest and prioritize structured data compared with the many unstructured signals they rely on. Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with E-E-A-T — shallow authorship signals Attaching the names, credentials, and biographies of real experts follows familiar E-E-A-T logic and represents reasonable hygiene. The problem is that the treatment remains superficial. It risks pushing you to focus on cosmetic signals such as bios, headshots, and credential lists without strengthening the underlying expertise pipeline. There is a meaningful difference between placing an author bio on a page and cultivating a genuine expert entity whose work appears in conferences, third-party publications, standards committees, or academic collaborations. Only the latter produces signals that models are more likely to recognize and trust. Vanity concepts The article also suggests creating branded frameworks or concepts — for example, something like “The Acme Index” — to help models associate ideas with your company. In theory this sounds appealing, but in practice it’s extremely difficult to execute. Unless those ideas spread into the trusted datasets LLMs tend to prioritize, they rarely gain traction. You need those concepts and frameworks adopted and discussed by entities other than yourself, including academic journals, technical standards, widely used software ecosystems, and other prominent entities in your category. What often results instead is a proliferation of branded labels that remain largely invisible to the models they were meant to influence. The structural blind spots Beyond these tactical issues, the analysis overlooks deeper structural challenges. It treats AI primarily as an external platform shift. The implication is that you must simply adapt to it rather than actively shaping your own environment. Internalizing AI infrastructure HBR never seriously considers the possibility of building AI into your own infrastructure. You can deploy assistants, RAG systems, and domain-specific agents within your own products and customer experiences. These systems operate in logged-in, transactional contexts where first-party data and controlled interfaces still matter enormously. In those environments, traditional concerns such as site architecture, structured data, and product design remain deeply relevant, though they operate differently from public search optimization. It’s not just SEO The discussion also frames SEO primarily as a page-ranking problem tied to discovery. That perspective misses the broader shift toward entity-level knowledge management (things, not strings). Visibility within LLMs increasingly depends on how well you structure entities, taxonomies, and knowledge graphs, and on how those systems connect with external data sources. Most LLMs don’t process data at the petabyte scale Google uses to understand entity relationships. There is a strong correlation that when something ranks well on Google, third-party LLMs often correlate and “trust” Google’s guidance on which brands to show, for what, and when. HBR’s phrase “engineering recall” points directly to this deeper data engineering work, yet the implications aren’t expanded. LLM model heterogeneity Another major omission is the diversity of AI systems themselves. Different AI assistants and models rely on different training datasets, refresh cycles, retrieval mechanisms, and safety layers. That heterogeneity means you can’t assume a single optimization strategy will work across all AI surfaces. It also doesn’t explore the risk of broad-stroke approaches. If you try to increase visibility within AI models without accounting for safety filters, attribution errors, or hallucinations, you may gain visibility in ways that are inaccurate or reputationally damaging. See the complete picture of your search visibility. Track, optimize, and win in Google and AI search from one platform. Start Free Trial Get started with Surface-level tactics won’t build AI visibility HBR’s article works well as a high-level explanation of how AI is changing marketing. It helps you understand that traditional SEO alone is no longer enough and that you must consider how AI systems see and describe your brand. As a practical guide, however, the advice is thin. Most recommendations focus on surface-level tactics that many companies will quickly copy, reinforcing the echo chamber of flock tactics that are easy to sell and quantify, but risk narrowing your focus to short-term wins at the expense of longer-term strategy. The real challenge is deeper. You need clear entity definitions, structured knowledge systems, reliable data in trusted sources AI models use, testing across how different models represent you, and AI-powered experiences within your own products. “Winning” in the AI era will depend less on cosmetic SEO improvements and more on the harder structural work behind the scenes. 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ChatGPT retrieves far more webpages than it cites. A new AirOps analysis found that 85% of discovered sources never appear in the final answer. Why we care. If you want your content cited in AI-generated answers, discovery isn’t enough. Most retrieved pages never become visible to users. Key finding. In AI answers, retrieval doesn’t equal citation. Your page can rank and be retrieved yet still lose the citation to a source that better matches the prompt or supporting context. This shifts optimization toward earning selection inside the AI synthesis process—not just appearing in search results, per the report. By the numbers: 82,108 citations appeared in final responses. Only 15% of retrieved pages were cited. 85% of pages surfaced during research never appeared in answers. Citation rates also varied by query type: 18.3% for product discovery queries 16.9% for how-to queries 11.3% for validation searches Fan-out queries. ChatGPT often expands prompts with additional internal searches while generating an answer, creating what the report calls a “second citation surface.” Across the dataset: 89.6% of prompts triggered two or more follow-up searches. Fan-out searches expanded 15,000 prompts into 43,233 queries. 32.9% of cited pages appeared only in fan-out results—not the original prompt. 95% of fan-out queries had zero traditional search volume. Google ranking correlation. High Google rankings strongly correlated with citations: 55.8% of cited pages ranked in Google’s top 20. Pages ranking in Position 1 were cited 3.5 times more often than pages outside the top 20. About the data. AirOps analyzed 548,534 pages retrieved across 15,000 prompts to examine how ChatGPT expands queries and selects citations. The study. The Influence of Retrieval, Fan-out, and Google SERPs on ChatGPT Citations View the full article

New third-party data shows local publishers lost national reach after Google's Discover core update. The post Google Discover Core Update Data: Local Publishers Lost Reach appeared first on Search Engine Journal. View the full article

But there’s a practical distinction worth drawing, and it changes how you apply the idea. Search intent is about optimizing content to match what the search results reward. Keyword intent is the same concept applied one step earlier. Think of…Read more ›View the full article

Nearly every part of the United States is getting walloped by wild weather or just about to be. Days of downpours have begun in Hawaii. The Southwest will soon bake with day after day of record 100-degree-plus (38 Celsius-plus) heat. Two storms will dump snow by the foot over northern Great Lakes states. And the dreaded polar vortex will again invade the Midwest and East with soul-crushing Arctic chill. This forecast of extremes comes as weather whiplash already hit much of the East. On Wednesday, Washington, D.C. residents walked around in shorts in record-breaking 86 degrees Fahrenheit (about 30 Celsius). On Thursday, it snowed. “All of the country, even if you’re not necessarily seeing extremes, are going to see generally changing from cold to warm, or warm to cold to warm,” said meteorologist Marc Chenard of the weather service’s Weather Prediction Center in Maryland. Former National Oceanic and Atmospheric Administration chief scientist Ryan Maue said he expects extreme weather in all 50 states. Triple-digit heat persists in Southwest A heat dome will form early next week and park over the Southwest, baking temperatures to triple digits that haven’t been seen this early in the year, Maue and Chenard said. Some forecasts see 98 (almost 37 Celsius) in Phoenix on Tuesday, followed by 103, 105 and two days of 107 (almost 42 C). In 137 years of record-keeping, Phoenix never hit 100 before March 26 and usually hit its first 100-degree day in early May, according to the weather service, which warned people: “Since we are not acclimated to this level of heat this early in the year, it will be more impactful than usual.” It has already started in Los Angeles with unusual 90-degree March weather that had people in shorts and tank tops seeking shade anywhere they could get it, even if it was as slender as a light post. Shane Dixon, 40, usually runs about 5 miles near his home in Culver City without much effort, he said, his face glistening with sweat and his T-shirt tucked into his shorts. But Thursday was hard because of the heat, and he had to cut it short. “The back of my neck was melting,” he said. But he preferred it to the cold and snow that will hit elsewhere. “I could go literally soak myself and walk out in the sun and I’ll make it home fine. If it was freezing cold I could not do this,” he said. Single-digit cold invades North Around the same time as the heat starts blasting Phoenix, the polar vortex — a system that usually keeps frigid air penned up near the North Pole — is forecast to send its chill deep into the Midwest and East, even bordering some of the Southeast, Maue said Minneapolis will hover around zero for a low, and Chicago will be in the single digits Tuesday. The next day “temperatures in the teens and 20s in the northeast and 20s in the Mid-Atlantic,” Maue said. Even Atlanta could drop to the 20s. One-two snowstorm punch Two storm systems in a row — one Friday, then another Sunday into Monday — will chug along the country’s northern tier and Great Lakes and between them could dump 3 to 4 feet of snow in places, Maue said. That bigger second storm system will see its barometric pressure drop so quickly and sharply — meaning it is intensifying and winds are strengthening — that it will qualify as a bomb cyclone, which is quite unusual to develop over land. Normally bomb cyclones get their energy from warm ocean waters, but this one will draw power from the polar vortex. Even Alaska and Hawaii aren’t quite right Maue said Hawaii is getting an atmospheric river that will have such persistent heavy rain that flooding will be a major issue. Oahu is under a flash flood warning. And Alaska is normally frigid now, but it will be about 30 degrees colder than usual, he said. It is “the time of year where we can see stuff like this,” Chenard said. “But this does seem even anomalous from what you would typically see. I mean, some of these areas will be setting records. Record-high temperatures for March and maybe multiple times.” In the past week or so, tornadoes have killed at least eight people in Oklahoma, Michiganand Indiana. The forecast for severe storms doesn’t look as big or widespread for the next week, but dangerous thunderstorms could pop up “anywhere from the Mississippi Valley toward the East Coast” on Sunday or Monday, Chenard said. The jet stream goes nuts Underlying this is a jet stream gone wild, Maue and Chenard said. The jet stream is the river of air that moves weather from west to east on a roller-coaster-like path. Usually the plunges are as mild as a kiddie roller coaster. But now that jet stream is going on near-vertical, scream-inducing drops following by straight-up ascents. “Which means you get a lot of extremes next to each other,” Maue said. Storm fronts coming from the Pacific hit that high pressure heat dome in the Southwest and are pushed north to climb that mountainous jet stream peak, “grab access to that cold air reservoir up there” and bring it back down south down the other side of the hill, he said. Numerous studies have connected unusual jet stream and polar vortex activity to shrinking Arctic sea ice and human-caused climate change. But there is hope. “The first day of spring is 20th (of March), and then after that we get recovery,” Maue said. Associated Press writer Dorany Pineda contributed. The Associated Press’ climate and environmental coverage receives financial support from multiple private foundations. AP is solely responsible for all content. Find AP’s standards for working with philanthropies, a list of supporters and funded coverage areas at AP.org. —Seth Borenstein, AP Science Writer View the full article

Why traditional “utility SEO” content is losing value, and how marketers can create demand instead of chasing existing searches. The post Starting Or Steering The Wave appeared first on Search Engine Journal. View the full article

Gone are the days when marketers can think in five- or 10-year plans. These days, it’s about tomorrow, not the next 16 months, because culture and what captures consumers’ attention is changing faster than ever. Today, it’s Love Island and Traitors reality TV star Rob Rausch posing shirtless on a giant billboard in Times Square for MAC Cosmetics. And tomorrow, it’s Punch the Monkey holding on to his plush doll. (And if you know what we’re talking about, congrats, you are chronically online and in tune with the culture. If you don’t, you’ve got some work to do, but that’s why we’re here.) The state of brand building in 2026 looks vastly different than what any veteran—or new—marketer remembers from even two years ago. Consumers have pulled back on purchases, with retail sales falling 0.2% in January, according to Commerce Department statistics. More consumers have mixed feelings about the economy than overall negativity, says global management consulting firm McKinsey & Co. in its February research report. But consumers are still buying, whether it’s “little treat culture” or bigger luxury products at both retail shops and the grocery store. It’s how we convince them as brands to keep buying with us that’s changing. And thus, the state of brand marketing in 2026 is born—it’s fast, it’s weird, and honestly, at times, it makes no sense. But for those of you in the room making decisions on how to engage consumers, it could be the time of your life, as long as you keep your finger on the pulse and move quickly and intently with these principles in mind. KPIs are cringe: Instead, understand the data, but don’t rely on it To be a responsible marketer, you need to understand any data a campaign or activation provides. But besides that, execute without key performance indicators, or KPIs, in mind. (To us, this term is cringe in 2026.) It’s about gut calls, vibes, and how anything is going to make someone feel in order for them to buy with their heart, not their heads. Vibe marketing is resonating with consumers—we know, because some of us started that trend. At the organic infant formula company Bobbie, we led the first breastfeeding billboard in Times Square with cookbook author Molly Baz; we also empowered mothers to parent with confidence by naming artist Cardi B chief confidence officer. At Poppi, our Super Bowl campaign with Charli XCX and Rachel Sennott was all vibes—it did not take itself too seriously, which is exactly how the company operates—leaning into top-of-funnel marketing moments for our highly captive audience of women and Gen Zers. All of this changes depending on your marketing budgets, of course. But reaching people doesn’t always take a multimillion-dollar campaign. It’s surprising and delighting your community with moments that were once exclusive to media and influencers; it’s engaging with your comments sections and turning those into campaign moments, or simply a touchpoint to send someone merch “just because.” Leaning into your community and who your consumers already are will help you develop the best messaging for your brand: What’s the story you want people to tell your brand when they’re talking to their friends, family, and neighbors? Say something, do something Culture isn’t the only thing that’s rapidly evolving. With escalating geopolitical and domestic issues, consumers are looking for their favorite brands to weigh in and stand by their values. It’s important to stress that not every brand has to take a stance if it’s not in its DNA, and that’s okay. However, many companies have always been purpose-driven. But it’s no longer enough to have a random web page with a vague statement. Consumers want to see companies put their money where their mouth is by donating or partaking in some sort of advocacy work. It doesn’t always mean launching a new product or campaign with the hopes that someone purchases your product. At Bobbie, we just released our Paint the Hill Green docuseries, which shows our efforts to bring the Black Maternal Health Momnibus Act back to Congress. Our work—along with countless others—has resulted in the bill being reintroduced to Congress under this administration for the first time. We didn’t just sign a petition or pledge to do something. We put in the time and work and brought our community along with us. For SolComms, our communications agency has advised countless brands on when they should enter a political conversation. We assess the risk and a brand’s right to win within a certain issue, and then we execute. For example, with August, the sustainable period care company, we helped them work to fight the tampon tax by refunding customers who’ve paid a sales tax on menstrual products. And for Blueland, the sustainable cleaning product brand, we assisted in introducing a bill in the New York City Council to ban the distribution and sale of plastic detergent pods and sheets in NYC. Both efforts were actionable and on-brand, and resonated strongly with their respective target audiences. Stay true to your customers Whether it’s social media, email, or even direct mail, consumers are being sold to at every single possible moment. And they’re over it. They’ll let a brand know if they don’t believe in their product and post on social media to tell people—where it can quickly take off and turn into a nightmare that no one saw coming. Instead of working on crisis communications, brands should stay true to who they are and what their products are about. Continue to make sure your products have the best quality. If you’re marketing to a certain generation, stay the course, and they’ll most likely stay with you. Drunk Elephant has become another example of this in practice. The company enjoyed an uptick in sales and awareness from Gen Alpha tweens who would stock up on the brand’s $79 serums and $66 moisturizers. The pivot to relying on this generation meant leaving behind older consumers. Tweens are fickle consumers, however, as they’re quick to chase whatever the latest trend might be. And soon Drunk Elephant was not at the top of their list. The company’s sales dropped 65% year over year in the first quarter of 2025. In January, Drunk Elephant announced a new brand direction along with a “Please Enjoy Responsibly” campaign. At Poppi, we thought we had to gain more audience, so we signed a bunch of creators and influencers, and expanded our reach into sports because we wanted to reach more men. We didn’t see any positive results from these initiatives, so we pivoted and found that talking to our female customers is how we’d get to men. It’s easy to get obsessed with other audiences and not your core audiences, in order to chase the shiny new generation. But the smarter strategy is to go deeper into your core audience. It’s easier than ever to get distracted by the hundreds of signals we think we should be following—whether it’s AI, community building, LinkedIn posts, flashy out-of-home advertisements, activations at every single major music festival, and the list goes on and on. But the brands that are capturing a consumer’s attention—and dollars—are the ones thinking about them, and only them, and what they want. Those are the brands receiving $2 billion exits, major retail exposure, and organic love from consumers; those are the companies we’ll still be writing about 20 years from now, and that will eventually become the rare, coveted 100-year-legacy brand. 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My new favorite creator on TikTok is Apple. Yes, that Apple. On March 4, Apple launched its newest product, the head-turningly affordable $599 MacBook Neo. That same day, the company also deleted all of the content that once populated its TikTok page and started over. Its new videos—on view there are now 15—run the gamut from a clip inspired by Steve Jobs’s original introduction of the 1984 Macintosh to a cutesy animation of the Mac finder icon giggling and blushing. The videos have consistently debuted in batches of three, each corresponding to one of the brand colors associated with the Neo. This TikTok refresh is a clear play to cater to the audience that Apple knows is most interested in the Neo: Gen Z. The new laptop model, powered by the same architecture inside your iPhone, is targeting a younger user base with its unprecedentedly low price point and aesthetic color options, which tap into Gen Z’s long-demonstrated obsession with retro-tech. So far, the new TikTok strategy seems to be working. Based on a Wayback Machine capture from February 28, Apple was sitting at 7 million followers and 21.9 million likes before the change; figures that have now jumped to 7.8 million and 31.6 million, respectively. Apple also recently debuted a secondary Instagram account called @helloapple, which will be dedicated to news, product marketing, and customer stories. This account has a decidedly more corporate feel than the brand’s TikTok, but demonstrates the company’s broader desire to expand its presence on socials. Apple’s new TikTok page works because it takes an amalgamation of trending aesthetics and blends them with Apple’s high design point of view, turning every silly video into a loopable work of art. Why Apple’s new TikTok is genius Plenty of brands have experimented with how to best capture Gen Z on TikTok, and Apple’s team has evidently taken notes out of multiple playbooks. The company is experimenting with everything from brain rot content to y2k nostalgia, ASMR, goofy branded songs, and creepy edits. Ordinarily, such a wide range of aesthetics might make a brand seem cringeworthy and pandering. For Apple, though, the meticulous creative execution of the launch ties everything together. Take, for example, one 14-second clip of a woman opening and swatching a pink blush, referencing the “Blush”-hued Neo. The concept is simple, but every detail of the video has been optimized to tap into Gen Z’s love for y2k aesthetics—from the model’s striped top and the pink shag rug to the custom blush container, featuring Apple’s logo, that appears to be an allusion to the colorful plastic shell of the ‘90s iMac G3 computer. This mash-up of nostalgiacore with a direct reference to a recognizable Apple product of the era makes the video feel authentic, not forced. The post’s engagement reflects that: as of this writing, it’s notched more than 64 million views and nearly 35,000 comments, most of which are begging for Apple to bring back some of its beloved colorful hardware. In a similar vein, other clips cleverly pair Apple’s signature sonic design with eye-catching visuals, like a 3-second video of the sun rising to the Mac startup chime, or a juicy mash-up of citrus fruits choreographed to an edit of various notification sounds. The account is also testing some videos that brush into brain-rot territory, a social trend we’ve described as a form of digital marketing that “embraces head-turning, often nonsensical choices, like fried visuals, abrasive design, and unsettling storylines.” These include clips like a slightly unnerving compilation of people with their hands dyed blue (presumably as a reference to the “Indigo” Neo), a custom brand song dedicated to Apple’s fingerprint recognition software, and a silly clip of a lemon facetiming a lime (mimicking the colors of the Neo’s default background screen). While other brands like Duolingo, Nutter Butter, and Brita have taken similar brain-rot strategies to the extreme on their accounts, Apple’s twist on brain-rot demonstrates that it understands what makes this content resonate—a combination of irreverence and unexpectedness—yet also knows to keep its approach restrained and aesthetically pleasing, giving it a distinctly Apple feel. It’s Steve Jobs-meets-brain-rot, in the best way possible. View the full article

I was walking down the street with my partner in London’s Camden neighborhood on Wednesday night when we saw an ad that said, “This app was designed to keep you hooked.” A finger could be seen tapping Instagram’s app icon above a claim reading, “45% of teens say they spend too much time on social media.” In theory, this was all straightforward messaging, but the ad’s final note in the corner threw us: “From Meta,” logo and all. We turned to each other in confusion, trying to make sense of it. The ad looked so professionally designed that we wondered, could Meta Platforms, a company that has repeatedly denied responsibility for its users’ mental health, be advertising it? No. In short, Instagram and Facebook’s parent company has done nothing of the sort. Instead, the ad is from Just Treatment, a U.K.-based health justice group started in 2017. The organization’s latest campaign is Mad Youth Organise, a push to improve accessible, quality mental health care for young people. The “ad” we saw was one of eight that activists have plastered guerrilla-style across London, Just Treatment told Fast Company. A similar design to the one we saw features a photo of Meta CEO Mark Zuckerberg smiling. “If you feel worse, it’s working,” it says. Other ads are plastered with statements such as “Our anxiety is exploited by Meta” and “We’re more lonely with Meta.” Each includes a statistic to back up these claims. The campaign launched Wednesday and included a group of young people blocking Meta’s London office with another ad that bluntly stated: “The youth mental health crisis, sponsored by Meta.” The individuals involved in the protest believe social media has “pushed them into mental health crisis,” according to Mad Youth Organise. Young activists who’ve lived with adverse mental health have run and designed the entire campaign, Just Treatment says. Alongside Meta, Mad Youth Organise has also targeted TikTok. One sign reads, “Eating disorders start on TikTok,” while another says, “Misery starts on TikTok.” Both also cite a statistic claiming 46% of teens feel social media makes them have a worse body image. Fast Company has reached out to Meta and TikTok for comment. We will update this post if we hear back. What does the Mad Youth Organise campaign want? Mad Youth Organise is pushing for a “Big Tech Tax,” a 4% tax on tech companies earning over £500 million ($663 million) globally. The money raised would be put toward funding youth mental health services. It’s also insisting that Big Tech’s social media monopoly be severed, among other demands. How bad is social media for young people? It’s no secret that social media has been shown to cause adverse effects. A high-profile social media trial in the U.S. held closing arguments on Thursday: TikTok, Meta, YouTube, and Snap have been accused of knowingly designing products that are both addictive and harmful to young people’s mental health. These social media companies have all taken the same approach to these accusations: Deny. Deny. Deny. TikTok and Snap previously settled with the plaintiff, identified only by her initials KGM. She claims that early social media use made her addicted to technology and exacerbated her depression and suicidal thoughts. However, this is the first of a consolidated group of cases for over 1,600 plaintiffs, including families and school districts. Research has consistently found evidence of social media’s harm to young people’s mental health. A 2025 survey from Pew Research found that 48% of U.S. teens aged 13 to 17 believe social media sites have a mostly negative effect on their age group. This figure is a significant jump from the 32% who felt the same in a 2022 survey. Participants also listed social media as the most negative influence on teen mental health (22%), higher than bullying (17%), pressure and expectations (16%) and school (5%). Young Minds, a U.K.-based charity for young people’s mental health, reports that 34% of young people feel trapped on social media sites. Meanwhile, 22% report receiving distressing content on social media at least weekly. View the full article

Revised figures show GDP rose at a 0.7% rate in fourth quarter, down from earlier reading of 1.4%View the full article

Towers in Dubai International Financial Centre suffer damage but most drones and missiles are interceptedView the full article

Tehran has done ‘more with less’ as it hit major targets around the Gulf, but its firing has begun to waneView the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. The Samsung Galaxy Tab S10 FE+ (128GB) is currently $499.99 (down from $649.99) on Amazon, and price trackers confirm this is the lowest price it has ever reached. According to PCMag’s “excellent” review, the Tab S10 FE+ works well as a general-purpose tablet for both entertainment and productivity, making it one of the best tablets you can buy in 2026. Samsung Galaxy Tab S10 FE+ 13.1” 128GB WiFi Android Tablet $499.99 at Amazon $649.99 Save $150.00 Get Deal Get Deal $499.99 at Amazon $649.99 Save $150.00 Samsung gives the tablet an IP68 rating for dust and water resistance, something you still don’t see on every tablet. It runs Android 15 with Samsung’s One UI interface and comes with the S Pen stylus included, which is useful if you like taking handwritten notes, marking up documents, or sketching. Storage caps at 128GB, but there’s a microSD slot that supports cards up to 2TB, so you can expand it later if your tablet ends up holding a lot of downloads, files, or videos. Its 13.1-inch display has a resolution of 2,880 by 1,800 pixels and supports refresh rates up to 90Hz, so scrolling through apps, reading, and watching videos all look smooth and sharp. The tablet itself stays fairly slim for its size at 0.24 inches thick and weighs about 1.46 pounds. It feels balanced whether you hold it in portrait for reading or landscape for movies. Inside, the tablet runs on Samsung’s Exynos 1580 processor with 8GB of RAM, which keeps everyday tasks running smoothly. Apps open quickly, and Samsung’s software helps you use the large screen more effectively. Tools like the Edge Panel and multi-window mode make it easy to keep two or three apps open at once, while Samsung’s DeX mode can turn the tablet into a more desktop-like workspace if you connect a keyboard or external display. The battery reportedly lasts around eight hours, which is enough for a day of streaming, browsing, or light work. The tablet’s speakers sound loud and clear with Dolby Atmos support, and the cameras—a 13MP rear and 12MP front—are decent for video calls or quick photos. The main omission compared with Samsung’s flagship tablets is Galaxy AI, though you still get tools like Circle to Search, Object Eraser, and Best Face for basic editing and everyday convenience. Our Best Editor-Vetted Tech Deals Right Now Apple AirPods 4 Active Noise Cancelling Wireless Earbuds — $119.99 (List Price $179.00) Samsung Galaxy S26 512GB + $100 Amazon Gift Card (Black) — $1,099.99 (List Price $1,099.99) Google Pixel 10a 128GB 6.3" Unlocked Smartphone + $100 Gift Card — $599.00 (List Price $599.00) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $299.00 (List Price $349.00) Apple Watch Series 11 (GPS, 42mm, S/M Black Sport Band) — $299.00 (List Price $399.00) Amazon Fire TV Soundbar — $99.99 (List Price $119.99) Deals are selected by our commerce team View the full article

The standard agency reporting call is broken. Budgets are under extreme scrutiny, yet you still invest in vendors that celebrate arbitrary traffic gains while your sales pipeline stays flat. Optimizing for raw traffic volume is a legacy mindset that hides real commercial performance. The new mandate is to build an acquisition engine that influences buyers and protects your profit and loss (P&L) long before the transaction. To survive as a marketing leader today, you must ruthlessly challenge your internal teams and external agencies. Stop accepting reports on operational output and demand hard financial accountability: pipeline contribution, customer lifetime value (LTV) to customer acquisition cost (CAC) ratios, and reduced paid media dependency. The new path to purchase: Why traffic is bleeding your budget Chasing top-of-funnel informational traffic is a trap. If the users clicking your links aren’t actively buying, you’re paying for vanity metrics, not business outcomes. This happens because many buyers now use large language models (LLMs) to conduct deep research before they reach a search engine’s transactional layer. If you aren’t the cited authority during that AI-driven research phase, you’re invisible by the time buyers finalize their purchase decisions. The 7.48% reality: The power of the educated buyer The contrast in traffic quality is staggering when you look at the data. Across our enterprise client base, traditional organic search converts at 2.75%, while AI search converts at 7.48%. LLMs function as the ultimate trust proxy for today’s consumers. When tools like Gemini, ChatGPT, or Perplexity synthesize dozens of reviews, whitepapers, and Reddit threads to recommend your enterprise software, users trust the LLM’s consensus more than a branded blog post. AI engines arm consumers with comprehensive data, comparisons, and consensus. By the time a user clicks your AI citation, they’ve already made their decision based on your authority and are prepared to transact. Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with From found to cited: Architecting the default recommendation Want to capture this 7.48% conversion rate? Your entire approach to digital asset creation must evolve. The strategy no longer centers on ranking among a list of links, but on being cited as the definitive option. To win the AI consensus, you must translate your marketing strategy into structured capital management. The old way: Publishing a 2,000-word blog post on top supply chain trends that generates 5,000 monthly visitors who bounce after reading and add zero value to your pipeline. The new way: Build a generative engine optimization (GEO) hub—a dedicated supply chain cost calculator page with proprietary data tables, expert author schema tagging your lead engineers, and strict answer-first formatting. LLMs require consensus and verifiable facts to generate confident answers. By structuring your digital assets with proprietary data and verifiable entities, you become the default recommendation. This approach may yield only 500 highly qualified visitors, but it gives LLMs what they need to cite you in vendor comparison prompts and captures buyers at the exact moment of commercial evaluation. Strategic ROI: Using citation authority to reduce ad spend It’s time to stop viewing SEO as a siloed traffic generator. You must treat organic citation authority as a strategic financial lever to reduce overall CAC. Align your organic assets with your highest-CAC paid campaigns. When organic search owns the AI Overview, your paid team can confidently pull back defensive ad spend. Here’s how to leverage paid and AI search: IF your brand becomes the default AI recommendation for a high-cost commercial category, THEN your paid team must aggressively reduce defensive brand bidding to slash overall cost per acquisition (CPA). IF paid search identifies a highly profitable long-tail query, THEN SEO must prioritize building a structured asset to organically capture that exact demand in the future. IF an LLM cites your competitor as the superior enterprise solution, THEN your paid team must immediately deploy targeted, bottom-of-funnel conquesting ads to intercept that user before the transaction, while the organic team rapidly engineers a proprietary data asset to win back the consensus. The monthly cannibalization review: Your immediate action item If your Head of Search and Head of Paid Media aren’t in the same room once a month mapping organic citations against paid brand bidding, you’re burning capital. Align your teams and channels. Routinely audit where you’re paying for clicks on terms where you already own the AI citation and the top organic spot. Treat this cannibalization review as a strict financial audit. Identify wasted defensive ad spend and immediately reallocate those dollars toward net-new market expansion. The enterprise scorecard: 3 questions to ask your agency tomorrow To regain control of your P&L, you must challenge your vendors to step up. Ask your agency these three questions tomorrow morning to see if they’re true business partners or order-takers. 1. What’s our citation share of voice for our highest-margin categories? Challenge your team to map their organic efforts directly to the AI research phase of your most profitable products. The answer you should hear: “We’ve mapped your 50 highest-margin queries. By securing the primary AI citation for these, we’ve generated $1.2 million in pipeline this quarter at a 3:1 LTV:CAC ratio.” 2. How is our citation strategy directly reducing our paid media CAC? Require teams to prove how their organic authority captures demand that would otherwise require paid ad spend. The answer you should hear: “By capturing the definitive AI citation for [category], we paused paid bidding on those terms. This reduced our blended CAC by 18% and saved $45,000 in defensive ad spend — which we’ve immediately reallocated to net-new market expansion.” 3. Are our digital assets structured for LLM extraction? Push your teams to explain their strategy for AI-driven search models. It’s no longer enough to publish standard web pages. The answer you should hear: “We’ve restructured your core commercial pages away from standard marketing copy, deploying answer-first’ frameworks, proprietary data tables, and expert author entities to ensure LLMs confidently extract and recommend your brand. This structural shift has increased our inclusion in commercial AI Overviews by 40% this quarter, directly feeding our bottom-of-funnel pipeline.” See the complete picture of your search visibility. Track, optimize, and win in Google and AI search from one platform. Start Free Trial Get started with Demand commercial outcomes, not operational output In a tough economy, SEO is a measurable business unit that must defend its budget with revenue data. Don’t accept operational output as proof of commercial success. Audit your reporting frameworks immediately. Stop accepting vanity metrics as evidence of success. Demand pipeline impact, LTV:CAC ratios, and a resilient acquisition engine. Any agency or internal team unwilling to tie its work directly to your P&L will become obsolete. Your job as an enterprise leader is to ensure your brand is cited as the authority long before the transaction begins. View the full article

In SEO Pulse: AI Mode keeps more links inside Google, Maps adds conversational discovery, and Search Console rolls out automated brand segmentation. The post AI Mode Data, Ask Maps & Branded Queries Go Live – SEO Pulse appeared first on Search Engine Journal. View the full article

Europeans look for ways to restart energy shipments as Iran’s new supreme leader vows to keep strait shutView the full article

Carmaker’s technology means EVs can be ready almost as quickly as filling a fuel tank View the full article

For years, SEO followed a fairly predictable playbook: create valuable content, optimize it for search engines, and compete for rankings on Google. But the way people discover information online is changing quickly. Tools like ChatGPT, Perplexity, and Gemini are introducing a new layer between users and search engines, where answers are generated and synthesized rather than simply retrieved. In a recent episode of the Get Discovered podcast, Joe Walsh, CEO of Prerender.io, sat down with Yoast’s Principal Architect Alain Schlesser to discuss what this shift means for SEO and online discoverability. Their conversation explores how AI answer engines are reshaping the search landscape and why many traditional SEO assumptions no longer fully apply. Alain shares insights on: How AI systems retrieve and surface information Why brands must rethink their online positioning, and What businesses should start preparing for as AI-driven discovery evolves over the next 12–18 months? Watch the full conversation between Joe Walsh and Yoast’s Principal Architect, Alain Schlesser, in the Get Discovered podcast below. Table of contents The new discovery layer: AI is becoming the gatekeeper Search is fragmenting beyond Google The “top results or nothing” reality Why Yoast launched AI visibility tracking The next evolution: AI agents making decisions SEO matters more than ever The new discovery layer: AI is becoming the gatekeeper “There’s now a layer in front of search that acts as a gatekeeper before you even hit those search engines.” That’s how Alain describes one of the biggest structural shifts happening in online discovery today. For years, the flow of search was straightforward: a user typed a search term into a search engine, the engine returned a list of results, and the user decided which link to click. But AI-powered systems have added a new layer to that process. From search queries to conversational discovery Today, many users begin their search journey by asking questions in tools like ChatGPT, Perplexity, or Gemini instead of typing traditional keyword queries. The AI system then determines whether it needs external information and may generate multiple search queries behind the scenes to retrieve relevant sources. The discovery flow now looks something like this: Previously: User → Search engine → Website Now: User → AI model → Search engine → Website → AI synthesis → User Instead of presenting a list of links, the AI model interprets and combines information before generating an answer. Alain explains this process in more detail in the podcast, highlighting how AI systems now act as a filtering layer between users and the web. Search is fragmenting beyond Google “We were in a rather comfortable position where we were only dealing with a monopoly search.” For much of the past two decades, SEO largely meant optimizing for one ecosystem: Google. Even though other search engines existed, Google dominated how people discovered information online. But that environment is changing. As Alain explains, AI systems are introducing a new layer of fragmentation in discovery. Different AI platforms rely on different combinations of search engines, indexes, and training data, which means results can vary widely between them. In practice, that means a brand might appear prominently in one AI system while barely showing up in another. For SEO teams, this marks a shift toward thinking about visibility across multiple AI-driven environments rather than just one search engine. Do checkout: Why does having insights across multiple LLMs matter for brand visibility? What hasn’t changed: The fundamentals of SEO Despite technological changes, Alain emphasizes that the core principles of good SEO remain intact. “You shouldn’t try to game the search engine. You need to create valuable content that humans actually want to read, and structure it so search engines can understand it.” At its core, search still aims to deliver the best possible answers to users. Whether the request comes from a person typing a query or an AI model generating one behind the scenes, the goal remains the same: surface useful, reliable information. That means SEO teams should continue focusing on fundamentals such as: high-quality content clear structure indexable and accessible pages content that satisfies the user’s search intent AI systems may change how information is surfaced, but they still rely on the same underlying signals of quality and relevance. The “top results or nothing” reality As the discovery landscape evolves, another important shift emerges in how AI systems interact with search results. “They don’t see the full search result page. What the LLM typically sees is just the five topmost elements per search query.” Unlike human users, AI systems typically work with a very small set of retrieved sources before generating an answer. That means if your content doesn’t appear among those top results, it may never reach the AI system at all. In a world where AI answers rely on the summarization of modern content, only the sources that make it into that small retrieval window influence the final response. This makes strong search visibility more important than ever. Ranking well isn’t just about earning clicks anymore. It determines whether your content is even considered when AI systems construct an answer. Why “safe” content strategies are no longer enough Even if your content reaches those top results, there’s another layer of filtering happening inside the AI model itself. Large language models compress enormous amounts of information during training. As Alain explains: What the model keeps are the dominant signal and the outliers. Everything in between is often compressed away as statistical noise. In the podcast, Alain uses this idea to explain why brands that try to be broadly acceptable or “safe” may struggle to stand out in AI-driven discovery. The takeaway is clear: in a world where AI systems summarize and compress information, having a clear and distinctive perspective becomes increasingly important. Why Yoast launched AI visibility tracking As AI systems reshape how information is discovered and summarized, a new challenge emerges for businesses: understanding how their brand appears in AI-generated answers. That’s the problem Yoast set out to address with Yoast SEO AI +, a feature designed to help businesses monitor how their brand shows up across major AI platforms. Earlier in this article, we explored how AI systems now sit between users and search engines, retrieve only a small set of results, and synthesize answers through the summarization of modern content. Together, these changes create a new discovery layer that is far less transparent than traditional search. As Alain explains in the podcast: “We need more visibility and observability into that AI-based layer to figure out what is going on there. Right now, it’s mostly a black box.” Unlike traditional search engines, AI systems don’t provide clear rankings, impressions, or click data that explain why a source was selected. Instead, answers are generated from a mix of retrieved content, training data, and model reasoning. For businesses, that makes it much harder to understand whether their brand is visible in AI-driven discovery. This is where AI visibility tracking becomes valuable. Rather than focusing only on search rankings, teams also need insight into how their brand is represented inside AI responses. Yoast SEO AI + helps surface that layer by allowing teams to observe how their brand appears across AI systems, such as ChatGPT, Perplexity, and Gemini. Must read: What is ChatGPT Search (and how does it use Bing data)? The goal is not simply to track another metric. It’s to help businesses understand how AI systems interpret and represent their brand. As Alain notes, visibility in AI systems can vary significantly depending on the platform, because each one relies on different combinations of: search engines indexes training datasets This means a brand might appear frequently in one AI system while barely showing up in another. Without visibility into those differences, it becomes difficult for teams to understand how their content performs in the new discovery landscape. In that sense, tools like Yoast SEO AI + are less about selling a new SEO feature and more about helping businesses observe a rapidly changing ecosystem where discoverability no longer happens only in search results. The next evolution: AI agents making decisions “What we will increasingly see is automated transactions where AI agents navigate websites and initiate actions on behalf of users.” So far, much of the discussion around AI and search has focused on how answers are generated. But according to Alain, the next phase of this evolution may go further. Over the next 12–18 months, AI systems may begin moving beyond answering questions and start performing tasks on behalf of users. Instead of guiding someone toward a website to make a decision, AI agents could increasingly compare options, interact with websites, and complete actions automatically. If that shift happens, the traditional customer journey could change significantly. Alain shares a fascinating perspective on what this might mean for businesses in the coming years in the full podcast conversation. SEO matters more than ever AI isn’t replacing SEO. If anything, it’s reinforcing why good SEO matters in the first place. What’s changing is the path between users and content. Instead of navigating search results themselves, users increasingly receive answers that AI systems retrieve, interpret, and synthesize. That makes strong fundamentals more important than ever. Businesses still need to focus on: valuable content clear structure discoverable and indexable pages a distinctive brand identity But the central question for SEO is evolving. It’s no longer just: “Can Google find my website?” It’s now: “Does the AI have a reason to remember my brand?” For more insights from Alain Schlesser on how AI is reshaping SEO, watch the full Get Discovered podcast episode. The post Rethinking SEO in the age of AI appeared first on Yoast. View the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. The Google Pixel 10 Pro Fold (256GB, Unlocked) is currently $1,499 (originally $1,799) on Amazon, and price trackers show this is the lowest it has reached so far. Physically, the phone keeps the same overall size as the earlier 9 Pro Fold, but it runs on the new Tensor G5 processor with Android 16 and, since the phone is unlocked, works across major U.S. carriers like Google Fi, Verizon, T-Mobile, and AT&T. That flexibility is helpful if you plan to change carriers down the line. Google Pixel 10 Pro Fold 256GB Unlocked Android Smartphone (Jade) $1,499.00 at Amazon $1,799.00 Save $300.00 Get Deal Get Deal $1,499.00 at Amazon $1,799.00 Save $300.00 Folded, it measures 6.11 by 3.00 by 0.43 inches, and when opened, it spreads into an eight-inch inner display that feels more like a small tablet. The outer screen is now 6.4 inches with slimmer bezels and significantly brighter output, reaching roughly 3,000 nits, which makes a noticeable difference when using the phone outdoors. Both screens support refresh rates up to 120Hz, so scrolling and animations look smooth. Google also strengthened the aluminum frame and simplified the hinge design by reducing the number of internal parts. It is also one of the few foldable phones with an IP68 rating for dust and water resistance, something still rare in this category. At 9.1 ounces, though, the phone is heavier than many competing foldables, and the raised camera module on the back causes a bit of wobble when placed on a table. As for its battery life, it lasted over 13 hours in PCMag’s testing, which puts it ahead of others in its category, including Samsung's Z Fold 7. Charging is capped at 25W wired and 15W Qi2 wireless, and it works with Google’s new Pixelsnap magnetic charging accessories (which our writer has called a delightful MagSafe clone). Google also leans heavily on its AI features here. The phone runs Gemini tools locally, including Live Voice Translation and Instant View, which briefly shows the photo you just took on the outer screen before you move on to the next shot. The cameras are another strong point. You get a 48MP main sensor, a 10.5MP ultra-wide, and a 10.8MP telephoto lens with 5x optical zoom, along with Pixel photo tools like Best Take and Add Me. In practice, the phone delivers some of the best camera results currently available on a folding phone, according to this PCMag review. Our Best Editor-Vetted Tech Deals Right Now Apple AirPods 4 Active Noise Cancelling Wireless Earbuds — $119.99 (List Price $179.00) Samsung Galaxy S26 512GB + $100 Amazon Gift Card (Black) — $1,099.99 (List Price $1,099.99) Google Pixel 10a 128GB 6.3" Unlocked Smartphone + $100 Gift Card — $599.00 (List Price $599.00) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $299.00 (List Price $349.00) Apple Watch Series 11 (GPS, 42mm, S/M Black Sport Band) — $299.00 (List Price $399.00) Amazon Fire TV Soundbar — $99.99 (List Price $119.99) Deals are selected by our commerce team View the full article

Shares in the preeminent graphics software company Adobe Inc. (Nasdaq: ADBE) are dropping significantly in premarket trading this morning following the company’s Q1 2026 earnings results. Yet it’s not the earnings themselves that are driving ADBE stock lower. It’s an announcement from the company’s CEO, Shantanu Narayen, who said he plans to exit the role he has held for over 18 years. Here’s what you need to know: What’s happened? On Thursday, Adobe announced the results of its first quarter for fiscal 2026. And for all intents and purposes, the results were of the caliber that would normally make investors happy: Total revenue of $6.4 billion (up 12% year-over-year) Diluted earnings per share (EPS) of $6.06 adjusted Total annualized recurring revenue (ARR) of $26.06 billion As noted by CNBC, for the quarter, Adobe’s total revenue and EPS figures exceeded investor expectations. The LSEG analyst consensus was that Adobe would bring in total revenue of $6.28 billion and achieve an EPS of $5.87. But if Adobe beat expectations, why is the stock down significantly this morning? Longtime boss is saying goodbye The main reason Adobe’s shares are in the red this morning is that in addition to the company’s earnings results yesterday, the Photoshop maker also announced that its long-running CEO, Shantanu Narayen, will be stepping down from the role. Without a doubt, the departure of Narayen is a loss for the company. As the departing CEO said in his resignation letter, Narayen has worked for Adobe for 28 years and led the company in the chief executive role for over 18 years. Narayen, who is 62, first became CEO in 2007. Adobe shares have grown more than 542% over that period, although they are down considerably since 2024. During Narayen’s 28-year tenure at Adobe, the company’s workforce has grown tenfold, going from 3,000 to 30,000 employees. Its revenue has grown from less than a billion dollars annually to more than $25 billion. Perhaps most critically, under Narayen’s chief executive tenure, Adobe transitioned from a company that primarily sold one-time software licenses to one that is now primarily subscription-based. While that move was not always popular with Adobe’s customer base, it has built a foundation for the recurring annual revenue the company now relies on. Narayen has long been a respected figure at Adobe, and within the broader tech industry, so it’s no surprise that his announced departure is having a negative effect on Adobe’s stock price. Narayen says he will stay on as CEO until Adobe’s board appoints a new one, at which point he will remain as Chair of the Board at Adobe. Adobe investors can’t shake AI anxieties Another element to Narayen’s departure that is likely causing investor jitters is that he is stepping down at a time when Adobe has never been more vulnerable. Narayen successfully navigated Adobe through the largely iPhone-driving death of its core Flash technology in the early years of his tenure as CEO. But now the company arguably faces an even more critical flashpoint. As AI tools become more advanced, investors are increasingly worried that they threaten the very foundations of Adobe’s business models. If an AI chatbot can generate a photo on demand, investors worry that customers will find less value in its stock photo service. And if AI can make edits and enhancements to photos and graphics simply by using natural language prompts, will fewer future creatives find less value in the company’s Creative Cloud software? To be fair, the AI threat isn’t a problem unique to Adobe. In the first part of this year, software companies of all stripes have been hit hard by investor worries that AI chatbots and their increasing capabilities will negatively impact enterprise and commercial software solutions. And while Adobe itself is of course embracing AI tools in its own products, the planned departure of the company’s beloved CEO at this critical time in the industry is making a lot of investors nervous today, as is evident by the company’s plunging stock price. Adobe shares crash on CEO’s planned departure As of this writing, in premarket trading, ADBE shares are down over 7.5% to $249.31 after yesterday’s announcement of Narayen’s upcoming exit. The company’s shares ended yesterday down 1.43% to $269.78. But even before today’s steep drop, Adobe’s shares have had a bad year. As of yesterday’s close, ADBE shares had lost nearly 23% of their value since the year began. Looking back over Narayen’s tenure as CEO, Adobe’s share price has had a stellar run. In December 2007, when Narayen became chief executive, ADBE shares were trading around the $42 range. By 2021, the company’s shares had peaked at nearly $700. But, particularly since 2024, the company’s shares have declined significantly, as fears over AI’s impact on legacy software companies have grown. Those fears are now something that Adobe’s next CEO, whoever that may be, will have to effectively manage. View the full article

Being seen is a fundamental human need. We all can recall a moment when we truly felt “seen” by someone for who we are, and how good and empowering it made us feel. When this happens, it deepens our sense of belonging and makes us more connected to our work, and to others. And today, with so much of our attention being scattered and superficial, being truly seen is as surprising as it is refreshing. Research supports this: a sense of social belonging is one of the strongest predictors of engagement and performance at work. According to Deloitte’s Global Human Capital Trends report, 79% of organizations say that creating a sense of belonging is important or very important for their success. However, only a small percentage feel equipped to make it happen. This needs to change, now. Because when people feel seen, they feel validated, appreciated, and engaged. And that’s where leadership truly begins. According to Nina Bressler, Global Head of Service Academy at Hitachi Energy, “Every time we see someone fully, not just their role but in their humanity, we have the experience of learning and growing together. People lean in, share what they know, and risk showing what they don’t. In that mutual recognition, performance becomes a natural outcome of belonging.” A Personal Story: The Power of Sawabona In the Zulu language, there’s a greeting I love that captures this sense of belonging. It’s “Sawabona.” It means “I see you,” but it’s much deeper than that. It’s not just an acknowledgment or a greeting; it’s an affirmation of someone’s existence and humanity. The response to “Sawabona” is just as powerful: “Ngikhona,” which means “I am here.” This exchange conveys mutual respect, and sets the tone for meaningful connection and authentic interaction. For years, I sat on a leadership advisory board within the intelligence community, made up of accomplished experts across a variety of fields. We always sat at the boardroom table, putting our heads together to urgently tackle the high-stakes issues that needed our input. The pressure to perform was always stressful, and the environment felt as intimidating as it was inspiring. But one day, the mood changed. The chairwoman of our board, Renee, began our meeting with “Sawabona,” she said. This was definitely different from the typical call to order and reading of the agenda, and people were seemingly caught off guard. We all then said the response: “Ngikhona,” I am here. And immediately, people smiled. Not just because it was a little awkward, but because it was so … human. This exchange set the tone for the entire meeting. It was a kind acknowledgment of each person’s presence, and importance. That single act of recognition created an atmosphere where we could show up genuinely and engage deeply, not just as experts but as humans with unique experiences, values, and stories. Why Sawabona Matters for Your Team At work, we forget the power of seeing each other fully. I know I’m guilty of this, because I get, well, busy. We all focus on tasks, deadlines, and outcomes, but better outcomes happen when people feel seen as themselves. Research from BetterUp found that when employees experience a strong sense of belonging, organizations see: 75% fewer sick days 56% improved job performance 50% lower turnover risk These kinds of results are worth the risk of an awkward moment, in my opinion, no? Sawabona is rooted in the African philosophy of Ubuntu, which emphasizes both interconnectedness and mutual care. “I am because we are” speaks to the understanding that our individual worth is shaped by our connection to others. When we see each other, we strengthen the bonds that foster collaboration, innovation, and shared purpose. If you want your team to thrive, fostering a sense of Sawabona is key. Leaders who do this are recognizing people for who they are, not just what they produce. When you honor someone’s existence and humanity, you unlock their potential. How to Bring Sawabona to Work Incorporating Sawabona into your team culture isn’t about using the phrase as a token gesture. It’s about showing everyone mutual respect and authentic connection, even in small ways. Here’s how to start: Show Up Fully – Sawabona means showing up, not just physically, but emotionally and mentally. That means you don’t just show up and sit in the room; be engaged. When people feel their presence is valued, they’re more likely to show up as their best selves. Practice Active Listening – The foundation of Sawabona is truly listening. So, be attentive, ask thoughtful questions, and seem understanding. Celebrate Individuality – Everyone on your team is unique. Their perspectives, experiences, and backgrounds shape what they bring to the table. Take time to acknowledge what makes each person special. Let that perspective add to new ideas and solutions. Create Space to Share – People need to feel safe to express themselves. Create an environment where your team can give ideas, voice concerns, and add to the conversation without fear of judgment or rejection. The Radical Power of Being Seen The act of being seen is alarmingly radical in a world that frequently treats people as a means to an end. Sawabona rejects the transactional nature of work to focus on a deeper, more authentic human connection. Because people aren’t just cogs in a machine. They’re individuals with worth, complexity, and unique contributions. As a leader, it’s your responsibility to create an environment of support, because your success depends on it. Sawabona is a practice that says, “I see you for who you are, and I value your presence.” Next time you gather your team, start by greeting them with Sawabona, and watch how it transforms the way you work, collaborate, and connect. SEO Tags: Sawabona, Ubuntu leadership, team engagement, mutual respect, leadership culture, active listening, team empowerment, empathy at work, authentic leadership. View the full article

Brandon Ervin, Director of Product Management for Google Search Ads, recently discussed campaign consolidation, AI Max, and what advertiser control looks like in 2026 on Google’s Ads Decoded podcast. The conversation was serious and informed, and reflected a product team that understands advertiser concerns and is actively working to address them. But the podcast is also incomplete. The gap between what Google said and what advertisers actually experience from their sales organization is large enough to warrant a direct response. Ervin’s team is doing genuinely good work, but the platform’s structural incentives haven’t changed. Google’s evolving product is creating problems faster than it can solve them. Performance is now measured on economic standards, shaping how a search ads audit is performed. Recent improvements to Google Search Ads Recentish improvements are genuine: Brand exclusions in Performance Max and Demand Gen. Site visitor and customer exclusions from PMax campaigns. Network-level reporting within bundled campaigns. Improved search term visibility. Brand and geo controls inside AI Max at the ad group level. Semantic modeling that doesn’t anchor on campaign or ad group IDs, reducing learning period risk during consolidation. These are meaningful. They are also solutions to issues introduced by bundling, opacity, and aggressive automation rollout. These products have been mercilessly shopped to advertisers since 2021, and the controls that make it usable arrived years after the sales push began. The ability to separate brand from non-brand traffic inside PMax/AI Max should not be framed as innovation. It restores a fundamental distinction that previously existed by default. The ability to see network performance inside a bundled campaign is not an expansion of control. It restores visibility that was removed. An audit must ask whether new tools are genuinely expanding control or merely reintroducing baseline transparency. Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with Table stakes: What everyone agrees on Before the real audit begins, the fundamentals. These are uncontroversial and should already be in place: Run full ad extensions (sitelinks, callouts, structured snippets, image, call). Use automated bidding with intentional target-setting and conversion action selection (I recognize there are still holdouts here but seems crazy to me). Maintain negative keyword lists. Write ads relevant to the queries they serve. Audit automatically created assets for accuracy and brand safety. Cut Search Partners and Display expansion from Search campaigns. Separate brand and generic campaigns using brand controls. Exclude site visitors and past customers from prospecting campaigns where appropriate. Import offline conversion data (MQLs, SQLs, revenue, CLV, repeat rate,) to feed the algorithm downstream signals. Weight conversion values by actual downstream conversion rates. Account for mobile vs. desktop performance gaps. Those are table stakes. The real audit begins after that. What a 2026 search audit must focus on With the prevalence of AI, advertisers need to focus on reconstructing economic visibility in systems designed around aggregation and automation. Signal architecture In the podcast, Ervin says “control still exists, it just looks different.” Ad controls — where, when, and to whom ads appear — are still important and changing, some think, for the worse. The old ad controls — exact match, manual bids, network selection, and device modifiers — gave advertisers direct influence over where ads appeared and what they paid. However, the new controls are indirect. Control now lives in data quality, density, and selectivity. They influence the algorithm, but the algorithm makes the final call. An audit should focus on three questions: Quality: Are you importing revenue, pipeline stage, or qualified lead status, or only surface conversions? Density: Is there enough high-quality data for the model to learn from, or is it sparse and noisy? Selectivity: Are you intentionally limiting what Google can see, or are you passing everything indiscriminately? IMG With these new tactics, you only pass net-new customers or high-value customers. The majority of the time, it is better to just pass the densest and most predictive conversion set. Incrementality Google optimizes toward reported conversions, not incremental conversions. Brand search often captures existing demand. Retargeting often captures users already in motion. Pmax/AI Max frequently blends these signals. Ervin was asked: Are AI-driven campaigns over-indexing on warm brand traffic to inflate blended ROAS (return on ad spend)? He doesn’t dispute the problem, but points to partial solutions, including using brand controls, better theme your account, and looking at multi-campaign A/B testing. If incrementality is not measured, automation amplifies non-incremental signals. Marginal returns Google uses a blended cost-per-action (CPA). For example, the first $50K of spend might return a $30 CPA, while the next $50K might return $120. With automation, money is spent until the blended metric falls within tolerance, meaning the last dollar is not spent efficiently. The vast majority of advertisers are bidding far beyond what they should be and have no idea it is happening. An audit must: Plot spend against incremental conversions. Estimate marginal CPA at each spend tier. Identify diminishing return curves. Compare marginal CPA to lifetime value. A lower target makes the algorithm more selective, competing in fewer high-value auctions. Google doesn’t suggest this because that would mean less spend and lower bids are less effective in general. Query resolution and ability to lower targets On the podcast, Ervin acknowledges that some AI Max matches can “look a little wonky” and says his team is working on exposing the model’s reasoning. Query mapping has gotten meaningfully worse over the past several years: queries landing in the wrong ad groups, matching to keywords with different intent, and broad match pulling in traffic unrelated to the keyword. AI Max has accelerated this — there’s been an increase in the volume of irrelevant queries flowing through AI Max campaigns, with no connection to the advertiser’s business or keywords in the account. Meanwhile, Google’s recommendations consistently push toward broad matching and large themed ad groups. The issue is not whether broad match works, but whether high-value intent is being diluted in larger, broader ad groups. Fewer ad groups means that we cannot effectively or meaningfully lower targets without a massive structural negative schema, so performance differences have to be large enough to validate the new structure. An audit should: Extract full search term reports. Classify queries by intent tier. Compare CPA and lifetime value by query type. Quantify irrelevant or weakly related matches. Measure performance drift across match types. Network economics Performance Max and Demand Gen bundle multiple networks into single campaigns, but offer limited visibility into which networks drive results. This makes it hard to cut the underperforming ones. The slow rollout of network-level controls systematically benefits Google’s less competitive inventory. An audit must: Break out performance by network. Compare CPA and lifetime value by placement. Identify cross-subsidization. Determine whether weaker networks are relying on surplus from strong search inventory. Value redistribution Combining these elements in your audit will help you succeed in this new world of ad search: Non-incremental traffic inflates conversion counts, making performance look better than it is. Looser match types expand where ads appear, diluting intent precision and forcing fewer ad groups/spend and blanket-level targets/bids. No clean marginal return visibility means it is much more difficult to find the point of negative return Network bundling hides which channels actually perform. The cumulative effect is that the surplus value generated by your best inventory and high-intent, high-converting search queries gets redistributed across Google’s weaker inventory (i.e., Display, YouTube, Discover, Gmail, crazy tail queries). This is how to get a dwindling supply of valuable search queries to inflate the cost-per-clicks (CPCs) of low-quality inventory. The Ads Decoded episode: Is your campaign structure holding you back in the era of AI? View the full article

That may sound defeatist, but unfortunately that’s just how the web works. Rankings slip, competitors improve, search intent shifts, and what was your best-performing article two years ago might be leaking traffic right now without you even noticing. This is…Read more ›View the full article

Hello again, and welcome back to Fast Company’s Plugged In. On March 9, Jay Graber stepped down as CEO of Bluesky. She will become the social networking platform’s chief innovation officer, while Toni Schneider, a venture capitalist and former CEO of WordPress parent company Automattic, joins Bluesky as interim CEO. (I may be the last person left who also associates Schneider with Oddpost, an impressive browser-based email client he co-created way back before Gmail existed.) Graber explained her decision as stemming in part from a desire to turn the CEO role over to someone who can help scale up the platform. From November 2024 to January 2025, as Elon Musk’s role in Donald The President’s reelection prompted many Twitter users (including me) to hatch exit strategies, Bluesky added 10 million users. That turned out to be the peak of the network’s boom, at least so far; 10 million users is also how many it’s added in the past 12 months. It’s still growing, but not at the torrid pace that will get it to hundreds of millions of people anytime soon. If I had invested in Bluesky—which Schneider’s venture firm, True Ventures, has—I’d want to see it grow far larger. As an individual user, however, I find it quite pleasant at its current size. Maybe even cozy, in a way Twitter had stopped being long before Musk trashed it. (I also enjoy the even tinier Mastodon.) Should Bluesky ever get ginormous, I hope it manages to retain the intimacy that it kindles today. But I’m less curious about the future of Bluesky the social network than I am about the technology behind it. Called AT Protocol, it’s responsible for organizing all those users and posts so that the right people see the right stuff at the right time. And unlike the comparable infrastructure in place at behemoths such as Twitter, Facebook, and Instagram, it’s open. Anyone can create their own social network based upon AT Protocol, or remix an existing one (such as Bluesky) by tweaking its algorithm or other attributes. Users can preserve their personal social graphs even if they use several otherwise distinct networks based on the protocol. When I first talked to Graber in December 2023, Bluesky wasn’t yet fully open to the public, and had just 2.3 million members. She seemed as excited about AT Protocol as Bluesky itself, and told me she saw it as a potential antidote to social-media toxicity, moderation problems, and general user dissatisfaction with how the people who operate social networks do their jobs. If you didn’t like Bluesky as Graber managed it, you could switch to a version of the service powered by a different algorithm, or a wholly independent social network running AT Protocol. You wouldn’t even have to do so much as create a user account. From both a technological and cultural standpoint, that’s a way more grandiose goal than simply building a social network that’s bigger and better than Twitter. As someone who loved Twitter until I didn’t, I found it immensely appealing. Who wouldn’t want more control over their social presence? But a little over two years later, it remains a vision more than reality. Indeed, Bluesky has a festering reputation in some quarters as an obnoxious liberal bubble unwelcoming of other perspectives, which might not be a problem if people were remastering the network or creating new alternatives based on its technology. AT Protocol was hardly dead on arrival. There are hundreds of applications that use it, from Instagram and TikTok alternatives to a stock portfolio tracker to an app that puts Bluesky on your Apple Watch. Many are intriguing in their own right. But most are satellites revolving around Bluesky and its community, which was not the original idea. Even when I spoke to Graber in 2023, the possibility of an open social protocol changing everything was not exactly new. Mastodon, which turns 10 on March 16, is powered by ActivityPub, a standard with goals similar to AT Protocol. Meta incorporated a measure of ActivityPub support into Threads (kinda, sorta)—and it’s not clear how invested the company is in going further. Even more to the point, Twitter cofounder and former CEO Jack Dorsey has long said that he regrets that Twitter ever became a company. Instead, he contends, it should have been an open protocol all along. Toward the end of his time there, he channeled that belief into incubating two such protocols. One became Bluesky; the other is the lesser-known Nostr, whose homepage cheerfully acknowledges the challenge it faces with the tagline “An open social protocol with a chance of working.” I wish the best for everyone behind AT Protocol, ActivityPub, and Nostr, but I can’t help but wonder if the failure of the relatively small number of people interested in this stuff to coalesce around one protocol helps explain why progress has been so slow. (As computer scientist Andrew S. Tanenbaum waggishly put it in the 1980s, “The nice thing about standards is that you have so many to choose from.”) It’s as if the companies that made browsers had never agreed on the shared technological underpinnings that let us use Chrome, Safari, Firefox, or any of innumerable other options to explore the same World Wide Web. For now, I am attempting to stay active on Bluesky, Mastodon, and Threads, though it’s hardly a cakewalk. Openvibe, the app I used to post to all three, has become so unreliable lately that I’ve mostly given up on it. Flipboard CEO Mike McCue tells me that he wants to add crossposting to Surf—a wildly ambitious app, still in closed beta, that weaves together the entire internet into user-curated feeds—but is still figuring out how to do it well. The only long-term solution involves all of these networks—plus Twitter, Facebook, and many others yet to be born—settling on a protocol so universal that they all just work together, without 99.9% of us needing to stop and wonder why. I’m realistic about the daunting odds of this happening, but I haven’t given up. And I hope that Bluesky won’t either—regardless of where it goes under new management. You’ve been reading Plugged In, Fast Company’s weekly tech newsletter from me, global technology editor Harry McCracken. If a friend or colleague forwarded this edition to you—or if you’re reading it on fastcompany.com—you can check out previous issues and sign up to get it yourself every Friday morning. I love hearing from you: Ping me at hmccracken@fastcompany.com with your feedback and ideas for future newsletters. I’m also on Bluesky, Mastodon, and Threads, and you can follow Plugged In on Flipboard. More top tech stories from Fast Company MacBook Neo review: niceness on a budget Apple’s long-awaited laptop is even cheaper than the pundits expected, and still feels like a Mac. Read More → Phoenix has lived with Waymos longer than any U.S. city. Here’s what its mayor learned Mayor Kate Gallego talks about working with Waymo, redesigning cities for autonomous vehicles, and why robotaxis may reshape everything from parking to public transit. Read More → GoFundMe launches AI fundraising coach to help people raise more money The new tool drafts campaign messages, suggests titles and photos, and guides users on how to share their fundraiser. Read More → This new foldable phone may have upstaged Apple in the ‘zero-crease’ war Oppo’s Find N6 isn’t fully creaseless, but it’s close. Read More → OpenAI’s delayed ‘adult mode’ underscores the challenges of age-gating AI A lot is riding on OpenAI’s ability to separate older ChatGPT users from younger ones. Read More → The uncomfortable valley: Microsoft Teams emoji faces have got to go They don’t make the digital workplace more casual. They make it uncomfortably weird. Read More → View the full article

The problem: ChatGPT doesn’t have “rankings”. At least not in any traditional sense. Its responses are probabilistic: different every time, with brands appearing and disappearing from one query to the next. According to research from SparkToro, there’s a <1 in…Read more ›View the full article