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The housing market just crossed an important thresholdone thats especially good news for anyone who might be planning on buying a home any time soon. The massive wave of COVID-19-era mortgages with ultra-low rates were a huge boon for many homebuyers, but the housing market hasnt been the same since. A huge swath of homeowners in the U.S. suddenly had mortgage interest rates well below 4%and very little incentive to sell their homes for less affordable options with todays higher rates. That dilemma has created a nightmarish scenario for the U.S. housing market. Many potential buyers and aspiring first-time homeowners remain priced out due to high home prices and higher interest rates. With more homeowners staying put whether they want to or not, housing inventory dried up considerably, shrinking the pool of options for home shoppers. Thats beginning to change. According to new data from Realtor.com, the share of U.S. homeowners with mortgage rates over 6% is now greater than the share hanging onto those ultra low sub-3% rates. In the third quarter of 2025, 21% of outstanding mortgages carried a rate above 6% compared to the 20% of mortgages with rates below 3%. That change signals a meaningful shift from the gridlock thats defined the last few years in the U.S. housing market. Mortgage rates above 6% now represent a larger share of outstanding loans than the ultra-low rates that defined the pandemic-era housing boom, Realtor.com Chief Economist Danielle Hale said in a press release. This crossover reflects a gradual resetting as some households trade in low-rate mortgages for higher-rate loans or enter the market for the first time, even as rate lock-in continues to limit the pace of inventory recovery. Lasting impact of low rates and lock-in Those ultra-low rates are on their way out, but many homeowners still have rates well below what theyd be offered today. According to the new data, over 50% of mortgages still have rates at or below 4% and almost 70% have rates of 5% or lower. As long as that remains the case, the average homeowner might see their monthly mortgage payment spike by as much as $1,000 if they sold their home and took on a mortgage with todays rates. Still, the new mortgage data is a promising sign. Rates are very unlikely to get as low as they did during the early days of COVID-19 again in our lifetimesparticularly now that we know just what a lasting disruptive impact the low rate homebuying frenzy had on the market at large. The period between July 2020 and September 2021 is the only time that the U.S. 30-year fixed mortgage rate has gone below 3% since those records began being kept in the early 1970s. The high cost of buying a home is more salt in the wound for many Americans, who have seen the price of everything from groceries to used cars soar in recent years. With little relief in 2025, the unaffordability crisis seems to be on everyones mind lately. If interest rates settle down and the present trends continue, at least the housing market might be getting back to something a little closer to normal this year. Even with rates still elevated, modest mortgage rate decreases into the low-6% range could encourage additional home buying activity, Hale said. Further easing in inflation and mortgage rates would be key to unlocking more seller participation, helping to relieve price pressure and competition in an under-supplied market.
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E-Commerce
Leaders typically spend January prepping for the year ahead. But thats difficult when youre eight months pregnant, and your baby has zero concern for your deadlines. Ive lost count of how many times people have asked how long Ill be away, whether Ill be checking my emails, or what support Ill need when I return. People often expect leaders to have all the answers, but the truth is: I dont know yet. Lucky for me, that uncertainty worked to my advantage. It forced me to change my approach from setting goals to building flexibility. This has resulted in a team that is autonomous and adaptable, whether Im in the room or away on leave. You dont have to have all the answers According to a report by Careers After Babies, 98% of moms want to return to work after having a child. However, less than a quarter actually do. Early parenthood is unpredictable, and theres no way of knowing how itll unfold. While Im committed to my career, Im under no illusions that March might bring me sleepless nights, and the months ahead may be full of doctors appointments. I might have no time to work at all. That isnt a challenge you can plan your way through. Sure, you might end up returning after six weeks. But if you set yourself that deadline and you end up delaying, you may end up feeling like youve failed and start to question your leadership when youre actually managing two of the most demanding roles there are. But you do have to be ready for anything When you dont know the outcome, you need to prepare for every possibility. That means focusing on building flexibility and developing resilience, because systems that can cope with volatility and deal with change dont rely on a single timeline or person. At Woofz, were focused on setting out clear decision ownership, so everyone understands where to turn for support, and also how to train our teams to handle pivots and take on new responsibilities when we need to. We aimed to create a team capable of thriving even when conditions change, without constant oversight. Resilience doesnt just help organizations get through difficult moments. It actively improves long-term performance. Research from software and consultancy firm MHR Global found that 82% of the most resilient organizations rank highly for customer satisfaction, while 76% score highly for employee engagement. Overall, resilient businesses are far more confident in their ability to outperform competitors across growth, profitability, reputation, innovation, and adoption. And the flexibility that this culture of autonomy and adaptability provides will allow me to be flexible too, as I deal with the birth of my child. How to embed flexibility within your organization If you dont have flexibility embedded in your organization, the following can be helpful: Encourage cross-training: Let your team experiment and explore new skills, or take on “side quests” as we like to call them, even if it doesnt support their primary role. If only one person knows how something works, thats a risk. Theres high value in having people who can step in when a problem arises, and the person whose job it is to fix it is unavailable. Give your team some slack: Its okay to set deadlines and timelines, but if you dont leave room for issues to arise and situations to change, thats a problem. When theres no time to adjust (and you inevitably miss deadlines), you start to associate change with failure. Plan for scenarios, not certainties: You cant set one plan and expect the universe to deliver. There are many potential outcomes to any given situation, so it helps to agree in advance how you would respond to each one. When you anticipate change rather than react to it, it becomes way less scary. Take a momentary step back: Make yourself unavailable for a day and see where the system wobbles. Its useful to identify where dependencies lie, what gaps exist, and where there isnt a clear sense of ownership. Pinpointing issues while the stakes are low gives you time to fix them before the system breaks down and youre not there to step in. Not knowing is part of the job The concept of the all-knowing leader is such a myth. Many leaders talk big, but the fact that 44% of founders suffer from imposter syndrome says it all. Were human, and nobody has it all figured out. Most of the time, were putting on a brave face and hoping for the best. If the experience of managing pregnancy and leadership has taught me anything, its that admitting I dont know yet isnt a weakness. Like early parenthood, startups are full of unknowns. What separates good leaders isnt their ability to eliminate uncertainty, but how they equip their teams to respond when difficulties arise and circumstances inevitably change.
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E-Commerce
It’s hard to avoid the conclusion that the market for artificial intelligence and its associated industries are over inflated. In 2025, just five hyperscalersAlphabet, Meta, Microsoft, Amazon, and Oracleaccounted for a capital investment of $399 billion, which will rise to over $600 billion annually in coming years. For the first nine months of last year, real GDP growth rate in the U.S. was 2.1%, but would have been 1.5% without the contribution of AI investment. This dependence is dangerous. A recent note by Deutsche Bank questioned whether this boon might in fact be a bubble, noting the historically unprecedented concentration of the industry, which now accounts for around 35% of total U.S. market capitalization, with the top 10 U.S. companies making up more than 20% of the global equity market value. For such an investment to yield no benefit would be a failure of unprecedented proportions. In their book Power and Progress, Nobel Prize-winning economists Daron Acemoglu and Simon Johnson narrate the calamitous failure of the French Panama Canal project in the late 19th century. Thousands of investors, large and small, lost their fortunes, and 20,000 people who worked on the project died for no benefit. The problem, Acemoglu and Simon write, was that the vision for progress did not include everyoneand failure to incorporate feedback from others resulted in poor quality decision making. As they observe, what you do with technology depends on the direction of progress you are trying to chart and what you regard as an acceptable cost.Fast forward 150 years and a significant chunk of the U.S. economy is similarly dependent on a small coterie of grand visionaries, ambitious investors, and techno-optimists. Their capacity to ignore their critics and sideline those forced to bear the costs of their mission risks catastrophic consequences. Trustworthy AI systems cannot be conjured by marketing magic. We must ensure those building, deploying, and working with these systems can have a say in how we direct the progress of this technology. Mistrust and a general lack of optimism The data suggests that there is an urgent need to chart a new course. Even a generous analysis of the market for generative AI products would likely struggle to show how a decent return on the gargantuan investment in capital is realistic. A recent report from MIT found that notwithstanding $30 billion to $40 billion in enterprise investment into GenAI, 95% of organizations are getting zero return. It is difficult to imagine another industry raising so much capital despite producing so little to show for it. But this appears to be Sam Altmans true superpower, as Brian Merchant has documented extensively. This is coupled with significant levels of mistrust and a general lack of optimism from everyday people about the potential of this technology. In the most comprehensive global survey of 48,000 people across 47 countries, KPMG found that 54% of respondents are wary about trusting AI. They also want more regulation: 70% of respondents said regulation is necessary, but only 43% believe current laws are adequate. The report concludes that the most promising pathway towards improving trust in AI was through strengthening safeguards, regulation, and laws to promote safe AI use. This, most obviously, sits in stark contrast with the position of the Trump administration, which has repeatedly framed regulation of the industry as an impediment to innovation. But the trust deficit cannot simply be hyped out of existence. It represents a significant structural barrier to the take up and valuable deployment of emerging technologies. One of the key conclusions of the MIT report is that the small subset of companies that actually saw productivity gains from generative AI products were doing so because they build adaptive, embedded systems that learn from feedback. Highly centralized decisions about procurement were more likely to result in employees being required to use off-the-shelf products unsuited to the enterprise environment and generating outputs that employees mistrusted, especially for higher-stakes tasks, resulting in work arounds or dwindling rates of usage. The problem is that these tools fail to learn and adapt. In turn, there are too few opportunities for executives to receive that feedback or incorporate it meaningfully into model development and adaptation. The narrative spun by politicians and media commentators that the AI industry is full of visionary leaders inadvertently points to a key cause of why these products are failing. Trust in AI systems can only be earned if feedback is both sought and acted onwhich is a significant challenge for the hyperscalers, because their foundational models are less capable of adapting and responding to unique and varied contexts. Unless we decentralize the development and governance of this, the benefits may remain elusive. The workers’ view There are useful ideas lying around that could help navigate a different path of technological progress. The Human Technology Institute at the University of Technology Sydney published research about how workers are treated as invisible bystanders in the roll out of AI systems. Through deep, qualitative consultations with nurses, retail workers, and public servants to solicit feedback about automated systems and their impact on their work. Rather than exhibiting backward or unhelpful attitudes to AI, workers expressed nuanced and constructive contributions to the impact on their workplaces. Retail workers, for example, talked about the difficulties of automated systems that disempowered workers, and curtailed their discretion: unlike a production line, retail is an unpredictable environment. You have these things called customers that get in the way of a nice steady flow. A nurse noted how “the increasing roll-out of automated systems and alerts causes severe alarm fatigue among nurses. When an (AI system) alarm goes off, we tend to ignore or not take it seriously. Or immediately override to stop the alarm. One might think that increased investment in such systems would contend with the problem of alarm fatigue. But without worker input, its easy to miss this as a problem entirely. The upshot is that, as one public servant put it, in workplaces whre channels for worker feedback are absent, a necessary quality of employees was “the gift of the workaround.” Traditionally, this kind of consultation and engagement would happen through worker organizations. But with the rate of unionization slipping below 10% in the U.S., this becomes a problem not just for workers but also employers, who are left with few methods to meaningfully engage with their workforce at scale. Some unions are nonetheless leading on this issue, and in the absence of political leadership, might be the best hope of making change. The AFL-CIO has developed a promising model law aimed at protecting workers from harmful AI systems. The proposal focuses on limiting the use of worker data to train models, as well as introducing friction into the automation of significant decisions, such as hiring and firing. It also emphasizes giving workers the right to refuse to follow directives from AI systemsessentially, building in feedback loops for when automation goes wrong. The right to refuse is an essential failsafe that can also cultivate a culture of critical engagement with technology, and serve as a foundation for trust. Businesses are welcome to ignore workers views, but workers may end up making themselves heard in other ways. Recent surveys indicate that 31% of employees admit to actively sabotaging their companys AI strategy, and for younger workers, the rates are even higher. Even companies that fail to seek feedback from workers may still end up receiving it all the same. Our current course of technological progress relies on narrow understandings of expertise and places too much faith in small numbers of very large companies. We need to start listening to the people who are working with this technology on a daily basis to solve real world problems. This decentralization of power is a necessary step if we want technology that is both trustworthy and effective.
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E-Commerce
Fujifilms newest camera model, the Instax Mini Evo Cinema, is a gadget thats designed for the retro camera craze. The device is a vertically oriented instant camera that can take still images, videos (an Instax camera first), connect with your smartphone to turn its photos into physical prints, and capture images in a wide range of retro aesthetics. Its debuting in North American markets in early February for $409.95. Fujifilms new model taps into a younger consumer bases growing interest both in retro tech and film photography aestheticsa trend thats been driven, in large part, by platforms like TikTok. The Instax Mini Evo Cinema turns that niche into a clever feature called the Gen Dial: a literal dial that lets users toggle between decades to capture their perfect retro shot. [Photo: Fujifilm] How the Gen Dial works Almost everything about the Instax Mini Evo Cinema screams nostalgia, from its satisfying tactile buttons to its vertical orientationand thats by design. According to Fujifilm, the cameras silhouette is inspired by the 1965 Fujica Single-8, an 8-millimeter camera initially introduced as an alternative to Kodaks Super 8. While the Instax Mini Evo Cinema does come with a small LCD display, its main functions are controlled with a series of dials, buttons, and switches, which Fujifilm says are designed to evoke the feel of winding film by hand, add to the analog charm, and expand the joy of shooting and printing. The most innovative of these is undoubtedly the Gen Dial. While there are plenty of existing editing apps and filter presets to give a photo a certain vintage look in-post, this may be the first instant camera to actually brand in-camera filters by era. [Photo: Fujifilm] The dial is labeled in 10-year increments, from 1930 to 2020. To choose an effect, users can simply click to the era theyd like to replicate, then shoot and print. According to the company, selecting 1940 will result in a look inspired by the vivid color expression of the three-color film processes, for example; 1980 pulls cues from 35-millimeter color negative film; and 2010 evokes the style of early smartphone photo-editing apps (throwback!). “Overall, our goal with Mini Evo Cinema is to deepen options for creative expression,” says Ashley Reeder Morgan, VP of consumer products for Fujifilm’s North America division. “Beyond video, the Gen Dial provides an experience to transcend time and space over 100 years (10 eras), applying both visual and audio to the mini Evo Cinema output.” From left: 1940, 1980, and 2010 styles [Photos: Fujifilm] For amateur photographers looking to achieve a certain vintage aesthetic without spending endless hours in Adobe Lightroom or fiddling with complicated camera settings, its the perfect intuitive solution. Retro cameras get a TikTok-driven boost For Fujifilm, the Instax Mini Evo Cinema is part of a broader, internet-driven revival of the brands camera division. While Fujifilm previously spent years moving away from its legacy camera business to focus on healthcare, its $1,599 retro-themed X100V camerawhich went viral on TikTokrecently triggered a resurgence in its sales. The companys most recent financials, released in September, show that its imaging division (which includes cameras) experienced a 15.6% revenue increase year over year, which Morgan says is attributable to the success of its instant and digital cameras. “Overall, we have been thrilled to see younger generations rediscovering the joy of photography, whether instant, analog, or digital,” Morgan says. The X100Vs popularity online is likely driven by Gen Z and Gen Alphas interest in retro tech aesthetics (see: Urban Outfitters iPod revival), as well as a more general resurgence in film photography in recent years. Analog cameras are having a moment, and companies like Polaroid and Fujifilm are cashing in.
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E-Commerce
Anthropic’s Claude Code tool is having a moment: It’s recently become popular among software developers for its use of agents to write code, run tests, call tools, and multitask. In recent months the company has begun to stress that Claude Code isnt just for developers, but can let other kinds of workers build websites, create presentations, and do researchand stories about non-coders completing interesting projects have filled social media. The latest offering, called Cowork, is a new version (and a rebranding) of Claude Code for work beyond coding, and it could dramatically widen the audience for Anthropics tools within the enterprise. Cowork is in research preview and is available only to Anthropics $100-per-month Max plan subscribers; theres a waitlist for users on other plans. While Claude Code requires an API key and runs in the terminal, users can access Cowork through the Claude desktop app with a familiar chatbot interface. Most important, Cowork is built to access content stored in the file system on the users computer. A user can give the tool permission to modify, or just read, files in a given folder. They can also allow Claude to create new files or organize existing ones. The new tool could help Anthropic as it eyes an IPO in 2026 (reportedly at a $350 billion valuation), and may put additional pressure on Microsoft, which offers a number of predesigned AI agents (for things like research, analysis, and meeting facilitation) as part of its Copilot AI assistant. A December 2025 report from The Information claimed that Microsoft salespeople have been having trouble hitting their quotas selling the companys Azure (cloud) AI products (including agents and agent builders) to enterprises. Microsoft denied the report. Cowork can do simple things like organize a users desktop folders or the contents of a downloads folder. Or it can search folders and emails for recent expenses and collect them in a new folder. But its most powerful use cases involve more complicated tasks. The tool can produce slide decks, large reports, or spreadsheets by calling up local (folder) data or data from connected business tools (such as Microsoft Teams or Zendesk) and then synthesizing the information. For multipart tasks, Cowork can create subagents for each part. Each of the subagents start with a clean context window so it has plenty of room to gather and remember information about its task. (In single chats with complex tasks, chatbots sometimes run out of context window memory, or become overwhelmed with data and then fail to make sense of it.) For example, a user might present the tool with a long document, then ask the AI to analyze it from different perspectives (legal, financial, ethical, public relations, etc.). A main agent might assign each perspective to a subagent. Each subagent would work independently to collect data and form a draft document, then return to sync up its work with that of the other subagents. A master document would be created and delivered to the user. Then the user might begin talking to the chatbot about how to refine the result. The Anthropic model that underpins Cowork is the same or very similar to the ones that power Claude Code. These models have already spent a significant amount of time working with real-world developers on real work. The models have already seen lots of different kinds of complex tasks, including unique edge cases, and have run into many types of roadblocks. Theyve been trained on lessons learned from that experience. For those reasons, along with the inherent quality of Anthropics models, workers may find in Cowork their first taste of AI agents that build trust through qualitywhich could change how people see the technology as a tool that can actually help them at work.
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E-Commerce
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