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As a home business owner, knowing when to say no can be just as crucial as knowing when to say yes. Have you ever faced opportunities that seemed tempting but didn’t align with your goals? **Focus on Your Vision**: It’s easy to get sidetracked by investor offers or partnership proposals that don’t fit your business model. Prioritizing your core vision helps maintain your focus and accelerates your startup’s growth. **Evaluate Opportunities**: Not every opportunity is worth your time. Assess each potential partnership or investment against your strategic goals to determine its true value. **Practice Saying No**: It’s a skill that can be developed. Being direct yet respectful when declining can help you maintain professional relationships while keeping your business on track. **Set Boundaries**: Establish clear criteria for what types of opportunities you will consider. This helps streamline decision-making and prevents you from being overwhelmed by choices. In the fast-paced world of entrepreneurship, the ability to say no can be just as powerful as any business idea or side hustle you pursue. What strategies do you use to evaluate opportunities? Share your thoughts below! Ready to take the next step? join our home business community and connect with thousands of solopreneurs sharing real strategies. View the full article

As a home business owner, staying updated on successful passive income strategies can be a game changer for your financial freedom. What strategies have you found most effective in your journey? **Understanding Change in Leadership** The recent transition of ownership at Smart Passive Income signifies a fresh perspective on passive income ideas and strategies. With new leadership, there’s potential for innovative approaches that could benefit entrepreneurs looking to diversify their income streams. **Embracing New Strategies** The new owner brings a wealth of experience and a commitment to enhancing the platform's offerings. This could mean updated resources, new courses, and fresh insights that reflect the evolving landscape of passive income. **Community Engagement** Engaging with the community is crucial for any platform's success. As the new owner emphasizes collaboration and feedback, this is a great opportunity for you to share your thoughts and experiences. Your input could help shape future content and strategies that resonate with home business owners. **Final Thoughts** Change can be daunting, but it also opens doors to new opportunities. Keep an eye on Smart Passive Income for upcoming strategies that could elevate your passive income game. What are your thoughts on this transition? Have you had any experiences with changes in leadership that impacted your business? Ready to take the next step? join our home business community and connect with thousands of solopreneurs sharing real strategies. View the full article

As a home business owner, fostering a productive team dynamic is crucial for success. Have you considered how healthy disagreement might actually benefit your operations? **Encourage Open Dialogue:** It's essential to create an environment where team members feel comfortable expressing differing opinions. When people are afraid to voice their thoughts, you risk stagnation and missed opportunities. **Value Diverse Perspectives:** Embracing disagreement can lead to innovative solutions. When team members challenge each other's ideas, they often uncover new angles and strategies that can propel your business forward. **Set Ground Rules:** Establish guidelines for constructive conflict. This ensures that disagreements remain respectful and focused on ideas rather than personal attacks, leading to a more cohesive team. **Facilitate Regular Check-Ins:** Regular discussions can help normalize disagreement. Use these sessions to encourage team members to share their thoughts openly, reinforcing the idea that differing viewpoints are valued. **Lead by Example:** As a leader, demonstrate how to handle disagreements constructively. Your approach will set the tone for your team and encourage them to engage in healthy debates. Incorporating these strategies can transform how your team collaborates and innovates. What methods have you used to encourage healthy disagreement in your business? Share your experiences below! Ready to take the next step? join our home business community and connect with thousands of solopreneurs sharing real strategies. View the full article

As a home business owner, understanding passive income can be a game-changer for your financial strategy. What are your thoughts on the most effective passive income ideas and strategies? **Why Passive Income Matters** Passive income allows you to generate revenue without the constant grind of active work. This can free up your time to focus on other aspects of your business or personal life. **Diverse Income Streams** Consider exploring various avenues such as real estate investments, affiliate marketing, or digital products. Each option requires different levels of initial investment and ongoing management, so choose what aligns best with your skills and resources. **Long-Term Vision** Building a successful passive income stream takes time and effort upfront, but the long-term benefits can significantly outweigh the initial challenges. It’s crucial to stay committed and continuously evaluate your strategies to ensure they are yielding the desired results. **Engage with the Community** What passive income strategies have you tried, and what results did you see? Sharing your experiences can help others in the community refine their approaches and inspire new ideas. Let's discuss your insights and strategies for creating sustainable passive income! Ready to take the next step? join our home business community and connect with thousands of solopreneurs sharing real strategies. View the full article

As a home business owner, understanding the dynamics of ownership transitions can provide valuable insights into building your own passive income streams. Have you ever considered how acquisitions can impact your business strategy? **Liz Wilcox’s recent acquisition of Smart Passive Income (SPI)** is a prime example of how strategic moves can reshape a brand and its offerings. Here are some key takeaways: **1. Focus on Value Creation:** Liz didn’t just buy a brand; she bought a community. This highlights the importance of creating value for your audience, which is essential for any passive income strategy. **2. Diversification of Income Streams:** With her background in email marketing and content creation, Liz is likely to diversify SPI’s offerings. This teaches us that having multiple income streams can safeguard against market fluctuations. **3. Leveraging Existing Assets:** Liz plans to utilize SPI’s existing resources and audience. As a home business owner, consider what assets you already have that can be leveraged to enhance your income. **4. Community Engagement:** Liz emphasizes the importance of engaging with the SPI community. Building a loyal following can significantly boost your passive income potential. Reflecting on these points, what strategies are you currently implementing to enhance your passive income? Share your thoughts and let’s discuss! Ready to take the next step? join our home business community and connect with thousands of solopreneurs sharing real strategies. View the full article

As a home business owner, maintaining a steady growth in your audience is crucial for sustainable passive income. Have you ever faced a sudden drop in your subscribers, and how did you handle it? **Understanding Subscriber Loss** Losing 17,000 subscribers can feel devastating, but it’s essential to analyze the reasons behind this drop. Factors may include changes in content relevance, audience engagement, or even external market shifts. Recognizing these elements can help you pivot your strategy effectively. **Reassessing Your Content Strategy** Evaluate your content to ensure it aligns with your audience's interests. Are you providing value that keeps them engaged? Consider conducting surveys or polls to gather feedback directly from your subscribers. This can guide you in tailoring your content to better meet their needs. **Diversifying Your Income Streams** Relying solely on one source of passive income can be risky. Explore additional avenues such as affiliate marketing, online courses, or digital products. By diversifying, you can mitigate the impact of subscriber loss on your overall income. **Leveraging Social Media** Utilize social media platforms to reconnect with your audience. Share valuable insights, updates, and engage in conversations that resonate with your brand. Building a community around your content can help regain lost subscribers and attract new ones. **Analyzing Metrics** Regularly review your analytics to understand subscriber behavior. Identify trends and patterns that can inform your strategy moving forward. This data-driven approach can help you make informed decisions to enhance your passive income strategies. **Conclusion** Subscriber loss is a challenge, but it can also be an opportunity for growth and improvement. What strategies have you implemented to recover from subscriber loss, and what lessons have you learned from the experience? Share your thoughts! Ready to take the next step? join our home business community and connect with thousands of solopreneurs sharing real strategies. View the full article

Vice-president Luis de Guindos says Washington’s volatile trade policies and reduced co-operation also threaten stabilityView the full article

Curiosity is one of the most consequential forces in human history. Every scientific breakthrough, technological leap, and cultural advance begins not with knowledge, but the desire to know. At its core, curiosity drives us to close the gap between what we know and what we want to know, a cognitive itch triggered by uncertainty and resolved through learning and the pursuit of meaning. Curiosity as an evolutionary advantage Early humans who explored their environments, experimented with tools, and learned from novel stimuli were more likely to secure resources, avoid threats, and pass on their genes. As a result, curiosity became embedded in our biology, reinforced by neural reward systems that make learning intrinsically pleasurable. In line, neuroscientific research shows that curiosity activates the brain’s dopaminergic pathways, the same circuits involved in motivation and reward, which explains the positive correlation between curiosity and impulsivity. When we encounter a gap in our knowledge, we experience a mild form of cognitive discomfort. Resolving that gap produces satisfaction, reinforcing future exploration. In that sense, curiosity is a built-in, biologically coded feedback loop for learning. But evolution also imposed constraints. Curiosity, like any adaptive trait, is beneficial only within limits. For example, there are many scenarios in which too much exploration could prove fatal. A hunter-gatherer wandering too far from their tribe risked encountering predators or hostile groups. In such contexts, restraint was adaptive. Curiosity had to be expressed with caution. This tension between exploration and exploitation remains with us today. We are wired both to seek novelty and to prefer predictability. The familiar is efficient but boring; the unknown is exciting but costly. History offers similar patterns. During periods of intellectual repression, such as the Inquisition, curiosity was actively punished, making individual inquiry dangerous. By contrast, the Enlightenment celebrated curiosity as a virtue, unleashing scientific and philosophical progress. The same underlying human drive manifested differently depending on cultural conditions. Curiosity, then, is universal, but its expression is highly variable. The paradox of AI: A triumph that threatens its own foundation Fast forward to the present, and we are witnessing one of humanity’s greatest achievements: artificial intelligence. The convergence of mathematics, computer science, and data has enabled machines to simulate aspects of human cognition. We have, in effect, built systems that can approximate, emulate, and even surpass our thinking. Even if AI stopped evolving tomorrow (which seems unlikely), its implications are already profound. AI can augment human capability, accelerate problem-solving, and democratize access to knowledge. It functions as a cognitive copilot, allowing individuals to perform tasks that once required entire teams. But every technological advance also carries unintended consequences. And in the case of AI, the risks are not just economic and ethical, but psychological, too. Specifically, AI threatens to erode curiosity. The erosion of curiosity in the age of artificial certainty Curiosity depends on uncertainty. It requires a gap between what we know and what we want to know. AI, by design, collapses that gap. When answers are instantly available, prepackaged, and delivered with confidence, the motivation to explore diminishes. Why struggle with a problem when a machine can solve it in seconds? Why engage in deep learning when surface-level understanding is sufficient to get by? This is what I have described elsewhere as “artificial certainty.” AI does not just provide answers; it creates the illusion that we understand them. The output is coherent, fluent, and persuasive. But coherence is not comprehension. The result is a shift from active to passive cognition. We consume knowledge rather than generate it. We outsource thinking rather than exercise it. A useful analogy is physical fitness. Imagine a world where machines do all the lifting for you. Your muscles would atrophy. The same applies to the mind. Curiosity is a mental muscle, and like any muscle, it weakens with disuse. In this sense, AI is the equivalent of a microwave for ideas. It delivers fast, convenient results, but often at the expense of depth and craftsmanship. We move from “slow thinking,” which is effortful and reflective, to “fast consumption,” which is effortless but shallow. There is also a linguistic irony worth noting. “Deep learning,” once a human aspiration, is now primarily associated with machines. Meanwhile, human learning risks becoming increasingly superficial, if not dormant. To be sure, such concerns may ultimately prove overstated, as they often have in the past. Socrates, after all, warned that writing would erode memory, fearing that reliance on external tools would weaken internal capacities. Yet history also suggests that overcorrection is safer than complacency. There are, in fact, good reasons to be vigilant: When effort is removed from the learning process, engagement tends to decline; when answers are readily available, the incentive to question diminishes; and when cognition is outsourced too readily, the underlying skills can atrophy. The point is not to resist technological progress, but to ensure that convenience does not quietly displace the very mental habits that made such progress possible in the first place. What the science says about cultivating curiosity If curiosity is both essential and at risk, the obvious question is: Can it be developed? The answer is yes, but not in the simplistic way often suggested. Curiosity is influenced by both stable traits and situational factors. While some individuals are naturally more curious than others, environments and habits play a critical role. Before diving into what to do, it is worth pausing on a more basic question: How curious are you, really? The first step is a proper self-assessment. Not the flattering version you might hold of yourself, but a more objective view grounded in data and external feedback. Curiosity is closely linked to well-established personality traits, particularly openness to experience, one of the Big Five, which captures intellectual curiosity, imagination, and a preference for novelty. Science-based assessments can provide a reliable baseline here. So can 360-degree feedback, which often reveals a gap between how curious we think we are and how we are experienced by others. Even informal input from colleagues, friends, or mentors can be illuminating, especially when it highlights whether you ask thoughtful questions, challenge assumptions, or genuinely engage with new ideas. Equally important is specificity. Curiosity is not a uniform trait. People are rarely equally curious about everything. Reflect on where your curiosity naturally shows up and where it does not. You may be deeply inquisitive about ideas but indifferent to people, or fascinated by technology but incurious about history, culture, or opposing viewpoints. Mapping these patterns matters, because developing curiosity is not about becoming universally interested in everything. It is about understanding your blind spots and deliberately expanding into areas where your instinct is to disengage. First, intrinsic motivation matters. Studies grounded in self-determination theory show that curiosity flourishes when individuals feel autonomous, competent, and connected to others. In practical terms, this means people are more curious when they pursue topics that genuinely interest them, rather than those imposed externally. The implication for organizations is clear: forced learning rarely produces genuine curiosity. Second, exposure to novelty is key. Curiosity thrives on diversity of input. Interacting with people from different backgrounds, disciplines, and perspectives increases the likelihood of encountering information gaps. This is why interdisciplinary environments are often more innovative. They create friction between ideas. Third, habits of reflection enhance curiosity. Research on learning and memory suggests that active engagement, such as writing, teaching, or debating, deepens understanding and sustains curiosity. Passive consumption, by contrast, leads to the illusion of knowledge without real insight. Fourth, time allocation matters. Curiosity requires cognitive space. In environments dominated by urgency and efficiency, there is little room for exploration. Scheduling time for reading, thinking, and unstructured inquiry is not a luxury; it is a necessity. Fifth, tolerance for uncertainty is crucial. Individuals with a high need for cognitive closure prefer quick answers and are less likely to engage in open-ended exploration. Developing comfort with ambiguity, through practices such as Socratic questioning or deliberate exposure to complex problems, can enhance curiosity. Finally, there is evidence that curiosity can be trained through small behavioral interventions. For example, prompting individuals to generate questions before receiving answers increases engagement and retention. Similarly, framing tasks as puzzles or challenges can activate curiosity-driven motivation. These findings align with the broader argument that curiosity is not a fixed trait but a dynamic capability shaped by both internal and external factors. The role of leaders in modeling curiosity While individual strategies matter, curiosity is ultimately a social phenomenon. It is shaped, amplified, or suppressed by cultural norms. From early childhood, curiosity is not simply an individual trait but a product of developmental context. Parents, teachers, and early environmental experiences play a decisive role in shaping how, and whether, curiosity endures into adulthood. Research in developmental psychology shows that children whose caregivers respond contingently to their questions, encourage exploration, and tolerate uncertainty tend to develop higher levels of intrinsic curiosity. Conversely, environments that emphasize compliance, correct answers, and performance over inquiry can suppress exploratory behavior over time. Educational studies also find that classroom climates prioritizing rote learning and standardized outcomes often erode students’ natural inquisitiveness, even when baseline curiosity is high. Longitudinal evidence suggests that these early patterns persist, shaping adult tendencies toward intellectual risk-taking, openness, and lifelong learning. In short, curiosity is cultivated or constrained early, but its trajectory can be reinforced or reversed later, especially through social and organizational contexts. This is where leadership becomes critical. Leaders set the tone for what is valued. If they prioritize certainty, speed, and efficiency above all else, curiosity will decline. Employees will learn to avoid questions, minimize exploration, and focus on immediate outputs. Conversely, leaders who model curiosity create environments where inquiry is rewarded. This does not mean celebrating randomness or distraction. It means demonstrating intellectual humility, asking better questions, and showing a willingness to challenge assumptions. One of the most powerful signals a leader can send is admitting what they do not know. This reduces the perceived cost of ignorance and encourages others to engage in learning. It also counteracts overconfidence, which is one of the main barriers to curiosity. Leaders can also design systems that embed curiosity into workflows. This includes allocating time for experimentation, encouraging cross-functional collaboration, and measuring not just outcomes but learning processes. Importantly, curiosity must be linked to performance. It is not about asking more questions for their own sake, but about asking better questions that lead to better decisions. In the age of AI, this becomes even more important. As machines take over routine cognitive tasks, the human advantage shifts to areas that require judgment, interpretation, and creativity. These are all downstream of curiosity. But judgment without experience is meaningless. AI can simulate answers, but it cannot substitute for the depth that comes from actually engaging with the world. There is a difference between consuming a microwaved meal and cooking one from scratch, sourcing ingredients, understanding how they interact, and adjusting along the way. The former is efficient and convenient; the latter builds intuition, tacit knowledge, and real expertise. In the same way, relying on AI-generated outputs without cultivating firsthand learning experiences produces a thin version of competence, what might be called artificial understanding. Curiosity, when acted upon, pushes us into those richer experiences that give judgment its substance and make our thinking genuinely our own. Curiosity as a strategic imperative The rise of AI has not just expanded access to information; it has quietly eroded the premium once attached to possessing it. When virtually all answers are instant, abundant, and convincingly packaged, the differentiator is no longer what you know, but how you engage with what can be known. In that sense, the economics of expertise are shifting. Knowledge, at least in its most accessible forms, is becoming commoditized, while the capacity to interrogate, refine, and build on that knowledge is becoming scarcer and more valuable. This is where curiosity earns its value, not as a soft or “nice to have” trait, but as the underlying mechanism that sustains learning over time. Without curiosity, the risk is not ignorance, but something more insidious: the illusion of understanding. AI can generate coherent explanations, summarize complexity, and produce plausible insights at scale. But unless these outputs are met with questioning, skepticism, and a desire to go beyond what is given, they are unlikely to translate into genuine insight or better decisions. The danger, then, is not that machines will think for us, but that we will gradually outsource the very effort required to think well, confusing fluency with depth and access with mastery. This places a different kind of demand on individuals and organizations. The task is no longer simply to adopt AI tools or increase their usage, but to integrate them in ways that augment rather than atrophy human judgment. At the individual level, this implies a degree of intentionality that is often underestimated: cultivating habits that prioritize inquiry over convenience, depth over speed, and exploration over closure. At the organizational level, it requires more than rhetoric about innovation. It calls for environments where questioning is not penalized by the pressures of efficiency, and where time spent exploring is not automatically seen as time wasted. And at the leadership level, it demands a visible commitment to curiosity as a norm, expressed less through slogans and more through behavior: the questions senior exeuctives ask, the uncertainty they tolerate, and the assumptions they are willing to revisit, will all shape the organization’s level of curiosity and appetite for learning. There is an obvious irony here. The more capable our machines become at producing answers, the more valuable it becomes to remain interested in the questions. This is not a nostalgic defense of human uniqueness, but a pragmatic recognition of where advantage now lies. In a world where everyone has access to the same tools, and AI becomes as ubiquitous as smartphones, Wi-Fi, or electricity, the differentiating factor shifts to how those tools are used, and that, in turn, depends on the quality of human curiosity brought to bear on them. Seen in this light, curiosity becomes a strategic necessity, one that shapes not only how individuals learn, but how organizations adapt and compete in an environment where knowing is easy, but understanding remains hard, and is quietly becoming a niche pursuit. View the full article

As 7.4 million Americans sit unemployed, the path to employment has completely changed. Amid fake listings, AI filtering of candidates and widening talent pools, job seekers believe that they’re competing against a hiring ecosystem that penalizes honesty and rewards perception. The result? A hiring environment where the signals employers have traditionally relied on to evaluate candidates have become deeply unreliable. Now, both sides are operating with diminishing trust in each other. What’s Driving the Deception? Hiring today is not facing a character problem, but a structural one. When candidates believe that presenting themselves accurately will cost them a job offer, the rational response is to become the person they think the employer is looking for. But when this approach becomes standard, those who still choose to tell the truth take on an “honesty tax,” the systemic disadvantage honest candidates face when exaggeration becomes the market norm. GCheck’s Trust in Hiring Report revealed that 93% of job seekers have lied or embellished their experience during the hiring process, while 60% do not believe they would have been hired had they presented their qualifications more accurately. This is beyond a confession—it’s a market signal. Part of what drives this dynamic is opacity on the employer side. When candidates do not know what will be verified, they assume the answer is minimal, and they calibrate their self-presentation accordingly. In fact, GCheck found that although 88% of job seekers believe misrepresentation puts businesses at risk, 53% assumed employers wouldn’t verify their claims and only about a quarter (26%) report ever being caught lying or exaggerating. Verification that is invisible to candidates is not a deterrent. It is permission. And thanks to artificial intelligence, candidates can disguise their true skills and identity almost instantaneously. AI Accelerates Dishonesty in Hiring LinkedIn’s 2025 Work Change Report estimates that 70% of the skills used in most jobs will change by 2030, driven largely by AI. When job seekers navigate a market where the definition of “qualified” is constantly shifting, the pressure to appear more capable than they are significantly intensifies. AI has not created that pressure, but it has handed candidates sophisticated tools to act on it at every stage of the hiring process. Employer concerns have moved beyond job seekers’ using AI to compile resumes or assist with writing. Now, the degree to which AI has migrated into live interviews and assessments is worrisome. GCheck found that 61% of candidates have used AI to rehearse interview answers until they sounded more impressive than authentic, and 25% reported deploying an AI avatar in place of their own face during a virtual interview. ​ The result is a hiring process where trust is eroding on both sides. On one hand, candidates feel pressure to optimize and automate their performance in a highly mediated, virtual environment; on the other, employers struggle to assess who is genuinely behind the screen. When interviews are increasingly remote, scripted and technology driven, the lines between preparation and performance become blurred. This highlights how broken and transactional the modern hiring process has become. There’s also an emerging phenomenon of systematic embellishment, distortion or fabrication of professional qualifications across resumes, interviews, and references as a deliberate competitive strategy driven by market pressure and weak verification expectations. It’s been dubbed “careerfishing,” and it’s no longer the behavior of a fringe group. What Employers Must Do to Rebuild Trust Rebuilding trust in hiring is not only a technology problem, but also a standards and transparency issue. Employers who treat verification as a confidential back-end process get exactly what opacity produces: candidates who assume they can game the system, largely because they can. Three leadership-level shifts matter most here: Make verification standards visible. Communicate what will be checked before a candidate applies. Transparency disrupts embellishment at its source, not after the offer. The FTC’s guidance on employment background checks under the FCRA already mandates disclosure at specific stages. Moving that clarity upstream changes candidate behavior earlier in the process in measurable ways. For example, candidates who know credentials or work samples will be actually verified are less likely to exaggerate or rely on AI-generated materials they cannot defend later. Make screening decisions reviewable by a person. Candidates who know a human will review findings, not only an algorithm, engage with the process more honestly. Make verification proportionate to actual risk. Applying the same screening depth to every role signals to candidates that the process is performative. Calibrating scope to genuine role risk makes verification more credible, more defensible, and more likely to deter the embellishment it is meant to catch. In recent years, hiring integrity has evolved from a checkbox exercise into a strategic priority. When AI-driven careerfishing corrupts the foundational data a company uses to build its workforce, the damage surfaces in performance gaps. The goal is not to catch more people lying. The goal is to build a hiring environment where honesty carries a genuine advantage rather than a competitive penalty. When employers operate transparently and verify consistently, they stop performing diligence and start practicing it. That distinction is what separates organizations that attract trustworthy people from those that inadvertently select for the most convincing ones. View the full article

The outgoing chair has made some mistakes, but his decision to stand up to The President was heroicView the full article

Chinese territory enjoys surge of investment from mainland as wealthy spread assets across different jurisdictionsView the full article

Andrius Kubilius pushes for governments to open weapons stockpiles to Ukraine View the full article

Despite $17bn in pledges, organisation is stuck in limbo with no money flowing to projects in GazaView the full article

Sovereign borrowers look to issuance in US dollars, Swiss francs and other currenciesView the full article

The technology opens the door for smaller, well-funded challengers to take market share from the Big Four and others View the full article

Agreement with unions ends wrangling over how to share spoils of boom at memory-chip makerView the full article

Albert Manifold’s behaviour and use of personal devices cited as factors in his removal over conduct and governance concernsView the full article

Hands-on approach was viewed as aggressive by several colleagues at UK oil majorView the full article

Foreign Office announces measures against Huobi among several entities it says helped Russia evade economic pressureView the full article

Last weekend, when Puck announced that the sustainable fashion startup Everlane had been acquired by the Chinese ultra fast fashion retailer Shein, it sent shockwaves throughout the fashion world. Michael Preysman, who founded Everlane in 2011, was just as shocked. “I found out the same time as everyone else,” he said in a LinkedIn post a week ago. “I’m not involved with the company anymore, and like many, am still digesting the news.” Well, Preysman is done digesting. And it seems that he’s ready to do something about it. Preysman just announced stillradical.com, a new venture that we know little about other than the bare bones website it launched with. The website lays out the new vision with brevity: “I started Everlane in 2011. Last week, the current management team sold it to Shein. So we’re starting over. Same principles, but a new take. And this time: no venture capital, no private equity.” The site says you can learn more by signing up for a waitlist. (Preysman did not respond to a request for comment.) Preysman launched Everlane when he was in his mid-20s, after starting his career in finance. His vision was to sell high quality products directly to customers online, without the markup of middlemen like department stores. This helped kickstart the direct-to-consumer movement that dominated the 2010s, producing brands like Away, Warby Parker, Allbirds, and Glossier. To fuel its growth, Everlane took an undisclosed amount of venture capital. A few years in, Preysman turned his attention to the human and environmental impact of the fashion industry. Everlane promised to eradicate virgin plastic from its supply chain, and showed customers inside the factories they used, to highlight how it was paying attention to the working conditions of laborers. All of this was good for business. By 2016, Everlane was valued at $250 million, although it was unclear whether it had ever become profitable. In recent years, its growth slowed. It went through two rounds of layoffs, once during the pandemic and then again in 2023. L. Catterton—the venture capital wing of the luxury conglomerate LVMH—bought a majority stake in Everlane in 2020. Shortly after, Preysman left the company to launch a new supplements brand called Magna in 2024. For many, Everlane’s acquisition by Shein was a disappointing final chapter for a company that stood for optimism and ethics. Clearly, Preysman felt the same way about it. This new business suggests that he hasn’t given up on the idea of sustainable fashion. However, he’s realized that venture capital is not the right tool for launching an apparel business. It will be fascinating to see what lessons Preysman has taken from the rise and fall of Everlane, and how we plans to build his new company differently. View the full article

Victory of flawed Senate candidate Ken Paxton could cement the president’s hold on the party View the full article

Current CEO Rick Thornberry is retiring as Radian shifts to a multi-line business, with former Mr. Cooper President Mike Weinbach taking over on Aug. 13. View the full article

Unlike some of his industry peers, OpenAI CEO Sam Altman has been surprisingly skeptical of the notion that AI is displacing workers. In an interview a few months ago, he argued that AI was a convenient scapegoat for some companies, echoing what some economists and experts have expressed about the narrative that AI is driving layoffs across corporate America. “I don’t know what the exact percentage is, but there’s some AI washing where people are blaming AI for layoffs that they would otherwise do. And then there’s some real displacement by AI of different kinds of jobs,” Altman said at the time. In an interview this week, however, Altman made a bolder statement, suggesting there was little evidence AI would do extensive damage to white-collar jobs, despite predictions to the contrary. “I’m delighted to ⁠be wrong about this,” he said on Tuesday during a virtual appearance at the Commonwealth Bank of Australia conference, according to a Reuters report. “I thought there would have been more impact on entry-level white-collar jobs being eliminated by now than ​has actually happened.” “My intuitions were just off,” he added. “People are like, ‘oh, you could have saved the world a lot of fear mongering and a lot of doom and gloom.’ But at the time I was like, ‘I see this is a real risk. We should probably ​talk about it.’” Part of the reason for this realization, Altman claims, is that he underestimated the human element that so many jobs require. He had tried using AI to field emails and Slack chats, but increasingly found himself responding to those messages himself—which apparently led him to believe the impact on jobs will be different than he had originally anticipated. “I don’t think we’re going to have the kind ​of jobs apocalypse that some of the companies in our space advocate or talk about,” he said. While companies have repeatedly cited AI and automation when conducting layoffs, the labor market does not yet reflect a mass reduction in jobs across the workforce. On top of that, even as tech leaders remain bullish about the promise of AI, there are signs that all their spending may not yield the results they are expecting. In another recent interview, an Uber executive cast doubt on the idea that the company’s AI investments had meaningfully boosted productivity, despite blowing through its 2026 AI budget in just a few months. On the Rapid Response podcast, Uber president Andrew Macdonald claimed the growing use of Claude Code tokens had not necessarily resulted in better features for consumers. “That link is not there yet, right? I think maybe implicitly there is more that is getting shipped, but it’s very hard to draw a line between one of those stats and, ‘Okay, now we’re actually producing 25% more useful consumer features,’” he said. Still, that awareness may not help preserve jobs, especially as companies demand greater productivity from their workforce. Whether or not AI can replace workers, tech employers continue making cuts to headcount to offset their sweeping AI investments. Some workers are already feeling the effects of widespread AI adoption, from Amazon warehouse workers to people who hold administrative jobs—and despite the concerns about white-collar employees, researchers have found there could be significant downstream effects for workers without college degrees. For all his talk, even Altman has noted that there’s a chance the fallout from AI could be worse than it seems right now—and that it could eventually come for his job, too. View the full article

Tehran vows to ‘not leave any mischief unanswered’ after the attacks View the full article

Most enterprise generative AI investments have yet to deliver the value companies envisioned, and every day, more leaders are recognizing that people lie at the heart of the struggle. In this year’s AI & Data Leadership Executive Benchmark Survey, 93% of executives leading AI and data efforts identified human issues around culture and change management as the primary obstacle to adoption. McKinsey Global Managing Partner Bob Sternfels put it plainly on HBR’s IdeaCast: “Half if not more of the secret sauce” in getting value from AI, he said, “is organizational change, as opposed to technology implementation.” As such, many leading companies have launched initiatives over the past several months to drive AI adoption across their workforces. These efforts run the gamut from carrot-to-stick approaches, with some rolling out hackathon programs and prizes for innovative uses. Others use weekly logins and token consumption as proxies for performance. A PERFORMATIVE APPROACH Leaders are right to focus on the people side of adoption. They need to be deliberate, however, about what they’re encouraging. I’ve learned something in my three decades helping some of the world’s largest companies through culture transformation. Employees prioritize what leaders model, incentivize, and reward. And initiatives built around shallow metrics can do more harm than good. It’s understandable why many leaders today celebrate deliverables simply because they were made with AI, or reward employees for integrating it into workflows. Facing underwhelming internal adoption metrics, many have come to see any increase in AI usage as a win. At my firm, however, we call this “trophy-style” AI adoption—which is to say, a performative approach focused more on usage than results. It’s focused on participation trophies over proof of impact. Leaders need to be wary of this trap. Because as anyone following the “workslop” problem or the emerging research on cognitive atrophy will know, not all AI use cases are created equal. Trophy-style adoption creates a dangerous illusion of progress, where activity masquerades as impact. In other words, we’re rewarding output over outcomes. A culture built around shallow adoption risks more than struggling to achieve ROI; in some cases, it might leave employees less equipped to meet business needs than prior to AI. IMPACTFUL ADOPTION Impactful AI adoption will look different based on the company, a person’s role, and many other factors. For some, it means deepening the quality of the same work product. For others, it means increasing output without sacrificing quality. And for still others, it means getting the same work done in less time, repurposing time and energy toward new questions and tasks. All the best adoption initiatives, however, will be reverse-engineered from the larger business strategy. They will be built around metrics that connect to it. The process of designing an adoption initiative should start with clarity and specificity around big-picture questions. What does value look like for our organization? How can different roles change to better deliver it? Leaders cannot lose sight of these framing questions as they determine what gets modeled and encouraged. Wise ones will drive for real business impacts that come from the usage. And when they showcase strong use cases, they will not just reward speed or deep integration. Instead, they will keep the focus on the larger picture, taking great care to explain the meaningful organizational outcomes driven by the use case. In Gagen MacDonald’s latest white paper, we dive into what it takes to do this well, and what organizations can do to bridge the separate realities that exist between leaders and employees around AI. Because while the employees who create the most impact with AI will certainly use it frequently, it’s a mistake to think of usage as synonymous with impact. And given how much companies have spent and plan to keep spending on this technology, it’s not a mistake many leaders can afford to make. Maril MacDonald is founder and CEO of Gagen MacDonald. View the full article