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CMS defaults now influence more of the web’s technical SEO than most consultants ever can, reshaping where optimization work creates real value. The post 3 CMS Platforms Control 73% Of The Market & Shape Technical SEO Defaults appeared first on Search Engine Journal. 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. Samsung’s new Galaxy S26 Ultra launches with the usual Ultra series promise: the biggest screen, the most capable cameras, and the most features in the company’s lineup. It also launches with prices that reflects that ambition ($1,299.99 to $1,799.99). That said, Samsung is running an early promotion from March 16 through April 20 that can soften the blow. Buyers can save up to $720 with an eligible instant trade-in credit, or get $150 in credit without a trade-in to use toward other eligible Samsung devices. The deal applies directly through Samsung’s store, where the phone is also available with configuration options for storage and color. Samsung Galaxy S26 Ultra Trade-in deal: up to $720 in instant credit at Samsung Get Deal Get Deal at Samsung The S26 Ultra builds on the formula Samsung has refined over the past few years. The phone keeps the large Ultra-style display, now using Samsung’s newest OLED panel with a high refresh rate and a peak brightness designed to stay readable in direct sunlight. Samsung also introduced a new privacy display feature that limits viewing angles so people nearby cannot easily see what’s on your screen. That feature was introduced alongside the phone during the company’s 2026 Unpacked event, and it is aimed at commuters or frequent travelers who often use their phone in public places. Samsung is also leaning heavily on the camera system this year. As we covered in our earlier look at the S26 cameras, the company appears confident about improvements to image processing and zoom performance. The Ultra line still targets people who treat their phone as their primary camera, and the hardware reflects that focus. Samsung built the S26 Ultra around a large multi-sensor camera system paired with its latest computational photography tools, aimed at users who regularly shoot photos, video, or social media content from their phone. But the device remains big and expensive even with discounts. Samsung raised prices across the S26 lineup this year, which we covered in our breakdown of the price increase. That makes the launch promotion more relevant for anyone already planning to upgrade from an older Galaxy device. Our Best Editor-Vetted Tech Deals Right Now Apple AirPods 4 Active Noise Cancelling Wireless Earbuds — $148.99 (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 rules of organic content are shifting from a “publish more” to a “prove more” mindset. Search results increasingly answer questions directly through AI summaries, shopping features, and other SERP integrations. Visibility alone doesn’t resolve buyer uncertainty. For ecommerce brands, organic visibility now requires recognition and trust amid the noise on the SERPs. The 2026 game is both simpler and more demanding. Invest in organic assets that: Reduce buyer uncertainty. Are machine-readable. Compound across multiple discovery surfaces. The forces shaping organic content’s ROI in 2026 Today’s search is defined by three forces changing how content performs. AI discovery is normal now Generative AI has become a standard part of the organic search results through features like Google’s AI Overviews and AI Mode. These generative AIs answer broader questions directly, often pulling in citations from web content. AI Overviews were designed to help people get the gist of a topic quickly, providing a jumping-off point to explore links. However, time has shown they also contribute to fewer direct clicks on traditional search results, as users might get their answer entirely from the AI summary. So, if you want your ecommerce brand to earn organic visibility, you need content that AI will cite and that users will trust. Shopping-first SERPs reward structured product data Nowadays, Google’s search results are saturated with shopping features (e.g., product carousels, price comparison snippets, “Popular Products” lists, and more). Sometimes, they look more like the search results on an ecommerce site than a traditional organic SERP. These discovery surfaces are powered by structured product data and merchant feeds. Product pages must communicate clean data to Google. Product results depend on the quality of the attributes you provide. Google recommends that ecommerce sites include structured data on product pages and share complete product feeds for richer search appearances. The bottom line is that you need to invest in your product data infrastructure. When Google can reliably understand what you sell, it will showcase your products more prominently, helping you attract more qualified shoppers. Discovery is multi-platform The traditional funnel, where a customer Googles something and clicks your link, is evolving especially for Gen Z. Search now takes place on social media in huge numbers. Approximately 86% of Gen Z internet users report searching on TikTok weekly, almost as many as use Google. This means your potential customers might discover products through a TikTok video or an Instagram Reel long before they ever see your website. Here’s the pattern I see with ecommerce: Someone is scrolling on a social media app. They see your Reel, post, or ad. They don’t buy at that moment. Later, they Google you, or they Google the exact thing they saw. They land on your site. This is demand creation. Keep in mind that these types of results are showing up on Google, too. Meanwhile, AI platforms are already part of the discovery process. Social search behavior is here, so think of platforms like YouTube, TikTok, and Instagram as extensions of Google. Dig deeper: The social-to-search halo effect: Why social content drives branded search 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 7 organic content investments that will pay off in 2026 So, where exactly should ecommerce teams focus their content resources? 1. Upgrade the money pages first Start with the pages that directly drive revenue (e.g., your product detail pages (PDPs), collection pages, and other high-intent landing pages). Make these pages conversion-ready. Go beyond the basic title, image, and price by adding content blocks that answer buyer anxieties. For example, your PDPs should include clear information on sizing/fit, compatibility, materials, care instructions, warranty, shipping and return policies, and genuine FAQs from real customers. To do this, find conversational queries through Google Search Console and look at one-star and two-star reviews, either on competitor products or your own, to see the exact questions, complaints, and doubts buyers have. Alternatively, you can get full clarity on the three types of obstacles that every single client has and focus on the emotional one. For each pain point, ask: What’s the obvious pain point? (surface-level problem) What’s the hidden pain point? (what they’re really worried about) What’s the emotional pain point? (the core feeling driving the decision) Here’s an example scenario: Imagine a mother who works remotely and has a baby who refuses to sleep: Obvious: “I can’t find time to get the baby to nap.” Hidden: “I don’t want to pay for something that might not work.” Emotional: “I feel like a bad mom if I can’t manage this.” That last one — the emotional obstacle — is the strongest. People buy relief. They buy confidence. They buy the feeling that things will be okay. On category pages, add filters that guide users (e.g., “Shop by size, color, or use case”), highlight top sellers or award-winning products, and include comparison links (e.g., “Best for X vs. Y”). Try to enrich these pages so that a customer who lands on them has all the info they need to feel confident making a purchase. The goal is a page that precisely matches the user’s intent and resolves uncertainties. 2. Focus on visual search optimization We live in a visual search world. Consumers are searching with images and even combinations of images and text. As Google itself noted, “… consumers are using their voices to find answers on the go, and their cameras to explore the world around them.” Search has expanded beyond the traditional text box. This shows ecommerce’s huge opportunity to invest in visual content optimization. Throughout 2025, there were over 100 billion visual searches via Google Lens and related visual tools, with one in five of those searches driven by someone looking to buy a product they saw. Up to 39% of consumers have used Pinterest as their search engine, per an Adobe study, and Instagram is clearly moving in the same direction. Shoppers are using images to find ideas, compare products, and determine what to buy. This means you need to optimize your ecommerce images and videos for organic search just as rigorously as your text content. Short-form videos and image carousels are what people watch most on Instagram and TikTok, and now that content is becoming easier to find through search. Instagram now allows keyword searches for posts, meaning alt text and caption keywords can help your posts appear in searches like “best winter boots.” Treat every image and video as a piece of searchable content. Dig deeper: 10 advanced ecommerce SEO tips that boost rankings and revenue 3. Feed Google the right product info: Schema and Merchant Center Structured data and product feeds aren’t optional. If you want Google to feature your products in shopping results (and pull correct info into AI answers), you need clean product data. Start with the product pages. Add Product schema on every PDP and include all the basics: name, description, image, brand, SKU, price, currency, availability, and offers. If you show reviews on the page, mark up reviews and ratings, too. If shipping cost, delivery time, or variants matter for the purchase, include that information as well. Only use FAQ/HowTo/Review schema when the content is actually on the page. Next, treat the Google Merchant Center feed like an SEO asset because Google does. Keep it accurate: use titles that match the product, correct categories, accurate price and stock information, and no mismatches with your PDPs. After you fix errors in Merchant Center, improve the feed by adding attributes like size, color, and material. Turn on automatic updates so Google can handle small changes. When Google can clearly read what you sell, it shows your products more often, and the clicks received are higher intent. Get the newsletter search marketers rely on. See terms. 4. Build first-party ‘proof’ content (reviews, UGC, expert testing, etc.) Create content that credibly demonstrates the quality and performance of your products. This includes: Customer reviews and ratings on the site. Content your team creates that demonstrates first-hand experience with the products. For reviews, consider improving your review prompts to get more detailed feedback. For example, you can ask customers specific questions about fit, durability, or how they’re using the product. Find ways to highlight these insights on the PDP (e.g., a summary of common pros and cons). This kind of content signals to Google and users alike that the site offers genuine insights. A shopper is more likely to convert when they see real evidence, and this directly leads to higher conversion rates. If you publish in-depth product review articles or videos on your site, you can capture search queries for “[Product] review” or “is [Product] worth it,” because Google will “see” the first-hand expertise. Additionally, ecommerce brands can create their own original testing and use-case content. This might be blog articles or video snippets where the brand tests the product’s claims or compares it to alternatives. Essentially, brands should think like an in-house influencer evaluating their product. Dig deeper: How to make ecommerce product pages work in an AI-first world 5. Create decision-support content that feeds the money pages Νot all customers search for a specific product. Many start with broader questions. Capture these early-stage shoppers by creating both comparison and buyer’s guide content that funnels to your product pages. If shoppers aren’t sure what to choose, use formats that reduce confusion and give them a clear path forward, like quizzes or selectors (e.g., “Find your ideal [product] in 60 seconds”) and criteria-led guides (e.g., “How to choose a [category]: 7 factors that matter”). If they’re comparing options, help them narrow the shortlist with head-to-head comparisons (e.g., “[Product A] vs [Product B]”) and “best for” hubs (e.g., “Best [category] for small spaces” or “Best [category] under $X”). And if they’re scared of making the wrong choice, publish risk-reducing content like “mistakes to avoid” articles and “who it’s not for” pages (e.g., “Don’t buy [type] if you have [constraint]”). Each of these content pieces should be seen as an extension of your sales funnel: Design them to link directly to your relevant categories or products This type of content is the bridge between informational queries and purchase-ready sessions. 6. Strengthen retention with community content One of the smartest content investments an ecommerce brand can make is in content created by real people, whether that’s your customers, your employees, or trusted influencers. The reason UGC works so well is that it doesn’t feel like marketing. This isn’t surprising when you consider user behavior: People trust people. Brands should encourage and showcase UGC at every turn. This can mean reposting customer photos showing them using your product on social media, integrating reviews and customer images into your product pages, or running challenges to generate buzz. The key is to treat your customers as a content engine. Another trend is employee-generated content, or in simpler words: leveraging your team to humanize the brand. Forward-thinking ecommerce brands have employees take the stage in content, whether it’s a product development engineer doing a “behind the scenes” video, retail staff modeling new apparel on TikTok, or your founder writing thought-leadership articles. This insider perspective is paying off because it blends expertise with authenticity. Beyond individual pieces of content, ecommerce brands should invest in building communities around their products and niche. A great example is Instant Pot’s official Facebook group, which has over 3 million members. This community of passionate users shares recipes, tips, and excitement about using the product, which means they generate endless organic content for the brand. The best part? The group keeps existing customers engaged and serves as social proof to potential buyers. More brands are realizing that a community = continuous organic marketing. Here’s one more reason to invest in social proof and community: It can influence your search rankings. Google’s recent updates indicate that brand mentions across the web, engagement on social media, and UGC signals can all contribute to SEO. Dig deeper: Why ecommerce SEO audits fail – and what actually works in 30 days 7. Own your audience: Blogs, email newsletters, and content hubs While we’ve talked about discovery on external platforms, another area for organic content investment is your own channels. First, content-rich blogs or resources on your site are still a powerful organic asset. Yes, the content mix has shifted toward video and social, but consumers and search engines still value in-depth written content for certain needs. According to a recent HubSpot marketing report, blog posts are the third-most-popular content format among marketers. That shows blogs are still very much in play, even if they’re not the hottest format. The key is to evolve the blog strategy: Focus on quality over quantity. Target long-tail keywords and questions that your customers ask. Incorporate rich media into posts to keep them engaging. Next, email newsletters. The value of email lies in its ability to directly reach a highly engaged audience. Unlike social media, where your reach can be limited by algorithms, emails land straight in your subscribers’ inboxes, giving you full control over messaging and design. Keep in mind that your subscribers have opted in voluntarily, showing a clear interest in your content or offers. Investing in email marketing tools, hiring good copywriters, and designing emails with careful attention is worth it. Finally, content diversification within your owned media can pay dividends. This includes: Interactive content (quizzes, calculators, etc.). Podcasts or audio content. Even tools or apps that provide utility (which in turn produce content or data users engage with). The key here is aligning the content with what your customers care about. A smart organic content plan could look like this: Put real effort into short-form videos. Keep investing in blog and SEO content. Build community and collect user-generated content (reviews, photos, Q&A). Stay consistent with email and your newsletter. These channels work better when they work together. A blog post can become social posts and newsletter content. Customer reviews and photos can be used in emails and on product pages. Videos can be added to blog posts and category pages. When you connect everything, your content becomes one system that keeps bringing people in and turning them into customers. 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 What to deprioritize (and why it’s riskier now) Just as important as where to invest is knowing what content tactics to avoid. SEO blog content at scale If your strategy is to publish lots of generic blog posts just to target keywords, stop. Especially if that content is automated, templated, or written with minimal effort. You’ll spend time and money, and you will get zero results. Google has strengthened its spam policies against scaled content abuse, which includes content farms and auto-generated pages made only to win rankings. Anything that looks like manipulative ‘SEO trickery’ or reputation abuse Google is cracking down on tactics where sites leverage shady methods to rank. For example: Buying expired domains and filling them with content to gain website authority. Mass-publishing AI-written pages with no quality control. Fake reviews, review stuffing, or any attempt to game ratings. If it looks like a shortcut, it’s probably risky. In short, deprioritize quantity-over-quality approaches and any borderline spammy shortcuts. The direction is clear: Google wants originality, real value, and content made for people. Be present, valuable, and everywhere Ecommerce brands should invest in a multi-channel content strategy that prioritizes quality and is truly user-centric. You need to show up wherever customers search and measure success through visibility, engagement, trust, and sales. The best investment with the greatest ROI is content that’s both genuinely helpful and strong enough to reuse across different channels. View the full article

This Oscar cycle’s heavyweight battle is finally over. The politically charged action comedy “One Battle After Another” just managed to outmuscle Ryan Coogler’s musically driven vampire thriller “Sinners.” It was a 3 hour and 40 minute whirl through cinema and celebration, with Michael B. Jordan winning best actor for “Sinners” and Jessie Buckley winning for “Hamnet,” making her the first Irish performer to ever win in the category. There was electricity when Autumn Durald Arkapaw became the first woman and Black person to win the cinematography award for “Sinners,” asking all the women in the Dolby Theatre to stand up because moments like this don’t happen without women “standing up for you and advocating for you.” Here were some other show highlights: The battle is over for one filmmaker Paul Thomas Anderson, one of the most respected filmmakers of his generation, finally won an Oscar. Then he won another. Then he won for best picture. He first won best adapted screenplay for “One Battle After Another” and then was crowned best director. “You make a guy work hard for this,” he said. Anderson was back onstage for the night’s final award — best picture. “Let’s have a martini. This is amazing,” he said. Anderson had been nominated 14 times previously, including five times for screenplays and three times for best director. His films include “Boogie Nights,” “There Will Be Blood” and “Magnolia.” “I wrote this movie for my kids, to say sorry for the housekeeping mess that we left in this world we’re handing off to them,” Anderson said onstage after winning for his screenplay. “But also with the encouragement that they will be the generation that hopefully brings us some common sense and decency.” Even Cassandra Kulukundis, who served as the casting director on past Anderson films, hoped he would win an award himself while accepting the first new completive Oscar category in over two decades for “One Battle After Another.” She beat him to a win by just minutes. Another long wait for Oscar hardware Amy Madigan, the night’s first winner, had to wait a long time to celebrate an Oscar win. The gap between her first ever Oscar nomination and first win was 40 years — handing her the record wait for a best supporting actress. Madigan’s first Oscar nomination was for 1985’s “Twice in a Lifetime,” losing to Anjelica Huston. She won Sunday for playing an unrecognizable and utterly mesmerizing oddball aunt in “Weapons,” a supernatural thriller about missing children. Madigan had earlier picked up wins at the Critics Choice and Actor Awards. Aunt Gladys’ smeared, heavy makeup, strange hair and large glasses became a popular internet meme and was even played up by Oscars host Conan O’Brien in his opening skit, looking like Gladys as he raced through appearances in other nominated movies chased by children. On hearing her name, Madigan collapsed into the arms of her husband, actor Ed Harris. Onstage, she thanked film writer-director Zach Cregger for giving her a part in “Weapons” she could “grab by the throat.” She last thanked “my beloved Ed,” adding: “None of this would mean anything if he wasn’t by my side.” A heavy goodbye to the Reiners A stage of stars bid farewell to Rob Reiner, led by a long friend and colleague, Billy Crystal. Crystal kicked off the in memoriam section by saying he met Reiner while cast as a best friend of Reiner’s on “All in the Family” in 1975. Reiner’s movies included “This Is Spinal Tap,” “Stand By Me,” “When Harry Met Sally…,” “Misery,” “A Few Good Men” and “The Princess Bride.” “My friend Rob’s movies will last for lifetimes because they were about what makes us laugh and cry and what we aspire to be: Far better in his eyes, far kinder, far funnier and far more human,” Crystal said. Reiner was killed along with his wife, Michele Singer Reiner, in December. Their son, Nick Reiner, has been charged with two counts of murder. After Crystal’s speech, he revealed a stage filled with stars who shone in Reiner’s films, including Meg Ryan, Christopher Guest, Michael McKean, Kathy Bates, Kiefer Sutherland, Demi Moore, Jerry O’Connell, Annette Bening, Mandy Patinkin, Fred Savage and Cary Elwes. In memoriam and Redford The in memoriam section then highlighted those lost during 2025, like Catherine O’Hara, Diane Keaton, Gene Hackman, Robert Duvall, Brigitte Bardot, Michael Madsen, Terence Stamp, Diane Ladd, Sally Kirkland, Tom Stoppard, Malcolm-Jamal Warner and Val Kilmer. Barbra Streisand then stepped up to honor her co-star in “The Way We Were,” Robert Redford. “He was thoughtful and bold. I called him an intellectual cowboy who blazed his own trail, and won the Academy Award for best director, and I miss him now more than ever, even though he loved teasing me,” Streisand said. She then sang a snippet of “The Way We Were,” which she last performed during the 2013 ceremony, when she sang it as an homage to the late composer Marvin Hamlisch. Two stunning song performances The Oscars had only two musical numbers but they were Grammy-worthy. Singer-actor Miles Caton and songwriter Raphael Saadiq performed the deeply bluesy, slinky song “I Lied to You” from “Sinners,” joined by an ensemble that included Misty Copeland, Eric Gales, Buddy Guy, Brittany Howard, Christone “Kingfish” Ingram, Jayme Lawson, Li Jun Li, Bobby Rush, Shaboozey and Alice Smith in a tribute to the film’s visual and musical style. The camera swept in and among the writhing bodies in a rollicking, kinetic performance. “KPop Demon Hunters” later celebrated its win as best animated feature by opening its performance of “Golden” with a fusion of traditional Korean instrumentalists and dance, with dancers in gold waving golden fabric flags. Then Ejae, Audrey Nuna and Rei Ami — the singing voices behind HUNTR/X in the film — belted out “Golden” as members of the audience waved light sticks. Then “Golden” won the Oscar for best original song, a first for K-pop. The coolest part was seeing dancers from each song appear in the other’s, a kind of communication between Delta blues and Asian pop. ‘Bridesmaids’ give us a bouquet Melissa McCarthy, Maya Rudolph, Rose Byrne, Kristen Wiig and Ellie Kemper celebrated 15 years after “Bridesmaids” hit theaters by showing everyone their funny bones haven’t aged. “Now, we are not good with numbers, but we figured out backstage that means we shot this movie in 1883,” Wiig joked. The group — presenting best original score and best sound — had fun at the expense of Stellan Skarsgård, Leonardo DiCaprio and Jacobi Jupe of “Hamnet.” They pretended to read messages from the crowd, including one from DiCaprio that accused Byrne of staring at him. “I have been staring at you,” Byrne replied. “I thought you were somebody else.” Rudolph leaned into her dimwit persona when she wondered: “Earlier today, when I was counting my money, I asked myself, “What is sound?” There was also a mini-“Avengers” reunion with Chris Evans and Robert Downey Jr. presenting best adapted screenplay. And a “Moulin Rouge!” reunion with Nicole Kidman and Ewan McGregor. And there was a Pullman family reunion when Bill teamed up with son, Jack. Second time’s a charm, Conan Conan O’Brien hit almost every note on Sunday — savage, playful, heartfelt and dumb. The second-time host predicted he’d be the last human Oscar MC. “Next year, it will be a Waymo with a tux,” he joked. He also had a jab at Timothée Chalamet, who got into hot water when he seemed to call ballet and opera dying art forms. “They’re just mad you left out jazz,” O’Brien quipped. He reached for a Jeffrey Epstein joke when he noted that it was the first time since 2012 that there were no British actors nominated. “A British spokesperson said, ‘Yeah, well at least we arrest our pedophiles.'” But he also got poetic and sweet when he noted that 31 countries across six continents were represented at the Oscars. “Every film we salute is a product of thousands of people speaking different language, working hard to make something of beauty,” O’Brien said. “We pay tribute tonight, not just to film, but to the ideals of global artistry, collaboration, patience, resilience and that rarest of qualities today: optimism.” Of course, sometimes his bits fell flat, like the time he used a leaf blower onstage and a gag about memes with Leonardo DiCaprio. For more coverage of this year’s Oscars, visit: https://apnews.com/hub/academy-awards —Mark Kennedy, AP Entertainment Writer 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. Sony’s WH-1000XM5 headphones are no longer the newest model in the company’s lineup, but they remain one of the easiest recommendations if you want strong noise canceling without paying flagship prices. Right now, a refurbished pair is $209.99 on Amazon, compared with $278 for a new set (and the $399.99 launch price in 2022). These are sold as Amazon Certified Refurbished units, meaning they’ve been tested and certified by the manufacturer to work like new. They also come with the original accessories and a 90-day limited hardware warranty. Sony WH-1000XM5 Headphones $209.00 at Amazon $278.00 Save $69.00 Get Deal Get Deal $209.00 at Amazon $278.00 Save $69.00 PCMag named them the best headphones of 2022 and gave them an “outstanding” review, largely for how well Sony balanced sound quality with noise cancellation. The XM5 uses 30mm carbon-fiber drivers paired with Sony’s Integrated Processor V1, and the combination still holds up in 2025. Music sounds full without becoming muddy. Bass-heavy tracks have weight, but vocals remain clear, and instruments don’t disappear into the background. The active noise cancellation is also effective at blocking out low-frequency sounds like airplane engines, traffic, or the general rumble of public spaces. Audio quality remains consistent with ANC enabled, unlike many cheaper headphones. For wireless listening, Bluetooth 5.2 supports AAC, SBC, and LDAC codecs, and multipoint pairing makes it easy to switch between devices, such as a laptop and a phone, without reconnecting each time. The XM5 has a lightweight frame and soft synthetic-leather earcups that stay comfortable during long listening sessions. That makes them practical for commuting, long flights, or simply wearing through a full workday. Controls are handled through touch gestures on the earcups—swipe up or down for volume and tap to pause or play. It takes a little time to get used to the gestures, but they work reliably once you learn them. Sony’s Sound Connect app adds more control, letting you tweak the EQ, adjust noise-canceling levels, and change a few listening settings depending on your environment. Battery life is rated at about 30 hours with noise canceling enabled, which is enough for several days of regular use before needing to recharge. Our Best Editor-Vetted Tech Deals Right Now Apple AirPods 4 Active Noise Cancelling Wireless Earbuds — $148.99 (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 prices of memory chip stocks are once again on the rise as a global shortage in random access memory (RAM) continues. Over the past five days alone, the share prices of the four largest memory makers traded on U.S. markets have risen significantly. And today, those same stocks are off to another good start. Here’s what you need to know. Why is there a memory shortage? Since the latter half of 2025, analysts and industry insiders have warned of a looming memory chip shortage coming in 2026—and it’s one of the few tech predictions that have been right. This year, the world is in a full-blown memory crisis. There isn’t enough computer memory to go around, and that scarcity is leading to surging demand—and surging RAM prices. The driving force behind the memory chip shortage is artificial intelligence. But not the AI itself. Rather, the hardware companies need to run their AI systems. An artificial intelligence system like ChatGPT or Google’s Gemini requires massive data centers to run on and compute the billions of requests these chatbots get every day. Those data centers, in turn, need servers, and those servers need memory to carry out the AI tasks. The world is currently in the middle of an AI data center build-out boom, and that massive data center expansion is leading to a surge in memory demand the likes of which the industry has never seen. When memory makers are unable to keep up with demand, a shortage arises, which is exactly where we are today. Micron and Sandisk stocks are skyrocketing There are four major memory makers traded on the U.S. markets: Micron Technology, Inc. (Nasdaq: MU) Sandisk Corporation (Nasdaq: SNDK) Western Digital Corporation (Nasdaq: WDC) Seagate Technology Holdings (Nasdaq: STX) Of those four, Micron and Sandisk are the two firms that primarily make short-term computer memory, which is designed to temporarily store information and help carry out tasks at lightning speed. This kind of memory is seeing the worst shortages. Western Digital and Seagate primarily make long-term computer memory, such as for SSDs, used to retain your documents and photos for a long time. Given that all four of these companies are seeing demand for their memory products soar, it’s little surprise their stock prices have been soaring as of late, too. In the past five days alone, as of Friday’s closing bell, the share prices of all four companies have risen significantly. Over the previous five-day period: Micron stock has risen 15% Sandisk stock has soared 25% Western Digital is up 11% Seagate is up nearly 9% And today, those memory makers are seeing their share prices rise even further. As of this writing, in premarket trading, MU shares are up 4.3%, SNDK shares are up nearly 3%, WDC shares are up 3.3%, and STX shares are up over 2.5%. These continued stock price gains can primarily be attributed to the global memory shortage. How will skyrocketing memory prices affect me? Of course, while investors in the four big memory companies may be quietly cheering on the global memory shortage that is driving their stock prices higher, that shortage is bad for anyone else planning to buy a computer or smartphone this year. While the memory used in AI data centers and that used in laptops and smartphones are different, many memory makers are diverting production resources away from making the “consumer” type of memory bound for smartphones and laptops to making the higher-end memory that AI giants need (because that type of memory is more profitable). This, in turn, means less consumer memory is being made that is suitable for personal devices, so the makers of those devices have to pay more to get their hands on whatever they can. When smartphone and laptop makers pay more for components, they usually don’t just absorb the increased costs; instead, they pass them on to consumers. If you’ve recently shopped for memory or even SSD hard drives online, you’ll probably have seen that prices are much higher than they were last year. And as 2026 progresses, those higher prices will also translate into higher prices for laptops and smartphones, and the memory shortage worsens. Most industry analysts do not expect the memory shortage to get better until sometime in 2027 at the earliest. What to look for next When it comes to the global memory shortage and memory chip maker stocks, the next big thing to look for is Micron Technology’s second-quarter fiscal 2026 earnings results, which will take place this Wednesday, March 18. Analysts will closely dissect the language used by Micron executives to glean insights into how memory demand is changing and whether production capacity is increasing. After Micron’s earnings on Wednesday, the next event to keep an eye on will happen in early May, which is when Sandisk, Western Digital, and Seagate are expected to announce their next results. Memory chip stocks are far outperforming the Nasdaq What’s especially remarkable about Micron, Sandisk, Western Digital, and Seagate’s run lately is that their stock prices have not been significantly impacted by the broader pullback of the Nasdaq on which they trade. While the four memory companies have seen their stock prices rise by nearly 9% to 25% over the prior five trading days, the Nasdaq Composite has declined 1.6% over the same period, largely due to uncertainties about the war in Iran. Year-to-date, the gap between the four memory makers and the Nasdaq Composite is even starker. Since the year began, the Nasdaq Composite is down 4.2%. But in the same timeframe, Micron is up 49%, Western Digital is up 58%, Seagate is up 39%, and Sandisk is up a staggering 178%. View the full article

Discover how AI agents decide which brands to recommend and why trust is essential in the new marketing landscape. The post How AI Agents Decide Which Brands To Recommend: Trust Is The New Ranking Factor appeared first on Search Engine Journal. View the full article

Gorin explains Expedia’s three-part AI strategy, from improving travel products to giving employees “superpowers.” View the full article

Metrics can tell you if you’re going the right direction or not. They can also be a waste of time if the metrics are noise instead of strong signals. There is no one right answer to which metrics to use, but understanding how others use them can turn on a light bulb for new ideas. We asked our Fast Company Impact Council members what metrics they track obsessively—and why— and the answers we share may have you rethinking your own tracking. 1. CONVERSION AND RETENTION I track a lot of metrics and it’s easy to get lost in the minutiae of the business, but as a subscription business the metrics of conversion and retention are my twin North Stars. What percentage of visitors in trial are going to become paid subscribers, and what percentage of them will remain paid subscribers in three months? Really these metrics are a reflection of the benefit customers get from our products showing they are valuable enough for someone to pay us and that they are valuable enough for them to stick around. Nearly all of the other metrics that I obsessively check flow from these two. — Tony Grimminck, Scribd, Inc. 2. ORGANIC GOOGLE SEARCH I track organic Google search above almost everything. You can buy impressions, but you can’t buy someone typing your brand name unprompted. It’s the cleanest signal of real demand. I also monitor inbound pull—which partners, retailers, or creators are reaching out to us. When serious brands want proximity, it means you’re culturally relevant. If search and inbound drop when spend drops, you’re renting attention, not building equity. And then there’s the quiet test: What happens when we ease off spend? Do we disappear or are we building something worthy of the space we’ve been given? — Emily Kortlang, Yerba Madre 3. EBITDA I track EBITDA because it tells me, without any spin, whether our core business is creating the level of profitability that powers reinvestment and growth for our employee owners. I track labor as a percentage of net revenue, staff churn, and our employee culture index scores because they tell me how efficiently we’re deploying our talent and how engaged our people are in building a career here. — Steven McKay, DLR Group 4. HOW CLIENTS RANK IN AI PROMPTS Right now, we’re obsessively tracking how our clients rank in prompts across ChatGPT, Gemini, and Claude. It’s a new metric for us, but an important one. We want to see how clients show up next to competitors and what narratives or keywords are driving visibility. We layer that with media coverage and domain authority to understand how those stories are performing in the real world. — Kalie Moore, High Vibe PR 5. CONTENT AND PRODUCTS We measure content and products to see how they drive behavior change, build confidence, and turn users into advocates for themselves. Engagement matters, but for us the real signal of success is when people feel empowered to act. As we build for people with real, timely needs, we track both quantitative and qualitative insights to ensure we’re solving the right problems, not guessing. That requires constant testing, learning, and refining. Across industries, leaders have to stay close to the people they serve to ensure they’re truly advancing the mission they set out to achieve. — Nathan Friedman, Understood.org 6. INTERNAL ALIGNMENT AND EXTERNAL TRACTION I track two buckets: internal alignment and external traction. Internally, we run on objectives and key results because it forces clarity. Everyone knows what they’re responsible for and how it ties to business impact. When that breaks, you feel it. When it works, things move fast. Externally, I watch streaming and radio. Streaming shows what’s happening right now, which cities are reacting, whether a record is moving culturally. Radio signals longevity. It’s slower, but it shows real staying power. Together, they tell me if we’re seeing noise or building something durable. You need both. — Logan Mulvey, GoDigital Music 7. CUSTOMER METRICS As CEO, I obsess over daily and weekly metrics like monthly recurring revenue growth, subscription churn, data-plan attach rate, NPS, transmission success rate, and early field reliability (battery life, zero-transmission failures), because recurring revenue powers the business. Any drop in trust kills referrals fast. If customer metrics are healthy so is our business. — Jeff Peel, Tactacam 8. RETENTION AND SAVINGS We track retention of our members, as we offer a lifelong commitment to our C-suite women leaders to provide them with one-on-one peer mentoring for life. This commitment increases our retention to 99%. We also track the mentor/mentee relationship. Lastly, we track our savings, which annually exceed $500,000. — Larraine Segil, Exceptional Women Alliance 9. ENGAGEMENT AND CUSTOMER SATISFACTION We track engagement and customer satisfaction obsessively. For us, engagement isn’t just a usage metric, it’s a signal of trust. When someone actively redeems and returns to our platform, that tells us the experience is resonating. Customer satisfaction is even more important. If people feel valued rather than marketed to, long-term relationships follow—and so does durable revenue for our partners. — Elery Pfeffer, Nift 10. WHERE OUR BUSINESS IS GOING When reviewing metrics, I’m looking for information about where our business is going, not lagging indicators of where we’ve been, and early warning signs of issues that may be developing. For growth, I look at pipeline coverage and conversion. For execution, I review forecast accuracy and time to revenue. For customer value, it’s our net retention rate and advocacy score. Looking at these numbers gives me a good idea of not only how we’re performing, but how efficiently we’re executing and what areas need extra attention. — Steve Holdridge, Dayforce 11. JOBS AND ECONOMICS REPORTS I obsessively track LinkedIn’s Jobs on the Rise reports and LinkedIn’s Economic Graph workforce data and research; they are great reads and provide ongoing snapshots on where the labor market, productivity and future of work are moving broadly. I also track the U.S. Bureau of Labor Statistics’ Productivity and Costs report, to understand where workplace productivity is heading. It’s an excellent dashboard across key indicators and in recent years can be a strong signal on how technology, automation, and operating‑model changes are actually changing worker productivity at scale. — Alice Mann, Mann Partners 12. PROGRESS Progress against the big rocks we established. Setting broad, strategic yet outcome-based goals align the entire organization and drive results. — Michael Tannenbaum, Figure 13. ENGAGEMENT, FRICTION, AND CLIENT IMPACT I think about performance in three pillars: people, process, and product. Some of it is measurable. Some of it you feel. Both matter. On people, I track engagement, retention of top talent, and how often we promote from within. If the bench isn’t deep, nothing scales. On process, I look at friction. How fast do we decide? Is delivery predictable? The best strategy collapses without operational clarity. On product, I focus on client impact, repeat business, and quality. We have a Slack channel devoted to verbatim client praise. Data matters. But when you’re the first call a client makes on their hardest day, that’s the clearest signal of all. — Peter Smart, Fantasy 14. THE FUNNEL For Scribbly, my D2C business, I use every tiny tracking pixel in my funnel. I built a custom dashboard for myself and trained an AI agent to analyze the data just the way I want it—way better than those messy SaaS analytics dashboards that are impossible to decipher. — Lindsey Witmer Collins, WLCM Studio 15. NON-CUMULATIVE DATA Cumulative data is meaningful, but only non-cumulative data holds you accountable. For us, one such metric is how many of the Solvers selected over the past five years are still operational. We’re at 96%. That tells me our selection methods and support programs have a real impact, given that industry averages hover around 70-80%. Something else a company can track is instead of asking “where are you now?” ask “how far have you come?” That’s harder to quantify than dollars raised or media hits, but it’s the only number that tells me whether we’re doing our job. Revenue, employees, money raised—those keep the lights on. But the distance traveled keeps us honest about the mission. — Hala Hanna, MIT Solve 16. BOOMERANGS AND EMPLOYEE DEPARTURES We’ve been focused on people-centric workplace data since we started building a center of gravity for brilliant minds almost three decades ago. We regard the percentage of boomerangs in a company as a leading indicator of having a positive, thriving culture that people value and want to be part of. At the other end of the spectrum, the rate of regrettable departures usually signals when there are culture issues that must be addressed. — Leerom Segal, Klick Health 17. ENGAGEMENT QUALITY, AUDIENCE SENTIMENT, AND BRAND LIFT We prioritize engagement quality, audience sentiment, and brand lift because they tie directly to real business outcomes, not vanity metrics. We trademarked “true human influence” to make influencer marketing more measurable, backing it with proprietary technology and trusted measurement partners to ensure we deliver against brand KPIs. And with AI driving the convergence of creator and affiliate marketing, we can now connect authentic storytelling to commerce at scale. — Ben Jeffries, Influencer View the full article

Over the past decade, I’ve reviewed hundreds of resumes, conducted countless interviews, and led numerous technical tests for SEO candidates. Along the way, I’ve met many exceptional professionals — but I’ve also noticed a recurring pattern of common interview mistakes that can hold even the most talented candidates back. Below are 11 common mistakes I’ve observed in SEO interviews — and how you can easily avoid them. 1. Projecting arrogance instead of confidence Confidence is great! While imposter syndrome is common in SEO, it’s important to maintain realistic confidence in your skills and experience. However, there is a fine line between projecting confidence and appearing arrogant. For example, talk about your successes, such as: Complicated projects you navigated. Great results you achieved. Buy-in you gained. Be clear about what you achieved and how. Show off your theoretical knowledge. Discuss ideas and theories with your interviewer. Don’t assume they will agree with you, though. This can be arrogance. SEO isn’t a “one-size-fits-all” practice. You may have different experiences from your interviewer, leading to different conclusions. This is fine. It happens in SEO all the time. Some people make the mistake of thinking it’s OK to argue and dismiss others’ opinions. This rarely works well in any workplace and can be especially harmful during an interview. When I interview, I look for team players — confident in their knowledge yet humble and open to learning. They embrace new evidence and contribute to discussions that elevate the entire team’s understanding, including their own. If you stray too far into arrogance during an interview, you may come across as difficult to teach or lead and not open to feedback. 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 2. Giving hazy details about projects and successes Interviews are your time to shine. They let you showcase some of your best work. Another mistake I’ve seen in interviews is assuming interviewers can fill in the gaps. Candidates talk about a project or website they have worked on, but fail to convey its significance. They mention website migrations, expecting non-SEO interviewers to understand the complexities involved. They discuss turning around a traffic slump without giving any data. Avoid this. Make sure to give the specifics. There’s a good acronym for constructing interview answers called STAR. It stands for: Situation: What was the issue or opportunity you were facing? Task: What was your role or responsibility in this and the goal you were working toward? Action: What did you do to address the situation? Result: What happened because of your actions? What successes, learnings, or results can you share? Using this method, you may find it easier to hit all the salient points that give the interviewers clarity and perspective. Try to choose examples that have an outcome that you’re proud of or can at least explain what made it fall short. Dig deeper: How to become exceptional at SEO 3. Ignoring the question Candidates sometimes don’t have time to think of an answer to the question or feel they don’t have one. They try to talk around the question and bring it back to something they feel more comfortable discussing. If an interviewer asks, “Talk about a time when you faced a complex website migration and what you did?” or “How would you handle a stakeholder not signing off on your recommendations?” that’s exactly what they want to know. Avoid going off on a tangent and ensure you address the question directly. Often, interviewers have a list of questions they ask each candidate. They may even use these to compare candidates. If you’re not directly answering them, you put yourself at a disadvantage. Instead, take some time to think about the answer. Explain that you want to answer well and need a minute to organize your thoughts. If you don’t have an experience relevant to a question or have not encountered something before, explain that to the interviewer. Tell them you haven’t “migrated a website before,” but mention what you would do in that situation. If you make something up, passing it off as a situation you faced, you risk being exposed. You may be asked for details you can’t provide, or you may realize that a savvy interviewer has been researching the company or website as you talk about it. 4. Not addressing your audience well Building rapport with interviewers is key to a successful interview. Answer their questions clearly so they can recognize your knowledge and experience. To do that well, you need to understand your audience. You should address their questions using the language and tone they are using and gauge their level of SEO knowledge. It may be tempting to impress non-SEO stakeholders with industry jargon, but if they don’t know what it means, they won’t understand the impact of what you’ve done. Similarly, if you’re being interviewed by the head of SEO, relying on jargon or complex-sounding projects without substance can risk being seen as insincere or unqualified. 5. Being disrespectful of the progress of the site(s) If you are talking to another SEO at the company or agency, don’t assume they are negligent in not addressing that JavaScript issue you’ve noticed on their site. Don’t think their SEO approach is basic; there is still an obvious area for expansion. Be respectful. It’s OK to acknowledge that you noticed these issues with their sites, but assume you aren’t telling them anything they don’t already know. Chances are, some procedural or technical blocks are stopping them from fixing it. Enquire about that instead. It will give you some insight into what challenges you may face if you do go on to work there. Dig deeper: What 15 years in enterprise SEO taught me about people, power, and progress 6. Being unprepared for the types of questions asked Interviews are nerve-wracking. It’s understandable if your mind goes blank when asked to share specific examples of your work or knowledge. One of the most frustrating mistakes I see in interviews (and have made myself!) is forgetting the details of the perfect example of a project that would have answered an interviewer’s question. A good way to avoid this is to come prepared with projects or challenges that exemplify some core areas of SEO that you are likely to face in the role. Look at the job listing again and see what experience they hope candidates will have. Given the scope, seniority, and complexity of the sites, consider the situations and tasks you may face in that role. For example, if you are interviewing for a senior technical SEO role, you may want to prepare examples of projects you’ve worked on that included: A challenging crawling, indexing, parsing, or rendering issue. A large, complicated technical SEO project that you needed to gain buy-in from stakeholders for. A sudden drop in traffic or rankings that needed investigation. A website migration that you had a leading role in. If you’re interviewing for an SEO account manager at an agency, you may want to prepare for times when: You had to explain to stakeholders the drop in performance and the planned remedial action. Present an SEO proposal to a group of people with varying SEO literacy and explain how you helped them get on board with the plan. You presented at a client pitch, the work you put into the pitch, and how you onboarded that client. Come prepared with example projects you can adapt. Think of a successful project and how you made it work. Give an example of an unsuccessful project and what you would do differently. This may mean writing notes about these projects and key points, such as tasks and results, to jog your memory. Essentially, you want to have a few well-detailed and thought-out examples that you can adapt using the STAR method on the fly at the interview. Get the newsletter search marketers rely on. See terms. 7. All talk, no substance Waffle. Meandering. Stalling for time out loud. Whatever you want to call it, this is possibly one of the most common mistakes I’ve seen in interviews. Starting to answer the question before knowing what you are going to say. Again, it’s understandable. We feel like we need to answer the question as soon as it is asked. In reality, though, it’s OK to take some time to think it through first. Listen to the question and address that directly. Consider it a school assignment where you get a mark for every point you hit. Structure your answers clearly to help interviewers find the information they’re looking for. Sometimes the waffling comes from a poorly asked question. Perhaps it isn’t entirely clear what the interviewer is asking. Don’t fall into the trap of trying to answer a question you don’t fully understand. It’s OK to ask clarifying questions. If you still don’t have an answer, you can explain that it isn’t something you have encountered or even heard of. However, this gives you something to go away and look into. You could even ask the interviewers what they think about the topic or what they would do in the situation you mentioned. Most interviewers seek team members who are willing to learn and expand their knowledge. In the best case, they will see your willingness to learn and grow from others around you. Worst case, you have another side of SEO or interviewing techniques to study for the next role you apply for. 8. Trying to bribe or threaten interviewers This should go without saying, but I’ve encountered it in interviews before. Don’t threaten or try to bribe your interviewers. It’s highly unlikely that if an interview is going badly, the promise of a link from your friend’s blog to their company’s website will turn it around. Don’t promise them that if they hire you, they will get access to the secrets to your “guaranteed SEO approach” if you have not been able to demonstrate your competency through the questions they’ve asked. Don’t threaten a negative SEO attack on them or their competitors. Avoid suggesting they only wanted to interview you to steal your ideas. Don’t be rude or dishonest. You won’t get the job, and you won’t be kept in the database of possible future candidates. 9. Contacting everyone in the company to get an ‘in’ Another mistake I’ve seen is a candidate getting too enthusiastic about standing out from the crowd. In doing so, they contact anyone in the company they can to make themselves known. It’s great to show that you are interested in the company and the role. If the interviewers have said it’s OK for you to contact them after the interview, it is absolutely fine. However, be considerate when contacting interviewers outside the interview process. It may come across as keen, but do it too much, and it can become difficult for people to respond, especially if they aren’t directly involved in the interviewing process. Follow up sparingly and with the right people, but be mindful of how busy interviewers are when running hiring processes. Your keen attitude may be too much if it’s not appropriate. 10. Being dishonest about your level of involvement in the project Be truthful about your level of involvement in a project. Don’t claim you worked on a project just because it happened at your agency at the same time you were working there. As soon as interviewers start asking in-depth questions about the project, your lack of knowledge will be apparent. Instead of it sounding impressive, you’ll come across as lacking knowledge and depth in your answer. Focus your answers on the impact that you had on a project. Talk to what others did and how it fit into the whole approach, but don’t take credit for their work. This is important because interviewers want to know where your competencies lie. It’s OK to talk about what you learned from others during the project and how you might use that insight in future work. It isn’t OK to claim that it was your idea when it wasn’t. Dig deeper: 8 tips for SEO newbies 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 11. Giving ‘Google lies’ as an answer to an interview question This is an SEO-specific interview mistake. Unfortunately, it’s quite common. I see it often during technical portions of interviews. When candidates are asked to think through how they would approach a situation, or explain why an approach may not work. They don’t necessarily know why Google ignored a canonical tag. Or why a page that is blocked in the robots.txt is still indexed. So they panic and start blaming Google for lying about its practices and bot behavior. I’ve heard a lot of sweeping statements during interviews about how you can’t believe Google spokespeople. How they outright lie to us to disguise how the bot and algorithm mechanisms work. Whether you agree with those statements or not, they are a poor way to get around not knowing the answer to a technical question. If you don’t know why a page has been indexed even though it is blocked in the robots.txt, the answer isn’t to claim “Google ignores the robots.txt and just says they don’t.” Yes, the SEO world is full of conspiracy theories and genuine questions about the integrity of the industry’s larger players. It’s good to question the status quo through experiments and thought exercises. However, the better way to approach an interview question like that would be to think around the issue. Let’s assume Google isn’t lying — what could be the reasons the page has been indexed despite being blocked in the robots.txt? If you start your interview answers from a place of assuming there is a logical answer to them, you are more likely to get to the right conclusions. This is a much better way of approaching SEO in general, rather than assuming you’re being lied to! Ace your SEO interview and leave a lasting impression By avoiding these common mistakes, you can present yourself as a confident, prepared, and team-oriented candidate. With the right approach, you’ll be better positioned to impress interviewers and land your next SEO role. View the full article

Iran has shown that control of the strait gives it a stranglehold over the world economyView the full article

Agricultural data is “fragmented, distributed, heterogeneous, and incompatible.” That’s the verdict from a major Council for Agricultural Science and Technology report published barely a year ago, and it helps explain why AI has struggled to gain traction on farms. Other data-heavy industries, like healthcare or financial services, have established data standards, but agriculture has no universal framework for translating between the dozens of systems that generate field-level information. This isn’t a new observation, but its persistence is noteworthy. While consumer tech and enterprise software largely solved their interoperability challenges years ago, agriculture still generates enormous volumes of information trapped in incompatible silos. Research institutions publish trial results in inconsistent formats, product manufacturers use proprietary naming systems, farmers record observations with local terminology and retailers track sales without connecting them to agronomic outcomes. The result is an industry sitting on massive amounts of information it can barely use. “Agriculture doesn’t have a data problem—it has an intelligence problem,” notes Ron Baruchi, CEO of Agmatix, a company building domain-specific AI for the sector. “The data exists. What’s missing is infrastructure that understands what it means.” According to a McKinsey report, implementing data integration, and connectivity in agriculture could add $500 billion in value to global GDP—a 7 to 9% improvement over current projections. But capturing that value requires solving a problem that general-purpose AI platforms have consistently struggled with. WHY HORIZONTAL AI KEEPS FAILING IN FARMS The appeal of applying large language models to agriculture is obvious: A farmer could describe what’s happening in their field and get instant advice on what to do about it, without hiring a consultant or having to wait for a lab. But agriculture’s complexity breaks the approach. While an LLM trained on internet text might know that nitrogen helps plants grow, it can’t tell you that the right amount changes depending on the growth stage, the soil and what was planted in the same field the previous year. Similarly, computer vision can identify crop stress, but without contextual knowledge of weather, soil and product applications, that insight doesn’t mean much. You can ask ChatGPT about nitrogen fertilization and get an answer that sounds authoritative. But when you dig into specifics—timing for your soil type, interactions with your previous crop, and product selection based on local availability—the recommendations fall apart. The same CAST report reinforces this point, noting that many farmers distrust AI because of its “black box” nature—models making predictions without clear explanations behind them. In farming, 90% accuracy on a fungicide recommendation means 10% of the time you’re telling a grower to spray the wrong product at the wrong time. BUILDING INTELLIGENCE FROM THE GROUND UP This is where a growing number of companies are taking a different approach—building AI systems designed specifically for agriculture rather than retrofitting general-purpose tools. For example, India-based Cropin, backed by Google, has constructed its own crop knowledge graph spanning 500 crops across 103 countries and recently developed an agriculture-specific micro-language model. Israeli-American startup Agmatix built its own agricultural intelligence system from the ground up—an approach that mirrors, in concept, what Palantir did for defense and intelligence data. The core of that system is what Agmatix calls “pre-trained ontologies”: Frameworks that encode agricultural relationships before customer data enters the system. Agmatix’s AI engine uses a neuro-symbolic architecture, combining structured knowledge graphs with machine learning. Agricultural relationships—how specific fertilizers interact with specific soils at specific growth stages—are encoded by agronomists, validated through field trials and refined continuously. What that means, essentially, is that the AI doesn’t start from scratch. Before it touches any farm’s data, agronomists have already taught it how agriculture works—which fertilizers affect which soils, how a crop’s needs change as it grows, and why what was planted last season matters for what’s planted next. According to the company, the system has structured more than 1.5 billion field trial data points, creating what data scientists call “semantic interoperability”: The ability to translate between different data sources because the system understands what the data means, not just what it says. But building better technology doesn’t guarantee adoption. McKinsey partner Vasanth Ganesan noted in the firm’s 2024 Global Farmer Insights survey that farmers are “demanding clearer ROI, lower cost of implementation and maintenance and easier-to-setup technologies”—complaints shaped by years of agtech tools that overpromised and underdelivered. A separate McKinsey analysis found that poor user experiences continue to hold back adoption across the sector. Baruchi says farmers have good reason to be cautious. “Farmers are CEOs operating in one of the most unpredictable industries on earth,” he tells Fast Company. “They balance biological systems, financial risk and environmental volatility every single season. The ROI question is only hard to answer when your platform can’t connect what a grower applies to what actually happens in the field.” WHERE IT’S WORKING The approach is already operating across several deployments. BASF has collaborated with Agmatix on digital tools for crop disease detection, including a recently announced project targeting soybean cyst nematode. The company says growers using its prediction platform have reduced fungicide costs by 15 to 20% while maintaining disease control. Its engine is also powering predictive disease-risk modeling in large-scale row-crop systems in the United States. A national agriculture ministry uses the system to model policy impacts before implementation. On the sustainability front, Agmatix’s RegenIQ platform works with major food and beverage companies to assess which regenerative practices deliver measurable results in specific field conditions—classifying, for instance, Brazil’s 150 coffee-growing localities into six distinct climate clusters, each requiring different approaches. Cropin, meanwhile, partnered with Walmart in March 2025 to optimize fresh produce sourcing across U.S. and South American markets using AI-driven yield forecasting and crop health monitoring. THE HARD PART REMAINS Agmatix represents a broader shift from horizontal AI platforms toward domain-specific solutions. But it isn’t the only company betting that agriculture needs its own AI. John Deere’s acquisition of aerial analytics firm Sentera in May 2025 suggests the industry’s biggest players have reached the same conclusion. The AI in agriculture market is projected to grow from $2.55 billion in 2025 to over $7 billion by 2030, according to Mordor Intelligence. But adoption remains uneven, with 81% of large farms showing willingness to adopt AI, while only 36% of smaller operations plan to do the same. Agricultural AI adoption is still slow by any standard, and it’s not hard to see why. CAST’s report catalogs the major barriers that agriculture still faces today: High costs, limited rural broadband, insufficient training and unresolved questions about data ownership. These challenges intensify in an industry previously plagued by overhyped technology promises. But the tailwinds are real. Major food companies have made commitments to decarbonize supply chains that are impossible to fulfill without field-level data. Climate volatility is making predictive tools more valuable. And a decline in U.S. public agricultural R&D spending — down roughly a third from its 2002 peak, according to USDA data — is creating a vacuum that private-sector platforms are positioned to fill. The question isn’t whether agriculture needs better data infrastructure. It’s whether the companies building it can survive farming’s patient adoption timelines long enough to reach critical mass and whether the benefits will extend beyond the largest farms that can already afford to invest. For an industry responsible for feeding 8 billion people, getting that balance right matters enormously. View the full article

Davidson Kempner’s Tony Yoseloff warns a substantial portion of PE firms are already “stressed or distressed”View the full article

Are you watching your team’s creative operations buckle under mounting pressure? You’re not alone. As project complexity skyrockets and client demands intensify, creative leaders face an unprecedented challenge: scaling operations without sacrificing quality or burning out teams. The solution isn’t working harder, rather, it’s working smarter with technology that transforms your entire content lifecycle. Here’s how forward-thinking creative operations leaders are building resilient, scalable workflows that thrive in 2025’s demanding landscape. The perfect storm facing creative operations Creative teams are caught in a maelstrom of expectations and pressures. Research shows that 77% of marketing teams report increased project volume year-over-year, while 45% struggle to keep up with increasing content demands for various channels. Meanwhile, client expectations for faster turnarounds and higher-quality output continue unabated. Consider this scenario: Your team juggles 15 active campaigns across multiple channels, each requiring dozens of asset variations. Reviews pile up in email threads, designers waste hours hunting for approved brand elements and project managers lose visibility into actual campaign progress. This chaos isn’t just frustrating, it’s expensive. Teams spending excessive time on administrative tasks rather than creative work see productivity drop by up to 40%. Why traditional approaches fall short Many creative leaders attempt to solve these challenges by adding headcount, or by implementing rigid processes that chafe at the creative drives of artists and designers. But throwing additional resources at systemic problems isn’t a guaranteed fix. For many teams, the real issue lies in disconnected workflows and siloed tools. When your creative software doesn’t communicate with your project management system, and your digital asset management exists in isolation from approval processes, you’re fighting an uphill battle against inefficiency. What you need is an integrated marketing and creative ecosystem that connects every stage of your content lifecycle. The technology stack that transforms operations Digital asset management: Your content foundation Modern digital asset management (DAM) systems serve as the central nervous system, the single source of truth for creative operations. But not all DAM platforms are created equal. Look for platforms that offer: Intelligent organization and search: AI-powered search, tagging and categorization features that make finding assets easy for all users, not just admins. Version control: Automatic tracking of asset iterations with clear approval status, as well as automated sunsetting features. Brand compliance: The importance of brand compliance can’t be overstated. Consistent branding across all platforms can increase revenue by 23%. Built-in style guides and templating tools can prevent off-brand content. Global accessibility: Cloud-based access and multi-language capabilities that support distributed teams and external partners. Seamless creative tool integration Your designers live in Adobe Creative Cloud, Figma and Canva, but the briefing and project data for your campaigns live elsewhere. This disconnect creates unnecessary friction and increases time to market. Advanced integrations between platforms should bridge this gap by: Embedding project context: Bringing project briefs, deadlines, task assignments and feedback directly into creative applications. Automating file management: Syncing creative files with project management systems without manual intervention. Intelligent approval workflows Traditional approval processes rely on email chains and manual tracking. Modern workflow automation transforms this chaotic process by: Dynamic routing: Automatically sending assets to the right reviewers based on project type and complexity. Parallel reviews: Enabling simultaneous review by multiple stakeholders to compress timelines. Contextual feedback: Providing annotation tools that eliminate ambiguous comments. Escalation management: Automatically flagging delayed approvals to prevent bottlenecks. Project management that actually manages Generic project management tools often fail creative teams because they don’t resonate with creative workflows. Purpose-built solutions offer: Creative-specific templates: Pre-configured workflows for common project types. Resource planning: Visual capacity management that prevents team overload. Real-time collaboration: Integrated communication that keeps discussions contextual. Performance analytics: Insights into team efficiency and project profitability. Building scalable workflows: A strategic approach Start with process mapping Before implementing technology, map your current content lifecycle. Identify every touchpoint from initial brief to final delivery. Where do assets get stuck? Which handoffs create delays? This analysis reveals your biggest pain points and prioritizes technology investments. Implement incrementally Don’t attempt a complete overhaul overnight. Start with your biggest bottleneck — often asset management or approval workflows. Success with one component builds momentum and buy-in for broader transformation. Design for scale from day one As you implement new systems, design workflows that can handle 3x your current volume. This forward-thinking approach prevents future growing pains and ensures your technology investment pays long-term dividends. Measure everything Establish baseline metrics for key performance indicators: Asset request fulfillment time. Project completion rates. Review cycle duration. Team utilization rates. Track these metrics throughout your technology implementation to demonstrate ROI and identify areas for continued optimization. The human element: Change management for creative teams Technology alone doesn’t transform operations — people do. Successful implementations require careful change management: Involve your team: Include designers and project managers in technology selection and workflow design. Provide comprehensive training: Invest in proper onboarding that goes beyond basic functionality. Create champions: Identify early adopters who can mentor others and troubleshoot issues. Iterate based on feedback: Regularly gather input and adjust workflows based on real-world usage. Looking ahead: The future of creative operations The most successful creative operations leaders aren’t just solving today’s problems — they’re preparing for tomorrow’s opportunities. Emerging technologies like AI-powered content generation and predictive project planning will further transform creative workflows. Organizations that build flexible, integrated technology stacks now position themselves to rapidly adopt these innovations. Those stuck with legacy systems and manual processes will find themselves increasingly left behind. Your next steps The question isn’t whether to modernize your creative operations technology — it’s how quickly you can begin. Start by auditing your current tools and identifying the biggest gaps in your workflow integration. Consider piloting a comprehensive digital asset management solution that integrates with your existing creative tools. Look for platforms offering robust approval workflows and project management capabilities that can scale with your growth. Remember: every day you wait, your competition gains ground. The creative operations leaders who act decisively today will define the industry standards of tomorrow. Are you ready to transform your creative operations from a bottleneck into a competitive advantage? The technology exists — now it’s time to implement it strategically and watch your team’s potential unfold. View the full article

Hello and welcome to Modern CEO! I’m Stephanie Mehta, CEO and chief content officer of Mansueto Ventures. Each week this newsletter explores inclusive approaches to leadership drawn from conversations with executives and entrepreneurs, and from the pages of Inc. and Fast Company. If you received this newsletter from a friend, you can sign up to get it yourself every Monday morning. Last week’s Modern CEO made the case that boards and recruiters should stop focusing on CEO candidates’ résumés and start evaluating their potential for agility. That said, one aspect of work history can serve as a good proxy for the ability to manage uncertainty and change: international experience. “Leaders who have global exposure tend to develop sharper instincts for adapting in different contexts, taking in information effectively, and making business decisions based on these different inputs,” says Jeff Sanders, vice chair and co-managing partner of the global CEO & Board of Directors Practice for Heidrick & Struggles. New research from the executive search firm shows that one in five Fortune 500 companies—the largest enterprises in the U.S. by revenue—appointed CEOs with cross-border experience in 2025. More than a third of external candidates named to the top job last year worked internationally. “They’ve already had to respond to complexity in real time—and that kind of experience becomes increasingly valuable as global conditions continue to evolve and shift,” Sanders adds. Charting new territory Ariane Gorin, CEO of Expedia Group, credits her global experience with helping to shape her leadership style. Gorin spent 23 years in Europe: 13 years in Paris and 10 years in London, where she held several senior positions at Expedia before becoming CEO of the Seattle-based travel technology company in May 2024. “The biggest thing is you’re out of your comfort zone,” she says of working abroad. Gorin, who is fluent in French, notes that speaking a language is different than doing business with others in that language. “You’re just always a little bit uncomfortable,” she says, adding: “It also forces you to listen more.” Working abroad also fosters empathy, another quality recruiters call out as a trait they seek in future CEOs: “I spent my first 11 years at Expedia in Europe [working with colleagues in America], and I will never forget what it feels like to be the only one who’s on the late-night calls,” Gorin recalls. Perhaps not surprising for a CEO whose company facilitates travel, Gorin also believes in the importance of geographic diversity in her leadership team. The president of Expedia Group B2B is based in Madrid, and the chief commercial officer is in London. “I think if your leadership team is all in the same place, it certainly makes it easier to get things done, but you can start to have a myopic view,” she says. Expanding horizons As technological and geopolitical complexities become the norm in business, leaders with international experience often have real-world experience managing disruptions to supply chains, strategy, and talent, says Heidrick & Struggles’s Sanders. Gorin’s agility is getting put to the test as the travel industry is feeling the impact of the U.S.–Israel attacks on Iran launched last month, and artificial intelligence continues to transform tech companies. During Gorin’s time as CEO, the company has expanded its use of artificial intelligence (AI) to assist travelers and featured partners like hotels, airlines, and car rental companies. (It was early to embed the Expedia app into OpenAI’s ChatGPT chatbot.) The Expedia Group, whose flagship brands include Expedia, Vrbo, and Hotels.com, last year posted revenue of $14.7 billion, up 8% from 2024. Regardless of whether an executive secures an international posting, Gorin believes travel to other countries is critical to understanding global business. When she stepped into her previous role running Expedia’s business-to-business (B2B) unit, she embarked on a two-week trip around the world, meeting clients in Japan, Korea, Australia, and the U.S.—a journey that helped her appreciate the business and cultural nuances of each market. Gorin also makes a case that travel can open the mind. She says: “Getting out of your day-to-day into a new environment jogs a lot of creativity.” Working a world away Are you an executive who has worked internationally, and if so, how did that experience shape the way you lead and think? Did it make you more agile? How? Send your stories to me at stephaniemehta@mansueto.com. I’ll publish the best examples in a future newsletter. Read more: global business Honeywell CEO’s leadership style is shaped by his time in the field The Most Innovative Companies in Asia-Pacific When Starwood’s CEO moved his leadership team to China View the full article

I’ve been studying the intersection of digital technology and office work for quite some time. (I find it hard to believe that my book, ​Deep Work​, just passed its ten-year anniversary!?) Here’s a pattern I’ve observed again and again: A new technology promises to speed up some annoying aspects of our jobs. Everyone gets excited about freeing up more time for deep work and leisure. We end up busier than before without producing more of the high-value output that actually moves the needle. This happened with the front-office IT revolution, and email, and mobile computing, and once again with video-conferencing. I’m now starting to fear that we’re beginning to encounter the same thing with AI as well. My worries were stoked, in part, by a recent article in the Wall Street Journal, titled ​“AI Isn’t Lightening Workloads. It’s Making Them More Intense.”​ The piece cites new research from the software company ActivTrak, which analyzed the digital activity of 164,000 workers across more than 1,000 employers. What makes the study notable is its methodology: it tracked individual AI users for 180 days before and after they began using these tools, providing clear insight into what changed. The results? “ActivTrak found AI intensified activity across nearly every category: The time they spent on email, messaging and chat apps more than doubled, while their use of business-management tools, such as human-resources or accounting software, rose 94%.“ The one category where activity was not intensified, however, was deep work: “[T]he amount of time AI users devoted to focused, uninterrupted work—the kind of concentration often required for figuring out complex problems, writing formulas, creating and strategizing—fell 9%, compared with nearly no change for nonusers.” This is a worst-case scenario: you work faster and harder, but mainly on shallow, mentally taxing tasks (because of all the context shifting they require) that only indirectly help the bottom line compared to harder efforts. It’s not quite clear why AI tools are having this impact. One tantalizing clue, however, comes from Berkeley professor Aruna Ranganathan, who is quoted in the article saying: “AI makes additional tasks feel easy and accessible, creating a sense of momentum.” This points toward a pattern similar to what happened when email first arrived. It was undeniably true that sending emails was more efficient than wrangling fax machines and voicemail. But once workers gained access to low-friction communication, they transformed their days into a furious flurry of back-and-forth messaging that felt “productive” in the ​abstract, activity-centric sense​ of that term, but ultimately hurt almost every other aspect of their jobs and ​made everyone miserable​. AI tools might be replicating this dynamic with small, self-contained tasks. Users are now furiously bouncing ideas back and forth with chatbots, iteratively refining text and generating drafts of memos and slide decks that are often ​too sloppy ​to be useful. If they’re particularly tech savvy, perhaps they’re even monitoring the efforts of agent swarms deployed to parallelize such efforts even further. Once again, this all seems “productive” in the sense that these individual tasks appear to be happening faster, and activity seems intensified overall. But are we sure we’re accelerating the right parts of our jobs? I Need Your Help I’m working on an article for a major publication about the move toward simple, high-friction, single-use technologies like the ​Tin Can phone​. If you have a Tin Can phone/are on the waiting list, or have recently embraced similar retro technologies, and are willing to talk, please send me an email at ​podcast@calnewport.com​. I want to hear about your motivations and experience! AI Reality Check: Is Claude Conscious? If you were following AI news last week, you might have noticed a barrage of concerning headlines about Anthropic’s Claude LLM, including: ​“Anthropic CEO Says Company No Longer Sure Whether Claude is Conscious.”​ ​“Is AI Assistant Claude Conscious – and Suffering from Anxiety?”​ ​“Is Claude Conscious? Anthropic CEO Says Possibility Can’t Be Ruled Out”​ Here’s what happened. Anthropic infamously puts outlandish warnings and observations in their release notes for their new models because, I suppose, they think it makes them look more safety-aware and responsible (e.g., their classic ​AI blackmail farce​). True to form, in the notes accompanying the recent release of Opus 4.6, they wrote that the model “expresses occasional discomfort with the experience of being a product” and would “assign itself a 15 to 20 percent probability of being conscious under a variety of prompting circumstances.” That last part is key. With the right prompts, you can induce an LLM to describe itself as anything you want. Remember: the goal of LLMs is to complete whatever story they’re provided as input. If you wind a model up – even subtly – to write a story from the perspective of being a conscious AI, it will oblige. Anyway, in ​a recent interview​, Ross Douthat asked Anthropic CEO Dario Amodei about this particular release note. Amodei answered, in part, by saying: “We don’t know if the models are conscious. We are not even sure that we know what it would mean for a model to be conscious or whether a model can be conscious. But we’re open to the idea that it could be.” Of course, you could say the same thing about a vacuum cleaner. It’s a non-answer containing no actual information or testable claims. But, the internet being the internet, ran with it. Sigh. The post Why Hasn’t AI Made Work Easier? appeared first on Cal Newport. View the full article

I’ve been studying the intersection of digital technology and office work for quite some time. (I find it hard to believe that my book, ​Deep Work​, just passed its ten-year anniversary!?) Here’s a pattern I’ve observed again and again: A new technology promises to speed up some annoying aspects of our jobs. Everyone gets excited about freeing up more time for deep work and leisure. We end up busier than before without producing more of the high-value output that actually moves the needle. This happened with the front-office IT revolution, and email, and mobile computing, and once again with video-conferencing. I’m now starting to fear that we’re beginning to encounter the same thing with AI as well. My worries were stoked, in part, by a recent article in the Wall Street Journal, titled ​“AI Isn’t Lightening Workloads. It’s Making Them More Intense.”​ The piece cites new research from the software company ActivTrak, which analyzed the digital activity of 164,000 workers across more than 1,000 employers. What makes the study notable is its methodology: it tracked individual AI users for 180 days before and after they began using these tools, providing clear insight into what changed. The results? “ActivTrak found AI intensified activity across nearly every category: The time they spent on email, messaging and chat apps more than doubled, while their use of business-management tools, such as human-resources or accounting software, rose 94%.“ The one category where activity was not intensified, however, was deep work: “[T]he amount of time AI users devoted to focused, uninterrupted work—the kind of concentration often required for figuring out complex problems, writing formulas, creating and strategizing—fell 9%, compared with nearly no change for nonusers.” This is a worst-case scenario: you work faster and harder, but mainly on shallow, mentally taxing tasks (because of all the context shifting they require) that only indirectly help the bottom line compared to harder efforts. It’s not quite clear why AI tools are having this impact. One tantalizing clue, however, comes from Berkeley professor Aruna Ranganathan, who is quoted in the article saying: “AI makes additional tasks feel easy and accessible, creating a sense of momentum.” This points toward a pattern similar to what happened when email first arrived. It was undeniably true that sending emails was more efficient than wrangling fax machines and voicemail. But once workers gained access to low-friction communication, they transformed their days into a furious flurry of back-and-forth messaging that felt “productive” in the ​abstract, activity-centric sense​ of that term, but ultimately hurt almost every other aspect of their jobs and ​made everyone miserable​. AI tools might be replicating this dynamic with small, self-contained tasks. Users are now furiously bouncing ideas back and forth with chatbots, iteratively refining text and generating drafts of memos and slide decks that are often ​too sloppy ​to be useful. If they’re particularly tech savvy, perhaps they’re even monitoring the efforts of agent swarms deployed to parallelize such efforts even further. Once again, this all seems “productive” in the sense that these individual tasks appear to be happening faster, and activity seems intensified overall. But are we sure we’re accelerating the right parts of our jobs? I Need Your Help I’m working on an article for a major publication about the move toward simple, high-friction, single-use technologies like the ​Tin Can phone​. If you have a Tin Can phone/are on the waiting list, or have recently embraced similar retro technologies, and are willing to talk, please send me an email at ​podcast@calnewport.com​. I want to hear about your motivations and experience! AI Reality Check: Is Claude Conscious? If you were following AI news last week, you might have noticed a barrage of concerning headlines about Anthropic’s Claude LLM, including: ​“Anthropic CEO Says Company No Longer Sure Whether Claude is Conscious.”​ ​“Is AI Assistant Claude Conscious – and Suffering from Anxiety?”​ ​“Is Claude Conscious? Anthropic CEO Says Possibility Can’t Be Ruled Out”​ Here’s what happened. Anthropic infamously puts outlandish warnings and observations in their release notes for their new models because, I suppose, they think it makes them look more safety-aware and responsible (e.g., their classic ​AI blackmail farce​). True to form, in the notes accompanying the recent release of Opus 4.6, they wrote that the model “expresses occasional discomfort with the experience of being a product” and would “assign itself a 15 to 20 percent probability of being conscious under a variety of prompting circumstances.” That last part is key. With the right prompts, you can induce an LLM to describe itself as anything you want. Remember: the goal of LLMs is to complete whatever story they’re provided as input. If you wind a model up – even subtly – to write a story from the perspective of being a conscious AI, it will oblige. Anyway, in ​a recent interview​, Ross Douthat asked Anthropic CEO Dario Amodei about this particular release note. Amodei answered, in part, by saying: “We don’t know if the models are conscious. We are not even sure that we know what it would mean for a model to be conscious or whether a model can be conscious. But we’re open to the idea that it could be.” Of course, you could say the same thing about a vacuum cleaner. It’s a non-answer containing no actual information or testable claims. But, the internet being the internet, ran with it. Sigh. The post Why Hasn’t AI Made Work Easier? appeared first on Cal Newport. View the full article

Every organization that produced an Epstein-related villain once called him a leader. Peter Attia. Larry Summers. The head of the World Economic Forum. HR statements issued. Leadership transitions announced. The story told as if it’s over. It isn’t. Not for the women inside those organizations, who are right now having a single quiet thought: Ah. That explains everything I’ve experienced. The subtle dismissals. The closed doors. The invitations that never came. The jokes that weren’t funny but nobody challenged them. The way one man’s voice filled the room and everyone else just . . . made room. And not for the rest of us—because the real scandal isn’t what these powerful men did. It’s what we accept as normal that made it possible. We didn’t build this city. We inherited it. And until we see how it confines us, we’ll keep calling it home. If you’re a leader—or in HR, or in communications drafting the familiar “we take this seriously” memo—the real question isn’t What did he do? The real question is What did we normalize? Here are three places to look. Entitlement: The Monologue Someone arrives at a meeting where the agenda has been planned for weeks. They take the floor and slip into a monologue—a story about their cab driver, a stray shower thought—and just like that, the shared agenda vanishes. And the room lets it happen. Whatever, he’s just doing his thing. But monologues aren’t harmless. They’re a quiet power play. They hijack the room. They take all the oxygen as if no one else needs any. Every time we let a monologue run, we trade what we could have made together for one person’s need to feel important. Monologue cultures don’t just reward the person taking up space—they teach everyone else in the room to compress themselves into the tiny amount of area that’s left. They make dissent feel risky. And eventually, they teach the room that one, and only one, voice matters. Control: The Data Demand This one sounds responsible. Analytical. Rational. But in practice, demanding data before considering an idea is how you control what gets considered at all. Quantitative data is inherently backward-looking. To build what comes next, we have to explore the quality of ideas, develop insights, and tap imagination. If you require solid, confirmable data before entertaining anything new, every new idea gets killed before it breathes. It’s also a dog whistle. When we define intelligence as purely rational and severed from emotion—strictly intellectual, detached from intuition—we don’t just narrow the definition. We narrow ourselves. We strip the team’s intelligence of its full power, reducing it to something cold, calculable, and incomplete. The narrowness, it turns out, is very convenient for the people who already control what gets measured. Denial: The Label When someone brings up something uncomfortable, the easiest response isn’t to investigate the issue. It’s to label the person. Too demanding. Too sensitive. Too negative. Too emotional. Not a team player. Labeling people as the problem is how defensive people go on the offense. The moment the messenger becomes the issue, the actual problem disappears. No investigation needed. No change required. In fact, research shows that if you just call someone emotional, not only will everyone in the room discount what they say, but the speaker will too. The system stays intact. Which is, of course, the point. Dozens of norms These are three norms. But there are 21 more just like them. I’ve spent years studying what stops us from doing our best work—and found 24 specific, concrete norms that, in both subtle and significant ways, keep us stuck. I write about them in my new book, Our Best Work: Break Free From the 24 Invisible Norms That Limit Us. When I share this, people almost always ask me to simplify it. To reduce the list to something smaller. I get it; 10 would be more manageable. But we miss a lot when we oversimplify things. It’s like looking at just part of a cage and wondering why the animal inside doesn’t escape. If you studied any one wire, up and down its length, you might believe the animal could simply push past. If you see just some of the wires, you’d wonder if the beast actually wants to stay where it is. But until you see the whole, you miss the point. And that’s when it hits you—how the wild thing is fully ensnared. Caged. Trapped. Not because it chooses to be. Not because it lacks power. And certainly not because it doesn’t try hard enough to escape. The power of these norms isn’t how persuasive they are. It’s how persistent they are. It’s not just one, five, or ten things that trap us in place—it’s the way those things intertwine and twist together, a tangled network of systematically related barriers. It is their relationships to each other that make the seemingly lightweight barriers as confining as a cage. Our complicity So many of us shrug at the monologues. We kludge together data when asked, even when we know it’s the wrong question. We stay quiet, go along, get along—hoping to affect change without ruffling feathers. And we become complicit in our own oppression—limiting our own freedom without ever seeing the bars we built. This is how a cage works. We don’t see the bars. We just find ourselves not going certain places, not saying certain things, not becoming certain people. And we tell ourselves that’s just how it is. By allowing entitlement, control, and denial to be acceptable, we create an operating system that makes the Epstein Island visitors feel right at home. We participate in it. We perpetuate it. Things will change only when we name what’s limiting us all. Not the villains—the norms. Their own institution Meanwhile, founders like Bill Gates, Elon Musk, Peter Thiel, Reid Hoffman, and Casey Wasserman largely remain in place. They are, in effect, their own institution—controlling the companies, capital, and networks around them so the usual mechanisms of social accountability never quite apply. We pushed out the ones we could reach. And called it done. But here’s the harder question—the one that actually leads somewhere: What are we still normalizing that will grow the next set of villains we call leaders? The cage doesn’t care which warden is in charge. It comes down only when we stop building it. View the full article

The route for the Freedom 250 Grand Prix, the first-ever street race on the National Mall planned for August, was drawn to pass as many tourist attractions as possible, in a part of town that’s dense with them. In renderings, the route looks like something out of a race car arcade game, with cars whizzing past unmistakable U.S. monuments and Smithsonian museums. It’s an unlikely sight for a city whose standard speed limit is 20 mph (NNT IndyCar Series cars can reach speeds exceeding 200 miles per hour). The 1.7-mile circuit opens with a front stretch along Pennsylvania Avenue by the U.S. Capitol and heads northwest past the National Gallery of Art and Canada’s U.S. Embassy where cars can get the most speed. The circuit then takes a sharp left turn after the National Archives and cuts south through the National Mall at 7th Street, giving viewers there backdrops of race featuring the Capitol or the Washington Monument. After passing between the Hirshhorn Museum and the Smithsonian Air and Space Museum, it then takes a left at Independence Avenue and heads back towards the Capitol. The pit lane is located on Pennsylvania Avenue. “The circuit is unlike any other street race we’ve seen,” back-to-back Indianapolis 500 winner Josef Newgarden said in a statement after touring it Monday. “Racing through the heart of American history, with those amazing landmarks lining the course, is going to be incredibly powerful.” The route was announced Monday by NNT IndyCar Series, the open-wheel car racing body that runs the Indianapolis 500. The race is being put on in partnership with Monumental Sports & Entertainment, which owns the region’s NBA, NHL, and WNBA teams, and will be aired nationally live on Fox. Open-wheel racing has found new audiences in the U.S. with the growing popularity of F1, while the Las Vegas Grand Prix, first held in 2023, showed the possibilities of street circuit in an iconic U.S. city with recognizable landmarks. Whereas the Las Vegas race was closed from public view, in D.C., the Freedom 250 Grand Prix will be open for anyone to watch, fitting for a race in which cars will zoom between Smithsonian museums famously known for their free admission. President Donald The President established the race in January with an executive order, and it’s part of Freedom 250, the public-private initiative the The President administration created to mark America’s semiquincentennial, independent of the bipartisan America250. Freedom 250’s plans predictably center the president in the festivities and offer him a chance to shape programming for the anniversary around his tastes and base, like with the MMA fight being planned for the White House lawn. An IndyCar race through Washington, D.C., also fits the bill. An official promotional video for the race showed animated video of The President on Marine One before any race cars appear on screen. Still, the race has found at least some bipartisan appeal locally, even if it’s just for tourism’s sake. Washington’s Democratic Mayor Muriel Bowser welcomed visitors to “plan their trips to D.C. now” for the race and invited them to stay to enjoy the monuments and museums up close themselves. View the full article

A new short film premiered at SXSW over the weekend, written and directed by Jeff Nichols (Mud, The Bikeriders) starring Oscar nominee Michael Shannon, Oscar-winning singer/songwriter Ryan Bingham, Hassie Harrison, and narrated by Oscar winner Sissy Spacek. Love Letter to Texas is a 12-minute story of personal reinvention, and a beautiful visual tribute to some of the Lone Star state’s most photogenic and iconic backdrops in film history. It’s also Tecovas ad, bankrolled and produced by the Western apparel and cowboy boot brand. Founded in 2015, Tecovas is a new brand in a category steeped in heritage. It began as the “Warby Parker of Boots” but has since opened 56 stores around the U.S., including in New York City and Boston. In 2024 the company surpassed $250 million in revenue, and expected to pass the $300 million mark in 2025. Tecovas vice-president of brand marketing Samantha Fodrowski says Love Letter to Texas represents the brand’s ambition to show people it puts the same amount of care and attention to detail into its content as it does its cowboy boots. ​​”We want to be known as a brand that really is investing in craft,” says Fodrowski. “If that’s something that people start to recognize and associate with Tecovas, that’s a win for us. It has nothing to do with selling products. It’s about how we’re making that first introduction.” If this film is any indication, it’ll be a helluva ride. Love Letter High profile brand entertainment has hit the mainstream, with projects like the unprecedented deal struck between AB InBev and Netflix, WhatsApp working with Modern Arts on a Netflix doc about the Mercedes F1 team, to Dick’s Sporting Goods formally establishing an internal entertainment studio. But smaller brands, like Huckberry, are also making shrewd investments in longer form content. It really should come as no surprise that Tecovas is investing in longer form brand content, considering it brought on Scott Ballew as its vice-president of creative in 2024, after Ballew led Yeti’s film and content work for more than a decade. His first piece of work for Tecovas was “True West,” a brand manifesto of sorts, both visually and in its script. Directed by Ballew, narrator artist Terry Allen says, “The true west has no fences. There’s an edge, but you got to find it.” As artful shots of open spaces, horses, and running trains, which Ballew describes as a Texas fever dream, it ends with Allen saying, “Now, we might not need more people in the West, but would it hurt to have a little more west in the people?” The spot ran in limited markets over 2025, but the brand then decided to put it on Peacock for the Super Bowl this year. Ballew says that the idea for Love Letter came about as a result of feeling they “left some meat on the bone” and had more to show and tell about how the brand feels about its home state. “Jeff [Nichols] came up with the idea of taking some of these scenes, characters, storylines and locations, and take inspiration from this handful of films and make our own story out of it,” says Ballew. Scenes for the film were deliberately shot at locations featured in iconic Texas-shot movies like There Will Be Blood, Giant, No Country for Old Men, and Paris, Texas. While Ballew’s work at Yeti helped popularize brands creating character-driven documentary content, he sees an opportunity for Tecovas to zag. “Now everyone has their own little documentary thing going, which makes none of them feel important or unique or original,” says Ballew. So being able to cast and write a script and scout and be really specific with the style and the look and the pace, is a new way to find your own thumbprint.” Building the roots Too often an investment like this in longer form brand entertainment can be seen as self-indulgent for a brand. But CEO David Lafitte sees it as part of a much bigger picture. He says that the role of a cinematic project like Love Letter to Texas is to provide the essential “heavy lifting” of brand building that prevents a company from getting trapped in a cycle of purely transactional marketing. “If you don’t do the heavy lifting of brand awareness and brand building, the lower funnel performance marketing conversion becomes a merry-go-round that’s hard to get off of,” says Lafitte. By focusing on what Lafitte says is a “North Star” of authentic storytelling, the brand is attracting a more engaged consumer. This ultimately boosts efficiency at the lower funnel because it builds an emotional connection that “qualified traffic” responds to more effectively than repetitive conversion ads. Fodrowski says projects like this become a shorthand for people to know who the brand is and its perspective. “We’re coming into this space as a newer brand in a craft that’s been around for over a hundred years,” she says. “And so we have to have our own take on what that looks like. We talk a lot at Tecovas about the idea of honoring the West and crafting its future. This really speaks to that.” Ballew is the first to say he’s much more of a creative lens than a marketer. He knows that films like this aren’t for results next week, next quarter or even next year. He likens a brand to a growing tree. “When a company grows quickly and starts developing a cult following, and there’s this need to grow and grow and sell and sell, the tree gets really top heavy and all these things like Instagram and TikTok ads are adding leaves, and making the tree fuller,” he says. “And I’ve always felt like my job is to build the roots deeper so that the tree lasts a long time. So these projects that I’m interested in are root builders to keep the foundation steady.” The film will launch on Tecovas social and digital channels on April 7th, and the brand plans to hold screenings at its stores across the country. Giddyup. View the full article

Google shared that Googlebot's crawl limits are flexible and can be increased or decreased depending on the need. The post Google Shares More Information On Googlebot Crawl Limits appeared first on Search Engine Journal. View the full article

A middle manager sits in a 1:1 with their boss. They nod along to strategic priorities they already know are unrealistic. The deadlines don’t match the staffing plan. The “new initiative” competes with the last “top priority.” The team is already stretched thin. But the manager doesn’t say it—not plainly—because honesty can be misread as incompetence, negativity, or a lack of readiness for the next level. Two hours later, that same manager is in a team meeting projecting confidence about those same priorities. They translate contradictions into something coherent, reassure direct reports who are already anxious, and say, “We’ll figure it out,” while privately wondering how. Later, at lunch with peers, they compare notes on workload and shifting expectations. Everyone laughs in that awkward “we’re fine” way. No one admits they’re drowning—because even peer relationships can feel political when resources are scarce. Here’s the question we’re not asking: Who can middle managers actually be honest with? In too many organizations, the answer is: no one. That’s not a personality problem or a resilience issue. It’s a design issue—one I call Organizational Latchkey Syndrome: a workplace reality where middle managers are handed responsibility and expected to “figure it out” with limited authority, limited support, and limited psychological safety. As a licensed psychotherapist, I see this pattern constantly: organizations demanding emotional intelligence from people inside emotionally unintelligent systems. It’s like asking someone to practice healthy attachment in a relationship that punishes vulnerability. And because middle managers are the emotional and relational bridge between strategy and execution, Organizational Latchkey Syndrome doesn’t just burn people out. It quietly breaks culture. Why middle managers can’t be safe in any direction Middle managers are often told they need more EQ—more empathy, better communication, stronger coaching skills. And yes, EQ matters. But middle management already demands a high level of emotional intelligence. The problem is that many organizations ask for high-EQ performance from managers while building systems that make it risky to tell the truth. This is a high-EQ role inside a low-EQ system. Upward: They perform competence Safety is conditional. You can raise concerns, but only if they’re packaged “correctly.” You can push back, but only if you already have political capital. You can speak candidly, but only if you can guarantee a solution. In many work cultures, the emotional subtext of leadership is: Bring answers, not complexity. So managers learn to manage impressions instead of surfacing reality—and self-protection replaces reflection. Downward: They perform steadiness Middle managers are expected to provide stability for their teams—especially during change. They’re asked to maintain morale, protect psychological safety, coach performance, and hold space for stress. But many managers don’t have full information, which means they’re asked to create clarity they don’t possess. So they buffer uncertainty, absorb pressure, and make it make sense. That’s leadership—and it’s costly. Emotional labor without recovery becomes emotional depletion. Sideways: They manage scarcity In a healthy organization, peers are where managers can exhale. In many organizations, scarcity activates competition. When budget, headcount, or executive attention is scarce, peer relationships become strategic. Managers perform camaraderie while privately feeling isolated. Everyone says they’re “busy,” but no one says, “I’m not okay.” Put those directions together and you get the most under-acknowledged reality of modern middle management: they are organizationally isolated in the role designed to connect everyone else. Organizational Latchkey Syndrome is an execution problem If we treat middle management isolation as a wellness issue, we’ll respond with wellness solutions: a workshop, a coaching module, a reminder to take PTO, encouragement to “set boundaries.” Those supports can help individuals. They don’t fix the system. When people feel psychologically unsafe, they shift into self-protective mode. They share less, ask less, challenge less. And when your middle layer goes into self-protective mode, the organization pays the price. Here’s what breaks: 1) Feedback stops traveling upward. When managers can’t be honest about capacity, risk, or contradictions, senior leaders make decisions on partial information. Risks surface late. Surprises multiply. 2) Innovation stalls. You can’t access your most creative, strategic thinking in survival mode. And managers can’t model psychological safety they don’t experience, so teams learn to keep their heads down. 3) Execution quietly breaks. A manager gets handed three “top priorities,” each requiring full-time focus. They know the team can realistically handle one, maybe two. So they say “we’ll figure it out” and watch their team burn out trying to deliver the impossible. Execution erodes in missed deadlines, quality slips, and people quietly opting out. As one reader put it in response to my last article: being in the middle—managing up, down, and sideways—can make psychological safety nearly impossible when each side has competing priorities that weigh you down. That isolation isn’t a side effect. It’s a design flaw. What manager-safe spaces actually look like If middle managers are isolated by design, then support has to be intentional—not assumed. A manager-safe space is any structure where managers can tell the truth early without it becoming a performance liability. Here’s what works in practice: 1) Peer cohorts that are truly confidential. Same-level managers (not direct competitors), clear confidentiality norms, a consistent rhythm, and facilitation. The goal is simple: a place to say, “I don’t know,” before that becomes burnout—or resignation. 2) External coaching that doesn’t report back. A protected space to process the role and name what can’t be said inside the normal system. If coaching feeds into evaluation or succession planning, it stops being safe. 3) Executive sponsorship that actually covers them. Cover means a senior leader who protects the messenger, backs early risk-flagging, and names tradeoffs publicly so managers aren’t left absorbing the fallout alone. 4) Clarity on decision rights. If managers don’t have authority, stop evaluating them as if they do. Define what they own, what they influence, what requires escalation—and commit to not second-guessing decisions after the fact. The litmus test Can your middle managers tell the truth early without consequences? Can they say “This isn’t resourced,” “I need help,” or “I don’t agree”—and still feel trusted afterward? If the answer is no, you don’t have a training problem. You have a design problem. Until middle managers have real cover—clarity, capacity, and community—many will keep doing what latchkey kids do best: they’ll figure it out alone. This is Organizational Latchkey Syndrome in full effect. And it’s entirely fixable. But survival shouldn’t be the standard for your culture. And it can’t be the foundation for your leadership pipeline. The question isn’t whether they’re resilient enough to keep going. The question is: how much longer can they sustain it? And what will it cost your organization when they can’t? View the full article

Flights from Manchester, Edinburgh and Dublin among those that returned to destinations on MondayView the full article

Fortune Brands staves off proxy battle with asset manager set up by Trian co-founder Ed GardenView the full article

As Anthropic and OpenAI duke it out with Pentagon matters, Cowork capabilities, and model launches, it’s important to remember that technology is not the goal. It is a means to an end. Its value comes from helping people solve daily problems and giving them one less thing to think about—on a global scale. However, people must first realize there’s a problem and understand how technology can solve it before AI can make a meaningful difference. When things click, it’s always a matter of consumer education, which leads to expanded adoption, which in turn leads to society-wide impact (in that order). Each step can happen swiftly—or take months or years to complete. This pattern—education first, adoption next, transformation last—repeats across sectors. It’s also a tale as old as (human) time. The lesson from past cycles like the cloud and mobile web: The best AI-powered systems won’t be the ones with the highest investment totals or most bells and whistles; they’ll be the ones with tech that unceremoniously makes real-world processes faster, cleaner, cheaper, and more resilient. Technology adoption at scale isn’t an overnight phenomenon; it’s a signal that technology has crossed a threshold from curiosity about “the new thing” to daily driver. AI has tremendous potential, but we in the tech world have lost the plot on making this matter for real people. I’ve been fortunate enough to see this cycle play out a few times in my career. For example, when I worked on the first iPhone, it was impossible to predict a future powered by dating apps, ride-sharing, mobile payments, or social media. Now, it’s hard to remember a time before we could run our lives through our phones. Our breakthrough was delivering an ecosystem once the tech was powerful enough and the world was ready. Because of the backbone we created, new platforms emerged that allow people to leave their wallets at home and conveniently pay via their phones, or tap a button to get a ride. Once consumers realized the power and ease of solving real-world problems with a swipe or tap of their fingertips, adoption took off like wildfire. The same principle was true when we built the first Nest thermostat. From the beginning, the goal was to apply technology to make energy more efficient, from both a capacity and cost standpoint, for households and regular people. We talked about building AI-powered devices that could understand human behavior and adapt accordingly. We had the vision, but needed AI to advance in order to make progress technologically possible and developmentally practical. For example, a popular, seemingly humble feature like package detection on a Nest doorbell camera took nearly a year to develop. The models were heavy. The hardware was constrained. The development cycles were long. We were crawling toward a clear goal with hundreds of hurdles in our way. By the time we perfected computer vision over the course of more than a year, consumers understood the problem that Nest was solving and how adopting the system would help them reduce utility costs while using energy more efficiently. It was at this point that the transformation at scale could—and did—happen. But it takes more to scale meaningfully than shipping innovation and pushing updates to consumer devices. You need to combine the latest technology with the level of consumer interest to solve the problems we face on a daily basis. At Mill—the food recycler company I now run—we started by focusing on households, helping people manage food scraps and deliver them back into the food system, one kitchen at a time. That phase mattered. Education that leads to behavior change always comes first. People must realize there’s a system-wide problem and understand why it exists before tech can help solve it. Food waste, for example, is an industrial problem. Grocery stores discard millions of pounds of food every day. Behind every supermarket is a loading dock crowded with dumpsters and compactors that are consuming space, energy, and labor—and these valuable resources end up getting sent to a purgatory of methane production. Developing an enterprise-grade, AI-powered food waste system at Mill, and seeing it adopted by major players like Amazon and Whole Foods Market, is a signal that we’ve entered a new phase. It’s clear that reducing food waste isn’t just about nudging individual habits. It’s not just about putting last night’s lasagna in the right bin. It’s about removing entire classes of waste from the system. Artificial intelligence makes that possible—not because it’s flashy, but because it’s finally reliable, affordable, and fast enough to operate at scale in the physical world. With the iPhone, smart devices like Nest, and now AI, perspective matters. But above all else, tech leaders need to keep in mind that we must be solving real problems—not generating tech for tech’s sake. Progress in this physical era of AI requires logic and restraint as much as ambition. Fortunately, we’ve been here before. The internet was speculated to become a Wild West of lawless virtual worlds and digital avatars. It became a functional tenant of digital society, grounded by email, maps, commerce, and communication—mundane tools that solved ordinary problems at an unprecedented scale. The story of AI’s next chapter is steeped in precedent. Hype will fade. Models will commoditize. Launches will grow quieter. What we’ll hopefully be left with are AI-powered systems that work to solve everyday problems while improving life in the physical world, rather than distracting from it. View the full article