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For the past decade I have volunteered at St. Francis Inn, a soup kitchen in the Kensington neighborhood of Philadelphia. Kensington, for those not from Philly, has long had a reputation for potent but affordable street drugs. Interstate 95 and the Market-Frankford elevated commuter train line provide easy access to the neighborhood for buyers and sellers, and abandoned buildings offer havens for drug use and other illicit activity. St. Francis Inn Ministries, which was founded by two Franciscan friars in 1979, serves sit-down breakfast and dinner for thousands of people each year, many of whom suffer from poverty, homelessness, and substance use disorder. It also runs Maries Closet, a charity that provides free used clothing and housewares. These ministries are operated by a core team of nine full-time members, hundreds of volunteers from local high schools and colleges, and an ad hoc team of folks from many walks of life. In the years Ive been volunteering at St. Francis, significant changes have occurred in Kensington, including gentrification, soaring housing prices and increased police activity. Such changes can make it harder for people who suffer from poverty and homelessness to remain in the neighborhood. Around 2018, the number of guests visiting St. Francis Inn was already dwindling noticeably. I heard volunteers speculate on whether St. Francis Inn should relocate further north in Philadelphia where there are more people in need. Others wondered whether St. Francis Inn should create a mobile unit that traveled to people in need wherever they may be. As I listened, I realized that this was a business decision. As a professor of management at St. Josephs University in Philadelphia, I decided to present this decision to the students in my Management Honors Capstone Seminar. In January 2026, I published a business case study titled Dealing with Change in Kensington, Philadelphia: The Case of Saint Francis Inn. An interesting business case The capstone seminar I teach is the second of two strategic management courses that honors business students take in their senior year. Using the Harvard case study method, students identify the critical issues embedded in a variety of cases and find the information needed to evaluate those issues using seminal theories in strategic management. Students then propose a solutiona hypothesis they believe best addresses the situation. They test whether that solution works by building a plan of actioncalled a proofthat provides logic and evidence that their solution would work. Part of what I believe makes this case study interesting is that it involves some of the most vulnerable people in Philadelphia. I felt it was important to give students the opportunity to consider important issues of social justice when applying their business decision-making skills. Morally sound recommendations Among other material, the course covers two different perspectives that students can use to make informed decisions and propose solutions for St. Francis Inn. The first is the resource-based view. Using this framework, students identify the unique resources and capabilities that a firmin this case, St. Francis Innhas built over the years. Then they determine how to use those resources and capabilities best to carry out the firms mission. St. Francis Inns mission is to live among and serve the poor, following the example of St. Francis of Assisi. The organization has built decades-long relationships with food companieswhich share leftover meat, vegetables and other products with the innas well as with members of the community in Kensington. In addition, they have developed a network of hundreds of well-trained and motivated volunteer workers throughout Philadelphia and, indeed, the entire country. The second framework that students are expected to use is formal moral theory, which provides a set of different theories for determining moral rules. It enables us to make ethical decisions that are structured, rational, and logical. For example, using utilitarianism, students quantify all of the costs and benefits of a decision and choose the option that provides the largest net benefitor utilityto society. Rights theory requires students to make decisions that respect the intrinsic dignity of all persons. Students can use these theories to make morally sound recommendations on how St. Francis Inn can best serve the stakeholders in its community. Perhaps the most obvious people affected by St. Francis Inn are the people living in the neighborhood who struggle with homelessness and substance use disorder and receive food and other assistance there. Other groups of concern include longtime neighbors who have homes nearby but still live in poverty, new residents moving into the neighborhood, local property developers who generally want to see fewer homeless people in the neighborhood, and city officials who are responsible for various government functions. These include police and emergency medical services, city council members and social services organizations. Students must answer a two-dimensional question: Given what St. Francis Inn does best, how can it best address the needs of its most important stakeholders? Since they are business majors, many quickly gravitate to logical business decisions that St. Francis Inn can make, such as continuing its operation where it is, relocating, or creating a mobile service. Without fail, there are students each semester who argue that regardless of whats best for St. Francis Inn, the interests of the various people of concern in the neighborhood must be respected. To be honest, I enjoy watching them grapple with this problem with sincerity and care. Here, students must balance an organizations core competencies with the moral impact of its decisions, while prioritizing the rights and needs of diverse, nontraditional groups who have a stake in this decision. Thats a valuable skill for any futureor, for that matter, currentbusiness executive. Read more of our stories about Philadelphia and Pennsylvania, or sign up for our Philadelphia newsletter on Substack. Tim Swift is a professor of management at St. Joseph’s University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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The Nancy Guthrie investigation is now in its third week, which means it was only a matter of time before the case piqued the interest of online armchair detectives. Nancy Guthrie, the mother of Today Show anchor Savannah Guthrie, was reported missing on Feb. 1. In the weeks since, the street outside her home in Tucson, Arizona, has become a destination for true-crime livestreamers. Online sleuths have dissected the publicly available details of the ongoing case while spreading far-fetched conspiracy theories. Some have filmed themselves driving through Guthries neighborhood. The hashtag #nancyguthrie currently has more than 16,000 posts on TikTok, where users analyze Ring doorbell footage and excerpts from Savannah Guthries 2024 memoir, capitalizing on public interest in the case and often drawing hundreds of thousands of views. @thedreydossier its all connected man #investigation #truecrimetok original sound – Drey These posts across social media platforms have forced law enforcement to repeatedly set the record straight and dispel rampant rumors and misinformation, particularly as it pertains to Guthries family members. Pima County Sheriff Chris Nanos announced Monday that Guthries children and their spouses had been fully cleared from the investigation. The family has been nothing but cooperative and gracious and are victims in this case, Sheriff Chris Nanos said in a statement posted on X. A statement from Sheriff Chris Nanos on the Nancy Guthrie Investigation: pic.twitter.com/YfhQSPkrFJ— Pima County Sheriff's Department (@PimaSheriff) February 16, 2026 His statement appeared to indirectly address those speculating online and reporting irresponsibly about the case. Influencer content is, by nature, unwieldy, reactionary, and unbeholden to the same standards as traditional news outlets covering ongoing investigations. Former Los Angeles Sheriffs Department Lt. Gil Carrillo told 13 News that online speculation has the potential to inadvertently hinder investigations. With all of these people that are getting on social media rendering their opinions and their thoughts, investigators have to take time from their investigation and assign people to follow those leads up because they all have to be followed, Carrillo said. Every one of them has to be vetted out. Members of the true-crime community counter that more eyes on an active case can help, something authorities themselves have acknowledged. As a person involved in the Guthrie investigation told CNN last week: The breakthrough tip could come from anyone, from anywhere. In 2021, online sleuths credited themselves with helping locate the remains of Gabby Petito, the 22-year-old who went missing during a road trip with her boyfriend. As the internet became consumed with the case, sharing images, analyzing Petitos YouTube uploads, and speculating about timelines, YouTubers Jenn and Kyle Bethune spotted Petitos van in their own travel footage. This helped point authorities to the area where Petitos body was ultimately found. Since then, similar episodes have played out across the hugely popular true-crime corner of the internet. Inspired by those successes, influencers and amateur sleuths are increasingly inserting themselves into both active and cold cases. But even well-meaning intervention can risk doing more harm than good.
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The deadline to claim the early-bird rate for Fast Companys Best Workplaces for Innovators is quickly approachingFriday, February 20, at 11:59 p.m. Pacific time. This marks the eighth year Fast Company will be recognizing companies and organizations from around the world that most effectively empower employees at all levels to improve processes, create new products, or invent whole new ways of doing business. In addition to ranking the worlds Best Workplaces for Innovators, we will also recognize companies in 19 categories, including a brand new category that focuses on skilled laborcompanies that depend heavily on talented employees with the kinds of increasingly coveted technical expertise acquired through vo-tech training and trade schools. Other new categories this year include: Cybersecurity and enterprise software Industrial and manufacturing Technology and science Advertising, marketing, and PR Biotech, healthcare, and life sciences Financial services and fintech What differentiates Best Workplaces for Innovators from existing best-places-to-work lists is that it goes beyond benefits, competitive compensation, and collegiality (mere table stakes in todays competition for talent) to identify which companies are actively creating and sustaining the kinds of innovative cultures that many top employees value as much as or even more than money. Places where they can do the best work of their careers and improve the lives of hundreds, thousands, or even millions of people around the world. Every application receives careful review by Fast Company editors. Start your Best Workplaces for Innovators application here. For more information on applying, see the FAQs. The final deadline to apply isnt until March 27, but all applications submitted by Friday, February 20, at 11:59 pm Pacific time receive the preferred rate.To sign up for Best Workplaces for Innovators notifications, register here
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In todays AI race, breakthroughs are no longer measured in yearsor even monthsbut in weeks. The release of Opus 4.6 just over two weeks ago was a major moment for its maker, Anthropic, delivering state-of-the-art performance in a number of fields. But within a week, Chinese competitor Z.ai had released its own Opus-like model, GLM-5. (Theres no suggestion that GLM-5 uses or borrows from Opus in any way.) Many on social media called it a cut-price Opus alternative. But Z.ais lead didnt last long, either. Just as Anthropic had been undercut by GLM-5s release, GLM-5 was quickly downloaded, compressed, and re-released in a version that could run locally without internet access. Allegations have flown about the ways AI companies can match, then surpass, the performance of their competitorsparticularly how Chinese AI firms can release models rivaling American ones within days or weeks. Google has long complained about the risks of distillation, where companies pepper models with prompts designed to extract internal reasoning patterns and logic by generating massive response datasets, which are then used to train cheaper clone models. One actor allegedly prompted Googles Gemini AI model more than 100,000 times to try and unlock the secrets of what makes the model work so powerfully. I do think the moat is shrinking, says Shayne Longpre, a PhD candidate at the Massachusetts Institute of Technology whose research focuses on AI policy. The shift is happening both in the speed of releases and the nature of the improvements. Longpre argues that the frontier gap between the best closed models and open-weight alternatives is decreasing drastically. The gap between that and fully open-source or open-weight models is about three to six months, he explains, pointing to research from the nonprofit research organization Epoch AI tracking model development. The reason for that dwindling gap is that much of the progress now arrives after a model ships. Longpre describes companies doing different reinforcement learning or fine tuning of those systems, or giving them more test time reasoning, or enabling to have longer context windowsall of which make the adaptation period much shorter, rather than having to pre-train a new model from scratch, he says. Each of those iterative improvements compounds speed advantages. They’re pushing things out every one or two weeks with all these variants, he says. It’s like patches to regular software. But American AI companies, which tend to pioneer many of these advances, have become increasingly outspoken against the practice. OpenAI has alleged that DeepSeek trained competitive systems by distilling outputs from American models, in a memo to U.S. lawmakers. Even when nobody is “stealing” in the strict sense, the open-weight ecosystem is getting faster at replicating techniques that prove effective in frontier models. The definition of what open means in model licenses is partly to blame, says Thibault Schrepel, an associate professor of law at Vrije Universiteit Amsterdam who studies competition in foundation models. Very often we hear that a system is or is not open source, he says. I think it’s very limited as a way to understand what is or what is not open source. Its important to examine the actual terms of those licenses, Schrepel adds. If you look carefully at the licenses of all the models, they actually very much limit what you can do with what they call open-source, he says. Metas Llama 3 license, for instance, includes a trigger for very large services but not smaller ones. If you deploy it to more than 700 million users, then you have to ask for a license, Schrepel says. That two-tier system can create gray areas where questionable practices can emerge. To compensate, the market is likely to diverge, MIT’s Longpre says. On one side will be cheap, increasingly capable self-hosted models for everyday tasks; on the other, premium frontier systems for harder, high-stakes work. I think the floor is rising, he adds, predicting more very affordable, self-hosted, self-hosted, general models of increasingly smaller sizes too. But he believes users will still navigate to using OpenAI, Google and Anthropic models for important, skilled work. Preventing distillation entirely may be impossible, Longpre adds. He believes its inevitable that whenever a new model is released, competitors will try to extract and replicate its best elements. I think its an unavoidable problem at the end of the day, he says.
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The AI boom began with ChatGPT and chatbots. Now chatbots are starting to grow arms and legs, as developers say, meaning they can use digital tools and work independently on a humans behalf. The open-source platform OpenClaw is notable because it lets people build agents with far more autonomy than those offered by big tech. OpenClaw agents can control a browser, send emails, do multi-step planning, and pursue persistent goals. Users often interact with them through iMessage or Discord, with the agent hosted locally on a Mac mini. One users agent reportedly negotiated with several car dealerships and shaved four grand off a cars price while its owner was in a meeting. Some say OpenClaw agents fulfill the promise of Samantha, the independent AI in Her. Developers are now racing to build their own. (To wit: The project hit 100,000 GitHub stars faster than any other.) That means the internet could soon be full of agents acting as proxies for humans. Thats why OpenClaws creator, Peter Steinberger, is worth hearing out. I listened to his recent three-hour interview with podcaster Lex Fridman, where the thoughtful (and quirky) Austrian shared prescient ideas about where AI agents could take personal computing, and how societies might respond. Below, the six most interesting things he said (lightly edited for clarity): On the Moltbot affair Some people are just way too trusty or gullible. You know . . . I literally had to argue with people that told me, ‘Yeah, but my agent said this and this.’ So, we, as a society, we [have] some catching up to do in terms of understanding that AI is incredibly powerful, but its not always right. Its not all-powerful, you know? And especially things like this, its very easy that it just hallucinates something or just comes up with a story. For many of us, the first we heard of OpenClaw was when its agents began congregating on their own social site, called Moltbook, where they dragged their human owners, posted manifestos, and debated topics like sentience. It gave people a real sense of future shock. Steinberger believes AI has raced ahead of peoples understanding and readiness. On OpenClaws security issues If you understand the risk profiles, fine. I mean, you can configure it in a way that nothing really bad can happen. But if you have no idea, then maybe wait a little bit more until we figure some stuff out. But they would not listen to the creator. They [installed] it anyhow. So the cats out of the bag, and securitys my next focus. When an agent is operating on its own and interfacing with the web and other services, it creates a larger attack surface. A hacker could inject malicious prompts to redirect the agent toward harmful or even criminal actions. Steinberger believes OpenClaw should be used only by people who understand these risks and how to mitigate them. On Macs (potential) AI moment Isnt it funny how they completely blunder AI, and yet everybodys buying Mac minis? No, you dont need a Mac mini to install OpenClaw. You can install it on the web. Theres a concept called nodes, so you can make your computer a node and it will do the same. There is something to be said for running it on separate hardware. That right now is useful. . . . And no, I dont get commission from Apple. They didnt really communicate much.” Many developers who want their OpenClaw agents running continuously on a local machine, rather than in the cloud, are buying Mac Studio or Mac mini computers. That demand has reportedly created shortages of certain configurations, with delivery times stretching from a few days to as long as six weeks for high-memory systems. On Zuckerberg’s feedback “Mark [Zuckerberg] basically played all week with my product, and sent me, ‘Oh, this is great.’ Or, ‘This is shit. Oh, I need to change this.’ Or, like, funny little anecdotes. And people using your stuff is kind of like the biggest compliment, and also shows me that, you know, they actually . . . care about it. And I didnt get the same on the OpenAI side. Steinberger surprised the AI world last Friday when he announced he would sell OpenClaw to OpenAI and join the company. In the Lex Fridman interview a few days prior, he said he was considering selling to either OpenAI or Meta, and without naming a favorite, he sounded like he was leaning toward Meta. OpenAIs Sam Altman may have done some fast talking after the interview was published, or Steinbergers Meta-leaning comments may have been part of a negotiation strategy. Either way, Steinberger will now have far more people and computing power at OpenAI to help advance its AI agents. On AIs not-so-great UX The current interface is probably not the final form. Like, if you think more globally, we copied Google for agents. You have a prompt, and then you have a chat interface. That, to me, very much feels like when we first created television and then people recorded radio shows on television and you saw that on TV. I think theres better ways how we eventually will communicate with models, and we are still very early in this ‘how will it even work’ phase. So, it will eventually converge and we will also figure out whole different ways to work with those things. Steinberger says OpenClaw isnt really competing with AI coding agents like Claude Code or OpenAIs Codex. Theyre different tools, he says, with OpenClaw functioning more like a personal assistant. But he believes they could eventually converge into something like an AI operating system, and that the way we interact with AI will change significantly in the years ahead. On ‘vibe coding’ I actually think vibe coding is a slur. Yeah, I always tell people I do agentic engineering, and then maybe after 3 a.m. I switch to vibe coding, and then I have regrets the next day. You just have to clean up and fix your shit. To Steinberger, vibe coding means using an AI coding assistant to quickly mock up an app or feature without much regard for security, testing, or its effects on a larger code base. Agentic engineering, meanwhile, is more like a collaboration between an experienced software engineer and an advanced coding assistant (such as Anthropics Claude Code or OpenAIs Codex), in which the two create a detailed plan for building new software without introducing security problems or bugs.
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