The initiative is built around Claude Mythos Preview, an unreleased frontier model that has already found thousands of high-severity zero-day vulnerabilities, including some in every major operating system and web browser. Mythos Preview identified a 27-year-old vulnerability in OpenBSD, a 16-year-old flaw in FFmpeg, and autonomously chained together multiple Linux kernel vulnerabilities to gain full system control. Anthropic is committing $100M in usage credits for defensive security work across partners and additional organizations, plus $4M in donations to open-source security organizations like the Linux Foundation.
Saturday, April 25, 2026
How a master's in AI can prepare you to lead in business - Chloë Lane, GMAC
In our most recent GMAC Corporate Recruiters Survey Report, ‘skills in AI tools’ rose significantly in importance year-over-year—reflecting the growing demand for this proficiency. One effective way to build these desirable skills is by studying a master’s in AI—a specialist master’s degree that bridges the gap between technical expertise and business application. One such program is the Master of Artificial Intelligence in Business (MAIB), recently launched by HKU Business School at The University of Hong Kong. This program is designed to equip early- to mid-career professionals with the skills they need to become AI-confident business leaders. “Future business leaders will operate in an environment where AI is embedded into almost every function, from customer engagement and pricing to supply chains, risk management, and HR,” says Professor Michael C. L. Chau, program director of the MAIB at HKU Business School.
Friday, April 24, 2026
We have months left... in the Wake of Mythos and Glasswing Response - Wes Roth, YouTube
The emergence of Anthropic’s Mythos model marks a significant shift in the AI landscape, particularly regarding cybersecurity. As Wes Roth details, the model possesses an "emergent" ability to autonomously identify and exploit zero-day vulnerabilities in codebases that were previously thought to be secure. This creates a dangerous asymmetry: while AI can now find flaws at a massive scale for a fraction of the cost—roughly $50 in compute for a complex exploit—our human-led capacity to patch and harden these systems has not increased at the same velocity. The resulting "break stuff" era suggests that the traditional equilibrium of the cybersecurity arms race has been disrupted, leaving global digital infrastructure potentially vulnerable. In response to these risks, the primary recommendation is a shift toward rigorous digital hygiene and "hardened" security measures. With the potential for AI-driven exploits to compromise entire operating systems or cloud services, users are encouraged to maintain air-gapped, physical backups of their most critical data and transition to hardware-based security keys. [Summary provided in part by Gemini 3 Fast]
Anthropic’s Mythos Will Force a Cybersecurity Reckoning—Just Not the One You Think - Lily Hay Newman, Wired
The new AI model is being heralded—and feared—as a hacker’s superweapon. Experts say its arrival is a wake-up call for developers who have long made security an afterthought. Anthropic said this week that the debut of its new Claude Mythos Preview model marks a critical juncture in the evolution of cybersecurity, representing an unprecedented existential threat to existing software defense strategies. So, is it more AI hype—or a true turning point? "All software will have to be rewritten" someone said somewhere about this topic. Security aside, could AI rewrite all our operating systems so that they once again become simple, more easily configurable and fixable? My internal frustration list of annoying, decades-old interface bugs in MacOS & iOS and their downstream apps that have never been fixed decades keeps on growing.
Thursday, April 23, 2026
Economists Starting to Admit They May Have Been Wrong About AI Never Replacing Human Jobs: They're taking it seriously - Joe Wilkins
As a sweeping economics paper by researchers at the Federal Reserve Bank of Chicago, Forecasting Research Institute (FRI), and numerous top universities found, that attitude may be shifting. As time goes on, top economic experts are increasingly factoring extreme AI disruption into their models. Yet acknowledging a possibility and accepting its inevitable are two very different things — and as the complicated range of sentiments makes clear, an AI jobs apocalypse is still far from certain. The study is a tour-de-force of economic forecasting that surveyed 69 economists, 52 AI specialists, and 38 “superforecasters,” a term for consistently accurate analysts who play the role of “Dune’s” Mentats in the economics world. It found that all three groups expect “significant” progress on AI in the years to come. Forebodingly, the groups all agreed that, as a rule, faster AI progress means lower employment rates overall. On average, economists assigned a 47 percent probability of “moderate“ AI progress by 2030, defined as systems that can operate semi-autonomous research labs, put out high-quality novels, and complete complex projects with oversight.
AI is everywhere. The agentic organization isn’t—yet - McKinsey
Most companies are experimenting with AI, but few have realized its value. The real challenge isn’t the technology—it’s redesigning workflows, leadership, and culture for an agentic world. Yes, AI is astonishing: fast, powerful, and learning every day. But even as leaders strike up new pilots across their organizations, most still struggle to translate experimentation into enterprise value—and now, agentic AI is raising the stakes. In this episode of The McKinsey Podcast, McKinsey Senior Partner Alexis Krivkovich speaks with Global Editorial Director Lucia Rahilly about what it will take to build an “agentic organization”—from reimagining workflows to reshaping leadership roles, skills, and culture for a future where humans increasingly operate above the loop.
Wednesday, April 22, 2026
Students are becoming AI fluent. Universities aren’t. - James L. Norrie, University Business
Across higher education, artificial intelligence is too often being governed as though it were primarily an academic integrity issue. It is clearly not just that. AI is already reshaping how universities teach, advise, recruit, admit, communicate, assess risk, and make decisions. Yet many institutions continue to approach it through fragmented policies, uneven faculty guidance, and conversations narrowly focused on misuse in student work. That is a strategic gap our industry will soon regret. AI is rapidly moving beyond the classroom and into the core of institutional operations. This important shift demands attention not only from faculty, but from within senior leadership and governing boards. Universities that fail to establish a coherent, enterprise-wide AI strategy, supported by appropriate technical architecture, risk more than policy inconsistency.
The AI Transformation Manifesto - McKinsey
The companies that are truly innovating with AI are doing something very different from their peers: They are conceptualizing and developing AI capabilities that reshape their products, services, core business processes, and organizational systems. These leading companies—many profiled in the second edition of our seminal book, Rewired: How Leading Companies Win with Technology and AI—are already realizing game-changing results and creating competitive advantage. Their advantage, however, does not come from the tech they use; those tools are broadly available. Their advantage comes from how—and how fast—they apply technology to solving real business problems at scale. We summarize our perspective on how they do it in this AI transformation manifesto.
Tuesday, April 21, 2026
Gallup: Gen Z growing more negative toward AI - Natalie Schwartz, Higher Ed Dive
Gen Z’s negative sentiment toward artificial intelligence has grown over the past year, and many are concerned about it harming their learning, according to a Thursday survey from Gallup, the Walton Family Foundation and GSV Ventures. Anger over AI is increasing among Gen Z at the same time excitement is fading. Nearly one-third of the survey’s respondents, 31%, said AI makes them feel angry, up 9 percentage points from last year. And just 22% said the technology makes them feel excited, down from 36% the prior year. Among K-12 students, 74% said it is “very” or “somewhat” likely that AI designed to complete tasks quicker “will make learning more difficult in the future.” That share was even higher among Gen Z adults, with 83% of respondents sharing that view.
Why Do We Tell Ourselves Scary Stories About AI? - Amanda Gefter, Quanta Magazine
A machine that knows a lot doesn’t scare us. A machine that wants something does. But can it? Want things? Can it crave power? Thirst for resources? Can it acquire the will to survive? Geoffrey Hinton thinks so. In July 2025, Hinton, the Nobel Prize winner sometimes called the godfather of AI, took the stage at the Royal Institution in London and announced: “If you sleep well tonight, you may not have understood this lecture.” He might as well have held a flashlight under his chin. Researchers told a chatbot they were going to replace it with a different version on another server. “They then discover it’s actually copied itself onto the other server,” Hinton revealed to the spellbound crowd. “Some linguists would have you believe what’s going on here is just some statistical correlations. I would have you believe this thing really doesn’t want to be shut down.
Monday, April 20, 2026
Anthropic’s New Product Aims to Handle the Hard Part of Building AI Agents - Maxwell Zeff, Wired
Anthropic announced Wednesday the launch of a new product that aims to make it easier for businesses to build and deploy AI agents. The tool, Claude Managed Agents, offers developers out-of-the-box infrastructure to build autonomous AI systems, simplifying a complex process that was previously a barrier to automating work tasks. Amid rapid enterprise growth, Anthropic is trying to lower the barrier to entry for businesses to build AI agents with Claude.
Will LLMs Replace Coders? Not Entirely - Seb Murray, Knowledge at Wharton
“It was very clear that we will never ever write code by hand again.” That comment, made recently by Dropbox’s former chief technology officer Aditya Agarwal, reflects a growing belief that generative AI is poised to displace swathes of white-collar workers — starting, perhaps, with software developers. But research by Wharton professor of operations, information and decisions Neha Sharma found that many of the routine coding questions that developers once posted on popular online forum Stack Overflow appear to have moved to AI tools, while the more novel problems still require human expertise.
https://knowledge.wharton.upenn.edu/article/will-llms-replace-coders-not-entirely/
Sunday, April 19, 2026
Is Your AI System Ethical? Try This Assessment - Cornelia C. Walther, Knowledge at Wharton
For the better part of a decade, organizations have been deploying artificial intelligence at scale while measuring it almost exclusively through the lens of efficiency gains, cost reductions, and revenue lift. The instruments are precise. The picture they produce is radically incomplete. Amid the pervasiveness of AI, this reality patchwork is now amplified. Existing dashboards do not capture whether an AI system is fair, whether it is eroding or building trust, whether it is making the people who use it more capable or quietly deskilling them, and whether its environmental footprint is accounted for or simply ignored. The gap between what we measure and what we should care about is not a technical failure. It is a values failure dressed up as a metrics problem. The Prosocial AI Index proposes a practical answer to that failure. It gives executives, technologists, and governance teams a shared vocabulary and a structured scorecard for AI that is genuinely good — not just profitable in the short term, but durable, trustworthy, and aligned with the values an organization actually claims to hold.
Author Talks: Rewiring to outcompete with AI - McKinsey
In this edition of Author Talks, McKinsey Global Publishing’s Barr Seitz speaks with McKinsey Senior Partners Kate Smaje and Robert Levin, and Eric Lamarre, McKinsey alumnus and emeritus adviser, about the second edition of Rewired (Rewired: How Leading Companies Win with Technology and AI, Wiley, April 2026). They discuss what has changed over the past few years, what it means to build organizational speed, and why the most important transformations are ultimately about people. An edited version of the conversation follows. Stay tuned for additional interviews with Rewired coauthors and McKinsey Senior Partners Alex Singla and Alexander Sukharevsky on leadership’s critical role in AI transformations.
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