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In todays professional landscape, we face a paradox. Even as businesses increasingly seek candidates who have mastered adaptive skills like navigating ambiguity, communicating effectively, and demonstrating resilience through setbacks, our classrooms remain largely fixated on teaching content knowledge that AI can now provide instantly. This skills and readiness disconnect isnt new. Consider that most corporate leadership development programs have emphasized many of these same adaptive skillsaka soft skillsfor decades. The difference is we can now see the disconnect more clearly, and the consequences of inaction are dramatic. AI has become an X-ray for our education system, revealing critical fractures that have long been masked by traditional assessment methods. When information is universally accessible, success increasingly depends on developing adaptive skills that our current educational approach has struggled to prioritize because theyre notoriously difficult to teach and measure at scale. With AIs proliferation, this disconnect will become a chasm if we dont address it now. 3 pillars for instructor-enterprise collaboration The why behind addressing this disconnect is straightforward. Classrooms are the source of workforce readiness. The how is more complex but represents an unprecedented opportunity for instructors and enterprises to develop solutions together and learn from each other. I see three key opportunities for collaboration. 1. Use AI-powered technology to measure vital adaptive skills. Enterprises have long recognized the value of adaptive skills, but theyve struggled to reliably evaluate them during hiring processes and performance evaluations. Similarly, educators understand the importance of these skills but lack scalable methods to teach and assess them. This shared challenge presents an opportunity for collaboration. AI technologies like sentiment analysis, natural language processing, and behavioral pattern recognition can revolutionize how we measure previously intangible qualities. Imagine environments where learners receive real-time feedback on communication effectiveness, collaboration patterns, or problem-solving approachesnot just whether they arrived at the right answer. By collaborating to develop these assessment technologies, enterprises can help instructors understand which specific behaviors and capabilities correlate with workplace success, while instructors can provide insights into how these skills develop over time. The result is graduation requirements that reflect workforce needs and hiring practices that meaningfully evaluate candidate readiness. 2. Create immersive learning laboratories to develop AI fluency. Both traditional and workplace learning environments are facing what Omid Fotuhi, director of learning innovation at WGU Labs, calls the AI Trolley Problem. It borrows from the classic ethical thought experiment which asks whether one should pull a lever to redirect a runaway trolley, sacrificing one life to save five. Fotuhi uses the metaphor to describe a form of institutional paralysis: a deep discomfort with taking action that might cause harm, even when inaction guarantees it. When it comes to AI, theres a tendency to fixate on what might go wrong if we act, Fotuhi explained to me. But we rarely consider what might go wrong if we dont. This aversion to action, though rooted in caution, can quietly perpetuate harm. Failing to implement AI tools could also mean missed opportunities to provide more personalized learning, reduce burnout among educators, or close equity gaps at scale. In many cases, the cost of doing nothing is not neutralit’s compounding. We need to shift the frame, Fotuhi added. Yes, using AI carries risk. But so does sitting still. If we only focus on the potential harm of pulling the lever, we ignore the damage being done by letting the trolley barrel forward. One way of overcoming the risks could lie in creating collaborative learning environments where learners and professionals can safely experiment with AI tools. Enterprises can provide real-world business challenges and access to industry-specific AI applications, while instructors contribute pedagogical expertise and learning environments where failure carries no permanent consequences. These immersive learning laboratories would serve dual purposes: Help learners develop practical AI fluency theyll need in future careers, while giving enterprises insights into how next-generation workers approach and leverage these tools. Such environments would help foster the metacognitive abilities to determine when and how to best leverage AI. Those are skills that no machine can replicate. 3. Establish continuous feedback loops between learning environments and workplaces. The pace of technological change demands a more dynamic relationship between classrooms and enterprise than our current system allows. Annual curriculum reviews and occasional industry advisory boards are insufficient when workforce needs evolve monthly rather than yearly. We need continuous, bidirectional feedback mechanisms where learning innovations inform workplace practices and workplace needs shape learning priorities. This means embedding instructors within businesses and bringing industry professionals into classrooms as integral contributors to the learning ecosystem. AI can facilitate this exchange by aggregating and analyzing real-time data about skill demands across industries, helping instructors understand emerging trends before they become mainstream requirements. Simultaneously, instructors can share insights about learning approaches that effectively develop adaptability and resiliencequalities that enterprises increasingly recognize as essential for organizational agility. A more collaborative future At Udemy, we believe instructors must prepare learners not to compete with AI, but to leverage it effectively. This requires a fundamental shift from mere knowledge acquisition to developing the metacognitive abilities and street smarts that machines cannot replicate. This vision for the future extends to instructors, too. Far from replacing them, AI is poised to elevate their role. By automating administrative tasks, enabling personalized support at scale, and creating new ways to teach and measure adaptive skills, it offers opportunities to create learning environments where instructors have the time and tools to set learners up for success in an AI-powered world. For enterprises, this partnership with instructors means investing in the future workforce by contributing expertise, challenges, and resources to classroom innovation, rather than lamenting skills gaps after they emerge. The disconnect between instructors and enterprise is not new, but AI has simultaneously amplified its consequences and offered powerful solutions. By working together to reimagine education with AI as an enabling force rather than a threat, we ca build learning environments that prepare learners for a lifetime of adaptation and growth. Hugo Sarrazin is CEO of Udemy.
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E-Commerce
Elon Musks AI company xAI sued Apple and ChatGPT maker OpenAI in federal court on Monday, alleging they conspired to freeze out competition in both the smartphone and AI chatbot markets. But xAIs lawyers face an uphill battle in proving that Apples defaulting to ChatGPT on iOS harms consumers. Apple has struggled to add its own advanced AI featuresincluding a chatbotto its operating systems for the iPhone, iPad, and Mac. At its June 2024 Worldwide Developers Conference (WWDC), Apple instead announced an exclusive agreement with OpenAI, making ChatGPT the default chatbot option on its devices. Musk and xAI argue that the deal hurts rivals, including xAIs Grok chatbot. Working in tandem, Defendants Apple and OpenAI have locked up markets to maintain their monopolies and prevent innovators like X and xAI from competing, reads the lawsuit, which was filed in the U.S. District Court for the Northern District of Texas. Plaintiffs bring this suit to stop Defendants from perpetrating their anticompetitive scheme and to recover billions in damages. Currently, iPhone users who want Grok must download its stand-alone app. Musk and xAI contend that Apple should be compelled to let users easily select any chatbot. While Apple has spoken about integrating other models such as Googles Gemini and Anthropics Claude, it has not acted on those talks so far. The suit raises antitrust issues, but recent precedent makes such cases hard to win. Courts typically judge them based on consumer benefitsuch as product quality and costrather than on harm to competition alone. (By one estimate, ChatGPT accounted for more than 80% of AI chatbot visits as of July.) Its also consistent with what antitrust laws are about, says Sarah Kreps, director of the Tech Policy Institute at Cornell University. Just because ChatGPT has 80% of the market doesnt mean that thats antitrust. The law doesnt want to punish companies for products that consumers want. OpenAI was first to market with a large language model-driven chatbot in late 2022, with ChatGPT hitting 100 million users in just two months. For many, ChatGPT became synonymous with AI chatbot well before its Apple deal. Kreps notes that xAIs lawyers must show the Apple-OpenAI partnership meaningfully raised prices for consumers, reduced innovation, or blocked consumer choice, which is a high bar to cross. The court may also question xAIs standing, since it is a direct competitor. The lawsuit also accuses Apple of favoring OpenAI in its App Store. “If not for its exclusive deal with OpenAI, Apple would have no reason to refrain from more prominently featuring the X app and the Grok app,” it claims. Musk previously threatened to sue Apple, saying it was impossible for any AI company besides OpenAI to reach #1 in the App Store. The new filing continues Musks long-running feud with OpenAI and CEO Sam Altman. Musk, who co-founded OpenAI in 2015 and left its board in 2018, sued the company last year for pursuing profit despite its nonprofit structure. A recent filing revealed Musk tried to buy OpenAIs core assets earlier this year, even approaching Meta CEO Mark Zuckerberg about a joint bid. The venue of xAI’s lawsuit also matters quite a bit here. Companies often file in the Northern District of Texas, where cases are frequently assigned to a single judge, allowing for judge shopping. That court falls under the conservative Fifth Circuit Court of Appeals, which can reduce the risk of unfavorable outcomes in antitrust cases. It also has a record of producing rulings that quickly rise to the Supreme Court. Politics could also influence the outcome. The cases visibility could lead the Trump administration to intervene, with President Donald Trump potentially siding with Musk (though the two men certainly have their differences) on Truth Social and calling Apples deal a monopoly. That, in turn, could prompt the Federal Trade Commission or Justice Department to investigate or file a brief urging Apple to stop favoring ChatGPT. But Kreps warns that the administrations stance is unpredictable. At one time, Trump courted tech industry players in part by promising minimal regulation, but then he’s also stoked populist resentment toward “West Coast elites” who run “liberal” tech companies. Given Trumps split loyalties and his fraught relationship with Musk, the safer political move might be to stay out of it. But whether Trump follows that advice is another matter.
Category:
E-Commerce
Turning an idea into working software has never been easier, faster, or more affordable. Thanks to a new class of AI-assisted tools, a movement known as vibe coding is reshaping how software gets built. If you’re not familiar with the term, vibe coding refers to the use of natural language tools that dramatically lower the technical barrier to software development. You describe what you wantliterally, just say itand the AI writes the code, building your app before your eyes. From there, you can give feedback, tweak results, and refine the product through simple, back-and-forth interaction. This shift empowers solopreneurs and business owners to focus on outcomes without getting bogged down in engineering. More importantly, it removes the steep cost and complexity once required just to get a prototype off the ground. Heres why vibe coding could be a game-changer for founders and small to midsize businessesand where its limits still lie. The upside: What vibe coding makes possible Build MVPs in hours, not weeks Before vibe coding, even testing an idea required weeks of planning and a sizable budget. Today, you can build a working minimum viable product in an afternoon. That means faster feedback loops, quicker iteration, and smarter go/no-go decisions. Move faster, pivot smarter With vibe coding, you can quickly test ideas in the market, pivot based on customer feedback, and invest engineering resources only in what gains traction. Its a more agile, lower-risk way to innovate. Empower internal teams Need a custom reporting dashboard? An onboarding tool? A resource scheduler? With vibe coding, nontechnical teams can create light apps that solve internal pain pointsno dev team required. Level the playing field for founders The broader impact? More ideas get a shot. More small businesses can take root. More diverse voices can be heard. For investors, it means concepts can be vetted earlier and with more clarityleading to smarter funding bets and higher odds of success. The limits: What vibe coding cant (yet) replace Of course, the obvious question arises: If a tool that once required a five-figure budget can now be built in an afternoon, are software professionals getting coded out of a job? The short answer: no. What vibe coding changes is when and why you bring in professional developersnot whether you need them. It democratizes access and speeds up early exploration. But there are important limits that still require experienced teams. Scalability becomes a bottleneck Vibe-coded apps are great for prototyping. But when you need scalehandling real users, integrating APIs, managing payments, maintaining uptimeyoull hit limits fast. For growth and complexity, youll need real engineers. Quality control still requires human judgment AI doesnt understand your edge cases. It doesnt anticipate compliance requirements or subtle business rules. Production-grade software needs thoughtful architecture, thorough testing, and rigorous review. Thats human territory. Security isnt baked in The moment you handle user dataeven something as basic as an emailyou step into legal and ethical territory. Most vibe-coded apps arent designed with secure auth flows, proper data storage, or access controls. Thats not a criticismits just not their purpose. Public-facing tools need professional-grade security. Bottom line: Vibe coding changes the game, but it doesnt replace the players. It simply lets more people step onto the field. A real-world example: My mom, a wedding venue, and an afternoon app My parents own a wedding venue, which theyve built over the years on a picturesque Midwest ranch. Their propertythe forest chapel, the refurbished historic barnits phenomenal. At the same time, this is a competitive industry, and they are constantly looking for new ways to add appeal: They built a stone bridge to a charming island they call Yonder; they raised a miniature donkey named Mojito who wears flowers and saddles beer for the reception. Its all good, but when budget is a primary concern, its unclear whether these added features will result in more yesses. My moms been doing this for a while. She knows that the primary concerns for couples are cost, sure, logistics, and the million little details and decisions that define both. I assured her that this is the sort of problem software can solve. So, the last time she visited, we vibe-coded a wedding planning app together on Lovable. It allows couples to mix, match, visualize, and budget, all on a single, simple interface. Its fun, it gives them transparency, and it delivers ease. Its making a difference for her business already, and it took us a single afternoon. A few key also trues from my moms example: Seeing a possible software solution and how it would work required mea career UX designer and professional software architect. The tool is private, used during venue toursnot something publicly hosted or scaled. The app uses static data, like a visual calculator. If we needed real-time bookings, payments, or user accounts, wed need proper backend infrastructureand a professional team. This is where vibe coding shines: rapid ideas, small use cases, single-user workflows. Its not the whole productit’s the first spark. Final thought: Get codingeven if you dont get coding I live in San Francisco, where it feels like everyone has an app idea. But I suspect millions of people across the country have equally brilliant conceptsideas that could improve their communities, businesses, or lives. Now, nothing stands in your way. If software shapes our worldand it increasingly doesthen its crucial that people from all walks of life help shape software. That starts by building. Spend an afternoon in Lovable, Replit, Bubble, or any other vibe-coding tool. If youre not sure which to use, describe your idea to ChatGPT or Perplexity and ask which platform fits best. Your first version doesnt need to be perfect. But it does need to exist. I cant wait to see where your experimentation leads. Lindsey Witmer Collins is CEO and founder of WLCM App Studio and Scribbly Inc.
Category:
E-Commerce
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