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A reader writes: I was offered a job last week, which was going to require a 2.5-hour move. I accepted as it’s a field I love and a company ownership I had worked for previously, just not at this location. Yesterday the job fell through because the expected job salary budget didn’t come through. At all. I had been waiting on paperwork to 100% make my hiring official. I even had a start date, which had been reiterated last week when they were waiting for the national leadership to send over the papers. I am lucky that I was able to reverse my resignation at my current job. I’m also lucky that I figure I’m only out about $100. I had applied for and been accepted for an apartment but hadn’t signed a lease or even set up a moving truck. Since I am not out much, I am naturally going to move on and merely grouse about the experience (they only let me know with a single text that the position was canceled!). But could I have had any recourse had I been out more money? Oh no. As a general rule, it’s best never to give notice at your existing job until the new job is 100% official, meaning that any paperwork has been signed and all contingencies are removed. Even then, something like this can still happen, but waiting lowers the risk of it. As for legal recourse if you had been out more money or if you had actually moved: in most states you wouldn’t have legal recourse unless you could show the employer had operated with deliberately fraudulent intent. There is a legal concept called “detrimental reliance,” where you would argue that you had relied on their offer to your detriment. Generally, though, courts mostly haven’t sided with those claims (largely because since employment is at-will, you also could have been fired on your first day without legal resource). That said, if you ever were in a situation where you were out a significant sum of money — or if you had already moved — it could be useful to talk with an employment lawyer to get their take. An additional option you’d have in that situation would be to tell the employer that you’d relied on their offer and start date in good faith and lost $X as a result, and ask them to make it right. Their offer might have used language that would protect them from any legal obligation to make you whole (especially if it was clear things were not yet finalized), but it would be reasonable to try. The post my job offer fell through after I’d already resigned (and when I was about to move) appeared first on Ask a Manager. View the full article

As the SaaS market reels from a sell-off sparked by autonomous AI agents like Claude Cowork, new data shows a 53% drop in AI-driven discovery sessions. Wall Street dubbed it the “SaaSpocalypse.” Whether AI agents will replace SaaS products is a bigger question than this dataset can answer. But the panic is already distorting interpretation, and this data cuts through the noise to show what SEO teams should actually watch. Copilot went from 0.3% to 9.6% of SaaS AI traffic in 14 months From November 2024 to December 2025, SaaS sites logged 774,331 LLM sessions. ChatGPT drove 82.3% of that traffic, but Copilot’s growth tells a different story: SaaS AI Traffic by Source (Nov 2024 – Dec 2025) SourceSessionsShareChatGPT637,55182.3%Copilot74,6259.6%Claude40,3635.2%Gemini15,7592.0%Perplexity6,0330.8% Starting with just 148 sessions in late 2024, Copilot grew more than 20x by May 2025. From May through December, it averaged 3,822 sessions per month, making it the second-largest AI referrer to SaaS sites by year-end 2025. Investors erased $300 billion from SaaS market caps over fears that AI agents will replace enterprise software. But this data points to a less dramatic force: proximity. Copilot thrives because it captures intent inside the workflow. Standalone tools saw a 53% traffic drop while workplace-embedded AI grew 20x. Software evaluation is work, and Copilot sits where that work happens. When someone asks, “What CRM should we use for a 20-person sales team?” while building a business case in Excel, that moment is captured—one ChatGPT never sees. The May surge reflects that activation: Microsoft 365 users realizing they could research software without opening a new tab. 41.4% of SaaS AI traffic lands on internal search pages SaaS AI discovery sends users to internal search results first, not product pages. Top SaaS Landing Pages by LLM Volume Page TypeLLM Sessions% of AI TrafficPenetration vs Site AvgSearch320,61541.4%8.7xBlog127,29116.4%8.1xPricing40,5035.2%3.2xProduct39,8645.1%2.0xSupport34,5994.5%2.1x Despite capturing 320,615 sessions — more than blog, pricing, and product pages combined — this dominance likely reflects LLM limitations, not superior content. LLMs route users to search when they lack a specific answer. For SaaS companies watching their stock crater, that’s useful news: there’s a concrete technical fix. The 41.4% isn’t an existential threat. It’s a crawlability problem. When an LLM can’t find a direct answer, it defaults to the site’s internal search. The AI treats your search bar as a trusted backup, assuming the search schema will generate a relevant page even if a specific product page isn’t indexed. At 1.22%, search page penetration is 8.7x the site average. The cause is a “safety net” effect, not optimization. When more specific pages — like Product or Pricing — lack the data an LLM needs, it falls back to broader search results. LLMs recognize the search URL structure and trust it will return something relevant, even if they can’t predict what. Blog pages follow with 127,291 sessions and 1.13% penetration. These are structured comparison posts — “best CRM for small teams” or “Salesforce alternatives” — that LLMs cite when they have specific recommendations. Pricing pages show 0.45% penetration; product pages, 0.28%. When users ask about software selection, LLMs route to comparison surfaces — search and blog — first. Direct product or pricing pages get cited only when the query is already vendor-specific. The July peak and Q4 decline reflect corporate work cycles SaaS AI traffic peaked in July at 146,512 sessions, then declined steadily through Q4: MonthSessionsChangeJuly 2025146,512PeakAugust 2025120,802-17.5%September 2025134,162+11.1%October 2025135,397+0.9%November 2025107,257-20.8%December 202568,896-35.8% Every platform declined. ChatGPT’s volume was cut in half, dropping from 127,510 sessions in July to 56,786 by year-end. Copilot fell from 4,737 to 2,351. Perplexity dropped from 7,475 to 3,752. Two factors drove the slide: People weren’t working. August is vacation season, November includes Thanksgiving, and December is the holidays. Software research happens during work hours; when offices close, discovery drops. Q4 ends the fiscal “buying window.” Most teams have spent their annual budgets or are deferring contracts until Q1 funding opens. Even teams still working aren’t evaluating tools because there’s no budget left until the new fiscal year. The July peak reflects midyear momentum: people are working, and Q3 budgets are still available. The Q4 decline reflects both fewer researchers and fewer active buying cycles. This is where the sell-off narrative breaks down. Investors treat a 53% traffic drop as proof that AI discovery is stalling. But the data aligns with standard B2B fiscal cycles. AI isn’t failing as a discovery channel. It’s settling into the same seasonal rhythms as every other B2B buying behavior. What this data means for SEO teams Raw traffic numbers don’t show where to invest. Penetration rates and landing page distribution reveal what matters. Track penetration by page type, not site-wide averages SaaS shows 0.41% sitewide AI penetration, but that average hides concentration. Search pages reach 1.22%—8.7x higher. Blog pages hit 1.13%. Pricing pages are at 0.45%. Product pages lag at 0.28%. If you’re only tracking total AI sessions, you’re measuring the wrong metric. AI traffic could grow 50% while penetration on high-value pages declines. Volume hides what matters: where AI users concentrate when they arrive with intent. Action: Segment AI traffic by page type in GA4 or your analytics platform. Track penetration (AI sessions ÷ total sessions) by page category monthly. Identify pages with elevated concentration, then optimize those surfaces first. Search results pages are now a primary discovery surface Internal search captures 41.4% of SaaS AI traffic. If those results aren’t crawlable, indexable, or structured for comparison, you’re invisible to the largest segment of AI-driven buyers. Most SaaS sites treat internal search as navigation, not content. Results return paginated lists with minimal product detail, no filter signals in URLs, and JavaScript-rendered content LLMs can’t parse. Action: With 41.4% of traffic hitting internal search, treat your search bar as an API for AI agents. Make search pages crawlable (check robots.txt and indexability). Add structured data using SoftwareApplication or Product schema. Surface comparison data — pricing, key features, user count — directly in results, not just product names. Make your data legible to LLMs — pricing and content both The sell-off is pricing in obsolescence, but for most SaaS companies the real risk is invisibility. Pricing pages show 0.45% AI penetration—below the 0.46% cross-industry average. Blog pages captured 127,291 sessions at 1.13% penetration, but only when content directly answered selection queries. The pattern is clear: LLMs cite what they can read and parse. They skip what they can’t. Many SaaS sites still gate pricing behind contact forms. If pricing requires a sales conversation, AI won’t recommend you for “tools under $100/month” queries. The same applies to blog content. When someone asks, “What CRM should I use?” the LLM looks for posts that compare options, define criteria, and explain tradeoffs. Generic thought leadership on CRM trends doesn’t get cited. Action: Publish pricing on a dedicated, crawlable page. Include representative examples, seat minimums, contract terms, and exclusions. Keep pricing transparent. Transparent pages get cited; gated pages don’t. Replace generic blog posts with structured comparison pages. Use tables and clear data points. Remove fluff. Provide grounding data that lets AI verify compliance and integration capabilities in seconds, not minutes. Workplace-embedded AI is growing 10x faster than standalone LLMs Copilot grew 15.89x year over year. Claude grew 7.79x. ChatGPT grew 1.42x. The fastest growth is in tools embedded in existing workflows. Workplace AI shifts discovery context. In ChatGPT, users are explicitly researching. In Copilot, they’re asking questions mid-task—drafting a proposal, building a comparison spreadsheet, or reviewing vendor options with their team. Action: Track Copilot and Claude referrals separately from ChatGPT. Monitor which pages these sources favor. Recognize intent: these users aren’t browsing — they’re mid-task, deeper in evaluation, and closer to a purchase decision. Show up in workplace AI discovery to support real-time purchase justification. Survival favors the findable The 53% drop from July to December reflects AI usage settling into the software buying process. Buyers are learning which decisions benefit from AI synthesis and which don’t. The remaining traffic is more deliberate, concentrated on complex evaluations where comparison matters. For SaaS companies, the window for early positioning is closing. The $300 billion sell-off is hitting the sector broadly, but the companies that survive the repricing will be those buyers can find when they ask an AI agent, “Should we renew this contract?” Teams investing now in transparent pricing, crawlable data, and comparison-focused content are building that findability while competitors debate whether AI discovery matters. View the full article

The 30-year fixed-rate mortgage averaged 6.09% Thursday, down two basis points from last week, while the 15-year rate fell to 5.44%, according to Freddie Mac. View the full article

Money feels manageable when you can actually see where it’s going. Instead of guessing at the end of the month, a personal budget template gives you structure, clarity and a simple way to stay in control. Whether you’re planning weekly spending or mapping out long-term savings, the right tool turns scattered numbers into a clear financial picture. What Is a Personal Budget Template? A personal budget template is a structured spreadsheet designed to help someone record income, track expenses and compare the two over a specific period of time. It organizes financial information into categories such as housing, groceries, utilities and discretionary spending, allowing you to see how money flows in and out on a daily, weekly or monthly basis. By laying everything out in one place, it becomes easier to identify spending patterns, adjust habits and maintain financial balance. Why Use a Personal Budget Template for Excel Using a personal budget template for Excel makes the budgeting process faster and more accurate because much of the calculation work happens automatically. Built-in formulas total income, sum expense categories and instantly show the difference between what you earn and what you spend. The following personal budgeting templates are fully customizable, you can adjust categories, timeframes and formatting to match your financial situation, turning a basic spreadsheet into a practical, personalized budgeting system. 5 Personal Budget Templates Some people want a simple split they can follow every month, while others need a personal budgeting template with a tighter breakdown that shows exactly what’s left after spending. These five personal budget templates make that process easier by turning your income into clear spending limits and then tracking how your real expenses stack up. 1. 50/30/20 Budget Template To use this personal budget template for Excel, start by filling in the small table at the top with your name and monthly income, then let the spreadsheet do the heavy lifting. As soon as that income number is entered, the template automatically divides it into three preset buckets: 50% for needs, 30% for wants and 20% for savings. With those targets set, you enter your actual expenses under each category. /wp-content/uploads/2025/03/50-30-20-template.png Once the expense lines are filled out, the template automatically totals spending for needs, wants and savings, then calculates the difference between the amount allocated to each bucket and what you actually spent, revealing your remaining balance for each category. 2. 70/20/10 Budget Template This personal budgeting template for Excel follows the exact same workflow as the 50/30/20 version, but it uses a different split to reflect a more expense-heavy or goal-driven budget. You begin by entering your name and monthly income in the top table, and the spreadsheet automatically allocates that income into three categories: 70% for living expenses, 20% for financial goals and 10% for fun and lifestyle spending. /wp-content/uploads/2026/01/70-20-10-Template-featured-image.png After that, you input your expenses under each bucket. The template then adds up the expenses per category and calculates the difference between each category’s income allocation and its total expenses, so you can immediately see the balance remaining for living expenses, financial goals and fun. 3. Weekly Budget Template Everything begins at the top of the sheet, where you enter your name and monthly income. As soon as that monthly figure is added, this personal budget template for Excel automatically divides it by four to calculate your available weekly budget. Just below, you define the four specific weeks you’re planning for by entering date ranges, such as “Week 1 (1/4/2026 – 1/10/2026),” so each period is clearly framed. /wp-content/uploads/2026/02/weekly-budget-template-scaled.png From there, the weekly amount is automatically divided by seven to determine your daily available budget. That daily limit is structured using a 50/30/20 split for needs, wants and savings. Once you begin entering daily expenses, the spreadsheet compares them against the calculated daily and weekly targets, making it immediately clear whether you’re staying within limits or gradually exceeding them. 4. Zero-Based Budget Template Every month starts from zero with this zero-based budget template, which helps you assign your entire income to specific expense categories before spending begins. Simply enter your monthly income and planned expenses, and built-in formulas automatically total your spending and calculate the balance. Adjust allocations until income minus expenses equals zero, ensuring every dollar has a clear purpose. /wp-content/uploads/2026/02/Zero-based-budget-template-600x509.png How to Make a Project Budget with ProjectManager A personal budget template for Excel is a useful tool for personal finance management, but if you’re interested in making a budget for your personal or professional projects, use ProjectManager instead. ProjectManager is designed to create detailed project budgets. Simply make a list of project tasks using the list, sheet or Gantt chart view, allocate resources such as people, materials or equipment and estimate their costs. Then, establish a budget amount. Once the project starts, enter actual project costs and ProjectManager will automatically calculate the difference between estimated costs and actual costs and will display this information in real-time dashboards and reports so you can check whether the project costs are exceeding the budget at a glance. Watch the video to learn more! Related Personal Budgeting Content How to Make a Budget Plan for Personal Finance Management How to Prioritize Tasks With Personal Kanban Boards 4 Steps to Personal Time Management 18 Budget Templates for Business & Project Budgeting Project Budget Tracking: A Step-by-Step Guide What Is a Budget Report? Purpose, Components & Benefits Manage a Project Budget with Project Budgeting Software What Is a Business Budget? Business Budgeting Basics The post 5 Personal Budget Templates for Excel (Free Download) appeared first on ProjectManager. View the full article

It's once again time to update your Apple devices. The company just released a whole host of security patches, including a fix for an actively exploited zero-day affecting iOS 26, iPadOS 26, and macOS Tahoe. These updates arrived alongside the official release of iOS 26.3, which includes features like more seamless data transfer between iPhone and Android. Other security patches address bugs in Photos, VoiceOver, and Screenshots, to name a few. iOS 26.3 patches a zero-day affecting dyldAccording to Apple's latest security bulletin, the zero-day—tracked as CVE-2026-20700—is a memory corruption issue in dyld, Apple's "Dynamic Link Editor." The flaw could allow attackers with memory write capability to execute arbitrary code—or, in other words, run their own code on your device. Apple says that the vulnerability may have been exploited in an "extremely sophisticated attack against specific targeted individuals" in earlier versions of iOS alongside CVE-2025-14174 and CVE-2025-43529. Those at greatest risk with this bug are likely high-profile users with access to sensitive data—users who might be inclined to use Apple's Lockdown Mode—but everyone should install the update to patch the issue. The patch for this flaw is available for the following iOS and iPadOS devices, in addition to all Macs that run macOS Tahoe: iPhone 11 and later iPad Pro 12.9-inch 3rd generation and later iPad Pro 11-inch 1st generation and later iPad Air 3rd generation and later iPad 8th generation and later iPad mini 5th generation and later How to install the latest security update for iPhoneYou should have automatic updates enabled to ensure you receive critical security patches ASAP, but you can confirm that you're on the latest OS version under Settings > General > Software Update. As a reminder, Apple won't message you urging you to click links, download attachments, or install apps related to security updates. Always go through your device settings to receive official fixes. View the full article

A House subcommittee hearing discussing the future of the government-sponsored enterprises, noted both are still severely undercapitalized. View the full article

The company formerly known as Ocwen confirmed that a deferred tax asset valuation helped boost net income to common shareholders despite servicing challenges. View the full article

If you're an Apple fan who closely follows tech news, you might have been looking forward to Siri's big AI overhaul for some time now—specifically, since the company initially announced it at WWDC 2024. But despite delay after delay, rumors have strongly suggested that the next generation of Siri is set to launch with iOS 26.4. And seeing as Apple just released iOS 26.3 this week, AI Siri is closer than ever, right? Wrong. As reported by Bloomberg's Mark Gurman, Apple has once again kicked Siri's big updates down the road. According to Gurman, the company really did intend to release AI Siri with iOS 26.4, which is reportedly planned to release sometime in March. However, due to testing "snags," the company is instead planning to break up Siri's major updates and distribute them across several iOS updates. Gurman notes that likely means iOS 26.5, which could launch in May, and iOS 27, which will likely release in September, if it follows Apple's usual release dates. But looking at Apple's track record here, don't hold your breath. AI Siri's upcoming features are a struggleAccording to Gurman's sources, Apple is struggling to get Siri to "properly process queries," or to actually respond fast enough, both of which would defeat the purpose of using a smart assistant. Apple is reportedly pushing engineers to use iOS 26.5 to test these features, particularly the ability for Siri to use your personal data to answer questions. Users may be able to flip a switch in Settings to "preview" these features, and may treat the rollout as a beta. Engineers are also struggling to get Siri's app intents to work, or the feature that lets Siri take actions on your behalf. You could ask Siri to open an image, edit it, then share it with a friend, but only if the feature itself actually works. This, too, may roll out with iOS 26.5, but it's unclear due to reliability issues. Siri is also cutting off user prompts too soon, and sometimes taps into ChatGPT instead of using Apple's underlying tech—which would look pretty bad for the company. Apple is also testing new AI features for iOS 26.5 that we haven't heard of yet. One is a new web search tool that functions like other AI search features from companies like Perplexity and Google. You ask a question to search on the web, and it returns a report with summaries and links. The other new feature is a custom image generation tool, that builds on Image Playground, but that too is hitting development hurdles. Looking even further ahead, Apple is planning more Siri advancements—namely, giving the assistant chatbot features, à la ChatGPT. (That said, it will reportedly use Gemini to power these features.) This version of Siri may even have its own app. What's going on with AI Siri?It seems Siri really is Apple's albatross. Despite arguably popularizing smart assistants for the general population, Siri quickly fell behind compared to the likes of Alexa and Gemini (née Google Assistant). Now, the latter have fully embraced modern generative AI, offering features like contextual awareness and natural language commands. While Amazon and Google users can ask their assistants increasingly complicated questions, Siri still feels designed mostly to handle setting alarms and checking the weather. That was going to change with iOS 18, alongside Apple Intelligence as a whole. Apple's initial pitch for AI Siri was an assistant that could see what's on your phone to better understand questions you ask, and take actions on your behalf—i.e., app intents. You could ask Siri to edit an image you have pulled up on your Photos app, and because the assistant is contextually aware, it would know what image you mean, and apply the edits you ask for. Or, you could ask when your friend was set to arrive, and the assistant would be able to scan messages and emails to know that, one, your friend is visiting town this weekend, and two, that they sent you their flight itinerary that gets them into the airport at 3:55 p.m. This Siri has never launched, however. While the company has rolled out iterative updates to Siri with some AI-powered features, its overhaul with these ambitious features have been a trial for Apple's AI team. It all stems from Apple's issues with AI in general: The company was caught off guard by the generative AI wave kicked off in late 2022 by OpenAI's ChatGPT, and following some resistance from corporate leadership, have been scrambling to keep up ever since. Apple Intelligence launched half-baked with issues of its own, but rather than launch a half-baked AI Siri, the company has been struggling to build up the assistant internally. Part of the problem is privacy-related: Unlike other tech companies, who have no problem hoovering up user data to train their models with, Apple still wants to preserve privacy while rolling out AI features. As such, that complicates their situation, as they need to ensure both the hardware and software involved meet those standards. You can't have Siri pull user data into the cloud without strict security measures if you want to ensure your users' data remains private. The company is also focused on building its own hardware for cloud-based AI processing, rather than focus on simply buying up GPUs as many other companies have. Apple is the second most valuable tech company in the world, but a host of factors—including with software, hardware, and leadership—have made it so even Apple can't magically produce an AI assistant. Though, I'm not sold that an AI Siri will move units for Apple in the first place. I can't imagine Gemini moves people to Android, and you can download ChatGPT on any device you own. It's even now built into your iPhone. View the full article

Think about how many emails you receive each day. Then how many of those include the phrase “please find attached” in the body. One X user has made a plea to retire the phrase, a relic leftover from a time when business communication relied on typewritten letters posted in envelopes, which actually included attached documents to be found. The post quickly went viral, gaining nearly 15 million views since it was posted earlier this week. While the user doesn’t elaborate why exactly they personally take issue with the phrase, or what to say instead, the post had the desired effect, with many weighing in with their own takes on modern email etiquette. Some agreed that the phrase is stuffy and outdated. “‘Please find attached’ adds zero information, sounds robotic, and does not respect the reader’s time,” one wrote. “‘Here’s the file’ does the job better than a sentence that adds zero information,” another added. It’s true, these days email attachments are instantly accessible, clearly marked, and don’t require a physical search. While young workers have no qualms including memes, emojis, slang, and abbreviations in their emails, and despite nearly one in four employees now using AI to help write emails, “please find attached” has somehow slipped through the net. Others staunchly defended the use of the tried-and-tested phrase. “But if I don’t type those magic words, how will Outlook know to warn me when I inevitably forget to actually attach the file?” one wrote. “Baby, no,” another added. “The people are stupid.” Many of us are trapped in a terminal cycle of “reaching out” and “circling back”, with dozens of corporate buzzwords and phrases that some argue make smart people sound less intelligent. But if you’re in the market for some more creative ways to signal there’s a PDF attached that needs attention, the replies to the X post is a goldmine. “Behold, the attachment,” one X user suggested as an alternative. For a sinister edge, “‘There are attachments in this email with us right now’,” another put forth, or “‘Watch out for the attachment below’.” Feeling pumped about the PDF attached? “Get a load of this MF attachment,” is another option. Or alternatively, feeling deflated? “Find attached, if you even care” works here. And if you’d rather the receiver doesn’t open the attachment, you could simply put: “‘Please don’t find attached’,” one wrote. “‘It’ll only be more work for us both’.” View the full article

Over the years, we’ve had many letters about animals at work. Here are some of them. my employee doesn’t think we’re doing enough about bears at work (and the update) people only ask me about the ducks I work with (with a video in the update!) the pumpkin-eating cat my office got us turtles to take care of and bring home on weekends my office is infested with wasps our building is full of bats, sewer smells, moths, and more an unexpected office bird how much can I pet my cat on video calls? (and the update) my colleague is allergic to me because of my cats actual llamas head of HR is waging a pressure campaign to make me adopt a puppy my VP of HR says my service dog is too small (and the update) I bring my dog to work — but an anonymous note asked me not to my company wants to sponsor me for a service dog, but I’m not sure I should accept (and the update) my boss’s dog rampages through our work gatherings the secret goat, the geese vs the CEO, and other stories of animals at work here are animals taking over home offices here are your animal coworkers (and part 2) the cats of AAM And we’ve had so many letters involving dogs at work (not all included above) that I created a whole new tag just for them. The post animals at work appeared first on Ask a Manager. View the full article

A mobile loyalty program is a digital solution designed to reward your repeat business through a smartphone app. It enables you to earn points with each purchase, track your rewards in real-time, and receive customized offers through notifications. This system eliminates the need for physical cards, simplifying your shopping experience. Comprehending how these programs function and their impact on customer retention can reveal significant advantages for both consumers and businesses alike. Key Takeaways A mobile loyalty program is a digital rewards system that enhances customer retention through mobile apps, allowing users to earn points for purchases. Customers can track their rewards in real-time, eliminating the need for physical loyalty cards and simplifying the shopping experience. Personalized offers and promotions are delivered via push notifications, increasing engagement and enhancing the perceived value of the loyalty program. Gamification features, such as challenges and badges, encourage user interaction and competition, making the experience more engaging. Data analytics informs marketing strategies, enabling personalized offers and optimizing customer satisfaction based on purchase patterns and behaviors. Understanding Mobile Loyalty Programs Mobile loyalty programs have become an important tool for businesses aiming to improve customer retention and brand loyalty. These programs leverage mobile technology to reward customers for their repeat purchases and engagement, often through a dedicated app. For instance, a gas rewards app allows you to earn points or discounts every time you fuel up, making gas station loyalty programs more appealing. With about 80% of consumers making purchases via mobile platforms, these apps offer real-time tracking of points and rewards, so you can easily check your balances and redeem offers without needing physical cards. Personalization is another crucial aspect, as mobile loyalty programs utilize your purchase history to tailor rewards and communications particularly for you. Furthermore, mobile wallet loyalty programs provide further convenience, letting you manage multiple digital cards and receive instant updates on new offers, all from your smartphone. Key Components of Mobile Loyalty Programs Effective mobile loyalty programs incorporate several key components that work together to improve customer engagement and retention. If you’re looking for the best gas loyalty program, comprehending these components is crucial. Points Accumulation: Earn points for every purchase, encouraging repeat visits. Personalized Offers: Use customer data to tailor promotions, enhancing perceived value. Mobile App Integration: Easily track points and rewards in real-time, eliminating the need for physical cards. Push Notifications: Stay informed about expiring rewards and new offers, keeping you engaged. Gamification Elements: Engage with challenges and badges, motivating you to reach milestones. Benefits of Using Mobile Loyalty Programs When you consider the advantages of using loyalty programs through your smartphone, convenience stands out as a primary benefit. Mobile loyalty programs let you earn points and rewards effortlessly, especially through the best gas rewards program. With 80% of consumers making purchases on mobile devices, it’s clear that these programs streamline your shopping experience. You can easily check your rewards balance and redeem offers without hassle, which increases customer retention and encourages repeat business. Additionally, gas loyalty programs often personalize offers based on your usage, enhancing your satisfaction and engagement. Digital loyalty cards in mobile wallets eliminate the need for physical cards, making transactions simpler and quicker. How Mobile Loyalty Programs Enhance Customer Engagement As consumers increasingly rely on their smartphones for everyday purchases, loyalty programs have adapted to improve engagement by delivering instant, personalized offers directly to users. Mobile loyalty programs do this effectively, enhancing customer interaction and boosting response rates. Here’s how they work: Push notifications provide timely offers based on your preferences. Gamification elements, like badges and tiered rewards, create a fun competition. User-friendly apps streamline enrollment and reward redemption, making participation easy. Targeted marketing strategies use collected data to tailor offers, increasing relevance. With 80% of consumers shopping on mobile, these programs guarantee constant access to rewards and information. For instance, gas station rewards programs offer you gas points that can be redeemed for discounts, making every visit more rewarding. The Role of Personalization in Mobile Loyalty Programs Mobile loyalty programs not merely engage customers through gamification and easy access to rewards but furthermore leverage personalization to improve the shopping experience. By using customer data, such as purchase history and preferences, these programs customize offers and communications, making them more relevant. For example, the best Shell gas station loyalty programs utilize personalized promotions that resonate with individual consumers, leading to increased engagement. Research shows that 80% of consumers prefer brands that provide customized experiences, and 70% state that personalized interactions influence their loyalty. Through a rewards application, businesses can send push notifications with timely updates on gas rewards and special offers, nurturing a stronger connection. This level of personalization not only boosts customer satisfaction but also increases retention rates, making it more likely that you’ll return for repeat purchases. Data Collection and Analysis in Loyalty Programs When you implement a mobile loyalty program, gathering data on purchase patterns becomes crucial for comprehending your customers. This information allows you to create personalized offers that resonate with their preferences, which can greatly improve their shopping experience. Insights From Purchase Patterns Comprehending customer purchase patterns is essential for enhancing loyalty programs. When you analyze data from mobile loyalty programs, you can uncover insights that inform your marketing strategies. This comprehension helps you tailor offers based on customer behavior, ultimately improving retention rates. Consider these key points: Identify trends in gas station reward points usage. Discover which gas discounts cards resonate most with customers. Determine how often customers engage with the best fuel loyalty programs. Track activation and churn rates for better retention efforts. Create targeted promotions that align with customer preferences. Personalized Offer Creation Analyzing customer purchase patterns sets the stage for creating personalized offers that improve loyalty program effectiveness. By collecting and examining data from your transactions, businesses can tailor promotions that resonate with your preferences, enhancing your engagement. For instance, a gas points card can be designed to reward frequent fuel purchases, making it one of the best fuel rewards programs available. These gasoline loyalty programs utilize insights from your shopping habits to generate timely push notifications, alerting you to deals that match your interests. This data-driven approach allows companies to refine their marketing strategies, ensuring that every offer feels relevant to you, which eventually increases your participation in their loyalty programs and boosts customer retention rates. Data-Driven Marketing Strategies Data-driven marketing strategies are essential for maximizing the effectiveness of loyalty programs, as they rely on the collection and analysis of customer data to create customized experiences. By utilizing insights gathered from customer interactions, brands can refine their offerings. Here are some key aspects to take into account: Track purchase history to identify preferences. Analyze activation and churn rates for retention insights. Tailor promotions like gas station discounts to specific segments. Leverage data to improve the appeal of the best gas rewards. Create dynamic marketing strategies that adapt to customer behavior, increasing engagement. With these strategies, businesses not just improve customer satisfaction but also optimize their loyalty programs, leading to better fuel discounts and overall retention rates. Popular Features of Mobile Loyalty Apps What makes mobile loyalty apps so appealing to consumers? These apps often feature points accumulation systems, allowing you to earn points with each purchase. You can redeem these points for discounts or rewards, which boosts your engagement. Many mobile loyalty apps additionally include gamification elements, like badges and tiered rewards, making your loyalty experience interactive and encouraging more frequent interactions with the brand. Push notifications keep you informed about personalized offers and reminders, ensuring you never miss out on valuable gas promotions or the best gas station rewards program. Furthermore, seamless integration with mobile wallets lets you manage multiple loyalty cards effortlessly, providing convenient access to your rewards without juggling physical cards. Finally, real-time updates on your points and rewards status are displayed in an easy-to-navigate interface, improving your overall user experience and prompting consistent engagement with the program. Real-Life Examples of Successful Mobile Loyalty Programs In exploring successful mobile loyalty programs, you’ll find several innovative features that boost user engagement. For instance, Lidl Plus combines point earning with personalized offers and shopping list capabilities, whereas KFC Rewards Arcade introduces gamified experiences for instant rewards. These strategies not just improve customer retention but likewise drive increased app usage and revenue across various Apple brands. Innovative Features Overview How do successful mobile loyalty programs capture and retain customer interest? They incorporate innovative features that improve user engagement and offer tangible benefits. Consider these real-life examples: Lidl Plus combines traditional point earning with personalized store offers and shopping list features. MyModanisa employs a tiered rewards system, boosting revenue considerably in its first year. KFC Rewards Arcade gamifies the experience with arcade-style games, increasing app usage. Dynamic tier systems motivate users to engage more by revealing greater benefits. Programs often integrate gamification and personalized offers, which effectively improve customer retention. When looking for the best gas station rewards or how to get discounted gas, these features demonstrate how mobile loyalty programs can provide valuable incentives. Engagement Strategies Highlighted Successful mobile loyalty programs leverage a variety of engagement strategies that not just attract customers but likewise keep them returning. For instance, the Exxon Mobil app offers gas deals and ExxonMobil discounts, incentivizing frequent visits. Lidl Plus improves user engagement through store-specific offers and a convenient shopping list feature. MyModanisa’s focus on tiered rewards and an earn & burn point system led to a remarkable 4x revenue increase in its first year. KFC’s Rewards Arcade incorporates gamified experiences, boosting app usage and active users. Starbucks stands out with personalized push notifications that deliver instant offers, improving customer retention. Finally, Sephora’s Beauty Insider program nurtures community through exclusive events and tiered rewards, driving repeat purchases among loyal members. Future Trends in Mobile Loyalty Programs What does the future hold for mobile loyalty programs? As technology evolves, you’ll see a notable shift in the direction of personalized and gamified experiences. With 79% of consumers indicating that loyalty engagement impacts their buying decisions, it’s essential for brands to adapt. Here are some trends you can expect: Biometric authentication for secure transactions. NFC tap-to-pay features simplifying the redemption process. Real-time updates through mobile wallets, like emrewards.com and mobil speedpass, keeping you informed about rewards. Seamless user experiences with easy enrollment and user-friendly interfaces. Expanding use cases beyond retail, incorporating rewards in transportation and healthcare. These advancements not only improve security but additionally deepen customer engagement, making rewards, like gasoline discounts, more accessible and relevant in your daily life. Frequently Asked Questions What Is Mobile Loyalty? Mobile loyalty refers to a digital approach where you’re rewarded for your purchases and engagement through your mobile device. Utilizing apps or SMS, you can easily access your rewards, track points, and receive personalized offers based on your shopping habits. This method streamlines your shopping experience, eliminating physical loyalty cards. As a result, it improves your connection with brands, promoting repeat business and potentially increasing your savings through discounts and exclusive rewards. How Does the Loyalty Program Work? The loyalty program works by allowing you to earn points with every purchase made through the mobile app. You’ll provide your information during enrollment, which starts your expedition. As you accumulate points, you can redeem them for discounts or freebies. Many programs feature tier-based systems, so the more you spend, the better your rewards become. Real-time tracking lets you monitor your points, as gamified elements keep you engaged and motivated to reach goals. What Are the Cons of a Loyalty Program? Loyalty programs can have several downsides. You might experience customer fatigue if the program demands too much engagement or offers minimal rewards. High operational costs could strain resources without delivering expected returns. Furthermore, some customers may join primarily for rewards, undermining genuine loyalty. Complex structures can confuse you, making participation feel intimidating. Finally, concerns about data privacy can arise as programs collect extensive personal information, potentially breeding mistrust in how your data is handled. What Are the Three R’s of Loyalty Programs? The three R’s of loyalty programs are Rewards, Recognition, and Retention. Rewards provide customers with tangible benefits like points or discounts for their purchases. Recognition acknowledges their loyalty through personalized offers or tiered memberships, enhancing their status. Retention focuses on keeping customers engaged over time by creating positive experiences and targeted marketing. Together, these elements aim to cultivate deeper connections with customers, ultimately driving their long-term loyalty and increasing their lifetime value to the brand. Conclusion To conclude, mobile loyalty programs are effective tools that reward customers for their repeat business through a user-friendly app. By accumulating points and receiving personalized offers, customers enjoy a more engaging shopping experience. Businesses benefit from improved customer retention and valuable insights through data analysis. As technology evolves, these programs are likely to incorporate more advanced features, ensuring they remain relevant and beneficial for both customers and businesses alike. Adopting a mobile loyalty program can greatly boost your brand’s loyalty initiatives. Image via Google Gemini This article, "What Is a Mobile Loyalty Program and How Does It Work?" was first published on Small Business Trends View the full article

China moved on Thursday to curb a fierce price war among automakers that has caused massive losses for the industry, after passenger car sales dropped nearly 20% in January from the year before, the fastest pace in almost two years. The State Administration for Market Regulation released guidelines for manufacturers, dealers, and parts suppliers aimed at preventing a race-to-the-bottom price war. They ban automakers from setting prices below the cost of production to “squeeze out competitors or monopolize the market.” Violators may face “significant legal risks,” the regulator warned. The rules also target deceptive pricing strategies and price fixing between parts suppliers and auto manufacturers. Passenger car sales in China fell 19.5% in January from a year earlier, according to the China Association of Automobile Manufacturers. That was the biggest percentage drop since February 2024. The 1.4 million passenger cars sold in January compared with 2.2 million units sold in December, CAAM said. Weakening demand reflects a reluctance of cash-strapped buyers to splash out on big purchases. Sales also have suffered from a cut in tax exemptions for EV purchases, coupled with uncertainties over whether trade-in subsidies for EV purchases will continue after some regions phased them out, auto analysts said. The aggressive price war in China’s auto sector has caused an estimated loss of 471 billion yuan ($68 billion) in output value across the whole industry in the past three years, Li Yanwei, a member of the China Automobile Dealers Association, wrote recently. Analysts expect domestic demand to dip this year. S&P has forecast sales of light vehicles, including passenger cars, in China will fall up to 3% in 2026. However, Chinese automakers are gaining ground in global markets. China’s exports of passenger cars jumped 49% year-on-year to 589,000 in January. “We don’t foresee a loss in momentum for the Chinese auto industry this year,” said Claire Yuan, director of corporate ratings for China autos at S&P Global Ratings. Chinese automakers such as BYD — the country’s largest and one that overtook Tesla as the world’s top electric vehicle maker — are targeting markets in Europe and Latin America as they confront intense competition in both prices and lineups at home due to oversupply. Analysts at Citi expect China’s car exports could jump 19% this year driven by exports of electric vehicles and plug-in hybrids. BYD is targetings around 1.3 million of overseas car sales in 2026, up from the 1.05 million last year. Other major Chinese automakers have also set ambitious sales targets with a focus on exports. Last month, Canada agreed to cut its hefty 100% tariff on China-made EV imports in a move welcomed by Chinese carmakers. China also recently reached a deal with the European Union that could allow more of its EVs to enter the European market. Earlier this week, the European Commission accepted a request by the German auto group Volkswagen to exempt import tariffs for one of its China-built EV models under the CUPRA brand — as long as those vehicles are sold at or above an agreed minimum import price — in a first of such exemptions. China’s commerce ministry said Thursday that it welcomed the move and that it hopes to see more such exemptions. —Chan Ho-Him, AP business writer View the full article

Adam Mosseri, the head of Meta’s Instagram, testified Wednesday during a landmark social media trial in Los Angeles that he disagrees with the idea that people can be clinically addicted to social media platforms. The question of addiction is a key pillar of the case, where plaintiffs seek to hold social media companies responsible for harms to children who use their platforms. Meta Platforms and Google’s YouTube are the two remaining defendants in the case, which TikTok and Snap have settled. At the core of the Los Angeles case is a 20-year-old identified only by the initials “KGM,” whose lawsuit could determine how thousands of similar lawsuits against social media companies would play out. She and two other plaintiffs have been selected for bellwether trials — essentially test cases for both sides to see how their arguments play out before a jury. Mosseri, who’s headed Instagram since 2018 said it’s important to differentiate between clinical addiction and what he called problematic use. The plaintiff’s lawyer, however, presented quotes directly from Mosseri in a podcast interview a few years ago where he used the term addiction in relation to social media use, but he clarified that he was probably using the term “too casually,” as people tend to do. Mosseri said he was not claiming to be a medical expert when questioned about his qualifications to comment on the legitimacy of social media addiction, but said someone “very close” to him has experienced serious clinical addiction, which is why he said he was “being careful with my words.” He said he and his colleagues use the term “problematic use” to refer to “someone spending more time on Instagram than they feel good about, and that definitely happens.” It’s “not good for the company, over the long run, to make decisions that profit for us but are poor for people’s well-being,” Mosseri said. Mosseri and the plaintiff’s lawyer, Mark Lanier, engaged in a lengthy back-and-forth about cosmetic filters on Instagram that changed people’s appearance in a way that seemed to promote plastic surgery. “We are trying to be as safe as possible but also censor as little as possible,” Mosseri said. In the courtroom, bereaved parents of children who have had social media struggles seemed visibly upset during a discussion around body dysmorphia and cosmetic filters. Meta shut down all third-party augmented reality filters in January 2025. The judge made an announcement to members of the public on Wednesday after the displays of emotion, reminding them not to make any indication of agreement or disagreement with testimony, saying that it would be “improper to indicate some position.” During cross examination, Mosseri and Meta lawyer Phyllis Jones tried to reframe the idea that Lanier was suggesting in his questioning that the company is looking to profit off of teens specifically. Mosseri said Instagram makes “less money from teens than from any other demographic on the app,” noting that teens don’t tend to click on ads and many don’t have disposable income that they spend on products from ads they receive. During his opportunity to question Mosseri for a second time, Lanier was quick to point to research that shows people who join social media platforms at a young age are more likely to stay on the platforms longer, which he said makes teen users prime for meaningful long-term profit. “Often people try to frame things as you either prioritize safety or you prioritize revenue,” Mosseri said. “It’s really hard to imagine any instance where prioritizing safety isn’t good for revenue.” Meta CEO Mark Zuckerberg is expected to take the stand next week. In recent years, Instagram has added a slew of features and tools it says have made the platform safer for young people. But this does not always work. A report last year, for instance, found that teen accounts researchers created were recommended age-inappropriate sexual content, including “graphic sexual descriptions, the use of cartoons to describe demeaning sexual acts, and brief displays of nudity.” In addition, Instagram also recommended a “range of self-harm, self-injury, and body image content” on teen accounts that the report says “would be reasonably likely to result in adverse impacts for young people, including teenagers experiencing poor mental health, or self-harm and suicidal ideation and behaviors.” Meta called the report “misleading, dangerously speculative” and said it misrepresents its efforts on teen safety. Meta is also facing a separate trial in New Mexico that began this week. —By Kaitlyn Huamani and Barbara Ortutay, AP Technology Writers View the full article

Gold and silver also drop while US Treasuries rallyView the full article

In a rapidly evolving technological landscape, Oracle is setting the stage for a groundbreaking shift in artificial intelligence (AI) infrastructure that could significantly benefit small businesses across the United States. Marking a pivotal year in 2026, Oracle aims to create AI data centers that not only drive scientific and economic advancements but also promise to enrich local communities involved in these initiatives. Oracle’s partnership with OpenAI has already commenced with infrastructure projects at two Texas campuses and additional sites in New Mexico, Wisconsin, and Michigan. These efforts position communities like Abilene, Shackelford County, and others at the forefront of America’s AI ambitions, reinforcing the nation’s leadership in this vital sector for generations to come. Oracle’s innovative approach is designed to minimize the environmental impact often associated with data centers. As the demand for AI capabilities grows, the company acknowledges the heightened energy requirements of such facilities. To address this, Oracle’s AI data centers will incorporate on-site power generation and contribute to local utility upgrades. “Oracle is committed to paying our own way on energy,” a company representative stated, emphasizing the firm’s responsibility in mitigating energy costs for local residents. Small business owners may find the implications of these developments particularly compelling. The advancements in energy reliability are poised to benefit local economies. By investing in infrastructure improvements, Oracle is setting a precedent that could inspire other tech companies, leading to better utilities and more stable energy supplies in the region. This stability is crucial for small businesses that depend on consistent power sources, enabling them to operate efficiently and reduce unexpected costs. Moreover, Oracle’s commitment to sustainability includes the introduction of closed-loop non-evaporative cooling systems at their data centers. These systems will lead to significantly reduced water usage, aligning the operations of these centers with the consumption levels typical of regular office buildings. This could alleviate one of the main concerns small business owners have regarding resource scarcity, particularly in regions where water availability is already a pressing issue. Oracle’s initiatives to create AI infrastructure also emphasize job creation. The corporation plans to source and hire locally, with thousands of construction jobs and permanent positions anticipated as data centers become operational. On average, a site utilizing around 1 gigawatt of energy will require over 1,000 permanent staff members. This shift could invigorate local job markets, presenting an exciting opportunity for small enterprises to tap into a new talent pool. “Providing technical skills training and workforce development, supporting local charities, and engaging in the life of the community are all commitments we make and take seriously,” Oracle representatives stressed. This sentiment underscores the potential for symbiotic relationships between Oracle and small businesses, as increased local employment can lead to enhanced community engagement and economic resilience. While the prospects are promising, small business owners might consider potential challenges as well. The sheer scale of these developments can lead to increased traffic and changes in local infrastructure, potentially disrupting day-to-day operations. Business owners may need to proactively engage with local authorities to stay informed and prepared for any infrastructural changes that could impact accessibility. The extensive landscape screening around Oracle’s data centers aims to address concerns regarding noise and visual disruption. With measures in place to ensure that noise levels approximate those of normal farming operations, there seems to be a concerted effort to minimize any adverse impacts on surrounding communities. As Oracle builds out its AI infrastructure in 2026, small businesses have many reasons to pay attention. The advancements in energy reliability, local job creation, and sustainable practices promise to foster an environment conducive to growth. However, it will be essential for small business owners to stay vigilant, engage with their communities, and explore how they can leverage the new opportunities emerging from these developments. For more information about Oracle’s initiatives and their impact on local communities, you can visit the original post here. Image via Google Gemini This article, "Oracle Pioneers AI Infrastructure Projects to Transform Local Communities" was first published on Small Business Trends View the full article

In a rapidly evolving technological landscape, Oracle is setting the stage for a groundbreaking shift in artificial intelligence (AI) infrastructure that could significantly benefit small businesses across the United States. Marking a pivotal year in 2026, Oracle aims to create AI data centers that not only drive scientific and economic advancements but also promise to enrich local communities involved in these initiatives. Oracle’s partnership with OpenAI has already commenced with infrastructure projects at two Texas campuses and additional sites in New Mexico, Wisconsin, and Michigan. These efforts position communities like Abilene, Shackelford County, and others at the forefront of America’s AI ambitions, reinforcing the nation’s leadership in this vital sector for generations to come. Oracle’s innovative approach is designed to minimize the environmental impact often associated with data centers. As the demand for AI capabilities grows, the company acknowledges the heightened energy requirements of such facilities. To address this, Oracle’s AI data centers will incorporate on-site power generation and contribute to local utility upgrades. “Oracle is committed to paying our own way on energy,” a company representative stated, emphasizing the firm’s responsibility in mitigating energy costs for local residents. Small business owners may find the implications of these developments particularly compelling. The advancements in energy reliability are poised to benefit local economies. By investing in infrastructure improvements, Oracle is setting a precedent that could inspire other tech companies, leading to better utilities and more stable energy supplies in the region. This stability is crucial for small businesses that depend on consistent power sources, enabling them to operate efficiently and reduce unexpected costs. Moreover, Oracle’s commitment to sustainability includes the introduction of closed-loop non-evaporative cooling systems at their data centers. These systems will lead to significantly reduced water usage, aligning the operations of these centers with the consumption levels typical of regular office buildings. This could alleviate one of the main concerns small business owners have regarding resource scarcity, particularly in regions where water availability is already a pressing issue. Oracle’s initiatives to create AI infrastructure also emphasize job creation. The corporation plans to source and hire locally, with thousands of construction jobs and permanent positions anticipated as data centers become operational. On average, a site utilizing around 1 gigawatt of energy will require over 1,000 permanent staff members. This shift could invigorate local job markets, presenting an exciting opportunity for small enterprises to tap into a new talent pool. “Providing technical skills training and workforce development, supporting local charities, and engaging in the life of the community are all commitments we make and take seriously,” Oracle representatives stressed. This sentiment underscores the potential for symbiotic relationships between Oracle and small businesses, as increased local employment can lead to enhanced community engagement and economic resilience. While the prospects are promising, small business owners might consider potential challenges as well. The sheer scale of these developments can lead to increased traffic and changes in local infrastructure, potentially disrupting day-to-day operations. Business owners may need to proactively engage with local authorities to stay informed and prepared for any infrastructural changes that could impact accessibility. The extensive landscape screening around Oracle’s data centers aims to address concerns regarding noise and visual disruption. With measures in place to ensure that noise levels approximate those of normal farming operations, there seems to be a concerted effort to minimize any adverse impacts on surrounding communities. As Oracle builds out its AI infrastructure in 2026, small businesses have many reasons to pay attention. The advancements in energy reliability, local job creation, and sustainable practices promise to foster an environment conducive to growth. However, it will be essential for small business owners to stay vigilant, engage with their communities, and explore how they can leverage the new opportunities emerging from these developments. For more information about Oracle’s initiatives and their impact on local communities, you can visit the original post here. Image via Google Gemini This article, "Oracle Pioneers AI Infrastructure Projects to Transform Local Communities" was first published on Small Business Trends View the full article

Today's Bissett Bullet: “It’s often a controversial point but some partners in our firms don’t want to learn how to sell.” By Martin Bissett See more Bissett Bullets here Go PRO for members-only access to more Martin Bissett. View the full article

Today's Bissett Bullet: “It’s often a controversial point but some partners in our firms don’t want to learn how to sell.” By Martin Bissett See more Bissett Bullets here Go PRO for members-only access to more Martin Bissett. View the full article

Welcome to AI Decoded, Fast Company’s weekly newsletter that breaks down the most important news in the world of AI. You can sign up to receive this newsletter every week via email here. Is ‘AI slop’ code here to stay? A few months ago I wrote about the dark side of vibe coding tools: they often generate code that introduces bugs or security vulnerabilities that surface later. They can solve an immediate problem while making a codebase harder to maintain over time. It’s true that more developers are using AI coding assistants, and using them more frequently and for more tasks. But many seem to be weighing the time saved today against the cleanup they may face tomorrow. When human engineers build projects with lots of moving parts and dependencies, they have to hold a vast amount of information in their heads and then find the simplest, most elegant way to execute their plan. AI models face a similar challenge. Developers have told me candidly that AI coding tools, including Claude Code and Codex, still struggle when they need to account for large amounts of context in complex projects. The models can lose track of key details, misinterpret the meaning or implications of project data, or make planning mistakes that lead to inconsistencies in the code—all things that an experienced software engineer would catch. The most advanced AI coding tools are only now beginning to add testing and validation features that can proactively surface problematic code. When I asked OpenAI CEO Sam Altman during a recent press call whether Codex is improving at testing and validating generated code, he became visibly excited. Altman said OpenAI likes the idea of deploying agents to work behind developers, validating code and sniffing out potential problems. Indeed, Codex can run tests on code it generates or modifies, executing test suites in a sandboxed environment and iterating until the code passes or meets acceptance criteria defined by the developer. Claude Code, meanwhile, has its own set of validation and security features. Anthropic has built testing and validation routines into its Claude Code product, too. Some developers say Claude is stronger at higher-level planning and understanding intent, while Codex is better at following specific instructions and matching an existing codebase. The real question may be what developers should expect from these AI coding tools. Should they be held to the standard of a junior engineer whose work may contain errors and requires careful review? Or should the bar be higher? Perhaps the goal should be not only to avoid generating “slop” code but also to act as a kind of internal auditor, catching and fixing bad code written by humans. Altman likes that idea. But judging by comments from another OpenAI executive, Greg Brockman, it’s not clear the company believes that standard is fully attainable. Brockman, OpenAI’s president, suggests in a recently posted set of AI coding guidelines that AI “slop” code isn’t something to eliminate so much as a reality to manage. “Managing AI generated code at scale is an emerging problem, and will require new processes and conventions to keep code quality high,” Brockman wrote on X. Saas stocks still smarting from last week’s ‘SaaSpocalypse’ Last week, shares of several major software companies tumbled amid growing anxiety about AI. The share prices of ServiceNow, Oracle, Salesforce, AppLovin, Workday, Intuit, CrowdStrike, Factset Research, and Thompson Reuters fell so sharply that Wall Street types began to refer to the event as the “SaaSpocalypse.” The stocks fell sharply on two pieces of news. First, late in the day on Friday, January 30, Anthropic announced a slate of new AI plugins for its Cowork AI tool aimed at information workers, including capabilities for legal, product management, marketing, and other functions. Then, on February 4, the company unveiled its most powerful model yet, Claude Opus 4.6, which now powers the Claude chatbot, Claude Code, and Cowork. For investors, Anthropic’s releases raised a scary question: How will old-school SaaS companies survive when their products are already being challenged by AI-native tools? Although software shares rebounded somewhat later in the week, as analysts circulated reassurances that many of these companies are integrating new AI capabilities into their products, the unease lingers. In fact, many of the stocks mentioned above have yet to recover to their late-January levels. (Some SaaS players, like ServiceNow, are now even using Anthropic’s models to power their AI features.) But it’s a sign of the times, and investors will continue to watch carefully for signs that enterprises are moving on from traditional SaaS solutions to newer AI apps or autonomous agents. China is flexing its video models This week, some new entrants in the race for best model are very hard to miss. X is awash with posts showcasing video generated by new Chinese video generation models—Seedance 2.0 from ByteDance and Kling 3.0 from Kuaishou. The video is impressive. Many of the clips are difficult to distinguish from traditionally shot footage, and both tools make it easier to edit and steer the look and feel of a scene. AI-generated video is getting scary-good, its main limitation being that the generated videos are still pretty short. Sample videos from Kling 3.0, which range from 3 seconds to 15 seconds, feature smooth scene transitions and a variety of camera angles. The characters and objects look consistent from scene to scene, a quality that video models have struggled with. The improvements are owed in part to the model’s ability to glean the creator’s intent from the prompts, which can include reference images and videos. Kling also includes native audio generation, meaning it can generate speech, sound effects, ambient audio, lip-sync, and multi-character dialogue in a number of languages, dialects, and accents. ByteDance’s Seedance 2.0, like Kling 3.0, generates video with multiple scenes and multiple camera angles, even from a single prompt. One video featured a shot from within a Learjet in flight to a shot from outside the aircraft. The video motion looks smooth and realistic, with good character consistency across frames and scenes, so that it can handle complex high-motion scenes like fights, dances, and action sequences. Seedance can be prompted with text, images, reference videos, and audio. And like Kling, Seedance can generate synchronized audio including voices, sound effects, and lip-sync in multiple languages. More AI coverage from Fast Company: We’re entering the era of ‘AI unless proven otherwise’ A Palantir cofounder is backing a group attacking Alex Bores over his work with . . . Palantir Why a Korean film exec is betting big on AI Mozilla’s new AI strategy marks a return to its ‘rebel alliance’ roots Want exclusive reporting and trend analysis on technology, business innovation, future of work, and design? Sign up for Fast Company Premium. View the full article

Some discipline will make your practice better. By Sandi Leyva The Complete Guide to Marketing for Tax & Accounting Firms Go PRO for members-only access to more Sandi Smith Leyva. View the full article

Some discipline will make your practice better. By Sandi Leyva The Complete Guide to Marketing for Tax & Accounting Firms Go PRO for members-only access to more Sandi Smith Leyva. View the full article

Starmer’s restive MPs should acknowledge that Britain’s fortunes are shaped abroadView the full article

Russia has attempted to fully block WhatsApp in the country, the company said, the latest move in an ongoing government effort to tighten control over the internet. A WhatsApp spokesperson said late Wednesday that the Russian authorities’ action was intended to “drive users to a state-owned surveillance app,” a reference to Russia’s own state-supported MAX messaging app that’s seen by critics as a surveillance tool. “Trying to isolate over 100 million people from private and secure communication is a backwards step and can only lead to less safety for people in Russia,” the WhatsApp spokesperson said. “We continue to do everything we can to keep people connected.” Russia’s government has already blocked major social media like Twitter, Facebook and Instagram and ramped up other online restrictions since Russia’s full-scale invasion of Ukraine in 2022. Kremlin spokesman Dmitry Peskov said WhatsApp owner Meta Platforms should comply with Russian law to see it unblocked, according to the state Tass news agency. Earlier this week, Russian communications watchdog Roskomnadzor said it will introduce new restrictions on the Telegram messaging app after accusing it of refusing to abide by the law. The move triggered widespread criticism from military bloggers, who warned that Telegram was widely used by Russian troops fighting in Ukraine and its throttling would derail military communications. Despite the announcement, Telegram has largely been working normally. Some experts say it’s a more difficult target, compared with WhatsApp. Some Russian experts said that blocking WhatsApp would free up technological resources and allow authorities to fully focus on Telegram, their priority target. Authorities had previously restricted access to WhatsApp before moving to finally ban it Wednesday. Under President Vladimir Putin, authorities have engaged in deliberate and multipronged efforts to rein in the internet. They have adopted restrictive laws and banned websites and platforms that don’t comply, and focused on improving technology to monitor and manipulate online traffic. Russian authorities have throttled YouTube and methodically ramped up restrictions against popular messaging platforms, blocking Signal and Viber and banning online calls on WhatsApp and Telegram. In December, they imposed restrictions on Apple’s video calling service FaceTime. While it’s still possible to circumvent some of the restrictions by using virtual private network services, many of them are routinely blocked, too. At the same time, authorities actively promoted the “national” messaging app called MAX, which critics say could be used for surveillance. The platform, touted by developers and officials as a one-stop shop for messaging, online government services, making payments and more, openly declares it will share user data with authorities upon request. Experts also say it doesn’t use end-to-end encryption. —Associated Press View the full article

Daniel Kokotajlo predicted the end of the world would happen in April 2027. In “AI 2027” — a document outlining the impending impacts of AI, published in April 2025 — the former OpenAI employee and several peers announced that by April 2027, unchecked AI development would lead to superintelligence and consequently destroy humanity. The authors, however are going back on their predictions. Now, Kokotajlo forecasts superintelligence will land in 2034, but he doesn’t know if and when AI will destroy humanity. In “AI 2027,” Kokotajlo argued that superintelligence will emerge through “fully autonomous coding,” enabling AI systems to drive their own development. The release of ChatGPT in 2022 accelerated predictions around artificial general intelligence, with some forecasting its arrival within years rather than decades. These predictions accrued widespread attention. Notably, JD Vance, U.S. vice president, reportedly read “AI 2027” and later urged Pope Leo XIV — who underscored AI as a main challenge facing humanity — to provide international leadership to avoid outcomes listed in the document. On the other hand, people like Gary Marcus, emeritus professor of neuroscience at New York University, disregarded “AI 2027” as a “work of fiction,” even calling various predictions “pure science fiction mumbo jumbo.” As researchers and the public alike begin to reckon with “how jagged AI performance is,” AGI timelines are starting to stretch again, according to Malcolm Murray, an AI risk management expert and one of the authors of the “International AI Safety Report.” “For a scenario like ‘AI 2027’ to happen, [AI] would need a lot of more practical skills that are useful in real-world complexities,” Murray said. Still, developing AI models that can train themselves remains a steady goal for leading AI companies. Sam Altman, OpenAI CEO, set internal goals for “a true automated AI researcher by March of 2028.” However, he’s not entirely confident in the company’s capabilities to develop superintelligence. “We may totally fail at this goal,” he admitted on X, “but given the extraordinary potential impacts we think it is in the public interest to be transparent about this.” And so, superintelligence may still be possible, but when it arrives and what it will be capable of remains far murkier than “AI 2027” once suggested. —Leila Sheridan This article originally appeared on Fast Company‘s sister publication, Inc. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy. View the full article

Contract closings decreased 8.4%, the biggest drop since February 2022, to a 3.91 million annualized pace in January, according to National Association of Realtors data released Thursday. View the full article