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Threads is testing a simpler way for people to nudge their feed in a specific direction without digging through settings or retraining the algorithm long term. The new feature, called Dear Algo, lets users tell Threads what they want to see more or less of for a short period of time. Instead of relying only on likes, follows, and past behavior, you can now directly ask the app to adjust what shows up in your feed. It works by writing a public post that starts with “Dear Algo,” followed by your request. For instance, “Dear Algo, show me more posts about podcasts,” or “Dear Algo, show me fewer posts about spoilers for Heated Rivalry.” After you post it, Threads adjusts your feed for the next three days based on what you asked for. The change is temporary on purpose. During a live NBA game, you might want your feed filled with reactions and commentary. A day later, you might want to move on to something else. Dear Algo lets you make those shifts without permanently changing how the algorithm understands you. A public request others can use These requests are regular posts, not private settings. Other users can see them, interact with them, and repost them. If you repost someone else’s Dear Algo request, Threads applies those same preferences to your feed for three days. This turns feed preferences into a kind of discovery tool. If someone you follow is deep into a niche conversation you have not seen yet, you can try their version of the feed for a few days. A more direct way to guide the feed Most social platforms offer some form of feed control, but it’s usually tucked into menus or tied to long term settings. “Controlling your algorithm shouldn’t be complicated. It should feel like a normal part of using the app,” Connor Hayes, head of Threads at parent company Meta Platforms, tells Fast Company. “We saw our community experimenting with ‘Dear Algo’ posts to shape their feed, which inspired us to turn that behavior into an official feature that feels unique to Threads.” He added, “When what you care about shifts—whether it’s a big game tonight or a TV premiere next week—you should be able to tell your feed to shift with you. This is about making Threads the most timely and essential place for what’s happening right now.” Where it is available Dear Algo is rolling out now in the United States, New Zealand, Australia, and the United Kingdom, with plans to expand to more countries. View the full article

If your employer offered you a lump sum to permanently ditch the job that stresses you out like no other, would you take the money and run—or worry about what it might cost you later? I never thought I’d actually encounter this career conundrum. Looking back, I’m surprised by the choice I made. The all-company virtual meeting initially seemed like any of the weeklies that had preceded it. There was a weird icebreaker to get folks loose, various team updates, some HR housekeeping. Then the billionaire who signed all of our checks took the screen. For months, senior leadership had been deprioritizing a project that I—and the vast majority of my colleagues—had been specifically recruited to the startup to produce. They called it a strategic realignment. Or something like that. Our CEO knew many of us weren’t exactly enthusiastic about the reroute. Achieving this newfound mission, he explained, would require the company to get lean. He wasn’t referring to Ozempic. In retrospect, the writing was on the wall like Destiny’s Child’s second album. But those markings might as well have been hieroglyphics, because I sure as hell couldn’t decode them. I didn’t anticipate what came next. Corporate folks call it a “voluntary separation package,” but at the time, it seemed like both a trap door and an escape. It was a lot like the severance packages that most professionals are familiar with, but instead of outright cutting roles, the company presented every employee with a tantalizing offer: five months of gross salary and half a year of covered health insurance. All that was asked in return was that you leave the company. And don’t look back. We had a week to decide. Workflows hit a halt. All outstanding deliverables entered a strange purgatory. For my coworkers, the VSP became the only topic of discussion, as whispers spread about who was clocking out for good, who would remain, and what would be left behind. For some, the decision to secure the bag was a no-brainer. “You could have a dope summer,” said Gary, one of my Slack homies based in the DMV. He imagined months of passport stamps and midday mischief, and as he spoke, I could damn near feel the beach breeze sweeping across my brow. Gary meant well, but I had to be real. These were the final days of quarantine. The pandemic had ravaged headcounts at rival companies—and Black folks like me were often the first out of the door and seldom rehired. Those fortunate enough to be employed held onto their jobs tighter than Stevie Wonder and his locs. I wasn’t afraid of chucking the deuces. But I was afraid of starting over in a job market that had already shown me who it was willing to discard first. I didn’t have the luxury of pretending this decision was just about vibes. That whole week, the second verse of Donell Jones’ “Where I Wanna Be” played on repeat in my head: “Do I leave? Do I stay? Do I go? Or think about my life and what matters to me the most?” Essentially, I was deciding between the risk of extended unemployment (albeit with a nice runway) or the uncertainty that awaited those who remained at the gig. Dominique Dawes had nothing on the mental gymnastics twirling in my brain. The key to escaping decision paralysis was having conversations with the powers that be. Really, they were more like negotiations. What’s in it for me if I bypass five months of paid freedom and remain on the team? One of our directors hinted that the anticipated departures might open opportunities to ascend the org chart. She couldn’t straight up promise upward mobility, but I was very capable of reading between the lines. For the first time since the offer was announced, the decision stopped feeling emotional and began to feel strategic. If I decided not to abandon ship, it wouldn’t be out of fear or blind loyalty. It would be because there was something tangible on the other side of “thanks, but no thanks.” That week felt like a month, and it ended with an exodus. But I decided to stay put. And it worked out: I was elevated to senior management, and the work… well, let’s just say the pay bump motivated me to get on board with the new objectives. But sometimes I wonder how the opposite decision might’ve played out, considering the stream of job offers that came pouring in once word got out about the company shakeup. I’m not a math guy, but I’m smart enough to know two salaries beat one. (Gary would agree; he, like some of my other former colleagues, picked up a new gig within a few weeks.) In the end, the voluntary severance was a lesson in recognizing my leverage. It forced me to ask what I wanted, what I was willing to risk, and what decision put me in the strongest position to win. For that one week, my value and my priorities were crystal clear. View the full article

A reader writes: My office is returning to a physical space in the fall and they are giving managers a lot of leeway to decide on remote/hybrid work. I manage eight people on my team and I know a number of them would be happy to never come into the office again. They have all proven themselves more than capable to work from home. However, I personally work best when I can see/talk with people in person, at least periodically. What balance can I strike between giving my team what they want and what I need in my own work style? I would love to ask each team member to come in at least once every 1-2 weeks, but unless there’s a true need is that out of line? I guess my question is, as a manager, when does my own work style matter and when do I need to get over it? I answer this question — and two others — over at Inc. today, where I’m revisiting letters that have been buried in the archives here from years ago (and sometimes updating/expanding my answers to them). You can read it here. Other questions I’m answering there today include: My company ghosted a candidate I recommended How do I gracefully reject a former employee who keeps applying for a new job with me? The post the team I manage prefers remote work — but I prefer working in-person appeared first on Ask a Manager. View the full article

Oracle’s recent strategic move to build AI data centers across the United States signifies not only a leap in technological infrastructure but also an urgent call for skilled professionals to harness their potential. As many small business owners seek to leverage AI in their operations, this initiative presents actionable insights and opportunities for workforce development. Currently, Oracle is fortifying America’s AI leadership by establishing advanced data centers in states like Texas, New Mexico, Michigan, and Wisconsin. However, simply creating infrastructure isn’t enough; Oracle emphasizes the importance of human expertise and creativity. This is where the Oracle Academy, a philanthropic education initiative, steps in. For nearly 30 years, the Oracle Academy has been instrumental in helping educational institutions equip students with the technological skills demanded in today’s job market. By providing access to a suite of resources—including curriculum, cloud technologies, software, and hands-on labs—Oracle Academy enriches the learning environment for both educators and students. This collective effort prepares a new generation of professionals for careers in enterprise technologies and data-intensive systems, skills that are crucial for businesses looking to thrive in a competitive landscape. The rollout of Oracle’s AI data centers is not merely about infrastructure but also about preparing a workforce ready for the challenges these innovations bring. The company plans to recruit thousands of skilled employees for various roles in these facilities. To effectively bridge the talent gap in the industry, Oracle Academy introduces specialized courses aimed at fast-tracking candidates into essential job roles, particularly in data center operations. In Texas, the Oracle Academy has already engaged with over 130 institutions and nearly 350 faculty members, focusing on disciplines such as computer science, civil engineering, and supply chain management. This extensive network highlights the Academy’s commitment to building local talent pools that can contribute to data centers and other AI-driven industries in the region. In addition to Texas, Oracle’s partnerships span Michigan and Wisconsin, where the Academy collaborates with numerous institutions to foster the technical and analytical skills necessary for modern infrastructure and enterprise systems. New Mexico also benefits from this initiative, with educational collaborations involving prominent institutions like New Mexico State University and the University of New Mexico. Small business owners could see tangible benefits from these developments. With a skilled workforce emerging from Oracle Academy programs, businesses have the potential to hire locally trained talent better equipped to develop and integrate AI technologies. This could enhance operational efficiency, drive innovation, and facilitate data-driven decision-making. Moreover, the Academy has recently launched courses on AI and machine learning, alongside workshops and hands-on labs focused on analytics. Notably, while Oracle software and cloud services are utilized in these curricula, the emphasis remains on broadly applicable skills such as data modeling, cloud architecture, and software development. This practical approach ensures that students are prepared to meet real-world challenges, making them valuable assets to businesses across various sectors. Despite these promising initiatives, small business owners should consider the challenges that may arise from this rapidly changing landscape. Integrating AI technologies requires not only skilled personnel but also an understanding of new systems and processes. For businesses lacking in-house tech capabilities, reliance on external resources for training and support could lead to additional costs and complexity. Furthermore, as the demand for skilled tech talent escalates, small businesses may find themselves in competition with larger corporations, which often offer more attractive compensation packages and career growth opportunities. Therefore, cultivating a strong employer brand and investing in employee development will be critical for attracting and retaining talent. Oracle’s dual investment in AI infrastructure and workforce development through the Oracle Academy signifies a transformative opportunity for small businesses. By tapping into this wave of skilled talent, business owners can position themselves to capitalize on the efficiencies and innovations that AI promises. For more details about Oracle Academy and its initiatives, visit the original post here. Image via Google Gemini This article, "Oracle Champions AI Workforce Development with New Academy Courses" was first published on Small Business Trends View the full article

More than two dozen privacy and advocacy organizations are calling on California Gov. Gavin Newsom to remove a network of covert license plate readers deployed across Southern California that the groups believe feed data into a controversial U.S. Border Patrol predictive domestic intelligence program that scans the country’s roadways for suspicious travel patterns. “We ask that your administration investigate and release the relevant permits, revoke them, and initiate the removal of these devices,” read the letter sent Tuesday by the Electronic Frontier Foundation, Imperial Valley Equity and Justice and other nonprofits. An Associated Press investigation published in November revealed that the U.S. Border Patrol, an agency under U.S. Customs and Border Protection, had hidden license plate readers in ordinary traffic safety equipment. The data collected by the Border Patrol plate readers was then fed into a predictive intelligence program monitoring millions of American drivers nationwide to identify and detain people whose travel patterns it deems suspicious. AP obtained land use permits from Arizona showing that the Border Patrol went to great lengths to conceal its surveillance equipment in that state, camouflaging it by placing it inside orange and yellow construction barrels dotting highways. The letter said the groups’ researchers have identified a similar network of devices in California, finding about 40 license plate readers in San Diego and Imperial counties, both of which border Mexico. More than two dozen of the plate readers identified by the groups were hidden in construction barrels. They could not determine of the ownership of every device, but the groups said in the letter that they obtained some permits from the California Department of Transportation, showing both the Border Patrol and Drug Enforcement Administration had applied for permission to place readers along state highways. DEA shares its license plate reader data with Border Patrol, documents show. The letter cited the AP’s reporting, which found that Border Patrol uses a network of cameras to scan and record vehicle license plate information. An algorithm flags vehicles deemed suspicious based on where they came from, where they were going and which route they took. Agents appeared to be looking for vehicles making short trips to the border region, claiming that such travel is indicative of potential drug or human smuggling. Federal agents in turn sometimes refer drivers they deem suspicious to local law enforcement who make a traffic stop citing a reason like speeding or lane change violations. Drivers often have no idea they have been caught up in a predictive intelligence program being run by a federal agency. The AP identified at least two cases in which California residents appeared to have been caught up in the Border Patrol’s surveillance of domestic travel patterns. In one 2024 incident described in court documents, a Border Patrol agent pulled over the driver of a Nissan Altima based in part on vehicle travel data showing that it took the driver six hours to travel the approximately 50 miles between the U.S.-Mexican border and Oceanside, California, where the agent had been on patrol. “This type of delay in travel after crossing the International Border from Mexico is a common tactic used by persons involved in illicit smuggling,” the agent wrote in a court document. In another case, Border Patrol agents said in a court document in 2023 they detained a woman at an internal checkpoint because she had traveled a circuitous route between Los Angeles and Phoenix. In both cases, law enforcement accused the drivers of smuggling immigrants in the country unlawfully and were seeking to seize their property or charge them with a crime. The intelligence program, which has existed under administrations of both parties, has drawn scrutiny from lawmakers since the AP revealed its existence last year. A spokesperson for the California Department of Transportation said state law prioritizes public safety and privacy. The office of Newsom, a Democrat, did not immediately respond to requests for comment. Courts have generally upheld license plate reader collection on public roads but have curtailed warrantless government access to other kinds of persistent tracking data that might reveal sensitive details about people’s movements, such as GPS devices or cellphone location data. Some scholars and civil libertarians argues that large-scale collection systems like plate readers might be unconstitutional under the Fourth Amendment. “Increasingly, courts have recognized that the use of surveillance technologies can violate the Fourth Amendment’s protections against unreasonable searches and seizures. Although this area of law is still developing, the use of LPRs and predictive algorithms to track and flag individuals’ movements represents the type of sweeping surveillance that should raise constitutional concerns,” the organizations wrote. CBP did not immediately respond to a request for comment, but previously said the agency uses plate readers to help identify threats and disrupt criminal networks and their use of the technology is “governed by a stringent, multi-layered policy framework, as well as federal law and constitutional protections, to ensure the technology is applied responsibly and for clearly defined security purposes.” The DEA said in a statement that the agency does not publicly discuss its investigative tools and techniques. Burke reported from San Francisco. Tau reported from Washington. Contact AP’s global investigative team at Investigative@ap.org or https://www.ap.org/tips/. —Garance Burke and Byron Tau, Associated Press View the full article

Generative engine optimization (GEO) is the practice of positioning your brand and content so that AI platforms like Google AI Overviews, ChatGPT, and Perplexity cite, recommend, or mention you when users search for answers. If that sounds abstract, the results aren’t. For bootstrapped form builder tool, Tally, ChatGPT became the #1 referral source. They’re not alone. Across industries, the shift is already measurable. ChatGPT reaches over 800 million weekly users. Google’s Gemini app has surpassed 750 million monthly users. And AI Overviews are appearing in at least 16% of all searches (significantly higher for comparison and high-intent queries). The question isn’t whether AI is changing discovery. It’s whether your brand is showing up when it happens. So GEO is real. But is it stable enough to invest in seriously? That’s a fair question. When we tracked 2,500 prompts across Google AI Mode and ChatGPT through the Semrush AI Visibility Index, the first thing we noticed was volatility. Between 40 and 60% of cited sources change from month to month. But underneath the variances, patterns emerged. The brands showing up consistently shared specific structural characteristics. Entity clarity, content extractability, multi-platform presence made them easier for AI systems to find, trust, and reference. In this guide, I’ll share what we’ve found about what GEO requires, how it differs from SEO, and the framework for increasing your visibility in AI-driven discovery. What GEO Looks Like in Practice GEO helps your brand appear in AI-generated answers. For example, when someone asks an AI tool “What is the best whey protein powder for a mom in their 50s,” the response typically evaluates brands and recommends options based on ingredients, reviews, and credibility signals. If your content or brand is included in that response, it’s an example of GEO in action. Getting there requires coordinated effort across several areas: Content strategy: Publishing information that AI systems can discover, understand, and extract for answers Brand presence: Establishing your authority across platforms where AI tools pull information (not just your website) Technical Optimization: Ensuring AI crawlers can access and process your content Reputation Building: Earning mentions and associations that signal credibility to AI systems These activities overlap with traditional SEO, but the emphasis shifts. How GEO Differs from Traditional SEO GEO builds on the same SEO fundamentals you already use. But it shifts the focus from rankings and clicks to how your brand is mentioned and cited inside AI-generated answers. Here’s a snapshot of some key differences between GEO and traditional SEO: What ChangesTraditional SEOGEOPrimary goalRank in top search positionsBe referenced or mentioned in AI answersSuccess metricsRankings, clicks, trafficCitations, mentions, share of voiceHow users find youClick through to your siteAI includes you in generated responsesKey platformsGoogle, BingGoogle AI Overviews and AI Mode, ChatGPT, PerplexityHow you optimize contentTitle tags, keywords, site speed, content qualitySelf-contained paragraphs, clear facts, structured dataHow you build credibilityBacklinks, author credentials, reviews, domain authorityPositive mentions across trusted platforms and communities Use this table to update your mental model. Traditional SEO fundamentals still matter. We’re just adapting how we apply them as AI systems change how people discover information. Now, let’s break down what this means in practice. What Stays the Same The core principles behind effective SEO still apply to GEO. You still need to publish high-quality, authoritative content for real users. Your site still needs to be technically accessible. You still need credible signals of trust and expertise. And you still need to understand user intent and deliver clear value. AI systems tend to reference content that is authoritative, well-structured, and easy to interpret. Those are the same qualities that support strong SEO performance. If you already have a solid SEO foundation, GEO builds on it rather than replacing it. Further reading: SEO vs. GEO, AEO, LLMO: What Marketers Need to Know What Changes Where GEO diverges is in how that foundation is applied. 1. Where You Need Presence Traditional SEO focuses primarily on your owned properties, i.e. your website and blog. GEO benefits from strategic presence across platforms where AI tools discover information, including: Reddit threads where your target audience asks questions YouTube videos demonstrating your expertise Industry publications that establish your authority Review sites where customers discuss solutions Social platforms where conversations happen 2. How You Structure Information AI systems extract specific passages from your content to construct answers. They pull a paragraph here, a statistic there, and weave them together. This changes how you need to structure information. When you’re explaining a concept, defining a term, or sharing data, that paragraph should ideally work on its own. AI systems often extract these substantive passages without the conversational setup around them. (We’ll cover the mechanics of how this works in the strategic framework later.) You need clear headings to help AI identify which section answers which question. Also, putting answers early in sections may make them easier for AI to find and extract. Traditional SEO often rewards comprehensive coverage. GEO places more emphasis on content that’s easy to extract and reassemble. We’re still learning exactly how different AI systems prioritize structure, but clarity consistently helps. 3. What You Measure Traditional SEO metrics like rankings, clicks, and bounce rate tell part of the story. GEO adds new measurements, like: AI visibility score: A benchmark of how often and where your brand appears in AI-generated answers Share of voice: Your visibility compared to competitors in AI responses Sentiment: Whether mentions are positive, neutral, or negative Context or prompt: What questions or topics trigger mentions of your brand Together, these metrics help you understand not just whether you’re visible, but how your brand is being positioned inside AI-generated responses. You need both traditional SEO metrics and AI visibility metrics to understand your full organic search presence in 2026. Note: You can track these metrics using Semrush’s Enterprise AIO, which monitors your brand’s visibility across AI platforms like ChatGPT, Google AI Mode, and Perplexity. It provides granular tracking of mentions, sentiment, share of voice, and competitive benchmarking to help you optimize your AI visibility strategy. 5 Principles for AI Visibility: A Strategic Framework An effective GEO strategy rests on five connected principles that work together to maximize your AI visibility. (As AI systems evolve, specific patterns may shift, but these underlying principles provide a stable foundation.) Each one addresses how AI systems discover, evaluate, and reference your brand. Let’s look at them in detail. 1. SEO Fundamentals Are the Foundation SEO fundamentals still matter for GEO, but for a different reason than in traditional search. In AI-driven discovery, these fundamentals still function as optimization levers, but they influence retrieval, interpretation, and attribution rather than rankings alone. They create the baseline conditions that allow AI systems to retrieve information, interpret it accurately, and attribute it to a source with confidence. For instance, AI-generated answers are assembled from content that is accessible, readable, and attributable. When accessibility, readability, or clear attribution are weak, even strong content becomes harder for AI systems to surface or reference reliably. This is why many sources cited by AI platforms share characteristics long associated with solid SEO foundations. The overlap exists because clarity and reliability still matter across discovery systems, even as the surfaces change. Technical accessibility plays a role here. Content that cannot be consistently crawled, indexed, or rendered introduces uncertainty at the retrieval layer. Page performance has a similar effect. Slower or unstable experiences don’t block inclusion outright. But they reduce how dependable a source appears when answers are assembled. JavaScript-heavy implementations highlight this dynamic. Many AI crawlers still struggle to consistently process client-side rendered content, which can make core information harder to extract or interpret. When that happens, AI systems have less certainty about using the content as a reference point. But technical setup is only part of the equation. AI systems also assess content quality and credibility. Information that reflects real experience, clear expertise, and identifiable authorship is easier to contextualize and trust. Signals associated with E-E-A-T (Experience, Expertise, Authoritativeness, and Trust) influence not just whether content is referenced, but how it is framed within an answer. Taken together, these foundations explain why SEO still underpins GEO. Not as a ranking system, but as the infrastructure that makes AI visibility possible. Further reading: A technical SEO blueprint for GEO: Optimize for AI-powered search 2. Entity Clarity Shapes AI Understanding Entities help AI systems understand and categorize information on the web. This includes distinguishing your brand from similar names, identifying what category you belong to, and understanding which topics you’re credible for. AI systems don’t just read words. They interpret structure. Before schema ever comes into play, they look for clear signals about: What your brand is What category it belongs to What it offers What it’s authoritative for The most reliable way to provide those signals is through well-structured information. If those signals are unclear or inconsistent, AI systems have less confidence when deciding whether and how to reference you. Take monday.com as an example. When AI systems crawl websites and process information, they see “monday” mentioned in many different contexts. Clear, consistent descriptions across the site and supporting sources help AI understand that monday.com refers to project management software. Not the day of the week. The same principle applies to category clarity. If you sell organic dog food, AI needs to categorize your brand under pet nutrition, not general groceries or pet accessories. When someone asks “what’s the best grain-free dog food,” AI is more likely to consider brands it can clearly place in the correct category. On a product page, it should be unambiguous what each element represents — the product name, the description, the price, the attributes, availability and variants. That clarity needs to exist in the visible page content first. Schema markup can then mirror that structure in a machine-readable format (typically JSON-LD). And that same structured understanding should also be reflected in downstream systems, like your product feed submitted to Google Merchant Center. In other words, the page structure, the schema markup, and the commerce feed should all describe the same thing in the same way. The goal isn’t to “add schema.” The goal is to make your information logically structured so machines can consistently understand it across systems. This is important because we don’t know how structured data is used inside large language models. Or how exactly schema influences training, retrieval, or real-time answer generation. But we do know this: AI systems cross-reference signals from multiple sources and formats. Your brand description on LinkedIn should align with what appears on your site. Profiles on Crunchbase, review platforms, or industry directories should reinforce the same category, positioning, and value proposition. When these signals are consistent across sources, AI systems can categorize and reference your brand with greater confidence. When they conflict, confidence drops, and your brand is less likely to be mentioned. This is why entity clarity isn’t just about a single markup tactic. It comes from designing your content and presence so machines can reliably understand who you are, what you offer, and where you belong wherever your brand appears. Further reading: How Ecommerce Brands Actually Get Discovered In AI Search Tip: You can check if your site has missing structured data that makes entity relationships unclear — along with other issues that could potentially be hurting your AI search visibility — using Semrush’s Site Audit. 3. Content Must Be Easy to Extract and Reuse If entity clarity determines whether AI systems consider your content at all, extractability determines which specific parts get pulled into AI-generated answers. This principle operates at the retrieval layer. AI systems don’t consume pages the way humans do. When generating answers, they retrieve specific passages from across the web and assemble them into a response. Here’s how it works mechanically: LLMs break content into chunks, convert those chunks into numerical representations (vectors), and retrieve the most relevant passages when assembling an answer. Those retrieved chunks are then synthesized into a response — often without the surrounding context from your original page. This has practical implications. Based on what we’ve observed, passages that retain meaning when read in isolation are more likely to be retrieved and used accurately. Passages that rely on conversational setup or references like “as mentioned above” or “this is why” tend to lose clarity when extracted. Now this may not apply to every paragraph on a page. But paragraphs that contain definitions, explanations, comparisons, or key facts should ideally stand on their own. These are the passages AI systems are most likely to extract without the surrounding narrative. So what makes content extractable? Self-contained paragraphs: Each paragraph expresses one complete idea that makes sense on its own, without vague references to surrounding text Specific facts and statistics: Concrete numbers and clear statements are easier for AI to extract than vague generalizations Clear, descriptive headings: Headings signal what each section covers, helping AI understand content organization Front-loaded information: The main point appears at the start of paragraphs rather than at the end One important distinction: This principle mainly applies to retrieval-augmented systems — like Google AI Mode and Perplexity with grounding, and ChatGPT with browsing enabled. These systems get content in real-time. For base model knowledge (what the LLM learned during training), content structure is less important. That knowledge comes from training, not from retrieving per-query. Building presence in training data takes time and requires consistent, authoritative publishing. Below is an example of self-contained content that AI systems can easily extract and reference. It answers a single, well-defined question: which sources AI platforms rely on for finance-related queries The main takeaway is stated immediately, without setup Supporting context (platforms, percentages, category) is included within the same frame The insight makes sense on its own, even if quoted or summarized elsewhere The same extractability principle shows up in everyday writing as well. For example, compare these two ways of explaining the same cooking technique: Hard to extract: “There are several reasons this method works. After trying it, most people find their eggplant tastes better. That’s why many chefs use it.” Easy to extract: “Salting eggplant for 15 minutes before cooking removes bitterness and excess moisture. This technique improves the final texture.” Both explain the same idea. But the second version states the technique, timing, benefit, and result clearly, which makes it easy for AI to extract as a standalone passage. Here are other examples: When content is structured this way, AI systems can reliably retrieve relevant passages and include them in answers. Over time, that increases the likelihood that your expertise is surfaced accurately when users ask questions related to your domain. 4. AI Visibility Extends Beyond Your Website AI systems don’t just pull from your website when building answers. They gather information from YouTube, Reddit, review sites, industry publications, social platforms, and more. This creates two opportunities for visibility: (I) Your Owned Presence Owned presence is content you or your team create on platforms beyond your website. Your YouTube channel showing product features gives AI video content to reference Your company’s participation in relevant subreddit discussions shows expertise in action Your executives’ LinkedIn newsletters establish thought leadership Podcasts, webinars, conference presentations, and educational platforms provide additional long-form content AI systems can extract from. These platforms often play an important role in AI discovery. In fact, Reddit, Linkedin, and YouTube were among the top cited sources by the top LLMs in October 2025. When your brand creates valuable content on these platforms, you give AI systems more material to draw from. But the key is creating substantive, helpful content that addresses real problems in your industry. (II) Earned Mentions Earned mentions are references to your brand that you don’t directly control. Customer reviews on G2, Capterra, or Trustpilot describe real experiences with your product Industry journalists mentioning your company in news articles provide third-party validation Community discussions on Reddit or Quora where users recommend your solution show authentic sentiment. Like this: When multiple independent sources discuss your brand in relevant contexts, AI systems have clearer signals to interpret your credibility. Further reading: 7 ways to grow brand mentions, a key metric for AI Overviews visibility Side note: Tools like Semrush’s AI PR Toolkit make this easier to evaluate at scale. Beyond counting earned mentions, it shows how your brand is framed across sources, including whether mentions skew positive, neutral, or negative. This metric can be very important as you work to extend brand visibility beyond your website. Because sentiment influences how AI systems frame your brand in answers, not just whether they mention you at all. Why Both Matter Owned presence and earned mentions work together. Your owned content demonstrates expertise and provides detailed information AI can reference. Earned mentions from customers and industry sources validate your credibility. When AI systems encounter both, they build a comprehensive understanding of what you offer. This owned and earned content may also become part of LLM training data in the future, shaping how AI systems learn about and reference your brand long-term. 5. Visibility Is Measured Differently in AI Search Traditional SEO metrics (like rankings, clicks, and traffic) only tell part of the story. But they had one major advantage: the attribution path was clear. A user clicked, landed on your site, and either converted or didn’t. You could tie that traffic directly to revenue. AI search breaks that path. When an AI tool recommends your product to a user, they might never click through to your site. The conversion may still happen — they Google your brand name later, sign up the following week — but your analytics won’t connect it back to the AI mention that started it. That’s the real measurement challenge. It’s not just that the metrics are different. It’s that the link between visibility and revenue becomes harder to trace. The value here isn’t just the click. It’s being part of the answer. This requires measuring your visibility differently. Here are the key metrics to consider: Citation frequency: This measures how often AI platforms mention your brand when answering questions Share of voice: Your mention rate compared to competitors. If an AI answers 100 questions about “best CRM,” how many times do you appear vs. your rivals? This reveals your true competitive position. Context tracking: Where do you appear? Understanding which specific prompts or topics trigger your brand mentions helps you identify the subjects you own versus where you’re invisible. Sentiment: Are the mentions positive, neutral, or negative? A high share of voice means nothing if the AI is telling users your product is “overpriced” or “buggy.” The challenge is that traditional analytics platforms (like GA4 or Google Search Console) cannot track these signals. They only see what happens after a click. This creates a “measurement blind spot.” You might be the most mentioned brand in ChatGPT, but your standard dashboards would show zero activity. Platforms like Semrush’s AI Visibility Toolkit are built to solve this specific problem. They help quantify these “invisible” GEO metrics, turning qualitative data (like sentiment and mention frequency) into trackable numbers. Its Brand Performance report shows how visible your brand is in AI answers, how you compare to competitors, and whether mentions skew positive, neutral, or negative. The toolkit also highlights AI visibility insights, helping you understand how your brand is currently interpreted in AI answers and where adjustments may improve visibility. Ultimately, a modern search strategy requires monitoring two distinct dashboards: One for your website’s performance (rankings and traffic) in traditional search. And one for your brand’s mentions across AI search You need both to see the full picture. What This Framework Doesn’t Guarantee These principles increase your probability of appearing in AI answers. They don’t guarantee it. The volatility in AI citations means even well-optimized brands experience fluctuation. Different AI platforms weigh signals differently. User context and conversation history affect what gets cited. And AI systems are evolving rapidly — what works today may shift as models update. Think of GEO like brand building: you’re increasing your odds across many moments of potential visibility, not securing a fixed position. The brands that do this well show up more often, more accurately, and in better context. But there’s no “rank #1” equivalent to chase. That realism isn’t a reason to ignore GEO. It’s a reason to approach it as an ongoing discipline. Showing up consistently, across surfaces, over time, is how you build trust with AI systems. Frequently Asked Questions What’s the biggest misconception about GEO right now? The biggest misconception is that AI-generated answers are too volatile to optimize for. While individual responses change, the underlying inputs do not. AI systems consistently rely on durable signals like authority, clarity, and trust. Brands with strong entity clarity and credible sources appear repeatedly, even as surface-level outputs fluctuate. The patterns are stable enough to act on. Is GEO replacing SEO? No, GEO builds on SEO fundamentals. Traditional SEO optimizes for rankings and clicks. GEO optimizes for mentions, citations, and recommendations inside AI-generated answers. They work together. Strong SEO creates the foundation (technical accessibility, quality content, credibility signals) that AI systems rely on when deciding which brands to reference. How should we think about GEO in the bigger AI search shift? The clearest way to frame it is as a hierarchy. AI search is the environment AI SEO is the practice AI visibility is the outcome GEO sits inside AI SEO as one way to improve visibility within generative systems. The goal is not optimizing for a single model or interface. The goal is being seen, trusted, and reused wherever people search for answers. Further reading: How to Rank in AI Search (New Strategy & Framework) What types of content are more likely to appear in generative AI responses? Content that is easy for AI systems to retrieve, understand, and reuse is most likely to appear in generative AI responses. In practice, this means clear, direct answers to specific questions, self-contained explanations, fact-based comparisons, and concise definitions that make sense without surrounding context. AI systems tend to pull individual passages, not entire pages, so structure and clarity matter more than length. Does AI search favor large, well-known brands, or does GEO level the playing field? Well-known brands often start with more authority, but they don’t automatically win. Smaller publishers can compete when they own a clearly defined topic, show up consistently across platforms, and are easy for AI systems to understand and trust. In practice, focused niche sites may outperform larger brands when their expertise is clearer, better structured, and tightly aligned with specific audience needs. What’s the right way to think about GEO moving forward? The right way to think about GEO is as a long-term visibility discipline, not a short-term optimization tactic. Success comes from making your expertise clear, consistent, and reusable wherever AI systems look for answers. That requires strong alignment across content, SEO, brand, PR, product, and customer touchpoints. AI search does not change the goal of helping users. It raises the standard for coherence, accuracy, and trust across the entire web. View the full article

Microsoft's February security update is a big one. This latest "Patch Tuesday" fixes 58 vulnerabilities in total, six of which are zero-day flaws. As a reminder, a zero-day is a vulnerability that has been either actively exploited in the wild or publicly disclosed before an official fix is released by the developer. As BleepingComputer reports, security flaws were found in the following categories: 25 elevation-of-privilege vulnerabilities, five security feature bypass vulnerabilities, 12 remote code-execution vulnerabilities, six information disclosure vulnerabilities, three denial of service vulnerabilities, and seven spoofing vulnerabilities. Three of the elevation of privilege vulnerabilities and two of the information disclosure vulnerabilities are considered "critical." (These numbers do not include the three Microsoft Edge vulnerabilities patched earlier in February.) Patch Tuesday updates are typically released around 10 am PT on the second Tuesday of every month, and your device should receive them automatically. BleepingComputer reports that this month's release also includes Secure Boot certificate updates for 2011 certificates that are expiring in June. Six zero-days patched in FebruaryThree of the six actively exploited zero-days fixed in February are security feature bypass vulnerabilities: CVE-2026-21510: This is a flaw the Windows Shell that allows an attacker to execute content without warning or gaining user consent, though the user does need to open a malicious link or shortcut file. CVE-2026-21513: This MSHTML Framework vulnerability allows an unauthorized attacker to bypass a security feature over a network. Microsoft has not released details on how this flaw was exploited. CVE-2026-21514: This vulnerability in Microsoft Word allows an attacker to bypasses OLE mitigations in Microsoft 365 and Microsoft Office once a user has opened a malicious Office file. All three of the above flaws have been attributed to Microsoft Threat Intelligence Center (MSTIC), Microsoft Security Response Center (MSRC), Office Product Group Security Team, and Google Threat Intelligence Group along with an anonymous researcher for CVE-2026-21510 and CVE-2026-21514. Two of the zero-days are elevation of privilege vulnerabilities. CVE-2026-21519 is a Desktop Windows Manager flaw that allows an attacker to gain SYSTEM privileges, while CVE-2026-21533 is a Windows Remote Desktop Services flaw that allows an attacker to elevate privileges locally. The former has been attributed to MSTIC and MSRC, while the latter was discovered by the Advanced Research Team at CrowdStrike. Finally, CVE-2026-21525 is a denial of service vulnerability in the Windows Remote Access Connection Manager that allows an unauthorized attacker to deny service locally. This flaw was discovered by the ACROS Security team with 0patch—it was reportedly found in a public malware repository in December 2025. View the full article

At work, we still talk about careers like they’re ladders. As if success must be a straight line upward: more responsibility, bigger title, better office. But that old image isn’t just outdated. It can be harmful. Ladders come with an unspoken message: if you’re not climbing, you must be falling. If you experience job loss, the ladder metaphor makes you feel like you slipped off and can’t recover. If you take a step sideways, it makes you look like you stalled and aren’t motivated. If you change careers completely, it can feel like you have to start from scratch. Most people don’t need any more pressure or extra worry about what others think, when they’re already trying to make hard decisions about their work and their lives. That’s why I think we need a better metaphor. Why a quilt is a better model than a ladder Imagine a quilt. It’s not one long piece of cloth that stretches up into the sky. Instead, it’s many pieces, each with its own shape, material, color, and history, stitched together into something useful and uniquely meaningful. That’s what modern careers look like: Pieces of skill you build over time Patterns of work that overlap and influence one another Mistakes, leaps, and detours that add texture Priorities and goals that can shift as life changes (sometimes by your own choice, and sometimes because a square ended before you expected) A career quilt has direction, purpose, and depth. And unlike a ladder, it doesn’t require you to constantly compare your height to someone else’s. How to think about your own career If you’ve been picturing your career as a ladder, it’s easy to fall into critical self-talk about where you “should” be. You might feel behind or worry that a change means you’ve lost everything you’ve worked for. The ladder metaphor leaves very little room for life’s unexpected turns, or for choices that don’t look like a straight climb upward. A quilt gives you a different way to look at your past, and your future. A job loss isn’t slipping off the ladder, it’s simply a square that ended before you expected. A pivot isn’t failure, it’s a new piece of fabric. A sideways move isn’t stalling, it’s part of your quilt that builds depth, resilience, and new skills. So instead of asking, “What’s my next rung?” try asking, “What do I want my next square to be?” What skills do you want to strengthen? What kind of work feels most important to you right now? What chapter are you ready for, even if it doesn’t look like a promotion on paper? Careers don’t have to be explained in a straight line to be valid. You’re allowed to choose your next piece intentionally, without worrying about how it looks from the outside. How to support your team members’ career quilts You don’t just stitch your own quilt. Managers (from first-line leaders through senior executives) have an enormous influence on whether your team members feel boxed into ladders or supported in building something broader. One of the most helpful things you can do is expand the conversation beyond titles and promotions, and focus instead on skills, experiences, and growth that can happen in many forms. If someone feels stuck waiting for a promotion, instead of saying, “You just have to wait for the next role,” a manager might say: “Let’s look at the skills you want to build and how you can grow and demonstrate them in this role so you’ll be ready when the time comes.” That feels empowering and grounded, instead of simply waiting to be chosen. If someone shares that they’re interested in trying something new, even if they’re not 100% sure it’s for them, respond with openness: “I’m glad you let me know. Let’s think about ways you can start getting exposure – maybe by shadowing someone, sitting in on a project, or meeting a few people on that team.” This acknowledges that growth often starts with exploration, not certainty. And if someone shifts direction entirely – for example, moving from people leadership back into an individual contributor role – your words matter. Reminding them that it isn’t a step down, but another meaningful square in their career quilt can help make that transition successful, and it may matter more to them than you realize. Redefining success Ladders measure success by how high you climb. Quilts measure success by what you build along the way. When we help people (including ourselves) see their careers in a different light, we stop equating promotions with progress. We start valuing depth over direction, learning over hierarchy, and stories over status. And careers become something people shape, rather than something they endure while waiting for their turn. Because real growth isn’t about how high you go—it’s about shaping a career that reflects who you are and allows you to contribute something uniquely valuable along the way. View the full article

Time management strategies go beyond blocking. By Jackie Meyer Go PRO for members-only access to more Jackie Meyer. View the full article

Time management strategies go beyond blocking. By Jackie Meyer Go PRO for members-only access to more Jackie Meyer. View the full article

Plus two possible exceptions. By Ed Mendlowitz Call Me Before You Do Anything: The Art of Accounting Go PRO for members-only access to more Edward Mendlowitz. View the full article

Plus two possible exceptions. By Ed Mendlowitz Call Me Before You Do Anything: The Art of Accounting Go PRO for members-only access to more Edward Mendlowitz. View the full article

Mark Zuckerberg’s new house in Miami Beach has sweeping waterfront views. It also sits at ground zero for climate change. Zuckerberg and his wife, Priscilla Chan, are the latest in a string of billionaires and celebrities to move to Indian Creek, a private island in Miami’s Biscayne Bay. Neighbors include Jeff Bezos, who owns three homes on the island, as well as investor Carl Icahn, Ivanka The President, and Jared Kushner. Like much of Miami, the area faces mounting climate risks. “It’s very subject to flooding and rising seas,” says Stephen Leatherman, an environmental professor at Florida International University who studies the state’s islands. Miami’s sea levels have risen eight inches since 1950. By 2040, the water is projected to be 10 to 17 inches higher than it was in 2000. As the water rises, that’s making “sunny day” flooding from high tides more common—up 400% over the last 20 years in Miami Beach—and storm surges are increasingly dangerous. First Street, an organization that analyzes climate risk for specific properties, doesn’t yet have data for Zuckerberg’s house, which was newly built. But it estimates that a home down the street faces “severe” flood risk, with the potential for 5.9 feet of flooding in an extreme event. That property also faces possible 184-mile-per-hour hurricane winds and more than three weeks per year of extreme heat. Indian Creek is an artificial island, created in the early 1900s by dredging sediment from the bay. It was once a mangrove forest, dense with trees and shrubs that helped shield Miami from storms. Today, only about 2% of mangroves remain in the area. Ironically, wealthy homeowners have often cut down mangroves in front of their own homes to have better views, increasing their flood risk. The island sits around seven feet above sea level, slightly higher than some other parts of Miami. But other parts of Miami are sinking, and it’s not clear if the island, built on soft sediment, may also be subsiding. And “if a hurricane comes, they’re going to get a big storm surge in there,” says Leatherman. In theory, the water could surge as high as 15 feet to 20 feet in parts of Miami in a worst-case hurricane. Of course, Zuckerberg and his neighbors have money to throw at the problem. “If you’re willing to build to a higher standard to mitigate against wind by putting concrete gables on your house, and you basically build a bunker, you can do that,” says Ed Kearns, chief science officer at First Street. “And if you raise that bunker up 10 feet, then you’re above the storm surge.” He points to a house that survived Hurricane Michael when every nearby house was destroyed. (Zuckerberg and Chan did not immediately respond to Fast Company‘s request for comment.) Climate change also poses other threats to infrastructure in the area—for example, saltwater is beginning to contaminate drinking water, and critical power stations are more exposed to flooding. Still, a billionaire has the option to easily leave in a disaster: Zuckerberg, for example, also owns other houses in California and Hawaii. The new house, worth perhaps $150 to $200 million, is only 0.087% of his net worth; if it was destroyed in a hurricane, he could handle the loss. (It’s worth noting that Zuckerberg may be changing his primary residence to avoid the possibility of a 5% wealth tax in California, which could put him on the hook for an $11 billion tax bill; so far, the proposed tax hasn’t yet been approved as a ballot measure for this fall’s election, but some wealthy residents are already moving.) The same isn’t true for non-billionaires in the area. Floridians are already grappling with rising insurance premiums—or the challenge of getting insurance at all—as extreme storms keep hitting the state. As Miami’s population grows, housing costs are climbing, potentially pushing lower-income residents into more flood-prone neighborhoods. The city as a whole has far fewer resources to invest in resilience than the small, heavily fortified “Billionaire Bunker” island of Indian Creek. The contrast is stark. Most Miami residents face increasing vulnerability to climate change. Billionaires like Zuckerberg can mitigate many of the risks, but doing so comes at a price and raises broader questions about whether $200 million might be better spent strengthening public resilience rather than building private fortifications. View the full article

Google announced an early preview of WebMCP, which is a protocol for how AI agents interact with websites. “WebMCP aims to provide a standard way for exposing structured tools, ensuring AI agents can perform actions on your side with increased speed, reliability, and precision,” wrote André Cipriani Bandarra from Google. WebMCP enables developers to communicate with LLMs via your website about the actions certain buttons or links take. WebMCP allows websites to explicitly publish a “Tool Contract.” It uses a new browser API (navigator.modelContext). Instead of the AI guessing, the website provides a structured list of tools (e.g., function buyTicket(destination, date)). The AI can then “call” these functions directly. Structured interactions for the agentic web. WebMCP proposes two new APIs that allow browser agents to take action on behalf of the user: Declarative API: Perform standard actions that can be defined directly in HTML forms. Imperative API: Perform complex, more dynamic interactions that require JavaScript execution. These APIs serve as a bridge, making your website “agent-ready” and enabling more reliable and performant agent workflows compared to raw DOM actuation. Use cases. Here are the use cases Google posted for an AI agent that can handle complex tasks for your users with confidence and speed. Travel: Users could more easily get the exact flights they want, by allowing the agent to search, filter results, and handle bookings using structured data to ensure accurate results every time. Customer support: Help users create detailed customer support tickets, by enabling agents to fill in all of the necessary technical details automatically. Ecommerce: Users can better shop your products when agents can easily find what they’re looking for, configure particular shopping options, and navigate checkout flows with precision. How to access the preview. You can apply for the preview to WebMCP over here. Why we care. Agentic experiences are the future of search and possibly SEO. Dan Petrovic called this the biggest shift in technical SEO since structured data. Glenn Gabe called this a big deal. It is definitely worth exploring these new protocols. View the full article

In relation to commercial real estate financing, knowing the different types of loans is crucial for making informed decisions. You’ll encounter options like SBA loans designed for small businesses, traditional Bank of America loans for stable properties, and CMBS loans for higher leverage. Furthermore, there are bridge and construction loans for urgent funding needs, plus various equity financing methods. Comprehending these loan types can greatly influence your investment strategy, so let’s explore each one in detail. Key Takeaways SBA Loans: Ideal for small businesses, with low down payments and long repayment terms, partially guaranteed by the U.S. Small Business Administration. Traditional Bank Loans: Typically used for stabilized properties, requiring higher down payments and offering fixed or variable interest rates over 5 to 20 years. CMBS Loans: Provide non-recourse financing for stabilized properties, with strict performance standards and significant prepayment penalties. Bridge Loans: Short-term financing options ranging from 12 to 36 months, focused on property value and requiring a clear exit strategy. Construction Loans: Designed for funding construction projects, these loans have variable rates and disburse funds in stages, with repayment typically converting to permanent financing. SBA Loans (7(a) and 504 Programs) When considering financing options for your commercial real estate needs, SBA loans—specifically the 7(a) and 504 programs—can be highly beneficial. Both of these types of commercial real estate loans are partially guaranteed by the U.S. Small Business Administration, making them attractive for small businesses. The SBA 7(a) loan program offers flexibility, allowing you to finance various business purposes, including real estate acquisitions. You can secure down payments as low as 10% and enjoy repayment terms that extend up to 25 years. Conversely, the SBA 504 loan program focuses on major fixed asset purchases, like real estate or equipment, providing long-term, fixed-rate financing. With interest rates typically ranging from 2.25% to 6.0%, these loans offer competitive options compared to traditional financing. Meanwhile, the application process requires detailed documentation; the favorable terms make SBA loans a strong choice among the types of real estate loans available. Permanent Loans/Traditional Bank Loans Permanent loans, often referred to as traditional bank loans, are primarily aimed at stabilized, income-producing properties. These loans typically come with terms ranging from five to twenty years, making them suitable for long-term financing needs. To secure a permanent loan, you might expect to provide a down payment of 20-30%, with interest rates that can be fixed or variable based on lender conditions. Key features of permanent loans include: Focus on lower-risk property types Requirement for strong borrower financials Necessity of detailed documentation, like rent rolls and operating statements Potential for extended amortization schedules, enabling longer repayment periods Due to these characteristics, permanent loans are frequently utilized for refinancing existing debts or acquiring properties that already generate income. Comprehending these aspects can help you make informed decisions in commercial real estate financing. CMBS Loans (Conduit Loans) CMBS loans, or conduit loans, offer a non-recourse financing structure that limits your personal liability to the collateral property, making them an attractive option for many investors. These loans provide high leverage opportunities, allowing you to secure significant funding for stabilized, income-producing properties that meet specific performance requirements. Nonetheless, it’s important to keep in mind that the prepayment penalties can be steep, so they’re typically better suited for those looking to hold assets long-term rather than for quick financing solutions. Non-Recourse Financing Structure In the domain of commercial real estate financing, non-recourse loans, particularly through conduit financing, stand out due to their unique structure. With a non-recourse structure, you’re only liable for the loan up to the property’s value, which protects your personal assets from creditor claims. This feature makes CMBS loans appealing, especially for long-term investors. Nevertheless, to qualify for this type of financing, your property must meet strict performance standards, including: Consistent cash flow High occupancy rates Compliance with underwriting criteria A stable financial history Keep in mind that prepayment penalties can be costly and complex, making CMBS loans more suitable for those looking to hold properties long-term rather than those seeking short-term financing options. High Leverage Opportunities High leverage opportunities through conduit loans allow investors to maximize their financing potential during minimizing personal risk. CMBS loans are pooled commercial mortgages sold as bonds, offering competitive fixed rates and financing for stabilized, income-producing properties. With a non-recourse structure, your liability is limited to the property itself, protecting your personal assets. To qualify, properties must meet strict performance standards, including a strong debt service coverage ratio and stable occupancy rates. Whereas these loans can provide financing up to 80% of a property’s value, they typically require a minimum loan amount of $1 million. Keep in mind that prepayment penalties can be costly, making CMBS loans more suitable for long-term asset holders rather than those seeking short-term financing solutions. Property Performance Requirements For investors considering conduit loans, comprehending property performance requirements is crucial to securing financing. CMBS loans come with strict standards that properties must meet, guaranteeing they’re viable investments. Key performance criteria include: Strong net operating income (NOI) to demonstrate profitability Consistent occupancy rates, reflecting tenant demand and stability Extensive documentation to validate financial performance Suitability for stabilized, income-producing properties These requirements help lenders assess risk and guarantee the property can generate sufficient cash flow. Moreover, the non-recourse nature of CMBS loans limits your personal liability, making them appealing for long-term investors. Nonetheless, be mindful of potential prepayment penalties, which can deter early payoff unless you have a clear exit strategy in place. Bridge Loans Bridge loans serve as a valuable short-term financing option, typically ranging from 12 to 36 months, designed to provide quick access to capital during changeover periods in commercial real estate. These loans are often interest-only, allowing you to focus on managing cash flow during the acquisition or renovation of a property. The approval process is primarily asset-based, meaning lenders assess the property’s value and potential rather than your creditworthiness. As a borrower, it’s essential to have a clear exit strategy in place. This often involves refinancing, selling the property, or stabilizing it to secure long-term financing when the loan matures. Nonetheless, keep in mind that because of the higher risks associated with bridge loans, you’ll typically face higher interest rates compared to traditional financing options. Comprehending these factors can help you make informed decisions about using bridge loans in your commercial real estate endeavors. Construction Loans When financing a new construction project, grasping construction loans is pivotal for securing the necessary funds. These short-term financing options cover costs like land acquisition and construction expenses. Here are some key aspects to reflect on: Construction loans typically have variable interest rates and are disbursed in stages based on project milestones. A down payment of 20-30% of the total project cost is usually required. The loan term typically ranges from 6 months to 3 years, after which it converts to permanent financing. Lenders require thorough documentation, including a detailed budget and detailed plans, to assess project viability. Upon project completion, you can refinance your construction loan into a permanent mortgage, allowing for longer repayment terms and stable monthly payments. Grasping these elements will help you navigate the financing process effectively and guarantee your project stays on track. Commercial Refinance & Cash-Out Loans Grasping commercial refinance and cash-out loans is vital for property owners looking to optimize their financial strategies. Commercial refinance loans can replace existing loans to secure lower interest rates or modify terms, which often results in reduced monthly payments. Conversely, cash-out loans let you access built-up equity by refinancing your existing mortgage for a higher amount than owed, providing additional funds for various uses. To qualify for both refinance and cash-out loans, showing strong property performance through financial documents like operating statements and rent rolls is fundamental. It’s likewise important to evaluate transaction costs, such as closing fees and potential penalties for early repayment. Typically, you’ll need a minimum of 20% equity in the property, along with a favorable credit history and financial stability, to access these loan options effectively. Comprehending these elements can help you make informed financial decisions. Private Equity Financing and Equity Financing When you consider private equity financing and equity financing for commercial real estate, it’s critical to understand the different funding stages and investment structures involved. Private equity financing often targets large-scale projects and requires a solid business proposal, whereas equity financing allows you to raise capital by selling shares, reducing your debt burden. Both methods can offer high returns, but they come with varying levels of risk based on the project’s success. Funding Stages Overview Comprehension of the funding stages for commercial real estate projects is vital for developers seeking financial support. Grasping private equity financing and equity financing can greatly impact your project’s success. Here’s a quick overview: Private equity financing involves firms investing at various stages, expecting substantial returns. Equity financing allows you to raise capital by selling shares, reducing financial risk without debt. Investors in private equity deals typically want a share of profits, affecting ownership structures. Both financing types offer flexible terms, customized to your project’s needs and investor preferences. Crafting a strong business proposal is important, as investors will evaluate potential returns based on market conditions and project viability. Knowing these funding stages can help you secure necessary capital effectively. Investment Structure Differences Comprehending the differences in investment structures between private equity financing and equity financing is crucial for anyone involved in commercial real estate. Private equity financing typically attracts large investments from firms aimed at significant developments or acquisitions. These firms often seek strong business proposals and offer flexible terms customized to specific projects. Conversely, equity financing raises capital by selling shares in a property, allowing a broader range of investors to participate without incurring debt, which minimizes financial risks for borrowers. Whereas private equity demands higher returns because of perceived risks, equity financing can engage smaller investors through crowdfunding. Ultimately, private equity sources funds from institutional investors, whereas equity financing opens opportunities for various investors to partake in ownership. Frequently Asked Questions What Are the Different Types of Commercial Real Estate Loans? There are several types of commercial real estate loans you should know about. Owner-occupied mortgages serve businesses using their properties, whereas income-producing mortgages rely on tenant rent. Construction loans finance new developments but come with higher risks. Bridge loans offer short-term financing for immediate needs, and SBA loans provide flexible terms for purchasing properties. Finally, CMBS loans are pooled mortgages suited for stabilized properties, limiting personal liability to the collateral involved. What Are the 5 Cs of Commercial Lending? The 5 Cs of commercial lending are essential for evaluating your creditworthiness. First, character evaluates your credit history and reliability. Next, capacity measures your ability to repay the loan, often through cash flow statements. Capital refers to your equity investment, typically a 20-30% down payment. Collateral involves the property being financed, serving as security for the loan. Finally, conditions reflect the broader economic environment that might impact your repayment ability. What Are the 4 Cs of Commercial Lending? In commercial lending, the 4 Cs are essential for evaluating your creditworthiness. Credit evaluates your history and score, indicating repayment likelihood. Capacity measures your ability to repay, using cash flow statements and projected income. Capital reflects your investment in the project, demonstrating commitment through your down payment. Finally, collateral involves assets pledged against the loan, providing security for lenders if you default. Comprehending these elements can greatly impact your borrowing experience. What Are the Basics of Commercial Real Estate Lending? Commercial real estate lending involves financing properties used for business purposes, like offices or retail spaces. You’ll need to understand key metrics lenders assess, including loan-to-value (LTV) ratios, net operating income (NOI), and capitalization rates. Typically, loans range from 5 to 20 years, with amortization periods often extending longer. Different types of loans cater to specific needs, such as owner-occupied mortgages and construction loans, each customized to various risk profiles. Conclusion In conclusion, grasping the seven crucial types of commercial real estate loans is important for making informed financing decisions. Each loan type, from SBA loans to private equity financing, serves specific purposes and caters to different needs. Whether you’re seeking immediate funding or looking to refinance an existing property, knowing your options empowers you to choose the best solution for your situation. By evaluating these loans, you can effectively navigate the intricacies of commercial real estate financing. Image via Google Gemini This article, "7 Essential Types of Commercial Real Estate Loans to Know" was first published on Small Business Trends View the full article

Live translation is probably the most genuinely useful thing to come out of the AI boom, but if you want to use it during a phone call, you usually need to use a specific device or a separate app. T-Mobile is looking to change that. The carrier announced today that it will soon introduce live translation to all phones connected to its 5G or 4G networks, and to get in on the action, you're going to want to sign up for the beta now. According to a press release sent to journalists today, the new feature will kick in for you automatically once you're selected for it, no matter what phone app or device you use. All you'll need to do to access it is type in "87" on the keypad during a phone call. Which means that, yes, it will also be compatible with feature phones, aka classic-style flip phones with physical buttons. How T-Mobile live translation worksThe device you use doesn't matter because all of the computing for the translation will happen on T-Mobile's end, rather than on your device. The downside is that you won't get to pick which AI model the translation uses, and T-Mobile hasn't yet to provide any indication of which one it will use. You'll also just have to trust T-Mobile's servers with any audio recorded from your conversation. T-Mobile spokesperson Mason Miller told Lifehacker's sister site PCMag via email that, "[T-Mobile does] not save call recordings or transcripts," but the company will certainly ave to run your data through its servers at some point to make the feature work. By comparison, competing translation apps often rely on downloaded language packs and on-device models. Still, I see where T-Mobile is coming from with this offering: When live translation is limited to specific devices or apps, it vastly impacts its usability, since both callers need to have a compatible device for it to work. Processing translation over the cloud makes it more likely you'll be able to use it exactly when you need it—and as a bonus, only one caller will actually need to be on T-Mobile's 5G or 4G network to pull this trick off. While T-Mobile's press release focuses on 5G, the carrier confirmed availability for the feature on 4G to The Verge earlier today. The Verge also reports that, in addition to dialing 87, beta participants will eventually be able to trigger live translation by saying "Hey T-Mobile" instead. When T-Mobile live translations will go liveTesting for T-Mobile's live translation will begin "for selected users" this spring, with more general availability planned for "later this year." The feature will be free during the beta, although a surcharge might be added after it goes into wide release. "We will share more on pricing and plan details closer to commercial launch," Miller told PCMag. To sign up for the beta and put your hat in the ring for selection, head over to t-mobile.com/benefits/live-translation. View the full article

In her third annual letter, Vidhya Srinivasan, VP/GM of Ads & Commerce at Google, lays out how AI is transforming shopping and advertising in 2026 — making experiences faster, more personal, and more seamless for both consumers and businesses. Key trends: Creators to commerce: YouTube continues to be a discovery hub, with creators acting as trusted tastemakers. AI is helping match brands to the right creators, turning influence into measurable business impact. Search ads evolve: With conversational and visual queries on the rise, AI Mode is reimagining ads as part of the discovery journey. New formats, like sponsored retail listings and Direct Offers, aim to help users find products and services while giving brands meaningful ways to convert interest into sales. Agentic commerce arrives: Google is standardizing AI-driven shopping with the Universal Commerce Protocol (UCP), letting consumers browse, pay, and complete purchases seamlessly in AI Mode. Early rollouts include Etsy and Wayfair, with Shopify, Target, and Walmart coming soon. AI-powered creative and performance: Gemini 3 powers ad tools that automate creative production and campaign optimization. Generative tools like Nano Banana and Veo 3 let advertisers create studio-quality assets in minutes, while AI Max expands reach and drives performance. Trust as a foundation: All these experiences are designed with privacy and security in mind. Data handling, agent actions, and ad personalization are grounded in Google’s 25-year standards for consumer trust. Why we care. 2026 is shaping up as a pivotal year where AI turns every stage of the consumer journey into a seamless opportunity to connect. With AI-powered tools like Gemini 3, Nano Banana, Veo 3, and AI Mode, brands can create high-quality content faster, target the right audiences more precisely, and convert interest into purchases directly within search and discovery environments. The rollout of agentic commerce via UCP also opens new, integrated buying moments, letting advertisers meet consumers exactly when they’re ready to act — all while maintaining trust and transparency. The big picture: 2026 marks an expansionary moment for digital commerce and advertising — one where speed, personalization, and AI-driven insights remove friction, turning discovery into confident purchase decisions while keeping trust at the center. Dig Deeper. What to expect in digital advertising and commerce in 2026 View the full article

Federal Reserve Bank of Kansas City President Jeff Schmid said the US central bank should hold rates at a "somewhat restrictive" level, as he expressed continued concerns over inflation that remains too high. View the full article

The U.S. Food and Drug Administration is refusing to consider Moderna’s application for a new flu vaccine made with Nobel Prize-winning mRNA technology, the company announced Tuesday. The news is the latest sign of the FDA’s heightened scrutiny of vaccines under Health Secretary Robert F. Kennedy Jr., particularly those using mRNA technology, which he has criticized before and after becoming the nation’s top health official. Moderna received what’s called a “refusal-to-file” letter from the FDA that objected to how it conducted a 40,000-person clinical trial comparing its new vaccine to one of the standard flu shots used today. That trial concluded the new vaccine was somewhat more effective in adults 50 and older than that standard shot. The letter from FDA vaccine director Dr. Vinay Prasad said the agency doesn’t consider the application to contain an “adequate and well-controlled trial” because it didn’t compare the new shot to “the best-available standard of care in the United States at the time of the study.” Prasad’s letter pointed to some advice FDA officials gave Moderna in 2024, under the Biden administration, which Moderna didn’t follow. According to Moderna, that feedback said it was acceptable to use the standard-dose flu shot the company had chosen—but that another brand specifically recommended for seniors would be preferred for anyone 65 and older in the study. Still, Moderna said, the FDA did agree to let the study proceed as originally planned. The company said it also had shared with FDA additional data from a separate trial comparing the new vaccine against a licensed high-dose shot used for seniors. The FDA “did not identify any safety or efficacy concerns with our product” and “does not further our shared goal of enhancing America’s leadership in developing innovative medicines,” Moderna CEO Stephane Bancel said in a statement. It’s rare that FDA refuses to file an application, particularly for a new vaccine, which requires companies and FDA staff to engage in months or years of discussions. Moderna has requested an urgent meeting with FDA, and noted that it has applied for the vaccine’s approval in Europe, Canada, and Australia. In the last year, FDA officials working under Kennedy have rolled back recommendations around COVID-19 shots, added extra warnings to the two leading COVID vaccines—which are made with mRNA technology—and removed critics of the administration’s approach from an FDA advisory panel. Kennedy announced last year that his department would cancel more than $500 million in contracts and funding for the development of vaccines using mRNA. The FDA for decades has allowed vaccine makers to quickly update their annual flu shots to target the latest strains by showing that they trigger an immune response in patients. That’s a far more efficient approach than running long-term studies tracking whether patients get the flu and how they fare. In an internal memo last year, Prasad wrote that the streamlined method would no longer be permitted—leading more than a dozen former FDA commissioners to pen an editorial condemning the statements. —- The Associated Press Health and Science Department receives support from the Howard Hughes Medical Institute’s Department of Science Education and the Robert Wood Johnson Foundation. The AP is solely responsible for all content. —Lauran Neergaard and Matthew Perrone, Associated Press View the full article

This year, the number of mothers with young children exiting the U.S. labor market saw the sharpest January-to-June decline in more than four decades. That isn’t a coincidence—and it isn’t a lack of ambition. Across industries, women are reassessing how—and whether—work fits into their lives. Not because they want to step back, but because too many workplaces are still designed around outdated assumptions about who provides care and how work gets done. As leaders debate return-to-office mandates, women are quietly doing the math—and deciding whether staying is worth the cost. This isn’t a women’s issue. It’s a design failure. And it’s one leaders can choose to fix. THE PERPETUAL STRUGGLE OF THE DOUBLE SHIFT The pandemic exposed and intensified a long-standing dilemma: how working women can balance their careers with family demands. Even years later, in dual-income households, women continue to shoulder the majority of caregiving responsibilities, often juggling work, childcare, elder care, and the invisible but relentless mental load that comes with it. Even now, many women are still working two full-time jobs: one at work and another at home. In a recent workplace study conducted by my company, 65% of working mothers reported carrying more household and childcare responsibilities than their partners, and nearly half said they shoulder most of the mental and emotional burden at home. When workplaces remain rigid and unsupportive, that strain compounds, pushing women toward burnout or out of the workforce entirely. Now, rigid return-to-office (RTO) mandates threaten to add more fuel to the fire. For the first time since COVID, most Fortune 100 companies have reinstated full-time, in-office policies, and women are among the groups disproportionately affected. In our study, three out of four working women said RTO mandates make it harder for them to stay in the workforce long term. THE HIGH COST OF LOSING SENIOR FEMALE TALENT Supporting and retaining female talent isn’t only about equity; it’s about competitive advantage. While losing top-performing talent of either gender can hurt, when senior female leaders leave, there are broader financial and cultural ripple effects. The business case is well established: when women hold 30% or more executive roles within an organization, the company outperforms its peers. In a competitive labor market, the ability to attract and retain top talent—including highly educated, experienced women—can make or break a company’s growth trajectory. THE REDESIGN: FLEXIBILITY, SUPPORT, AND TRUST The solution isn’t another round of workplace perks. It’s redesigning work. I’m a strong believer in the value of coming together in person. Offices create connections and strengthen culture in ways that are hard to replicate remotely. They provide an environment for collaboration and problem-solving. But returning to the office can exacerbate the challenges many employees—especially caregivers—are navigating if not done thoughtfully. How work is structured matters just as much as where it happens. Flexibility isn’t about eliminating expectations or avoiding the office. It’s about trusting employees to manage their time responsibly and deliver results within a clear, well-designed framework. Our research shows that 90% of employees believe return-to-office policies—whether hybrid or full-time—are more successful when companies pair them with real support, including mental health resources, reasonable flexibility, and leaders who model balance and trust. I’ve lived this firsthand. For nearly a decade, I built an executive career while caring for my father through repeated ICU and hospital stays and critical illness. I was fortunate to have the support of my husband, friends, and family—but what made it truly possible was the flexibility and trust my managers extended to me during that time. That trust wasn’t given lightly; I earned it through commitment and performance. In return, their support during one of the hardest periods of my life made me fiercely loyal to my company and a stronger, more empathetic leader. Practical support matters just as much. Flexible time-off policies, backup care for emergencies, elder care resources, and mental health services aren’t perks—they’re infrastructure and are foundational to productivity, engagement, and loyalty. Companies invest millions in office space and technology. To truly benefit from those investments, they must also invest in systems that allow people to show up consistently, focused, and ready to do their best work. And this isn’t only about women. Forty percent of men now identify as their family’s primary caregiver. If organizations don’t support them as well, the imbalance many women experience will only grow. I know from my own life that even today, I couldn’t manage my work and family responsibilities without my husband’s partnership. BLUEPRINT FOR SUCCESS Companies face a clear choice: cling to outdated assumptions about work and risk losing talented women or evolve how they support work. Some organizations will operate in hybrid models; others will return fully to the office. The real differentiator won’t be the policy itself; it will be how thoughtfully leaders design and support work within it, especially for caregivers. Redesigning work doesn’t mean lowering standards. It means aligning expectations with how life actually works, and giving people the structure, support, and trust they need to perform at a high level. Workplaces built this way don’t just retain women—they build stronger cultures, develop better leaders, and outperform over the long term. Alison Borland is Chief People and Strategy Officer at Modern Health. View the full article

Google's VP of Ads & Commerce published her annual letter previewing agentic commerce updates, AI Mode ad expansion, and creator-brand matching tools for 2026. The post Google’s Ads Chief Details UCP Expansion, New AI Mode Ads appeared first on Search Engine Journal. View the full article

We may earn a commission from links on this page. Cooking can be a creative outlet, a way of showing affection, and a way to take control of your health. But cooking can also be stressful and time-consuming, especially on a weeknight when you're already exhausted from a long day at work and you've got a hungry family (or just yourself) to feed. Ordering in is always tempting, but that gets expensive and can have an adverse impact on your waistline. You might already have some of the more obvious and established time-saving appliances in your kitchen, but you can always shave a few more minutes and adrenaline spikes off your nightly cook. These kitchen gadgets will make cooking weeknight dinners easier no matter what the menu looks like. Snap-on strainers prevent you from dumping pasta in the sink If you have ever had a weeknight dinner go off the rails due to a pot of pasta accidentally dumped in the sink during a straining misadventure, know that snap-on strainers exist. Just pop one onto your pot, and you can easily strain without worrying about the dreaded dump out (or a fourth-degree burn from pasta water). These strainers are flexible and will fit just about any pot or pan you need to strain out of. An automatic pot stirrer will stir while you finish other tasksCooking is often a series of dull, repetitive tasks, and sometimes those tasks need to be performed simultaneously—so why not at least outsource all that pot stirring? This battery-operated device does just what it says: You place it in your pot or pan, press the button, and it stirs anything that needs it while you go and live your life (or chop vegetables). Uutensil Stirr - The Unique Automatic Pan Stirrer - With LED Speed Indicator, Red $38.95 at Amazon Shop Now Shop Now $38.95 at Amazon "Souper Cubes" help you better portion food to freeze for laterHere's a mistake I make over and over again when prepping sauces, stock, or soup for future dinners: I forget to divide it up before I pop it in the freezer. When it's time to make that weekday dinner, I have plenty of pre-made sauce—or, rather, I have too much of it, and I either defrost the whole bit and waste some or try hacking off a piece. Enter: Souper Cubes. These are like ice cube trays for food, and make it easy to freeze precise amounts of prepped or leftover food. Oven guards protect your hands from hot racks Anyone who cooks regularly has the minor wounds and scars to show for it—including the tell-tale burns from hurriedly grabbing stuff from a hot oven. Oven rack guards allow you to throw caution to the wind when pulling trays out of a crowded oven, even when reaching into a lower rack or grabbing something that's migrated to the rear of the oven. A self-stirring cooker lets you outsource most of the meal's workIf an automated pot stirrer is cool, a cooker that also stirs itself is even cooler. If your life goals include being able to make dinner every night while somehow doing other things, this is the kitchen appliance you need. It can cook a wide range of meals more or less on its own, and will stir meals automatically. Just load up your ingredients, set your parameters, and walk away. An automatic can opener saves time and effortCooking using canned ingredients is nothing to be ashamed of, but opening all those cans can be a chore that keeps you away from other cooking tasks. Enter the automatic can opener—just pop it on a can, press the button, and let it do its thing while you do literally anything more useful with your time. A warming mat will keep everything hot for youIf your dinner plans involve more than one dish, you know the stress of being on the clock when something is ready long before the rest of the meal. Serving up cold sides or sauces is no fun, so a warming mat like this is the answer. Just place dishes on it as they're ready and keep working on the balance of the meal, and everything will still be piping hot by the time you're ready to sit down. A divided skillet lets you cook multiple things at onceWe've all been there: You need to fry up several different things, but you only have one skillet. Your choice is to desperately cook and put aside each portion of the meal, or get yourself a divided non-stick skillet that makes it easy to cook several things simultaneously, speeding up your dinner process and ensuring that everything hits the table hot and ready. Master Pan Non-Stick Divided Grill/Fry/Oven Meal Skillet, 15", Black $65.59 at Amazon Shop Now Shop Now $65.59 at Amazon A "Thaw Claw" can speed up your defrosting processIf you're like me and you consistently forget to plan ahead when it comes to thawing out frozen ingredients ahead of time, you also know the struggle of trying to speed up the process. Submerging frozen meat in cold water is a proven way of speeding up the thawing process—unless your frozen goods just float to the surface. Enter the Thaw Claw, a simple device that clamps your frozen food to the bottom of your sink or bowl so it can defrost more quickly and effectively. Digital measuring spoons save you time on measuringSaving time when cooking dinner is all about accumulating small wins. The time spent weighing and measuring all the ingredients for your meal adds up, so having a digital measuring spoon can make the process faster and more efficient, since you won't have to place anything on a scale, adjust, and then use a separate implement to transfer it to your pots and skillets. Just measure as you scoop and keep moving. "Fry Away" disposes of oil or grease more easilyCleanup is part of the time and effort of any mid-week meal, and if you were tired before you started making dinner, you're not going to be less tired after eating. So make cleanup a little easier with Fry Away, which makes disposing of all that grease and oil a very simple process: Add some to hot oil or grease, let it cool, and then peel off the somewhat gross results and toss into the trash. Not having a jar of old oil sitting on the kitchen counter (or not calling a plumber to clean your drains if you're too lazy to have a jar of old oil on your kitchen counter) or needing to scrub away at a greasy pan? This is the way. View the full article

As consumers lean into AI search, the industry has focused on the technical “how” – tracking everything from Agentic Commerce Protocols (ACP) to ChatGPT’s latest shopping research tools. In doing so, it often misses the larger shift: conversational search, which is changing how visibility is earned. There’s a common argument that big brands will always win in AI. I disagree. When you move beyond the “best running shoes” shorthand and look at the deep context users now provide, the playing field levels. AI is trying to match user needs to specific solutions, and it’s up to your brand to provide the details. This article explains how conversational search changes product discovery and what ecommerce teams need to update on product detail pages (PDPs) to remain visible in AI-driven shopping experiences. How conversational search builds on semantic search While semantic search is critical for understanding the meaning and context of words, conversational search is the ability to maintain a back-and-forth dialogue with a user over time. Semantic search is the foundation for conversational visibility. Think of it like a restaurant: If semantic search is the chef who knows exactly what you mean by “something light,” conversational search is the waiter who remembers that you’re ordering for dinner. FeatureSemantic searchConversational searchGoalTo understand intent and contextTo handle a flow of questionsHow it thinksIt knows “car” and “automobile” are the same thingIt knows that when you say “how much is it?”, “it” refers to the car you just mentionedThe interactionSearching with a phrase instead of keywordsHaving a chat where the computer remembers what you were asking about beforeExampleAsking “What is a healthy meal?” and getting results for “nutritious recipes.”Asking “What is a healthy meal?” followed by “give me a recipe for that.” AI blends them together. It uses semantic understanding to decode your complex intent and conversational logic to keep the thread of the story moving. For brands, this means your content has to be clear enough for the “chef” to interpret and consistent enough for the “waiter” to follow. 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 What conversational search and AI discovery mean for ecommerce I recently shared how my mom was using ChatGPT to remodel her kitchen. She didn’t start by searching for “the best cabinets.” Instead, she leveraged ChatGPT as her pseudo-designer and contractor, using AI to solve specific problems. Product discovery happened naturally through constraint-based queries: “Find cabinets that fit these dimensions and match this specific wood type.” “Are these cabinets easy for a DIY installation?” Her conversations were piling up, allowing her to reach multiple solutions at once. Her discovery journey was layered. When ChatGPT recommended products to complete her tasks, she simply followed up with, “Where can I buy those?” Brands and marketers need to stop optimizing for keywords and start optimizing for tasks. Identify the specific conversations where your product becomes the solution. If your data can’t answer the “Will this fit?” or “Is this easy?” questions, you won’t be part of the final recommendation. “Recommend products” is the top task users trust AI to handle, highlighting a clear opportunity for brands, according to Tinuiti’s 2026 AI Trends Study. (Disclosure: I am the Sr. Director of AI SEO Innovation at Tinuiti.) For your brand to be the one recommended, your PDPs must provide the “ground truth” details these assistants need to make a confident selection. Dig deeper: How to make ecommerce product pages work in an AI-first world What to do before you start changing every PDP Step away from the keyword research tools and stop asking for “prompt volumes.” In an AI-driven world, intent is more important than volume. Before changing a single page, you need to understand the high-intent journeys your personas are actually taking. To identify your high-intent semantic opportunities: Audit your personas: Who is your buyer, and what are their non-negotiable questions? If you haven’t mapped these lately, start there. Bridge the team gap: Talk to your product and sales teams. They know the specific attributes and “deal-breaker” details that actually drive conversions. Listen to the market: Use sentiment analysis and social listening to find hidden use cases or brand problems. How are people actually using, or struggling with, your product in ways your brand team hasn’t considered? Map constraints, not keywords: Identify the specific constraints (size, compatibility, budget) that AI agents use to filter recommendations. How to build PDPs for AI search with decision support Your PDP should operate like a product knowledge document and be optimized for natural language. This helps an AI system decide whether to recommend the product for a specific situation. Name your ideal buyer and edge cases Content should support better decision-making. Audit your PDPs to determine whether they provide enough detail on who the product is best for – and not for. Does the page explicitly name your ideal buyer, their skill level, lifestyle constraints, and deal-breakers? AI shopping queries often include exclusions, and clearly outlining the important parts of your user search journey will help you understand where your products fit best. Cover compatibility and product specifications Compatibility feels synonymous with electronics (e.g., “Will my headphones connect to this computer?”). But think beyond one-to-one compatibility and expand into lifestyle compatibility: Is this laptop bag waterproof enough for a 20-minute bike ride in the rain, and does it have a clip for a taillight? Can I fit a Kindle and a book in this purse? Will this detergent work with my HE washer? Will this carry-on suitcase fit in the overhead compartment on every airline? Is this “family-sized” cutting board actually small enough to fit inside a standard dishwasher? People are searching for how products fit into their lifestyle needs. Highlight and emphasize the features that make your products compatible with their lifestyle. Dig deeper: How to make products machine-readable for multimodal AI search Get the newsletter search marketers rely on. See terms. Provide vertical-specific product guidance Breaking down your customer search journey and listening to your customers’ concerns, either through AI sentiment analysis, social listening, or product reviews, will help you understand what you need to be specific about. Apparel brands should add sizing and fit guidance. Maybe you’re comparing your size 10 jeans to competitors’ sizing, or considering sizing changes based on the cut or style of your other jeans. Beauty or skincare brands need ingredient combination details. Is this product compatible with other common formulas? Can I layer it over a vitamin C serum? Toy brands could include important details for parents. Does your product need to be assembled, and how long will it take? Can they assemble it the night before Christmas? If your biggest customer complaint is understanding when and how to use your products, you’re likely not making it easy enough for them to buy. Better defining your product attributes helps users and LLMs alike better understand your products. Write for constraint matching instead of browsing AI shopping discovery is driven by constraints instead of keywords. Shoppers aren’t asking for “the best laptop bag.” They’re asking for a bag that fits under an airplane seat, survives a rainy commute, and still looks professional in a meeting. PDPs should be written to reflect that reality. Audit your product pages to see whether they answer common “Can I …?” and “Will this work if …?” questions in plain language. These details often live in reviews, FAQs, or support tickets, but rarely surface in core product copy where AI systems are most likely to pull from. Here’s what transforming your content can look like: Traditional PDP copy Laptop backpack Water-resistant polyester exterior. Fits laptops up to 15″. Multiple interior compartments. Lightweight design. USB charging port. PDP copy written for constraints Laptop backpack Best for: Daily commuters, frequent flyers, and students who need to carry tech in unpredictable weather. Not ideal for: Extended outdoor exposure or laptops larger than 15.6″. Weather readiness: Water-resistant coating protects electronics during short walks or bike commutes in light rain, but is not designed for heavy downpours. Travel compatibility: Fits comfortably under most airplane seats and in overhead bins on domestic flights. Capacity and layout: Holds a 15-15.6″ laptop, charger, and tablet, with room for a book or light jacket – but not bulky items. Lifestyle considerations: Integrated USB port supports charging on the go (power bank not included). LLMs evaluate how well a product satisfies specific constraints in conversational queries or based on predetermined user preference information. PDPs that clearly articulate those constraints are more likely to be selected, summarized, and recommended. This type of copy should also help your on-site customers better understand your products. Dig deeper: Why ecommerce SEO audits fail – and what actually works in 30 days Technical foundations still matter for ecommerce Just because search platforms change doesn’t mean we should abandon everything we’ve learned in traditional optimization. Technical SEO fundamentals still heavily apply in AI search: Can crawlers access and index your site? Are your product listing pages (PLPs) and PDPs clearly linked and structured? Do pages load quickly enough for crawlers and users? Is your most critical content accessible? In conversational shopping, structured data is playing a different role than it did in traditional SEO strategies. In conversational shopping, it’s about verification. AI systems use your schema to validate facts before they risk reusing them in an answer. If the AI can’t verify your price, availability, or shipping details through a merchant feed or structured data, it won’t risk recommending you. Variant clarity is just as important. When differences like size, color, or configuration aren’t clearly defined, AI systems may treat variants as separate products or merge them incorrectly. The result is inaccurate pricing, incompatible recommendations, or missed visibility. Most importantly, structured data must match what’s visibly true on the page. When schema contradicts on-page content, AI systems avoid recommending uncertain information. Dig deeper: How SEO leaders can explain agentic AI to ecommerce executives 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 Owning the digital shelf in 2026 Success on the digital shelf has moved beyond high-volume keywords. In this new era, your visibility depends on how well you satisfy the complex constraints users can provide in a single search. AI models are scanning your pages to see if you meet specific, nuanced requirements, like “gluten-free,” “easy to install,” or “fits a 30-inch window.” The shift to conversational discovery means your product data must be ready to sustain a dialogue. The goal is simple: provide the density of information necessary for an AI to confidently transact on a user’s behalf. Those who build for these multi-layered journeys will own the future of discovery. View the full article

In the comment section on a recent letter from someone whose coworkers were upset about her work anniversary gift, there was a lot of discussion about corporate gift programs. I heard from a reader who works for one of the larger companies that organizes these programs, and they generously offered to answer questions about it. Here’s our interview. To start, what are these programs all about, and how do rewards and recognition companies like yours fit in? Rewards and recognition falls under the bigger HR tech umbrella. Other things under the umbrella include incentives, promotional items, wellness programs, payroll, benefits, and HRIS that does pretty much everything. Some companies manage all this stuff in-house with programs they’ve cobbled together, but there are software providers for all of them. Rewards and recognition (when done well!) helps companies build better cultures, decrease attrition, and improve employee engagement. The idea is, if you appreciate employees for their work regularly, they will be happier, more loyal, and more productive. Some vendor names you might find surprising: Tiffany’s used to offer service awards, Hallmark offered recognition before that part of the business was bought, Jostens owns a recognition company. Rolex used to be a very popular service award or retirement award, but a few years ago, they stopped doing B2B sales (it was diluting their brand). No recognition vendors can now offer Rolexes — and some companies find that very upsetting. The rewards and recognition industry tries to relieve the burden of administration from HR and automates the program flow, so its easy for employees to use. Rewards and recognition software generally has two components (and companies might do one or both): A. Performance recognition. This is focused on publicly recognizing employees for good work. A user can write up a note thanking a coworker for something (things like “thanks for covering while I was out” or “good job on that presentation”), attach an amount of points to that note, and then send it off. The note is then published on a feed so other coworkers can see it, like it, and comment on it. The points go into a bank, so users can save them up and redeem them from a catalog of items. B. Service awards. This recognizes employees for how long they have been with the company, usually starting at five years and every five years after. One of the easiest/most common approaches is a points deposit. Say you are celebrating five years at your company. On your anniversary, you would get an email that says something like, “Congrats on five years! Here’s to another five!” and a notification that 500 points have been deposited into your points bank. This could be a specific bank that now has 500 points for you to redeem in the catalog, or the points could be deposited into your recognition bank, so you can use your service award and recognition points together to redeem for something bigger. What challenges do you see companies run into most often with corporate gifts and rewards/recognition programs? I think the biggest challenge is a lack of commitment. There are all sorts of proven benefits to these types of programs (lowered attrition, improved business outcomes, etc.) and some companies think they can get those benefits by just purchasing a software. They don’t want to spend the time or money on creating a comprehensive strategy — and since every company culture is so different, you really need to make a strategy that focuses on what’s right for your specific organization. So instead, they end up wasting money on a platform that doesn’t get used, because no one knows it exists or how to use it. And because they’re not getting the ROI they want, they get mad and fire their vendor, move onto another one, and have the same issues because they won’t commit, all while losing money on the software shift and confusing any users who where engaging. Executive buy-in is also a big issue. I can’t tell you how many times a CHRO has been ready to sign a contract when the CEO comes in and shuts everything down. Along with that is making sure they stay bought-in. A lot of larger organizations with long-standing programs have started questioning the value of recognition programs. When the economy gets rough, this is usually one of the first things to get cut, as it seems extraneous. But companies who kept up with recognition during the pandemic saw improved morale and increased employee loyalty. What do you think are some of the “secrets of success” of the companies that do it well? 1. Communicating to employees not only that this program is available, but also offering info on the best way to use it. This might be paper guides, email reminders, formal training — whatever is best for that company’s culture. 2. Having a reasonable budget. Being stingy will make employees feel less appreciated than if there had been no recognition program at all! Healthcare is notorious for having tiny budgets. Imagine working endless shifts saving people’s lives and being thanked with nothing more than a branded pen. 3. Celebrating a variety of events. Not everyone will end up being recognized for everything, but celebrating different things with different types of rewards (company milestones, service awards, promotions, personal life events, department wins, company challenges, etc.) will give each employee more chances to feel appreciated. 4. Letting everyone send recognition. Some companies set their programs up so only managers can give recognition and/or points. So if your manager doesn’t see or hear about something great you did, you will never receive recognition for it. If peers can instead recognize each other, then the volume of recognition greatly increases. And so does employee goodwill! 5. Ensuring recognition doesn’t feel transactional. We all know the feeling when you receive a birthday card and it’s a bunch of signatures vs. receiving one with actual, thoughtful notes. Companies with expectations of how recognition should be done have more sincere interactions. For example, if their policy is to mail someone a plaque for the 10th anniversary, the item becomes just another thing to set on the shelf and forget about. But if they instead present the plaque in person to the celebrant, maybe along with a handwritten card from the manager or by sharing some achievements with the team (if the person enjoys being recognized publicly), then that plaque feels a lot more significant. Essentially, throw enough money at it that it makes an impact, but throw that money strategically. One thing that comes up over and over on Ask a Manager is that there’s no one gift that everyone will like (except for more money and time off!). As soon as one person mentions a gift that sounds amazing to them, someone else will be ready to let them know they’d hate it. How can companies navigate that thoughtfully? Offering a variety of options is the best way to do this. Let’s say the company is celebrating their hundred year anniversary. Rather than giving everyone the same branded jacket, the company could instead offer a few different types of jackets, maybe a vest and pullover, and then other things that could be branded, like a cooler, a Bluetooth speaker, a suitcase, an expensive blanket, etc. and throw in some things that aren’t branded at all! (I personally love a branded item, but I know many, many people hate it.) What’s something that’s surprised you about working in this field? And/or something that you think would surprise people outside of it to learn about? Receiving recognition points counts as reportable income, so you get taxed on it. Seeing that on your paystub without knowing why its there can be kind of upsetting (one of those things that I don’t think companies tell their employees about). It’s especially upsetting if it ends up being a burden on you, rather than your employer. That’s why R+R providers recommend organizations “gross up,” i.e. if you are awarded $100 of points, the company actually pays something like $140 for those points, so the employee receives the full $100 and the $40 goes to covering the income tax portion. Service/milestone awards have their own tax situations. In the U.S. and Canada, if a milestone award meets certain requirements, there is no income tax on it. Also, this industry is cutthroat, which is funny for an industry ostensibly focused on helping create positive employee experiences. The R+R industry is not super large and there’s maybe five really big players. Lots of employees move between these different companies, so plenty of company secrets get passed around. It is always funny when the executive of one company goes on LinkedIn and writes a rant about another company being mean to them, or stealing their idea, or spreading rumors. It happens more than you would expect! When you say companies run into trouble because they don’t commit to a good strategy, what does that look like in reality (when it’s done well and when it’s done badly)? First, most important thing: recognition cannot be used as a substitute for a living wage, raises, bonuses, or benefits. You have to first make sure you are adequately providing those things, or else spending money on recognition (especially when your employees are paycheck to paycheck) is only going to breed resentment. Signs a company has a good strategy in place: Users know how to access the software and use it regularly Can find worthwhile items to redeem for in the catalog Career anniversary gifts/trophies become a point of pride, rather than a useless tchotchke Employee satisfaction scores usually increase Signs a company has a bad/no strategy in place: Users don’t know about the software or can’t access it easily Limited users can send recognition Budgets are so low that recognition points are quickly spent Point values or gift options are so low that it is offensive There is no company culture around recognition, so people feel disappointed when their work is not recognized or their anniversary goes by without comment Career anniversaries are non-existent or don’t start for a long time, like year 10 There are no regular notifications nudging employees to take action, such as giving recognition, approving recognition, or redeeming points (companies like to turn these off) Holidays, employee appreciation day, and company milestones are not celebrated Example of bad strategy: My sister was at her job for three years before realizing she’d received hundreds of points she could redeem. There was no communication on the software (that it existed, how to access it, or how to use it). Giving recognition is limited to managers and above. Since she works different hours from her manager, they rarely saw her work and thus could not recognize it in person. For her first anniversary, she received a tiny bonus and doesn’t know what people receive on other anniversaries. The company is spending money on this software, but probably receiving very little ROI. In this case, they’d probably have better ROI if they forewent the software and gave that money directly to employees via raises, increased PTO, or better benefits. You mentioned stingy gifts, and I hear about this all the time (like a hospital that gave its doctors hospital socks for Christmas or a company that gave everyone “cheaply-printed gratitude journals” during Covid). Any insight into what these companies are thinking?! It seems like it should be obvious that really cheap gifts are going to harm morale more than if they did nothing at all. I think this is the same mindset that leads to giving overworked employees a pizza party rather than rewarding them with bonuses. It’s that paternalistic “They should be grateful for anything I give them” sort of feeling. The people making these decisions can be very out of touch about what actually matters to employees. How to fix that? When coming up with the recognition strategy, companies should involve employee feedback (surveys, focus groups, town halls, etc). They should also keep doing this (some vendors have features to help with this) throughout the program and adjusting as needed. You recommended letting peers send recognition. Do companies worry that if they set it up that way, people will abuse it? Does that ever happen in reality? Yes, they worry about abuse, and no, it doesn’t really happen that often. There’s ways to flag if recognition looks suspicious; you can put checks in place like all recognition has to be approved by a manager, and you can put caps on how much recognition people can give and/or receive. I think this worry comes from that same mentality that leads to sick leave policies requiring a doctor’s note; some employers think their employees are unruly children that need to be managed with a firm hand rather than responsible adults you can trust. Does your company do amazing employee gifts for you and your coworkers? I feel like the expectations must be very high! My company loves doing gifts. There are some events that have the same gift every year, but they go all in for big milestone events. There was a large anniversary a few years before I started and people still talk about the items they got. One person uses the collapsible wagon they ordered all the time, and I am jealous whenever they wheel it into the office. They really commit for service awards, and I’ve never heard anyone complain about their experience. They also do gifts for Employee Appreciation Day, and sometimes they miss the mark, but the gesture is always appreciated. I have received more water bottles than anyone could possibly need, but they’re always high-quality, so I can always find a friend or family member who would like one. The post interview with someone who works in the corporate gifts industry appeared first on Ask a Manager. View the full article

In a conversation on the OpenAI podcast, host Andrew Maine spoke with OpenAI executive Assad Awan, who detailed how ads will roll out in ChatGPT, who will see them and how the company plans to protect user trust. Who will see ads: Ads will appear for Free and Go tier users Plus, Pro and Enterprise subscribers won’t see ads Enterprise workspaces will remain fully ad-free The guardrails: Awan emphasized that OpenAI is structuring ads around strict trust principles: Separation: Ads are visually and technically separate from model answers Privacy: Conversations aren’t shared with advertisers Sensitive topics: Health, politics and other sensitive chats won’t show ads Controls: Users can adjust or turn off personalization — or upgrade to remove ads According to Awan, the model itself doesn’t know when ads are present and can’t reference them unless a user explicitly asks about one. Zoom in. OpenAI internally prioritizes user trust over user value, advertiser value and revenue, Awan said — a framework meant to prevent ads from shaping how the model responds. For small businesses. Awan described a future where AI acts as an advertising agent, helping small businesses run campaigns by describing goals in plain language rather than managing complex dashboards. Why we care. ChatGPT ads could open a new, high-intent channel where businesses reach users during active conversations and decision-making moments. The platform’s focus on relevance, AI-driven matching and agent-style campaign tools could lower the barrier to entry for small and midsize advertisers while improving performance for larger brands. If OpenAI succeeds in building a trusted ad environment, it may reshape how advertisers think about discovery and customer engagement in AI-driven interfaces. What’s next. Early ad tests will be conservative, focusing on usefulness and relevance over volume as OpenAI refines formats and placement. The big picture. Through advertising, OpenAI is aiming to scale ChatGPT access while maintaining a trust-first design — a balance the company says is central to its long-term strategy. Dig deeper. Watch full interview with Assad Awan View the full article