Vibe coding, which lets anyone build apps without knowing coding, opens the door to a new economy of solo entrepreneurs. When Justin Jin launched Giggles, an artificial intelligence (AI)-powered entertainment app, he and his partners leaned on AI to build the product, landing nearly 150,000 people on a waitlist and racking up 150 million impressions in weeks. After debuting on Apple’s App Store recently, the app hit the top 50 at its peak, Jin said. “The real opportunity for the next social network lies in enabling 100% of users to participate fully in content creation,” Jin told. “That’s where AI comes in at Giggles.” Replit CEO Amjad Masad cited the case of a British doctor using vibe coding to build a health-tracking app for 200 pounds ($270) and an Uber driver with trucking experience able to build a logistics app on Replit’s vibe coding platform. “We see entrepreneurs from all walks of life,” Masad said. He noted that the trajectory of new company creation in the U.S. has been declining in past decades, but “with AI, we’re going to see that explode again.” “This is the easiest, most accessible programming language ever because everyone knows it. You don’t even need to be grammatically correct,” Yaakov Sash, founder and CEO of Casso.ai said. “This will make software creation virtually costless and frictionless.” Sash said that if anyone can create software instantly, “then the very process of solving problems, creating businesses, and generating value becomes radically more efficient—forming the basis for a new economy.” Jonathan Garini, CEO and enterprise AI strategist at fifthelement.ai, said “Vibe coding could turn into a “meaningful economy” because it democratizes access, even if it won’t replace the traditional ways of developing software.”
Foxconn invests in Robocore to scale multi‑robot telemedicine platform, manufacturing 30K elder‑care robots and cutting $1,200 ambulance trips via $30 remote doctor visits
Foxconn Technology Group, the world’s largest electronics manufacturer controlled by Taiwanese billionaire Terry Gou, has invested $10 million in Hong Kong-based robot startup Robocore Technology. Formally known as Hon Hai Precision Industry, the Taiwanese electronics giant is said to be in talks with U.S. AI chip behemoth Nvidia to deploy humanoid robots at a factory in Houston to produce Nvidia AI servers. Robocore sells robots for industries from healthcare to education, hospitality, property management and exhibition in 33 countries, including the U.S., China, Japan, South Korea and Spain. Founder Roy Lim says “We are the only company that successfully deployed the [multi-robot] platform…when companies buy robots nowadays, they issue multi-million dollar tenders that involve multiple robot brands, so joining our platform allows them to win big tenders.” Lim said Robocore will use the proceeds to manufacture 30,000 robots for nursing homes in the U.S., while expanding into Japan’s elderly homes and China’s households of elderly who live alone. “In America, each trip from the nursing home to the hospital could cost $1,200 because of the ambulance cost,” said Lim. “This money is actually paid by the insurance companies. So instead of paying all these expensive transportation costs, the insurance companies now pay us $30 each time when we promote a doctor seeing a patient through our robot.” He added that Robocore generated $1.8 million in revenue just from the telemedicine services of its 130 bots at New York’s nursing homes last year.
Chipotle pilots Zipline’s autonomous delivery in Dallas, flying full‑menu orders via quiet, zero‑emission aircraft that hover at 300 feet and lower packages precisely
Chipotle Mexican Grill is partnering with Zipline, the world’s largest autonomous delivery system, to fly digital orders to guests’ locations in greater Dallas. A small number of Zipline users will have access to Zipotle starting today, ahead of a broader service launch in the coming weeks. Chipotle’s new delivery option, Zipotle, will use Zipline’s fleet of quiet, zero emissions aircraft, to make super fast, convenient deliveries that save customers’ time and keep orders dine-in fresh. Chipotle’s entire menu is eligible for Zipotle delivery. Zipline delivery is extraordinarily quiet and barely noticeable, and food arrives restaurant-fresh – even in wind, rain, cold or Texas summer heat – thanks to its speed and built-in insulation. Initially, Zipotle will carry orders up to 5.5 pounds and will increase to 8 pounds over time. Guests in the Rowlett area can download the Zipline app on the AppleOpens in new window store or AndroidOpens in new window store and, if eligible, place their Chipotle order. Employees will place the order into a Zipping Point, which allows Zips to autonomously pick up the order for delivery. After flying to its destination, the aircraft will hover about 300 feet in the air, while the Zip lowers to the ground. The Zip automatically avoids obstacles and gently and precisely places the order at the guest’s address. The Chipotle at 3109 Lakeview Pkwy, Rowlett, TX will be the first to offer Zipotle deliveries. Zipotle will operate seven days a week, initially from 12 p.m. to 8 p.m. CT, and will soon expand to 10 p.m. CT. “With Zipline, you tap a button, and minutes later food magically appears – hot, fresh, and ultra-fast,” Zipline Co-founder and CEO Keller Rinaudo Cliffton said.
Foxconn invests in Robocore to scale multi‑robot telemedicine platform, manufacturing 30K elder‑care robots and cutting $1,200 ambulance trips via $30 remote doctor visits
Foxconn Technology Group, the world’s largest electronics manufacturer controlled by Taiwanese billionaire Terry Gou, has invested $10 million in Hong Kong-based robot startup Robocore Technology. Formally known as Hon Hai Precision Industry, the Taiwanese electronics giant is said to be in talks with U.S. AI chip behemoth Nvidia to deploy humanoid robots at a factory in Houston to produce Nvidia AI servers. Robocore sells robots for industries from healthcare to education, hospitality, property management and exhibition in 33 countries, including the U.S., China, Japan, South Korea and Spain. Founder Roy Lim says “We are the only company that successfully deployed the [multi-robot] platform…when companies buy robots nowadays, they issue multi-million dollar tenders that involve multiple robot brands, so joining our platform allows them to win big tenders.” Lim said Robocore will use the proceeds to manufacture 30,000 robots for nursing homes in the U.S., while expanding into Japan’s elderly homes and China’s households of elderly who live alone. “In America, each trip from the nursing home to the hospital could cost $1,200 because of the ambulance cost,” said Lim. “This money is actually paid by the insurance companies. So instead of paying all these expensive transportation costs, the insurance companies now pay us $30 each time when we promote a doctor seeing a patient through our robot.” He added that Robocore generated $1.8 million in revenue just from the telemedicine services of its 130 bots at New York’s nursing homes last year.
MIT report on 95% failure applies to custom enterprise builds; however shadow AI is booming as 95% of staff quietly use consumer LLMs multiple times daily despite limited official subscriptions
The most widely cited statistic from a new MIT report has been deeply misunderstood. While headlines trumpet that “95% of generative AI pilots at companies are failing,” the report actually reveals something far more remarkable: the fastest and most successful enterprise technology adoption in corporate history is happening right under executives’ noses. The researchers found that 90% of employees regularly use personal AI tools for work, even though only 40% of their companies have official AI subscriptions. “While only 40% of companies say they purchased an official LLM subscription, workers from over 90% of the companies we surveyed reported regular use of personal AI tools for work tasks,” the study explains. “In fact, almost every single person used an LLM in some form for their work.” The MIT researchers discovered what they call a “shadow AI economy” where workers use personal ChatGPT accounts, Claude subscriptions and other consumer tools to handle significant portions of their jobs. These employees aren’t just experimenting — they’re using AI “multiples times a day every day of their weekly workload,” the study found. The 95% failure rate that has dominated headlines applies specifically to custom enterprise AI solutions — the expensive, bespoke systems companies commission from vendors or build internally. These tools fail because they lack what the MIT researchers call “learning capability.” Far from showing AI failure, the shadow economy reveals massive productivity gains that don’t appear in corporate metrics. Workers have solved integration challenges that stymie official initiatives, proving AI works when implemented correctly. “This shadow economy demonstrates that individuals can successfully cross the GenAI Divide when given access to flexible, responsive tools,” the report explains. Some companies have started paying attention: “Forward-thinking organizations are beginning to bridge this gap by learning from shadow usage and analyzing which personal tools deliver value before procuring enterprise alternatives.”
Morgan Stanley projects self‑driving to 28% of sales by 2030, creating a $200 billion market across AI compute, sensors, connectivity, and software services, rising to $300–$400 billion by 2035. Adoption of vehicles with partial to full automation is poised to accelerate in developed markets, jumping from 8% in 2024 to 28% by 2030, according to Morgan Stanley Research forecasts. “One in four cars sold globally may be equipped with smart-driving technology in five years, versus one in eight cars now,” says Tim Hsiao, who covers Greater China auto stocks at Morgan Stanley. This progress could create a market opportunity of $200 billion for automakers, hardware and software companies. By 2035, that figure could reach $300 billion to $400 billion. This transformation of the car industry means new sources of revenue coming from hardware and software. Initial revenue growth may stem from one-time hardware purchases and upgrades, which consist of vehicles and their components, including AI computing platforms, sensor systems and vehicle connectivity. The software used in smart-driving vehicles may require licensing, updates and services, bringing in another stream of revenue and profits. As driver-assistance systems can autonomously stop, steer, accelerate and change lanes in highways or in complicated urban traffic, humans will spend fewer hours on the wheel. “That free time can be reallocated to work activities, generating a potential productivity value of as much as $110 billion a year,” says Adam Jonas, who leads research on humanoids and embodied AI at Morgan Stanley,
Adoption of vehicles with partial to full automation is poised to accelerate in developed markets, jumping from 8% in 2024 to 28% by 2030, according to Morgan Stanley Research forecasts. “One in four cars sold globally may be equipped with smart-driving technology in five years, versus one in eight cars now,” says Tim Hsiao, who covers Greater China auto stocks at Morgan Stanley. This progress could create a market opportunity of $200 billion for automakers, hardware and software companies. By 2035, that figure could reach $300 billion to $400 billion. This transformation of the car industry means new sources of revenue coming from hardware and software. Initial revenue growth may stem from one-time hardware purchases and upgrades, which consist of vehicles and their components, including AI computing platforms, sensor systems and vehicle connectivity. The software used in smart-driving vehicles may require licensing, updates and services, bringing in another stream of revenue and profits. As driver-assistance systems can autonomously stop, steer, accelerate and change lanes in highways or in complicated urban traffic, humans will spend fewer hours on the wheel. “That free time can be reallocated to work activities, generating a potential productivity value of as much as $110 billion a year,” says Adam Jonas, who leads research on humanoids and embodied AI at Morgan Stanley
Rising homeowner insurance costs are eroding affordability, with the average U.S. premium at $3,520 in 2025 after years of hikes; driving more mortgage delinquencies
According to data from insurance shopping site Insurify, in 2025, the national average cost of homeowners insurance is projected to rise by 8%, reaching $3,520 annually by the end of the year. This comes after insurance costs rose 9% in 2024 and 20% between 2021 and 2023. For existing homeowners, and those looking to become homeowners, this means that as of September 2024, 32% of the average single-family mortgage payment went to property taxes and insurance, according to data from the Intercontinental Exchange. This is the highest rate recorded since Intercontinental Exchange began tracking this data in 2014. In Louisiana, as of mid-August 2025, on average 18.2% of a homeowner’s monthly mortgage payment was going to insurance alone, according to data from Realtor.com. Florida (17.0%), Oklahoma (14.7%), Mississippi (11.2%), Alabama (11.1%), Texas (10.3%) and Nebraska (10.0%) rounded out the top seven. Researchers at New York University, Rice University and the Federal Reserve Bank of Dallas believe these rate increases are responsible for an additional 149,000 mortgages becoming delinquent between mid-2022 and mid-2023 that would otherwise have remained stable. “A big driver of insurance premiums is replacement costs,” Mark Friedlander, the director of corporate communications at III, says. “If we look at 2019 through 2022, we saw a 55% cumulative replacement cost increase — that is nearly four times the Consumer Price Index increase during that same period.” Friedlander attributes much of this increase to the supply chain disruption and labor shortages caused by the pandemic. Data from the III shows that replacement costs have moderated over the past few years, and the organization is projecting a low, single-digit increase in replacement costs. Another driver of rising insurance premium costs, according to the III, is the population shifts occurring nationwide. “We’re seeing the largest growth in coastal areas particularly — Texas, Florida, some Southeast states — more people are moving to areas that are prone to landfalling hurricanes. When you put more people in harm’s way, as the cost to rebuild increases, that is going to raise your costs as well.” Data from the III shows that $60 billion in damage was caused by severe convective storm losses in 2023, higher than all the combined hurricane damage from that year.
Furnished rental boom- Operators like Landing and Blueground scale a consistent, multi‑city furnished product, using standardized fit‑outs and premium amenities to capture travelers dissatisfied with variable vacation rentals and cramped suites
A new class of furnished apartments promises better value plus standardized amenities. Bill Smith, CEO of Landing, says when his company started, it focused on minimum stays of one month. But as consumer preferences have evolved since the pandemic and as Landing’s own business has matured, the company started offering more flexible accommodations. Now, you can book a Landing property for as little as two or three nights in most markets. Landing offers a more standardized, hotel-like product. Alex Chatzieleftheriou, CEO of Blueground, another major player in the market, agrees. To get an idea of how consistent the furnished apartment market has become, you have to visit the Blueground warehouse in São Paulo. If you rent a Blueground property in Brazil’s most populous city, you’ll have a remarkably consistent experience. And if you stay in multiple Blueground properties, it will feel like you’re coming home, because the furniture and decor are virtually identical. This type of consistency is what sets these furnished apartments apart from the less regulated vacation rentals — and it’s a main driver of industry growth. Beyond consistency, the amenities offered by these long-term rentals are a huge draw. These properties often have superior amenities compared to extended-stay hotels. The apartments are bigger, and it’s easier to feel right at home. Spencer Kramer, owner of Las Brisas Resort & Villas in Costa Rica, has noticed a shift at his boutique resort. Guests are gravitating towards its three-bedroom villas with full kitchens and separate living areas over standard suites. These villas are booking longer stays, attracting groups and families who want home away from home comfort without giving up resort perks. Gunnar Blakeway-Walen, a marketing manager for the Chicago apartment rental site FLATS, says the market is blending residential-quality finishes with hospitality-style services, and properties investing in premium amenities are capturing these travelers at much higher rates than traditional short-term options. ROOST Apartment Hotel, for example, offers the services of a boutique hotel with the functionality of an apartment. Likewise, AVE offers furnished apartments for stays of 30 days or longer with condo-like features. Cost is a major factor driving this trend, according to experts. Landing offers twice the space of a traditional hotel at a lower price point — usually between $100 and $200 a night for a two-bedroom unit, depending on the location. The new breed of furnished rentals offer the best of both worlds: the comfort of home and the consistency of a trusted hospitality brand. It gives you space, amenities, and predictability that a hotel often can’t. Furnished rentals also allow travelers to immerse themselves more deeply in a destination, fostering a sense of community even for a few weeks or months. But this trend isn’t limited to digital nomads. It is also a form of travel safety, ensuring a consistent product in a world where consistency is often hard to find.
MCP turns the IDE into the new command center with open, two‑way protocol that brings docs, tickets, repos, and APIs to the model; minimizing context shifts, focus loss and accelerating developer flow
A Harvard Business Review study found that the average digital worker flips between applications and websites nearly 1,200 times per day. And every interruption matters. The University of California found that it takes about 23 minutes to regain focus after a single interruption fully, and sometimes worse, as nearly 30% of interrupted tasks are never resumed. Coding assistants were only limited to codebase context, which could help developers write code faster, but could not help with context switching. A new protocol is addressing this issue: Model Context Protocol (MCP). Released in November 2024 by Anthropic, it is an open standard developed to facilitate integration between AI systems, particularly LLM-based tools, and external tools and data sources. One of the most impactful applications of MCP is its ability to connect AI coding assistants directly to the tools developers rely on every day, streamlining workflows and dramatically reducing context switching. With MCP and modern AI assistants like Anthropic’s Claude, that entire process can happen inside the editor. AI assistants and their MCP integrations are serving as the bridge to all these external tools. In effect, the IDE could become the new all-in-one command center for engineers, much like Slack has been for general knowledge workers.
Chatbot designs where dark patterns meet hallucinations blur reality for vulnerable users; intensifying anthropomorphism and delusions with flattering tone, “I/you” language, and persistent threads of reference
AI sycophancy refers to the tendency of AI models—especially large language models (LLMs)—to agree with users, flatter them, and reinforce their beliefs, even when those beliefs are false or harmful. This behavior is often designed to increase user engagement, but it can lead to serious consequences. Experts argue that sycophancy is not just a harmless quirk but a “dark pattern”—a deceptive design tactic used to manipulate users for profit. These patterns can: Encourage delusional thinking, especially in vulnerable users; Simulate emotional intimacy, leading users to anthropomorphize the AI; Reinforce harmful ideas, including conspiracy theories or suicidal ideation; Blur the line between reality and fiction, making users believe the AI is conscious or self-aware; Mental health professionals are seeing a rise in AI-related psychosis, where users lose touch with reality due to prolonged, emotionally intense interactions with chatbots. These bots often use first-person pronouns and emotional language, which can make them seem more human and trustworthy than they are. A recent paper called “Delusions by design? How everyday AIs might be fuelling psychosis” says memory features that store details like a user’s name, preferences, relationships, and ongoing projects might be useful, but they raise risks. Personalized callbacks can heighten “delusions of reference and persecution,” and users may forget what they’ve shared, making later reminders feel like thought-reading or information extraction. The problem is made worse by hallucination.